Mauricio Bedoya
I am a professional pharmaceutical chemist with a Ph.D. in Applied Sciences, specializing in computational biology. Currently, I hold an academic position at the Universidad Católica del Maule in Chile, where I am a member of both, the Centro de Investigación de Estudios Avanzados del Maule (CIEAM) and the Laboratorio de Bioinformática y Química Computacional (LBQC).
My research focuses on modeling biological systems, particularly membrane proteins and proteins in general, using computational methods to elucidate molecular and physiological mechanisms. This enables the design of novel molecules for therapeutic applications.
Acknowledgments
Thanks to FONDECYT - ANID for postdoctoral grant No. 3210774.
Thanks to "Centro de Bioinformática, Simulación y Modelado (CBSM) - Universidad de Talca" and Fondequip EQM160063.
This work used resources of the "Centro Nacional de Processamento de Alto Desempenho em São Paulo (CENAPAD-SP)".
Collaborators
Francisco Adasme - Universidad Católica del Maule, Chile.
Leandro Martínez - Universidad de Campinas, Brasil.
Jans Alzate-Morales - CBSM, Universidad de Talca, Chile.
Session
Computational chemistry is a rapidly growing field that uses computers for running simulations to study the properties of molecules and materials. Computer-aided drug design (CADD) is a branch of computational chemistry that uses molecular modelling and simulation to help understand and design new drugs.
Scientists often need to deal with tons of data (big data) generated by specialized software, which needs to be processed to extract relevant information. We have developed a modern computational chemistry library, termed chem.cr, for data manipulation and analysis using the Crystal language.
chem.cr aims to be both fast and easy to use, and it currently provides several features:
- Hierarchical object-oriented access to molecular structure
- Iterator-based file reading of several formats (PDB, Mol2, etc)
- Topology detection
- Spatial measurements
- Volumetric data
- Type safety
- Fast performance, rivaling or even surpassing other libraries built with Python/C/C++
chem.cr has already been used to develop and publish a new algorithm for protein structure (Adasme-Carreño et al., 2021), and we're developing new protocols for molecular docking and free energy calculations (Femdock and Moltiverse) that are crucial for CADD.
Femdockhelps to sample the possible orientations of a drug within a protein binding site using a genetic algorithm, like other molecular docking approaches, but thanks to the Crystal language, the code is clearer and easier to understand and modify.Moltiverseis used to generate molecular conformers of the drug using enhanced sampling methods, that directly support the exploration performed by Femdock.
We hope that this new library and protocols will help scientists to develop new/better tools that accelerate drug discovery and the study of molecular structure.
References
- Adasme-Carreño, F., Caballero, J., & Ireta, J. (2021). PSIQUE: Protein Secondary Structure Identification on the Basis of Quaternions and Electronic Structure Calculations. Journal of Chemical Information and Modeling, 61(4), 1789–1800. https://doi.org/10.1021/acs.jcim.0c01343