Ligand-based pharmacophore modeling and Bayesian approaches to identify c-Src inhibitors

Integration of ligand and structure-based pharmacophore screening for the identification of novel natural leads against Euchromatic histone lysine methyltransferase 2 (EHMT2/G9a)

Herein, we report a blended ligand and structure-based pharmacophore screening approach to identify new natural leads against the Protein Lysine Methyltransferase 2 (EHMT2/G9a). The EHMT2/G9a has been associated with Cancer, Alzheimer's, and aging and is considered an emerging drug target having no clinically passed inhibitor. Purposefully, we developed the ligand-based pharmacophore (Pharmacophore-L) based on the common features of known inhibitors and the structure-based pharmacophore (Pharmacophore-S) based on the interaction profile of available crystal structures. The Pharmacophore-L and Pharmacophore-S were subjected to multiple tiers of validations and utilized in combination for the screening of total 741543 compounds coming from multiple databases. Additional layers of stringency were applied in the screening process to test drug-likeness (using Lipinski's rule, Veber's rule, SMARTS and ADMET filtration), to rule out any toxicity (TOPKAT analysis). The interaction profiles, stabilities, and comparative analysis against the reference were carried out by flexible docking, MD simulation, and MM-GBSA analysis, which finally led to three leads as potential inhibitors of G9a.Communicated by Ramaswamy H. Sarma.

Development of pharmacophore models for AcrB protein and the identification of potential adjuvant candidates for overcoming efflux-mediated colistin resistance

Growing multi-drug resistance (MDR) among ESKAPE pathogens is a huge challenge. Increased resistance to last-resort antibiotics, like colistin, has further aggravated this. Efflux is identified as a major route of colistin resistance. So, finding an FDA-approved efflux inhibitor for potential application as an adjuvant to colistin was the primary objective of this study. E. coli-AcrB pump inhibitors and substrates were used to develop and validate the pharmacophoric model. Drugs confirming this pharmacophore were subjected to molecular docking to identify hits for the AcrB binding pocket. The efflux inhibition potential of the top hit was validated through the in vitro evaluation of the minimum inhibitory concentration (MIC) in combination with colistin. The checkerboard assay was done to demonstrate synergism, which was further corroborated by the Time-kill assay. Ten common pharmacophore hypotheses were successfully generated using substrate/inhibitors. Following enrichment analysis, AHHNR.100 was identified as the top-ranked hypothesis, and 207 unique compounds were found to conform to this hypothesis. The multi-step docking of these compounds against the AcrB protein revealed argatroban as the top non-antibiotic hit. This significantly inhibited the efflux activity of colistin-resistant clinical isolates K. pneumoniae (n = 1) and M. morganii (n = 2). Further, their combination with colistin enhanced the susceptibility of these isolates, and the effect was found to be synergistic. Accordingly, the time-kill assay of this combination showed 8-log and 2-log reductions against K. pneumoniae and M. morganii, respectively. In conclusion, this study found argatroban as a bacterial efflux inhibitor that can be potentially used to overcome efflux-mediated resistance.

Design, synthesis, and pharmacological evaluation of indazole carboxamides of N-substituted pyrrole derivatives as soybean lipoxygenase inhibitors

In this paper, we attempted to develop a novel class of compounds against lipoxygenase, a key enzyme in the biosynthesis of leukotrienes implicated in a series of inflammatory diseases. Given the absence of appropriate human 5-lipoxygenase crystallographic data, solved soybean lipoxygenase-1 and -3 structures were used as a template to generate an accurate pharmacophore model which was further used for virtual screening purposes. Eight compounds (1-8) have been derived from the in-house library consisting of N-substituted pyrroles conjugated with 5- or 6-indazole moieties through a carboxamide linker. This study led to the discovery of hit molecule 8 bearing a naphthyl group with the IC50 value of 22 μM according to soybean lipoxygenase in vitro assay. Isosteric replacement of naphthyl ring with quinoline moieties and reduction of carbonyl carboxamide group resulted in compounds 9-12 and 13, respectively. Compound 12 demonstrated the most promising enzyme inhibition. In addition, compounds 8 and 12 were found to reduce the carrageenan-induced paw edema in vivo by 52.6 and 49.8%, respectively. In view of the encouraging outcomes concerning their notable in vitro and in vivo anti-inflammatory activities, compounds 8 and 12 could be further optimized for the discovery of novel 5-lipoxygenase inhibitors in future. A structure-based 3D pharmacophore model was used in the virtual screening of in-house library to discover novel potential 5-lipoxygenase inhibitors.

