scholarly journals Identification of Novel Src Inhibitors: Pharmacophore-Based Virtual Screening, Molecular Docking and Molecular Dynamics Simulations

Molecules ◽  
2020 ◽  
Vol 25 (18) ◽  
pp. 4094
Author(s):  
Yi Zhang ◽  
Ting-jian Zhang ◽  
Shun Tu ◽  
Zhen-hao Zhang ◽  
Fan-hao Meng
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Root Mean Square ◽  
Protein Complexes ◽  
Md Simulations ◽  
Binding Mode ◽  
Strong Interactions ◽  
Mean Square ◽  
Dynamics Simulations

Src plays a crucial role in many signaling pathways and contributes to a variety of cancers. Therefore, Src has long been considered an attractive drug target in oncology. However, the development of Src inhibitors with selectivity and novelty has been challenging. In the present study, pharmacophore-based virtual screening and molecular docking were carried out to identify potential Src inhibitors. A total of 891 molecules were obtained after pharmacophore-based virtual screening, and 10 molecules with high docking scores and strong interactions were selected as potential active molecules for further study. Absorption, distribution, metabolism, elimination and toxicity (ADMET) property evaluation was used to ascertain the drug-like properties of the obtained molecules. The proposed inhibitor–protein complexes were further subjected to molecular dynamics (MD) simulations involving root-mean-square deviation and root-mean-square fluctuation to explore the binding mode stability inside active pockets. Finally, two molecules (ZINC3214460 and ZINC1380384) were obtained as potential lead compounds against Src kinase. All these analyses provide a reference for the further development of novel Src inhibitors.

scholarly journals A Possible Mechanism of Graphene Oxide to Enhance Thermostability of D-Psicose 3-Epimerase Revealed by Molecular Dynamics Simulations

2021 ◽  
Vol 22 (19) ◽  
pp. 10813
Author(s):  
Congcong Li ◽  
Zhongkui Lu ◽  
Min Wang ◽  
Siao Chen ◽  
Lu Han ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Thermal Stability ◽  
Graphene Oxide ◽  
Md Simulations ◽  
Strong Interactions ◽  
Limiting Factor ◽  
Active Site Residues ◽  
Detailed Mechanism ◽  
Dynamics Simulations ◽  
Thermal Stability Of

Thermal stability is a limiting factor for effective application of D-psicose 3-epimerase (DPEase) enzyme. Recently, it was reported that the thermal stability of DPEase was improved by immobilizing enzymes on graphene oxide (GO) nanoparticles. However, the detailed mechanism is not known. In this study, we investigated interaction details between GO and DPEase by performing molecular dynamics (MD) simulations. The results indicated that the domain (K248 to D268) of DPEase was an important anchor for immobilizing DPEase on GO surface. Moreover, the strong interactions between DPEase and GO can prevent loop α1′-α1 and β4-α4 of DPEase from the drastic fluctuation. Since these two loops contained active site residues, the geometry of the active pocket of the enzyme remained stable at high temperature after the DPEase was immobilized by GO, which facilitated efficient catalytic activity of the enzyme. Our research provided a detailed mechanism for the interaction between GO and DPEase at the nano–biology interface.

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.

scholarly journals Discovery of Potential Chemical Probe as Inhibitors of CXCL12 Using Ligand-Based Virtual Screening and Molecular Dynamic Simulation

Molecules ◽  
2020 ◽  
Vol 25 (20) ◽  
pp. 4829
Author(s):  
Sajjad Haider ◽  
Assem Barakat ◽  
Zaheer Ul-Haq
Keyword(s):  
Virtual Screening ◽  
Molecular Dynamic ◽  
Root Mean Square ◽  
Cancer Metastasis ◽  
Pharmacophore Model ◽  
Binding Mode ◽  
Dynamics Simulation ◽  
Radius Of Gyration ◽  
Mean Square ◽  
Dynamic Simulations

