# Algorithmic improvements in large scale polarizable QM/MM simulations > **NIH NIH R44** · Q-CHEM, INC. · 2022 · $623,245 ## Abstract Project Summary Modeling of chemical reactivity in heterogeneous environments such as protein pockets and complex solvents is an essential part of a drug discovery workflow. However, such modeling is challenging, due to large system sizes and necessity of extensive sampling of environment degrees of freedom. The goal of this project is to develop a suite of efficient, accurate and scalable computational tools based on the polarizable quantum me- chanics / effective fragment potential (QM/EFP) methodology that will provide academic and private industry users with fast and robust software for the computational characterization of free energy profiles of chemical reactions in complex condensed phase systems. Phase II of this project builds upon the outcomes of a success- ful completion of Phase I, in which the team has developed algorithms and computer codes that dramatically decrease the computational cost of EFP and QM/EFP simulations by employing fast multipole method (FMM). In Phase II the team will further improve the efficiency of FMM-QM/EFP codes by implementing robust par- allel algorithms. Modeling of chemical transformations will be enabled by development of analytic nuclear gradients and second derivatives. Additionally, FMM-QM/EFP will be interfaced with polarizable continuum models (PCM) and extended to periodic boundary conditions that will provide users with complimentary tools for modeling long-range electrostatic and polarization interactions. New methodology will be validated on established and emerging data for mechanisms and energetics of solution-phase and enzymatic reactions. ## Key facts - **NIH application ID:** 10547634 - **Project number:** 2R44GM126804-02A1 - **Recipient organization:** Q-CHEM, INC. - **Principal Investigator:** Xintian Feng - **Activity code:** R44 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $623,245 - **Award type:** 2 - **Project period:** 2019-01-01 → 2024-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10547634 ## Citation > US National Institutes of Health, RePORTER application 10547634, Algorithmic improvements in large scale polarizable QM/MM simulations (2R44GM126804-02A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10547634. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*