Pharmacophore Modelling and 3D-QSAR Studies on -Phenylpyrazinones as Corticotropin-Releasing Factor 1 Receptor Antagonists

Pharmacophore modelling-based virtual screening of compound is a ligand-based approach and is useful when the 3D structure of target is not available but a few known active compounds are known. Pharmacophore mapping studies were undertaken for a set of 50 N3-phenylpyrazinones possessing Corticotropin-releasing Factor 1 (CRF 1) antagonistic activity. Six point pharmacophores with two hydrogen bond acceptors, one hydrogen bond donor, two hydrophobic regions, and one aromatic ring as pharmacophoric features were developed. Amongst them the pharmacophore hypothesis AADHHR.47 yielded a statistically significant 3D-QSAR model with 0.803 as value and was considered to be the best pharmacophore hypothesis. The developed pharmacophore model was externally validated by predicting the activity of test set molecules. The squared predictive correlation coefficient of 0.91 was observed between experimental and predicted activity values of test set molecules. The geometry and features of pharmacophore were expected to be useful for the design of selective CRF 1 receptor antagonists.

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The search for peptide deformylase inhibitor from Indonesian Medicinal Plant Database: an in-silico investigation

Biointerface Research in Applied Chemistry ◽

10.33263/briac102.117121 ◽

2020 ◽

Vol 10 (2) ◽

pp. 5117-5121

Keyword(s):

Medicinal Plant ◽

Md Simulation ◽

Pharmacophore Model ◽

Peptide Deformylase ◽

Hydrogen Bond Donor ◽

Pharmacophore Modelling ◽

Promising Target ◽

Poisson Boltzmann ◽

Pharmacophore Hypothesis ◽

Novel Antibiotics

The peptide deformylase protein (PDF) has emerged as a promising target for the discovery of novel antibiotics with a novel mechanism of action. The current investigation was aimed at identifying potential inhibitor of PDF by using structure-based pharmacophore modelling. The pharmacophore hypothesis consisted of one hydrophobic, one negative ionizable, and one hydrogen bond donor features which were built using the structure of cognate ligand of PDF (BB2). Further, the pharmacophore model was validated and used to screen hit molecule against Indonesian Medicinal Plant Database and retrieved 32 hit molecules. All hit molecules were docked to PDF and four best molecules were subjected for 50-ns molecular dynamics (MD) simulation. MD simulation confirmed the docked poses of ligand as indicated by the RMSD and RMSF values. Prediction of affinities employing Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) method revealed that quercetin 3-(6''-malonylneohesperidoside) had a comparable affinity with that of BB2, which indicated its potential as a novel herbal-based PDF inhibitor.

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Prediction of Novel Anoctamin1 (ANO1) Inhibitors Using 3D-QSAR Pharmacophore Modeling and Molecular Docking

International Journal of Molecular Sciences ◽

10.3390/ijms19103204 ◽

2018 ◽

Vol 19 (10) ◽

pp. 3204 ◽

Cited By ~ 5

Author(s):

Yoon Lee ◽

Gwan-Su Yi

Keyword(s):

Hydrogen Bond ◽

Molecular Docking ◽

Correlation Coefficient ◽

High Throughput Screening ◽

Interaction Analysis ◽

Pharmacophore Model ◽

3D Qsar ◽

Pharmacophore Modeling ◽

Hydrogen Bond Acceptor ◽

Test Set

Recently, anoctamin1 (ANO1), a calcium-activated chloride channel, has been considered an important drug target, due to its involvement in various physiological functions, as well as its possibility for treatment of cancer, pain, diarrhea, hypertension, and asthma. Although several ANO1 inhibitors have been discovered by high-throughput screening, a discovery of new ANO1 inhibitors is still in the early phase, in terms of their potency and specificity. Moreover, there is no computational model to be able to identify a novel lead candidate of ANO1 inhibitor. Therefore, three-dimensional quantitative structure-activity relationship (3D-QSAR) pharmacophore modeling approach was employed for identifying the essential chemical features to be required in the inhibition of ANO1. The pharmacophore hypothesis 2 (Hypo2) was selected as the best model based on the highest correlation coefficient of prediction on the test set (0.909). Hypo2 comprised a hydrogen bond acceptor, a hydrogen bond donor, a hydrophobic, and a ring aromatic feature with good statistics of the total cost (73.604), the correlation coefficient of the training set (0.969), and the root-mean-square deviation (RMSD) value (0.946). Hypo2 was well assessed by the test set, Fischer randomization, and leave-one-out methods. Virtual screening of the ZINC database with Hypo2 retrieved the 580 drug-like candidates with good potency and ADMET properties. Finally, two compounds were selected as novel lead candidates of ANO1 inhibitor, based on the molecular docking score and the interaction analysis. In this study, the best pharmacophore model, Hypo2, with notable predictive ability was successfully generated, and two potential leads of ANO1 inhibitors were identified. We believe that these compounds and the 3D-QSAR pharmacophore model could contribute to discovering novel and potent ANO1 inhibitors in the future.

