Journal of Enzyme Inhibition and Medicinal Chemistry ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/ienz20 Rational design of small molecules able to inhibit α-synuclein amyloid aggregation for the treatment of Parkinson’s disease Serena Vittorio , Ilenia Adornato , Rosaria Gitto , Samuel Peña-Díaz , Salvador Ventura & Laura De Luca To cite this article: Serena Vittorio , Ilenia Adornato , Rosaria Gitto , Samuel Peña-Díaz , Salvador Ventura & Laura De Luca (2020) Rational design of small molecules able to inhibit α-synuclein amyloid aggregation for the treatment of Parkinson’s disease, Journal of Enzyme Inhibition and Medicinal Chemistry, 35:1, 1727-1735, DOI: 10.1080/14756366.2020.1816999 To link to this article: https://doi.org/10.1080/14756366.2020.1816999 © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Published online: 14 Sep 2020. Submit your article to this journal Article views: 561 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=ienz20 JOURNAL OF ENZYME INHIBITION AND MEDICINAL CHEMISTRY 2020, VOL. 35, NO. 1, 1727–1735 https://doi.org/10.1080/14756366.2020.1816999 RESEARCH PAPER Rational design of small molecules able to inhibit a-synuclein amyloid aggregation for the treatment of Parkinson’s disease Serena Vittorioa , Ilenia Adornatoa, Rosaria Gittoa ~a-Dıazb,c, Salvador Venturab,c,d and , Samuel Pen Laura De Lucaa a Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, University of Messina Viale Palatucci, Messina, Italy; bInstitut de Biotecnologia i Biomedicina, Universitat Autonoma de Barcelona, Spain; cDepartament de Bioquimica i Biologia Molecular, Universitat Autonoma de Barcelona, Spain; dICREA, Passeig Lluis Companys 23, Barcelona, Spain ABSTRACT ARTICLE HISTORY Parkinson’s disease is one of the most common neurodegenerative disorders in elderly age. One of the Received 7 July 2020 mechanisms involved in the neurodegeneration appears related to the aggregation of the presynaptic Revised 20 August 2020 protein alpha synuclein (a-syn) into toxic oligomers and fibrils. To date, no highly effective treatment is Accepted 21 August 2020 currently available; therefore, there is an increasing interest in the search of new therapeutic tools. The KEYWORDS modulation of a-syn aggregation represents an emergent and promising disease-modifying strategy for Parkinson’s disease; alpha- reducing or blocking the neurodegenerative process. Herein, by combining in silico and in vitro screenings synuclein; ligand-based we initially identified 3-(cinnamylsulfanyl)-5-(4-pyridinyl)-1,2,4-triazol-4-amine (3) as a-syn aggregation pharmacophore; aggrega- inhibitor that was then considered a promising hit for the further design of a new series of small mole- tion inhibitors; cules. Therefore, we rationally designed new hit-derivatives that were synthesised and evaluated by bio- docking studies logical assays. Lastly, the binding mode of the newer inhibitors was predicted by docking studies. GRAPHICAL ABSTRACT 1. Introduction the central NAC domain (aa 61-95) and the C-terminal domain (aa 96-140)6. In its monomeric soluble form, a-syn assumes an alpha Parkinson’s disease (PD) is a neurodegenerative disorder character- helical conformation upon interaction with phospholipids,7 while ised by the loss of dopaminergic neurons in the substantia nigra of the brain. These cells are involved in the production of the in the pathological misfolded state, it aggregates into amyloid neurotransmitter dopamine which regulates the muscular move- fibrils composed by parallel hydrogen bonded b-sheets8,9. The for- ments1. Typical manifestations of PD include motor symptoms mation of these aggregates causes cytotoxicity through lipid due to the dopaminergic loss, like bradykinesia, rigidity, postural membrane permeabilisation, mitochondrial damage and oxidative instability and rest tremor2. Additionally, non-motor features such stress10. Another relevant mechanism that contributes to the as olfactory dysfunction, constipation, cognitive impairments, propagation of neurodegeneration is