Abstract

BackgroundDocking large ligands, and especially peptides, to protein receptors is still considered a challenge in computational structural biology. Besides the issue of accurately scoring the binding modes of a protein-ligand complex produced by a molecular docking tool, the conformational sampling of a large ligand is also often considered a challenge because of its underlying combinatorial complexity. In this study, we evaluate the impact of using parallelized and incremental paradigms on the accuracy and performance of conformational sampling when docking large ligands. We use five datasets of protein-ligand complexes involving ligands that could not be accurately docked by classical protein-ligand docking tools in previous similar studies.ResultsOur computational evaluation shows that simply increasing the amount of conformational sampling performed by a protein-ligand docking tool, such as Vina, by running it for longer is rarely beneficial. Instead, it is more efficient and advantageous to run several short instances of this docking tool in parallel and group their results together, in a straightforward parallelized docking protocol. Even greater accuracy and efficiency are achieved by our parallelized incremental meta-docking tool, DINC, showing the additional benefits of its incremental paradigm. Using DINC, we could accurately reproduce the vast majority of the protein-ligand complexes we considered.ConclusionsOur study suggests that, even when trying to dock large ligands to proteins, the conformational sampling of the ligand should no longer be considered an issue, as simple docking protocols using existing tools can solve it. Therefore, scoring should currently be regarded as the biggest unmet challenge in molecular docking.

Highlights

  • IntroductionEspecially peptides, to protein receptors is still considered a challenge in computational structural biology

  • Docking large ligands, and especially peptides, to protein receptors is still considered a challenge in computational structural biology

  • Results we present the results of our evaluation of several docking methodologies that involve the classical molecular docking tool Vina, including our parallelized incremental meta-docking tool, Docking incrementally (DINC)

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Summary

Introduction

Especially peptides, to protein receptors is still considered a challenge in computational structural biology. Besides the issue of accurately scoring the binding modes of a protein-ligand complex produced by a molecular docking tool, the conformational sampling of a large ligand is often considered a challenge because of its underlying combinatorial complexity. We evaluate the impact of using parallelized and incremental paradigms on the accuracy and performance of conformational sampling when docking large ligands. Proteins are essential components of living cells, performing structural functions, chemical reactions, transportation, signaling, and so on. Most of these functions involve molecular interactions with other proteins, nucleic acids or small molecules (i.e., ligands or peptides). Most molecules involve rotatable bonds allowing them to adopt alternative conformations

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