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Pharmacophore modelling of vanillin derivatives, favipiravir, chloroquine, hydroxychloroquine, monolaurin and tetrodotoxin as MPro inhibitors of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)

BMC Research Notes ◽

10.1186/s13104-020-05379-6 ◽

2020 ◽

Vol 13 (1) ◽

Author(s):

Woon Yi Law ◽

Mohd Razip Asaruddin ◽

Showkat Ahamd Bhawani ◽

Samsur Mohamad

Keyword(s):

Hydrogen Bond ◽

Pharmacophore Model ◽

Significant Activity ◽

Inhibition Activity ◽

Pharmacophore Modelling ◽

Common Features ◽

Complex Interactions ◽

Test Sets ◽

Vanillin Derivatives ◽

Modelling Approach

Abstract Objectives The aim of this study was to use Ligand-based pharmacophore modelling approach for four established antiviral drugs, namely remdesivir, lopinavir, ritonavir and hydroxychloroquine for COVID-19 inhibitors as training sets. In this study Twenty vanillin derivatives together with monolaurin and tetrodotoxin were used as test sets to evaluate as potential SARS-CoV-2 inhibitors. The Structure-based pharmacophore modelling approach was also performed using 5RE6, 5REX and 5RFZ in order to analyse the binding site and ligand–protein complex interactions. Results The pharmacophore modelling mode of 5RE6 displayed two Hydrogen Bond Acceptors (HBA) and one Hydrophobic (HY) interaction. Besides, the pharmacophore model of 5REX showed two HBA and two HY interactions. Finally, the pharmacophore model of 5RFZ showed three HBA and one HY interaction. Based on ligand-based approach, 20 Schiff-based vanillin derivatives, showed strong MPro inhibition activity. This was due to their good alignment and common features to PDB-5RE6. Similarly, monolaurin and tetrodotoxin displayed some significant activity against SARS-CoV-2. From structure-based approach, vanillin derivatives (1) to (12) displayed some potent MPro inhibition against SARS-CoV-2. Favipiravir, chloroquine and hydroxychloroquine also showed some significant MPro inhibition.

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The Characteristics of PD-L1 Inhibitors, from Peptides to Small Molecules

Molecules ◽

10.3390/molecules24101940 ◽

2019 ◽

Vol 24 (10) ◽

pp. 1940 ◽

Cited By ~ 3

Author(s):

Yanwen Zhong ◽

Xuanyi Li ◽

Hequan Yao ◽

Kejiang Lin

Keyword(s):

Hydrogen Bond ◽

Small Molecules ◽

Pharmacophore Model ◽

Amino Acid Residues ◽

Tumor Treatment ◽

Hydrogen Bond Donor ◽

Treatment Results ◽

Hydrogen Bond Acceptor ◽

Checkpoint Pathway ◽

Pharmacophore Models

The programmed cell death ligand protein 1 (PD-L1) is a member of the B7 protein family and consists of 290 amino acid residues. The blockade of the PD-1/PD-L1 immune checkpoint pathway is effective in tumor treatment. Results: Two pharmacophore models were generated based on peptides and small molecules. Hypo 1A consists of one hydrogen bond donor, one hydrogen bond acceptor, two hydrophobic points and one aromatic ring point. Hypo 1B consists of one hydrogen bond donor, three hydrophobic points and one positive ionizable point. Conclusions: The pharmacophore model consisting of a hydrogen bond donor, hydrophobic points and a positive ionizable point may be helpful for designing small-molecule inhibitors targeting PD-L1.

