Pharmacophore-based Approach Research Articles

Pharmacophore-based approach for the identification of potent inhibitors against LpxC Enzyme from Salmonella Typhi

Antimicrobial resistance (AMR) is currently a global health concern, mostly caused by microorganisms like bacteria, viruses, parasites, and fungi that acquire resistance to antimicrobial drugs. Salmonella is responsible for a variety of diseases but mainly cause typhoid. The primary concern is the rise in resistance in both non-typhoid and typhoid strains of this species. To address this issue, it is necessary to identify novel targets and strategies for the development of new antibacterial drugs. Lipid A, a strong bacterial endotoxin that modulates the immune system in human, is a key component of the virulence factor generated during the salmonella infection. Lipid A is synthesized in case of Gram-negative bacteria by cascade of nine enzyme pathway. The second step in case of Lipid A biosynthesis, catalysed by LpxC, a Zn+ dependent metallo-amidase considered as rate limiting step. In this manuscript we have used protein-ligand interaction fingerprint (PLIF)–derived pharmacophore models to screen small molecules (natural products library from Zinc database, Asinex database, Thiophene analogues) against Salmonella typhi LpxC (StLpxC). Further top hit molecules were subjected to MD-simulation and ADMET studies. We identified three optimal compounds, s1_dl_mseq2, s1_ll_mseq2, and s2_ll_mseq8, that exhibit strong binding affinity towards the LpxC active site.

A Review of the Therapeutic Importance of Indole Scaffold in Drug Discovery.

Indole is known as a versatile heterocyclic building block for its multiple pharmacological activities and has a high probability of success in the race for drug candidates. Many natural products, alkaloids, and bioactive heterocycles contain indole as the active principle pharmacophore. These encourage the researchers to explore it as a lead in the drug development process. The current manuscript will serve as a torchbearer for understanding the structurally diverse class of indole derivatives with extensive pharmacological activity. The current manuscript describes the intermediates and their functional groups responsible for superior biological activity compared to the standard. The review is written to help researchers to choose leads against their target but also to provide crucial insight into the design of a hybrid pharmacophore-based approach in drug design with enhanced potential. The present reviews on the indole derivatives correlate the structures with biological activities as well as essential pharmacophores, which were highlighted. The discussion was explored under challenging targets like dengue, chikungunya (anti-viral), antihypertensive, diuretic, immunomodulator, CNS stimulant, antihyperlipidemic, antiarrhythmic, anti-Alzheimer's, and neuroprotective, along with anticancer, antitubercular, antimicrobial, anti-HIV, antimalarial, anti-inflammatory, antileishmanial, antianthelmintic, and enzyme inhibitors. So, this review includes a discussion of 19 different pharmacological targets for indole derivatives that could be utilized to derive extensive information needed for ligand-based drug design. The article will guide the researchers in the selection, design of lead and pharmacophore, and ligand-based drug design using indole moiety.

A pharmacophore-based approach to demonstrating the scope of alcohol dehydrogenases

Barriers to the ready adoption of biocatalysis into asymmetric synthesis for early stage medicinal chemistry are addressed, using ketone reduction by alcohol dehydrogenase as a model reaction. An efficient substrate screening approach is used to show the wide substrate scope of commercial alcohol dehydrogenase enzymes, with a high tolerance to chemical groups employed in drug discovery (heterocycle, trifluoromethyl and nitrile/nitro groups) observed. We use our screening data to build a preliminary predictive pharmacophore-based screening tool using Forge software, with a precision of 0.67/1, demonstrating the potential for developing substrate screening tools for commercially available enzymes without publicly available structures. We hope that this work will facilitate a culture shift towards adopting biocatalysis alongside traditional chemical catalytic methods in early stage drug discovery.

