scholarly journals Ligand binding to telomeric G-quadruplex DNA investigated by funnel-metadynamics simulations

2017 ◽  
Vol 114 (11) ◽  
pp. E2136-E2145 ◽  
Author(s):  
Federica Moraca ◽  
Jussara Amato ◽  
Francesco Ortuso ◽  
Anna Artese ◽  
Bruno Pagano ◽  
...  
Keyword(s):  
Free Energy ◽  
Ligand Binding ◽  
Rational Design ◽  
Binding Free Energy ◽  
Binding Mode ◽  
Dna Interaction ◽  
Accurate Estimate ◽  
Binding Modes ◽  
Binding Mechanism ◽  
Promoter Regions

G-quadruplexes (G4s) are higher-order DNA structures typically present at promoter regions of genes and telomeres. Here, the G4 formation decreases the replicative DNA at each cell cycle, finally leading to apoptosis. The ability to control this mitotic clock, particularly in cancer cells, is fascinating and passes through a rational understanding of the ligand/G4 interaction. We demonstrate that an accurate description of the ligand/G4 binding mechanism is possible using an innovative free-energy method called funnel-metadynamics (FM), which we have recently developed to investigate ligand/protein interaction. Using FM simulations, we have elucidated the binding mechanism of the anticancer alkaloid berberine to the human telomeric G4 (d[AG3(T2AG3)3]), computing also the binding free-energy landscape. Two ligand binding modes have been identified as the lowest energy states. Furthermore, we have found prebinding sites, which are preparatory to reach the final binding mode. In our simulations, the ions and the water molecules have been explicitly represented and the energetic contribution of the solvent during ligand binding evaluated. Our theoretical results provide an accurate estimate of the absolute ligand/DNA binding free energy (ΔGb0 = −10.3 ± 0.5 kcal/mol) that we validated through steady-state fluorescence binding assays. The good agreement between the theoretical and experimental value demonstrates that FM is a most powerful method to investigate ligand/DNA interaction and can be a useful tool for the rational design also of G4 ligands.

scholarly journals Ligand deconstruction: Why some fragment binding positions are conserved and others are not

2015 ◽  
Vol 112 (20) ◽  
pp. E2585-E2594 ◽  
Author(s):  
Dima Kozakov ◽  
David R. Hall ◽  
Stefan Jehle ◽  
Lingqi Luo ◽  
Stefan O. Ochiana ◽  
...  
Keyword(s):  
Free Energy ◽  
Ligand Binding ◽  
Binding Free Energy ◽  
Hot Spot ◽  
Binding Mode ◽  
Binding Potential ◽  
Binding Modes ◽  
Affinity Ligand ◽  
Ligand Binding Sites ◽  
Free Energy Of Binding

Fragment-based drug discovery (FBDD) relies on the premise that the fragment binding mode will be conserved on subsequent expansion to a larger ligand. However, no general condition has been established to explain when fragment binding modes will be conserved. We show that a remarkably simple condition can be developed in terms of how fragments coincide with binding energy hot spots—regions of the protein where interactions with a ligand contribute substantial binding free energy—the locations of which can easily be determined computationally. Because a substantial fraction of the free energy of ligand binding comes from interacting with the residues in the energetically most important hot spot, a ligand moiety that sufficiently overlaps with this region will retain its location even when other parts of the ligand are removed. This hypothesis is supported by eight case studies. The condition helps identify whether a protein is suitable for FBDD, predicts the size of fragments required for screening, and determines whether a fragment hit can be extended into a higher affinity ligand. Our results show that ligand binding sites can usefully be thought of in terms of an anchor site, which is the top-ranked hot spot and dominates the free energy of binding, surrounded by a number of weaker satellite sites that confer improved affinity and selectivity for a particular ligand and that it is the intrinsic binding potential of the protein surface that determines whether it can serve as a robust binding site for a suitably optimized ligand.

scholarly journals Influence of Mg2+ ions on the interaction between 3,5-dicaffeoylquinic acid and HTLV-I integrase

2012 ◽  
Vol 17 (1) ◽  
pp. 5 ◽  
Author(s):  
Ángela Peña ◽  
Juvenal Yosa ◽  
Yesid Cuesta-Astroz ◽  
Orlando Acevedo ◽  
Leonardo Lareo ◽  
...  
Keyword(s):  
Free Energy ◽  
Rational Design ◽  
Catalytic Domain ◽  
Binding Free Energy ◽  
Homology Model ◽  
Binding Mode ◽  
Antiretroviral Drugs ◽  
Type I ◽  
Interaction Sites ◽  
Dicaffeoylquinic Acid

