scholarly journals Structure-Based Pharmacophore Modeling, Virtual Screening, Molecular Docking, ADMET, and Molecular Dynamics (MD) Simulation of Potential Inhibitors of PD-L1 from the Library of Marine Natural Products

Marine Drugs ◽  
2021 ◽  
Vol 20 (1) ◽  
pp. 29
Author(s):  
Lianxiang Luo ◽  
Ai Zhong ◽  
Qu Wang ◽  
Tongyu Zheng
Keyword(s):  
Molecular Dynamics ◽  
Natural Products ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Marine Natural Products ◽  
Md Simulation ◽  
Pharmacophore Model ◽  
Pharmacophore Modeling ◽  
Dynamics Simulation ◽  
Stable Conformation

Background: In the past decade, several antibodies directed against the PD-1/PD-L1 interaction have been approved. However, therapeutic antibodies also exhibit some shortcomings. Using small molecules to regulate the PD-1/PD-L1 pathway may be another way to mobilize the immune system to fight cancer. Method: 52,765 marine natural products were screened against PD-L1(PDBID: 6R3K). To identify natural compounds, a structure-based pharmacophore model was generated, following by virtual screening and molecular docking. Then, the absorption, distribution, metabolism, and excretion (ADME) test was carried out to select the most suitable compounds. Finally, molecular dynamics simulation was also performed to validate the binding property of the top compound. Results: Initially, 13 small marine molecules were screened based on the pharmacophore model. Then, two compounds were selected for further evaluation based on the molecular docking scores. After ADME and toxicity studies, molecule 51320 was selected for further verification. By molecular dynamics analysis, molecule 51320 maintains a stable conformation with the target protein, so it has the chance to become an inhibitor of PD-L1. Conclusions: Through structure-based pharmacophore modeling, virtual screening, molecular docking, ADMET approaches, and molecular dynamics (MD) simulation, the marine natural compound 51320 can be used as a small molecule inhibitor of PD-L1.

Discovery of potential negative allosteric modulators of mGluR5 from natural products using pharmacophore modeling, molecular docking, and molecular dynamics simulation studies

2015 ◽  
Vol 93 (11) ◽  
pp. 1199-1206 ◽  
Author(s):  
Ludi Jiang ◽  
Yong Li ◽  
Liansheng Qiao ◽  
Xi Chen ◽  
Yusu He ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Natural Products ◽  
Molecular Docking ◽  
Molecular Dynamics Simulation ◽  
Pharmacophore Model ◽  
Pharmacophore Modeling ◽  
Dynamics Simulation ◽  
Allosteric Modulators ◽  
Subtype Selectivity ◽  
Wide Range

mGluR5, which belongs to the G-protein-coupled receptor superfamily, is believed to be associated with many human diseases, such as a wide range of neurological disorders, gastroesophageal reflux disease, and cancer. Comparing with compounds that target on the orthosteric binding site, significant roles have been established for mGluR5 negative allosteric modulators (NAMs) due to their higher subtype selectivity and more suitable pharmacokinetic profiles. Nevertheless, to date, none of them have come to market for various reasons. In this study, a 3D quantitative pharmacophore model was generated by using the HypoGen module in Discovery Studio 4.0. With several validation methods ultilized, the optimal pharmacophore model Hypo2 was selected to discover potential mGluR5 NAMs from natural products. Two hundred and seventeen potential NAMs were obtained after being filtered by Lipinski’s rule (≥4). Then, molecular docking was used to refine the pharmacophore-based screening results and analyze the binding mode of NAMs and mGluR5. Three compounds, aglaiduline, 5-O-ethyl-hirsutanonol, and yakuchinone A, with good ADMET properties, acceptable Fit value and estimated value, and high docking score, were reserved for a molecular dynamics simulation study. All of them have stability of ligand binding. From our computational results, there might exhibit drug-like negative allosteric moderating effects on mGluR5 in these natural products. This work provides a reliable method for discovering mGluR5 NAMs from natural products.

scholarly journals Structure based pharmacophore modeling, virtual screening, molecular docking and ADMET approaches for identification of natural anti-cancer agents targeting XIAP protein

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Firoz A. Dain Md Opo ◽  
Mohammed M. Rahman ◽  
Foysal Ahammad ◽  
Istiak Ahmed ◽  
Mohiuddin Ahmed Bhuiyan ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
Md Simulation ◽  
Pharmacophore Model ◽  
Pharmacophore Modeling ◽  
Drug Candidate ◽  
Inhibitor Of Apoptosis ◽  
Inhibitor Of Apoptosis Protein ◽  
Apoptosis Protein ◽  
Apoptosis Process

