Receptor-based Pharmacophore Model Research Articles

Receptor-based pharmacophore modeling, molecular docking, synthesis and biological evaluation of novel VEGFR-2, FGFR-1, and BRAF multi-kinase inhibitors

A receptor-based pharmacophore model describing the binding features required for the multi-kinase inhibition of the target kinases (VEGFR-2, FGFR-1, and BRAF) were constructed and validated. It showed a good overall quality in discriminating between the active and the inactive in a compiled test set compounds with F1 score of 0.502 and Mathew’s correlation coefficient of 0.513. It described the ligand binding to the hinge region Cys or Ala, the glutamate residue of the Glu-Lys αC helix conserved pair, the DFG motif Asp at the activation loop, and the allosteric back pocket next to the ATP binding site. Moreover, excluded volumes were used to define the steric extent of the binding sites. The application of the developed pharmacophore model in virtual screening of an in-house scaffold dataset resulted in the identification of a benzimidazole-based scaffold as a promising hit within the dataset. Compounds 8a-u were designed through structural optimization of the hit benzimidazole-based scaffold through (un)substituted aryl substitution on 2 and 5 positions of the benzimidazole ring. Molecular docking simulations and ADME properties predictions confirmed the promising characteristics of the designed compounds in terms of binding affinity and pharmacokinetic properties, respectively. The designed compounds 8a-u were synthesized, and they demonstrated moderate to potent VEGFR-2 inhibitory activity at 10 µM. Compound 8u exhibited a potent inhibitory activity against the target kinases (VEGFR-2, FGFR-1, and BRAF) with IC50 values of 0.93, 3.74, 0.25 µM, respectively. The benzimidazole derivatives 8a-u were all selected by the NCI (USA) to conduct their anti-proliferation screening. Compounds 8a and 8d resulted in a potent mean growth inhibition % (GI%) of 97.73% and 92.51%, respectively. Whereas compounds 8h, 8j, 8k, 8o, 8q, 8r, and 8u showed a mean GI% > 100% (lethal effect). The most potent compounds on the NCI panel of 60 different cancer cell lines were progressed further to NCI five-dose testing. The benzimidazole derivatives 8a, 8d, 8h, 8j, 8k, 8o, 8q, 8r and 8u exhibited potent anticancer activity on the tested cell lines reaching sub-micromolar range. Moreover, 8u was found to induce cell cycle arrest of MCF-7 cell line at the G2/M phase and accumulating cells at the sub-G1 phase as a result of cell apoptosis.

Discovery of dual kinase inhibitors targeting VEGFR2 and FAK: structure-based pharmacophore modeling, virtual screening, and molecular docking studies

VEGFR2 and FAK signaling pathways are interconnected and have synergistic effects on tumor angiogenesis, growth, and metastasis. Thus, instead of the conventional targeting of each of these proteins individually with a specific inhibitor, the present work aimed to discover novel dual inhibitors targeting both VEGFR2 and FAK exploiting their association. To this end, receptor-based pharmacophore modeling technique was opted to generate 3D pharmacophore models for VEGFR2 and FAK type II kinase inhibitors. The generated pharmacophore models were validated by assessing their ability to discriminate between active and decoy compounds in a pre-compiled test set of VEGFR2 and FAK active compounds and decoys. ZINCPharmer web tool was then used to screen the ZINC database purchasable subset using the validated pharmacophore models retrieving 42,616 hits for VEGFR2 and 28,475 hits for FAK. Subsequently, they were filtered using various filters leaving 13,023 and 6,832 survived compounds for VEGFR2 and FAK, respectively, with 124 common compounds. Based on molecular docking simulations, thirteen compounds were found to satisfy all necessary interactions with VEGFR2 and FAK kinase domains. Thus, they are predicted to have a possible dual VEGFR2/FAK inhibitory activity. Finally, SwissADME web tool showed that compound ZINC09875266 is not only promising in terms of binding pattern to our target kinases, but also in terms of pharmacokinetic properties.