the prion-like spread of depression and sleep disorders can occur; these further symptoms a-syn aggregates. Indeed, experimental studies revealed that the are due to the implication of the neurodegenerative process in injection of a-syn inclusions in animal’s brain promotes the forma- other areas of the peripheral and central nervous system3. The tion of cellular inclusions at the injection site from where they can hallmark of PD is represented by the presence of neuronal inclu- spread in other brain regions11. To date, the therapies available sions, termed Lewis Bodies, mainly composed of aggregates of for the treatment of PD are addressed to reduce the motor symp- misfolded alpha synuclein (a-syn)4. a-Syn is a 140 aa presynaptic toms and include the administration of drugs able to restore the protein which regulates the release of neurotransmitters from the level of dopamine. Among them the most used is L-Dopa, which synaptic vesicles5. From a structural point of view, a-syn is organ- acts as a prodrug being converted in dopamine in the brain1,12. ised in three different regions: the N-terminal domain (aa 1-60), Other dopaminergic drugs used for the treatment of PD are CONTACT Serena Vittorio serena.vittorio@unime.it; Laura De Luca laura.deluca@unime.it Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, University of Messina Viale Palatucci, 13, I-98168, Messina, Italy ß 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1728 S. VITTORIO ET AL. dopamine agonists like ropinirole or rotigotine, monoamine oxi- mixture was stirred for 15 min at room temperature for desired dase B (MAO-B) inhibitors such as rasagiline and selegiline and compounds 5 and 7–11, whereas for desired compound 6 the catechol-O-methyltransferase (COMT) inhibitors such as tolcapone reaction time was 120 min. The resulting solid residue was washed and entacapone which inhibit the enzymes responsible of dopa- with water, dried and recrystallized from ethanol to provide pure mine metabolism2,13. Unfortunately, the use of these drugs indu- desired final pyridyl-triazole derivatives 5–11. For all synthesised ces unwanted side effects such as dyskinesia, dizziness, compounds the registered CAS numbers have been already headaches, nausea and somnolence13. More serious problems like assigned; However, the synthetic procedure, chemical and struc- hallucinations, confusion and impulse control disorders are often tural characterisation are not available in literature with exception associated with the assumption of dopamine agonists14. of compound 5, for which the structural characterisation is an Furthermore, these therapies lose their efficacy as the disease pro- agreement with literature22. gresses and are unable to block or reduce the neurodegenerative process15,16. In the last decade, several efforts have been made to 2.2.3.1. 3-(Phenethylthio)-5-(pyridin-4-yl)-4H-1,2,4-triazol-4-amine find a disease modifying strategy to halt or slow the neurodegen- (6). CAS number: 691366-30-0. Yield 12%. Yellow solid. M.p. eration17. In this context, the inhibition of a-syn aggregation by 168–169  C. 1H NMR (DMSO-d6): d 3.04 (t, 2H, J ¼ 7.74 Hz, CH2); small molecules proved to be a valid approach for the develop- 3.44 (t, 2H, J ¼ 7.74 Hz, CH2); 6.19 (s, 2H, NH2); 7.21–8.72 (m, 9H, ment of new therapeutics for the treatment of PD and several ArH) Anal. for C15H15N5S: C, 60.58%; H, 5.08%; N, 23.55%. Found C, inhibitors have been discovered through high-throughput screen- 60.48%; H, 5.33%; N, 23.43%. ing campaigns and drug repositioning18,19. In this work, we applied a pharmacophore-based virtual screen- ing approach as effective tool to discover novel a-syn aggregation 2.2.3.2. 3-((4-Fluorobenzyl)thio)-5-(pyridin-4-yl)-4H-1,2,4-triazol-4- inhibitors. Firstly, we developed a computational model that was amine (7). CAS number: 575460-68-3. Yield 39%. Yellow solid. subsequently combined with in vitro experiments to test their M.p. 186–187  C. 1H NMR (DMSO-d6): d 4.44 (s, 2H, CH2); 6.21 (s, ability to reduce a-syn aggregation; as result we discovered a 2H, NH2); 7.13–8.71 (m, 8H, ArH). 