Molecular docking using shape descriptors

TLDR

Molecular docking studies binding modes of interacting molecules, especially protein‑ligand interactions, but faces a combinatorial orientation‑space challenge. The study aims to describe and evaluate algorithms that enhance the efficiency and accuracy of a shape‑based docking method. The authors employ molecular organization and sampling techniques to eliminate exponential time dependence on molecular size, enabling testing on ten protein‑ligand systems, including seven protein ligands. The new algorithms accurately reproduce experimentally determined ligand configurations in all tested protein‑ligand systems.

Abstract

Abstract Molecular docking explores the binding modes of two interacting molecules. The technique is increasingly popular for studying protein‐ligand interactions and for drug design. A fundamental problem problem with molecular docking is that orientation space is very large and grows combinatorially with the number of degrees of freedom of the interacting molecules. Here, we describe and evaluate algorithms that improve the efficiency and accuracy of a shape‐based docking method. We use molecular organization and sampling techniques to remove the exponential time dependence on molecular size in docking calculations. The new techniques allow us to study systems that were prohibitively large for the original method. The new algorithms are tested in 10 different protein‐ligand systems, including 7 systems where the ligand is itself a protein. In all cases, the new algorithms successfully reproduce the experimentally determined configurations of the ligand in the protein.