Discovery of dual rho-associated protein kinase 1 (ROCK1)/apoptosis signal–regulating kinase 1 (ASK1) inhibitors as a novel approach for non-alcoholic steatohepatitis (NASH) treatment

In the current study we suggest a novel approach to curb non-alcoholic steatohepatitis (NASH) progression, and we suggest privileged scaffolds for the design of novel compounds for this aim. NASH is an advanced form of non-alcoholic fatty liver disease that can further progress into fibrosis, cirrhosis, and hepatocellular carcinoma. It is a widely emerging disease affecting 25% of the global population and has no current approved treatments. Protein kinases are key regulators of cellular pathways, of which, Rho-associated protein kinase 1 (ROCK1) and apoptosis signal–regulating kinase 1 (ASK1) play an important role in the progression of NASH and they stand out as promising targets for NASH therapy. Interestingly, their kinase domains are found to be similar in sequence and topology; therefore, dual inhibition of ROCK1 and ASK1 is expected to be amenable and could achieve a more favourable outcome. To reach this goal, a training set of ROCK1 and ASK1 protein structures co-crystalized with type 1 (ATP-competitive) inhibitors was constructed to manually generate receptor-based pharmacophore models representing ROCK1 and ASK1 inhibitors’ common pharmacophoric features. The models produced were assessed using a test set of both ROCK1 and ASK1 actives and decoys, and their performance was evaluated using different assessment metrics. The best pharmacophore model obtained, showing a Mathew’s correlation coefficient (MCC) of 0.71, was then used to screen the ZINC purchasable database retrieving 6178 hits that were filtered accordingly using several medicinal chemistry and pharmacokinetics filters returning 407 promising compounds. To confirm that these compounds are capable of binding to the target kinases, they were subjected to molecular docking simulations at both protein structures. The results were then assessed individually and filtered, setting the spotlight on various privileged scaffolds that could be exploited as the nucleus for designing novel ROCK1/ASK1 dual inhibitors.

CSC01 shows promise as a potential inhibitor of the oncogenic G13D mutant of KRAS: an in silico approach.

About 30% of malignant tumors include KRAS mutations, which are frequently required for the development and maintenance of malignancies. KRAS is now a top-priority cancer target as a result. After years of research, it is now understood that the oncogenic KRAS-G12C can be targeted. However, many other forms, such as the G13D mutant, are yet to be addressed. Here, we used a receptor-based pharmacophore modeling technique to generate potential inhibitors of the KRAS-G13D oncogenic mutant. Using a comprehensive virtual screening workflow model, top hits were selected, out of which CSC01 was identified as a promising inhibitor of the oncogenic KRAS mutant (G13D). The stability of CSC01 upon binding the switch II pocket was evaluated through an exhaustive molecular dynamics simulation study. The several post-simulation analyses conducted suggest that CSC01 formed a stable complex with KRAS-G13D. CSC01, through a dynamic protein-ligand interaction profiling analysis, was also shown to maintain strong interactions with the mutated aspartic acid residue throughout the simulation. Although binding free energy analysis through the umbrella sampling approach suggested that the affinity of CSC01 with the switch II pocket of KRAS-G13D is moderate, our DFT analysis showed that the stable interaction of the compound might be facilitated by the existence of favorable molecular electrostatic potentials. Furthermore, based on ADMET predictions, CSC01 demonstrated a satisfactory drug likeness and toxicity profile, making it an exemplary candidate for consideration as a potential KRAS-G13D inhibitor.

Discovery of a new Daboia russelli viper venom PLA2 inhibitor using virtual screening of pharmacophoric features of co-crystallized compound

Snake venom PLA2, a member of the group of hydrolase enzymes, has been recognized as a promising drug target for snake envenomation. In the present study, an attempt was made to identify potential inhibitors of snake venom PLA2 by employing a pharmacophore-based virtual screening, docking, and dynamics approach. A receptor-based pharmacophore model was generated based on the features of the established and bound co-crystal ligand (2-carbamoylmethyl-5-propyl-octahydro-indol-7-yl)-acetic acid in the PLA2 complex. The best pharmacophore model (ADDH) derived, consisted of four features, namely one hydrogen bond acceptor, two hydrogen bond donors, and one hydrophobic region. This common pharmacophore was then used to perform virtual screening against a drug-like diverse database, with due consideration to the Lipinski ‘rule of five’, so as to obtain a pool of lead molecules. The short-listed lead molecules were then subjected to docking analysis with that of the Daboia russelli viper venom PLA2 followed by a molecular simulation study for a duration of 100 ns. CAP04815700 was chosen as the best compound based on the simulation parameters, which were then taken for MM/PBSA calculation, and it was revealed that it has a similar effective inhibitory potential as that of the crystal ligand. Further, the cluster analysis also revealed the structural significance of the backbone protein after the interaction with CAP04815700. This study will continue to explore its bioactivity in vitro and in vivo. Communicated by Ramaswamy H. Sarma

