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Overview of Major Research Directions

Here you will find some of the major research lines I have explored in the past and am currently pursuing, ranging from machine learning applied to drug design, to understanding protein and small molecule interactions at atomic scale.


Protein Design and Interactions

Using dynamics to understand protein interactions and function

Protein interactions are essential for regulation of cellular processes from the formation of multi-protein complexes to the allosteric activation of enzymes. Computational biochemistry allows us to identify the essential residues and molecular features that regulate such interactions, paving the way for a better understanding of diverse biochemical processed. Among multiple applications, this research allows for suppression of a reaction through drug interventions or optimization of a chemical process using bioengineered molecules.


Computer Aided Drug Design

Leveraging ML/AI to design new drugs

Despite the dangerous and urgent threats from multi-drug resistant bacteria and viruses that can quickly affect human at a global scale, drug development is still a slow costly process. While some steps (like clinical trials) can and should be done in a careful and thorough manner, molecular design and optimization can and should leverage as much of our computational capabilities as it does our biological and chemical experience. This research integrated machine learning and biochemical information to further computational efforts in drug design


Hybrid QM/MM Simulations

Integrating QM and MM potentials in Molecular Dynamics simulations

The NAMD QM/MM interface extends existing NAMD features to the quantum mechanical level, presenting new features and possibilities for the world of computational chemistry. Investigations of processes occurring on a timescale usually not accessible by QM/MM methods can be performed by combining enhanced sampling and free energy calculation method already present in NAMD. Taking advantage of an easy-to-use Tcl based interface and capabilities integrated from VMD, this interface has the ability to execute multiple QM regions in parallel, thorough independent executions of your choice of quantum chemistry code.


Cellular and Microbiome Metabolism

Simulating whole-cell metabolism to understand microbial communities

Hundreds of microbial species have been identified in our gut microbiome, however we still lack tools to precisely probe and engineer this community. Using systems biology tools to describe the interactions between microbial species is essential to develop predictive and quantitative models of our microbiome.


Protein Folding and Enhanced Sampling

Exploring protein structure and intrinsically disordered regions

GSAFold applies the Generalized Simulated Annealing (GSA) algorithm for ab-initio structure prediction of small proteins and intrinsically disordered regions. This new package combines a precise implementation of GSA with the broadly used NAMD Molecular Dynamics software to carry out energy calculations, allowing different force fields and parameterizations to be used in enhanced structure sampling of flexible molecular regions.

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