CXCL12 are small pro-inflammatory chemo-attractant cytokines that bind to a specific receptor CXCR4 with a role in angiogenesis, tumor progression, metastasis, and cell survival. Globally, cancer metastasis is a major cause of morbidity and mortality. In this study, we targeted CXCL12 rather than the chemokine receptor (CXCR4) because most of the drugs failed in clinical trials due to unmanageable toxicities. Until now, no FDA approved medication has been available against CXCL12. Therefore, we aimed to find new inhibitors for CXCL12 through virtual screening followed by molecular dynamics simulation. For virtual screening, active compounds against CXCL12 were taken as potent inhibitors and utilized in the generation of a pharmacophore model, followed by validation against different datasets. Ligand based virtual screening was performed on the ChEMBL and in-house databases, which resulted in successive elimination through the steps of pharmacophore-based and score-based screenings, and finally, sixteen compounds of various interactions with significant crucial amino acid residues were selected as virtual hits. Furthermore, the binding mode of these compounds were refined through molecular dynamic simulations. Moreover, the stability of protein complexes, Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), and radius of gyration were analyzed, which led to the identification of three potent inhibitors of CXCL12 that may be pursued in the drug discovery process against cancer metastasis.

scholarly journals In SilicoIdentification of Potent PPAR-γAgonists from Traditional Chinese Medicine: A Bioactivity Prediction, Virtual Screening, and Molecular Dynamics Study

2014 ◽  
Vol 2014 ◽  
pp. 1-19 ◽  
Author(s):  
Kuan-Chung Chen ◽  
Calvin Yu-Chian Chen
Keyword(s):  
Molecular Dynamics ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Virtual Screening ◽  
Prediction Models ◽  
Protein Complexes ◽  
Md Simulations ◽  
Peroxisome Proliferator ◽  
Peroxisome Proliferator Activated Receptors ◽  
Key Residues

The peroxisome proliferator-activated receptors (PPARs) related to regulation of lipid metabolism, inflammation, cell proliferation, differentiation, and glucose homeostasis by controlling the related ligand-dependent transcription of networks of genes. They are used to be served as therapeutic targets against metabolic disorder, such as obesity, dyslipidemia, and diabetes; especially, PPAR-γis the most extensively investigated isoform for the treatment of dyslipidemic type 2 diabetes. In this study, we filter compounds of traditional Chinese medicine (TCM) using bioactivities predicted by three distinct prediction models before the virtual screening. For the top candidates, the molecular dynamics (MD) simulations were also utilized to investigate the stability of interactions between ligand and PPAR-γprotein. The top two TCM candidates, 5-hydroxy-L-tryptophan and abrine, have an indole ring and carboxyl group to form the H-bonds with the key residues of PPAR-γprotein, such as residues Ser289 and Lys367. The secondary amine group of abrine also stabilized an H-bond with residue Ser289. From the figures of root mean square fluctuations (RMSFs), the key residues were stabilized in protein complexes with 5-Hydroxy-L-tryptophan and abrine as control. Hence, we propose 5-hydroxy-L-tryptophan and abrine as potential lead compounds for further study in drug development process with the PPAR-γprotein.

scholarly journals Prediction of Molecular Interactions And Physicochemical Properties Relevant For Vasopressin V2 Receptor Antagonism

2021 ◽  
Author(s):  
Ania de la Nuez Veulens ◽  
Yoanna María Álvarez Ginarte ◽  
Rolando Eduardo Rodríguez Fernandez ◽  
Fabrice Leclerc ◽  
Luis Alberto Montero Cabrera
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Physicochemical Properties ◽  
Molecular Dynamics Simulations ◽  
Binding Mode ◽  
Qsar Model ◽  
Antagonist Activity ◽  
Vasopressin V2 Receptor ◽  
V2 Receptor ◽  
Dynamics Simulations

