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PROMALS3D: multiple protein sequence alignment enhanced with evolutionary and three-dimensional structural

Jimin Pei1, Nick V Grishin

  • 1Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA.

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PubMed
Summary
This summary is machine-generated.

Accurate protein multiple sequence alignment (MSA) is challenging for divergent proteins. PROMALS3D improves MSA quality by integrating evolutionary and structural data from public databases.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Multiple sequence alignment (MSA) is crucial for bioinformatics and computational biology.
  • Accurate MSA construction for divergent proteins is computationally challenging.
  • Publicly available protein sequence and structure data can enhance MSA quality.

Purpose of the Study:

  • To introduce PROMALS3D, a tool for protein MSA construction.
  • To leverage evolutionary and structural information for improved alignment accuracy.
  • To provide a web server and package for PROMALS3D accessibility.

Main Methods:

  • PROMALS3D identifies homologous sequences and structures using database searches.
  • It derives structure-based constraints from 3D structure alignments.
  • It combines sequence-based and structure-based constraints within a consistency framework.

Main Results:

  • PROMALS3D generates high-quality multiple sequence alignments.
  • The output is a consensus alignment enriched with evolutionary and structural insights.
  • The tool effectively utilizes diverse biological data for alignment.

Conclusions:

  • PROMALS3D offers an enhanced approach to protein MSA construction.
  • Integration of sequence and structural data improves alignment accuracy for divergent proteins.
  • The PROMALS3D web server provides a valuable resource for researchers.