3D QSAR pharmacophore based lead identification of G9a lysine methyltransferase towards epigenetic therapeutics

The G9a, Lysine Methyltransferase that methylates the histone 3 lysine 9 (H3K9) of the nucleosome, is an excellent epigenetic target having no clinically passed inhibitor currently owing to adverse in vivo ADMET toxicities. In this work, we have carried out detailed computational investigations to find novel and safer lead against the target using advanced 3 D QSAR pharmacophore screening of databases containing more than 400000 entrees of natural compounds. The screening was conducted at different levels at increasing stringencies by employing pharmacophore mapping, druglikenesses and interaction profiles of the selected to identify potential hit compounds. The potential hits were further screened by advanced flexible docking, ADME and toxicity analysis to eight hit compounds. Based on the comparative analysis of the hits with the reference inhibitor, we identified one lead inhibitor against the G9a, having better binding efficacy and a safer ADMET profile than the reference inhibitor. Finally, the results were further verified using robust molecular dynamics simulation and MM-GBSA binding energy calculation. The natural compounds are generally considered benign due to their long human uses and this is the first attempt of in silico screening of a large natural compound library against G9a to our best knowledge. Therefore, the finding of this study may add value towards the development of epigenetic therapeutics against the G9a.Communicated by Ramaswamy H. Sarma.

Hybrid Pharmacophore- and Structure-Based Virtual Screening Pipeline to Identify Novel EGFR Inhibitors That Suppress Non-Small Cell Lung Cancer Cell Growth

Dysregulated epidermal growth factor receptor (EGFR) expression is frequently observed in non-small cell lung cancer (NSCLC) growth and metastasis. Despite recent successes in the development of tyrosine kinase inhibitors (TKIs), inevitable resistance to TKIs has led to urgent calls for novel EGFR inhibitors. Herein, we report a rational workflow used to identify novel EGFR-TKIs by combining hybrid ligand- and structure-based pharmacophore models. Three types of models were developed in this workflow, including 3D QSAR-, common feature-, and structure-based EGFR-TK domain-containing pharmacophores. A National Cancer Institute (NCI) compound dataset was adopted for multiple-stage pharmacophore-based virtual screening (PBVS) of various pharmacophore models. The six top-scoring compounds were identified through the PBVS pipeline coupled with molecular docking. Among these compounds, NSC609077 exerted a significant inhibitory effect on EGFR activity in gefitinib-resistant H1975 cells, as determined by an enzyme-linked immunosorbent assay (ELISA). Further investigations showed that NSC609077 inhibited the anchorage-dependent growth and migration of lung cancer cells. Furthermore, NSC609077 exerted a suppressive effect on the EGFR/PI3K/AKT pathway in H1975 cells. In conclusion, these findings suggest that hybrid virtual screening may accelerate the development of targeted drugs for lung cancer treatment.

Ligand-based G Protein Coupled Receptor pharmacophore modeling: Assessing the role of ligand function in model development

Integral membrane proteins in the G Protein-Coupled Receptor (GPCR) class are attractive drug development targets. However, computational methods applicable to ligand discovery for many GPCR targets are restricted by limited numbers of known ligands. Pharmacophore models can be developed using variously sized training sets and applied in database mining to prioritize candidate ligands for subsequent validation. This in silico study assessed the impact of key pharmacophore modeling decisions that arise when known ligand numbers for a target of interest are low. GPCR included in this study are the adrenergic alpha-1A, 1D and 2A, adrenergic beta 2 and 3, kappa, delta and mu opioid, serotonin 1A and 2A, and the muscarinic 1 and 2 receptors, all of which have rich ligand data sets suitable to assess the performance of protocols intended for application to GPCR with limited ligand data availability. Impact of ligand function, potency and structural diversity in training set selection was assessed to define when pharmacophore modeling targeting GPCR with limited known ligands becomes viable. Pharmacophore elements and pharmacophore model selection criteria were also assessed. Pharmacophore model assessment was based on percent pharmacophore model generation failure, as well as Güner-Henry enrichment and goodness-of-hit scores. Three of seven pharmacophore element schemes evaluated in MOE 2018.0101, Unified, PCHD, and CHD, showed substantially lower failure rates and higher enrichment scores than the others. Enrichment and GH scores were used to compare construction protocol for pharmacophore models of varying purposes- such as function specific versus nonspecific ligand identification. Notably, pharmacophore models constructed from ligands of mixed functions (agonists and antagonists) were capable of enriching hitlists with active compounds, and therefore can be used when available sets of known ligands are limited in number.

