bioRxivBioinformaticsPreprint
DDI_single: Single-Sequence-Based Protein Domain Assembly
Abstract
Domains are the basic units of protein structure and function. Appropriate inter-domain organization is critical to enable cooperative execution of multiple related functions. It is thus a crucial step to determine the full-length structure of multi-domain proteins for the purpose of elucidating their functions and designing new drugs to regulate these functions. Existing structure prediction algorithms are generally better at solving the internal conformation of domains, rather than modeling the relative positions between domains. To address the challenge of accurately determining multi-domain protein conformations, we develop a single-sequence-based domain assembly algorithm called DDI_single. DDI_single directly extracts features from the amino acid sequence using the protein language model ESM-lb, and accurately predicts the interactions between residue pairs of structural domains through a novel gated cross-attention module, thus achieving the correct assembly of structural domains. With the knowledge of domain definition, DDI_single achieves more than 20% higher accuracy in the task of predicting the relative distances of residue pairs between domains than that of the single-sequence-based structure prediction algorithm trRosettaX_single. When assembling domains with known spatial conformations, DDI_single correctly assembles 74.4% of the samples in the test set (TM-score>0.5). When assembling domains with unknown spatial conformations, in cases where the internal spatial conformations of domains are correctly modeled, DDI_single correctly assembles 73.9% of the samples.
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- E2EDA: Protein domain assembly based on end-to-end deep learning
Haitao Zhu, Yuhao Xia, Guijun Zhang·Journal of Chemical Information and ModelingPeer-reviewed·Oct 3, 2023
- Inter-domain distance prediction based on deep learning for domain assembly
Fengqi Ge, Chunxiang Peng, … Guijun Zhang·Briefings in BioinformaticsPeer-reviewed·Mar 15, 2023
- Domain-based multi-domain protein and complex structure prediction using inter-domain interactions from deep learning
Yuhao Xia, Kailong Zhao, … Guijun Zhang·bioRxiv·May 5, 2023
- Structural analogue-based protein structure domain assembly assisted by deep learning
Chunxiang Peng, Xiaogen Zhou, … Guijun Zhang·BioinformaticsPeer-reviewed·Aug 13, 2022
- DomBpred: protein domain boundary predictor using inter-residue distance and domain-residue level clustering
Zhong-Ze Yu, Chunxiang Peng, … Guijun Zhang·bioRxiv·Nov 19, 2021
- DeepAssembly2: A Web Server for Protein Complex Structure Assembly Based on Domain-Domain Interactions
Yuhao Xia, Yilin Pu, … Guijun Zhang·Journal of Molecular BiologyPeer-reviewed·Apr 6, 2025