Targeting α-amylase enzyme through multi-fold structure-based virtual screening and molecular dynamic simulation

α-Amylase play important role in hydrolyses of α-bonds of large α-linked polysaccharides; thus, it is a potential drug target in diabetes mellites (DM) and its inhibition is one of the therapeutic strategies in DM. With the aim to discover novel and safer therapeutic molecules to combat diabetes, a huge dataset of ∼0.69 billion compounds from ZINC20 database were screened against α-amylase using multi-fold structure-based virtual screening protocol. Based on receptor-based pharmacophore model, docking results, pharmacokinetic profile, molecular interactions with α-amylase, several compounds were retrieved as lead candidates to be further scrutinized in the in vitro assay and in vivo animal testing. Among the selected hits, CP26 exhibited the highest binding free energy in MMGB-SA analysis, followed by CP7 and CP9, which is higher than the binding free energy of acarbose. While CP20 and CP21 showed comparative binding free energy to acarbose. All the selected ligands showed acceptable binding energy range, therefore, several molecules with enhanced efficacy can be designed by derivatizing these molecules. The in-silico results indicates that the selected molecules could serve as potential selective α-amylase inhibitors and can be used for the treatment of diabetes. Communicated by Ramaswamy H. Sarma

Discovery of Potential RAGE inhibitors using Receptor-Based Pharmacophore Modeling, High Throughput Virtual Screening and Docking Studies.

Receptor for Advanced Glycation End products (RAGE) is a transmembrane receptor that can bind to various endogenous and exogenous ligands and initiate the inflammatory downstream signaling pathways. So far RAGE has been involved in various disorders including cardiovascular and neurodegenerative diseases, cancer, and diabetes. Blocking the interactions between RAGE and its ligands is a therapeutic approach to treat these conditions. In this context, we effectively utilized the receptor-based-pharmacophore modeling to discover structurally diverse molecular compounds having potential to effectively bind with RAGE. Two pharmacophore models were developed on V-domain of RAGE using Phase application of Schrodinger suite. The developed pharmacophoric features were used for screening of 1.8 million drug-like molecules downloaded from ChEMBL database. The molecules were scrutinized according to their molecular weight as well as clogP values. Phase screening was performed to find out the molecules that matched the developed pharmacophoric features that were further selected to analyze their binding modes using high-throughput virtual screening, extra precision docking studies and MM-GBSA ΔG binding calculations. These analyses provided ten hit RAGE inhibitory molecules that can bind to two different shallow binding sites on the V-domain of RAGE. Among the obtained compounds two compounds ChEMBL501494 and ChEMBL4081874 were found with best binding free energies that proved their receptor-ligand complex stability within their respective binding cavity on RAGE. Therefore, these molecules could be utilized for further designing and optimizing the future class of potential RAGE inhibitors.

Apo2ph4: A Versatile Workflow for the Generation of Receptor-based Pharmacophore Models for Virtual Screening.

Pharmacophore models are widely used as efficient virtual screening (VS) filters for the target-directed enrichment of large compound libraries. However, the generation of pharmacophore models that have the power to discriminate between active and inactive molecules traditionally requires structural information about ligand-target complexes or at the very least knowledge of one active ligand. The fact that the discovery of the first known active ligand of a newly investigated target represents a major hurdle at the beginning of every drug discovery project underscores the need for methods that are able to derive high-quality pharmacophore models even without the prior knowledge of any active ligand structures. In this work, we introduce a novel workflow, called apo2ph4, that enables the rapid derivation of pharmacophore models solely from the three-dimensional structure of the target receptor. The utility of this workflow is demonstrated retrospectively for the generation of a pharmacophore model for the M2 muscarinic acetylcholine receptor. Furthermore, in order to show the general applicability of apo2ph4, the workflow was employed for all 15 targets of the recently published LIT-PCBA dataset. Pharmacophore-based VS runs using the apo2ph4-derived models achieved a significant enrichment of actives for 13 targets. In the last presented example, a pharmacophore model derived from the etomidate site of the α1β2γ2 GABAA receptor was used in VS campaigns. Subsequent in vitro testing of selected hits revealed that 19 out of 20 (95%) tested compounds were able to significantly enhance GABA currents, which impressively demonstrates the applicability of apo2ph4 for real-world drug design projects.