AbstractX-linked inhibitor of apoptosis protein (XIAP) is a member of inhibitor of apoptosis protein (IAP) family responsible for neutralizing the caspases-3, caspases-7, and caspases-9. Overexpression of the protein decreased the apoptosis process in the cell and resulting development of cancer. Different types of XIAP antagonists are generally used to repair the defective apoptosis process that can eliminate carcinoma from living bodies. The chemically synthesis compounds discovered till now as XIAP inhibitors exhibiting side effects, which is making difficulties during the treatment of chemotherapy. So, the study has design to identifying new natural compounds that are able to induce apoptosis by freeing up caspases and will be low toxic. To identify natural compound, a structure-based pharmacophore model to the protein active site cavity was generated following by virtual screening, molecular docking and molecular dynamics (MD) simulation. Initially, seven hit compounds were retrieved and based on molecular docking approach four compounds has chosen for further evaluation. To confirm stability of the selected drug candidate to the target protein the MD simulation approach were employed, which confirmed stability of the three compounds. Based on the finding, three newly obtained compounds namely Caucasicoside A (ZINC77257307), Polygalaxanthone III (ZINC247950187), and MCULE-9896837409 (ZINC107434573) may serve as lead compounds to fight against the treatment of XIAP related cancer, although further evaluation through wet lab is necessary to measure the efficacy of the compounds.

scholarly journals Potential Inhibitors of Fascin From A Database of Marine Natural Products: A Virtual Screening and Molecular Dynamics Study

2021 ◽  
Vol 9 ◽  
Author(s):  
Lirui Lin ◽  
Kai Lin ◽  
Xiaodong Wu ◽  
Jia Liu ◽  
Yinwei Cheng ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Natural Products ◽  
Virtual Screening ◽  
Marine Natural Products ◽  
Pharmacophore Model ◽  
Binding Affinities ◽  
Dynamic Interactions ◽  
Generalized Born ◽  
Accelerated Molecular Dynamics ◽  
Potential Inhibitors

Marine nature products are unique compounds that are produced by the marine environment including plants, animals, and microorganisms. The wide diversity of marine natural products have great potential and are versatile in terms of drug discovery. In this paper, we use state-of-the-art computational methods to discover inhibitors from marine natural products to block the function of Fascin, an overexpressed protein in various cancers. First, virtual screening (pharmacophore model and molecular docking) was carried out based on a marine natural products database (12015 molecules) and provided eighteen molecules that could potentially inhibit the function of Fascin. Next, molecular mechanics generalized Born surface area (MM/GBSA) calculations were conducted and indicated that four molecules have higher binding affinities than the inhibitor NP-G2-029, which was validated experimentally. ADMET analyses of pharmacokinetics demonstrated that one of the four molecules does not match the criterion. Finally, ligand Gaussian accelerated molecular dynamics (LiGaMD) simulations were carried out to validate the three inhibitors binding to Fascin stably. In addition, dynamic interactions between protein and ligands were analyzed systematically. Our study will accelerate the development of the cancer drugs targeting Fascin.

scholarly journals Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis

2021 ◽  
Vol 14 (4) ◽  
pp. 357
Author(s):  
Magdi E. A. Zaki ◽  
Sami A. Al-Hussain ◽  
Vijay H. Masand ◽  
Siddhartha Akasapu ◽  
Sumit O. Bajaj ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Simulation Analysis ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Dynamics Simulation ◽  
Multilinear Regression ◽  
Qsar Analysis ◽  
Main Protease

Due to the genetic similarity between SARS-CoV-2 and SARS-CoV, the present work endeavored to derive a balanced Quantitative Structure−Activity Relationship (QSAR) model, molecular docking, and molecular dynamics (MD) simulation studies to identify novel molecules having inhibitory potential against the main protease (Mpro) of SARS-CoV-2. The QSAR analysis developed on multivariate GA–MLR (Genetic Algorithm–Multilinear Regression) model with acceptable statistical performance (R2 = 0.898, Q2loo = 0.859, etc.). QSAR analysis attributed the good correlation with different types of atoms like non-ring Carbons and Nitrogens, amide Nitrogen, sp2-hybridized Carbons, etc. Thus, the QSAR model has a good balance of qualitative and quantitative requirements (balanced QSAR model) and satisfies the Organisation for Economic Co-operation and Development (OECD) guidelines. After that, a QSAR-based virtual screening of 26,467 food compounds and 360 heterocyclic variants of molecule 1 (benzotriazole–indole hybrid molecule) helped to identify promising hits. Furthermore, the molecular docking and molecular dynamics (MD) simulations of Mpro with molecule 1 recognized the structural motifs with significant stability. Molecular docking and QSAR provided consensus and complementary results. The validated analyses are capable of optimizing a drug/lead candidate for better inhibitory activity against the main protease of SARS-CoV-2.

