Assessment of protein–ligand complexes in CASP15

Author:

Robin Xavier12ORCID,Studer Gabriel12ORCID,Durairaj Janani12,Eberhardt Jerome12,Schwede Torsten12ORCID,Walters W. Patrick3ORCID

Affiliation:

1. Biozentrum, University of Basel Basel Switzerland

2. SIB Swiss Institute of Bioinformatics Basel Switzerland

3. Relay Therapeutics Cambridge Massachusetts USA

Abstract

AbstractCASP15 introduced a new category, ligand prediction, where participants were provided with a protein or nucleic acid sequence, SMILES line notation, and stoichiometry for ligands and tasked with generating computational models for the three‐dimensional structure of the corresponding protein–ligand complex. These models were subsequently compared with experimental structures determined by x‐ray crystallography or cryoEM. To assess these predictions, two novel scores were developed. The Binding‐Site Superposed, Symmetry‐Corrected Pose Root Mean Square Deviation (BiSyRMSD) evaluated the absolute deviations of the models from the experimental structures. At the same time, the Local Distance Difference Test for Protein–Ligand Interactions (lDDT‐PLI) assessed the ability of models to reproduce the protein–ligand interactions in the experimental structures. The ligands evaluated in this challenge range from single‐atom ions to large flexible organic molecules. More than 1800 submissions were evaluated for their ability to predict 23 different protein–ligand complexes. Overall, the best models could faithfully reproduce the geometries of more than half of the prediction targets. The ligands' size and flexibility were the primary factors influencing the predictions' quality. Small ions and organic molecules with limited flexibility were predicted with high fidelity, while reproducing the binding poses of larger, flexible ligands proved more challenging.

Publisher

Wiley

Subject

Molecular Biology,Biochemistry,Structural Biology

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A High-Quality Data Set of Protein–Ligand Binding Interactions Via Comparative Complex Structure Modeling;Journal of Chemical Information and Modeling;2024-01-05

2. Fully flexible molecular alignment enables accurate ligand structure modelling;2023-12-17

3. Critical assessment of methods of protein structure prediction (CASP)—Round XV;Proteins: Structure, Function, and Bioinformatics;2023-11-02

4. Automated benchmarking of combined protein structure and ligand conformation prediction;Proteins: Structure, Function, and Bioinformatics;2023-10-26

5. New prediction categories in CASP15;Proteins: Structure, Function, and Bioinformatics;2023-06-12

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