Maximum Common Binding Modes (MCBM):  Consensus Docking Scoring Using Multiple Ligand Information and Interaction Fingerprints

2008 ◽  
Vol 48 (2) ◽  
pp. 319-332 ◽  
Author(s):  
Steffen Renner ◽  
Swetlana Derksen ◽  
Sebastian Radestock ◽  
Fabian Mörchen
Keyword(s):  
Binding Modes ◽  
Multiple Ligand ◽  
Interaction Fingerprints

Predicting Ligand Binding Modes from Neural Networks Trained on Protein–Ligand Interaction Fingerprints

2013 ◽  
Vol 53 (4) ◽  
pp. 763-772 ◽  
Author(s):  
Vladimir Chupakhin ◽  
Gilles Marcou ◽  
Igor Baskin ◽  
Alexandre Varnek ◽  
Didier Rognan
Keyword(s):  
Neural Networks ◽  
Ligand Binding ◽  
Binding Modes ◽  
Ligand Interaction ◽  
Protein Ligand Interaction ◽  
Interaction Fingerprints

AutoMap: A tool for analyzing protein–ligand recognition using multiple ligand binding modes

2013 ◽  
Vol 40 ◽  
pp. 80-90 ◽  
Author(s):  
Mark Agostino ◽  
Ricardo L. Mancera ◽  
Paul A. Ramsland ◽  
Elizabeth Yuriev
Keyword(s):  
Ligand Binding ◽  
Ligand Recognition ◽  
Binding Modes ◽  
Multiple Ligand

Multiple ligand-binding modes in bacterial R67 dihydrofolate reductase

2005 ◽  
Vol 19 (3) ◽  
pp. 165-187 ◽  
Author(s):  
Hernán Alonso ◽  
Malcolm B. Gillies ◽  
Peter L. Cummins ◽  
Andrey A. Bliznyuk ◽  
Jill E. Gready
Keyword(s):  
Ligand Binding ◽  
Dihydrofolate Reductase ◽  
Binding Modes ◽  
R67 Dihydrofolate Reductase ◽  
Multiple Ligand

On the Adsorption of Aspartate Derivatives to Calcite Surfaces in Aqueous Environment

2020 ◽  
Author(s):  
Robert Stepic ◽  
Lara Jurković ◽  
Ksenia Klementyeva ◽  
Marko Ukrainczyk ◽  
Matija Gredičak ◽  
...  
Keyword(s):  
Active Sites ◽  
Realistic Model ◽  
Binding Energies ◽  
Inhibition Mechanism ◽  
Aqueous Environment ◽  
Binding Modes ◽  
Carboxylate Groups ◽  
Dissolved Ions ◽  
Living Organisms ◽  
Dynamics Simulations

In many living organisms, biomolecules interact favorably with various surfaces of calcium carbonate. In this work, we have considered the interactions of aspartate (Asp) derivatives, as models of complex biomolecules, with calcite. Using kinetic growth experiments, we have investigated the inhibition of calcite growth by Asp, Asp2 and Asp3.This entailed the determination of a step-pinning growth regime as well as the evaluation of the adsorption constants and binding free energies for the three species to calcite crystals. These latter values are compared to free energy profiles obtained from fully atomistic molecular dynamics simulations. When using a flat (104) calcite surface in the models, the measured trend of binding energies is poorly reproduced. However, a more realistic model comprised of a surface with an island containing edges and corners, yields binding energies that compare very well with experiments. Surprisingly, we find that most binding modes involve the positively charged, ammonium group. Moreover, while attachment of the negatively charged carboxylate groups is also frequently observed, it is always balanced by the aqueous solvation of an equal or greater number of carboxylates. These effects are observed on all calcite features including edges and corners, the latter being associated with dominant affinities to Asp derivatives. As these features are also precisely the active sites for crystal growth, the experimental and theoretical results point strongly to a growth inhibition mechanism whereby these sites become blocked, preventing further attachment of dissolved ions and halting further growth.

Reversibly Sampling Conformations and Binding Modes Using Molecular Darting

2020 ◽  
Author(s):  
Samuel C. Gill ◽  
David Mobley
Keyword(s):  
Monte Carlo ◽  
Ligand Binding ◽  
Binding Sites ◽  
Degrees Of Freedom ◽  
Dynamics Simulation ◽  
Hiv Integrase ◽  
Binding Modes ◽  
System A ◽  
Multiple Binding ◽  
Internal Degrees Of Freedom

<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>

Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes Using Nonequilibrium Candidate Monte Carlo

2017 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Ligand Binding ◽  
Binding Mode ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Binding Modes ◽  
Enhanced Sampling ◽  
Recent Success ◽  
Multiple Binding ◽  
Proper Sampling

<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>

Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes Using Nonequilibrium Candidate Monte Carlo

2018 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Ligand Binding ◽  
Binding Mode ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Binding Modes ◽  
Enhanced Sampling ◽  
Recent Success ◽  
Multiple Binding ◽  
Proper Sampling

<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>

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