Continuous Evaluation of Ligand Protein Predictions: A Weekly Community Challenge for Drug Docking

Wagner, Jeffrey; Churas, Christopher; Liu, Shuai; Swift, Robert V.; Chiu, Michael; Shao, Chenghua; Feher, Victoria A.; Burley, S.K.; Gilson, Michael K.; Amaro, Rommie E.

doi:10.1016/j.str.2019.05.012

“…Binding free energies were computed for the cocrystal structure, 5uf0 60 , and also for five ligand poses generated by computational docking. This docking workflow uses a modified version of the one explained in the CELPPade tutorial 61 , 62 . Note that the docking workflow is not part of the BAT package and the docked poses it generated are included in the input examples associated with the present paper.…”

Section: Methodsmentioning

confidence: 99%

“…This makes it possible to move to expanded testing of ABFE calculations as a tool for scoring docked ligand poses, while also estimating overall binding free energies, so that many ligands can be ranked in terms of their calculated affinities. We plan next to extend these calculations to other protein systems, testing different force fields, water models and simulation parameters, including in the context of the rolling CELPP pose-prediction exercise 62 . In future work, it may be useful to seek accelerated convergence through enhanced sampling techniques 71 and hybrid Monte Carlo/MD methods that enable water to exchange between buried sites and the bulk solvent 72 , 73 .…”

Section: Ready For High-throughput?mentioning

confidence: 99%

Automation of absolute protein-ligand binding free energy calculations for docking refinement and compound evaluation

Heinzelmann

¹

,

Gilson

²

2021

Sci Rep

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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 automate the calculation of binding free energies for a protein with a series of ligands. The software supports the attach-pull-release (APR) and double decoupling (DD) binding free energy methods, as well as the simultaneous decoupling-recoupling (SDR) method, a variant of double decoupling that avoids numerical artifacts associated with charged 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 positions this procedure to be applied in a relatively high-throughput mode and thus stands to enable new applications in early-stage drug discovery.

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“…As a complementary approach to experimental HTS, virtual screening (VS) is able to screen a large compound database and has become an alternative or even better choice for both academic groups and pharmaceutical industries for lead identification 82 . The VS method can be roughly divided into two categories: ligand‐based VS (LBVS), starting from known ligands of a target, and target/structural‐based VS (TBVS/SBVS), which starts from the three‐dimensional (3D) crystal structure of a target (Figure 7).…”

Section: Structural Biology Of Pi3kγmentioning

confidence: 99%

Targeting phosphatidylinositol 3‐kinase gamma (PI3Kγ): Discovery and development of its selective inhibitors

Zhu

¹

,

Li

²

,

Liu

³

et al. 2020

Medicinal Research Reviews

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Phosphatidylinositol 3‐kinase gamma (PI3Kγ) has been regarded as a promising drug target for the treatment of advanced solid tumors, leukemia, lymphoma, and inflammatory and autoimmune diseases. However, the high level of structural conservation among the members of the PI3K family and the diverse physiological roles of Class I PI3K isoforms (α, β, δ, and γ) highlight the importance of isoform selectivity in the development of PI3Kγ inhibitors. In this review, we provide an overview of the structural features of PI3Kγ that influence γ‐isoform selectivity and discuss the structure‐selectivity‐activity relationship of existing clinical PI3Kγ inhibitors. Additionally, we summarize the experimental and computational techniques utilized to identify PI3Kγ inhibitors. The insights gained so far could be used to overcome the main challenges in development and accelerate the discovery of PI3Kγ‐selective inhibitors.

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“…The docking workflow uses a modified version of the one explained in the CELPPade tutorial, 54 which is associated with the CELPP blinded prediction challenge. 55 It uses Autodock Vina 56 for the docking and Chimera 57 for protein and ligand setup and to convert the output files to pdb format. The protein structure used for docking is 5uez, 58 as this was identified by CELPP as having the ligand with the largest maximum common substructure (LMCSS) with our target ligand (right of Fig.…”

Section: Protein-ligand Test Systemmentioning

confidence: 99%

“…We plan next to extend these calculations to other protein systems, testing different force fields, water models and simulation parameters, including in the context of the rolling CELPP pose-prediction exercise. 55…”

Section: Performance and Costsmentioning

confidence: 99%

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

Heinzelmann¹,

Gilson

²

2020

Preprint

Self Cite

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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

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Continuous Evaluation of Ligand Protein Predictions: A Weekly Community Challenge for Drug Docking

Abstract: Highlights d The CELPP challenge evaluates protein-ligand pose prediction workflows d Participants are tasked with predicting dozens of complexes each week d We invite additional researchers to participate in CELPP

Cited by 40 publications

References 106 publications

Automation of absolute protein-ligand binding free energy calculations for docking refinement and compound evaluation

Automation of absolute protein-ligand binding free energy calculations for docking refinement and compound evaluation

Targeting phosphatidylinositol 3‐kinase gamma (PI3Kγ): Discovery and development of its selective inhibitors

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

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