Fusion of Structure and Ligand Based Methods for Identification of Novel CDK2 Inhibitors

Cyclin dependent kinases play a central role in cell cycle regulation which makes them a promising target with multifarious therapeutic potential. CDK2 regulates various events of the eukaryotic cell division cycle, and the pharmacological evidence indicates that overexpression of CDK2 causes abnormal cell-cycle regulation, which is directly associated with hyperproliferation of cancer cells. Therefore, CDK2 is regarded as a potential target molecule for anticancer medication. Thus, to decline CDK2 activity by potential lead compounds has proved to be an effective treatment for cancer. The availability of a large number of X-ray crystal structures and known inhibitors of CDK2 provides a gateway to perform efficient computational studies on this target. With the aim to identify new chemical entities from commercial libraries, with increased inhibitory potency for CDK2, ligand and structure based computational drug designing approaches were applied. A druglike library of 50,000 compounds from ChemDiv and ChemBridge databases was screened against CDK2, and 110 compounds were identified using the parallel application of these models. On <i>in vitro</i> evaluation of 40 compounds, seven compounds were found to have more than 50% inhibition at 10 μM. MD studies of the hits revealed the stability of these inhibitors and pivotal role of Glu81 and Leu83 for binding with CDK2. The overall study resulted in the identification of four new chemical entities possessing CDK2 inhibitory activity

Computationally Guided Identification of Novel <i>Mycobacterium tuberculosis</i> GlmU Inhibitory Leads, Their Optimization, and in Vitro Validation

<i>Mycobacterium tuberculosis</i> (Mtb) infections are causing serious health concerns worldwide. Antituberculosis drug resistance threatens the current therapies and causes further need to develop effective antituberculosis therapy. GlmU represents an interesting target for developing novel Mtb drug candidates. It is a bifunctional acetyltransferase/uridyltransferase enzyme that catalyzes the biosynthesis of UDP-<i>N</i>-acetyl-glucosamine (UDP-GlcNAc) from glucosamine-1-phosphate (GlcN-1-P). UDP-GlcNAc is a substrate for the biosynthesis of lipopolysaccharide and peptidoglycan that are constituents of the bacterial cell wall. In the current study, structure and ligand based computational models were developed and rationally applied to screen a drug-like compound repository of 20 000 compounds procured from ChemBridge DIVERSet database for the identification of probable inhibitors of Mtb GlmU. The in vitro evaluation of the in silico identified inhibitor candidates resulted in the identification of 15 inhibitory leads of this target. Literature search of these leads through SciFinder and their similarity analysis with the PubChem training data set (AID 1376) revealed the structural novelty of these hits with respect to Mtb GlmU. IC₅₀ of the most potent identified inhibitory lead (5810599) was found to be 9.018 ± 0.04 μM. Molecular dynamics (MD) simulation of this inhibitory lead (5810599) in complex with protein affirms the stability of the lead within the binding pocket and also emphasizes on the key interactive residues for further designing. Binding site analysis of the acetyltransferase pocket with respect to the identified structural moieties provides a thorough analysis for carrying out the lead optimization studies

Benzothiazole Derivative as a Novel <i>Mycobacterium tuberculosis</i> Shikimate Kinase Inhibitor: Identification and Elucidation of Its Allosteric Mode of Inhibition

<i>Mycobacterium tuberculosis</i> shikimate kinase (Mtb-SK) is a key enzyme involved in the biosynthesis of aromatic amino acids through the shikimate pathway. Since it is proven to be essential for the survival of the microbe and is absent from mammals, it is a promising target for anti-TB drug discovery. In this study, a combined approach of <i>in silico</i> similarity search and pharmacophore building using already reported inhibitors was used to screen a procured library of 20,000 compounds of the commercially available ChemBridge database. From the <i>in silico</i> screening, 15 hits were identified, and these hits were evaluated <i>in vitro</i> for Mtb-SK enzyme inhibition. Two compounds presented significant enzyme inhibition with IC₅₀ values of 10.69 ± 0.9 and 46.22 ± 1.2 μM. The best hit was then evaluated for the <i>in vitro</i> mode of inhibition where it came out to be an uncompetitive and noncompetitive inhibitor with respect to shikimate (SKM) and ATP, respectively, suggesting its binding at an allosteric site. Potential binding sites of Mtb-SK were identified which confirmed the presence of an allosteric binding pocket apart from the ATP and SKM binding sites. The docking simulations were performed at this pocket in order to find the mode of binding of the best hit in the presence of substrates and the products of the enzymatic reaction. Molecular dynamics (MD) simulations elucidated the probability of inhibitor binding at the allosteric site in the presence of ADP and shikimate-3-phosphate (S-3-P), that is, after the formation of products of the reaction. The inhibitor binding may prevent the release of the product from Mtb-SK, thereby inhibiting its activity. The binding stability and the key residue interactions of the inhibitor to this product complex were also revealed by the MD simulations. Residues ARG43, ILE45, and PHE57 were identified as crucial that were involved in interactions with the best hit. This is the first report of an allosteric binding site of Mtb-SK, which could largely address the selectivity issue associated with kinase inhibitors

2-D representation of interactions of UGT86C4 and UGT94F2.