13C NMR (DMSO-d6): d 34.0; small molecule as promising inhibitor, which was used as lead 115.1 (d, 2JC-F ¼ 19.1 Hz), 115.3 (d, 2JC-F ¼ 19.1 Hz); 121.2; 121.3; compound for the development of a further series of compounds. 131.0 (d, 3JC-F ¼ 8.6 Hz); 131.1 (d, 3JC-F ¼ 8.6 Hz); 133.8 (d, 4JC- Then, the designed molecules were synthesised, tested in vitro F ¼ 2.9 Hz) 134.0; 150.1; 152.0; 154.5; 161.4 (d, 1 JC-F ¼ 243.2 Hz). and studied to decipher the putative binding mode by molecular Anal. for C14H12FN5S: C, 55.80%; H, 4.01%; N, 23.24%. Found C, docking simulation. 55.68%; H, 4.31%; N, 23.44%. 2.2.3.3. 3-((3-Fluorobenzyl)thio)-5-(pyridin-4-yl)-4H-1,2,4-triazol–4- 2. Materials and Methods amine (8). CAS number: 674812-86-3. Yield 52%. Yellow solid. 2.1. Pharmacophore modelling and virtual screening M.p. 164–165  C. 1H NMR (DMSO-d6): d 4.45 (s, 2H, CH2); 6.25 (s, LigandScout V4.420 was used for the pharmacophore generation 2H, NH2); 7.06–8.72 (m, 8H, ArH); 13C NMR (DMSO-d6): d 34.6; and the virtual screening experiments. Three small molecules able 114.6 (d, 2JC-F ¼ 20.9 Hz), 116.3 (d, 2JC-F ¼ 21.0 Hz); 121.7; 121.8; to bind to the N-terminal region of a-syn have been selected from 125.6 (d, 4JC-F ¼ 2.7 Hz); 130.8 (d, 3JC-F ¼ 8.2 Hz); 134.4, 141.0 (d, 3JC- F ¼ 8.2 Hz); 150.5; 152.5; 154.8; 162.4 (d, JC-F ¼ 243.4 Hz). Anal. for 1 literature21 and used as training set. A shared-feature pharmaco- phore model was created applying the default settings. C14H12FN5S: C, 55.80%; H, 4.01%; N, 23.24%. Found C, 55.89%; H, All virtual screening runs were performed by setting the option 4.00%; N, 23.15%. “Get best matching conformation” as retrieval mode. 2.2.3.4. 3-((4-Methylbenzyl)thio)-5-(pyridin-4-yl)-4H-1,2,4-triazol-4- amine (9). CAS number: 676147-32-3. Yield 13%. Yellow solid. 2.2. Chemistry M.p. 180–181  C 1H NMR (DMSO-d6): d 2.25 (s, 3H, CH3); 4.40 (s, All reagents were used without further purification and bought 2H, CH2); 6.19 (s, 2H, NH2); 7.10–8.71 (m, 8H, ArH). 13C NMR from common commercial suppliers. Melting points were deter- (DMSO-d6): d 21.0; 35.2; 110.0; 121.7; 121.8; 129.3; 129.6 134.4; mined on a Buchi B-545 apparatus (BUCHILabortechnik AG Flawil, 134.7; 137.1; 141.0; 150.4; 150.7; 152.4; 155.1. Anal. for C15H15N5S: Switzerland). By combustion analysis (C, H, N) carried out on a C, 60.58%; H, 5.08%; N, 23.55%. Found C, 60.23%; H, 5.26%; Carlo Erba Model1106-Elemental Analyser we determined the pur- N, 23.40%. ity of synthesised compounds; the results confirmed a ± 95% pur- ity. Merck Silica Gel 60 F254 plates were used for analytical TLC 2.2.3.5. 3-((3-Methylbenzyl)thio)-5-(pyridin-4-yl)-4H-1,2,4-triazol-4- (Merck KGaA, Darmstadt, Germany). For detection, iodine vapour amine (10). CAS number: 676548-28-0. Yield 16%. Whitish solid. and UV light (254 nm) were used. 1H and 13C NMR spectra were M.p 175–176  C; 1H NMR (DMSO-d6): d 2.26 (s, 3H, CH3); 4.40 (s, measured in dimethylsulfoxide-d6 (DMSO-d6) with a Varian 2H, CH2); 6.19 (s, 2H, NH2); 7.07–8.71 (m, 8H, ArH). 13C NMR Gemini 500 spectrometer (Varian Inc. Palo Alto, California USA); (DMSO-d6): d 21.3; 35.4; 121.7; 126.7; 128.5; 128.8; 130.0; 134.4; chemical shifts are expressed in d (ppm). 137.6; 138.0; 150.6; 152.4; 155.1. Anal. for C15H15N5S: C, 60.58%; H, 5.08%; N, 23.55%. Found C, 60.70%; H, 5.01%; N, 23.32%. 2.2.3. General procedure for the synthesis of pyridinyl-triazole derivatives 5-11 2.2.3.6. 3-((4-Chlorobenzyl)thio)-5-(pyridin-4-yl)-4H-1,2,4-triazol–4- The 4-amino-5–(4-pyridinyl)-4H-1,2,4-triazole-3-thiol 12 (200 mg, amine (11). CAS number: 901093-20-7. Yield 39%. Yellow solid. 1,03 mmol) was dissolved in a mixture of NaOH (41 mg, 1,03 mmol) M.p 198–199  C; 1H NMR (DMSO-d6): d 4.44 (s, 2H, CH2); 6.22 (s, and MeOH (5 ml); after complete dissolution, the suitable benzyl 2H, NH2); 7.37–8.70 (m, 8H, ArH). 