Target-Bound Generated Pharmacophore Model to Improve the Pharmacophore-Based Virtual Screening: Identification of G-Protein Coupled Human CCR2 Receptors Inhibitors as Anti-Inflammatory Drugs

Hybrid Virtual Screening Approach to Predict Novel Natural Compounds against HIV-1 CCR5

BACKGROUND

Human immunodeficiency virus (HIV) infection continues to pose a major global health challenge. HIV entry into host cells via membrane fusion mediated by the viral envelope glycoprotein gp120/gp41 is a key step in the HIV life cycle. CCR5, expressed on CD4+ T cells and macrophages, acts as a coreceptor facilitating HIV-1 entry. The CCR5 antagonist maraviroc is used to treat HIV infection. However, it can cause adverse effects and has limitations such as only inhibiting CCR5-tropic viruses. There remains a need to develop alternative CCR5 inhibitors with improved safety profiles.

PROBLEM STATEMENT

Natural products may offer advantages over synthetic inhibitors including higher bioavailability, binding affinity, effectiveness, lower toxicity, and molecular diversity. However, screening the vast chemical space of natural compounds to identify novel CCR5 inhibitors presents challenges. This study aimed to address this gap through a hybrid ligand-based pharmacophore modeling and molecular docking approach to virtually screen large natural product databases.

METHODS

A reliable pharmacophore model was developed based on 311 known CCR5 antagonists and validated against an external data set. Five natural product databases containing over 306,000 compounds were filtered based on drug-likeness rules. The validated pharmacophore model screened the databases to identify 611 hits. Key residues of the CCR5 receptor crystal structure were identified for docking. The top hits were docked, and interactions were analyzed. Molecular dynamics simulations were conducted to examine complex stability. Computational prediction evaluated pharmacokinetic properties.

RESULTS

Three compounds exhibited similar interactions and binding energies to maraviroc. MD simulations demonstrated complex stability comparable to maraviroc. One compound showed optimal predicted absorption, minimal metabolism, and a lower likelihood of interactions than maraviroc.

CONCLUSION

This computational screening workflow identified three natural compounds with promising CCR5 inhibition and favorable pharmacokinetic profiles. One compound emerged as a lead based on bioavailability potential and minimal interaction risk. These findings present opportunities for developing alternative CCR5 antagonists and warrant further experimental investigation. Overall, the hybrid virtual screening approach proved effective for mining large natural product spaces to discover novel molecular entities with drug-like properties.

Exploring the structural determinants of novel xanthine derivatives as A2B adenosine receptor antagonists: a computational study

Adenosine is a ubiquitous endogenous nucleoside that controls numerous physiological functions via interacting with its specific G-coupled receptors. Activation of adenosine receptors (AdoRs), particularly A_2B AdoRs promotes the release of inflammatory cytokines; reduces vascular permeabilization and induces angiogenesis, thereby making A_2B AdoR becomes a potentially pharmacological target for drug development. Presently, for investigating the structural determinants of 164 xanthine derivatives as A_2B AdoR antagonists, we performed an in silico study integrating with 3D-QSAR, docking and molecular dynamics (MD) simulation. The obtained optimal model shows strong predictability (Q² = 0.647, R²_ncv = 0.955, and R²_pred = 0.848). Additionally, to explore the binding mode of the ligand with A_2B AdoR and to understand their binding mechanism, docking analysis, MD simulations (20 ns), and the calculation of binding free energy were also carried out. Finally, the structural determinants of these xanthine derivatives were identified and a total of 20 novel A_2B AdoR antagonists with improved potency were computationally designed, and their synthetic feasibility and selectivity were also evaluated. The information derived from the present study offers a better appreciation for exploring the interaction mechanism of the ligand with A_2B AdoR, which could be helpful for designing novel potent A_2B AdoR antagonists. Communicated by Ramaswamy H. Sarma.

Tailored-pharmacophore model to enhance virtual screening and drug discovery: a case study on the identification of potential inhibitors against drug-resistant Mycobacterium tuberculosis (3R)-hydroxyacyl-ACP dehydratases

Aim: Virtual screening (VS) is powerful tool in discovering molecular inhibitors that are most likely to bind to drug targets of interest. Herein, we introduce a novel VS approach, so-called ‘tailored-pharmacophore’, in order to explore inhibitors that overcome drug resistance. Methodology & results: The emergence and spread of drug resistance strains of tuberculosis is one of the most critical issues in healthcare. A tailored-pharmacophore approach was found promising to identify in silico predicted hit with better binding affinities in case of the resistance mutations in MtbHadAB as compared with thiacetazone, a prodrug used in the clinical treatment of tuberculosis. Conclusion: This approach can potentially be enforced for the discovery and design of drugs against a wide range of resistance targets.

Brain grants permission of access to Zika virus but denies entry to drugs: a molecular modeling perspective to infiltrate the boundary

Thein silicodesign of targeted Zika virus inhibitors.

