TY - JOUR
T1 - FEP-SPell-ABFE
T2 - An Open-Source Automated Alchemical Absolute Binding Free-Energy Calculation Workflow for Drug Discovery
AU - Li, Pengfei
AU - Pu, Tingting
AU - Mei, Ye
N1 - Publisher Copyright:
© 2025 American Chemical Society.
PY - 2025/3/24
Y1 - 2025/3/24
N2 - The binding affinity between a drug molecule and its target, measured by the absolute binding free energy (ABFE), is a crucial factor in the lead discovery phase of drug development. Recent research has highlighted the potential of in silico ABFE predictions to directly aid drug development by allowing for the ranking and prioritization of promising candidates. This work introduces an open-source Python workflow called FEP-SPell-ABFE, designed to automate ABFE calculations with minimal user involvement. The workflow requires only three key inputs: a receptor protein structure in PDB format, candidate ligands in SDF format, and a configuration file (config.yaml) that governs both the workflow and molecular dynamics simulation parameters. It produces a ranked list of ligands along with their binding free energies in the comma-separated values (CSV) format. The workflow leverages SLURM (Simple Linux Utility for Resource Management) for automating task execution and resource allocation across the modules. A usage example and several benchmark systems for validation are provided. The FEP-SPell-ABFE workflow, along with a practical example, is publicly accessible on GitHub at https://github.com/freeenergylab/FEP-SPell-ABFE, distributed under the MIT License.
AB - The binding affinity between a drug molecule and its target, measured by the absolute binding free energy (ABFE), is a crucial factor in the lead discovery phase of drug development. Recent research has highlighted the potential of in silico ABFE predictions to directly aid drug development by allowing for the ranking and prioritization of promising candidates. This work introduces an open-source Python workflow called FEP-SPell-ABFE, designed to automate ABFE calculations with minimal user involvement. The workflow requires only three key inputs: a receptor protein structure in PDB format, candidate ligands in SDF format, and a configuration file (config.yaml) that governs both the workflow and molecular dynamics simulation parameters. It produces a ranked list of ligands along with their binding free energies in the comma-separated values (CSV) format. The workflow leverages SLURM (Simple Linux Utility for Resource Management) for automating task execution and resource allocation across the modules. A usage example and several benchmark systems for validation are provided. The FEP-SPell-ABFE workflow, along with a practical example, is publicly accessible on GitHub at https://github.com/freeenergylab/FEP-SPell-ABFE, distributed under the MIT License.
UR - https://www.scopus.com/pages/publications/105001074009
U2 - 10.1021/acs.jcim.4c01986
DO - 10.1021/acs.jcim.4c01986
M3 - 文章
C2 - 40029615
AN - SCOPUS:105001074009
SN - 1549-9596
VL - 65
SP - 2711
EP - 2721
JO - Journal of Chemical Information and Modeling
JF - Journal of Chemical Information and Modeling
IS - 6
ER -