학술논문

Faster Lead Optimization Mapper Algorithm for Large-Scale Relative Free Energy Perturbation
Document Type
Conference
Source
2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE) CSCE Computer Science, Computer Engineering, & Applied Computing (CSCE), 2023 Congress in. :2126-2132 Jul, 2023
Subject
Computing and Processing
Drugs
Perturbation methods
Redundancy
Lead
Fingerprint recognition
Computational efficiency
Planning
free energy perturbation (FEP)
Lomap
computational drug discovery
acceleration
FastLomap
Language
Abstract
In recent years, free energy perturbation (FEP) calculations have garnered increasing attention as tools to support drug discovery. The lead optimization mapper (Lomap) was proposed as an algorithm to calculate the relative free energy between ligands efficiently. However, Lomap requires checking whether each edge in the FEP graph is removable, which necessitates checking the constraints for all edges. Consequently, conventional Lomap requires significant computation time, at least several hours for cases involving hundreds of compounds, and is impractical for cases with more than tens of thousands of edges. In this study, we aimed to reduce the computational cost of Lomap to enable the construction of FEP graphs for hundreds of compounds. We can reduce the overall number of constraint checks required from an amount dependent on the number of edges to one dependent on the number of nodes by using the chunk check process to check the constraints for as many edges as possible simultaneously. Moreover, the output graph is the same as that obtained using the conventional Lomap, enabling direct replacement of the original one with our method. With our improvement, the execution was tens to hundreds of times faster than that of the original Lomap.