Lin_F9

Lin_F9 enhances scoring accuracy for protein–ligand docking by using a linear empirical scoring function composed of nine empirically derived terms, including a unified metal bond term to model metal–ligand interactions.


Key Features:

  • Linear empirical scoring function: Combines nine empirically derived terms in a linear functional form to score protein–ligand interactions.
  • Unified metal bond term: Includes a unified metal bond term specifically tailored to describe metal–ligand interactions.
  • Multistage fitting with explicit waters: Parameters were obtained via a multistage fitting protocol that used explicit water-included structures.
  • Benchmark performance (CASF-2016): Demonstrated scoring power on CASF-2016 with Pearson correlation coefficients of 0.680 for original crystal poses and 0.687 for locally optimized poses versus 34 other classical scoring functions.
  • Performance versus Vina and docking scenarios: Outperformed Vina in scoring and ranking across end-to-end flexible docking scenarios using single or ensemble protein receptor structures in CASF-2016 and D3R Grand Challenge (GC4) test sets.
  • Implementation: Implemented in a fork of Smina.

Scientific Applications:

  • Structure-based drug design: Improves scoring and ranking of protein–ligand complexes for structure-based drug design studies.
  • Modeling metal-containing complexes: Models metal–ligand interactions in metalloproteins and metalloenzymes via the unified metal bond term.
  • Docking benchmark and method development: Serves as a benchmarked scoring function for docking method evaluation using CASF-2016 and D3R Grand Challenge (GC4) datasets.
  • Flexible and ensemble receptor docking: Applicable to end-to-end flexible docking workflows using single or ensemble protein receptor structures.

Methodology:

Parameters were fitted by a multistage fitting protocol using explicit water-included structures; performance was evaluated on CASF-2016 and D3R Grand Challenge (GC4) benchmarks using Pearson correlation coefficients; implemented in a fork of Smina.

Topics

Details

License:
GPL-3.0
Cost:
Free of charge
Tool Type:
command-line tool
Operating Systems:
Linux
Programming Languages:
Python, Shell
Added:
2/20/2022
Last Updated:
2/20/2022

Operations

Publications

Yang C, Zhang Y. Lin_F9: A Linear Empirical Scoring Function for Protein–Ligand Docking. Journal of Chemical Information and Modeling. 2021;61(9):4630-4644. doi:10.1021/acs.jcim.1c00737. PMID:34469692. PMCID:PMC8478859.

PMID: 34469692
PMCID: PMC8478859
Funding: - National Institute of General Medical Sciences: R35-GM127040