2020
DOI: 10.1007/s10822-020-00289-y
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D3R grand challenge 4: blind prediction of protein–ligand poses, affinity rankings, and relative binding free energies

Abstract: The Drug Design Data Resource (D3R) aims to identify best practice methods for computer aided drug design through blinded ligand pose prediction and affinity challenges. Herein, we report on the results of Grand Challenge 4 (GC4). GC4 focused on proteins beta secretase 1 and Cathepsin S, and was run in an analogous manner to prior challenges. In Stage 1, participant ability to predict the pose and affinity of BACE1 ligands were assessed. Following the completion of Stage 1, all BACE1 co-crystal structures were… Show more

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Cited by 102 publications
(111 citation statements)
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References 92 publications
(78 reference statements)
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“…During the D3R grand challenge 2, the core hopping transformation between ligands 91 and 93 could have been easily achieved by scaling and restraining, rather than the less rigorous approach that we improvised at that time 54 . Soft bonds would have been necessary to efficiently study the macrocycle perturbations with MS λ D in the D4R grand challenge 4 55 . Finally, scaling and restraining enables a broader scope of MS λ D multisite systems, because alchemical regions may be directly bonded to each other rather than requiring two intervening environment atoms.…”
Section: Discussionmentioning
confidence: 99%
“…During the D3R grand challenge 2, the core hopping transformation between ligands 91 and 93 could have been easily achieved by scaling and restraining, rather than the less rigorous approach that we improvised at that time 54 . Soft bonds would have been necessary to efficiently study the macrocycle perturbations with MS λ D in the D4R grand challenge 4 55 . Finally, scaling and restraining enables a broader scope of MS λ D multisite systems, because alchemical regions may be directly bonded to each other rather than requiring two intervening environment atoms.…”
Section: Discussionmentioning
confidence: 99%
“…It may be that host-guest systems are "simple" enough that there is essentially nowhere for problems to hide, or confounding factors like polarizability and force field limitations may be more profound in these simple mini-receptors. Alternatively, performance of protein-ligand binding free energy calculations has often been worse in blind challenges like the SAMPL [18] and D3R [19][20][21][22] blind challenges than in the large-scale tests cited above, so it may be that typical retrospective tests simply benefit from participants utilizing additional knowledge which is not available prospectively or in blind challenges. This is supported to some extent by recent benchmarking work from Merck KGaA [13], and by an earlier industry perspective [23].…”
Section: Why Use Host Guest Systems?mentioning
confidence: 99%
“…It may be that host-guest systems are "simple" enough that there is essentially nowhere for problems to hide, or confounding factors like polarizability and force field limitations may be more profound in these simple mini-receptors. Alternatively, performance of protein-ligand binding free energy calculations has often been worse in blind challenges like the SAMPL [18] and D3R [19][20][21][22] blind challenges than in the large-scale tests cited above, so it may be that typical retrospective tests simply benefit from participants utilizing additional knowledge which is not available prospectively or in blind challenges. This is supported to some extent by recent benchmarking work from Merck KGaA [13], and by an earlier industry perspective [23].…”
Section: Why Use Host Guest Systems?mentioning
confidence: 99%