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ModFlex: Towards Function Focused Protein Modeling.

Mayya Sedova1, Lukasz Jaroszewski1, Mallika Iyer2

  • 1University of California Riverside School of Medicine, Biosciences Division, Riverside, CA, United States.

Journal of Molecular Biology
|May 11, 2021
PubMed
Summary
This summary is machine-generated.

The ModFlex server helps bridge the gap between protein sequences and structures. It aids researchers in selecting optimal templates for homology modeling, accounting for protein flexibility and conformational diversity.

Keywords:
functional substateshomology-based modelingstructural flexibilitystructure modelingstructure prediction

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Area of Science:

  • Structural biology
  • Bioinformatics

Background:

  • A significant gap exists between experimentally determined protein structures and those known only by amino acid sequence.
  • Homology modeling, using known protein structures as templates, is crucial for predicting structures of uncharacterized proteins.

Purpose of the Study:

  • To address limitations in standard homology modeling by providing tools for optimal template selection.
  • To facilitate the exploration of protein structural diversity and flexibility during modeling.

Main Methods:

  • Development of the ModFlex server for homology modeling.
  • Integration of tools for selecting relevant templates, considering conformational diversity and functional relevance.
  • Utilizing multiple coordinate sets and homologous proteins as templates.

Main Results:

  • ModFlex offers enhanced template selection options beyond standard homology modeling.
  • The server allows users to explore structural diversity and flexibility within available template structures.
  • Facilitates more informative protein structure predictions by considering functional context.

Conclusions:

  • The ModFlex server provides a valuable resource for improving homology modeling accuracy.
  • Addressing protein conformational flexibility is key to closing the sequence-structure gap.
  • ModFlex aids researchers in leveraging structural diversity for better protein structure prediction.