DOCKING AND SCORING IN VIRTUAL SCREENING FOR DRUG DISCOVERY

Abstract | Computational approaches that ‘dock’ small molecules into the structures of macromolecular targets and ‘score’ their potential complementarity to binding sites are widely used in hit identification and lead optimization. Indeed, there are now a number of drugs whose development was heavily influenced by or based on structure-based design and screening strategies, such as HIV protease inhibitors. Nevertheless, there remain significant challenges in the application of these approaches, in particular in relation to current scoring schemes. Here, we review key concepts and specific features of small-molecule–protein docking methods, highlight selected applications and discuss recent advances that aim to address the acknowledged limitations of established approaches. The number of proteins with a known three-dimensional structure is increasing rapidly, and structures produced by structural genomics initiatives are beginning to become publicly available1,2. The increase in the number of structural targets is in part due to improvements in techniques for structure determination, such as highthroughput X-ray crystallography3 . With large-scale structure-determination projects driven by genomics consortia, many current target proteins have been selected for their therapeutic potential. Computational methodologies have become a crucial component of many drug discovery programmes, from hit identification to lead optimization and beyond4–6, and approaches such as ligand-4 or structurebased virtual screening7 techniques are widely used in many discovery efforts. One key methodology — docking of small molecules to protein binding sites — was pioneered during the early 1980s8 , and remains a highly active area of research7 . When only the structure of a target and its active or binding site is available, high-throughput docking is primarily used as a hitidentification tool. However, similar calculations are often also used later on during lead optimization, when modifications to known active structures can quickly be tested in computer models before compound synthesis. Furthermore, docking can also contribute to the analysis of drug metabolism using structures such as cytochrome P450 isoforms9,10. Here, we review basic concepts and specific features of small-molecule–protein docking methods and several selected applications, with particular emphasis on hit identification and lead optimization, but do not specifically review protein–protein docking, which is less relevant for small-molecule drug discovery. We attempt to distinguish between the problems of docking compounds into target sites and of scoring docked conformations, because the available data indicate that numerous robust and accurate docking algorithms are available, whereas imperfections of scoring functions continue to be a major limiting factor. An introduction to docking The docking process involves the prediction of ligand conformation and orientation (or posing) within a targeted binding site (BOX 1). In general, there are two aims of docking studies: accurate structural modelling and correct prediction of activity. However, the identification of molecular features that are responsible for specific biological recognition, or the prediction of compound modifications that improve potency, are complex issues that are often difficult to understand and — even more so — to simulate on a computer. In view of these challenges, docking is generally devised as a multi-step process in which each step introduces one or more additional degrees of complexity11. The process begins with the application of docking algorithms that POSE small molecules in the active site. This in itself is challenging, as even relatively simple organic molecules can contain many conformational degrees of freedom. Sampling these degrees of freedom must be performed with sufficient accuracy to identify the conformation that best matches the receptor structure, and must be fast enough to permit the evaluation of thousands of compounds in a given docking run. Algorithms are complemented by SCORING FUNCTIONS that are designed to predict the biological activity through the evaluation of interactions between compounds and potential targets. Early scoring functions evaluated compound fits on the basis of calculations of approximate shape and electrostatic complementarities. Relatively simple scoring functions continue to be heavily used, at least during the early stages of docking simulations. Pre-selected conformers are often further evaluated using more complex scoring schemes with more detailed treatment of electrostatic and van der Waals interactions, and inclusion of at least some solvation or entropic effects7 . It should also be noted that ligand-binding events are driven by a combination of enthalpic and entropic effects, and that either entropy or enthalpy can dominate specific interactions. This often presents a conceptual problem for contemporary scoring functions (discussed below), because most of them are much more focused on capturing energetic than entropic effects. In addition to problems associated with scoring of compound conformations, other complications exist that make it challenging to accurately predict binding conformations and compound activity. These include, among others, limited resolution of crystallographic targets, inherent flexibility, induced fit or other conformational changes that occur on binding, and the participation of water molecules in protein–ligand interactions.Without doubt, the docking process is scientifically complex.