Large-Scale Assessment of Binding Free Energy Calculations in Active Drug Discovery Projects

Schindler, Christina; Baumann, Hannah M.; Blum, Andreas; Böse, Dietrich; Buchstaller, Hans‐Peter; Burgdorf, Lars T.; Cappel, Daniel; Chekler, Eugene L. Piatnitski; Czodrowski, Paul; Dorsch, Dieter; Eguida, Merveille; Follows, Bruce; Fuchß, Thomas; Grädler, Ulrich; Gunera, Jakub; Johnson, Theresa; Lebrun, Catherine Jorand; Karra, Srinivasa; Klein, Markus; Knehans, Tim; Koetzner, Lisa; Krier, Mireille; Leiendecker, Matthias; Leuthner, Birgitta; Li, Liwei; Mochalkin, Igor; Müsil, Djordje; Neagu, Constantin; Rippmann, Friedrich; Schiemann, Kai; Schulz, Robert; Steinbrecher, Thomas; Tanzer, Eva‐Maria; Lopez, Andrea Unzue; Follis, Ariele Viacava; Wegener, Ansgar; Kühn, Daniel

doi:10.1021/acs.jcim.0c00900

Cited by 204 publications

(365 citation statements)

References 97 publications

(176 reference statements)

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“…Unfortunately, it promotes the uncritical use of one-off simulations. Merck recently published a large-scale study using FEP+ and discussed several challenges in its application within the drug discovery process [75]. However, the authors did not perform ensemble simulations to confirm the robustness and reproducibility of their findings which therefore have only a provisional status.…”

Section: Ensemble Averagingmentioning

confidence: 99%

“…In such cases, an accurate ranking of the available drugs based on their binding affinities when bound to different mutants of the target protein is the prerequisite. We studied the efficacy of two inhibitors to wild-type and mutant fibroblast growth factor receptor 1 (FGFR1) using ensemble simulations [75]. FGFR1 is a recognized therapeutic target in cancer.…”

Section: Application Of Free Energy Calculationsmentioning

confidence: 99%

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Rapid, accurate, precise and reproducible ligand–protein binding free energy prediction

et al. 2020

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A central quantity of interest in molecular biology and medicine is the free energy of binding of a molecule to a target biomacromolecule. Until recently, the accurate prediction of binding affinity had been widely regarded as out of reach of theoretical methods owing to the lack of reproducibility of the available methods, not to mention their complexity, computational cost and time-consuming procedures. The lack of reproducibility stems primarily from the chaotic nature of classical molecular dynamics (MD) and the associated extreme sensitivity of trajectories to their initial conditions. Here, we review computational approaches for both relative and absolute binding free energy calculations, and illustrate their application to a diverse set of ligands bound to a range of proteins with immediate relevance in a number of medical domains. We focus on ensemble-based methods which are essential in order to compute statistically robust results, including two we have recently developed, namely thermodynamic integration with enhanced sampling and enhanced sampling of MD with an approximation of continuum solvent. Together, these form a set of rapid, accurate, precise and reproducible free energy methods. They can be used in real-world problems such as hit-to-lead and lead optimization stages in drug discovery, and in personalized medicine. These applications show that individual binding affinities equipped with uncertainty quantification may be computed in a few hours on a massive scale given access to suitable high-end computing resources and workflow automation. A high level of accuracy can be achieved using these approaches.

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Section: Ensemble Averagingmentioning

confidence: 99%

Section: Application Of Free Energy Calculationsmentioning

confidence: 99%

Rapid, accurate, precise and reproducible ligand–protein binding free energy prediction

et al. 2020

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“…The initialization of the simulations with a proper starting structure has a profound effect on the accuracy of estimated ∆G (Fig 2). This observation, however, could be interpreted merely as a sampling issue: routine free energy calculation protocols use short (5-20 ns) equilibrium simulations 16,43,52 that may not be sufficient for generating a representative apo state ensemble. Inaccuracies in the estimated free energies due to undersampling have been previously reported for both rel-ative 31 and absolute 5 protein-ligand binding free energy calculations.…”

Section: Apo Protein State In Absolute ∆G Calculationsmentioning

confidence: 99%

Alchemical absolute protein–ligand binding free energies for drug design

et al. 2021

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“…The initialization of the simulations with a proper starting structure has a profound effect on the accuracy of estimated ∆G (Fig 2). This observation, however, could be inter-preted merely as a sampling issue: routine free energy calculation protocols use short (5-20 ns) equilibrium simulations 15,39,47 that may not be sufficient for generating a representative apo state ensemble. Inaccuracies in the estimated free energies due to undersampling have been previously reported for both relative 28 and absolute 4 protein-ligand binding free energy calculations.…”

Section: Apo Protein State In Absolute ∆G Calculationsmentioning

confidence: 99%

Alchemical Absolute Protein-Ligand Binding Free Energies for Drug Design

Khalak

Tresadern

Aldeghi

et al. 2021

Preprint

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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 remains a challenging endeavour, mostly limited to small model cases. We demonstrate accurate absolute binding free energy estimates for 128 pharmaceutically relevant ligands across 7 proteins using a highly parallelizable non-equilibrium method. These calculations also provide detailed physical insight into the structural determinants of binding, identifying subtle rotamer rearrangements between protein apo and holo states that are crucial for binding. The challenge behind absolute binding free energy calculations stems in large part from the need to explicitly account for the protein's apo state. In this work we present several approaches to obtain apo state ensembles, including a novel rigorous method to generate protein-ligand ensembles for the ligand in its decoupled state. Altogether, we present an effective open-source protocol for prospective application in drug discovery.

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Large-Scale Assessment of Binding Free Energy Calculations in Active Drug Discovery Projects

Cited by 204 publications

References 97 publications

Rapid, accurate, precise and reproducible ligand–protein binding free energy prediction

Rapid, accurate, precise and reproducible ligand–protein binding free energy prediction

Alchemical absolute protein–ligand binding free energies for drug design

Alchemical Absolute Protein-Ligand Binding Free Energies for Drug Design

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