Methods and Applications

Machine learning (ML) methods have transformed the fields of chemistry and molecular sciences in recent years and will continue to do so in the future. The Cal State LA-MolSSI PREC (Partnership for Research and Education in Chemistry) will be organized around three thematic research thrusts that each use ML and physics-based simulation methods to create new computational models applicable to a range of chemical and biochemical phenomena.

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Method & Application

Thrust 1 will focus on developing ML approaches for computing the relative entropies and thermodynamic stabilities of molecular crystal polymorphs.  

Thrust 2 will aim to develop a hybrid physics-based and ML approach for predicting the relative binding free energies of small protein-ligand complexes.  

Thrust 3 will use ML to parametrize small molecule force fields that include a direct polarization electrostatic model and other advanced nonbonded potentials. The results of this research will help answer pressing questions in chemistry, biophysics, materials science, and pharmacology.

Events & Activities


Please contact Cal State LA-MoISSI PREC at [email protected] with any questions or inquiries on how you can get involved!

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