Structure-based pose prediction: Non-cognate docking extended to macrocyclic ligands

So-called "cross-docking" is the prediction of the bound configuration of small-molecule ligands that differ from the cognate ligand of a protein co-crystal structure. This is a much more challenging problem than re-docking the cognate ligand, particularly when the new ligand is structurally dissimilar from prior known ones. We have updated the previously introduced PINC ("PINC Is Not Cognate") benchmark which introduced the idea of temporal segregation to measure cross-docking performance. The temporal set encompasses 846 future ligands for ten targets based on information from the earliest 25% of X-ray co-crystal structures known for each target. Here, we extend the benchmark to include thirteen targets where the bound poses of 128 macrocyclic ligands are to be predicted based on knowledge from structures of bound non-macrocyclic ligands. Performance was roughly equivalent for both the temporally-split non-macrocyclic ligand set and the macrocycle prediction set. Using standard and fully automatic protocols for the Surflex-Dock and ForceGen methods, across the combined 974 non-macrocyclic and macrocyclic ligands, the top-scoring pose family was correct 68% of the time, with the top-two pose families achieving a 79% success rate. Correct poses among all those predicted were identified 92% of the time. These success rates far exceeded those observed for the alternative methods AutoDock Vina and Gnina on both sets.

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Publication Details

Journal
Journal of Computer-Aided Molecular Design
Published
2024-10-16
DOI
https://doi.org/10.1007/s10822-024-00574-0
Citations
2
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.72
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article

Structure-based pose prediction: Non-cognate docking extended to macrocyclic ligands

Ajay N. Jain, Ann E. Cleves, Himani Tandon
2 citations
Journal of Computer-Aided Molecular Design
Computational Drug Discovery Methods
0.72
article

Structure-based pose prediction: Non-cognate docking extended to macrocyclic ligands

Ajay N. Jain, Ann E. Cleves, Himani Tandon
article en
2 citations

Abstract

So-called "cross-docking" is the prediction of the bound configuration of small-molecule ligands that differ from the cognate ligand of a protein co-crystal structure. This is a much more challenging problem than re-docking the cognate ligand, particularly when the new ligand is structurally dissimilar from prior known ones. We have updated the previously introduced PINC ("PINC Is Not Cognate") benchmark which introduced the idea of temporal segregation to measure cross-docking performance. The temporal set encompasses 846 future ligands for ten targets based on information from the earliest 25% of X-ray co-crystal structures known for each target. Here, we extend the benchmark to include thirteen targets where the bound poses of 128 macrocyclic ligands are to be predicted based on knowledge from structures of bound non-macrocyclic ligands. Performance was roughly equivalent for both the temporally-split non-macrocyclic ligand set and the macrocycle prediction set. Using standard and fully automatic protocols for the Surflex-Dock and ForceGen methods, across the combined 974 non-macrocyclic and macrocyclic ligands, the top-scoring pose family was correct 68% of the time, with the top-two pose families achieving a 79% success rate. Correct poses among all those predicted were identified 92% of the time. These success rates far exceeded those observed for the alternative methods AutoDock Vina and Gnina on both sets.

Journal of Computer-Aided Molecular DesignVol. 38(1)
Optibrium (United Kingdom) (GB), BioPharm (United Kingdom) (GB)
Zero hunger
Openalex Percentile: Top 25%
Computational Drug Discovery Methods
0.72
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Structure-based pose prediction: Non-cognate docking extended to macrocyclic ligands — Ajay N. Jain, Ann E. Cleves, et al. · Journal of Computer-Aided Molecular Design (2024) | TGRS Research Map | TGRS