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In Silico Ligand-Based Methods Targeting Porcupine Receptor Inhibitors with Potential Anticancer Effect

Proceedings ◽

10.3390/ecsoc-22-05674 ◽

2018 ◽

Vol 9 (1) ◽

pp. 19

Author(s):

Ana Borota ◽

Luminita Crisan

Keyword(s):

Wnt Signaling ◽

In Silico ◽

Pharmacophore Model ◽

Correlation Coefficients ◽

3D Qsar ◽

Qsar Model ◽

Hydrogen Bond Donor ◽

Screening Process ◽

Wnt Proteins ◽

In Silico Study

Porcupine is a protein belonging to the O-acyltransferase family, involved in the catalyzing of palmitoylation of wingless-related integration (WNT) proteins. WNT signaling has significant roles in many physiological functions, e.g., hematopoiesis, homeostasis, neurogenesis, and apoptosis. Anomalous WNT signaling has been observed to be related to tumor generation, and metabolic and neurodegenerative disorders. Therefore, compounds that inhibit this pathway are of great interest for the development of therapeutic approaches. For a better understanding of the common traits of such compounds, we have undertaken an in silico study in order to develop a valid ligand-based pharmacophore model based on a series of porcupine inhibitors. The best pharmacophore hypothesis found after the 3D QSAR validation process is represented by the following features: one hydrogen bond donor (D), three rings (R) and one hydrophobic centroid (H). The 3D-QSAR model obtained using the DRRRH hypothesis shows statistically significant parameters: correlation coefficients for the training set: R2 of 0.90, and a predictive correlation coefficient for the test set, Q2 of 0.86. The assessment of the pharmacophore model was also done and provided very reliable metrics values (Receiver Operating Characteristic—ROC of 1; Robust Initial Enhancement—RIE of 17.97). Thereby, we obtained valuable results which can be further used in the virtual screening process for the discovery of new active compounds with potential anticancer activity.

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Sub-Pharmacophore Generation of JNK3 Inhibitors

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.444-445.1756 ◽

2013 ◽

Vol 444-445 ◽

pp. 1756-1760 ◽

Cited By ~ 1

Author(s):

Yan Ling Zhang ◽

Yuan Ming Wang ◽

Yan Jiang Qiao

Keyword(s):

Hydrogen Bond ◽

Pharmacophore Model ◽

High Specificity ◽

Data Bank ◽

Chinese Herbs ◽

Mitogen Activated Protein Kinase ◽

Specific Class ◽

Hydrogen Bond Donor ◽

Hydrogen Bond Acceptor ◽

Appraisal Index

The structure-based pharmacophore (SBP) model is consisted by the complementarity of the chemical features and space of the interaction between the ligand and receptor. The SBP models always have a high specificity which can only represent the specific class of the ligand. To simplify the models, sub-pharmacophore was then proposed in present study, and was expected to have and only have the most important or the common chemical features which play the major role in the interaction of ligand and receptor. Sub-pharmacophore should contain 4-6 features, the higher specificity with more features, and vice versa. The sub-pharmacophore was generated by the random combination of features from the structure-based models. With the MDL Drug Data Report database used as the testing database, a new metric CAI (comprehensive appraisal index), which integrated the metrics of E and A%, was defined and used to determine the best sub-pharmacophore model. C-Jun N-terminal kinase (JNKs) is one of the mitogen-activated protein kinase family, and widely involved in immune response and inflammatory response, and other pathological processes. JNK3 is mainly distributed in the brain and nervous system. In present study, twenty-five initial SBP models of JNK3 inhibitors were directly constructed from the Protein Data Bank (PDB) complexes by the LigandScout software. Then, 1018 sub-pharmacophore models were obtained from the 25 initial models. Finally, the best sub-pharmacophore was determined which was simplified from the initial model generated from the 3FI2 complex, and included four features: one hydrogen bond donor, one hydrogen bond acceptor, and two hydrophobic groups. The metrics of E, A% and CAI value of the best sub-pharmacophore model are 17.47, 31.15 and 5.44, respectively. The potential JNK3 inhibitors were then identified from Chinese herbs with the best sub-pharmacophore model, and 286 compounds were obtained.

