> Specializing in
Computational Biophysics, Biology, and Bioinformatics group focused on drug design, machine learning, theoretical chemistry, and computational biology applied to pharmaceutical and environmental sciences.
Our interdisciplinary research spans computational chemistry, biology, machine learning, and experimental methods—all applied to drug design, development, environmental sciences, and chemical regulation.
Antibiotic resistance (ABR) is a critical global public health threat—1.27 million deaths worldwide in 2019 alone, with projections surpassing cancer mortality by 2050. In collaboration with IRTA (Institute of Agrifood Research and Technology, Spain), we design bioinspired superantibiotics based on personalized host defense peptides (HDPs) selected by artificial intelligence. Our transdisciplinary approach integrates broad antimicrobial screening with experimental and in-silico physicochemical characterization to recombinantly produce tailored HDPs with superior potency, selectivity, and lower toxicity than existing antimicrobials.
🤝 Collaboration: IRTA · Dra. Elena García & Dra. Ana Arís (Barcelona)
Chemoinformatics tools, ADME-Tox profiling, molecular docking with Glide, QSAR studies, and classical molecular dynamics simulations with AMBER—focused on antibiotic and drug discovery pipelines.
QSAR and MD simulations in peptides and proteins, especially antimicrobial peptides (AMPs). Mutation-effect prediction in diseases such as Alzheimer's and Myotonia. Study of neuroprotective and antioxidant peptides.
Development and parameterization of the IEFPCM/MST continuum solvation model using Gaussian. Determination of QM-based physicochemical properties in drugs and environmental pollutants, including SAMPL blind challenges.
Theoretical models for pH-dependent lipophilicity profiles of ionizable compounds and for relative water content in aerosols as a function of organic solutes in colloidal suspensions. Development of scoring functions for docking studies with Pharmacelera Inc.
Machine learning models for physicochemical properties in small molecules (bioactivity, lipophilicity, tautomeric equilibria) and pollutants (solubility, toxicity). ML-based environmental bioaccumulation prediction. Structure-based lipophilicity scale for amino acids.
Potentiometric and Shake-flask methods for pKa and lipophilicity. Quantification of emerging environmental pollutants via analytical techniques. Phytotherapeutics with nanotechnology. Chromatography (HPLC, UPLC), NMR, MS, IR, and ORAC antioxidant methods.
The researchers leading the CBio3 laboratory at the Universidad de Costa Rica.
Graduate, undergraduate, and former members of the CBio3 group. Profiles will be updated as students join and contribute to ongoing projects.
Software and web tools developed by the CBio3 lab, freely available to the scientific community.
Committed to open science and FAIR data principles. Our curated databases are freely available to the global research community.
Peer-reviewed articles, preprints, and conference proceedings from the CBio3 group. Search by title, author, or journal.
Due to the interdisciplinary nature of our group, we leverage our own facilities as well as computing resources generously shared by our international collaborators.
Our on-site laboratory equipped with all necessary software for computational chemistry, molecular dynamics, machine learning, bioinformatics, and chemoinformatics research.
High-performance computing from the Consorci de Serveis Universitaris de Catalunya (CSUC), accessible through our collaboration with Dr. Javier Luque, Dr. Antonio Viayna, Dr. Javier Vázquez, and Dr. Carles Curutchet (UB). CBCG Group ↗
Computational Cluster of the Materials Science and Engineering Research Center at UCR. Contact: Dr. Federico Muñoz (federico.munozrojas@ucr.ac.cr). Cluster Info ↗
National High Technology Center's Advanced Computing Laboratory (CNCA) supercomputing infrastructure, including the KABRE HPC cluster. KABRE ↗
Access to the Universidad de Costa Rica's institutional cluster for large-scale computational research. UCR HPC ↗
