11 research outputs found
Faster Lead Optimization Mapper Algorithm for Large-Scale Relative Free Energy Perturbation
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 equivalent to that
obtained using conventional Lomap, enabling direct replacement of the original
Lomap with our method. With our improvement, the execution was tens to hundreds
of times faster than that of the original Lomap.
https://github.com/ohuelab/FastLoma