MU3DSP

MU3DSP predicts changes in protein thermodynamic stability caused by single-point variants to assess mutation-induced effects on protein biophysics and disease.


Key Features:

  • Integration of Sequence-Level and Structural Data: MU3DSP combines sequence-level features with averaged structural data derived from protein sequence alignments to known Protein Data Bank (PDB) structures.
  • No Requirement for Experimental Structures: MU3DSP does not require experimentally determined tertiary structures and instead uses averaged structural profiles inferred from alignments to PDB entries.
  • Benchmark Performance: MU3DSP has demonstrated superior performance compared to existing methods on various benchmarks for predicting stability changes.
  • Variant Scope: MU3DSP assesses the impact of both somatic and germline amino acid substitution variants on protein stability.

Scientific Applications:

  • Mutation Analysis: It supports studies of how single-point mutations affect protein thermodynamic stability, informing understanding of mutation-related diseases.
  • Protein Design: Predicted stability changes can guide the design of proteins with desired stability properties for biotechnology and therapeutic development.
  • Variant Impact Assessment: MU3DSP aids interpretation of substitution variants in genomic and proteomic studies by quantifying stability effects.

Methodology:

MU3DSP takes a protein sequence with a single variant as input, integrates sequence-level features with averaged 3D structural profiles obtained by alignment to PDB structures, and outputs predicted thermodynamic stability changes for the amino acid substitution.

Topics

Details

License:
Not licensed
Cost:
Free of charge
Tool Type:
command-line tool
Operating Systems:
Mac, Linux, Windows
Programming Languages:
Python
Added:
2/20/2023
Last Updated:
11/24/2024

Operations

Publications

Gong J, Wang J, Zong X, Ma Z, Xu D. Prediction of protein stability changes upon single-point variant using 3D structure profile. Computational and Structural Biotechnology Journal. 2023;21:354-364. doi:10.1016/j.csbj.2022.12.008. PMID:36582438. PMCID:PMC9791599.

PMID: 36582438
PMCID: PMC9791599
Funding: - National Institutes of Health: R35-GM126985 - China Scholarship Council: 201906620047