13C NMR (DMSO-d6): d 34.4; bromide derivative (194,7 mg, 1,03 mmol) was added. The reaction 121.7; 121.8; 128.61; 129.0; 131.2; 131.5; 132.4; 134.4; 137.2; 150.4; JOURNAL OF ENZYME INHIBITION AND MEDICINAL CHEMISTRY 1729 150.7; 152.5; 154.8. Anal. for C14H12ClN5S: C, 52.91%; H, 3.81%; N, 10 protein  ligand binding poses for each compound by using 23.04%. Found C, 52.66%; H, 3.78%; N, 23.36%. the default settings. The highest scored docking pose was chosen for analysis and representation. PyMOL software was used to visualise docking results while the analysis of the putative 2.2. 2.3. Alpha synuclein aggregation and inhibition ligand–protein interactions was performed by Discovery Studio in vitro assays Visualiser27. WT a-Syn was expressed and purified as previously described23. The resultant protein was kept lyophilised at 80  C. Lyophilised protein was delicately resuspended in sterile PBS 1X and filtered 3. Results and discussion through 0.22-mm membrane to eliminate small aggregates. 3.1. Pharmacophore model generation, virtual screening and Aggregation assays were performed as previously described for preliminary biological assay ZPD-2 and SynuClean-D, the latter used as reference compound for kinetic studies16,24. Briefly, 70 mM of a-Syn, in a final volume of With the aim to find new molecules able to inhibit a-syn aggrega- 150 mL, was placed in a sealed 96-well plate, which also contains tion, we used a computational approach to generate a ligand- 40 lM Th-T in PBS 1X, a 1/8” diameter Teflon polyball (Polysciences based pharmacophore model by means of the software Europe GmbH, Eppelheim, Germany) and 100 lM of the different LigandScout20. compounds or DMSO (in control samples). The plates were fixed To build the model, we used a training set (TS) including a-syn in an orbital shaker Max-Q 4000 (ThermoScientific, Waltham, aggregation inhibitors that target the N-terminal portion of the Massachusetts, USA) and incubated at 37  C and 100 rpm. Th-T protein. Specifically, we selected three small molecules from litera- fluorescence emission was measured every 2 h in a Victor3.0 ture21 belonging to different chemotypes as polyphenolic and Multilabel Reader (PerkinElmer, Waltham, Massachusetts, USA) by non-polyphenolic inhibitors (Table 1) for which the binding inter- exciting through a 430–450 nm filter and collecting with a 480- action to N-terminal portion of a-syn is corroborated by experi- 510 filter. Triplicates were performed and the kinetics were fitted mental data. with the following equation: In particular, we considered only the common features for all 1 the selected molecules of the TS for the model construction gen- /¼ 1  (1) erating shared feature pharmacophore models. kb e  1Þ þ 1 ð k a t As result, we obtained ten pharmacophore hypotheses and In which kb and ka represent the homogeneous nucleation rate selected the hypothesis possessing the highest score to perform constant and the secondary rate constant (it means, fibril elong- virtual screening studies. As displayed in Figure 1, the above-men- ation and secondary nucleation), respectively25. tioned pharmacophore model consisted of five features: (i) two Light-scattering measurements were performed in a Cary hydrogen bond acceptors, (ii) two hydrophobic features, (iii) one Eclipse Fluorescence Spectrophotometer (Agilent, Santa Clara, aromatic feature and 45 excluded volumes as forbidden areas. California, USA). 80 mL of end-point aggregates was placed into a  quartz cuvette and excited at 300 nm, the 90 emission was thus collected between 280 and 360 nm. For transmission electron microscopy (TEM) assays, endpoint Table 1. Chemical structures of the a-syn aggregation inhibitors used as train- treated and untreated aggregates diluted 1:10 in PBS 1X. Samples ing set (TS). were then softly sonicated for 5 min and 5 mL of the resultant mix- NAME STRUCTURE ture were placed on a carbon-coated copper grid for 5 min. The grids were dried with filter paper to remove the excess and washed twice in miliQ water, whose excess was also removed. Finally, 5 lL of 2% (w/v) uranyl acetate solution was added and left incubate for 2 min. As previously, the excess of uranyl acetate was removed, and grids were left to air-dry for 10 min. Images Congo Red were obtained using a Transmission Electron Microscopy Jeol 1400 (Peabody, Massachusetts, USA) operating at an accelerating voltage of 120 kV. A minimum of 30 fields were screened per sam- ple, in order to collect representative images. 