biomolecules Article Molecular Context-Dependent Effects Induced by Rett Syndrome-Associated Mutations in MeCP2 David Ortega-Alarcon 1,† , Rafael Claveria-Gimeno 1,2,3,†,‡ , Sonia Vega 1 , Olga C. Jorge-Torres 4 , Manel Esteller 4,5,6,7 , Olga Abian 1,2,3,8,9, * and Adrian Velazquez-Campoy 1,3,8,9,10, * 1 Institute of Biocomputation and Physics of Complex Systems (BIFI), Joint Units IQFR-CSIC-BIFI, and GBsC-CSIC-BIFI, Universidad de Zaragoza, 50018 Zaragoza, Spain; dortega@bifi.es (D.O.-A.); rafacg@bifi.es (R.C.-G.); svega@bifi.es (S.V.) 2 Instituto Aragonés de Ciencias de la Salud (IACS), 50009 Zaragoza, Spain 3 Instituto de Investigación Sanitaria Aragón (IIS Aragón), 50009 Zaragoza, Spain 4 Josep Carreras Leukaemia Research Institute (IJC), 08916 Badalona, Spain; ojorge@carrerasresearch.org (O.C.J.-T.); mesteller@carrerasresearch.org (M.E.) 5 Centro de Investigacion Biomedica en Red Cancer (CIBERONC), 28029 Madrid, Spain 6 Institucio Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain 7 Physiological Sciences Department, School of Medicine and Health Sciences, University of Barcelona (UB), l’Hospitalet de Llobregat, 08907 Barcelona, Spain 8 Centro de Investigación Biomédica en Red en el Área Temática de Enfermedades Hepáticas y Digestivas (CIBERehd), 28029 Madrid, Spain 9 Departamento de Bioquímica y Biología Molecular y Celular, Universidad de Zaragoza, 50009 Zaragoza, Spain 10 Fundación ARAID, Gobierno de Aragón, 50009 Zaragoza, Spain * Correspondence: oabifra@unizar.es (O.A.); adrianvc@unizar.es (A.V.-C.); Tel.: +34-876-555-417 (O.A.); +34-976-762-996 (A.V.-C.) † Contributed equally. ‡ Current address: Certest Biotec S.L., 50840 Zaragoza, Spain; rclaveria@certest.es.  Received: 11 October 2020; Accepted: 8 November 2020; Published: 10 November 2020  Abstract: Methyl-CpG binding protein 2 (MeCP2) is a transcriptional regulator and a chromatin-binding protein involved in neuronal development and maturation. Loss-of-function mutations in MeCP2 result in Rett syndrome (RTT), a neurodevelopmental disorder that is the main cause of mental retardation in females. MeCP2 is an intrinsically disordered protein (IDP) constituted by six domains. Two domains are the main responsible elements for DNA binding (methyl-CpG binding domain, MBD) and recruitment of gene transcription/silencing machinery (transcription repressor domain, TRD). These two domains concentrate most of the RTT-associated mutations. R106W and R133C are associated with severe and mild RTT phenotype, respectively. We have performed a comprehensive characterization of the structural and functional impact of these substitutions at molecular level. Because we have previously shown that the MBD-flanking disordered domains (N-terminal domain, NTD, and intervening domain, ID) exert a considerable influence on the structural and functional features of the MBD (Claveria-Gimeno, R. et al. Sci Rep. 2017, 7, 41635), here we report the biophysical study of the influence of the protein scaffold on the structural and functional effect induced by these two RTT-associated mutations. These results represent an example of how a given mutation may show different effects (sometimes opposing effects) depending on the molecular context. Keywords: Methyl-CpG-binding protein 2 (MeCP2); Rett syndrome; intrinsically disordered protein (IDP); protein stability; protein-DNA interaction; isothermal titration calorimetry (ITC) Biomolecules 2020, 10, 1533; doi:10.3390/biom10111533 www.mdpi.com/journal/biomolecules Biomolecules 2020, 10, 1533 2 of 19 1. Introduction Methyl-CpG binding protein 2 (MeCP2) is an intrinsically disordered protein (IDP) involved in early stages of neuronal development, differentiation, maturation, and synaptic plasticity control [1]. Although it was identified as a methyl-dependent chromatin binding protein and an epigenetic methylation reader, and, therefore, associated to gene silencing, recent evidences suggest it could be considered as a transcriptional regulator whose primary role is recruiting co-repressor complexes to methylated sites and contributing to decreasing transcriptional noise [2]. MeCP2 exhibits a promoter-specific dsDNA interaction required for finely tuning gene transcription, but it also binds massively to heterochromatin when acting as a chromatin architecture remodeling factor. From the initial embryonic development stages, MeCP2 gradually replaces histone 1 as a sort of nucleosomal linker [3–5]. The possibility to establish different types of interaction with DNA together with its ability to interact with other many biological partners (RNA, structural and transcriptional proteins, nucleosomal elements) and its central role as an important network interaction hub within gene transcription regulation networks, as well as the additional regulatory level of MeCP2 activity through post-translational modifications are made possible thanks to its modular, dynamic and adaptive structure [6,7]. Abnormal MeCP2 activity leads to disease [2,8,9]. MeCP2 point mutations or deletions causing activity loss are associated with Rett syndrome (RTT). RTT is the main cause of mental retardation in females (1:10,000 births), exhibiting a clinically broad expression phenotype gradation. RTT shares features with other neurological diseases from the autistic spectrum. Importantly, duplication of mecp2 gene results in overexpression of MeCP2 and leads to MeCP2 duplication syndrome (MDS), another much rarer disorder affecting males and, strikingly, sharing phenotypic features with RTT, such as severe intellectual disability and impaired motor function. Each of the six domains MeCP2 is either completely or partially disordered: N-terminal domain (NTD), methyl binding domain (MBD), intervening domain (ID), transcriptional repression domain (TRD), C-terminal domain α (CTDα), and C-terminal domain β (CTDβ) (Supplemental Figure S1) [3,10]. Because of the importance of the interaction of MeCP2 with the nuclear co-receptor co-repressor (NCoR), an additional NCoR/SMRT interaction domain (NID) is often considered between TRD and CTDα [11]. Most of MeCP2 polypeptide chain (≥60%) lacks well-defined secondary/tertiary structure. Flexible, disordered regions facilitate structural rearrangements necessary for exposing different interaction motifs and adapting to the many interacting partners, as well as the giving rise to the allosteric regulation through which the protein conformational landscape is modulated by ligand binding. The most important domains are MBD, initially associated with methylated CpG (mCpG) DNA binding, and TRD, associated with transcription repression activities [12,13]. Most RTT-associated mutations are concentrated within these two domains, including missense and nonsense mutations, insertions, duplications, and deletions [14]. Nevertheless, only eight missense and nonsense mutations (R106W, R133C, T158M, R168X, R255X, R270X, R294X and R306C) account for approximately 70% of all mutations in RTT [15]. In particular, R133C, T158M, and R106W (in increasing order for phenotype severity and disease burden) represent 5%, 12%, and 3% of RTT cases [16,17]. MBD is the best characterized domain in MeCP2. MBD structure basically consists of a wedge-shaped structured core containing a 3-stranded anti-parallel β-sheet with an α-helix on the C-terminal side, with two unstructured regions flanking this core [16,17]. MBD is considered to be directly involved in maintaining the global organization of the protein through interactions with other domains through inter-domain coupling [5,18,19]. Mutations in this domain would have an impact on the local and the global stability in MeCP2 [3,18]. In a previous biophysical study of three MeCP2 variants (MBD, and NTD-MBD, and NTD-MBD-ID), we established that the isolated MBD might not be the appropriate construct to study and assay its dsDNA binding features, because the presence of NTD and ID increased considerably the dsDNA binding affinity and the structural stability, besides adding a second, functionally independent Biomolecules 2020, 10, 1533 3 of 19 dsDNA binding site [20]. Here we report a biophysical study of the structural stability and the dsDNA interaction of mutant variants containing the substitutions R106W and R133C, two main RTT-mutations. These mutations were selected because they consist in an arginine substitution by a bulkier or a smaller residue, they are located in different positions regarding the dsDNA binding interface, and they correspond to different disease severity and burden levels. According to the results presented here, the inclusion of those substitutions into different protein constructions (MBD and NTD-MBD-ID) results in different structural and functional effects, highlighting the importance of selecting an appropriate molecular context (i.e., protein construction) when evaluation mutational effects, and emphasizing, in particular for MeCP2, the potential interdomain interaction in intrinsically disordered proteins [18,19]. 2. Materials and Methods 2.1. Plasmid Construction MeCP2 variants from isoform were expressed in E. coli using a pET30b plasmid. The different protein variants were obtained by inserting appropriate substitutions: MBD, MBD R106W, MBD R133C, NTD-MBD-ID, NTD-MBD-ID R106W, and NTD-MBD-ID R133C (Supplemental Figure S1). An N-terminal polyhistidine-tag was inserted for quick purification, and it was removed through an inserted PreScission Protease cleavage site. Appropriate expression was assessed by sequencing analysis: Sanger sequencing using a BigDye Terminator v3.1 Cycle Sequencing Kit (Life Technologies, Carlsbad, CA, USA) in an Applied Biosystems 3730/DNA Analyzer (Thermo Fisher Scientific, Waltham, MA, USA). 