SBIR-STTR Award

Algorithmic improvements in large scale polarizable QM/MM simulations
Award last edited on: 2/17/2024

Sponsored Program
SBIR
Awarding Agency
NIH : NIGMS
Total Award Amount
$1,407,285
Award Phase
2
Solicitation Topic Code
859
Principal Investigator
Evgeny Epifanovsky

Company Information

Q-Chem Inc

6601 Owens Drive Suite 105
Pleasanton, CA 94588
   (412) 687-0695
   info@q-chem.com
   www.q-chem.com
Location: Single
Congr. District: 15
County: Alameda

Phase I

Contract Number: 1R43GM126804-01A1
Start Date: 1/1/2019    Completed: 3/31/2020
Phase I year
2019
Phase I Amount
$149,892
The goal of the project is to develop new algorithms and computer codes based on the continuous fast multipole method that will dramatically decrease the computational complexity of large-scale modeling of redox processes and other bio- and photo-chemical reactions accompanying metabolic pathways of drug molecules. Redox processes are at the heart of various biological functions, including respiration, redox signaling, protection from oxidative stress. Redox-active enzymes serve as drug targets for antibacterial and antiviral therapy. Quantitative atomic-level description of redox processes in biomolecules paves the way to mechanistic understanding of their function and potentially to the development of novel therapeutic agents. Current state-of-the art in computational modeling of biochemical processes is to use hybrid quan- tum mechanics-molecular mechanics (QM/MM) methods that provide a balance between computational accuracy and efficiency. Furthermore, polarizable model potentials and polarizable QM/MM schemes become increasingly more important as they provide a more rigorous description of the classical environ- ment. In particular, polarizable models are essential for modeling redox processes as different oxidation states induce significant changes in charge distribution in the surrounding environment. However, despite enormous computational speed-ups attained through describing the majority of the system classically, re- maining bottlenecks of the QM/MM models are due to the necessity of computing long-range electrostatic interactions in an extended system. The proposed algorithms aim to eliminate these bottlenecks and enable the users in academia and the industry to perform simulations of biological systems in a more efficient and robust way, using either classical point-charge or polarizable QM/MM models. New computer codes will be implemented within the Q-Chem quantum chemistry package developed by Q-Chem, Inc.

Public Health Relevance Statement:
Project Narrative The proposed project aims to dramatically reduce the computational cost of accurate modeling of biochem- ical reactions in realistic environments. The resulting software will create new research opportunities in theoretical and applied biochemistry.

Project Terms:
Algorithms; Biochemistry; Biological Chemistry; Charge; Computer Architectures; virtual simulation; in silico; computerized simulation; computerized modeling; computer based models; computational simulation; computational models; computational modeling; Mathematical Models and Simulations; Mathematical Model Simulation; Computerized Models; Computer based Simulation; Computer Models; Computer Simulation; drug/agent; Pharmaceutic Preparations; Medication; Drugs; Pharmaceutical Preparations; electron transfer; Electron Transport; Environment; Enzyme Gene; Enzymes; balance function; balance; Equilibrium; Goals; Heart; Hybrids; Industry; Methods; Methodology; Model System; Biologic Models; Biological Models; Modernization; National Institutes of Health; NIH; United States National Institutes of Health; oxidation; oxidation reduction reaction; Redox; Oxidation-Reduction; Proteins; Research; respiratory mechanism; Respiration; biological signal transduction; Signaling; Signal Transduction Systems; Intracellular Communication and Signaling; Cell Signaling; Cell Communication and Signaling; Signal Transduction; Software; Computer software; Solvents; Time; Work; base; density; macromolecule; Phase; Variant; Variation; Biological; Biochemical; Chemicals; Evaluation; Development Plans; Oxidative Stress; Biological Process; Biological Function; Anti-Bacterial Agents; antibacterial; anti-bacterial; Antibacterial Agents; Antiviral Therapy; viral infectious disease treatment; anti-viral therapy; Therapeutic Agents; tool; Nature; Electrostatics; Dimensions; Complex; Reaction; System; interest; chemical reaction; molecular dynamics; Molecular Dynamics Simulation; quantum chemistry; Speed; Potential Energy; simulation; Modeling; Sampling; computational chemistry; molecular mechanics; Metabolic Pathway; Academia; Biochemical Process; Biochemical Reaction; Enzymatic Reaction; Quantum Mechanics; Scheme; Molecular; Process; Development; developmental; cost; computer code; biochemical model; design; designing; Outcome; practical application; application in practice; parallel computer; parallel computing; parallel computation; novel therapeutics; novel therapy; novel drugs; novel drug treatments; next generation therapeutics; new therapy; new therapeutics; new drugs; new drug treatments; biological systems; Drug Targeting; Geometry; Cost efficiency

Phase II

Contract Number: 2R44GM126804-02A1
Start Date: 1/1/2019    Completed: 7/31/2024
Phase II year
2022
(last award dollars: 2023)
Phase II Amount
$1,257,393

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.

Public Health Relevance Statement:
Project Narrative Novel software will be developed for computer modeling of chemical reactivity in proteins and solvents. The software will facilitate research tasks throughout computer-aided drug development workflows.

Project Terms:
Algorithms; Catalysis; Chemistry; Drug Design; Pharmaceutical Preparations; Drugs; Medication; Pharmaceutic Preparations; drug/agent; Environment; Freedom; Liberty; Goals; Hybrids; Industry; Literature; Methods; Methodology; Chemical Models; Nobel Prize; Cyclicity; Rhythmicity; Periodicity; Polymers; Privatization; Proteins; Research; Software; Computer software; Solvents; base; improved; Surface; Phase; Biological; biologic; Physiological; Physiologic; Chemicals; Evaluation; Intuition; Spottings; tool; Nature; Electrostatics; Complex; Reaction; System; Nuclear; chemical reaction; intermolecular interaction; Molecular Dynamics Simulation; molecular dynamics; Molecular Modeling Nucleic Acid Biochemistry; Molecular Modeling Protein/Amino Acid Biochemistry; Molecular Models; molecular modeling; Potential Energy; Free Energy; simulation; novel; Coding System; Code; Modeling; Sampling; drug development; molecular mechanics; drug discovery; Enzymatic Reaction; Biochemical Reaction; Data; Quantum Mechanics; Molecular; Process; Development; developmental; cost; computer code; computerized tools; computational tools; Computer Assisted; computer aided; design; designing; quantum; Outcome; practical application; application in practice; Computational algorithm; computer algorithm; Geometry; Algorithmic Software; Algorithmic Tools; Software Algorithm; Grain; Computer Models; Computerized Models; computational modeling; computational models; computer based models; computerized modeling; algorithm development