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Identification of new checkpoint kinase-1 (Chk1) inhibitors by docking, 3D-QSAR, and pharmacophore-modeling methods

Canadian Journal of Chemistry ◽

10.1139/v2012-047 ◽

2012 ◽

Vol 90 (8) ◽

pp. 675-692 ◽

Cited By ~ 6

Author(s):

Premlata K. Ambre ◽

Raghuvir R. S. Pissurlenkar ◽

Evans C. Coutinho ◽

Radhakrishnan P. Iyer

Keyword(s):

Hydrogen Bond ◽

3D Qsar ◽

Pharmacophore Modeling ◽

Docking Studies ◽

Hydrogen Bond Donor ◽

Hydrogen Bond Acceptor ◽

Checkpoint Kinase ◽

Checkpoint Kinase 1 ◽

Qsar Models ◽

Potential Inhibitors

Inhibition of checkpoint kinase-1 (Chk1) by small molecules is of great therapeutic interest in the field of oncology and for understanding cell-cycle regulations. This paper presents a model with elements from docking, pharmacophore mapping, the 3D-QSAR approaches CoMFA, CoMSIA and CoRIA, and virtual screening to identify novel hits against Chk1. Docking, 3D-QSAR (CoRIA, CoMFA and CoMSIA), and pharmacophore studies delineate crucial site points on the Chk1 inhibitors, which can be modified to improve activity. The docking analysis showed residues in the proximity of the ligands that are involved in ligand–receptor interactions, whereas CoRIA models were able to derive the magnitude of these interactions that impact the activity. The ligand-based 3D-QSAR methods (CoMFA and CoMSIA) highlight key areas on the molecules that are beneficial and (or) detrimental for activity. The docking studies and 3D-QSAR models are in excellent agreement in terms of binding-site interactions. The pharmacophore hypotheses validated using sensitivity, selectivity, and specificity parameters is a four-point model, characterized by a hydrogen-bond acceptor (A), hydrogen-bond donor (D), and two hydrophobes (H). This map was used to screen a database of 2.7 million druglike compounds, which were pruned to a small set of potential inhibitors by CoRIA, CoMFA, and CoMSIA models with predicted activity in the range of 8.5–10.5 log units.

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IDENTIFICATION OF POTENTIAL INHIBITORS FOR LOWERING CHOLESTEROL LEVEL BY INHIBITING PCSK9

Asian Journal of Pharmaceutical and Clinical Research ◽

10.22159/ajpcr.2016.v9i6.14272 ◽

2016 ◽

Vol 9 (6) ◽

pp. 230 ◽

Cited By ~ 1

Author(s):

Rathi Suganya

Keyword(s):

Molecular Dynamics ◽

Hydrogen Bond ◽

Cholesterol Level ◽

Ldl Cholesterol ◽

Ldl Receptor ◽

Pharmacophore Model ◽

Dynamics Simulation ◽

Hydrogen Bond Donor ◽

Hydrogen Bond Acceptor ◽

Cholesterol Levels

ABSTRACTObjective: PCSK9 has medical significance in lowering cholesterol levels. Inhibitors target and inactivate PCSK9 in the liver. Knocking out PCSK9 (proprotein convertase subtilisin kexin 9) reduces the amount of harmful LDL cholesterol circulating in the bloodstream. There are two known inhibitors for treating the cardiovascular disease “Arilocumab” and “Evalocumab”. However there are many side-effects. The current study is to identify natural and synthetic inhibitor using the pharmacophoric feature of the known inhibitor and validating the short listed candidates using Molecular dynamics and ADMET properties.Methods: Known inhibitors for the PCSK9 Protein were taken from the BINDING DATABASE. Molecular docking was performed for the known inhibitors with the PCSK9 protein. After docking the best inhibitor was selected and the docking result was then imported to find the pharmacophoric features.Results: The pharmacophore model was generated with 3 features containing 1 hydrogen bond acceptor(A),1 Hydrogen bond donor(B) and 1 Aromatic ring. The constructed e-pharmacophore model was screened with more than 20000 natural compounds. 5 compounds were short listed. Among them ZINC85625485 has glide score of -13.03 kcal/mol with glide energy was -57.62 kcal/mol and ZINC85625406 has glide score of -8.1kcal/mol with glide energy was -39.33kcal/mol were taken as the best Hits.Conclusion: PCSK9 is known to be a therapeutic agent as it controls the plasma LDL cholesterol levels by posttranslational regulation of the LDL receptor. Therefore, up-regulation of PCSk9 can lead to elevated cholesterol level in such case inhibition of PCSK9 will be a effective remedy. In this study already known inhibitors were taken and pharmacophore feature was generated. Zinc database was screened to find out novel compounds with similar pharmacophore features that can act as potentially active compound against PCSK9. ZINC85625485 and ZINC85625406 were short listed as lead compounds with Molecular dynamics simulation and checking the ADMET properties. Keywords: PCSK9, Docking, ADMET, Molecular Dynamics.