2.2. Protein Expression and Purification Protein variants (MBD, MBD R106W, MBD R133C, NTD-MBD-ID, NTD-MBD-ID R106W, NTD-MBD-ID R133C) were expressed and purified following identical procedures. Plasmids were transformed into BL21 (DE3) Star E. coli strain. Cultures were grown in 150 mL of LB/kanamycin (50 µg/mL) media at 37 ◦ C overnight. Then, 4 L of LB/kanamycin (25 µg/mL) were inoculated (1:100 dilution) and incubated under the same conditions until reaching an OD (λ = 600 nm) of 0.6. Protein expression was induced with 1 mM isopropyl 1-thio-β-D-galactopyranoside (IPTG) at 18 ◦ C overnight. Cells were sonicated in ice and benzonase (Merck-Millipore, Madrid, Spain) was added (20 U/mL) to remove nucleic acids. Proteins were purified using metal affinity chromatography employing a HiTrap TALON column (GE-Healthcare Life Sciences, Barcelona, Spain) with two washing steps: buffer sodium phosphate 50 mM, pH 7, NaCl 300 mM, and buffer sodium phosphate 50 mM, pH 7, NaCl 800 mM. Elution was performed applying an imidazole 10–150 mM elution gradient. Protein purity was evaluated by SDS-PAGE. The polyhistidine-tag was removed by processing with GST-tagged PreScission Protease in protease buffer (50 mM Tris-HCl, 150 mM NaCl, pH 7.5) at 4 ◦ C for 4 h. Progress of the proteolytic processing was monitored by SDS-PAGE. In the final step the protein was further purified with a combination of two affinity chromatographic steps to remove the polyhistidine-tag (HiTrap TALON column) and the GST-tagged PreScission Protease (GST TALON column, from GE-Healthcare Life Sciences, Barcelona, Spain). Purity and homogeneity were evaluated by SDS-PAGE and size-exclusion chromatography. Storage buffer consisted of Tris 50 mM pH 7.0 and pooled samples were kept at −80 ◦ C. The identity of all proteins was checked by mass spectrometry (4800plus MALDI-TOF/MS, from Applied Biosystems-Thermo Fisher Scientific, Waltham, MA, USA). Potential DNA contamination was always estimated by UV absorption 260/280 ratio. Because a single tryptophan is located in MBD, an extinction coefficient of 11,460 M−1 cm−1 at 280 nm was employed for all variants, except for the R106W mutants for which a value of 16,960 M−1 cm−1 was applied. Stability and binding assays were performed at different pH and buffer conditions (Tris 50 mM pH 7–9, NaCl 0–150 mM; Pipes 50 mM, pH 7; Phosphate 50 mM, pH 7). When needed, buffer Biomolecules 2020, 10, 1533 4 of 19 exchange was done employing a 3 or 10 kDa-pore size ultrafiltration device (Amicon centrifugal filter, Merck-Millipore, Madrid, Spain) at 4000 rpm and 4 ◦ C. 2.3. Double-Stranded DNA HPLC-purified methylated and unmethylated 45-bp single-stranded DNA (ssDNA) oligomers corresponding to the promoter IV of the mouse brain-derived neurotrophic factor (BDNF) gene [18,19], were purchased from Integrated DNA Technologies. Two complementary pairs of DNA were used for DNA binding assays: forward unmethylated: 5’- GCCATGCCCTGGAACGGAACTCTCCTAATAAAAG-ATGTATCATTT-3’; reverse unmethylated: 5’- AAATGATACATCTTTTATTAGGAGAGTTCCGTTCC-AGGGCATGGC-3’; forward mCpG: 5’- GCCATGCCCTGGAA(5-Me)CGGAACTCTCCTAATAAA-AGATGTATCATTT-3’; reverse mCpG: 5’- AAATGATACATCTTTTATTAGGAGAGTTC(5-Me)CGTT-CCAGGGCATGGC-3’. The ssDNA oligonucleotides were dissolved at a concentration of 0.5 mM, mixed at equimolar ratio, and annealed to obtain 45-bp double-stranded DNA (dsDNA) using a Stratagene Mx3005P qPCR real-time thermal cycler (Agilent Technologies, Santa Clara, CA, USA). The thermal annealing profile consisted of: (1) equilibration at 25 ◦ C for 30 s; (2) heating ramp up to 99 ◦ C; (3) equilibration at 99 ◦ C for 1 min; and (4) 3-h cooling process down to 25 ◦ C at a rate of 1 ◦ C/3 min. 2.4. Circular Dichroism Circular dichroism spectra were recorded in a thermostated Chirascan spectrometer (Applied Photophysics, Leatherhead, UK) using a 0.1 cm (far-UV) or 0.4 cm (near-UV) path-length quartz cuvette (Hellma Analytics, Müllheim, Germany) with a bandwidth of 1 nm, a spectral resolution of 0.5 nm, and a response time of 5 s. Temperature was controlled by a Peltier unit and monitored using a temperature probe. The assays were performed in the far-UV (200–260 nm) and the near-UV (250–310 nm) ranges. Protein concentration was set at 10–50 µM, depending on the signal-to-noise ratio. 2.5. Fluorescence Spectroscopy Protein thermal unfolding studies were performed in a Cary Eclipse fluorescence spectrophotometer (Varian—Agilent, Santa Clara, CA, USA) using a protein concentration of 5 µM and a 1 cm path-length quartz cuvette (Hellma Analytics, Müllheim, Germany). The temperature was controlled by a Peltier unit and monitored using a temperature probe, at a heating rate of 1 ◦ C/min. Fluorescence emission spectra were recorded from 300 to 400 nm using an excitation wavelength of 290 nm and a bandwidth of 5 nm. Assays were performed and at the emission wavelength of 330 nm (maximal protein spectral change along the unfolding). A simple two-state unfolding model was considered for analyzing the assays: ∆G(T )   (AN +BN T )+(AU +BU T )exp − RT F(T ) =  ∆G(T )  1+exp − RT (1)     ∆G(T ) = ∆H (Tm ) 1 − T Tm + ∆CP T − Tm − T ln T Tm where F(T) is the fluorescence signal at a given absolute temperature T, Tm is the unfolding temperature, ∆H(Tm ) is the unfolding enthalpy (at the Tm ), ∆CP is the unfolding heat capacity, and ∆G(T) is the stabilization Gibbs energy (which is a temperature function). The adjustable parameters AN , BN , AU , and BU are instrumental parameters defining the pre- (native) and post-transition (unfolded) regions in the unfolding trace. The stabilizing effect upon dsDNA interaction was assessed performing thermal denaturations of the different proteins (at 5 µM) in the presence of methylated and unmethylated DNA (at 10 µM) under the same conditions. Biomolecules 2020, 10, 1533 5 of 19 2.6. Isothermal Titration Calorimetry (ITC) The interaction between the different proteins and dsDNA was studied in an Auto-iTC200 (MicroCal, Malvern-Panalytical, Malvern, UK). dsDNA (50 µM) in the injecting syringe was titrated into protein in the calorimetric cell (3–5 µM). Series of 2 µL-injections of titrant with a time-spacing of 150 s were programmed, maintaining a stirring speed of 750 rpm, and a reference power of 10 µcal/s. The association constant, KB , and the observed enthalpy of binding, ∆HB,obs , were estimated through non-linear regression of the experimental data employing a single ligand binding site model (1:1 protein:dsDNA stoichiometry) or a two ligand binding sites model (1:2 protein:dsDNA stoichiometry) implemented in Origin (OriginLab, Northampton, MA, USA) [21,22]. The dissociation constant Kd was calculated as the inverse of KB,obs , and the binding Gibbs energy and entropy were calculated applying standard well-known relationships: ∆G = −RT lnKB , ∆G = ∆H − T∆S. The number of protons released from or uptaken by the protein-dsDNA complex upon dsDNA binding, ∆nH , was determined, according to [23–25]: ∆HB,obs = ∆H + ∆nH ∆Hbu f f er (2) where ∆H is the buffer-independent binding enthalpy, and ∆Hbuffer is the ionization enthalpy of the buffer. Titrations were performed in buffers with different ionization enthalpies (Tris, 11.35 kcal/mol; Pipes, 2.67 kcal/mol; and phosphate, 0.86 kcal/mol) [26] in order to estimate the buffer-independent thermodynamic parameters (∆H and ∆nH ) from linear regression using Equation (2). From ∆G and ∆H, the buffer-independent binding entropy can be readily calculated. The parameter ∆nH may be non-zero if ligand binding results in changes in the proton dissociation constant of certain ionizable residues (either in the protein or the ligand) as a consequence of changes in their microenvironment upon complex formation. The association binding constant KB will be not affected by the buffer ionization as long as the pKa of the buffer is close to the experimental pH. However, the observed binding enthalpy (and, therefore, the observed entropic contribution) will contain an additional contribution from buffer ionization as indicated above. The experimental strategy allows removing the extrinsic contribution from buffer ionization. Noticeably, ∆nH has practical utility since it reports the change in binding affinity as a result of a (moderate) change in pH, according to Wyman’s linkage relationships [27]: ∂ log KB ! ∆nH = − (3) ∂pH P 3. Results 3.1. Mutation R106W Induces Larger Structural Rearrangements Compared to R133C RTT-associated MeCP2 variants were expressed in E. coli and successfully purified by affinity chromatography, allowing us to study the potential destabilizing impact of the selected mutations on the MBD conformation and its interaction with dsDNA. Far-UV and near-UV CD spectra were recorded to assess whether R106W and R133C mutations might disrupt MBD secondary and tertiary structure. Being tryptophan bulkier than cysteine (which is even smaller than arginine), and being R106 located buried inside the MBD while R133 is solvent exposed, a larger rearrangement would be expected for R106W mutation. In addition, assays with MBD and NTD-MBD-ID variants were carried out to determine the effect of flanking domains might exert on the destabilizing impact of these RTT-associated mutations. Far-UV CD spectra of MBD (Figure 1) exhibited two regions typical from β-sheet and random-coil (around 208–210 nm) and α-helix (around 222 nm). MBD mutants showed conserved secondary structure, exhibiting a similar proportion of α-helix and β-sheet to wild-type MBD, but a smaller intensity of the signal could be appreciated, which might be caused by disrupting effects that affected equally to α-helix and β-sheet elements (Figure 1). Furthermore, the MBD R106W mutant showed a Biomolecules 2020, 10, 1533 6 of 19 positive band around 230 nm typically produced by the presence of an additional tryptophan residue [28]. The far-UV CD spectra of the NTD-MBD-ID mutants exhibited a lower intensity (50% reduction in MRE, molar residue ellipticity) compared to the MBD spectra when normalized by the number of residues, indicating that the flanking domains, NTD and ID, are disordered and hardly contribute to the CD signal. Also, in the presence of NTD and ID the location of the minimum of the R106W CD signal was significantly Biomolecules 2020, 10,shifted x to larger wavelengths (minimum at 218 nm), while the minimum of R133C 6 of 18 CD signal remained at lower wavelengths minimum at 213 nm), showing that these mutations had a had a considerable considerable impact on impact on NTD-MBD-ID NTD-MBD-ID protein secondary protein secondary structure.structure. Even the Even the wild-type wild-type NTD-MBD-ID NTD- MBD-ID showed showedminimum a shifted a shifted minimum at larger wavelength at larger wavelength (around 215 (around 215 nm). nm). R106W alsoR106W alsoaexhibited exhibited CD banda CD band around 230around 230 nm,tocompared nm, compared to thealthough the wild type, wild type, although it was it smaller sensibly was sensibly smaller than that of MBDthanR106W. that of MBD R106W. Regarding Regarding the near-UV the near-UV spectra, the R106W spectra, mutantstheexhibit R106W mutants larger exhibitthan alterations larger alterations those observedthanfor those mutants, R133C observed whosefor R133C mutants, spectra whose are quite spectra similar are quite to those similar variants, of wild-type to those indicating of wild-type variants, that in the indicating R106W that in the R106W the environment the environment of the aromatic residues is of the aromatic altered. Similarly,residues is altered. normalization of theSimilarly, spectra normalization with the numberofofthe spectraresults residues with the in number of residues smaller signal, results in with in agreement smaller signal, in contribution a negligible agreement with to a negligible the spectra from contribution NTD and to ID.the spectra from NTD and ID. Figure 1. Far-UV (a,b) and near-UV (c,d) circular dichroism spectra of wild-type and mutant Figure 1. Far-UV Methyl-CpG (a,b) binding and near-UV protein (c,d) 2 (MeCP2) circular dichroism methyl-CpG bindingspectra domainof(MBD) wild-type (a,c) and and mutant Methyl- NTD-MBD-ID CpG wild-type (b,d): binding protein 2 (MeCP2) (continuous methyl-CpG line), R106W (dashed binding domain line), and R133C(MBD) (dotted(a,c) and line). NTD-MBD-ID Spectra (b,d): were recorded wild-type at pH 7. (continuous line), R106W (dashed line), and R133C (dotted line). Spectra were recorded at pH 7. 3.2. RTT-Associated Mutations Alter Protein Stability and the dsDNA-Induced Stabilization Effect 3.2. RTT-Associated Mutations Alter Protein Stability and the dsDNA-Induced Stabilization Effect 3.2.1. Stability Changes on MBD Induced by RTT-Associated Mutations 3.2.1. StabilityofChanges Because the lowon MBD Induced content by RTT-Associated in secondary structure andMutations the small change in the CD signal accompanying Because ofthe thethermal denaturation low content process, in secondary fluorescence structure and thespectroscopy small changewas in employed for the CD signal thermal unfolding assays. All protein variants exhibited a well-defined thermal accompanying the thermal denaturation process, fluorescence spectroscopy was employed forunfolding transition (Figures thermal2unfolding and 3), which, assays.together with All protein the CDexhibited variants data, indicate that all protein a well-defined thermalconstructs unfoldingpresent a transition well-folded conformation, likely corresponding to the structured region in MBD. (Figures 2,3), which, together with the CD data, indicate that all protein constructs present a well- Except folded for NTD-MBD-ID conformation, R106W, the Tto likely corresponding m decreased withregion the structured pH andin increased MBD. with ionic strength (Figure 2 and for Except Table 1), as observed NTD-MBD-ID with the R106W, the wild-type variants Tm decreased with[20]. Thisincreased pH and indicates with that the unfolding ionic strength (Figure 2 and Table 1), as observed with the wild-type variants [20]. This indicates that the unfolding process is coupled to the preferential interaction of protons and salt ions with the folded conformation of the protein variants (i.e., unfolding is accompanied by the release of protons and salt ions). Each MBD mutation has a different impact on protein stability (Figure 2 and Table 1). Thus, R106W mutation exhibited a stabilizing effect increasing the Tm value in all assayed experimental Biomolecules 2020, 10, x 7 of 18 deleterious effect might be related to the protein functionality. The stabilizing effect caused by salt Biomolecules 2020, 10, 1533 7 of 19 ions was similar in both R106W and R133C mutants. MBD R106W and R133C MBD mutants interact preferentially with salt ions in the native state, but very likely salt ions may have an additional charge-screening process is coupled toeffect and contribute the preferential to the increase interaction stability of protons at ions and salt highwith ionicthe strength folded by diminishing conformation ofrepulsive interactions the protein between variants (i.e., positively unfolding charged groups. is accompanied by the release of protons and salt ions). Figure 2. Fluorescence thermal denaturations for the MBD R106W (a–c), and MBD R133C (d–f) under Figure 2. Fluorescence thermal denaturations for the MBD R106W (a,b,c), and MBD R133C (d,e,f) different conditions. The influence of the pH was assessed (pH 7, black squares; pH 8, red squares; and under different conditions. The influence of the pH was assessed (pH 7, black squares; pH 8, red pH 9, green squares) (a,d). The influence of the presence of dsDNA at pH 7 was assessed (absence squares; and pH 9, green squares) (a,d). The influence of the presence of dsDNA at pH 7 was assessed of dsDNA, black squares; presence of unmethylated CpG-dsDNA, red squares; and presence of (absence of dsDNA, black squares; presence of unmethylated CpG-dsDNA, red squares; and presence methylated mCpG-dsDNA, green squares) at pH 7 and low ionic strength (b,e) and high ionic strength Biomolecules 2020, 10, x mCpG-dsDNA, green squares) at pH 7 and low ionic strength (b,e) and high ionic of methylated 8 of 18 (c,f). All unfolding traces could be fitted employing a two-state unfolding model (continuous lines) strength (c,f). All unfolding traces could be fitted employing a two-state unfolding model (continuous according to Equation (1). lines) according to equation 1. One of the most striking results for wild-type MBD was that, at any pH and ionic strength, the structural stability gradually increased with the addition of the disordered domains NTD and ID [20]. The stability of NTD-MBD-ID mutants was also assessed to determine the contribution of those disordered regions, through specific or unspecific effects, to the structural stability (Figure 3 and Table 1). Contrary to wild-type MBD, the addition of NTD and ID may increase or decrease the structural stability of the mutant variant depending on the pH and the ionic strength. For example, at pH 7 and low ionic strength, addition of MBD-flanking domains lowers the stability in the R106W mutant, but raises the stability in the R133C mutant; however, at high ionic strength, addition of MBD-flanking domains lowers the stability of the R106W, while the R133C undergoes no stability change. However, taking NTD-MBD-ID as a reference, both R106W and R133C lowered the stability, in reasonable agreement with previous reported results given the differences in the experimental conditions [18,19]. In general, R133C mutants unfolding parameters are closer to wild-type variants, compared to R106W mutants. Nevertheless, a stabilizing effect caused by R106W mutation can still be observed at higher pH values, indicating a stronger pH dependency of this mutant in the unfolding process. Figure 3. Fluorescence thermal denaturations for the NTD-MBD-ID R106W (a–c), and NTD-MBD-ID Figure 3. Fluorescence thermal denaturations for the NTD-MBD-ID R106W (a,b,c), and NTD-MBD- R133C (d–f) under different conditions. The influence of the pH was assessed (pH 7, black squares; pH 8,R133C ID (d,e,f) under red squares; and pHdifferent conditions. 9, green The influence squares) (a,d). of the pH The influence waspresence of the assessedof(pH 7, black dsDNA atsquares; pH 7 pHassessed was 8, red squares; (absenceand pH 9, green of dsDNA, blacksquares) squares;(a,d). The of presence influence of the presence unmethylated CpG-dsDNA,of dsDNA at pH 7 red squares; was and assessedof(absence presence of dsDNA, methylated black squares; mCpG-dsDNA, greenpresence squares)ofatunmethylated pH 7 and lowCpG-dsDNA, ionic strengthred squares; (b,e) and and presence of methylated mCpG-dsDNA, green squares) at pH 7 and low ionic strength high ionic strength (c,f). All unfolding traces could be fitted employing a two-state unfolding model (b,e) and high ionic strength (c,f). All unfolding (continuous lines) according to Equation (1). traces could be fitted employing a two-state unfolding model (continuous lines) according to equation 1. Table 1. Thermal stability of the different MeCP2 variants under different conditions. Tm ΔH(Tm) (°C) (kcal/mol) pH 7 38.4 ± 0.2 29 ± 1 pH 8 36.9 ± 0.3 33 ± 2 a MBD pH 9 30.8 ± 0.3 27 ± 1 Biomolecules 2020, 10, 1533 8 of 19 Table 1. Thermal stability of the different MeCP2 variants under different conditions. Tm ∆H(Tm ) (◦ C) (kcal/mol) pH 7 38.4 ± 0.2 29 ± 1 a pH 8 36.9 ± 0.3 33 ± 2 MBD pH 9 30.8 ± 0.3 27 ± 1 pH 7, NaCl 150 mM 46.4 ± 0.4 32 ± 1 pH 7 47.3 ± 0.2 21 ± 1 b pH 8 45.8 ± 0.2 20 ± 1 MBD R106W pH 9 46.7 ± 0.2 23 ± 1 pH 7, NaCl 150 mM 54.9 ± 0.2 28 ± 1 pH 7 39.2 ± 0.2 