scholarly journals In Silico Strategy for Targeting the mTOR Kinase at Rapamycin Binding Site by Small Molecules

Molecules ◽  
2021 ◽  
Vol 26 (4) ◽  
pp. 1103
Author(s):  
Serena Vittorio ◽  
Rosaria Gitto ◽  
Ilenia Adornato ◽  
Emilio Russo ◽  
Laura De Luca
Keyword(s):  
Binding Site ◽  
Ternary Complex ◽  
Md Simulation ◽  
Binding Free Energy ◽  
Mtor Inhibitors ◽  
Data Bank ◽  
Binding Mode ◽  
Docking Studies ◽  
Pharmacophore Modelling ◽  
Mtor Kinase

Computer aided drug-design methods proved to be powerful tools for the identification of new therapeutic agents. We employed a structure-based workflow to identify new inhibitors targeting mTOR kinase at rapamycin binding site. By combining molecular dynamics (MD) simulation and pharmacophore modelling, a simplified structure-based pharmacophore hypothesis was built starting from the FKBP12-rapamycin-FRB ternary complex retrieved from RCSB Protein Data Bank (PDB code 1FAP). Then, the obtained model was used as filter to screen the ZINC biogenic compounds library, containing molecules derived from natural sources or natural-inspired compounds. The resulting hits were clustered according to their similarity; moreover, compounds showing the highest pharmacophore fit-score were chosen from each cluster. The selected molecules were subjected to docking studies to clarify their putative binding mode. The binding free energy of the obtained complexes was calculated by MM/GBSA method and the hits characterized by the lowest ΔGbind values were identified as potential mTOR inhibitors. Furthermore, the stability of the resulting complexes was studied by means of MD simulation which revealed that the selected compounds were able to form a stable ternary complex with FKBP12 and FRB domain, thus underlining their potential ability to inhibit mTOR with a rapamycin-like mechanism.

Docking, Binding Free Energy Estimation, and MD Simulation of Newly Designed CQ and HCQ Analogues Against the Spike-ACE2 Complex of SARS-CoV-2

2021 ◽  
Vol 6 (4) ◽  
pp. 77-89
Author(s):  
Anjoomaara H. Patel ◽  
Riya B. Patel ◽  
MahammadHussain J. Memon ◽  
Samiya S. Patel ◽  
Sharav A. Desai ◽  
...  
Keyword(s):  
Free Energy ◽  
Md Simulation ◽  
Binding Free Energy ◽  
Docking Studies ◽  
Radius Of Gyration ◽  
Ligand Interaction ◽  
Energy Estimation ◽  
Efficacious Treatment ◽  
Protein Ligand Interaction ◽  
Derivatives Of

The coronavirus disease 2019 (COVID-19) virus has been spreading rapidly, and scientists are endeavouring to discover drugs for its efficacious treatment. Chloroquine phosphate, an old drug for treatment of malaria, has shown to have apparent efficacy and acceptable safety against COVID-19. As a part of Drug Discovery Hackathon-2020, in this study, the authors have tried making the derivatives of CQ and HCQ using MarvinSketch by ChemAxon. Molecular docking studies of these ligands were performed using Glide by Schrodinger, and ADME profiles were obtained by using QikProp. The obtained results after data analysis demonstrated that ligands HCQ_imidazoll, choloroquine_3c, HCQ_pyrrolC had good binding affinity and complied with all the ADME parameters. The molecular dynamic simulation of these ligands in complex with the 2019-nCoV RBD/ACE-2-B0AT1 complex PDB ID: 6M17 were carried out, and the parameters like RMSD, RMSF, and radius of gyration were observed to understand the fluctuations and protein-ligand interaction.

Recent Advancements in Docking Methodologies

Oncology ◽  
2017 ◽  
pp. 848-875
Author(s):  
Vijay Kumar Srivastav ◽  
Vineet Singh ◽  
Meena Tiwari
Keyword(s):  
Molecular Docking ◽  
Binding Free Energy ◽  
Binding Mode ◽  
Docking Studies ◽  
Protein Docking ◽  
Scoring Functions ◽  
Discovery Process ◽  
Ligand Complex ◽  
Small Molecule Databases ◽  
Homology Models

Nowadays molecular docking has become an important methodology in CADD (Computer-Aided Drug Design)-assisted drug discovery process. It is an important computational tool widely used to predict binding mode, binding affinity and binding free energy of a protein-ligand complex. The important factors responsible for accurate results in docking studies are correct binding site prediction, use of suitable small-molecule databases, consistent docking pose, high dock score with good MD (Molecular Dynamics), clarity whether the compound is an inhibitor or agonist, etc. However, still there are several limitations which make it difficult to obtain accurate results from docking studies. In this chapter, the main focus is on recent advancements in various aspects of molecular docking such as ligand sampling, protein flexibility, scoring functions, fragment docking, post-processing, docking into homology models and protein-protein docking.