De Novo Design of Cathepsin B1 Inhibitors as Potential Anti-Schistosomal Agents Using Computational Studies.

BackgroundSchistosomiasis is the world’s second most devastating disease after malaria and the leading cause of disease and mortality for more than 200 million people in developing countries. Cysteine proteases, in particular SmCB1, are the most well-researched biological targets for this disorder.ObjectiveTo apply computational techniques to design new antischistosomal agents against SmCB1 protein with favorable pharmacokinetic properties.MethodsThe smCB1 receptor-based pharmacophore model was created and used to screen 567,000 fragments from the Enamine library. The best scoring fragments have been linked to build novel compounds that were subjected to molecular docking, MM-GBSA free energy estimation, ADME prediction, and molecular dynamics.ResultsA seven-point pharmacophore hypothesis ADDDRRR was created. The developed hypothesis was used to screen 1.3 M fragment conformations. Among them, 23,732 fragments matched the hypothesis and screened against the protein. The top 50 fragments were used to design new 7745 compounds using the Breed ligand panel which were subjected to docking and MMGBSA binding energy. This led to the identification of 10 compounds with better docking scores (−8.033– −7.483 kcal/mol) and lower-bound free energies (−58.49 – −40.02 kcal/mol) compared to the reference bound ligand. Most of the designed compounds demonstrated good drug-like properties. Concerning Molecular dynamics (MD) simulation results, a low root mean square deviation (RMSD) range (0.25–1.2 Å) was found for the top 3 complexes which indicated their stability.ConclusionWe identified compounds that could be potential candidates in the search for novel Schistosoma mansoni inhibitors by targeting SmCB1 utilizing various computational tools. Three newly designed compounds namely breed 1, 2, and 3 showed promising affinity to the target as well as favorable drug-like properties which might be considered potential anti-schistosomal agents.

Atomic level and structural understanding of natural ligands inhibiting Helicobacter pylori peptide deformylase through ligand and receptor based screening, SIFT, molecular dynamics and DFT – a structural computational approach

Helicobacter pylori is a Gram-negative microaerophilic gastric pathogen, responsible for the cause of peptic ulcer around half of the global population. Although several antibiotics and combination therapies have been employed for H. pylori-related gastric ulcer and cancer regiments, identifying potent inhibitors for specific targets of this bacterium will help assessing better treatment periodicity and methods to eradicate H. pylori. Herein, 1,000,000 natural compounds were virtually screened against Helicobacter pylori Peptide deformylase (HpPDF). Pharmacophore hypotheses were created using ligand and receptor-based pharmacophore modeling of GLIDE. Stringent HTVS and IFD docking protocol of GLIDE predicted leads with stable intermolecular bonds and scores. Molecular dynamics simulation of HpPDF was carried out for 100 ns using GROMACS. Hits ZINC00225109 and ZINC44896875 came up with a glide score of −9.967 kcal/mol and −12.114 kcal/mol whereas; reference compound actinonin produced a glide score of −9.730 kcal/mol. Binding energy values of these hits revealed the involvement of significant Van der Waals and Coulomb forces and the deduction of lipophilic forces that portray the deep hydrophobic residues in the S1pocket of H. pylori. The DFT analysis established the electron density-based features of the molecules and observed that the results correlate with intermolecular docking interactions. Analysis of the MD trajectories revealed the crucial residues involved in HpPDF – ligand binding and the conformational changes in the receptor. We have identified and deciphered the crucial features necessary for the potent ligand binding at catalytic site of HpPDF. The resulting ZINC natural compound hits from the study could be further employed for potent drug development. Communicated by Ramaswamy H. Sarma