26 ± 1 b pH 8 38.4 ± 0.3 33 ± 2 MBD R133C pH 9 38.2 ± 0.2 25 ± 1 pH 7, NaCl 150 mM 47.0 ± 0.1 29 ± 2 pH 7 46.2 ± 0.2 37 ± 1 a pH 8 45.9 ± 0.3 48 ± 3 NTD-MBD-ID pH 9 45.4 ± 0.2 53 ± 2 pH 7, NaCl 150 mM 49.8 ± 0.1 38 ± 1 pH 7 43.1 ± 0.3 23 ± 1 b pH 8 52.8 ± 0.3 30 ± 2 NTD-MBD-ID R106W pH 9 54.3 ± 0.3 34 ± 2 pH 7, NaCl 150 mM 45.2 ± 0.2 37 ± 1 pH 7 45.8 ± 0.2 33 ± 1 b pH 8 43.8 ± 0.2 31 ± 1 NTD-MBD-ID-TRD R133C pH 9 34.5 ± 0.2 30 ± 1 pH 7, NaCl 150 mM 47.2 ± 0.1 37 ± 2 a Previous work [20]. b This work. Each MBD mutation has a different impact on protein stability (Figure 2 and Table 1). Thus, R106W mutation exhibited a stabilizing effect increasing the Tm value in all assayed experimental conditions compared to wild-type MBD. In contrast, R133C mutation did exhibit little impact on protein stability with regard to wild-type MBD, just a slight stabilization in agreement with previous results [18,19]; it seems that this mutation does not affect the protein stability, and, very likely, its deleterious effect might be related to the protein functionality. The stabilizing effect caused by salt ions was similar in both R106W and R133C mutants. MBD R106W and R133C MBD mutants interact preferentially with salt ions in the native state, but very likely salt ions may have an additional charge-screening effect and contribute to the increase stability at high ionic strength by diminishing repulsive interactions between positively charged groups. One of the most striking results for wild-type MBD was that, at any pH and ionic strength, the structural stability gradually increased with the addition of the disordered domains NTD and ID [20]. The stability of NTD-MBD-ID mutants was also assessed to determine the contribution of those disordered regions, through specific or unspecific effects, to the structural stability (Figure 3 and Table 1). Contrary to wild-type MBD, the addition of NTD and ID may increase or decrease the structural stability of the mutant variant depending on the pH and the ionic strength. For example, at pH 7 and low ionic strength, addition of MBD-flanking domains lowers the stability in the R106W mutant, but raises the stability in the R133C mutant; however, at high ionic strength, addition of MBD-flanking domains lowers the stability of the R106W, while the R133C undergoes no stability change. However, taking NTD-MBD-ID as a reference, both R106W and R133C lowered the stability, in reasonable agreement with previous reported results given the differences in the experimental conditions [18,19]. In general, R133C mutants unfolding parameters are closer to wild-type variants, compared to Biomolecules 2020, 10, 1533 9 of 19 R106W mutants. Nevertheless, a stabilizing effect caused by R106W mutation can still be observed at higher pH values, indicating a stronger pH dependency of this mutant in the unfolding process. 3.2.2. Stability Changes in RTT-Associated Mutant Proteins Induced by ds-DNA Binding The interaction of MBD and NTD-MBD-ID mutant variants with dsDNA was indirectly determined by assessing the stabilizing effect induced by unmethylated CpG-dsDNA and methylated mCpG-dsDNA. Thermal denaturations were performed for all MeCP2 protein variants employing the same protocol used for the dsDNA-free variants, in order to determine the apparent thermodynamic parameters for the unfolding of the protein-dsDNA complex (Figures 2 and 3 and Tables 2 and 3). Table 2. Thermal stability of the different MeCP2 variants in the presence of unmethylated (CpG-) and methylated (mCpG-) dsDNA at pH 7. Tm ∆H(Tm ) (◦ C) (kcal/mol) 38.4 ± 0.3 29 ± 1 a MBD CpG-dsDNA 48.9 ± 0.3 38 ± 2 mCpG-dsDNA 56.5 ± 0.3 44 ± 2 47.3 ± 0.2 21 ± 1 b MBD R106W CpG-dsDNA 60.7 ± 0.2 17 ± 1 mCpG-dsDNA 64.3 ± 0.2 28 ± 2 39.2 ± 0.2 26 ± 1 b MBD R133C CpG-dsDNA 39.4 ± 0.1 24 ± 1 mCpG-dsDNA 43.5 ± 0.2 29 ± 2 46.2 ± 0.2 37 ± 2 a NTD-MBD-ID CpG-dsDNA 64.5 ± 0.1 60 ± 2 mCpG-dsDNA 71.2 ± 0.2 86 ± 4 43.1 ± 0.2 23 ± 1 b NTD-MBD-ID R106W CpG-dsDNA 70.3± 0.2 47 ± 2 mCpG-dsDNA 72.8 ± 0.2 62 ± 3 45.8 ± 0.2 34 ± 2 b NTD-MBD-ID R133C CpG-dsDNA 59.1 ± 0.1 45 ± 2 mCpG-dsDNA 67.8 ± 0.2 51 ± 3 a Previous work [20]. b This work. Table 3. Thermal stability of the different MeCP2 variants in the presence of unmethylated (CpG-) and methylated (mCpG-) dsDNA at pH 7 and high ionic strength (NaCl 150 mM). Tm ∆H(Tm ) (◦ C) (kcal/mol) 46.4 ± 0.4 32 ± 1 a MBD CpG-dsDNA 48.3 ± 0.3 34 ± 2 mCpG-dsDNA 49.5 ± 0.3 35 ± 2 54.9 ± 0.2 27 ± 1 b MBD R106W CpG-dsDNA 57.4 ± 0.2 34 ± 2 mCpG-dsDNA 58.6 ± 0.2 33 ± 2 47.0 ± 0.1 29 ± 1 b MBD R133C CpG-dsDNA 46.6 ± 0.1 28 ± 1 mCpG-dsDNA 47.7 ± 0.2 29 ± 1 49.8 ± 0.1 38 ± 2 a NTD-MBD-ID CpG-dsDNA 65.6 ± 0.2 55 ± 2 mCpG-dsDNA 66.4 ± 0.2 63 ± 3 Biomolecules 2020, 10, 1533 10 of 19 Table 3. Cont. Tm ∆H(Tm ) (◦ C) (kcal/mol) 45.2 ± 0.1 23 ± 1 b NTD-MBD-ID R106W CpG-dsDNA 68.5 ± 0.2 33 ± 2 mCpG-dsDNA 70.2 ± 0.2 41 ± 2 47.2 ± 0.1 37 ± 2 b NTD-MBD-ID-TRD R133C CpG-dsDNA 58.4 ± 0.2 46 ± 2 mCpG-dsDNA 60.5 ± 0.2 50 ± 2 a Previous work [20]. b This work. In general, dsDNA increased the stability in all variants, as can be observed in the values in Tm compared to those for the dsDNA-free variants, at each experimental condition (Table 2). High ionic strength diminished the extent of the dsDNA stabilization effect (Table 3) through a double mechanism: ionic strength increases protein variants stability and decreases dsDNA binding affinity [20]. MBD R106W is preferentially stabilized by dsDNA, while MBD R133C shows a limited ability to bind dsDNA, because the stabilizing effect induced by dsDNA is very small (Figure 2 and Tables 2 and 3). A small stabilization effect can be observed for MBD R133C in presence of methylated dsDNA; therefore, MBD R133C might conserve its ability to bind dsDNA, but with a much lower affinity. Wild-type MBD was stabilized by both types of dsDNA, but the stabilizing effect induced by methylated dsDNA was significantly larger. However, MBD R106W showed more similar stabilizing effects for methylated and unmethylated dsDNA. In the constructs containing the two MBD-flanking domains, NTD-MBD-ID, methylated dsDNA always induced a larger stabilization effect than unmethylated dsDNA (Figure 3 and Tables 2 and 3), reflecting that the preferential interaction or specificity of MBD towards methylated dsDNA is maintained. Similarly to previous data [21], the MBD-flanking domains, NTD and ID, not only increase (in general) the thermal stability of dsDNA-free MBD mutants, but they also strengthen the stabilizing effect induced by dsDNA binding, and enhance the discriminating power regarding dsDNA methylation as observed by the extent of the stabilization effect. NTD-MBD-ID R106W showed a large stabilizing effect induced by dsDNA, exhibiting a slight difference between both methylated and unmethylated dsDNA effects. NTD-MBD-ID R133C showed an interesting behavior: whereas MBD R133C hardly exhibited a dsDNA-induced stabilizing effect, the addition of the MBD-flanking disordered domains rescued the ability to interact with dsDNA as indicated by the considerable dsDNA-induced stabilization effect. For both MBD and NTD-MBD-ID variants, the substitution R106W induces larger dsDNA stabilization effects compared to the wild-type variant, whereas the substitution R133C induces a smaller stabilization effects. This will be discussed later on. Although the stabilization effect induced by dsDNA illustrates the fact that MeCP2 mutant constructs are able to interact with dsDNA, this observable cannot be easily employed to measure and quantify binding affinities and other thermodynamic parameters for the interaction in a straightforward manner. The extent of the stabilization effect caused by the presence of dsDNA (∆Tm ) on a given protein conformation depends on the binding affinity, the binding stoichiometry, and the concentration of (free) dsDNA. Furthermore, the binding enthalpy and the binding heat capacity strongly influence the extent of the dsDNA-induced stabilization effect. This makes not possible to estimate binding affinities properly and to establish an affinity ranking based on ∆Tm values. Therefore, further ITC experiments were required to accomplish a biophysical characterization of the interaction between MeCP2 mutants and methylated and unmethylated dsDNA, in order to determine binding affinities and the enthalpic/entropic contributions to the binding. Biomolecules 2020, 10, 1533 11 of 19 3.3. RTT-Associated Mutations Affect dsDNA Interaction Differently Depending on the MeCP2 Construction 3.3.1. Interaction of MBD Mutants with ds-DNA Contrary to MBD R106W, which shows considerable binding affinity for dsDNA (Figure 4 and Table 4), MBD R133C did not show any interaction with dsDNA under any tested experimental condition (Supplemental Figure S2); this cannot be explained by a loss of structure due to the mutation, because the previous results provided evidence for MBD R133C being properly (partially) folded. The interaction of MBD R106W with dsDNA was characterized by moderate affinity (Kd in the submicromolar range), slightly higher than that of wild-type MBD, and exhibiting a much more favorable entropic contribution to the binding and a much more unfavorable binding enthalpy (Table 4). Opposite to what occurs with wild-type MBD, the formation of the MBD R106W dsDNA complex is accompanied by the uptake of about 2–3 protons from the bulk solution (i.e. at least three ionizable groups are involved in the proton exchange process) (Table 4). Hence, regarding the pH dependency Biomolecules 2020, 10, x 11 of 18 of the binding affinity, increasing the pH in 1 unit would cause a 400-fold decrease in the binding affinity, whereas in the case of wild-type MBD it would cause a 160-fold increase in binding affinity. affinity, whereas in the case of wild-type MBD it