scholarly journals Potential Mortalin-p53 complex abrogation of ent-kaurane diterpenoids from Croton tonkinensis revealed by homology modeling and docking simulation

2021 ◽  
Vol 58 (6A) ◽  
pp. 261
Author(s):  
Quan Minh PHAM ◽  
Hai Viet HA ◽  
Nghi Huu DO ◽  
Hung Viet DAO ◽  
Thu Le Thi VU
Keyword(s):  
Crystal Structure ◽  
Free Energy ◽  
Molecular Docking ◽  
Structure Prediction ◽  
Binding Free Energy ◽  
Docking Simulation ◽  
Data Bank ◽  
Docking Studies ◽  
Hepg2 Cell Line ◽  
Prediction Server

Seven ent-kaurane diterpenoids from Croton tonkinensis were tested for cytotoxicity against human HCC HepG2 cell line. The abrogation of mortalin-p53 interaction represent an original anticancer therapeutic approach. Teritary structure of protein mortalin was constructed using Protein Structure Prediction Server and crystal structure of p53 was selected from Protein Data Bank involving mortalin-p53 binding domain. Molecular docking studies revealed that the interaction with protein mortalin is more prominent than p53   compound 5 and 1 as the most two potential mortalin-p53 binding inhibitors based on binding free energy and interacting residues analysis.

Molecular Docking and Dynamic Simulation of UDP-N-Acetylenolpyruvoylglucosamine Reductase (MurB) Obtained from Mycobacterium Tuberculosis Using in Silico Approach

2020 ◽  
Author(s):  
Mustafa Alhaji Isa ◽  
Mohammed Mustapha Mohammed
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Molecular Docking ◽  
Binding Site ◽  
Md Simulation ◽  
Simulation Analysis ◽  
Data Bank ◽  
Binding Energies ◽  
Peptidoglycan Biosynthesis

<p>The UDP-N-acetylenolpyruvoylglucosamine reductase (MurB) catalyze the final steps of the UDP-N-acetylmuramic acid (UDPMurNAc) formation in the peptidoglycan biosynthesis pathway. The absence of this pathway in mammal made it an attractive target for drug development in <i>Mycobacterium tuberculosis</i> (MTB). In this study, the crystal structure of MurB from MTB (PDB Code: 5JZX and resolution of 2.2 Å) bound to FAD and K<sup>+</sup> was obtained from Protein Data Bank (PDB). A total of 2157 compounds with best binding conformations obtained from zinc database through virtual screening. These compounds further screened for drug-likeness, pharmacokinetic properties, physicochemical properties (Lipinski rule of five), and molecular docking analysis to obtained compounds with desirable therapeutic properties and good binding energies against MurB. Seven compounds (7) with minimum binding energies ranged between ─11.80 and ─10.39kcal/mol were selected, lower than the binding energy of FAD (─10.06kcal/mol). Four compounds with best binding energies (ZINC19837204 = ─11.80kcal/mol, ZINC11839554 = ─11.47kcal/mol, ZINC14976552 = ─10.77kcal/mol) and ability to interact with the residues (ZINC12242812 = ─10.39kcal/mol) of the substrate binding site further selected for the molecular dynamic (MD) simulation analysis. The result of the MD simulation showed that all the four ligands formed stable complexes in the binding site of the MurB, during the 50ns MD simulation, when compared with the cofactor (FAD). Therefore, these compounds were proposed to be novel inhibitors of MTB after <i>in vivo</i> and <i>in vitro</i> validation.</p>

scholarly journals Designs, Synthesis, Docking Studies, and Biological Evaluation of Novel Berberine Derivatives Targeting Zika Virus

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Cuong Quoc Nguyen ◽  
Thi Hong Minh Nguyen ◽  
Thi Thu Thuy Nguyen ◽  
Thi Buu Hue Bui ◽  
Trong Tuan Nguyen ◽  
...  
Keyword(s):  
Zika Virus ◽  
Binding Free Energy ◽  
Antiviral Drug ◽  
Binding Mode ◽  
Docking Studies ◽  
Biological Evaluation ◽  
World Health ◽  
Mode Analysis ◽  
Energy Calculation ◽  
Ns3 Protease

