Identification of important chemical features of 11β-hydroxysteroid dehydrogenase type1 inhibitors: application of ligand based virtual screening and density functional theory

11β-Hydroxysteroid dehydrogenase type1 (11βHSD1) regulates the conversion from inactive cortisone to active cortisol. Increased cortisol results in diabetes, hence quelling the activity of 11βHSD1 has been thought of as an effective approach for the treatment of diabetes. Quantitative hypotheses were developed and validated to identify the critical chemical features with reliable geometric constraints that contribute to the inhibition of 11βHSD1 function. The best hypothesis, Hypo1, which contains one-HBA; one-Hy-Ali, and two-RA features, was validated using Fischer's randomization method, a test and a decoy set. The well validated, Hypo1, was used as 3D query to perform a virtual screening of three different chemical databases. Compounds selected by Hypo1 in the virtual screening were filtered by applying Lipinski's rule of five, ADMET, and molecular docking. Finally, five hit compounds were selected as virtual novel hit molecules for 11βHSD1 based on their electronic properties calculated by Density functional theory.     

Exploration of Novel Xanthine Oxidase Inhibitors Based on 1,6-Dihydropyrimidine-5-Carboxylic Acids by an Integrated in Silico Study

Xanthine oxidase (XO) is an important target for the effective treatment of hyperuricemia-associated diseases. A series of novel 2-substituted 6-oxo-1,6-dihydropyrimidine-5-carboxylic acids (ODCs) as XO inhibitors (XOIs) with remarkable activities have been reported recently. To better understand the key pharmacological characteristics of these XOIs and explore more hit compounds, in the present study, the three-dimensional quantitative structure–activity relationship (3D-QSAR), molecular docking, pharmacophore modeling, and molecular dynamics (MD) studies were performed on 46 ODCs. The constructed 3D-QSAR models exhibited reliable predictability with satisfactory validation parameters, including q² = 0.897, R² = 0.983, r_pred² = 0.948 in a CoMFA model, and q² = 0.922, R² = 0.990, r_pred² = 0.840 in a CoMSIA model. Docking and MD simulations further gave insights into the binding modes of these ODCs with the XO protein. The results indicated that key residues Glu802, Arg880, Asn768, Thr1010, Phe914, and Phe1009 could interact with ODCs by hydrogen bonds, π-π stackings, or hydrophobic interactions, which might be significant for the activity of these XOIs. Four potential hits were virtually screened out using the constructed pharmacophore model in combination with molecular dockings and ADME predictions. The four hits were also found to be relatively stable in the binding pocket by MD simulations. The results in this study might provide effective information for the design and development of novel XOIs.     

Probing small-molecule binding to cytochrome P450 2D6 and 2C9: An in silico protocol for generating toxicity alerts

Drug metabolism, toxicity, and their interaction profiles are major issues in the drug-discovery and lead-optimization processes. The cytochromes P450 (CYPs) 2D6 and 2C9 are enzymes involved in the oxidative metabolism of a majority of marketed drugs. Therefore, the prediction of the binding affinity towards CYP2D6 and CYP2C9 would be beneficial for identifying cytochrome-mediated adverse effects triggered by drugs or chemicals (e.g., toxic reactions, drug-drug, and food-drug interactions). By identifying the binding mode by using pharmacophore prealignment, automated flexible docking, and by quantifying the binding affinity by multidimensional QSAR (mQSAR), we validated a model family of 56 compounds (46 training, 10 test) and 85 compounds (68 training, 17 test) for CYP2D6 and CYP2C9, respectively. The correlation with the experimental data (cross-validated r2=0.811 for CYP2D6 and 0.687 for CYP2C9) suggests that our approach is suited for predicting the binding affinity of compounds towards CYP2D6 and CYP2C9. The models were challenged by Y-scrambling and by testing an external dataset of binding compounds (15 compounds for CYP2D6 and 40 for CYP2C9). To assess the probability of false-positive predictions, datasets of nonbinders (64 compounds for CYP2D6 and 56 for CYP2C9) were tested by using the same protocol. The two validated mQSAR models were subsequently added to the VirtualToxLab (VTL, http://www.virtualtoxlab.org).     

