Multiple binding modes of an N‐terminal CCR5‐peptide in complex with HIV‐1 gp120

FEBS Journal ◽  
2021 ◽  
Author(s):  
Adi Moseri ◽  
Sabine R. Akabayov ◽  
Leah S. Cohen ◽  
Fred Naider ◽  
Jacob Anglister
Keyword(s):  
2011 ◽  
Vol 410 (4) ◽  
pp. 745-755 ◽  
Author(s):  
Andreas Blum ◽  
Jark Böttcher ◽  
Stefanie Dörr ◽  
Andreas Heine ◽  
Gerhard Klebe ◽  
...  

2010 ◽  
Vol 98 (3) ◽  
pp. 752a
Author(s):  
Thayaparan Paramanathan ◽  
Ioana D. Vladescu ◽  
Micah J. McCauley ◽  
Ioulia Rouzina ◽  
Mark C. Williams

2020 ◽  
Author(s):  
Samuel C. Gill ◽  
David Mobley

<div>Sampling multiple binding modes of a ligand in a single molecular dynamics simulation is difficult. A given ligand may have many internal degrees of freedom, along with many different ways it might orient itself a binding site or across several binding sites, all of which might be separated by large energy barriers. We have developed a novel Monte Carlo move called Molecular Darting (MolDarting) to reversibly sample between predefined binding modes of a ligand. Here, we couple this with nonequilibrium candidate Monte Carlo (NCMC) to improve acceptance of moves.</div><div>We apply this technique to a simple dipeptide system, a ligand binding to T4 Lysozyme L99A, and ligand binding to HIV integrase in order to test this new method. We observe significant increases in acceptance compared to uniformly sampling the internal, and rotational/translational degrees of freedom in these systems.</div>


2017 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  

<div>Accurately predicting protein-ligand binding is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes.</div><div><br></div><div>In this technique the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step towards applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.</div>


2018 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  

<div>Accurately predicting protein-ligand binding is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes.</div><div><br></div><div>In this technique the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step towards applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.</div>


Author(s):  
Arash Soltani ◽  
Seyed Isaac Hashemy ◽  
Farnaz Zahedi Avval ◽  
Houshang Rafatpanah ◽  
Seyed Abdolrahim Rezaee ◽  
...  

Introoduction: Inhibition of the reverse transcriptase (RT) enzyme of human immunodeficiency virus (HIV) by low molecular weight inhibitors is still an active area of research. Here, protein-ligand interactions and possible binding modes of novel compounds with the HIV-1 RT binding pocket (the wild-type as well as Y181C and K103N mutants) were obtained and discussed. Methods: A molecular fragment-based approach using FDA-approved drugs were followed to design novel chemical derivatives using delavirdine, efavirenz, etravirine and rilpivirine as the scaffolds. The drug-likeliness of the derivatives was evaluated using Swiss-ADME. Then the parent molecule and derivatives were docked into the binding pocket of related crystal structures (PDB ID: 4G1Q, 1IKW, 1KLM and 3MEC). Genetic Optimization for Ligand Docking (GOLD) Suite 5.2.2 software was used for docking and the results analyzed in the Discovery Studio Visualizer 4. A derivative was chosen for further analysis, if it passed drug-likeliness and the docked energy was more favorable than that of its parent molecule. Out of the fifty-seven derivatives, forty-eight failed in druglikeness screening by Swiss-ADME or in docking stage. Results: The final results showed that the selected compounds had higher predicted binding affinities than their parent scaffolds in both wild-type and the mutants. Binding energy improvement was higher for the structures designed based on second-generation NNRTIs (etravirine and rilpivirine) than the first-generation NNRTIs (delavirdine and efavirenz). For example, while the docked energy for rilpivirine was -51 KJ/mol, it was improved for its derivatives RPV01 and RPV15 up to -58.3 and -54.5 KJ/mol, respectively. Conclusion: In this study, we have identified and proposed some novel molecules with improved binding capacity for HIV RT using fragment-based approach.


1993 ◽  
Vol 36 (13) ◽  
pp. 1902-1913 ◽  
Author(s):  
Krystina Plucinska ◽  
Takahiro Kataoka ◽  
Mitsuaki Yodo ◽  
Wayne L. Cody ◽  
J. X. He ◽  
...  

2012 ◽  
Vol 22 (1) ◽  
pp. 56-64 ◽  
Author(s):  
Lorna J. Smith ◽  
Wilfred F. Van Gunsteren ◽  
Jane R. Allison

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