2.4. Docking studies Docking studies were performed by Autodock4.2 software by Lacmoid using the solid-state NMR of alpha-synuclein fibrils retrieved from RCSB Protein Data Bank (PDB code 2N0A). The structure is charac- terised by a central part with a greek-key topology and terminal flexible loops. A grid box with dimension of 126  126  126 Å3 and centre x ¼ 97.487, y ¼ 148.695 and z ¼ 34,111, was applied in order to include the aminoacid residues of the N-terminal Rosmarinic region discarding the ones present in the unstructured flexible Acid loops. Ligand structures were constructed by Vega ZZ software and energy minimised by following a conjugate gradient mini- misation by AMMP calculation as implemented in VEGAZZ pro- gram26. The Lamarckian Genetic Algorithm was used to calculate 1730 S. VITTORIO ET AL. Figure 1. (A) Best scored ligand-based pharmacophore model constituted by two hydrogen bond acceptors (red spheres), two hydrophobic features (yellow spheres), one aromatic feature (blue circle). Forty-five excluded volumes are represented by grey spheres. (B) TS molecules aligned with the highest scored pharmaco- phore model. Figure 2. (A) Chemical structure of compounds 1a-c. (B) Compound 1a aligned to the pharmacophore model. Compound 1a is represented by grey sticks. The obtained pharmacophore model was used as a query to yl)ethenone (1a) displaying the highest pharmacophore fit-score screen two three-dimensional databases containing small mole- as representative inhibitor filtered through virtual screening on cules belonging to different structural chemotypes: (i) the in-house CHIME database (Figure 2(B)). 3 D database CHIME collecting 1329 molecules designed and syn- The virtual screening on MyriaScreen Diversity Library II thesised by our group over the years, (ii) the MyriaScreen resulted in 113 hits (see supporting material). Among them, we Diversity Library II, consisting of 10,000 compounds with druglike selected three compounds (Figure 3.) such as 3-[5-[(4-methoxy- properties (https://www.sigmaaldrich.com/chemistry/chemistry- phenyl)methylsulfanyl]-4-methyl-1,2,4-triazol-3-yl]pyridine (2), 3- services/high-throughput-screening/screening-compounds.html). (cinnamylsulfanyl)-5–(4-pyridinyl)-1,2,4-triazol-4-amine (3) and From CHIME, the virtual screening led to the identification of 3-(3-chloro-4-fluoro-anilino)-1-(2-naphthyl)propan-1-one (4); the three hits 1a–c (Figure 2(A)). Considering that these molecules selection of the compounds 2–4 was made basing on the shared a very similar structure, we decided to select only 2-[4-[(4- pharmacophore-fit score value (>57) and the commercial avail- fluorophenyl)methyl]-1-piperidyl]-1-(6-methoxy-1H-indol-3- ability from the supplier. JOURNAL OF ENZYME INHIBITION AND MEDICINAL CHEMISTRY 1731 All selected compounds 1–4 proved to respect the Lipinski’s Therefore, this first screening highlighted that the best in vitro rule and no PAINS were in silico predicted by the online tool results were obtained for compound 3. This compound is charac- SwissAdme platform [http://www.swissadme.ch/]. To evaluate the terised by the presence of a pyridinyl-triazole moiety similarly to ability to inhibit a-syn aggregation, we have got compounds 1–4 compound 2, in which the nitrogen of the triazole ring presents a as follows. Compound 1 was readily synthesised in our laboratory methyl substituent while an amino group is present in compound following a previously optimised synthetic approach;28 while the 3 in the same position. Considering the obtained results, we can three commercially available compounds 2–4 were purchased speculate that the amino group could establish fundamental inter- from Sigma Aldrich as supplier of bioactive molecules [https:// action with the protein important for the inhibition of a-syn www.sigmaaldrich.com/italy.html]. aggregation. The anti-aggregation potential of selected compounds (1–4) was evaluated by a robust protocol previously applied in the iden- tification of strong inhibitors of a-syn aggregation16,24 like SynuClean-D, a well-known inhibitor of a-synuclein (a-Syn) aggre- gation24 that was used as reference compound in the same test. 3.2. Design and synthesis of new small molecules as derivatives The presence of 100 mM of the compounds during the incubation of compound 3 of 70 mM of a-Syn, reduced Thioflavin-T (Th-T) fluorescence emis- Based on the above reported results of biological screening, we sion up to a 10, 26, 31 and 10% for compound 1, compound 2, chose compound 3 as promising lead compound for the rational compound 3 and compound 4, respectively. As result, all tested design of a further series of pyridinyl-triazole derivatives 5–11 compounds impacted the kinetic constants (see Figure 4(A)). (Scheme 1) for which a very simple synthetic approach might be Particularly, the compound 2 reduced the homogeneous nucle- carried out. ation rate constant (kb ¼ 0.01591) when compared to untreated In particular, we chose to maintain the pyridinyl-triazole moiety sample (kb ¼ 0.03234). In contrast, compound 3 reduced the auto- of inhibitor 3 and reduce the length of the linker between the sul- catalytic rate constant (ka ¼ 0.1892 h1), compared to the control phur atom and the phenyl ring. Moreover, we planned to extend (ka ¼ 0.2037 h1). The compounds 1 and 4 did not impact signifi- cantly the aggregation rate constants. To confirm these results the series by introducing selected substituents in meta and in light-scattering measurements at 300 nm were performed at the para positions of phenyl ring. In detail, we introduced F, Cl or CH3 end-point of the reaction, thus revealing a reduction of 13 and substituents in order to preliminary probe the influence of elec- 43% of aggregates in the presence of compounds 2 and 3, tron withdrawing group (EWG) or electron donating group (EDG) respectively. on the aggregation of a-syn. For each designed derivative we To further assess the impact of the best candidate 3 on a-syn evaluated the adherence to the Lipinski’s rule and the absence of aggregation, end-point samples were analysed by transmission PAINS in silico by using SwissADME. Scheme 2 shows the syn- electron microscopy (TEM). Notably, TEM images certified a signifi- thetic procedure to obtain compounds 5-11 starting from the 4- cant reduction in the amount of fibrillar material in the presence amino-5–(4-pyridinyl)-4H-1,2,4-triazole-3-thiol 12, that was coupled of compound 3 (Figure 4(D)), when compared to untreated sam- with the appropriate benzyl bromide in alkaline medium at room ples (Figure 4(C)). temperature. Figure 3. (A) Chemical structures of compounds 2, 3 and 4. (B) Alignment of each of the reported hits (represented by pink (2), orange (3) and yellow (4) sticks) with the pharmacophore model. 1732 S. VITTORIO ET AL. Figure 4. Inhibitory in vitro characterisation of compounds 1 to 4. (A) Aggregation kinetic of a-syn in absence (black) and presence of 100 mM of Compound 1 (red), compound 2 (green), compound 3 (blue), compound 4 (orange) and SynuClean-D (grey), followed by Th-T fluorescence emission. (B) Light-scattering measurements at 300 nm in the absence (black) and presence of 100 mM of Compound 1 (red), compound 2 (green), compound 3 (blue) and compound 4 (orange). (C and D) Representative TEM images of untreated (C) and compound 3 treated samples (D). Th-T fluorescence is plotted as normalised means. Final points were obtained at 48 h. Error bars are represented as SE of mean values;  p < 0.01 and  p < 0.001. n R i 5 1 H 6 2 H 7 1 4-F 12 5-11 8 1 3-F Scheme 2. Reagents and conditions: i) Ar(CH2)nBr, NaOH, MeOH, rt. 9 1 4-CH3 5-11 10 1 3-CH3 described above. Incubation of 70 mM a-Syn in the presence of 11 1 4-Cl 100 mM of the different compounds, followed by Th-T fluorescence