In Silico Screening of Novel α1-GABAA Receptor PAMs towards Schizophrenia Based on Combined Modeling Studies of Imidazo [1,2-a]-Pyridines

The ionotropic GABA_A receptor (GABA_AR) has been proven to be an important target of atypical antipsychotics. A novel series of imidazo [1,2-a]-pyridine derivatives, as selective positive allosteric modulators (PAMs) of α1-containing GABA_ARs with potent antipsychotic activities, have been reported recently. To better clarify the pharmacological essentiality of these PAMs and explore novel antipsychotics hits, three-dimensional quantitative structure–activity relationships (3D-QSAR), molecular docking, pharmacophore modeling, and molecular dynamics (MD) were performed on 33 imidazo [1,2-a]-pyridines. The constructed 3D-QSAR models exhibited good predictive abilities. The dockings results and MD simulations demonstrated that hydrogen bonds, π–π stackings, and hydrophobic interactions play essential roles in the binding of these novel PAMs in the GABA_AR binding pocket. Four hit compounds (DS01–04) were then screened out by the combination of the constructed models and computations, including the pharmacophore model, Topomer Search, molecular dockings, ADME/T predictions, and MD simulations. The compounds DS03 and DS04, with higher docking scores and better predicted activities, were also found to be relatively stable in the binding pocket by MD simulations. These results might provide a significant theoretical direction or information for the rational design and development of novel α1-GABA_AR PAMs with antipsychotic activities.     

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.     

Targeting the SARS-CoV-2 HR1 with Small Molecules as Inhibitors of the Fusion Process

The rapid and global propagation of the novel human coronavirus that causes severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has produced an immediate urgency to discover promising targets for the treatment of this virus. In this paper, we studied the spike protein S2 domain of SARS-CoV-2 as it is the most conserved component and controls the crucial fusion process of SARS-CoV-2 as a target for different databases of small organic compounds. Our in silico methodology, based on pharmacophore modeling, docking simulation and molecular dynamics simulations, was first validated with ADS-J1, a potent small-molecule HIV fusion inhibitor that has already proved effective in binding the HR1 domain and inhibiting the fusion core of SARS-CoV-1. It then focused on finding novel small molecules and new peptides as fusion inhibitors. Our methodology identified several small molecules and peptides as potential inhibitors of the fusion process. Among these, NF 023 hydrate (MolPort-006-822-583) is one of the best-scored compounds. Other compounds of interest are ZINC00097961973, Salvianolic acid, Thalassiolin A and marine_160925_88_2. Two interesting active peptides were also identified: AP00094 (Temporin A) and AVP1227 (GBVA5). The inhibition of the spike protein of SARS-CoV-2 is a valid target to inhibit the virus entry in human cells. The discussed compounds reported in this paper led to encouraging results for future in vitro tests against SARS-CoV-2.     

Binding Thermodynamics and Dissociation Kinetics Analysis Uncover the Key Structural Motifs of Phenoxyphenol Derivatives as the Direct InhA Inhibitors and the Hotspot Residues of InhA

Given the current epidemic of multidrug-resistant tuberculosis, there is an urgent need to develop new drugs to combat drug-resistant tuberculosis. Direct inhibitors of the InhA target do not require activation and thus can overcome drug resistance caused by mutations in drug-activating enzymes. In this work, the binding thermodynamic and kinetic information of InhA to its direct inhibitors, phenoxyphenol derivatives, were explored through multiple computer-aided drug design (CADD) strategies. The results show that the van der Waals interactions were the main driving force for protein–ligand binding, among which hydrophobic residues such as Tyr158, Phe149, Met199 and Ile202 have high energy contribution. The AHRR pharmacophore model generated by multiple ligands demonstrated that phenoxyphenol derivatives inhibitors can form pi–pi stacking and hydrophobic interactions with InhA target. In addition, the order of residence time predicted by random acceleration molecular dynamics was consistent with the experimental values. The intermediate states of these inhibitors could form hydrogen bonds and van der Waals interactions with surrounding residues during dissociation. Overall, the binding and dissociation mechanisms at the atomic level obtained in this work can provide important theoretical guidance for the development of InhA direct inhibitors with higher activity and proper residence time.     

Highly potent HIV inhibition: engineering a key anti-HIV structure from PSC-RANTES into MIP-1 beta/CCL4

The HIV coreceptor CCR5 is a validated target for both the prevention and therapy of HIV infection. PSC-RANTES, an N-terminally modified analogue of one of the natural chemokine ligands of CCR5 (RANTES/CCL5), is a potent inhibitor of HIV entry into target cells. Here, we set out to engineer the anti-HIV activity of PSC-RANTES into another natural CCR5 ligand (MIP-1beta/CCL4), by grafting into it the key N-terminal pharmacophore region from PSC-RANTES. We were able to identify MIP-1beta/CCL4 analogues that retain the receptor binding profile of MIP-1beta/CCL4, but acquire the very high anti-HIV potency and characteristic inhibitory mechanism of PSC-RANTES. Unexpectedly, we discovered that in addition to N-terminal structures from PSC-RANTES, the side chain of Lys33 is also necessary for full anti-HIV potency.