Abstract 

 In this talk, I will present the newly developed quantum mechanics (QM) based free energy perturbation (FEP) approach and its applications to small-molecule lead optimization in computer-aided drug discovery (CADD). This novel approach that directly applies QM/MM dynamics to FEP, named QUELO, is based on the QM representation of drug molecules and interacting side chain/residues of the receptor proteins and has a throughput of up to 2-3ns using 4 cores of a CPU, with a single time step being ~60 ms walltime, which is only a few times that of the classical molecular mechanics (MM) counterparts on the same hardware. I will present several numerical examples for which QUELO significantly outperforms classical FEP due to the inclusion of better physics in the models, e.g., the polarization of proteins for charge-changing mutations. I further demonstrate the new simulation capabilities that QUELO enables, including the prediction of binding affinity for reversible covalent inhibitors and accurate residue scanning in liability analysis of proteins.