measurements at the end of the reaction indicated that 5, 8, 9 Scheme 1. Designed pyridinyltriazole derivatives 5–11 inspired by compound 3. and 11 could reduce the aggregation up to a 33, 15, 19 and 29%, respectively (Figure 5(A)). Light-scattering measurements at 300 nm indicated that 5, 6, 7, 8, 9 and 10 reduced the amount of 3.3. Screening of the activity of the new derivatives 5–11 aggregates up to a 23, 16, 26, 14, 24, 17%, respectively (Figure The synthesised derivatives were tested in order to study their 5(B)). However, TEM analysis indicated that only 5 (Figure 5(E)), 8 ability to reduce a-syn aggregation in vitro by using the method (Figure 5(F)), 9 (Figure 5(G)) and 11 (Figure 5(H)) reduced the JOURNAL OF ENZYME INHIBITION AND MEDICINAL CHEMISTRY 1733 Figure 5. Inhibitory in vitro characterisation of tested compounds 5–11. (A and B) Aggregation kinetics of a-syn in the absence (black) and presence of 100 mM of compounds 5 (red), 6 (green), 7 (violet), 8 (orange), 9 (blue), 10 (brown), 11 (yellow) and SynuClean-D (grey), followed by Th-T fluorescence emission. (C) Light-scatter- ing measurements at 300 nm in the absence (black) and presence of 100 mM of compounds 5 (red), 6 (green), 7 (violet), 8 (orange), 9 (blue), 10 (brown) and 11 (yel- low). (D to G) Representative TEM images of untreated (D) and 5 (E), 8 (F), 9 (G) and 11 (H) treated samples. Th-T fluorescence is plotted as normalised means. Final points were obtained at 48 h. Error bars are represented as SE of mean values;  p < 0.01 and  p < 0.001. Figure 6. Binding site of a-syn identified through docking studies for this class of inhibitors. The image is created by PyMOL software (https://pymol.org). Figure 7. Plausible binding mode of compound 3 (pink stick). The interacting residues of the binding site are represented as light blues stick. The image is cre- ated by PyMOL software (https://pymol.org). number of amyloid fibrils when compared to control samples (Figure 5(D)), in good agreement with the kinetic analysis. Considering that in our above reported molecular modelling studies we selected polyphenolic and non-polyphenolic inhibitors (see Table 1) that bind the N-terminal region of a-syn, we hypoth- 3.4. Docking studies esised that also derivatives 3, 5, 8, 9 and 11 could interact with same portion of the protein. For this reason, we defined this In order to ascertain the binding mode of pyridinyl-triazole deriva- region as the search space for the docking simulation (see tives 3, 5, 8, 9 and 11 that demonstrated the ability to reduce Material and Methods section). The docking results confirmed that a-syn aggregation in vitro, we carried out molecular docking simu- all the tested compounds bind in the same site of a-syn located lation by means of Autodock 4.2 suite;29 the computational stud- between the N-terminal and the NAC domains of the protein and ies were based on NMR structure of a-syn (PDB code 2N0A) as lined by Ala53, Val55, Thr59, Glu61, Thr72, Gly73 and Val74 structural coordinates30. (Figure 6). 1734 S. VITTORIO ET AL. Figure 8. Plausible binding modes for compound 5 (magenta stick, panel A), 8 (orange stick, panel B), 9 (green stick, panel C) and 11 (cyan stick, panel D). The inter- acting residues of the binding site are represented as light blues stick. The images are created by PyMOL software (https://pymol.org). Notably, in a recent work, Pujols and co-workers identified the of Glu61. Moreover, for inhibitors 5, 8, 9 a pi-anion interaction same portion of the protein as binding site of their inhibitor 2- was observed between the pyridine ring and Glu61B. hydroxy-5-nitro-6-(3-nitrophenyl)-4-(trifluoromethyl)nicotinonitrile Additionally, compound 5 might form a hydrogen bond with through a induced-fit docking simulation24; therefore, these evi- Thr72C through the sulphur atom and pi-sigma interaction with dences further supported the hypothesis that this region could Thr72C (Figure 8, Panel A). Concerning compound 8, it might represent a binding site for small molecules on a-syn