FastLomap: Faster Lead Optimization Mapper Algorithm for Large- Scale Relative Free Energy Perturbation

In recent years, free energy perturbation 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. Based on the analysis of the execution profiles, we also improved the speed of cycle constraint and diameter constraint checks. 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 hundreds of times faster than that of the original Lomap.

Publication Details

Journal
Tokyo Tech Research Repository (Tokyo Institute of Technology)
Published
2024-10-02
Primary Topic
Magnetic confinement fusion research
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article
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article

FastLomap: Faster Lead Optimization Mapper Algorithm for Large- Scale Relative Free Energy Perturbation

Tokyo Tech Research Repository (Tokyo Institute of Technology)
Magnetic confinement fusion research
article

FastLomap: Faster Lead Optimization Mapper Algorithm for Large- Scale Relative Free Energy Perturbation

article en

Abstract

In recent years, free energy perturbation 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. Based on the analysis of the execution profiles, we also improved the speed of cycle constraint and diameter constraint checks. 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 hundreds of times faster than that of the original Lomap.

Tokyo Tech Research Repository (Tokyo Institute of Technology)
Affordable and clean energy
Openalex Percentile: Top 74%
Magnetic confinement fusion research
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FastLomap: Faster Lead Optimization Mapper Algorithm for Large- Scale Relative Free Energy Perturbation · Tokyo Tech Research Repository (Tokyo Institute of Technology) (2024) | TGRS Research Map | TGRS