Assessing the effect of forcefield parameter sets on the accuracy of relative binding free energy calculations

Sun, Shan; Huggins, David J.

doi:10.3389/fmolb.2022.972162

Cited by 7 publications

(9 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A primary objective of small molecule drug discovery is to design compounds that can tightly and selectively bind to a target protein. Accurate calculation of protein–ligand binding free energy is therefore of central importance in computational drug discovery. − Benefiting from improved force fields and sampling algorithms and advanced hardware, rigorous free-energy calculation by free-energy perturbation or related methods in explicit solvent simulations has dramatically improved the accuracy and begun to play an increasingly important role in modern computational drug discovery projects. − As an example, the FEP+ implementation and other implementations − of free-energy calculation has demonstrated a high level of accuracy in relative protein–ligand binding free-energy (RBFE) calculations. The accurate modeling of complex perturbations, including scaffold hopping, , macrocyclization, net-charge changes, fragment linking, and linker enumeration, was also reported.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Hit Discovery in Virtual Screening through Absolute Protein–Ligand Binding Free-Energy Calculations

Chen

Cui

Jerome

et al. 2023

J. Chem. Inf. Model.

Self Cite

View full text Add to dashboard Cite

In the hit identification stage of drug discovery, a diverse chemical space needs to be explored to identify initial hits. Contrary to empirical scoring functions, absolute protein−ligand binding free-energy perturbation (ABFEP) provides a theoretically more rigorous and accurate description of protein−ligand binding thermodynamics and could, in principle, greatly improve the hit rates in virtual screening. In this work, we describe an implementation of an accurate and reliable ABFEP method in FEP+. We validated the ABFEP method on eight congeneric compound series binding to eight protein receptors including both neutral and charged ligands. For ligands with net charges, the alchemical ion approach is adopted to avoid artifacts in electrostatic potential energy calculations. The calculated binding free energies correlate with experimental results with a weighted average of R 2 = 0.55 for the entire dataset. We also observe an overall root-mean-square error (RMSE) of 1.1 kcal/mol after shifting the zero-point of the simulation data to match the average experimental values. Through ABFEP calculations using apo versus holo protein structures, we demonstrated that the protein conformational and protonation state changes between the apo and holo proteins are the main physical factors contributing to the protein reorganization free energy manifested by the overestimation of raw ABFEP calculated binding free energies using the holo structures of the proteins. Furthermore, we performed ABFEP calculations in three virtual screening applications for hit enrichment. ABFEP greatly improves the hit rates as compared to docking scores or other methods like metadynamics. The good performance of ABFEP in rank ordering compounds demonstrated in this work confirms it as a useful tool to improve the hit rates in virtual screening, thus facilitating hit discovery.

show abstract

Section: Introductionmentioning

confidence: 99%

Enhancing Hit Discovery in Virtual Screening through Absolute Protein–Ligand Binding Free-Energy Calculations

Chen

Cui

Jerome

et al. 2023

J. Chem. Inf. Model.

Self Cite

View full text Add to dashboard Cite

show abstract

“…43 The accuracy of the force field model can have a significant impact on the calculated free energy. 44–46 Here, to properly model the metal ion Mg 2+ coordination with the protein and ligand, we use a bonded model involving bond, angle, dihedral, electrostatic, and van der Waals terms 47–48 that are parameterized by following the procedure developed by Pengfei Li and Merz groups (Metal Center Parameter Builder (MCPB)). The bonded models 49 treat the interactions between the metal ion and its ligating atoms as covalent bonds.…”

Section: Methodsmentioning

confidence: 99%

“…43 The accuracy of the force field model can have a significant impact on the calculated free energy. [44][45][46] Here, to properly model the metal ion Mg 2+ coordination with the protein and ligand, we use a bonded model involving bond, angle, dihedral, electrostatic, and van der Waals terms [47][48] The conformational free energy difference between the extended and bent binding modes of 4f is computed using the R-FEP-R method (Fig 2 ), 16,53 which uses an alchemical pathway instead of the traditional physical pathway approach to connect the two conformational basins. In this method, the ligand atoms are divided into the shared part and the varying segment (see Fig.…”

