New Coarse Variables for the Accurate Determination of Standard Binding Free Energies

Fu, Haohao; Cai, Wensheng; Hénin, Jérôme; Roux, Benoît; Chipot, Christophe

doi:10.1021/acs.jctc.7b00791

Cited by 58 publications

(106 citation statements)

References 32 publications

Supporting

Mentioning

101

Contrasting

Unclassified

Order By: Relevance

“…Recently, we have developed an original framework based on first principles eliciting protein-ligand and protein-protein absolute binding free energies to be determined with utmost reliability [ 53 , 54 ]. The proposed strategy has been enhanced with the introduction of tailored coarse variables, germane to virtually any host-guest complexes [ 55 ]. Here, we probe this methodology to the challenging case of DNA-ligand recognition and association.…”

Section: Introductionmentioning

confidence: 99%

Accurate Estimation of the Standard Binding Free Energy of Netropsin with DNA

et al. 2018

Self Cite

View full text Add to dashboard Cite

DNA is the target of chemical compounds (drugs, pollutants, photosensitizers, etc.), which bind through non-covalent interactions. Depending on their structure and their chemical properties, DNA binders can associate to the minor or to the major groove of double-stranded DNA. They can also intercalate between two adjacent base pairs, or even replace one or two base pairs within the DNA double helix. The subsequent biological effects are strongly dependent on the architecture of the binding motif. Discriminating between the different binding patterns is of paramount importance to predict and rationalize the effect of a given compound on DNA. The structural characterization of DNA complexes remains, however, cumbersome at the experimental level. In this contribution, we employed all-atom molecular dynamics simulations to determine the standard binding free energy of DNA with netropsin, a well-characterized antiviral and antimicrobial drug, which associates to the minor groove of double-stranded DNA. To overcome the sampling limitations of classical molecular dynamics simulations, which cannot capture the large change in configurational entropy that accompanies binding, we resort to a series of potentials of mean force calculations involving a set of geometrical restraints acting on collective variables.

show abstract

Section: Introductionmentioning

confidence: 99%

Accurate Estimation of the Standard Binding Free Energy of Netropsin with DNA

et al. 2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…[32][33][34] The specific algorithm from Wang et al 35 is implemented in the colvars module of the utilized MD program NAMD 36 to control the six variables. 31,37 The same algorithm is also used in our MC program, MCPRO. In the MC implementation, the restraints are turned on simultaneously with the removal of the atomic charges so Gvb is included in the electrostatic portion of Gbound, but it requires a separate simulation in the MD calculations using NAMD.…”

Section: Methodsmentioning

confidence: 99%

Absolute Free Energy of Binding Calculations for Macrophage Migration Inhibitory Factor in Complex with a Druglike Inhibitor

et al. 2019

View full text Add to dashboard Cite

Calculation of the absolute free energy of binding (ΔGbind) for a complex in solution is challenging owing to the need for adequate configurational sampling and an accurate energetic description, typically with a force field (FF). In this study, Monte Carlo (MC) simulations with improved side-chain and backbone sampling are used to assess ΔGbind for the complex of a drug-like inhibitor (MIF180) with the protein macrophage migration inhibitory factor (MIF) using free energy perturbation (FEP) calculations. For comparison, molecular dynamics (MD) simulations were employed as an alternative sampling method for the same system. With the OPLS-AA/M FF and CM5 atomic charges for the inhibitor, the ΔGbind results from the MC/FEP and MD/FEP simulations,-8.80 ± 0.74 and-8.46 ± 0.85 kcal/mol, agree well with each other and with the experimental value of-8.98 ± 0.28 kcal/mol. The convergence of the results and analysis of the trajectories indicate that sufficient sampling was achieved for both approaches. Repeating the MD/FEP calculations using current versions of the CHARMM and AMBER FFs led to a 6-kcal/mol range of computed ΔGbind. These results show that calculation of accurate ΔGbind for large ligands is both feasible and numerically equivalent, within error limits, using either methodology.

show abstract

“…Important prior contributions toward automation of ABFE calculations include the CHARMM-GUI server 33,34 and the binding free energy estimator (BFEE). 35,36 The former is a web-based interface that helps create input files for the various stages listed above. The latter is a tcl plug-in for VMD, 37 with a graphical interface that creates a complete ABFE workflow starting from an initial prepared and equilibrated protein-ligand complex.…”

Section: Introductionmentioning

confidence: 99%

Automated docking refinement and virtual compound screening with absolute binding free energy calculations

Heinzelmann¹,

Gilson

2020

Preprint

View full text Add to dashboard Cite

Absolute binding free energy calculations with explicit solvent molecular simulations can provide estimates of protein-ligand affinities, and thus reduce the time and costs needed to find new drug candidates. However, these calculations can be complex to implement and perform. Here, we introduce the software BAT.py, a Python tool that invokes the AMBER simulation package to fully automate the calculation of binding free energies for a protein with a series of ligands. We report encouraging initial test applications of this software both to re-rank docked poses and to estimate overall binding free energies. We also show that it is practical to carry out these calculations cheaply by using graphical processing units in common machines that can be built for this purpose. The combination of automation and low cost allows this procedure to be applied in a relatively high-throughput mode, and thus enables new applications in early-stage drug discovery.Protein-ligand binding free energy calculations based on atomistic molecular simulations promise to play a growing role in drug discovery, as they provide estimates of the binding affinities of compounds proposed as drug candidates for a protein target, and thus may reduce the time and cost required for trial-and-error experimentation. 1,2 Thus, in settings where the calculations are sufficiently fast and accurate, 3 one may anticipate significant savings of time and cost in early stages of drug discovery. [4][5][6][7] It is informative to divide this broad class of methods into two subtypes: relative binding free energy (RBFE) calculations; [8][9][10][11][12][13][14] and absolute binding free energy (ABFE) calculations. [15][16][17][18][19][20][21][22][23] The former (RBFE) estimate the difference in binding free energy between two compounds by computing the change in free energy associated with a non-physical transformation of one compound to the other, in the binding site and in bulk solvent. 8,24 Because it is easiest to carry out such alchemical transformations between compounds that are similar to each other and that adopt similar bound poses, RBFE calculations are often regarded as particularly suitable for the leadoptimization stage of drug discovery, where small chemical modifications of the initial lead compound must be selected. Interestingly, though, a recent study reports greater impact on the earlier hit-to-lead stage. 3

show abstract

New Coarse Variables for the Accurate Determination of Standard Binding Free Energies

Cited by 58 publications

References 32 publications

Accurate Estimation of the Standard Binding Free Energy of Netropsin with DNA

Accurate Estimation of the Standard Binding Free Energy of Netropsin with DNA

Absolute Free Energy of Binding Calculations for Macrophage Migration Inhibitory Factor in Complex with a Druglike Inhibitor

Automated docking refinement and virtual compound screening with absolute binding free energy calculations

Contact Info

Product

Resources

About