would cause a 160-fold increase in binding affinity. These results indicated that, although the affinity is comparable or slightly better for MBD R106W, the These results indicated that, although the affinity is comparable or slightly better for MBD R106W, mode of interaction with dsDNA might be quite different compared to wild-type MBD. In addition, the mode of interaction with dsDNA might be quite different compared to wild-type MBD. In the ability to discriminate between unmethylated and methylated dsDNA was diminished. addition, the ability to discriminate between unmethylated and methylated dsDNA was diminished. Figure 4. Interaction of the MBD R106W with unmethylated CpG-dsDNA (a) and methylated Figure 4. Interaction mCpG-dsDNA (b) by of ITCthe inMBD PipesR106W 50 mM,withpH 7,unmethylated CpG-dsDNA 20 ◦ C. Upper plots show the(a) and methylated thermogram mCpG- (raw thermal dsDNA (b) by ITC in Pipes 50 mM, pH 7, 20 °C. Upper plots show the thermogram power as a function of time) and the lower plots show the binding isotherm (ligand-normalized heat (raw thermal poweras effects asaafunction functionof ofthe time) andratio). molar the lower plots show Non-linear the binding least-squares isotherm analysis (ligand-normalized using a single binding heatsite effects as a function of the molar ratio). Non-linear least-squares analysis model allowed estimating the observed binding affinity and enthalpy (continuous lines).using a single binding site (c) Equation (2) model was allowedfor employed estimating estimatingthethe observed binding affinity buffer-independent and enthalpy binding (continuous enthalpy: CpG-dsNA lines). (open(c) Equation squares) (2) was and employed for mCpG-dsDNA estimating (closed the buffer-independent squares). binding From linear regression, theenthalpy: intercept CpG-dsNA (open with the y-axis squares) (observed and mCpG-dsDNA enthalpy extrapolated(closed at zerosquares). From linear buffer ionization regression, enthalpy) the intercept provides with the y-axisinteraction the buffer-independent (observed enthalpy extrapolated at zero buffer enthalpy ∆H, and the slope provides ∆nH . ionization enthalpy) provides the buffer-independent interaction enthalpy ΔH, and the slope provides ΔnH. Table 4. Buffer-independent binding parameters for the interaction of the different MeCP2 variants 3.3.2.with unmethylated Interaction (CpG-) and methylated of NTD-MBD-ID Mutants (mCpG-) with ds-DNAdsDNA at pH 7 and 20 ◦ C. It was previously shown that the presence Kd ∆Ga small unstructured of ID, ∆H −T∆S located flanking domain ∆nH (nM) (kcal/mol) (kcal/mol) (kcal/mol) MBD in its C-terminal position, modified completely the dsDNA interaction: a second interaction site appeared together CpG-DNA a MBD with a marked increase −8.5 450in the binding 0.8of MBD for affinity −9.3 −2.4 dsDNA [19,20]. The mCpG-DNA interaction of the two mutants, NTD-MBD-ID 240 R106W −8.9 and R133C,1.5 −10.4 by ITC could be observed −2.1(Figures 5 and 6, Table 4). The presence of ID increased the binding affinity of the MBD site in NTD-MBD-ID R106W (taking MBD R106W as a reference), but that increase (3-fold) is small compared to that observed for wild-type (400-fold increase) (Table 4). However, taking NTD-MBD-ID as a reference, the R106W mutation decreased the dsDNA affinity. In NTD-MBD-ID R106W, the binding affinity of the MBD interaction site (high-affinity site) remained in the submicromolar range, comparable to that exhibited by the ID interaction site (low-affinity site), whose binding affinity is only 10-fold lower. Overall, the Biomolecules 2020, 10, 1533 12 of 19 Table 4. Cont. Kd ∆G ∆H −T∆S ∆nH (nM) (kcal/mol) (kcal/mol) (kcal/mol) b CpG-DNA 110 −9.3 16.7 −26.0 2.7 MBD R106W mCpG-DNA 95 −9.4 16.0 −25.4 2.6 b CpG-DNA n.i. NTD-MBD R133C mCpG-DNA n.i. 1.9 −11.7 −54.6 42.9 −0.1 CpG-DNA 250 −8.9 −7.6 −1.3 −2.9 a NTD-MBD-ID 0.56 −12.4 −48.4 36.0 −0.1 mCpG-DNA 62 −9.7 −2.1 −7.6 −1.3 27 −10.2 15.6 −25.8 1.4 CpG-DNA b 320 −8.7 −25.6 16.9 −1.6 NTD-MBD-ID R106W 23 −10.2 22.6 −32.8 1.4 mCpG-DNA 430 −8.5 −16.7 8.2 −1.7 2.5 −11.5 −49.1 37.6 −2.9 CpG-DNA b 83 −9.5 −11.8 2.3 −0.7 NTD-MBD-ID R133C 2.1 −11.6 −45.0 33.4 −2.9 mCpG-DNA 62 −9.7 −10.0 0.3 −0.5 Two dissociation constants Kd (for high-affinity site in MBD and low-affinity site in intervening domain (ID)) are provided for NTD-MBD-ID variants. Relative error in Kd is 15%, absolute error in ∆G is 0.1 kcal/mol, absolute error in ∆H and −T∆S is 0.3 kcal/mol, and absolute error in ∆nH is 0.2. a Previous work [20]. b This work. n.i.: no interaction was observed (at any experimental condition). 3.3.2. Interaction of NTD-MBD-ID Mutants with ds-DNA It was previously shown that the presence of ID, a small unstructured domain located flanking MBD in its C-terminal position, modified completely the dsDNA interaction: a second interaction site appeared together with a marked increase in the binding affinity of MBD for dsDNA [19,20]. The interaction of the two mutants, NTD-MBD-ID R106W and R133C, could be observed by ITC (Figures 5 and 6, Table 4). The presence of ID increased the binding affinity of the MBD site in NTD-MBD-ID R106W (taking MBD R106W as a reference), but that increase (3-fold) is small compared to that observed for wild-type (400-fold increase) (Table 4). However, taking NTD-MBD-ID as a reference, the R106W mutation decreased the dsDNA affinity. In NTD-MBD-ID R106W, the binding affinity of the MBD interaction site (high-affinity site) remained in the submicromolar range, comparable to that exhibited by the ID interaction site (low-affinity site), whose binding affinity is only 10-fold lower. Overall, the thermodynamic signature of the interaction was completely opposite to that of the wild type. The R106W mutation strongly disturbs the interaction with dsDNA at the MBD binding site, but also at the ID binding site. In NTD-MBD-ID R133C the addition of the ID domain not only provided an additional dsDNA binding site in ID with a binding affinity in the submicromolar range, but also recovered dsDNA-binding ability in the binding site in MBD with a dramatically increased affinity in the low nanomolar range (Table 4). NTD-MBD-ID R133C did not exhibit large variations in binding affinity regarding the wild type variant, showing similar binding affinities for both the MBD and the ID interaction sites. Strikingly, except the net number of exchanged protons, this mutant exhibited a thermodynamic binding profile similar to that of the wild-type variant. The presence of an additional dsDNA binding site in NTD-MBD-ID variants is responsible, together with the higher affinity, for the much larger dsDNA-induced stabilization effect observed on those variants, compared to the smaller stabilization effects observed for the MBD constructs. Biomolecules 2020, 10, x 12 of 18 the much larger dsDNA-induced stabilization effect observed on those variants, compared to the Biomolecules 2020, 10, x 12 of 18 smaller stabilization effects observed for the MBD constructs. Biomolecules the much2020, 10, 1533 larger dsDNA-induced stabilization effect observed on those variants, compared 13toofthe 19 smaller stabilization effects observed for the MBD constructs. Figure 5. Interaction of the NTD-MBD-ID R106W with unmethylated CpG-dsDNA (a) and methylated mCpG-dsDNA (b) by ITC in Tris 50 mM, 20 °C, pH 7. Upper plots show the thermogram Figure 5. Interaction (raw thermal powerofasthe NTD-MBD-ID a function of time)R106W withlower and the unmethylated plots showCpG-dsDNA the binding(a)isotherm and methylated (ligand- Figure 5. Interaction of the NTD-MBD-ID R106W with unmethylated CpG-dsDNA (a) and ◦ C, pH mCpG-dsDNA (b) by ITC in Tris 50 mM, 20 7. Upper plots show the thermogram normalized heat effects as a function of the molar ratio). Non-linear least-squares analysis using a two (raw thermal methylated mCpG-dsDNA (b) by ITC in Tris 50 mM, 20 °C, pH 7. Upper plots show the thermogram power bindingassites a function model of time) and allowed the lower estimating theplots showbinding observed the binding isotherm affinity (ligand-normalized and enthalpy heat (continuous lines). (raw thermal power as a function of time) and the lower plots show the binding isotherm (ligand- effects as a function (c) Equation of employed (2) was the molar ratio). Non-linear for estimating theleast-squares analysis using buffer-independent bindinga two bindingfor enthalpy sites model both sites normalized heat effects as a function of the molar ratio). Non-linear least-squares analysis using a two allowed estimating (high affinity, the observed squares; binding low affinity, affinity and triangles) enthalpy (continuous for CpG-dsNA lines). (c) (open symbols) andEquation mCpG-dsDNA(2) was binding sites model allowed estimating the observed binding affinity and enthalpy (continuous lines). employed for estimating (closed symbols). From thelinear buffer-independent regression, the binding enthalpy intercept withfor the bothy-axis sites (high affinity, enthalpy (observed squares; (c) Equation (2) was employed for estimating the buffer-independent binding enthalpy for both sites low affinity, triangles) for CpG-dsNA (open symbols) and mCpG-dsDNA (closed symbols). extrapolated at zero buffer ionization enthalpy) provides the buffer-independent interaction enthalpy From linear (high affinity, regression, squares; low affinity, triangles) for CpG-dsNA (open symbols) and mCpG-dsDNA y-axis (observed enthalpy extrapolated at zero buffer ionization ΔH, and thethe intercept slope provideswithΔnthe H. (closed symbols). enthalpy) provides theFrom linear regression, buffer-independent the intercept interaction enthalpywith the the ∆H, and y-axis slope(observed provides ∆n enthalpy H. extrapolated at zero buffer ionization enthalpy) provides the buffer-independent