Hybrid Receptor-Bound/MM-GBSA-Per-residue Energy-Based Pharmacophore Modelling: Enhanced Approach for Identification of Selective LTA4H Inhibitors as Potential Anti-inflammatory Drugs

Leukotriene A₄ hydrolase has been identified as an enzyme with dual anti- and pro-inflammatory role, thus, the conversion of leukotriene to leukotriene B₄ in the initiation stage of inflammation and the removal of the chemotactic Pro-Gly-Pro tripeptide. These findings make leukotriene A₄ hydrolase an attractive drug target: suggesting an innovative approach towards the identification and design of novel class of compounds that can selectively inhibit leukotriene B₄ synthesis while sparing the aminopeptidase activity. Previous inhibitors block the dual activity of the enzyme. Recently, a small lead molecule inhibitor denoted as ARM1 has been identified to block the hydrolase activity of leukotriene A₄ hydrolase whilst sparing the aminopeptidase activity. In this study, a hybrid receptor-bound/MM-GBSA-per-residue energy based pharmacophore modeling approach was implemented to identify potential selective hydrolase inhibitors of leukotriene A₄ hydrolase. In this approach, active site residues that favorably contributed to the binding of the bound conformation of ARM1 were derived from MD ensembles and MM/GBSA thermodynamic calculations. These residues were then mapped to key pharmacophore features of ARM1. The generated pharmacophore model was used to search the ZINC database for 3D structures that match the pharmacophore. Five new compounds have been identified and proposed as potential epoxide hydrolase selective inhibitors of leukotriene A₄ hydrolase. Molecular docking and MM/GBSA analyses revealed that, these top five lead-like compounds ZINC00142747, ZINC94260794, ZINC01382396, ZINC02508448, and ZINC53994447 showed better binding affinities to the hydrolase active site pocket compared to ARM1. Per-residue energy decomposition analysis revealed that amino acid residues Phe314, Tyr378, Pro382, Trp311, Val367, and Ala377 are key residues critical in the selective inhibition of these hits. Information highlighted in this study may guide the the design the next generation of novel and potent epoxide hydrolase selective inhibitors of leukotriene A₄ hydrolase.

Identification of Novel Potential gp120 of HIV-1 Antagonist Using Per-Residue Energy Contribution-Based Pharmacophore modelling

Inhibition of HIV-1 target cell entry, by targeting gp120, has been identified as a promising approach for the identification and development of prophylactic and salvage HIV infection inhibitors. A small molecule compound 18A is an important chemotype in the development of novel and diverse viral cell entry inhibitors, as it inhibits a wide variety of HIV strains by disrupting allosteric structuring on gp120. This study combines residue energy contribution (REC) pharmacophore mapping of 18A and in silico molecular docking in a virtual screening campaign to identify novel and diverse antagonists of gp120. The binding free energy of a validated docked complex of gp120-18A and the quantitative contribution of interacting residues were obtained with a more accurate molecular mechanics/generalised born surface area (MM/GBSA) method followed by mapping the energetically favourable residue contributions onto atom centres in 18A to obtain a pharmacophore model. The generated pharmacophore hypothesis was used to search the ZINC database for 3D structures that match the pharmacophore. Further, molecular docking, molecular dynamics simulations and binding free energy analysis were performed on retrieved hits in order to rank hits based on their affinity and interactions in the CD4 binding cavity of a gp120. Interestingly, the top scoring compound designated with ZINC database ID as ZINC64700951 (docking score = -8.8 kcal/mol, ∆G = -43.77 kcal/mol) showed higher affinity compared to compound 18A docking score = -7.3 kcal/mol, ∆G = -31.97 kcal/mol) and interaction of ZN64700951 with validated allosteric hot spot residues, Asp368 and Met426, and binding hot spot residues, Asn425, Glu370, Gly473, Trp427 and Met475 in gp120, suggest that ZN64700951 is a promising antagonist of gp120. Thus, ZN64700951 could serve as an additional prototype for further optimisation as an HIV target cell viral entry inhibitor.

In silico research to assist the investigation of carboxamide derivatives as potent TRPV1 antagonists

The transient receptor potential vanilloid type 1 (TRPV1), a non-selective cation channel, is known for its essential role in the pathogenesis of various pain conditions such as nerve damage induced hyperalgesia, diabetic neuropathy and cancer pain.

Profiling the interaction mechanism of quinoline/quinazoline derivatives as MCHR1 antagonists: an in silico method

Melanin concentrating hormone receptor 1 (MCHR1), a crucial regulator of energy homeostasis involved in the control of feeding and energy metabolism, is a promising target for treatment of obesity. In the present work, the up-to-date largest set of 181 quinoline/quinazoline derivatives as MCHR1 antagonists was subjected to both ligand- and receptor-based three-dimensional quantitative structure–activity (3D-QSAR) analysis applying comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The optimal predictable CoMSIA model exhibited significant validity with the cross-validated correlation coefficient (Q²) = 0.509, non-cross-validated correlation coefficient (R²_ncv) = 0.841 and the predicted correlation coefficient (R²_pred) = 0.745. In addition, docking studies and molecular dynamics (MD) simulations were carried out for further elucidation of the binding modes of MCHR1 antagonists. MD simulations in both water and lipid bilayer systems were performed. We hope that the obtained models and information may help to provide an insight into the interaction mechanism of MCHR1 antagonists and facilitate the design and optimization of novel antagonists as anti-obesity agents.