Mc. Sc. Joel Ricci López

Ph.D. Student - AguilaLab Team

Center for Scientific Research and Higher Education of Ensenada (CICESE)
Centre for Nanoscience and Nanotechnology (CNyN), UNAM.

Thesis title: “Virtual screening using machine learning techniques and ensemble docking-based molecular descriptors”

Ph.D. Advisors: Dr. Carlos A. Brizuela and Dr. Sergio A. Águila

Brief Synopsis of Research:

We aim to test and design a structure-based virtual screening pipeline, combing target molecular dynamics simulation in mixed solvents, conformational selection, ensemble-based docking, and machine learning techniques.

Publications:

Ricci-López, J., Vidal-Limon, A., Zuñiga, M., Jimenez, V. A., Alderete, J. B., Brizuela, C. A., & Aguila, S. (2019). Molecular modeling simulation studies reveal new potential inhibitors against HPV E6 protein. PLOS ONE, 14(3), e0213028. https://doi.org/10.1371/journal.pone.021302

Ricci-Lopez, J., Aguila, S. A., Gilson, M. K., & Brizuela, C. A. (2021). Improving Structure-Based Virtual Screening with Ensemble Docking and Machine Learning. Journal of Chemical Information and Modeling, 61(11), 5362–5376. https://doi.org/10.1021/acs.jcim.1c00511.

Web poster: Ricci-Lopez, J., Aguila, S. A., & Brizuela, C. A. (2021). Druggability prediction of protein conformations using convolutional neural networks. At LatinXChem2021 Twitter Virtual Conference. Best poster award in the ChemBio category. doi: 10.26226/morressier.616e5c2462ba8657678b132f
Interactive Poster.