In-silico virtual screening for identification of potent inhibitor for L2-β-lactamase from Stenotrophomonas maltophilia through molecular docking, molecular dynamics analysis study

2020 ◽  
pp. 1-15
Author(s):  
Ridhi Sharma ◽  
Dhananjay Jade ◽  
Surender Mohan ◽  
Rahul Chandel ◽  
Shobana Sugumar
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Virtual Screening ◽  
In Silico ◽  
Stenotrophomonas Maltophilia ◽  
Potent Inhibitor ◽  
Dynamics Analysis ◽  
Analysis Study

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.

Promising Anti-stroke Signature of Voglibose: Investigation through In- Silico Molecular Docking and Virtual Screening in In-Vivo Animal Studies

2020 ◽  
Vol 20 (3) ◽  
pp. 223-235
Author(s):  
Pooja Shah ◽  
Vishal Chavda ◽  
Snehal Patel ◽  
Shraddha Bhadada ◽  
Ghulam Md. Ashraf
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
In Silico ◽  
Reductase Activity ◽  
Infarct Volume ◽  
Docking Studies ◽  
Serum Glucose ◽  
In Vivo Studies ◽  
In Silico Molecular Docking

Background: Postprandial hyperglycemia considered to be a major risk factor for cerebrovascular complications. Objective: The current study was designed to elucidate the beneficial role of voglibose via in-silico in vitro to in-vivo studies in improving the postprandial glycaemic state by protection against strokeprone type 2 diabetes. Material and Methods: In-Silico molecular docking and virtual screening were carried out with the help of iGEMDOCK+ Pymol+docking software and Protein Drug Bank database (PDB). Based on the results of docking studies, in-vivo investigation was carried out for possible neuroprotective action. T2DM was induced by a single injection of streptozotocin (90mg/kg, i.v.) to neonates. Six weeks after induction, voglibose was administered at the dose of 10mg/kg p.o. for two weeks. After eight weeks, diabetic rats were subjected to middle cerebral artery occlusion, and after 72 hours of surgery, neurological deficits were determined. The blood was collected for the determination of serum glucose, CK-MB, LDH and lipid levels. Brains were excised for determination of brain infarct volume, brain hemisphere weight difference, Na+-K+ ATPase activity, ROS parameters, NO levels, and aldose reductase activity. Results: In-silico docking studies showed good docking binding score for stroke associated proteins, which possibly hypotheses neuroprotective action of voglibose in stroke. In the present in-vivo study, pre-treatment with voglibose showed a significant decrease (p<0.05) in serum glucose and lipid levels. Voglibose has shown significant (p<0.05) reduction in neurological score, brain infarct volume, the difference in brain hemisphere weight. On biochemical evaluation, treatment with voglibose produced significant (p<0.05) decrease in CK-MB, LDH, and NO levels in blood and reduction in Na+-K+ ATPase, oxidative stress, and aldose reductase activity in brain homogenate. Conclusion: In-silico molecular docking and virtual screening studies and in-vivo studies in MCAo induced stroke, animal model outcomes support the strong anti-stroke signature for possible neuroprotective therapeutics.

Virtual Screening, Molecular docking and in-silico ADME-Tox analysis for identification of potential main protease (Mpro) enzyme inhibitors

2020 ◽  
Vol 18 ◽  
Author(s):  
Debadash Panigrahi ◽  
Ganesh Prasad Mishra
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
In Silico ◽  
Data Bank ◽  
Future Research ◽  
Reference Compound ◽  
Unexpected Death ◽  
Main Protease ◽  
In Silico Admet

Objective:: Recent pandemic caused by SARS-CoV-2 described in Wuhan China in December-2019 spread widely almost all the countries of the world. Corona virus (COVID-19) is causing the unexpected death of many peoples and severe economic loss in several countries. Virtual screening based on molecular docking, drug-likeness prediction, and in silico ADMET study has become an effective tool for the identification of small molecules as novel antiviral drugs to treat diseases. Methods:: In the current study, virtual screening was performed through molecular docking for identifying potent inhibitors against Mpro enzyme from the ZINC library for the possible treatment of COVID-19 pandemic. Interestingly, some compounds are identified as possible anti-covid-19 agents for future research. 350 compounds were screened based on their similarity score with reference compound X77 from ZINC data bank and were subjected to docking with crystal structure available of Mpro enzyme. These compounds were then filtered by their in silico ADME-Tox and drug-likeness prediction values. Result:: Out of these 350 screened compounds, 10 compounds were selected based on their docking score and best docked pose in comparison to the reference compound X77. In silico ADME-Tox and drug likeliness predictions of the top compounds were performed and found to be excellent results. All the 10 screened compounds showed significant binding pose with the target enzyme main protease (Mpro) enzyme and satisfactory pharmacokinetic and toxicological properties. Conclusion:: Based on results we can suggest that the identified compounds may be considered for therapeutic development against the COVID-19 virus and can be further evaluated for in vitro activity, preclinical, clinical studies and formulated in a suitable dosage form to maximize their bioavailability.

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.

Sign in / Sign up

Export Citation Format

Share Document