The World Health Organization has designated Zika virus (ZIKV) as a dangerous, mosquito-borne flaviviral pathogen that was recently found to be responsible for a dramatically increased number of microcephaly cases and other congenital abnormalities in fetuses and newborns. There is neither a vaccine to prevent nor a drug to treat ZIKA virus infections, at the present time. Berberine (BBR) is a promising drug approved by FDA against flaviviral dengue virus, and BBR derivatives are of great interest in antiviral drug development. In this study, we synthesized eight BBR derivatives by introducing benzyl groups at the C-13 position of BBR and converting to respective 8-oxoberberine derivatives, performed molecular docking analysis, and evaluated their anti-Zika virus activity utilizing a cell‐based phenotypic assay. Binding mode analysis, absolute binding free energy calculation, and structure-activity relationship studies of these compounds with ZIKV NS3 receptor were collected. Amongst these studied compounds, compound 4d with a structure of 13-(2,6-difluoro)-benzylberberine showed high binding affinity (docking score of −7.31 kcal/mol) towards ZIKV NS2B-NS3 protease with critical binding formed within the active site. In the cell-based assay, compound 4d displayed the highest antiviral efficacy against ZIKV with a selective index (SI) of 15.3, with 3.7-fold greater than that of berberine. Together, our study suggests that the potential ZIKV NS2B-NS3 protease inhibitor, compound 4d, is the best alternative to BBR and, further, extends an assuring platform for developing antiviral competitive inhibitors against ZIKV infection.

scholarly journals Rigorous sampling of docking poses unveils binding hypothesis for the halogenated ligands of L-type Amino acid Transporter 1 (LAT1)

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Natesh Singh ◽  
Bruno O. Villoutreix ◽  
Gerhard F. Ecker
Keyword(s):  
Amino Acid ◽  
Electrostatic Interactions ◽  
Hydrophobic Interactions ◽  
Binding Free Energy ◽  
Homology Model ◽  
Binding Mode ◽  
Amino Acid Transporter ◽  
Docking Studies ◽  
Dual Nature ◽  
Acid Transporter

Abstract L-type Amino acid Transporter 1 (LAT1) plays a significant role in the growth and propagation of cancer cells by facilitating the cross-membrane transport of essential nutrients, and is an attractive drug target. Several halogen-containing L-phenylalanine-based ligands display high affinity and high selectivity for LAT1; nonetheless, their molecular mechanism of binding remains unclear. In this study, a combined in silico strategy consisting of homology modeling, molecular docking, and Quantum Mechanics-Molecular Mechanics (QM-MM) simulation was applied to elucidate the molecular basis of ligand binding in LAT1. First, a homology model of LAT1 based on the atomic structure of a prokaryotic homolog was constructed. Docking studies using a set of halogenated ligands allowed for deriving a binding hypothesis. Selected docking poses were subjected to QM-MM calculations to investigate the halogen interactions. Collectively, the results highlight the dual nature of the ligand-protein binding mode characterized by backbone hydrogen bond interactions of the amino acid moiety of the ligands and residues I63, S66, G67, F252, G255, as well as hydrophobic interactions of the ligand’s side chains with residues I139, I140, F252, G255, F402, W405. QM-MM optimizations indicated that the electrostatic interactions involving halogens contribute to the binding free energy. Importantly, our results are in good agreement with the recently unraveled cryo-Electron Microscopy structures of LAT1.

Recent Advancements in Docking Methodologies

2016 ◽  
pp. 267-294
Author(s):  
Vijay Kumar Srivastav ◽  
Vineet Singh ◽  
Meena Tiwari
Keyword(s):  
Molecular Docking ◽  
Binding Free Energy ◽  
Binding Mode ◽  
Docking Studies ◽  
Protein Docking ◽  
Scoring Functions ◽  
Discovery Process ◽  
Ligand Complex ◽  
Small Molecule Databases ◽  
Homology Models

Nowadays molecular docking has become an important methodology in CADD (Computer-Aided Drug Design)-assisted drug discovery process. It is an important computational tool widely used to predict binding mode, binding affinity and binding free energy of a protein-ligand complex. The important factors responsible for accurate results in docking studies are correct binding site prediction, use of suitable small-molecule databases, consistent docking pose, high dock score with good MD (Molecular Dynamics), clarity whether the compound is an inhibitor or agonist, etc. However, still there are several limitations which make it difficult to obtain accurate results from docking studies. In this chapter, the main focus is on recent advancements in various aspects of molecular docking such as ligand sampling, protein flexibility, scoring functions, fragment docking, post-processing, docking into homology models and protein-protein docking.

scholarly journals Molecular Docking and Dynamic Simulation of UDP-N-Acetylenolpyruvoylglucosamine Reductase (MurB) Obtained from Mycobacterium Tuberculosis Using in Silico Approach

2020 ◽  
Author(s):  
Mustafa Alhaji Isa ◽  
Mohammed Mustapha Mohammed
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Molecular Docking ◽  
Binding Site ◽  
Md Simulation ◽  
Simulation Analysis ◽  
Data Bank ◽  
Binding Energies ◽  
Peptidoglycan Biosynthesis

