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Proteomics01:33

Proteomics

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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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A Protocol for Computer-Based Protein Structure and Function Prediction
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Utilizing the scale-invariant feature transform algorithm to align distance matrices facilitates systematic protein

Zhengyang Guo1, Yang Wang1, Guangshuo Ou1

  • 1Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, McGovern Institute for Brain Research, State Key Laboratory of Membrane Biology, School of Life Sciences and MOE Key Laboratory for Protein Science, Tsinghua University, Beijing 100084, China.

Bioinformatics (Oxford, England)
|February 6, 2024
PubMed
Summary
This summary is machine-generated.

The align distance matrix with scale (ADAMS) pipeline offers efficient protein structure comparison. ADAMS accurately identifies similarities, even for flexible proteins, matching Foldseek

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Area of Science:

  • Structural bioinformatics
  • Computational biology
  • Protein science

Background:

  • Protein structure comparison is crucial for understanding protein function, homology, and evolution.
  • Advances in in-silico protein structure prediction generate vast numbers of models, requiring efficient comparison tools.
  • Existing methods face challenges with proteins exhibiting significant structural flexibility, especially when sequence similarity is low.

Purpose of the Study:

  • To develop a novel pipeline, ADAMS (align distance matrix with scale), for large-scale protein structure comparison.
  • To address limitations in comparing structurally flexible proteins.
  • To provide a tool with performance and accuracy comparable to existing methods like Foldseek.

Main Methods:

  • Developed the ADAMS pipeline, integrating distance matrix alignment with the scale-invariant feature transform algorithm.
  • Employed a computer vision-centric approach to compare distance matrices.
  • Evaluated ADAMS against existing tools for performance, accuracy, and handling of flexible protein structures.

Main Results:

  • ADAMS demonstrates performance and accuracy on par with Foldseek.
  • ADAMS effectively handles proteins with high structural flexibility, overcoming limitations of other tools.
  • The pipeline offers a streamlined approach to proteomic-scale protein structure comparison.

Conclusions:

  • ADAMS is an efficacious tool for in-depth protein structure analysis, offering heightened accuracy.
  • The pipeline provides a valuable alternative for comparing protein structures, particularly those with flexibility.
  • ADAMS is accessible as a Python package, with source code and an online server available.