Identification of novel influenza polymerase PB2 inhibitors using virtual screening approach and molecular dynamics simulation analysis of active compounds

Hierarchical virtual screening combined with ADME prediction and cluster analysis methods were used to identify influenza virus PB2 inhibitors with high activity, good druggability properties, and diverse structures. The 200,000 molecules in the ChemDiv core library were narrowed down to a final set of 97 molecules, of which six compounds were found to rescue cells from both H1N1 and H3N2 virus-induced CPE with EC50 values ranging from 5.81 μM to 42.77 μM, and could bind to the PB2 CBD of H1N1, with Kd values of 0.11 μM to 6.4 μM. The six compounds have novel structures and low molecular weight and are, thus, suitable serve as lead compounds for development as PB2 inhibitors. A receptor-based pharmacophore model was successfully constructed using key amino acid residues for the binding of inhibitors to PB2, provided by the MD simulations. This pharmacophore model suggested that to improve the activity of our active compounds, we should mainly focus on optimizing their existing structures with the aim of increasing their adaptability to the binding site, rather than adding chemical fragments to increase their binding to adjacent sites. This pharmacophore construction method facilitates the creation of a reasonable pharmacophore model without the need to fully understand the structure-activity relationships, and our descriptions provide a useful reference for similar research.

Structure-based pharmacophore modeling, virtual screening and simulation studies for the identification of potent anticancerous phytochemical lead targeting cyclin-dependent kinase 2

Cyclin-dependent kinases are of critical importance in directing various cell cycle phases making them as potential tumor targets. Cyclin-dependent kinase 2 (CDK2) in particular plays a significant part during cell cycle events and its imbalance roots out tumorogenic environment. Herein, we built a structure-based pharmacophore model complementing the ATP pocket site of CDK2 with four pharmacophoric features, using a series of structures obtained from cluster analysis during MD simulation assessment. This was followed by its validation and further database screening against Taiwan indigenous plants database (5284 compounds). The screened compounds were subjected toward Lipinski’s rule (RO5) and ADMET filter followed by docking analysis and simulation study. In filtering hits (10 compounds) via molecular docking against CDK2, Schinilenol with −8.1 kcal/mol fetched out as a best lead phytoinhibitor in the presence of standard drug (Dinaciclib). Additionally, pharmacophore mapping analysis also indicated relative fit values of dinaciclib and schinilenol as 2.37 and 2.31, respectively. Optimization, flexibility prediction and the stability of CDK2 in complex with the ligands were also ascertained by means of molecular dynamics for 50 ns, which further proposed schinilenol having better binding stability than dinaciclib with RMSD values ranging from 0.31 to 0.34 nm. Reactivity site, biological activity detection and cardiotoxicity assessment also proposed schinilenol as a better phytolead inhibitor than the existing dinaciclib. Abbreviations: CDK2: Cyclin dependent kinase2; ATP: Adenosine triphosphate; MD: Molecular dynamics, RO5: Rule of five; ADMET: Absorption, distribution, metabolism, and excretion; RMSD: Root mean square deviation; DS: Discovery Studio; SOM: Site of metabolism; RBPM: receptor based pharmacophore model; TIP: Schinilenol; hERG: human Ether-à-go-go - Related Gene Communicated by Ramaswamy H. Sarma

Receptor-Based Pharmacophore Modeling in the Search for Natural Products for COVID-19 Mpro.

Considering the urgency of the COVID-19 pandemic, we developed a receptor-based pharmacophore model for identifying FDA-approved drugs and hits from natural products. The COVID-19 main protease (Mpro) was selected for the development of the pharmacophore model. The model consisted of a hydrogen bond acceptor, donor, and hydrophobic features. These features demonstrated good corroboration with a previously reported model that was used to validate the present model, showing an RMSD value of 0.32. The virtual screening was carried out using the ZINC database. A set of 208,000 hits was extracted and filtered using the ligand pharmacophore mapping, applying the lead-like properties. Lipinski’s filter and the fit value filter were used to minimize hits to the top 2000. Simultaneous docking was carried out for 200 hits for natural drugs belonging to the FDA-approved drug database. The top 28 hits from these experiments, with promising predicted pharmacodynamic and pharmacokinetic properties, are reported here. To optimize these hits as Mpro inhibitors and potential treatment options for COVID-19, bench work investigations are needed.