Trioxolone Methyl, a Novel Cyano Enone-Bearing 18βH-Glycyrrhetinic Acid Derivative, Ameliorates Dextran Sulphate Sodium-Induced Colitis in Mice

Semi-synthetic triterpenoids, bearing cyano enone functionality in ring A, are considered to be novel promising therapeutic agents with complex inhibitory effects on tissue damage, inflammation and tumor growth. Previously, we showed that the cyano enone-containing 18βH-glycyrrhetinic acid derivative soloxolone methyl (SM) effectively suppressed the inflammatory response of macrophages in vitro and the development of influenza A-induced pneumonia and phlogogen-stimulated paw edema in vivo. In this work, we reported the synthesis of a novel 18βH-glycyrrhetinic acid derivative trioxolone methyl (TM), bearing a 2-cyano-3-oxo-1(2)-en moiety in ring A and a 12,19-dioxo-9(11),13(18)-dien moiety in rings C, D, and E. TM exhibited a high inhibitory effect on nitric oxide (II) production by lipopolysaccharide-stimulated J774 macrophages in vitro and dextran sulfate sodium (DSS)-induced colitis in mice, displaying higher anti-inflammatory activity in comparison with SM. TM effectively suppressed the DSS-induced epithelial damage and inflammatory infiltration of colon tissue, the hyperproduction of colonic neutral mucin and TNFα and increased glutathione synthesis. Our in silico analysis showed that Akt1, STAT3 and dopamine receptor D2 can be considered as mediators of the anti-colitic activity of TM. Our findings provided valuable information for a better understanding of the anti-inflammatory activity of cyano enone-bearing triterpenoids and revealed TM as a promising anti-inflammatory candidate.

Development of a Nicotinic Acetylcholine Receptor nAChR α7 Binding Activity Prediction Model

Despite the well-known adverse health effects associated with tobacco use, addiction to nicotine found in tobacco products causes difficulty in quitting among users. Nicotinic acetylcholine receptors (nAChRs) are the physiological targets of nicotine and facilitate addiction to tobacco products. The nAChR-α7 subtype plays an important role in addiction; therefore, predicting the binding activity of tobacco constituents to nAChR-α7 is an important component for assessing addictive potential of tobacco constituents. We developed an α7 binding activity prediction model based on a large training data set of 843 chemicals with human α7 binding activity data extracted from PubChem and ChEMBL. The model was tested using 1215 chemicals with rat α7 binding activity data from the same databases. Based on the competitive docking results, the docking scores were partitioned to the key residues that play important roles in the receptor-ligand binding. A decision forest was used to train the human α7 binding activity prediction model based on the partition of docking scores. Five-fold cross validations were conducted to estimate the performance of the decision forest models. The developed model was used to predict the potential human α7 binding activity for 5275 tobacco constituents. The human α7 binding activity data for 84 of the 5275 tobacco constituents were experimentally measured to confirm and empirically validate the prediction results. The prediction accuracy, sensitivity, and specificity were 64.3, 40.0, and 81.6%, respectively. The developed prediction model of human α7 may be a useful tool for high-throughput screening of potential addictive tobacco constituents.

Combiphore (Structure and Ligand Based Pharmacophore) - Approach for the Design of GPR40 Modulators in the Management of Diabetes

BACKGROUND

Pharmacophore mapping and molecular docking can be synergistically integrated to improve the drug design and discovery process. A rational strategy, combiphore approach, derived from the combined study of Structure and Ligand based pharmacophore has been described to identify novel GPR40 modulators.

METHODS

DISCOtech module from Discovery studio was used for the generation of the Structure and Ligand based pharmacophore models which gave hydrophobic aromatic, ring aromatic and negative ionizable as essential pharmacophoric features. The generated models were validated by screening active and inactive datasets, GH scoring and ROC curve analysis. The best model was exposed as a 3D query to screen the hits from databases like GLASS (GPCR-Ligand Association), GPCR SARfari and Mini-Maybridge. Various filters were applied to retrieve the hit molecules having good drug-like properties. A known protein structure of hGPR40 (pdb: 4PHU) having TAK-875 as ligand complex was used to perform the molecular docking studies; using SYBYL-X 1.2 software.

RESULTS AND CONCLUSION

Clustering both the models gave RMSD of 0.89. Therefore, the present approach explored the maximum features by combining both ligand and structure based pharmacophore models. A common structural motif as identified in combiphore for GPR40 modulation consists of the para-substituted phenyl propionic acid scaffold. Therefore, the combiphore approach, whereby maximum structural information (from both ligand and biological protein) is explored, gives maximum insights into the plausible protein-ligand interactions and provides potential lead candidates as exemplified in this study.