Abstract We have developed two ligand and receptor-based computational approaches to study the physicochemical properties relevant to the biological activity of vasopressin V2 receptor (V2R) antagonist and eventually to predict the expected binding mode to V2R. The obtained Quantitative Structure Activity Relationship (QSAR) model showed a correlation of the antagonist activity with the hydration energy (EH2O) , the polarizability (P) and the calculated partial charge on atom N7 (q6) of the common substructure. The first two descriptors showed a positive contribution to antagonist activity, while the third one had a negative contribution. V2R was modeled and further relaxed on a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocoline (POPC) membrane by molecular dynamics simulations. The receptor antagonist complexes were guessed by molecular docking, and the stability of the most relevant structures were also evaluated by molecular dynamics simulations. As a result, amino acid residues Q96, W99, F105, K116, F178, A194, F307, and M311 were identified with the probably most relevant antagonist-receptor interactions on the studied complexes. The proposed QSAR model could explain the molecular properties relevant to the antagonist activity. The contributions to the antagonist-receptor interaction appeared also in agreement with the binding mode of the complexes obtained by molecular docking and Molecular Dynamics. These models will be used in further studies to look for new V2R potential antagonist molecules.

scholarly journals Use of multiple picosecond high-mass molecular dynamics simulations to predict crystallographic B-factors of folded globular proteins

2016 ◽  
Author(s):  
Yuan-Ping Pang
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Molecular Dynamics Simulations ◽  
Root Mean Square ◽  
A Priori ◽  
Model Systems ◽  
Dynamics Simulation ◽  
High Mass ◽  
Mean Square ◽  
Dynamics Simulations

ABSTRACTPredicting crystallographic B-factors of a protein from a conventional molecular dynamics simulation is challenging in part because the B-factors calculated through sampling the atomic positional fluctuations in a picosecond molecular dynamics simulation are unreliable and the sampling of a longer simulation yields overly large root mean square deviations between calculated and experimental B-factors. This article reports improved B-factor prediction achieved by sampling the atomic positional fluctuations in multiple picosecond molecular dynamics simulations that use uniformly increased atomic masses by 100-fold to increase time resolution. Using the third immunoglobulin-binding domain of protein G, bovine pancreatic trypsin inhibitor, ubiquitin, and lysozyme as model systems, the B-factor root mean square deviations (mean ± standard error) of these proteins were 3.1 ± 0.2–9 ± 1 Å2for Cα and 7.3 ± 0.9–9.6 ± 0.2 Å2for Cγ, when the sampling was done, for each of these proteins, over 20 distinct, independent, and 50-picosecond high-mass molecular dynamics simulations using AMBER forcefield FF12MC or FF14SB. These results suggest that sampling the atomic positional fluctuations in multiple picosecond high-mass molecular dynamics simulations may be conducive toa prioriprediction of crystallographic B-factors of a folded globular protein.

scholarly journals Changes of Conformation in Albumin with Temperature by Molecular Dynamics Simulations

Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 405
Author(s):  
Piotr Weber ◽  
Piotr Bełdowski ◽  
Krzysztof Domino ◽  
Damian Ledziński ◽  
Adam Gadomski
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Root Mean Square ◽  
Mean Square Displacement ◽  
Conformational Space ◽  
Global Dynamics ◽  
Mean Square ◽  
Conformational Entropy ◽  
The Mean ◽  
Dynamics Simulations

This work presents the analysis of the conformation of albumin in the temperature range of 300 K – 312 K , i.e., in the physiological range. Using molecular dynamics simulations, we calculate values of the backbone and dihedral angles for this molecule. We analyze the global dynamic properties of albumin treated as a chain. In this range of temperature, we study parameters of the molecule and the conformational entropy derived from two angles that reflect global dynamics in the conformational space. A thorough rationalization, based on the scaling theory, for the subdiffusion Flory–De Gennes type exponent of 0 . 4 unfolds in conjunction with picking up the most appreciable fluctuations of the corresponding statistical-test parameter. These fluctuations coincide adequately with entropy fluctuations, namely the oscillations out of thermodynamic equilibrium. Using Fisher’s test, we investigate the conformational entropy over time and suggest its oscillatory properties in the corresponding time domain. Using the Kruscal–Wallis test, we also analyze differences between the mean root mean square displacement of a molecule at various temperatures. Here we show that its values in the range of 306 K – 309 K are different than in another temperature. Using the Kullback–Leibler theory, we investigate differences between the distribution of the mean root mean square displacement for each temperature and time window.

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