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