TALAIA : A 3D visual dictionary for protein structures
Alemany-Chavarria, Mercè (Universitat Autònoma de Barcelona. Departament de Química)
Rodríguez-Guerra Pedregal, Jaime (Universitat Autònoma de Barcelona. Departament de Química)
Maréchal, Jean-Didier (Universitat Autònoma de Barcelona. Departament de Química)

Data:	2023
Resum:	Motivation: Graphical analysis of the molecular structure of proteins can be very complex. Full-atom representations retain most geometric information but are generally crowded, and key structural patterns can be challenging to identify. Non-full-atom representations could be more instructive on physicochemical aspects but be insufficiently detailed regarding shapes (e. g. entity beans-like models in coarse grain approaches) or simple properties of amino acids (e. g. representation of superficial electrostatic properties). In this work, we present TALAIA a visual dictionary that aims to provide another layer of structural representations. TALAIA offers a visual grammar that combines simple representations of amino acids while retaining their general geometry and physicochemical properties. It uses unique objects, with differentiated shapes and colors to represent amino acids. It makes easier to spot crucial molecular information, including patches of amino acids or key interactions between side chains. Most conventions used in TALAIA are standard in chemistry and biochemistry, so experimentalists and modelers can rapidly grasp the meaning of any TALAIA depiction. Results: We propose TALAIA as a tool that renders protein structures and encodes structure and physicochemical aspects as a simple visual grammar. The approach is fast, highly informative, and intuitive, allowing the identification of possible interactions, hydrophobic patches, and other characteristic structural features at first glance. The first implementation of TALAIA can be found at https://github. com/insilichem/talaia.
Ajuts:	Agencia Estatal de Investigación PID-2020-116861GB-I00
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Publicat a:	Bioinformatics, Vol. 39, Issue 8 (August 2023) , art. btad476, ISSN 1367-4811

DOI: 10.1093/bioinformatics/btad476
PMID: 37549048

4 p, 3.5 MB

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