interaction enthalpy ΔH, and the slope provides ΔnH. Figure 6. Interaction of the NTD-MBD-ID R133C with unmethylated CpG-dsDNA (a) and methylated Figure 6. Interaction of the NTD-MBD-ID R133C with unmethylated CpG-dsDNA (a) and methylated mCpG-dsDNA (b) by ITC in Tris 50 mM, 20 ◦ C, pH 7. Upper plots show the thermogram (raw thermal mCpG-dsDNA (b) by ITC in Tris 50 mM, 20 °C, pH 7. Upper plots show the thermogram (raw thermal power as a function of time) and the lower plots show the binding isotherm (ligand-normalized heat power as a function of time) and the lower plots show the binding isotherm (ligand-normalized heat effects Figureas6.aInteraction function of ofthethe molar ratio). Non-linear NTD-MBD-ID R133C least-squares analysisCpG-dsDNA with unmethylated using a two binding (a) and sites model methylated effects as a function of the molar ratio). Non-linear least-squares analysis using a two binding sites allowed estimating mCpG-dsDNA (b) the observed by ITC in Trisbinding 20 °C, pH 50 mM,affinity and7.enthalpy (continuous Upper plots show thelines). (c) Equation thermogram (2) was (raw thermal model allowed estimating the observed binding affinity and enthalpy (continuous lines). (c) Equation employed power as afor estimating function the buffer-independent of time) and the lower plotsbinding show theenthalpy binding forisotherm both sites (high affinity, squares; (ligand-normalized heat (2) was employed for estimating the buffer-independent binding enthalpy for both sites (high affinity, low affinity, triangles) for CpG-dsNA (open symbols) and mCpG-dsDNA (closed symbols). effects as a function of the molar ratio). Non-linear least-squares analysis using a two binding sites From linear squares; low regression, affinity, triangles) the intercept for CpG-dsNA the y-axisbinding (open symbols) and mCpG-dsDNA (closedionization symbols). model allowed estimatingwiththe observed (observed enthalpy affinity extrapolated and enthalpy at zerolines). (continuous buffer(c) Equation From linear regression, the intercept with interaction the y-axis (observed enthalpy extrapolated at zero buffer enthalpy) provides (2) was employed theestimating for buffer-independent the buffer-independent binding∆H, enthalpy and the enthalpy forslope bothprovides ∆naffinity, sites (high H. ionization enthalpy) provides the buffer-independent interaction enthalpy ΔH, and the slope provides squares; low affinity, triangles) for CpG-dsNA (open symbols) and mCpG-dsDNA (closed symbols). ΔnH. 4. Discussion From linear regression, the intercept with the y-axis (observed enthalpy extrapolated at zero buffer Disordered regions ionization enthalpy) in proteins provides are characterized the buffer-independent interaction biasedΔH, by aenthalpy amino and theacid slopecomposition, provides whereΔnresidues H. exhibiting considerable propensity to be exposed to the solvent (polar and charged amino acids) predominate [29]. They may influence protein conformation and function through Biomolecules 2020, 10, 1533 14 of 19 steric effects, or exerting long-distance attractive or repulsive electrostatic interactions due to their highly polar/charged character, or making contacts with other structured regions affecting the global stability and the dynamics of the protein, as well as modulating the interaction with a binding partner. Thus, even lacking a well-defined structure, disordered regions may contribute to the overall stability of the protein, as it happens in MeCP2. Related to that, we have recently reported that: (1) NTD and ID, the two completely disordered MBD-flanking domains significantly increase the thermal stability of MBD [20]; and (2) the two differentially expressed MeCP2 isoforms (E1 and E2) as a result of differential splicing and differing in just a few amino acids at the N-terminal part of the completely disordered NTD, differ in their thermal stability and functional capabilities [30]. Thus, it may be possible that the conformation and/or the dynamics of MBD is altered by presence of the two disordered flanking domains, resulting in a different stability and different affinity toward binding partners. While it is reasonable to expect that the structural and functional impact of point mutations located on structured regions may be predicted with certain reliability, the impact of those located on or close to disordered regions may be more difficult to assess. The two mutations studied in this work, R106W and R133C, are some of the most relevant clinically associated with RTT. They are not located in disordered regions, but in the structured region of the MeCP2 MBD. However, the MBD is very dynamic and susceptible to many environmental factors (pH, temperature, solutes, ligands . . . ), being considered as a key element able to interact with or allosterically regulate the other functional domains [5,18,19]. Both mutations show some similarities and many dissimilarities: (1) both involve the substitution of an arginine residue, but R106W involves the substitution by a bulkier aromatic hydrophobic residue, while R133C involves the substitution by a smaller polar aliphatic residue; (2) R106 is located far from the DNA binding interface, while R133 is located in the DNA binding interface (Figure 7); (3) R106 establishes many interactions with many surrounding residues (in particular, four hydrogen bonding residues: M94, D156, T158, and V159), while R133 interacts with fewer residues (only one hydrogen bonding residue: E137) (Figure 7); and (4) R106 does not interact with DNA, while R133 interacts with DNA through hydrogen bonds and van der Waals contacts (Figure 7). Therefore, the impact of both substitutions is expected to be structurally and functionally different. In fact, if the main rotamers for tryptophan and cysteine are introduced in positions 106 and 133, respectively, all W106 rotamers clash with neighboring residues, while C133 shows no clashes at all, indicating that R106W substitution would result in considerable structural distortion in the vicinity of that position to accommodate such substitution. As indicated above, the purpose of this work was to gain insight into the relationship between the phenotypic effect and the molecular effect of RTT-associated mutations by assessing the impact of two clinically relevant substitutions in MeCP2 MBD. MBD variants containing the two R106W and R133C mutations were studied regarding their structural stability and dsDNA interaction. In addition, because we have reported before an allosteric coupling between MBD and ID, in which the presence of ID dramatically increased the MBD dsDNA binding affinity and contributed an additional dsDNA binding site, we wanted to address whether the location of those mutations on different scaffolds (MBD or NTD-MBD-ID) would result in different structural and/or functional properties. The experimental strategy consisted of a combination of spectroscopic (CD and fluorescence) and calorimetric (ITC), taking advantage of their strengths and overcoming their limitations. Thus, CD and fluorescence are suitable for gathering coarse-grained structural information, and ITC is the gold-standard for determining binding affinity and providing a complete thermodynamic description of biomolecular interactions. In addition, contrary to other techniques, ITC is appropriate for studying biological interactions with more than one binding site, where the interplay between binding affinity and enthalpy makes easy to observe different binding processes occurring at different locations in a macromolecule. with DNA, while R133 interacts with DNA through hydrogen bonds and van der Waals contacts (Figure 7). Therefore, the impact of both substitutions is expected to be structurally and functionally different. In fact, if the main rotamers for tryptophan and cysteine are introduced in positions 106 and 133, respectively, all W106 rotamers clash with neighboring residues, while C133 shows no Biomolecules clashes at 2020, 10, 1533 all, indicating 15 of in that R106W substitution would result in considerable structural distortion 19 the vicinity of that position to accommodate such substitution. Figure 7.7. (a) (a)Structure StructureofofMeCP2 MeCP2 MBDMBD(yellow) (yellow)in complex withwith in complex methylated mCpG-dsDNA methylated mCpG-dsDNA (CPK view) (CPK (pdb view)id:(pdb 3C2I). id:Residues R106 (light 3C2I). Residues R106green spheres) (light green and R133 (dark spheres) green(dark and R133 spheres) arespheres) green shown. Methylated are shown. cytosines Methylated are cytosines shown as pink sticks (b) are shown asClose pinkview sticksof (b) R133 (darkview Close green), of showing the elements R133 (dark establishing green), showing the hydrogen bonds with hydrogen elements establishing that residue: Glu137 bonds with(light green), deoxyguanosine-34 that residue: Glu137 (light green),(CPK view), and two deoxyguanosine-34 water molecules (CPK view), and(red twospheres). Methylated water molecules (redcytosines spheres). are shown incytosines Methylated pink sticks. are(c) Closeinview shown pinkofsticks. R106 (dark green), showing the elements establishing hydrogen bonds with that residue: (c) Close view of R106 (dark green), showing the elements establishing hydrogen bonds with that Met84, Asp156, T158, V159, residue: and Asp156, Met84, two water molecules T158, (redtwo V159, and spheres). water molecules (red spheres). From the results As indicated presented above, here, itof the purpose is this apparent work that wasthe impact to gain of R106W insight andrelationship into the R133C substitutions between on the phenotypic effect and the molecular effect of RTT-associated mutations by assessing thecontext, the structural stability and the dsDNA binding capability depends on the