Comprehensive screening of marine metabolites against class B1 metallo-β-lactamases of Klebsiella pneumoniae using two-pronged in silico approach

The emergence of antibiotic resistance is one of the major global threats in healthcare. Metallo-β-Lactamases (MBL) are a class of enzymes in bacteria that cleave β-lactam antibiotics and confer resistance. MBLs are further divided into subclasses B1, B2 and B3. Of these, subclasses B1-MBLs (including NDM-1, VIM-2 and IMP-1) constitute the clinically prevalent lactamases conferring resistance. To date, no effective drugs are available clinically against MBLs. In this work, we aim to identify potent inhibitors for the B1 subclass of MBL from available marine metabolites in Comprehensive Marine Natural Product database through integrated in silico approaches. We have used two methods, namely, the high-throughput strategy and the pharmacophore-based strategy to identify potential inhibitors from marine metabolites. High-throughput virtual screening identified N-methyl mycosporine-Ser, which had the highest binding affinity to NDM-1. The pharmacophore-based approach based on co-crystallized ligands identified makaluvic acid and didymellamide with higher binding affinity across B1-MBLs. Taking into account of the advantage of a pharmacophore model-based approach with higher binding affinity, we conclude that both makaluvic acid and didymellamide show potential broad-spectrum effects by binding to all three B1-MBL receptors. The study also indicates the need to take multiple in silico approaches to screen and identify novel inhibitors. Together, our study reveals promising inhibitors that can be identified from marine systems. Communicated by Ramaswamy H. Sarma

Identification of Human Dihydroorotate Dehydrogenase Inhibitor by a Pharmacophore-Based Virtual Screening Study.

Human dihydroorotate dehydrogenase (hDHODH) is an enzyme belonging to a flavin mononucleotide (FMN)-dependent family involved in de novo pyrimidine biosynthesis, a key biological pathway for highly proliferating cancer cells and pathogens. In fact, hDHODH proved to be a promising therapeutic target for the treatment of acute myelogenous leukemia, multiple myeloma, and viral and bacterial infections; therefore, the identification of novel hDHODH ligands represents a hot topic in medicinal chemistry. In this work, we reported a virtual screening study for the identification of new promising hDHODH inhibitors. A pharmacophore-based approach combined with a consensus docking analysis and molecular dynamics simulations was applied to screen a large database of commercial compounds. The whole virtual screening protocol allowed for the identification of a novel compound that is endowed with promising inhibitory activity against hDHODH and is structurally different from known ligands. These results validated the reliability of the in silico workflow and provided a valuable starting point for hit-to-lead and future lead optimization studies aimed at the development of new potent hDHODH inhibitors.

Identification of novel efflux pump inhibitors for Neisseria gonorrhoeae via multiple ligand-based pharmacophores, e-pharmacophore, molecular docking, density functional theory, and molecular dynamics approaches

Neisseria gonorrhoeae have progressively developed resistance to almost all antibiotics, and it has become imperative to develop novel approaches to combat its multi-drug resistance. Overexpression of the MtrCDE, an RND family efflux pump, is one of the primary causes of antibiotic resistance in the gonococcus and is considered an important target for combating anti-microbial resistance. PaβN, D13–9001, and other EPIs are identified to target the RND efflux pumps, but due to their cytotoxicity, they have failed in clinical trials. Herein, an extensive pharmacophore-based approach was performed to identify novel EPI inhibitors with improved pharmacology/safety profiles. An integrated computational framework comprising pharmacophore generation, virtual screening using HTVS, SP and XP Glide methodology, MM-GBSA analysis, Induced fit docking, QPLD, DFT, ADMET properties calculation, Molecular Dynamics, and MM-PBSA analysis was performed. The comprehensive study leads to the identification of five non-toxic bioactive compounds, namely - ZINC000008764610, ZINC000030879142, ZINC000030879358, ZINC000253414904, and ZINC000225394671, as potential EPIs for RND efflux pump of Neisseria gonorrhoeae. The five compounds were selected based on the pharmacophore mapping, higher dock score than the known EPIs, binding stability, molecular interactions with the critical residues of MtrD protein, higher ADMET properties, non-toxicity, and free energy estimations. In summary, the analysis led to the identification of five top hits from the natural compound subset of the ZINC database that has a higher binding affinity to the MtrD and adequate physiochemical/pharmacokinetic profile that can be used for the generation of novel EPIs against Neisseria gonorrhoeae.

Modern Paradigm Towards Potential Target Identification for Antiviral (SARS-nCoV-2) and Anticancer Lipopeptides: A Pharmacophore-Based Approach.

