• Molecular docking and reverse molecular docking; • Pharmacophore modeling and reverse pharmacophore modeling; • Prediction of compounds activity using machine learning (QSAR, artificial neural networks, and Bayesian modeling); • Virtual high-throughput screening and design of targeted compound libraries with high affinity to the molecular targets; • Structure-activity relationship (SAR) analysis and hit optimization using in-house facilities; • In silico ADME predictions; • Computational studies of drug-receptor, protein-protein, nucleic acids-protein, and other interactions; • Molecular dynamics of proteins, nucleic acids, extra large heterogeneous systems; • Accurate prediction of binding energy.