molecular impact i.e., of twotheclinically scaffold (MBD relevantor NTD-MBD-ID) substitutions inin whichMBD. MeCP2 the substitutions MBD variants arecontaining introduced.the Thus, two to highlight R106W and some R133Cof mutations the most important findings: were studied (1) R106W regarding andstructural their R133C substitutions increase stability and dsDNAthe thermal stability interaction. In of MBD, but decrease the thermal stability of NTD-MBD-ID (Figure 8); (2) high addition, because we have reported before an allosteric coupling between MBD and ID, in which the ionic strength induces apresence large stabilization in MBD wild-type of ID dramatically increasedand the mutants MBDR106WdsDNA andbinding R133C, maintaining affinity andthe same stability contributed an ranking, but a minor stabilization could be observed for NTD-MBD-ID variants additional dsDNA binding site, we wanted to address whether the location of those mutations on (Figure 8); (3) R106W induces differentan increase(MBD scaffolds in dsDNA binding affinity or NTD-MBD-ID) in MBD, would resultbut in adifferent decreasestructural in dsDNA binding and/or affinity functional in NTD-MBD-ID, compared to their respective wild-type variants; and properties. The experimental strategy consisted of a combination of spectroscopic (CD and 4) R133C abolishes dsDNA binding in MBD, fluorescence) andbut behaves similar calorimetric (ITC),totaking the wild-type advantage variant in NTD-MBD-ID of their strengths andinovercoming terms of dsDNA their affinity and methyl-dependent discrimination. limitations. Thus, CD and fluorescence are suitable for gathering coarse-grained structural The large information, stabilization and observed in NTD-MBD-ID ITC is the gold-standard for determining R106W binding when bound affinity and to dsDNA acompared providing complete to the small stabilization observed for NTD-MBD-ID R133C, taking wild-type thermodynamic description of biomolecular interactions. In addition, contrary to other techniques, NTD-MBD-ID as a reference, may be considered a largely unexpected result (Tables 2 and 3). The higher dsDNA affinity for the R133C mutant should have induced a larger stabilization extent for that mutant when bound to dsDNA, because the stabilization energy provided by dsDNA binding is equal to +RTln(1+[dsDNA]/Kd ). Thus, the extent of the stabilization effect caused by the presence of dsDNA on protein conformation (quantified as increase in stability energy or increase in Tm ) depends on the dsDNA binding affinity, the binding stoichiometry, and the concentration of dsDNA. But the binding affinity is dependent on temperature, and, as a consequence, it will change along the thermal Biomolecules 2020, 10, 1533 16 of 19 Biomolecules 2020, 10, x 15 of 18 denaturation process. The temperature dependency of the binding affinity will be determined by the dsDNA binding enthalpy (and the binding heat capacity), which might not be the same for each ITC is appropriate for studying biological interactions with more than one binding site, where the interaction (as it occurs for R106W and R133C variants) and will further modulate the overall extent of interplay between binding affinity and enthalpy makes easy to observe different binding processes the ligand-induced stabilization effect. The R106W variant exhibits a strongly endothermic dsDNA occurring at different locations in a macromolecule. binding to the high-affinity site, indicating that, as the temperature starts increasing during the thermal From the results presented here, it is apparent that the impact of R106W and R133C substitutions denaturation process, initially the binding affinity and the strength of the complex would increase on the structural stability and the dsDNA binding capability depends on the molecular context, i.e. (according to the van’t Hoff equation) until a temperature in which the binding enthalpy becomes the scaffold (MBD or NTD-MBD-ID) in which the substitutions are introduced. Thus, to highlight zero (the binding heat capacity is expected to be negative, as found for MBD and NTD-MBD-ID), some of the most important findings: 1) R106W and R133C substitutions increase the thermal stability and then the binding affinity decreases from that temperature. On the contrary, the R133C variant of MBD, but decrease the thermal stability of NTD-MBD-ID (Figure 8); 2) high ionic strength induces exhibits a strongly exothermic dsDNA binding, and the binding affinity and the strength of the a large stabilization in MBD wild-type and mutants R106W and R133C, maintaining the same complex would continuously decrease from the beginning of the thermal denaturation process. stability ranking, but a minor stabilization could be observed for NTD-MBD-ID variants (Figure 8); Therefore, the temperature evolution of Kd would be different for the two mutants and the stabilization 3) R106W induces an increase in dsDNA binding affinity in MBD, but a decrease in dsDNA binding extent would also be different. This is a nice example of two molecules (R106W and R133C variants) affinity in NTD-MBD-ID, compared to their respective wild-type variants; and 4) R133C abolishes binding to a common molecule with different binding affinities, but exerting different stabilization dsDNA binding in MBD, but behaves similar to the wild-type variant in NTD-MBD-ID in terms of effects: the higher affinity interaction is associated with a smaller stabilization effect. dsDNA affinity and methyl-dependent discrimination. Figure 8. Unfolding temperature for MBD and NTD-MBD-ID variants (wild-type, black bars; R106W, Figure gray 8. R133C, bars; Unfolding temperature white forand bars) at low MBD and high NTD-MBD-ID ionic variants strength (NaCl (wild-type, black bars; R106W, 150 mM). gray bars; R133C, white bars) at low and high ionic strength (NaCl 150 mM). There are several intriguing facts derived from the experimental results previously shown here. The large First, how R106W stabilization substitution, observed which is in far NTD-MBD-ID from the dsDNA R106W when bound binding to dsDNA interface, compared could affect dsDNAto the small stabilization observed for NTD-MBD-ID R133C, taking wild-type binding and increase its affinity? Of course, even located far from the dsDNA binding interface, NTD-MBD-ID as a reference, the may be considered large structural rearrangementsa largely unexpected resulting result (Tables from R106W 2 and could substitution 3). Thevery higher dsDNA likely affinity propagated tofor the R133C distal regionsmutant in MBD should thanks have induced to its intrinsica larger stabilization structural plasticity.extent for how Second, that mutant when bound R133C substitution oftoa main dsDNA, playerbecause the stabilization in the dsDNA interaction energy provided would result by dsDNA in abolishment binding is of interaction for equal isolatedto +RTln(1+[dsDNA]/K MBD, but almost no effect d). Thus, the extent of And in NTD-MBD-ID. the stabilization third, how these effectmolecular caused by the presence findings can be of dsDNA related to on protein conformation (quantified as increase in stability energy or increase the phenotypic outcomes associated with those mutations: What is the final consequence of R106W in T m ) depends on the dsDNA binding substitution affinity,level? at molecular the binding Is R106Wstoichiometry, substitutionand the concentration interfering of dsDNA.of with the interaction But the binding MeCP2 with affinity other is dependent biological partnerson temperature, through and,residues the surface as a consequence, around R106?itWhat will is change along the final the thermal consequence of denaturation process. The temperature dependency of the binding affinity R133C substitution at molecular level? Is R133C substitution causing an overlooked rearrangement will be determined by the dsDNA that binding interferes with enthalpy (and the binding other interactions? heat capacity), According whichclassification to the current might not beofthe RTTsame for each mutations, R106W is associated to a severe phenotype, whereas R133C is associated to a mild phenotypeextent interaction (as it occurs for R106W and R133C variants) and will further modulate the overall [31]. of the ligand-induced Interestingly, stabilization from the evidence effect.in gathered The R106W this work,variant we expect exhibits a strongly larger functionalendothermic alterations dsDNA due to binding R106W to the high-affinity site, indicating that, as the temperature starts increasing during the substitution. thermal denaturation process, initially the binding affinity and the strength of the complex would 5.increase Conclusions (according to the van’t Hoff equation) until a temperature in which the binding enthalpy becomes MeCP2 zero is a(the binding potential heat capacity isprotein pharmacological expected to be target negative,with associated as found for MBD RTT (caused by and NTD- defective MBD-ID), and then the binding affinity decreases from that temperature. MeCP2 activity) and MDS (caused by excess of MeCP2 activity), two neurological disorders with On the contrary, the R133C variant exhibits a strongly exothermic dsDNA binding, and the binding affinity and the strength of the complex would continuously decrease from the beginning of the thermal denaturation process. Therefore, the temperature evolution of Kd would be different for the two mutants and the stabilization extent would also be different. This is a nice example of two molecules (R106W and Biomolecules 2020, 10, 1533 17 of 19 similar phenotypic features. MeCP2 is mainly involved in neuronal development and maturation, and synaptic plasticity. While the in vivo effect of MeCP2 duplication is still difficult to explain and correlate with cellular