Background:Lipopeptides are potential microbial metabolites that are abandoned with broad spectrum biopharmaceutical properties ranging from antimicrobial, antiviral and anticancer, etc. Clinical studies are not much explored beyond the experimental methods to understand drug mechanisms on target proteins at the molecular level for large molecules. Due to the less available studies on potential target proteins of lipopeptide based drugs, their potential inhibitory role for more obvious treatment on disease have not been explored in the direction of lead optimization. However, Computational approaches need to be utilized to explore drug discovery aspects on lipopeptide based drugs, which are time saving and cost-effective techniques.Methods:Here a ligand-based drug discovery approach is coupled with reverse pharmacophore-mapping for the prediction of potential targets for antiviral (SARS-nCoV-2) and anticancer lipopeptides. Web-based servers PharmMapper and Swiss Target Prediction are used for the identification of target proteins for lipopeptides surfactin and iturin produced by Bacillus subtilis.Results:The studies have given the insight to treat the diseases with next-generation large molecule therapeutics. Results also indicate the affinity for Angiotensin-Converting Enzymes (ACE) and proteases as the potential viral targets for these categories of peptide therapeutics. A target protein for the Human Papilloma Virus (HPV) has also been mapped.Conclusion:The work will further help in exploring computer-aided drug designing of novel compounds with greater efficiency where the structure of the target proteins and lead compounds are known.

Identification of CDK7 Inhibitors from Natural Sources Using Pharmacoinformatics and Molecular Dynamics Simulations.

The cyclin-dependent kinase 7 (CDK7) plays a crucial role in regulating the cell cycle and RNA polymerase-based transcription. Overexpression of this kinase is linked with various cancers in humans due to its dual involvement in cell development. Furthermore, emerging evidence has revealed that inhibiting CDK7 has anti-cancer effects, driving the development of novel and more cost-effective inhibitors with enhanced selectivity for CDK7 over other CDKs. In the present investigation, a pharmacophore-based approach was utilized to identify potential hit compounds against CDK7. The generated pharmacophore models were validated and used as 3D queries to screen 55,578 natural drug-like compounds. The obtained compounds were then subjected to molecular docking and molecular dynamics simulations to predict their binding mode with CDK7. The molecular dynamics simulation trajectories were subsequently used to calculate binding affinity, revealing four hits—ZINC20392430, SN00112175, SN00004718, and SN00262261—having a better binding affinity towards CDK7 than the reference inhibitors (CT7001 and THZ1). The binding mode analysis displayed hydrogen bond interactions with the hinge region residues Met94 and Glu95, DFG motif residue Asp155, ATP-binding site residues Thr96, Asp97, and Gln141, and quintessential residue outside the kinase domain, Cys312 of CDK7. The in silico selectivity of the hits was further checked by docking with CDK2, the close homolog structure of CDK7. Additionally, the detailed pharmacokinetic properties were predicted, revealing that our hits have better properties than established CDK7 inhibitors CT7001 and THZ1. Hence, we argue that proposed hits may be crucial against CDK7-related malignancies.

Discovery of TMPRSS2 Inhibitors from Virtual Screening as a Potential Treatment of COVID-19.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has prompted researchers to pivot their efforts to finding antiviral compounds and vaccines. In this study, we focused on the human host cell transmembrane protease serine 2 (TMPRSS2), which plays an important role in the viral life cycle by cleaving the spike protein to initiate membrane fusion. TMPRSS2 is an attractive target and has received attention for the development of drugs against SARS and Middle East respiratory syndrome. Starting with comparative structural modeling and a binding model analysis, we developed an efficient pharmacophore-based approach and applied a large-scale in silico database screening for small-molecule inhibitors against TMPRSS2. The hits were evaluated in the TMPRSS2 biochemical assay and the SARS-CoV-2 pseudotyped particle entry assay. A number of novel inhibitors were identified, providing starting points for the further development of drug candidates for the treatment of coronavirus disease 2019.

