Virtual screening filters for the design of type II p38 MAP kinase inhibitors: A fragment based library generation approach

Badrinarayan, Preethi; Sastry, G. Narahari

doi:10.1016/j.jmgm.2011.12.009

Cited by 34 publications

(17 citation statements)

References 66 publications

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“…To optimize the chemotype requirements for the GDP/GTP-bound conformations, fragment library was generated by pruning screened molecules from these databases on the basis of binding interactions and were further suggested according to the (or) part of the pocket occupied. 44 …”

Section: Methodsmentioning

confidence: 99%

Lead identification for the K-Ras protein: virtual screening and combinatorial fragment-based approaches

Pathan¹,

Panthi²,

Khan³

et al. 2016

OTT

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ObjectiveKirsten rat sarcoma (K-Ras) protein is a member of Ras family belonging to the small guanosine triphosphatases superfamily. The members of this family share a conserved structure and biochemical properties, acting as binary molecular switches. The guanosine triphosphate-bound active K-Ras interacts with a range of effectors, resulting in the stimulation of downstream signaling pathways regulating cell proliferation, differentiation, and apoptosis. Efforts to target K-Ras have been unsuccessful until now, placing it among high-value molecules against which developing a therapy would have an enormous impact. K-Ras transduces signals when it binds to guanosine triphosphate by directly binding to downstream effector proteins, but in case of guanosine diphosphate-bound conformation, these interactions get disrupted.MethodsIn the present study, we targeted the nucleotide-binding site in the “on” and “off” state conformations of the K-Ras protein to find out suitable lead compounds. A structure-based virtual screening approach has been used to screen compounds from different databases, followed by a combinatorial fragment-based approach to design the apposite lead for the K-Ras protein.ResultsInterestingly, the designed compounds exhibit a binding preference for the “off” state over “on” state conformation of K-Ras protein. Moreover, the designed compounds’ interactions are similar to guanosine diphosphate and, thus, could presumably act as a potential lead for K-Ras. The predicted drug-likeness properties of these compounds suggest that these compounds follow the Lipinski’s rule of five and have tolerable absorption, distribution, metabolism, excretion and toxicity values.ConclusionThus, through the current study, we propose targeting only “off” state conformations as a promising strategy for the design of reversible inhibitors to pharmacologically inhibit distinct conformations of K-Ras protein.

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Section: Methodsmentioning

confidence: 99%

Lead identification for the K-Ras protein: virtual screening and combinatorial fragment-based approaches

Pathan¹,

Panthi²,

Khan³

et al. 2016

OTT

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“…A plausible reason for the poor performance is that the multiple-ligand templates we used here did not correctly reflect the pocket environments. For example, it is well known that p38 has two largely distinct binding conformations, DFG-in and DFG-out, and that their binding sites to their ligands are spatially largely separated [ 14 ]. However, as shown in Figure 4(E) , the multiple-ligand template for p38 we used here has only a single densely populated region and thus it should not correctly reflect the highly flexible pocket environment of p38.…”

Section: Resultsmentioning

confidence: 99%

Importance of consensus region of multiple-ligand templates in a virtual screening method

et al. 2016

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We discuss methods and ideas of virtual screening (VS) for drug discovery by examining the performance of VS-APPLE, a recently developed VS method, which extensively utilizes the tendency of single binding pockets to bind diversely different ligands, i.e. promiscuity of binding pockets. In VS-APPLE, multiple ligands bound to a pocket are spatially arranged by maximizing structural overlap of the protein while keeping their relative position and orientation with respect to the pocket surface, which are then combined into a multiple-ligand template for screening test compounds. To greatly reduce the computational cost, comparison of test compound structures are made only with limited regions of the multiple-ligand template. Even when we use the narrow regions with most densely populated atoms for the comparison, VSAPPLE outperforms other conventional VS methods in terms of Area Under the Curve (AUC) measure. This region with densely populated atoms corresponds to the consensus region among multiple ligands. It is typically observed that expansion of the sampled region including more atoms improves screening efficiency. However, for some target proteins, considering only a small consensus region is enough for the effective screening of test compounds. These results suggest that the performance test of VS methods sheds light on the mechanisms of protein-ligand interactions, and elucidation of the protein-ligand interactions should further help improvement of VS methods.

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“…5 ). The existing inhibitors can be reengineered with sub-pocket specific chemotypes or fragments to achieve specificity [83] , [84] . Although the basic framework of kinase inhibitors is identical, the nature of the preferred chemotypes varies.…”

Section: Resultsmentioning

confidence: 99%

Specificity Rendering ‘Hot-Spots’ for Aurora Kinase Inhibitor Design: The Role of Non-Covalent Interactions and Conformational Transitions

Badrinarayan

Sastry

2014

PLoS ONE

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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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Virtual screening filters for the design of type II p38 MAP kinase inhibitors: A fragment based library generation approach

Cited by 34 publications

References 66 publications

Lead identification for the K-Ras protein: virtual screening and combinatorial fragment-based approaches

Lead identification for the K-Ras protein: virtual screening and combinatorial fragment-based approaches

Importance of consensus region of multiple-ligand templates in a virtual screening method

Specificity Rendering ‘Hot-Spots’ for Aurora Kinase Inhibitor Design: The Role of Non-Covalent Interactions and Conformational Transitions

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