<strong>Objective</strong>. Using molecular simulation, we studied the influence of Mg2+ ions on the binding mode of HTLV-I Integrase (IN) catalytic domain (modeled by homology) with the 3,5- Dicaffeoylquinic Acid (DCQA). HTLV-I Integrase homology model was built using template-like crystallographic data of the IN catalytic domain solved for Avian Sarcoma Virus (VSA, pdb: 1VSD). <strong>Materials and</strong> <strong>methods</strong>. In order to analyze the role of Mg2+ in the interaction or coupling between 3,5-DCQA and Integrase, three models were created: i) in the absence of Mg2+ ions, ii) with a Mg2+ ion coordinated at Asp15 and Asp72 and iii) model with two Mg2+ ions coordinated at Asp15-Asp72 and Asp72-Glu108. Coupling force and binding free energy between 3,5-DCQA and HTLV-I IN were assessed in the three models. <strong>Results</strong>. The lowest docking score and free energy binding were obtained for the second model. Mg2+ ion strongly affected the coupling of the inhibitor 3,5-DCQA with HTLV-I catalytic domain of Integrase, thus revealing a strong interaction in the ligand-protein complex regardless of the ligand-catalytic interaction sites for all three models. <strong>Conclusion</strong>. Altogether, these results strengthen the hypothesis that the presence of one Mg2+ ion could enhance the interaction in the complex by decreasing free energy, therefore increasing the affinity. Moreover, we propose 3, 5-DCQA as an important pharmacophore in the rational design of new antiretroviral drugs.<br /><br /><strong>Key words</strong>: 3,5 -Dicaffeoylquinic Acid, Human T-Lymphotropic Type I (HTLV-1), Integrase (IN), Homology Model, Molecular Docking, Binding Free Energy, Mg2+ Ions.

scholarly journals Accelerating the Calculation of Protein-Ligand Binding Free Energy and Residence Times using Dynamically Optimized Collective Variables

2018 ◽  
Author(s):  
Z. Faidon Brotzakis ◽  
Vittorio Limongelli ◽  
Michele Parrinello
Keyword(s):  
Free Energy ◽  
Ligand Binding ◽  
Degrees Of Freedom ◽  
Binding Free Energy ◽  
Conformational Dynamics ◽  
Computational Cost ◽  
Binding Pocket ◽  
Binding Mode ◽  
Collective Variables ◽  
Binding Interaction

AbstractElucidation of the ligand/protein binding interaction is of paramount relevance in pharmacology to increase the success rate of drug design. To this end a number of computational methods have been proposed, however all of them suffer from limitations since the ligand binding/unbinding transitions to the molecular target involve many slow degrees of freedom that hamper a full characterization of the binding process. Being able to express this transition in simple and general slow degrees of freedom, would give a distinctive advantage, since it would require minimal knowledge of the system under study, while in turn it would elucidate its physics and accelerate the convergence speed of enhanced sampling methods relying on collective variables. In this study we pursuit this goal by combining for the first time Variation Approach to Conformational dynamics with Funnel-Metadynamics. In so doing, we predict for the benzamidine/trypsin system the ligand binding mode, and we accurately compute the absolute protein-ligand binding free energy and unbinding rate at unprecedented low computational cost. Finally, our simulation protocol reveals the energetics and structural details of the ligand binding mechanism and shows that water and binding pocket solvation/desolvation are the dominant slow degrees of freedom.

Automated, Accurate, and Scalable Relative Protein-Ligand Binding Free Energy Calculations using Lambda Dynamics

2020 ◽  
Author(s):  
E. Prabhu Raman ◽  
Thomas J. Paul ◽  
Ryan L. Hayes ◽  
Charles L. Brooks III
Keyword(s):  
Free Energy ◽  
Ligand Binding ◽  
Binding Affinity ◽  
Binding Free Energy ◽  
Computational Cost ◽  
Combinatorial Libraries ◽  
Free Energy Calculations ◽  
Lead Optimization ◽  
Efficient Estimation ◽  
Lead Compound