Screening of inhibitors as potential remedial against Ebolavirus infection: pharmacophore-based approach

Ebola virus disease (EVD) has been recognized as a major threat for humans and primates. Till now, therapeutic solution is a challenging for the treatment of Ebola virus disease. Therefore, new, novel with suitable effective antiviral drug against EVD is essential. In the present study pharmacophore modeling, 3DQSAR, molecular docking, DFT and molecular dynamic simulations were used to identify the new, novel with suitable effective potential inhibitors against Ebola virus through the computational methods. From the pharmacophore PHASE modeling, the best five hypothesis pharmacophore features such as three hydrogen bond acceptor, one positive ion and one aromatic ring are taken to study the 3D-QSAR structural model. The designed with correlation co-efficient is found to be R2 = 0.92 and the excellent predictive power with correlation co- efficient is found to be Q2 = 0.82. The 3D-QSAR model is used to study the virtual screening against the chemical libraries compounds (NCI, ZINC, Asinex, LifeChemical, ChemBridge, MayBridge, Enamine and specs) to identify the novel scaffolds. The best binding free energy (39.368769 kcal/mol) and the best docking score (12.419 kcal/mol) for NCI database are obtained from molecular docking and MM-GBSA respectively. The good electronic features of ligands are observed from DFT analysis. Finally, molecular dynamics simulations revealed the stability of ligand protein complexes ranging from 1 nm to 1.5 nm. We anticipated that, this ligand protein complex could be supportive to improve the potent inhibitor against the Ebola viral treatment. Communicated by Ramaswamy H. Sarma.

Pharmacophore-based tailoring of biphenyl amide derivatives as selective 5-hydroxytryptamine 2B receptor antagonists.

We designed and synthesized a new biphenyl amide-tryptamine hybrid molecule 7 utilizing a pharmacophore-based approach as a 5-HT2B antagonist. The hybrid compound 7 was evaluated for its affinity to a panel of seven 5-HT receptors, demonstrating high selectivity for the 5-HT2B receptor. Functional assays revealed potent antagonism of 5-HT2B by 7 with an IC50 value of 14.1 nM. Moreover, compound 7 possessed a desirable in vitro pharmacokinetic profile and maintained its antagonistic potency in the presence of physiological concentrations of serum proteins. The design approach implemented in this investigation would facilitate the development of a second generation of highly selective and potent 5-HT2B antagonists.

A Virtual Screening Study for Lactate Dehydrogenase 5 Inhibitors by Using a Pharmacophore-based Approach.

Inhibitors of human lactate dehydrogenase 5 (hLDH5) are promising therapeutic agents against cancer. This enzyme is generally found to be overexpressed in most invasive cancer cells and is linked to their vitality especially under hypoxic conditions. In this study, with the aim of identifying new hLDH5 inhibitors, a receptor-based pharmacophore modeling approach has been tested and, in order to verify the reliability of the reported approach, the Gold and Platinum database from Asinex were filtered. The top-ranked compounds were experimentally tested for their hLDH5 inhibition activity and enzymatic assays revealed that, among the ten selected compounds, two proved to inhibit the enzyme activity with Ki values in the micromolar range (Ki =33.1-76.7 μM).

An In Silico Approach for Identification of Potential Anti-Mycobacterial Targets of Vasicine and Related Chemical Compounds.

Tuberculosis (TB) is known to mankind as one of the most pervasive and persistent of diseases since the early days of civilization. The growing resistance of the causative pathogen Mycobacterium tuberculosis to the standard drug regimen for TB poses further difficulty in its treatment and control. Screening of novel plant-derived compounds with promising anti-tubercular activity has been cited as a prospective route for new anti-tubercular drug discovery and design. Justicia adhatoda L. is a perennial evergreen shrub which is widely mentioned in scientific literature on account of its potent anti-mycobacterial properties. In the present study, we have employed a series of computational methodologies to reveal the probable molecular interactions of vasicine, the principal alkaloid of Justicia adhatoda L., and two of its close natural derivatives- vasicinone and deoxyvasicine, with certain biological targets in M. tuberculosis. Targets were identified from literature and through a reverse Pharmacophore-based approach. Subsequent comparative molecular docking to identify the best ligand-target interactions revealed Antigen 85C of M. tuberculosis as the most potent biological target of vasicine on the basis of optimum molecular docking values. A chemogenomics approach was also employed to validate the molecular interactions between the same class of chemical compounds as vasicine and Antigen 85C. Further, a library of structural analogs of vasicine was created by bioiosterism-based drug design to identify structural analogs with better inhibitory potential against Antigen 85C.