Υπολογιστικά εργαλεία για την αναζήτηση νέων βιοδραστικών ενώσεων σε επιλεγμένους πρωτεϊνικούς στόχους

2017 ◽  
Author(s):  
Ευτυχία Κρίτση
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Molecular Dynamics Simulations ◽  
In Silico ◽  
Pharmacophore Modeling ◽  
Lead Optimization ◽  
Dynamics Simulations ◽  
Hiv 1

Στην παρούσα διατριβή πραγματοποιήθηκε εκτενής μελέτη για την αναζήτηση πρόδρομων βιοδραστικών ενώσεων (hits) από χημικές βιβλιοθήκες για τρείς βιολογικούς στόχους, μέσω της εφαρμογής εμπορικά διαθέσιμων in silico τεχνικών και μεθοδολογιών.Οι στόχοι που επιλέχθηκαν ανήκουν σε διαφορετικές κατηγορίες πρωτεϊνών με μεγάλο φαρμακευτικό ενδιαφέρον, που όμως παρουσιάζουν διαφορετικό επίπεδο ωριμότητας όσον αφορά την εφαρμογή υπολογιστικών εργαλείωνγια την ανακάλυψη νέων φαρμακευτικών ενώσεων. Συγκεριμένα, οι στόχοι που μελετήθηκαν είναι οι ακόλουθοι:•το ένζυμο της 14-α διμεθυλάσης της λανοστερόλης (CYP51) για την αναζήτηση νέων πρόδρομων βιοδραστικών ενώσεων με αντιμικροβιακές ιδιότητες,•το ένζυμο της HIV τύπου 1 πρωτεάσης (HIV-1 PR) για την αναζήτηση νέων πρόδρομων βιοδραστικών ενώσεων με αντι-HIV δράση,•ο διαμεμβρανικός υποδοχέας της Αγγειοτασίνης ΙΙ (ΑΤ1) για την αναζήτηση νέων πρόδρομων βιοδραστικών με αντιυπερτασική δράσηΟι κυριότερες τεχνικές που χρησιμοποιήθηκαν για την αναζήτηση πρόδρομων βιοδραστικών ενώσεων περιλαμβάνουν την Εικονική Σάρωση (Virtual Screening) με χρήση Φαρμακοφόρων Μοντέλων (Pharmacophore modeling), τη Μοριακή Πρόσδεση (Molecular Docking), την πρόβλεψη μοριακών ιδιοτήτων καθώς και Προσομοιώσεις Μοριακής Δυναμικής (Molecular Dynamics Simulations). Η στρατηγική που ακολουθήθηκε διαφέρει σημαντικά ανά στόχο όσον αφορά τη μεθοδολογική προσέγγιση και την επιλογή των υπολογιστικών εργαλείων-αλγορίθμων, δίνοντας έμφαση στη συμπληρωματικότητα των αποτελεσμάτων τους. Για την ανάδειξη των πρόδρομων βιοδραστικών ενώσεων, πραγματοποιήθηκαν in vitro βιολογικές δοκιμές των ενώσεων που προτάθηκαν μέσω των υπολογιστικών τεχνικών. Οι ενώσεις που επιλέχθηκαν παρουσίασαν ανασταλτική δράση (ή συγγένεια πρόσδεσης) σε ικανοποιητικό εύρος τιμών 102 nM–μΜ για να χαρακτηριστούν πρόδρομες βιοδραστικές. Μείζονος σημασίας είναι και το γεγονός ότι οι δομικοί σκελετοί των προτεινόμενων ενώσεων για κάθε στόχο, είναι διαφορετικοί τόσο μεταξύ τους όσο και συγκρινόμενοι με τα υφιστάμενα φαρμακευτικά μόρια. Ως εκ τούτου, μπορούν να αποτελέσουν κατάλληλα "υποστρώματα" για το επόμενο στάδιο που αφορά τη βελτιστοποίησή τους προς ενώσεις-οδηγούς (hit to lead optimization) και δυνητικά προς νέα φαρμακευτικά προϊόντα.

scholarly journals Molecular docking, pharmacophore based virtual screening and molecular dynamics studies towards the identification of potential leads for the management of H. pylori

RSC Advances ◽  
2019 ◽  
Vol 9 (45) ◽  
pp. 26176-26208 ◽  
Author(s):  
Manoj G. Damale ◽  
Rajesh B. Patil ◽  
Siddique Akber Ansari ◽  
Hamad M. Alkahtani ◽  
Abdulrahman A. Almehizia ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Md Simulations ◽  
Pharmacophore Modeling ◽  
Gastric Ulcers ◽  
Computational Approaches ◽  
Gastric Cancers ◽  
H Pylori

Computational approaches such as pharmacophore modeling, virtual screening and MD simulations were explored to find the potential hits as H. pylori specific panC inhibitors for the management of gastric ulcers and gastric cancers.

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