<p>Accurate predictions of changes to protein-ligand binding affinity in response to chemical modifications are of utility in small molecule lead optimization. Relative free energy perturbation (FEP) approaches are one of the most widely utilized for this goal, but involve significant computational cost, thus limiting their application to small sets of compounds. Lambda dynamics, also rigorously based on the principles of statistical mechanics, provides a more efficient alternative. In this paper, we describe the development of a workflow to setup, execute, and analyze Multi-Site Lambda Dynamics (MSLD) calculations run on GPUs with CHARMm implemented in BIOVIA Discovery Studio and Pipeline Pilot. The workflow establishes a framework for setting up simulation systems for exploratory screening of modifications to a lead compound, enabling the calculation of relative binding affinities of combinatorial libraries. To validate the workflow, a diverse dataset of congeneric ligands for seven proteins with experimental binding affinity data is examined. A protocol to automatically tailor fit biasing potentials iteratively to flatten the free energy landscape of any MSLD system is developed that enhances sampling and allows for efficient estimation of free energy differences. The protocol is first validated on a large number of ligand subsets that model diverse substituents, which shows accurate and reliable performance. The scalability of the workflow is also tested to screen more than a hundred ligands modeled in a single system, which also resulted in accurate predictions. With a cumulative sampling time of 150ns or less, the method results in average unsigned errors of under 1 kcal/mol in most cases for both small and large combinatorial libraries. For the multi-site systems examined, the method is estimated to be more than an order of magnitude more efficient than contemporary FEP applications. The results thus demonstrate the utility of the presented MSLD workflow to efficiently screen combinatorial libraries and explore chemical space around a lead compound, and thus are of utility in lead optimization.</p>

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>

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>

scholarly journals Molecular modeling study on the drug resistance mechanism of NS5B polymerase to TMC647055

2016 ◽  
Vol 94 (2) ◽  
pp. 147-158 ◽  
Author(s):  
Huiqun Wang ◽  
Wei Cui ◽  
Chenchen Guo ◽  
Bo-Zhen Chen ◽  
Mingjuan Ji
Keyword(s):  
Drug Resistance ◽  
Free Energy ◽  
Rational Design ◽  
Binding Free Energy ◽  
Resistance Mechanism ◽  
Free Energy Calculations ◽  
Side Chain ◽  
Free Energy Decomposition ◽  
Hcv Ns5b ◽  
Ns5b Polymerase

NS5B polymerase plays an important role in viral replication machinery. TMC647055 (TMC) is a novel and potent non-nucleoside inhibitor of the HCV NS5B polymerase. However, mutations that result in drug resistance to TMC have been reported. In this study, we used molecular dynamics (MD) simulations, binding free energy calculations, and free energy decomposition to investigate the drug resistance mechanism of HCV to TMC resulting from L392I, P495T, P495S, and P495L mutations in NS5B polymerase. From the calculated results we determined that the decrease in the binding affinity between TMC and NS5BL392I polymerase is mainly caused by the extra methyl group at the CB atom of Ile. The polarity of the side-chain of residue 495 has no distinct influence on residue 495 binding with TMC, whereas the smaller size of the side-chain of residue 495 causes a substantial decrease in the van der Walls interaction between TMC and residue 495. Moreover, the longer length of the side-chain of residue 495 has a significant effect on the electrostatic interaction between TMC and Arg-503. Finally, we performed the same calculations and detailed analysis on other 3 mutations (L392V, P495V, and P495I). The results further confirmed our conclusions. The computational results not only reveal the drug resistance mechanism between TMC647055 and NS5B polymerase, but also provide valuable information for the rational design of more potent non-nucleoside inhibitors targeting HCV NS5B polymerase.

scholarly journals Alchemical Absolute Protein-Ligand Binding Free Energies for Drug Design

2021 ◽  
Author(s):  
Yuriy Khalak ◽  
Gary Tresdern ◽  
Matteo Aldeghi ◽  
Hannah Magdalena Baumann ◽  
David L. Mobley ◽  
...  
Keyword(s):  
Free Energy ◽  
Drug Discovery ◽  
Drug Design ◽  
Ligand Binding ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Energy Calculations ◽  
Binding Free Energy Calculations ◽  
Binding Free Energies

The recent advances in relative protein-ligand binding free energy calculations have shown the value of alchemical methods in drug discovery. Accurately assessing absolute binding free energies, although highly desired, remains...

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