A Combination of Receptor-Based Pharmacophore Modeling & QM Techniques for Identification of Human Chymase Inhibitors

Inhibition of chymase is likely to divulge therapeutic ways for the treatment of cardiovascular diseases, and fibrotic disorders. To find novel and potent chymase inhibitors and to provide a new idea for drug design, we used both ligand-based and structure-based methods to perform the virtual screening(VS) of commercially available databases. Different pharmacophore models generated from various crystal structures of enzyme may depict diverse inhibitor binding modes. Therefore, multiple pharmacophore-based approach is applied in this study. X-ray crystallographic data of chymase in complex with different inhibitors were used to generate four structure–based pharmacophore models. One ligand–based pharmacophore model was also developed from experimentally known inhibitors. After successful validation, all pharmacophore models were employed in database screening to retrieve hits with novel chemical scaffolds. Drug-like hit compounds were subjected to molecular docking using GOLD and AutoDock. Finally four structurally diverse compounds with high GOLD score and binding affinity for several crystal structures of chymase were selected as final hits. Identification of final hits by three different pharmacophore models necessitates the use of multiple pharmacophore-based approach in VS process. Quantum mechanical calculation is also conducted for analysis of electrostatic characteristics of compounds which illustrates their significant role in driving the inhibitor to adopt a suitable bioactive conformation oriented in the active site of enzyme. In general, this study is used as example to illustrate how multiple pharmacophore approach can be useful in identifying structurally diverse hits which may bind to all possible bioactive conformations available in the active site of enzyme. The strategy used in the current study could be appropriate to design drugs for other enzymes as well.

Toward Greener Carbon Capture Technologies: A Pharmacophore-Based Approach to Predict CO2 Binding Sites in Proteins

Successful sequestration of emitted carbon dioxide is a crucial ingredient in addressing rising atmospheric CO2 concentrations, but current CO2 capture technologies are often corrosive and can generate hazardous waste. Inspiration for more environmentally friendly sequestration is sought in Nature by searching for common patterns by which proteins bind CO2. Specifically, three-dimensional functional group patterns responsible for binding CO2 are extracted from the few protein−CO2 complexes that have been characterized by X-ray crystallography. These motifs are used to generate pharmacophore-type queries, which are utilized in database mining efforts to locate similar binding motifs in a test set of enzymes that do not have an experimentally determined CO2 binding site. These predicted carbon dioxide binding sites are often located within the active site cleft. Moreover, some of these identified CO2-binding functional group patterns are found across various species and enzyme classes. Potential application...

Role of Halogen Bonds in Thyroid Hormone Receptor Selectivity: Pharmacophore-Based 3D-QSSR Studies

Most physiological effects of thyroid hormones are mediated by the two thyroid hormone receptor subtypes, TRalpha and TRbeta. Several pharmacological effects mediated by TRbeta might be beneficial in important medical conditions such as obesity, hypercholesterolemia and diabetes, and selective TRbeta activation may elicit these effects while maintaining an acceptable safety profile. To understand the molecular determinants of affinity and subtype selectivity of TR ligands, we have successfully employed a ligand- and structure-guided pharmacophore-based approach to obtain the molecular alignment of a large series of thyromimetics. Statistically reliable three-dimensional quantitative structure-activity relationship (3D-QSAR) and three-dimensional quantitative structure-selectivity relationship (3D-QSSR) models were obtained using the comparative molecular field analysis (CoMFA) method, and the visual analyses of the contour maps drew attention to a number of possible opportunities for the development of analogs with improved affinity and selectivity. Furthermore, the 3D-QSSR analysis allowed the identification of a novel and previously unmentioned halogen bond, bringing new insights to the mechanism of activity and selectivity of thyromimetics.