Evolutionary chemical binding similarity approach integrated with 3D-QSAR method for effective virtual screening

BackgroundDespite continued efforts using chemical similarity methods in virtual screening, currently developed approaches suffer from time-consuming multistep procedures and low success rates. We recently developed a machine learning-based chemical binding similarity model considering common structural features from molecules binding to the same, or evolutionarily related targets. The chemical binding similarity measures the resemblance of chemical compounds in terms of binding site similarity to better describe functional similarities that arise from target binding. In this study, we have shown how the chemical binding similarity could be used in virtual screening together with the conventional structure-based methods.ResultsThe chemical binding similarity, receptor-based pharmacophore, chemical structure similarity, and molecular docking methods were evaluated to identify an effective virtual screening procedure for desired target proteins. When we tested the chemical binding similarity method with test sets of 51 kinases, it outperformed the traditional structural similarity-based methods as well as structure-based methods, such as molecular docking and receptor-based pharmacophore modeling, in terms of finding active compounds. We further validated the results by performing virtual screening (using the chemical binding similarity and receptor-based pharmacophore methods) against a completely blind dataset for mitogen-activated protein kinase kinase 1 (MEK1), ephrin type-B receptor 4 (EPHB4) and wee1-like protein kinase (WEE1). The in vitro kinase binding assay confirmed that 6 out of 13 (46.2%) for MEK1 and 2 out of 12 (16.7%) for EPHB4 were newly identified only by the chemical binding similarity model.ConclusionsWe report that the virtual screening results could further be improved by combining the chemical binding similarity model with 3D-QSAR pharmacophore and molecular docking models. Not only the new inhibitors are identified in this study, but also many of the identified molecules have low structural similarity scores against already reported inhibitors and that show the revelation of novel scaffolds.

Pharmacophore model of immunocheckpoint protein PD-L1 by cosolvent molecular dynamics simulations

Due to the clinical success of cancer immunotherapy, the design of PD-1/PD-L1 inhibitors has become an area of active research. To date, only five monoclonal antibodies are approved by FDA. Despite the great effort for the development of small molecules and peptides as inhibitors, only one of those has reached clinical trials. Pharmacophore models are a proven useful tool for drug design. The effectiveness of receptor-based pharmacophore modeling is limited due to the neglect of protein flexibility and desolvation effects. In the present application, we performed co-solvent molecular dynamics simulations of PD-L1 protein in order to obtain a pharmacophore model of PD-L1 immunecheckpoint protein. The analysis of probe molecules affinities by PD-L1 resulted in the identification of C’CFG beta strands as the zone with the highest convergence of hotspots, which corresponds to PD-1/PD-L1 interaction surface. The interactions maintained with PD-L1 residues varied from hydrophobic interactions to hydrogen bonds and salt bridges with critical residues for PD-1/PD-L1 binding (M115, A121, Y123, I54, Y56, E58, R125). The superposition of known inhibitors of PD-L1 as Peptide-57, BMS-1166 and high affinity PD-1(HAPD-1) allowed us to validate the pharmacophore model due to the good correlation with its features. The pharmacophore described herein can lead to the optimization and design of more selective and potent anti-cancer drugs.

Receptor-based pharmacophore modeling, virtual screening, and molecular docking studies for the discovery of novel GSK-3β inhibitors.