events, the in vivo effect of RTT-associated mutations and their connection with molecular and cellular events may be even more challenging. A valuable strategy consists of gathering experimental evidence on the structural and functional impact of those RTT-associated mutations. Isolated MBD, full-length MeCP2, or other constructs have been previously employed as the protein scaffolds for studying those mutations. Because different MeCP2 constructs may behave differently [20,30], a different impact from RTT-associated substitutions might also be expected depending on the molecular context or protein scaffold in which they are introduced. We have provided here evidence for such phenomenon involving R106W and R133C substitutions. This finding underscores the importance of selecting an appropriate protein construction when assessing the effect of a given mutation, being even more important for intrinsically disordered proteins. Each MeCP2 mutation associated to RTT may cause different perturbations on protein structure, stability and functionality, depending on the disrupted intra- e intermolecular interactions. The environment of the mutation is crucial and strongly influences the potential deleterious impact caused on MeCP2 functionality, thus modulating MeCP2 ability to interact with dsDNA (binding affinity and methyl-dependent discrimination) or other biological partners (RNA and proteins), and further conditioning the ability to undergo functionally-related posttranslational modifications. Mutations can also produce detrimental effects in regions located far apart from them through allosteric coupling. In fact, the ID binding site was fairly compromised in terms of affinity by MBD mutations (Table 4), revealing that the MBD protein structure might be indispensable for ID-dsDNA interaction. Thus, the R106W substitution in NTD-MBD-ID not only affected the MBD interaction site, but its influence was extended to the ID interaction site, causing a non-negligible reduction in binding affinity. Supplementary Materials: The following are available online at http://www.mdpi.com/2218-273X/10/11/ 1533/s1, Figure S1: Domain structure of MeCP2, Figure S2: Calorimetric titration of MBD R133C with methylated mCpG-dsDNA. Author Contributions: Conceptualization, M.E., O.A. and A.V.-C.; methodology, O.A. and A.V.-C.; software, O.A. and A.V.-C.; validation, D.O.-A., R.C.-G., S.V., O.C.J.-T., M.E., O.A. and A.V.-C.; formal analysis, D.O.-A., R.C.-G., S.V., O.C.J.-T., M.E., O.A. and A.V.-C.; investigation, D.O.-A., R.C.-G., S.V. and O.C.J.-T.; resources, M.E., O.A. and A.V.-C.; data curation, D.O.-A. and R.C.-G.; writing—original draft preparation, O.A. and A.V.-C.; writing—review and editing, D.O.-A., R.C.-G., S.V., O.C.J.-T., M.E., O.A. and A.V.-C.; visualization, D.O.-A., R.C.-G., S.V., O.C.J.-T., M.E., O.A. and A.V.-C.; supervision, M.E., O.A. and A.V.-C.; project administration, O.A. and A.V.-C.; funding acquisition, O.A: and A.V.-C. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the Spanish Ministry of Economy and Competitiveness and European ERDF Funds (MCIU/AEI/FEDER, EU) (BFU2016-78232-P to A.V.C.; BES-2017-080739 to D.O.A.); Miguel Servet Program from Instituto de Salud Carlos III (CPII13/00017 to O.A.); Fondo de Investigaciones Sanitarias from Instituto de Salud Carlos III and European Union (ERDF/ESF, “Investing in your future”) (PI15/00663 and PI18/00349 to O.A.); Diputación General de Aragón (Protein Targets and Bioactive Compounds Group E45_17R to A.V.C. and Digestive Pathology Group B25_17R to O.A.); and the Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas (CIBERehd). Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. References 1. Ausio, J.; de Martínez Paz, A.; Esteller, M. MeCP2: The long trip from a chromatin protein to neurological disorders. Trends Mol. Med. 2014, 20, 487–498. [PubMed] 2. Tillotson, R.; Bird, A. The Molecular Basis of MeCP2 Function in the Brain. J. Mol. Biol. 2020, 432, 1602–1623. [CrossRef] 3. Adkins, N.L.; Georgel, P.T. MeCP2: Structure and function. Biochem. Cell Biol. 2011, 89, 1–11. [CrossRef] [PubMed] Biomolecules 2020, 10, 1533 18 of 19 4. Nan, X.; Campoy, F.; Bird, A. MeCP2 Is a Transcriptional Repressor with Abundant Binding Sites in Genomic Chromatin. Cell 1997, 88, 471–481. [CrossRef] [PubMed] 5. Hansen, J.C.; Ghosh, R.P.; Woodcock, C.L. Binding of the Rett syndrome protein, MeCP2, to methylated and unmethylated DNA and chromatin. IUBMB Life 2010, 62, 732–738. [CrossRef] 6. Guy, J.; Cheval, H.; Selfridge, J.; Bird, A. The Role of MeCP2 in the Brain. Annu. Rev. Cell Dev. Biol. 2011, 27, 631–652. [CrossRef] 7. Claveria-Gimeno, R.; Abian, O.; Velazquez-Campoy, A.; Ausio, J. MeCP2 . . . Nature’s wonder protein or medicine’s most feared one? Curr. Genet. Med. Rep. 2016, 4, 180–194. 8. Amir, R.E.; Veyver, I.B.V.D.; Wan, M.; Tran, C.Q.; Francke, U.; Zoghbi, H.Y. Rett syndrome is caused by mutations in X-linked MECP2, encoding methyl-CpG-binding protein 2. Nat. Genet. 1999, 23, 185–188. [CrossRef] 9. Neul, J.L. The relationship of Rett syndrome and MECP2 disorders to autism. Dialog. Clin. Neurosci. 2012, 14, 253–262. 10. Hite, K.C.; Adams, V.H.; Hansen, J.C. Recent advances in MeCP2 structure and function. Biochem. Cell Biol. 2009, 87, 219–227. [CrossRef] 11. Kokura, K.; Kaul, S.C.; Wadhwa, R.; Nomura, T.; Khan, M.; Shinagawa, T.; Yasukawa, T.; Colmenares, C.; Ishii, S. The Ski Protein Family Is Required for MeCP2-mediated Transcriptional Repression. J. Biol. Chem. 2001, 276, 34115–34121. [CrossRef] [PubMed] 12. Nan, X.; Meehan, R.R.; Bird, A. Dissection of the methyl-CpG binding domain from the chromosomal protein MeCP2. Nucleic Acids Res. 1993, 21, 4886–4892. [CrossRef] [PubMed] 13. Hall, J.A.; Georgel, P.T. CHD proteins: A diverse family with strong ties. Biochem. Cell Biol. 2007, 85, 463–476. [CrossRef] [PubMed] 14. Shah, R.R.; Bird, A.P. MeCP2 mutations: Progress towards understanding and treating Rett syndrome. Genome Med. 2017, 9, 1–4. [CrossRef] 15. Kyle, S.M.; Vashi, N.; Justice, M.J. Rett syndrome: A neurological disorder with metabolic components. Open Biol. 2018, 8, 170216. [CrossRef] 16. Brown, K.; Selfridge, J.; Lagger, S.; Connelly, J.; De Sousa, D.; Kerr, A.; Webb, S.; Guy, J.; Merusi, C.; Koerner, M.V.; et al. The molecular basis of variable phenotypic severity among common missense mutations causing Rett syndrome. Hum. Mol. Genet. 2016, 25, 558–570. [CrossRef] 17. Neul, J.L.; Fang, P.; Barrish, J.; Lane, J.; Caeg, E.B.; Smith, E.O.; Zoghbi, H.Y.; Percy, A.; Glaze, D.G. Specific mutations in methyl-CpG-binding protein 2 confer different severity in Rett syndrome. Neurology 2008, 70, 1313–1321. [CrossRef] 18. Ghosh, R.P.; Horowitz-Scherer, R.A.; Nikitina, T.; Gierasch, L.M.; Woodcock, C.L. Rett Syndrome-causing Mutations in Human MeCP2 Result in Diverse Structural Changes That Impact Folding and DNA Interactions. J. Biol. Chem. 2008, 283, 20523–20534. [CrossRef] 19. Ghosh, R.P.; Nikitina, T.; Horowitz-Scherer, R.A.; Gierasch, L.M.; Uversky, V.N.; Hite, K.; Hansen, J.C.; Woodcock, C.L. Unique Physical Properties and Interactions of the Domains of Methylated DNA Binding Protein 2. Biochemistry 2010, 49, 4395–4410. [CrossRef] 20. Clavería-Gimeno, R.; Lanuza, P.M.; Morales-Chueca, I.; Torres, O.D.L.C.J.; Vega, S.; Abian, O.; Esteller, M.; Velazquez-Campoy, A. The intervening domain from MeCP2 enhances the DNA affinity of the methyl binding domain and provides an independent DNA interaction site. Sci. Rep. 2017, 7, 41635. [CrossRef] 21. Vega, S.; Abian, O.; Velazquez-Campoy, A. A unified framework based on the binding polynomial for characterizing biological systems by isothermal titration calorimetry. Methods 2015, 76, 99–115. [CrossRef] [PubMed] 22. Freire, E.; Schön, A.; Velazquez-Campoy, A. Chapter 5 Isothermal Titration Calorimetry. Methods Enzymol. 2009, 455, 127–155. [CrossRef] [PubMed] 23. Eftink, M.; Biltonen, R.L. Thermodynamics of interacting biological systems. In Biological Microcalorimetry; Beezer, A.E., Ed.; Academic Press: London, UK, 1980; pp. 343–412. 24. Hinz, H.J.; Shiao, D.D.F.; Sturtevant, J.M. Calorimetric investigation of inhibitor binding to rabbit muscle aldolase. Biochemistry 1971, 10, 1347–1352. [CrossRef] [PubMed] 25. Gómez, J.; Freire, E. Thermodynamic Mapping of the Inhibitor Site of the Aspartic Protease Endothiapepsin. J. Mol. Biol. 1995, 252, 337–350. [CrossRef] Biomolecules 2020, 10, 1533 19 of 19 26. Goldberg, R.N.; Kishore, N.; Lennen, R.M. Thermodynamic Quantities for the Ionization Reactions of Buffers. J. Phys. Chem. Ref. Data 2002, 31, 231–370. [CrossRef] 27. Wyman, J. Linked Functions and Reciprocal Effects in Hemoglobin: A Second Look. Adv. Protein Chem. 1964, 19, 223–286. [CrossRef] 28. Vuilleumier, S.; Sancho, J.; Loewenthal, R.; Fersht, A.R. Circular dichroism studies of barnase and its mutants: Characterization of the contribution of aromatic side chains. Biochemistry 1993, 32, 10303–10313. [CrossRef] 29. Uversky, V.N. Unusual biophysics of intrinsically disordered proteins. Biochim. Biophys. Acta Proteins Proteom. 2013, 1834, 932–951. [CrossRef] 30. De Paz, A.M.; Khajavi, L.; Martin, H.; Claveria-Gimeno, R.; Dieck, S.T.; Cheema, M.S.; Sanchez-Mut, J.V.; Moksa, M.M.; Carles, A.; Brodie, N.I.; et al. MeCP2-E1 isoform is a dynamically expressed, weakly DNA-bound protein with different protein and DNA interactions compared to MeCP2-E2. Epigenetics Chromatin 2019, 12, 1–16. [CrossRef] 31. Cuddapah, V.A.; Pillai, R.B.; Shekar, K.V.; Lane, J.B.; Motil, K.J.; Skinner, S.A.; Tarquinio, D.C.; Glaze, D.G.; McGwin, G.; Kaufmann, W.E.; et al. Methyl-CpG-binding protein 2 (MECP2) mutation type is associated with disease severity in Rett syndrome. J. Med. Genet. 2014, 51, 152–158. [CrossRef] Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).