fibrils. establish a halogen bond between the fluorine atom and Thr72D In detail, compound 3 could bind to a-syn by establishing a (Figure 8, Panel B). Instead, 9 could engage pi-sigma interaction salt bridge between the amino group and Glu61 and p-anionic with Thr72C (Figure 8, Panel C). Finally, compound 11 might interaction between the pyridine ring and Glu61B. The cinnamyl establish van der Waals interactions with Val55C (Figure 8, moiety is oriented towards Ala53, Gly73 and Val74 and might Panel D). engage hydrophobic interaction with Ala53. Furthermore, van der Waals interactions with Val55, Thr59, Thr72, Gly73 and Val74 could be observed (Figure 7). 4. Conclusion In Figure 8, the binding mode of compounds 5, 8, 9 and 11 is displayed. The new derivatives showed a slight different binding The search for a cure of PD represents an important challenge in orientation in comparison to the parent compound 3, probably the pharmaceutical research field. The inhibition of a-syn aggrega- due to the shorter and more flexible linker between the sulphur tion has emerged as promising new therapeutic strategy for the atom and the aromatic ring. treatment of PD. In this work, we described the generation of a In particular, all the inhibitors could interact with a-syn by a ligand-based pharmacophore model, which was used as query to crucial salt bridge between the amino group and the side chain screen two chemical libraries. The hits selected from the virtual JOURNAL OF ENZYME INHIBITION AND MEDICINAL CHEMISTRY 1735 screening were tested in vitro to probe their ability to inhibit 12. Haddad F, Sawalha M, Khawaja Y, et al. Dopamine and levo- a-syn aggregation, resulting in the identification of the new hit 3. dopa prodrugs for the treatment of Parkinson’s disease. Structural modifications were carried out on compound 3 obtain- Molecules 2017;23: 40. ing four interesting derivatives. Finally, the binding mode of this 13. Carrera I, Cacabelos R. Current drugs and potential future new class of inhibitors on a-syn was investigated by molecular neuroprotective compounds for Parkinson’s disease. Curr docking simulation. All the information gained from these studies Neuropharmacol 2019;17:295–306. could be useful for the design of novel inhibitors a-syn aggrega- 14. Borovac JA. Side effects of a dopamine agonist therapy for tion inhibitors bearing a pyridinyl-triazole scaffold. Parkinson’s disease: a mini-review of clinical pharmacology. Yale J Biol Med 2016;89:37–47. 15. O’Hara DM, Kalia SK, Kalia LV. Emerging disease-modifying Disclosure statement strategies targeting a-synuclein for the treatment of The authors declare that there is no conflict of interest. Parkinson’s disease. Br J Pharmacol 2018;175:3080–9. 16. Pen~a-Dıaz S, Pujols J, Conde-Gimenez M, et al. ZPD-2, a small compound that inhibits a-synuclein amyloid aggrega- Funding tion and its seeded polymerization. Front Mol Neurosci The authors thank the “Programma Operativo Nazionale Ricerca & 2019;12: 306. Innovazione 2014-2020, Azione I(0).1 “Dottorati Innovativi con car- 17. Singh SK, Dutta A, Modi G. a-Synuclein aggregation modula- atterizzazione industriale” XXXIII cycle, for financial support in tion: an emerging approach for the treatment of Parkinson’s form of a PhD scholarship “DOT1314952” granted to SV. disease. Future Med Chem 2017;9:1039–53. 18. Shihabuddin LS, Brundin P, Greenamyre JT, et al. New fron- tiers in Parkinson’s disease: from genetics to the clinic. J Neurosci 2018;38:9375–82. ORCID 19. Teil M, Arotcarena ML, Faggiani E, et al. Targeting a-synu- Serena Vittorio http://orcid.org/0000-0001-6092-5011 clein for PD therapeutics: a pursuit on all fronts. Rosaria Gitto http://orcid.org/0000-0003-0002-2253 Biomolecules 2020;10:391. Laura De Luca http://orcid.org/0000-0003-0614-5713 20. Wolber G, Langer T. LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters. J Chem Inf Model 2005;45:160–9. References 21. Oliveri V. Toward the discovery and development of effect- 1. 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