Considering the emerging importance of glycogen synthase kinase 3 beta (GSK-3β) inhibitors in treatment of Alzheimer's disease, multi-protein structure receptor-based pharmacophore modeling was adopted to generate a 3D pharmacophore model for (GSK-3β) inhibitors. The generated 3D pharmacophore was then validated using a test set of 1235 compounds. The ZINCPharmer web tool was used to virtually screen the public ZINC database using the generated 3D pharmacophore. A set of 12,251 hits was produced and then filtered according to their lead-like properties, predicted central nervous system (CNS) activity, and Pan-assay interference compounds (PAINS) fragments to 630 compounds. Scaffold Hunter was then used to cluster the filtered compounds according to their chemical structure framework. From the different clusters, 123 compounds were selected to cover the whole chemical space of the obtained hits. The SwissADME online tool was then used to filter out the compounds with undesirable pharmacokinetic properties giving a set of 91 compounds with promising predicted pharmacodynamic and pharmacokinetic properties. To confirm their binding capability to the GSK-3β binding site, molecular docking simulations were performed for the final 91 compounds in the GSK-3β binding site. Twenty-five compounds showed acceptable binding poses that bind to the key amino acids in the binding site Asp133 and Val135 with good binding scores. The quinolin-2-one derivative ZINC67773573 was found to be a promising lead for designing new GSK-3β inhibitors for Alzheimer's disease treatment. Graphical abstract A 3D pharmacophore model for the discovery of novel(GSK-3β) inhibitors.

Discovery of quorum sensing inhibitors of Pseudomonas fluorescens P07 by using a receptor-based pharmacophore model and virtual screening

The quorum sensing (QS) system enables bacteria, such as Pseudomonas fluorescens, which are vital psychrotrophic food spoilage bacteria, to control various physiological processes. Hence, targeting the bacterial QS might be a good method to control food spoilage and improve food quality. In this study, we screened the ZINC natural product database to search for potential QS inhibitors (QSIs) of P. fluorescens P07 using receptor-based pharmacophore model and virtual screening methods. A total of 28 compounds with high docking scores were tested for their anti-QS activities. The results showed that 22 compounds possessed anti-QS activities and the hit rate was very high (78.57%). Among them, guaiacol, citral et al. showed potent anti-QS activities. Moreover, the effects of guaiacol and citral on the QS-regulated phenotypes were determined. The results showed that guaiacol and citral significantly inhibited the swimming motility, production of extracellular enzymes, and siderophores of P. fluorescens P07. The inhibitory mechanism on the bacterial QS system was investigated by molecular docking analysis.

Identification of human tau-tubulin kinase 1 inhibitors: an integrated e-pharmacophore-based virtual screening and molecular dynamics simulation

Tau-tubulin kinase 1 inhibitors inhibit tau protein phosphorylation on Ser198, Ser199, Ser202, Ser422, and also in paired helical filaments. We developed receptor-based pharmacophore models by exploiting three TTBK1 protein structures, i.e., 4NFN, 4BTM, and 4BTK. The integrated e-pharmacophore based virtual screening and molecular dynamics simulation recognized four hits viz. ZINC14644839, ZINC00012956, ZINC91332506, and ZINC69775110 as TTBK1 inhibitors. The Glide XP docking energies (−8.48 to −10.71 kcal.mol−1) of hits were better than cocrystal ligand of 4NFN protein structure (−8.37 kcal.mol−1). Among the hits, ZINC14644839 possessed best binding energy with four hydrogen bonding interactions. The inhibitors showed acceptable calculated ADME and blood-brain barrier permeability properties and could be potential TTBK1 inhibitors for neurodegenerative diseases.Communicated by Ramaswamy H. Sarma

Identification of PfENR inhibitors: A hybrid structure-based approach in conjunction with molecular dynamics simulations.

In the current study, we have constructed receptor-based pharmacophore models by exploiting the Plasmodium falciparum enoyl-acyl carrier protein reductase (PfENR) structural proteome. The derived models were subjected to a series of validation procedures to list the representative hypotheses that can be used for the screening of the Drug-like Diverse Database. A set of 739 molecules was retrieved and analyzed for the adsorption, distribution, metabolism, excretion and toxicity (ADMET) and drug-likeness attributes. The filtered drug-like molecules (64) were then subjected to molecular docking and HYDE assessment studies. The hybrid structure-based approach yielded 4 molecules, UKR1308259, ENA1096786, UKR403454, and ASI51224, as PfENR inhibitors. The stability of these inhibitors was assessed using molecular mechanics-generalized born surface area approach-based free binding energy calculations and molecular dynamics simulations. Molecular mechanics-generalized born surface area calculations and molecular dynamics simulations showed that UKR1308259, ENA1096786, and ASI51224 were more potent PfENR inhibitors. The rationale behind the current work was to identify orally available inhibitor molecules with diverse scaffolds that could serve as initial leads for the drug design against PfENR.

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).