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azevedolab.net

We are a research group working on the development of computer models to simulate natural systems. Our primary goal is the research focused on computational systems biology. We have been working on the creation of novel computational models for unraveling the molecular mechanisms underlying enzyme inhibition and protein-ligand interactions. These computational models can be used to predict the binding affinity of a potential inhibitor for an enzyme; such knowledge has the potential to speed up drug discovery and decrease the cost of new drugs. Furthermore, the availability of computational models to predict binding affinity based on the atomic coordinates of protein-ligand complexes adds flexibility to the process of drug discovery, since it allows us to computationally test different scenarios where a potential new drug may interact with a protein target.

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Topics: artificial intelligence, bioinformatics, bio-inspired computing, computational biology, deep learning, differential evolution, evolutionary computing, genetic algorithms, machine learning, molegro virtual docker, numpy root mean square, rmsd python, sandres, scientific computing, swiss dock

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