Q-Chem is a state-of-the-art commercial computational quantum chemistry program that has aided tens of thousands users in their modeling of molecular processes in a wide range of disciplines, including biology, chemistry, and materials science. In quantum chemistry, density functional theory (DFT) and second order Moller-Plesset theory (MP2) are already heavily used in the development of molecular mechanics force fields and in the hybrid quantum mechanical molecular mechanical simulations of protein-ligand binding affinities and enzymatic reaction free energies, despite their accuracy and computational cost limitations. To address these limitations, we seek to advance double hybrid density functionals (DHDFs) for computing conformational and binding energies. Specifically, we aim to: (1) Further enhance the computational efficiency of the short range MP2 (SR-MP2) method, which was developed in our Phase I research and demonstrated to yield unprecedented accuracy and efficiency;(2) Build new double hybrid density functionals on top of our SR-MP2 in order to further extend its applicability;and (3) Demonstrate the use of both SR-MP2 and associated new DHDFs in chemical and biological problems. The new tools coming out of this Phase II research will outperform existing DFT and MP2 methods, and yield improved accuracy with reduced computational cost, opening new applications as well as improving existing ones in chemical, biochemical and biomedical research. This work will further strengthen Q-Chem's position as a global leader in the molecular modeling software market, making our program the most efficient and reliable computational quantum chemistry package for simulating large, complex chemical/biological systems.
This project aims to develop the fastest software for accurately predicting the conformational energies of biopolymer (such as peptides, proteins, carbohydrates) and the binding affinities between a ligand and a receptor. Building upon sophisticated quantum mechanics, this can lead to reliable and efficient computational tools for use in computer-aided drug design, and in the simulation of large, complex chemical/biological systems.
