Receptor structure most affects molecular docking reproducibility scores
Which reported inputs govern molecular docking reproducibility? A benchmark from reporting audit to independent re-execution
Digital Libraries
Summary
Molecular docking is a computer method to predict how molecules, like drugs, fit into proteins. The authors studied which pieces of information are most important to reproduce these docking results accurately. They found that knowing the exact protein structure is the biggest factor, while small changes in parameters like search area have little effect. Identifying the molecule correctly and its charged state also matter but less so. This work helps show what details need to be reported to reliably repeat docking experiments.
What this means in practice
- •For computational chemists: Ensure exact receptor structures and clear ligand identities are reported to reliably reproduce docking scores.
- •For drug discovery teams: Use precise protein and ligand details from literature to validate docking results on different computing platforms.
Authors
Giap Duc Ha
Abstract
Computational docking results can be re-executed only when the molecular system and protocol are specified, yet reporting checklists do not quantify how strongly individual method fields affect the reported score. We combined a span-verified audit of 50 open-access papers with controlled one-factor perturbations, a Vinardo scoring-function check and a Vina cross-docking extension covering 12 targets in 7 protein families, and re-execution of 37 published claims on local and independent cloud infrastructure. Search-related fields were sparsely reported, but perturbing box centre, box size, exhaustiveness or random seed produced median absolute score changes of no more than 0.08 kcal mol$^{-1}$; ligand protonation and identity produced median changes of 0.19 and 0.29 kcal mol$^{-1}$, respectively, whereas receptor structure produced the largest change (1.02 kcal mol$^{-1}$; n = 85; P < 0.001), and 22% of 116 unique reported ligand strings remained unresolved or ambiguous after deterministic name normalization. These measurements yielded empirical field weights for the NewScience Evidence score and identified exact receptor structure, machine-resolvable ligand identity and protonation state as primary reporting elements; 29 of 37 local and 27 of 37 cloud re-executions were within 2.0 kcal mol$^{-1}$ of the reported score, but these descriptive rates do not estimate experimental replication or a calibrated probability of reproduction.