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