Section: System Setup and Simulation Detailsmentioning

confidence: 99%

Elucidating the molecular determinants for binding modes of a third-generation HIV-1 integrase strand transfer inhibitor: Importance of side chain and solvent reorganization

Sun,

Biswas,

Lyumkis

et al. 2023

Preprint

View full text Add to dashboard Cite

The first and second-generation clinically used HIV-1 integrase (IN) strand transfer inhibitors (INSTIs) are key components of antiretroviral therapy (ART), which work by blocking the integration step in the HIV-1 replication cycle that is catalyzed by a nucleoprotein assembly called an intasome. However, resistance to even the latest clinically used INSTIs is beginning to emerge. Developmental third-generation INSTIs, based on naphthyridine scaffold, are promising candidates to combat drug-resistant viral variants. Among these novel INSTIs, compound 4f exhibits two distinct conformations when binding to intasomes from HIV-1 and the closely related prototype foamy virus (PFV), despite the high structural similarity of their INSTI binding pockets. The molecular mechanism and the key active site residues responsible for these differing binding modes in closely related intasomes remain elusive. To unravel the molecular determinants governing the two distinct binding modes, we employ a novel molecular dynamics-based free energy approach that utilizes alchemical pathways to overcome the sampling challenges associated with transitioning between two ligand conformations within crowded environments along physical pathways. The calculated conformational free energies successfully recapitulate the experimentally observed binding mode preferences in the two viral intasomes. Analysis of the simulated structures suggests that the observed binding mode preferences are caused by amino acid residue differences in both the front and the central catalytic sub-pocket of the INSTI binding site in HIV-1 and PFV. Additional free energy calculations on mutants of HIV-1 and PFV revealed that while both sub-pockets contribute to the binding mode selection, the central sub-pocket plays a more important role. These results highlight the importance of both side chain and solvent reorganization, as well as the conformational entropy in determining the ligand binding mode and will help inform the development of more effective INSTIs for combatting drug-resistant viral variants.

show abstract

“…The Zwanzig relationship underwent a series of evaluation scheme improvements from the original exponential average with double-wide sampling 7 and overlap sampling, 8 to BAR, 9 and to MBAR, 10 where the latter is reported in various instances to perform most efficiently and reliably. [10][11][12] In contrast to the consensus on the estimator choice for the free energy analysis, many other aspects of the FEP protocol remain ambiguous, such as treatments of perturbations with net charge changes, 13,14 force fields, 15 and the sampling conditions. 4,16 The selection of perturbation parameters is experience-based and often needs to be tailored according to the outputs of several trial runs.…”

Section: Introductionmentioning

confidence: 99%

Adaptive lambda schemes for efficient relative binding free energy calculation

Zeng,

Qian

2023

J Comput Chem

View full text Add to dashboard Cite

The relative free energy perturbation (RFEP) calculation is one of the most theoretically sound computational chemistry approaches for the binding affinity prediction. However, its application is often hindered by the complexity of the calculation choices and the requirement of expertise in the field. Improper lambda scheme of RFEP may result in deviations from an accurate description of the perturbation process and is prone to erroneous affinity predictions. To address such challenges, an automated adaptive lambda method is proposed where the adaptive lambda schemes are obtained through a split‐and‐merge algorithm based on the pilot runs. The newly established workflow along with a series of improvements to the perturbation settings increases the consistency of the RFEP calculation results. Comparing the pilot and adaptive lambda schemes, the latter demonstrated improvements in convergence and reproducibility and lowered the mean unsigned error and the root‐mean‐square error. Overall, the adaptive lambda method is a reliable and robust choice to predict small molecule relative binding free energy and can be capitalized to benefit routine RFEP calculations for drug discovery projects.

show abstract

Assessing the effect of forcefield parameter sets on the accuracy of relative binding free energy calculations

Cited by 7 publications

References 65 publications

Enhancing Hit Discovery in Virtual Screening through Absolute Protein–Ligand Binding Free-Energy Calculations

Enhancing Hit Discovery in Virtual Screening through Absolute Protein–Ligand Binding Free-Energy Calculations

Elucidating the molecular determinants for binding modes of a third-generation HIV-1 integrase strand transfer inhibitor: Importance of side chain and solvent reorganization

Adaptive lambda schemes for efficient relative binding free energy calculation

Contact Info

Product

Resources

About