Abstract
The number of entries in the Protein Data Bank (PDB) has doubled in the last decade, and it has increased tenfold in the last twenty years. The availability of an ever-growing number of structures is having a huge impact on the Structure-Based Drug Discovery (SBDD), allowing investigation of new targets and giving the possibility to have multiple structures of the same macromolecule in a complex with different ligands. Such a large resource often implies the choice of the most suitable complex for molecular docking calculation, and this task is complicated by the plethora of possible posing and scoring function algorithms available, which may influence the quality of the outcomes. Here, we report a large benchmark performed on the PDBbind database containing more than four thousand entries and seventeen popular docking protocols. We found that, even in protein families wherein docking protocols generally showed acceptable results, certain ligand-protein complexes are poorly reproduced in the self-docking procedure. Such a trend in certain protein families is more pronounced, and this underlines the importance in identification of a suitable protein–ligand conformation coupled to a well-performing docking protocol.
Highlights
Since its introduction in the early 1980s [1], molecular docking has served to aid medicinal computational chemists in optimizing the drug discovery process
A docking protocol can be described as the combination of a search algorithm that samples the conformational space of a ligand, generating conformations for the ligand itself within a binding site, and a mathematical equation, called scoring function, which quantitatively evaluates the quality of such poses
The notable number of structures has offered the opportunity to evaluate the performance of molecular docking from different points of view, underlining how the efficiency of docking protocols may vary depending on the nature of the protein family
Summary
Since its introduction in the early 1980s [1], molecular docking has served to aid medicinal computational chemists in optimizing the drug discovery process. It should be considered that each docking software usually provides more than one scoring function in which performance ought to be evaluated in the protocol tuning step This means that computational chemists have at their disposal a plethora of different protocols when they face a docking calculation and, more importantly, the success, for example, of a Virtual Screening (VS) campaign, strongly relies on the accuracy of the protocol employed to place and rank the conformation of candidates into a target binding site [6]. More and more experimental structures are thankfully available, the range of possible combinations in protein conformation-docking protocol is growing in an unstoppable trend It is, clear that a crucial step in SBVS is the selection of a proper docking protocol and an appropriate protein conformation [7,8]. The notable number of structures has offered the opportunity to evaluate the performance of molecular docking from different points of view, underlining how the efficiency of docking protocols may vary depending on the nature of the protein family
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