<p>The UDP-N-acetylenolpyruvoylglucosamine reductase (MurB) catalyze the final steps of the UDP-N-acetylmuramic acid (UDPMurNAc) formation in the peptidoglycan biosynthesis pathway. The absence of this pathway in mammal made it an attractive target for drug development in <i>Mycobacterium tuberculosis</i> (MTB). In this study, the crystal structure of MurB from MTB (PDB Code: 5JZX and resolution of 2.2 Å) bound to FAD and K<sup>+</sup> was obtained from Protein Data Bank (PDB). A total of 2157 compounds with best binding conformations obtained from zinc database through virtual screening. These compounds further screened for drug-likeness, pharmacokinetic properties, physicochemical properties (Lipinski rule of five), and molecular docking analysis to obtained compounds with desirable therapeutic properties and good binding energies against MurB. Seven compounds (7) with minimum binding energies ranged between ─11.80 and ─10.39kcal/mol were selected, lower than the binding energy of FAD (─10.06kcal/mol). Four compounds with best binding energies (ZINC19837204 = ─11.80kcal/mol, ZINC11839554 = ─11.47kcal/mol, ZINC14976552 = ─10.77kcal/mol) and ability to interact with the residues (ZINC12242812 = ─10.39kcal/mol) of the substrate binding site further selected for the molecular dynamic (MD) simulation analysis. The result of the MD simulation showed that all the four ligands formed stable complexes in the binding site of the MurB, during the 50ns MD simulation, when compared with the cofactor (FAD). Therefore, these compounds were proposed to be novel inhibitors of MTB after <i>in vivo</i> and <i>in vitro</i> validation.</p>

scholarly journals Enhancing Sampling of Water Rearrangements on Ligand Binding: A Comparison of Techniques

2021 ◽  
Author(s):  
Yunhui Ge ◽  
David C. Wych ◽  
Marley L. Samways ◽  
Michael E. Wall ◽  
Jonathan W. Essex ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Binding Site ◽  
Md Simulation ◽  
Direct Analysis ◽  
Md Simulations ◽  
Binding Mode ◽  
Bulk Water ◽  
Free Energy Calculations ◽  
Water Sampling ◽  
Ligand Interactions

Water often plays a key role in protein structure, molecular recognition, and mediating protein-ligand interactions. Thus, free energy calculations must adequately sample water motions, which often proves challenging in typical MD simulation timescales. Thus, the accuracy of methods relying on MD simulations ends up limited by slow water sampling. Particularly, as a ligand is removed or modified, bulk water may not have time to fill or rearrange in the binding site. In this work, we focus on several molecular dynamics (MD) simulation-based methods attempting to help address water motions and occupancies: BLUES, using nonequilibrium candidate Monte Carlo (NCMC); grand, using grand canonical Monte Carlo (GCMC); and normal MD. We assess the accuracy and efficiency of these methods in sampling water motions. We selected a range of systems with varying numbers of waters in the binding site, as well as those where water occupancy is coupled to the identity or binding mode of the ligand. We analyzed water motions and occupancies using both clustering of trajectories and direct analysis of electron density maps. Our results suggest both BLUES and grand enhance water sampling relative to normal MD and grand is more robust than BLUES, but also that water sampling remains a major challenge for all of the methods tested. The lessons we learned for these methods and systems are discussed.

Application of the ESMACS Binding Free Energy Protocol to a Highly Varied Ligand Dataset: Lactate Dehydogenase A

2019 ◽  
Author(s):  
David Wright ◽  
Fouad Husseini ◽  
Shunzhou Wan ◽  
Christophe Meyer ◽  
Herman Van Vlijmen ◽  
...  
Keyword(s):  
Free Energy ◽  
Surface Area ◽  
Binding Free Energy ◽  
Normal Mode Analysis ◽  
Binding Mode ◽  
Accessible Surface Area ◽  
Solvent Accessible Surface Area ◽  
Mode Analysis ◽  
Energy Calculation ◽  
Accessible Surface

<div>Here, we evaluate the performance of our range of ensemble simulation based binding free energy calculation protocols, called ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) for use in fragment based drug design scenarios. ESMACS is designed to generate reproducible binding affinity predictions from the widely used molecular mechanics Poisson-Boltzmann surface area (MMPBSA) approach. We study ligands designed to target two binding pockets in the lactate dehydogenase A target protein, which vary in size, charge and binding mode. When comparing to experimental results, we obtain excellent statistical rankings across this highly diverse set of ligands. In addition, we investigate three approaches to account for entropic contributions not captured by standard MMPBSA calculations: (1) normal mode analysis, (2) weighted solvent accessible surface area (WSAS) and (3) variational entropy. </div>

Sign in / Sign up

Export Citation Format

Share Document