Cited by 15Protein Structure and DynamicsEnzyme Structure and FunctionMachine Learning in Bioinformatics

Distance‐based reconstruction of protein quaternary structures from inter‐chain contacts

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Soltanikazemi, Elham, Quadir, Farhan, Roy, Raj S, Guo, Zhiye, Cheng, Jianlin·2022·Proteins: Structure, Function, and Bioinformatics

Published version of a preprint

Abstract

Predicting the quaternary structure of protein complex is an important problem. Inter‐chain residue‐residue contact prediction can provide useful information to guide the ab initio reconstruction of quaternary structures. However, few methods have been developed to build quaternary structures from predicted inter‐chain contacts. Here, we develop the first method based on gradient descent optimization (GD) to build quaternary structures of protein dimers utilizing inter‐chain contacts as distance restraints. We evaluate GD on several datasets of homodimers and heterodimers using true/predicted contacts and monomer structures as input. GD consistently performs better than both simulated annealing and Markov Chain Monte Carlo simulation. Starting from an arbitrarily quaternary structure randomly initialized from the tertiary structures of protein chains and using true inter‐chain contacts as input, GD can reconstruct high‐quality structural models for homodimers and heterodimers with average TM‐score ranging from 0.92 to 0.99 and average interface root mean square distance from 0.72 Å to 1.64 Å. On a dataset of 115 homodimers, using predicted inter‐chain contacts as restraints, the average TM‐score of the structural models built by GD is 0.76. For 46% of the homodimers, high‐quality structural models with TM‐score ≥ 0.9 are reconstructed from predicted contacts. There is a strong correlation between the quality of the reconstructed models and the precision and recall of predicted contacts. Only a moderate precision or recall of inter‐chain contact prediction is needed to build good structural models for most homodimers. Moreover, GD improves the quality of quaternary structures predicted by AlphaFold2 on a Critical Assessment of Techniques for Protein Structure Prediction–Critical Assessments of Predictions of Interactions dataset.

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Authors
Soltanikazemi, E., Quadir, F., Roy, R. S., Guo, Z., & Cheng, J.
Affiliations
University of Missouri (US)
Corresponding author
Cheng, Jianlin
Venue
Proteins: Structure, Function, and Bioinformatics
Publisher
Wiley
Published
2021-11-02
Volume
90
Issue
3
Pages
720-731
ISSN
  • 0887-3585 (ISSN-L)
  • 1097-0134
OpenAlex
W3209920439
Cited by
15
References
4
Citations by year
2025: 1 · 2024: 5 · 2023: 3 · 2022: 4 · 2021: 2
FWCI
1.10
Type
journal article
Language
en
Open access
Locations
  • Proteins Structure Function and Bioinformatics (publishedVersion, cc-by-nc)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
Funders
  • U.S. Department of Energy (DE‐AR0001213, DE‐SC0020400, DE‐SC0021303)
  • National Institutes of Health (R01GM093123)
  • National Science Foundation of Sri Lanka (DBI1759934, IIS1763246)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
Keywords
quaternary structure, protein complex structure prediction, distance restraints, gradient descent, homodimer, heterodimer, protein dimer, contact prediction, AlphaFold2
MeSH terms
Monte Carlo Method, Protein Binding, Proteins, Computational Biology, Protein Structure, Quaternary, Databases, Protein, Protein Multimerization, Molecular Docking Simulation

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