Evidence map›Paper›PMID 39414633›Full record

ArticleJournal of computer-aided molecular design2024

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

Ann E Cleves, Himani Tandon, Ajay N Jain

Abstract read
In one paragraph

Article in Journal of computer-aided molecular design, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Reaction Engineering of In Vitro Natural Product Biosynthesis: Challenges and Strategies.Chembiochem : a European journal of chemical biology · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ann E ClevesBioPharmics Division, Optibrium Limited, Cambridge, CB25 9PB, UK.ORCID 0000-0002-1622-2770
Himani TandonResearch Department, Optibrium Limited, Cambridge, CB25 9PB, UK.ORCID 0000-0002-3469-8449
Ajay N JainBioPharmics Division, Optibrium Limited, Cambridge, CB25 9PB, UK. ajay@optibrium.com.ORCID 0000-0003-4641-8501

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Macrocyclic CompoundsMolecular Docking SimulationProtein BindingProteinsBinding SitesCrystallography, X-RayDrug DesignLigandsProtein ConformationLigandsMacrocyclic CompoundsProteinsAutoDockDockingForceGenGninaMacrocycleSurflex-DockVinaxGen

Identifiers

PMID39414633
PMCPMC11485047

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.