Drug discovery continues to be one of the greatest contemporary challenges and rational application of modelling approaches is the first important step to obtain lead compounds, which can be optimised further. Virtual high throughput screening (VHTS) is one of the efficient approaches to obtain lead structures for a given target. Strategic application of different screening filters like pharmacophore mapping, shape-based, ligand-based, molecular similarity etc., in combination with other drug design protocols provide invaluable insights in lead identification and optimization. Screening of large databases using these computational methods provides potential lead compounds, thus triggering a meaningful interplay between computations and experiments. In this review, we present a critical account on the relevance of molecular modelling approaches in general, lead optimization and virtual screening methods in particular for new lead identification. The importance of developing reliable scoring functions for non-bonded interactions has been highlighted, as it is an extremely important measure for the reliability of scoring function. The lead optimization and new lead design has also been illustrated with examples. The importance of employing a combination of general and target specific screening protocols has also been highlighted.

A new knowledge, structure, and sequence based strategy involving the effective exploitation of the DFG-out conformation is delineated. A comprehensive analysis of the structure, sequence, cocrystals, and active sites of p38 MAP kinase crystal structures present in Protein Data Bank (PDB) and the FDA approved MAP kinase drugs has been done, and the information is used for the design of type II leads. The 98 crystal structures, 138 cocrystals, and 31 FDA drugs comprise of 7 different sequences of 2 organisms viz., Homo sapiens and Mus musculus differing in sequence length, constituting both homo- and heterochains. Multiple sequence alignment with ClustalW showed >95% sequence similarity with highly conserved domains and a high propensity for mutations in the activation loop. The bound ligands were extracted, and their interactions with DFG in and out conformations were studied. These cocrystals and FDA drugs were fragmented on the basis of their binding interactions and their affinity to ATP and allosteric sites. The fragment library thus generated contains 106 fragments with overlapping drug fragments. A blue print constituting three main parts viz., head (ATP region), linker (DFG region), and tail (allosteric region) has thus been formulated and used to design 64 type II p38 MAP kinase inhibitors. The above strategy has been employed to design potent type II p38 MAP kinase inhibitors, which are shown to be very promising.

Kinases are one of the most popular classes of drug targets as they are involved in signal transduction pathways, which are wired through a phosphotransfer cascade and elicit a number of important and essential physiological responses. Kinase specificity has emerged as one of the major issues to be addressed in drug discovery approaches. In most kinases the active site is the ATP binding site and finding suitable hits which maximize the affinity of binding has been traditionally important to obtain the type I inhibitors. While type I inhibitors have effective binding affinity more often than not they encounter side-effects usually associated with specificity. Therefore in recent times it has become indispensable to optimize specificity for developing effective kinase inhibitors. The review presents an overview of kinase drug discovery and the different strategies used to date for the design of kinase leads accounting for their success and failure. A number of strategies exploiting different aspects of kinases like allosteric site, size of the gatekeeper residue, DFG-loop, chemotype selectivity, non-covalent interactions, salt-bridge, solvation, etc. have been explored to circumvent the specificity problem in kinases. The probable hot-spots in kinases having a propensity to bring in specificity have been delineated with special emphasis on the design of type II inhibitors with increased specificity from existing type I using fragment tailoring approach. In this review we illustrate the current strategies by taking p38 MAP kinase as a model and expect that such strategies are general and can be extended to the other members of the kinase family.

The present study examines the conformational transitions occurring among the major structural motifs of Aurora kinase (AK) concomitant with the DFG-flip and deciphers the role of non-covalent interactions in rendering specificity. Multiple sequence alignment, docking and structural analysis of a repertoire of 56 crystal structures of AK from Protein Data Bank (PDB) has been carried out. The crystal structures were systematically categorized based on the conformational disposition of the DFG-loop [in (DI) 42, out (DO) 5 and out-up (DOU) 9], G-loop [extended (GE) 53 and folded (GF) 3] and αC-helix [in (CI) 42 and out (CO) 14]. The overlapping subsets on categorization show the inter-dependency among structural motifs. Therefore, the four distinct possibilities a) 2W1C (DI, CI, GE) b) 3E5A (DI, CI, GF) c) 3DJ6 (DI, CO, GF) d) 3UNZ (DOU, CO, GF) along with their co-crystals and apo-forms were subjected to molecular dynamics simulations of 40 ns each to evaluate the variations of individual residues and their impact on forming interactions. The non-covalent interactions formed by the 157 AK co-crystals with different regions of the binding site were initially studied with the docked complexes and structure interaction fingerprints. The frequency of the most prominent interactions was gauged in the AK inhibitors from PDB and the four representative conformations during 40 ns. Based on this study, seven major non-covalent interactions and their complementary sites in AK capable of rendering specificity have been prioritized for the design of different classes of inhibitors.

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