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3D QSAR Studies on Benzoxazoles and Oxazolo-(4, 5-b)pyridines as Anti-fungal agents

International Journal of Pharmaceutical Sciences and Nanotechnology ◽

10.37285/ijpsn.2009.2.2.11 ◽

2009 ◽

Vol 2 (2) ◽

pp. 557-565

Author(s):

Shaheen Begum ◽

Satya Parameshwar K ◽

Ravindra G K ◽

Achaiah G

Keyword(s):

Hydrogen Bond ◽

Antifungal Activity ◽

Drug Research ◽

3D Qsar ◽

Qsar Model ◽

Hydrogen Bond Acceptor ◽

Test Set ◽

Qsar Studies ◽

The Cost ◽

Anti Fungal

Benzoxazoles and Oxazolo-[4,5-b]pyridines have been reported as potent anti-fungal agents. 3D QSAR tools including CoMFA and CoMSIA have been known to be a promising approaches is to correlate structures and activity which further enable the medicinal chemists to design more potent molecules thus curtailing the cost and time in drug research. CoMFA and CoMSIA studies have been carried out on 31 molecules of benzoxazole and oxazolopyridines in order to determine the structural properties required for effective antifungal activity. 26 compounds were evaluated for establishing QSAR model, which was then validated by predicting the activities of five test set molecules. All the molecules were aligned by SYBYL database alignment which led to a best model with q2 value of 0.835, r2=0.976 and r2pred=0.773. This model was further employed to derive CoMSIA models, a best model with steric, electrostatic, hydrophobic and hydrogen bond acceptor indices exhibited q2 = 0.812, r2=0.971 and r2pred=0.81. The models thus obtained from this study can be useful for the design and development of new potential anti-fungal agents.

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Discovery of structural prospects of imidazo[1,5-a]pyrazine derivatives as BTK inhibitors against cancer: A computational study

Letters in Drug Design & Discovery ◽

10.2174/1570180818666210802104517 ◽

2021 ◽

Vol 18 ◽

Author(s):

Amena Ali ◽

Abuzer Ali ◽

Mohamed Jawed Ahsan

Keyword(s):

Molecular Docking ◽

Virtual Screening ◽

Anticancer Agents ◽

Oral Absorption ◽

Computational Study ◽

Pharmacophore Model ◽

3D Qsar ◽

Pharmacokinetic Parameters ◽

Pharmacophore Hypothesis ◽

Btk Inhibitors

Background: Bruton’s tyrosine kinase (BTK) plays an important role in cell development and proliferation. BTK inhibitors are encouraging novel agents against B-cell malignancies and autoimmune diseases. Although BTK inhibitors have been approved by the FDA, but to lower off-target effects and to reduce emerging resistances, it is necessary to develop novel BTK inhibitors with better outcomes and minimum side effects. Objective: The present study includes pharmacophore hypothesis, 3D QSAR, virtual screening, docking, ADME analysis and screening of potential imidazo[1,5-a]pyrazine derivatives as BTK inhibitors. Methods: Generation of pharmacophore hypothesis, virtual screening, 3D QSAR, molecular docking and ADME analysis. Methods: Generation of pharmacophore hypothesis, virtual screening, 3D QSAR, molecular docking and ADME analysis. Results: Pharmacophore study generated 20 pharmacophore hypotheses as BTK inhibitor. The five-point hypothesis DPRRR_1 were selected, consist one hydrogen bond donor, one positive ionic, and three ring aromatic features. 3D QSAR study of the compounds provided the best model with high Q2 (0.8683), R2 (0.983) and R2CV (0.5338) values. The developed pharmacophore model was further taken for screening of ZINC database ligands for evaluation of docking interaction and physiochemical properties. Potent compounds of the series 15, 27, 8n and 38 showed good docking scores -8.567, -7.465, -6.922, -6.137, respectively. Conclusion: All the pharmacokinetic parameters analysed, including human oral absorption of active compounds of the series were found to be within the permissible range. The present geometry and features included in pharmacophore hypothesis can be used for the development of novel BTK inhibitors as anticancer agents.

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