Our group develops and applies computational methods to understand, characterize, and design chemical systems with applications in drug discovery and development. These systems include i) pharmaceutically relevant enzymes involved mainly in cancer and neurodegeneration and ii) functionalized nanoparticles for chemosensing, catalysis, and drug delivery. By achieving an atomic-level comprehension of the general principles that control molecular recognition and catalysis, the goal is to design new molecular tools capable of specific functions, such as potent enzymatic inhibitors to treat health issues and intelligent nanoparticles with programmed properties for molecular detection. To achieve this goal, we apply classical molecular dynamics (MD) simulations coupled with first-principles-based computational methods (e.g. QM/MM simulations) and enhanced sampling techniques for free energy estimation. This multiscale computational approach includes also docking, virtual screening, de novo small molecules computational design and in silico ADMET evaluation. These computational efforts are integrated with medicinal chemistry and molecular biology to identify and optimize novel small molecules able to inhibit the enzymatic function of interest.
Molecular Modeling and Drug Discovery
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