On designing non-saccharide, allosteric activators of antithrombin

Antithrombin, a plasma glycoprotein serpin, requires conformational activation by heparin to induce an anticoagulant effect, which is mediated through accelerated factor Xa inhibition. Heparin, a highly charged polymer and an allosteric activator of the serpin, is associated with major adverse effects. To design better, but radically different activators of antithrombin from heparin, we utilized a pharmacophore-based approach. A tetrahydroisoquinoline-based scaffold was designed to mimic four critical anionic groups of the key trisaccharide DEF constituting the sequence-specific pentasaccharide DEFGH in heparin. Activator IAS 5 containing 5,6-disulfated tetrahydroisoquinoline and 3,4,5-trisulfated phenyl rings was found to bind antithrombin at pH 7.4 with an affinity comparable to the reference trisaccharide DEF. IAS 5 activated the inhibitor nearly 30-fold, nearly 2- to 3-fold higher than our first generation flavanoid-based designs. This work advances the concept of antithrombin activation through non-saccharide, organic molecules and pinpoints a direction for the design of more potent molecules.

In Vitro and Pharmacophore-Based Discovery of Novel hPEPT1 Inhibitors

The human proton-coupled small peptide carrier (hPEPT1) is a low-affinity, high-capacity transporter with broad substrate specificity. We have taken an iterative in vitro and in silico approach to the discovery of molecules with hPEPT1 affinity. A pharmacophore-based approach was taken to identifying hPEPT1 inhibitors. The well-characterized and relatively high affinity ligands Gly-Sar, bestatin, and enalapril were used to generate a common features (HIPHOP) pharmacophore. This consisted of two hydrophobic features, a hydrogen bond donor, acceptor, and a negative ionizable feature. The pharmacophore was used to search the Comprehensive Medicinal Chemistry (CMC) database of more than 8000 drug-like molecules and retrieved 145 virtual hits mapping to the pharmacophore features. The highest scoring compounds within this set were selected and tested in a stably transfected CHO-hPepT1 cell model. The antidiabetic repaglinide and HMG CoA reductase inhibitor fluvastatin were found to inhibit hPEPT1 with sub-millimolar potency (IC(50) 178 +/- 1.0 and 337 +/- 4 microM, respectively). The pharmacophore was also able to identify known hPEPT1 substrates and inhibitors in further database mining of more than 500 commonly prescribed drugs. This study demonstrates the potential of combining computational and in vitro approaches to determine the affinity of compounds for hPEPT1 and, in turn, provides insights into key molecular interactions with this transporter.

Fuzzy pharmacophore models from molecular alignments for correlation-vector-based virtual screening.

A pharmacophore-based approach for compiling focused screening libraries is presented. It integrates information from three-dimensional molecular alignments into correlation vector-based database screening. The pharmacophore model is represented by a number of spheres of Gaussian-distributed feature densities. Different degrees of "fuzziness" can be introduced to influence the model's resolution. Transformation of this pharmacophore representation into a correlation vector results in a vector of feature probabilities which can be utilized for rapid virtual screening of compound databases or virtual libraries. The approach was validated by retrospective screening for cyclooxygenase 2 (COX-2) and thrombin ligands. A variety of models with different degrees of fuzziness were calculated and tested for both classes of molecules. Best performance was obtained with pharmacophore models reflecting an intermediate degree of fuzziness, yielding an enrichment factor of up to 39 for the first 1% of the ranked database. Appropriately weighted fuzzy pharmacophore models performed better in retrospective screening than similarity searching using only a single query molecule. The new pharmacophore method was shown to complement existing approaches.

Identification of a stable chymase inhibitor using a pharmacophore-Based database search

In general, serine protease chymase inhibitors readily decompose in plasma. We previously found that thiazolidine-2,4-dione and thiadiazole derivatives are also unstable. Using a pharmacophore-based database search, we identified a benzo[ b]thiophen-2-sulfonamide derivative as a stable chymase inhibitor. Finding a lead compound with adequate activity and stability by a pharmacophore-based approach is more efficient than modifying an unstable compound to reduce its instability without simultaneously decreasing its inhibitory activity. Our pharmacophore model of chymase inhibitors suggests that the two hydrophobic interactions in the S1 and S1′ regions and the two H-bonding interactions between them play important roles in chymase inhibitors.