<p>2-D representation of the interaction figure (in pink) of kaempferol with UGT86C4 (A), and 2-D interaction figure of 7-deoxyloganetin with UGT94F2 (B).</p

Molecular docking of UGT86C4.

<p>Diagram showing (A) kaempferol (B) naringenin (C) apigenin (D) 7-deoxyloganetin (E) 7-deoxyloganetic acid and (F) iridotrial docked into the proposed binding pockets of UGT86C4.</p

Nucleotide sequences of <i>Picrorhiza</i> UGT gene promoters.

<p>Nucleotide sequences of the UGT86C4 (A) and UGT94F2 (B) gene promoters. Numbering starts from the predicted transcription start site (dark green shaded). The putative core promoter consensus sequences and the motifs with significant similarity to the previously identified <i>cis</i>-acting elements are shaded and the names are given.</p

Molecular Characterization of UGT94F2 and UGT86C4, Two Glycosyltransferases from <i>Picrorhiza kurrooa</i>: Comparative Structural Insight and Evaluation of Substrate Recognition

<div><p>Uridine diphosphate glycosyltransferases (UGTs) are pivotal in the process of glycosylation for decorating natural products with sugars. It is one of the versatile mechanisms in determining chemical complexity and diversity for the production of suite of pharmacologically active plant natural products. <i>Picrorhiza kurrooa</i> is a highly reputed medicinal herb known for its hepato-protective properties which are attributed to a novel group of iridoid glycosides known as picrosides. Although the plant is well studied in terms of its pharmacological properties, very little is known about the biosynthesis of these important secondary metabolites. In this study, we identified two family-1 glucosyltransferases from <i>P. kurrooa</i>. The full length cDNAs of UGT94F4 and UGT86C4 contained open reading frames of 1455 and 1422 nucleotides, encoding polypeptides of 484 and 473 amino acids respectively. UGT94F2 and UGT86C4 showed differential expression pattern in leaves, rhizomes and inflorescence. To elucidate whether the differential expression pattern of the two <i>Picrorhiza</i> UGTs correlate with transcriptional regulation <i>via</i> their promoters and to identify elements that could be recognized by known iridoid-specific transcription factors, upstream regions of each gene were isolated and scanned for putative <i>cis</i>-regulatory elements. Interestingly, the presence of <i>cis</i>-regulatory elements within the promoter regions of each gene correlated positively with their expression profiles in response to different phytohormones. HPLC analysis of picrosides extracted from different tissues and elicitor-treated samples showed a significant increase in picroside levels, corroborating well with the expression profile of UGT94F2 possibly indicating its implication in picroside biosynthesis. Using homology modeling and molecular docking studies, we provide an insight into the donor and acceptor specificities of both UGTs identified in this study. UGT94F2 was predicted to be an iridoid-specific glucosyltransferase having maximum binding affinity towards 7-deoxyloganetin while as UGT86C4 was predicted to be a kaempferol-specific glucosyltransferase. These are the first UGTs being reported from <i>P. kurrooa.</i></p></div

A schematic diagram of the proposed picroside pathway in <i>Picrorhiza kurrooa.</i>

<p>Picrosides are derived from geranyl diphosphate that can be synthesized both from cytoplasmic MVA and plastidic MEP pathways. CPR: cytochrome P450 reductase; G10H: geraniol 10-hydroxylase; 10 HGO: 10-hydroxygeraniol oxidoreductase; IRS: Iridoid synthase; PAL: phenylalanine ammonia-lyase; C4H: cinnamoyl 4-hydroxylase; Route I: The route leading to the biosynthesis of secologanin, Route II: The route leading to the biosynthesis to picrosides <i>via</i> catalpol. Adapted from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0073804#pone.0073804-Damtoft1" target="_blank">[62]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0073804#pone.0073804-Mahmoud1" target="_blank">[63]</a>.</p

Three dimensional models and conserved residue prediction for UGT86C4 and UGT94F2.

<p>A and B: Ribbon display of the 3-D structures of UGT86C4 and UGT94F2 as predicted by PHYRE2 web server, using crystal structure <i>Arabidopsis thaliana</i> UGT72B1 (Protein Data Bank (PDB) Id. 2VCH-A) as template for modeling of both the proteins. N and C-terminal domains are shown. Donor and acceptor sites are also shown. C and D: Predicted ligand binding sites as predicted by 3DLigandSite web server. E and F: Evolutionary conserved residue analysis of UGT86C4 and UGT94F2 were performed using Consurf, an empirical Bayesian inference based web server. Residue conservation from variable to conserved is shown in blue (1) to violet (9). The residues involved in binding of the donor moieties are shown in the centre of the structures.</p

Molecular docking of UGT94F2.

<p>Diagram showing (A) kaempferol (B) naringenin (C) apigenin (D) 7-deoxyloganetin (E) 7-deoxyloganetic acid and (F) iridotrial docked into the proposed binding pockets of UGT94F2.</p