Molecular Docking Guided Drug Design and Discovery

Molecular docking, molecular dynamics simulation, and quantitative structure–activity relationships (QSAR) have emerged as rational alternatives to virtual screening or finding new active molecules. A fundamental goal for medicinal chemists is to develop a model for predicting the bioactivity of any series of chemical compounds based on molecular structure and target information. Molecular descriptors, biological activity-based regression analysis, and molecular docking or dynamics simulation approaches help in the identification of potential hit compounds or drug-like candidates. A modern drug discovery program uses computational modeling, molecular docking & dynamics simulation, and pharmacokinetics filters (ADMET) including Lipinski’s Rule of Five early as a screening and enrichment tool to estimate compounds that lack drug-like properties or chemicals predicted to elicit a toxic response. The basic assumption for all small molecules is based on the hypothesis that similar molecules have similar bioactivities. This study is called Structure–Activity Relationship (SAR). The underlying problem is how to define a slight difference on a structural level since each kind of activity, e.g., reaction ability, biotransformation, solubility, target activity, etc., may depend on another difference. Besides QSAR, molecular docking is also considered an essential tool for structure-based drug design and discovery programs. There are different molecular docking types and methods, which include various sampling algorithms and scoring functions. Flexible receptor docking methods are still a challenging task. From time to time, different docking approaches have evolved, such as Local Move Monte Carlo (LMMC), to improve the binding affinity prediction accuracy using a flexible protein approach. Besides QSAR and docking, researchers use a predictive pharmacokinetics (Absorption, Distribution, Metabolism, Excretion; ADME) approach for virtual screening of pharmacokinetics-compliant hits detection. Every method has some advantages and limitations. Therefore, more improvement is required in computational screening methods for identifying drug-like candidates.