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Updated: Dec 13, 2025

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

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Recent advances in user-friendly computational tools to engineer protein function.

Carlos Eduardo Sequeiros-Borja1, Bartłomiej Surpeta1, Jan Brezovsky2

  • 1Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University and the International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland.

Briefings in Bioinformatics
|August 4, 2020
PubMed
Summary
This summary is machine-generated.

Recent advancements in computational tools aid protein design and engineering. This review evaluates new software for semi-rational and rational protein engineering, focusing on mutation analysis and protein dynamics.

Keywords:
computational protein engineeringhotspot predictionmutational analysisrational engineeringsemi-rational engineering

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Area of Science:

  • Biotechnology
  • Computational Biology
  • Protein Engineering

Background:

  • Technological progress has significantly advanced protein design and engineering.
  • Computational methods are integral to tailoring proteins for biotechnological uses.
  • New software tools are continuously developed to meet protein engineering demands.

Purpose of the Study:

  • To critically evaluate recent computational tools for semi-rational and rational protein engineering.
  • To guide protein engineers and bioinformaticians in selecting appropriate software.
  • To assess the utility of new tools for analyzing protein properties and dynamics.

Main Methods:

  • Review and evaluation of recently developed computational software.
  • Analysis of tools for identifying mutation hotspots and predicting effects on protein properties.
  • Discussion of tools targeting protein dynamics, ligand binding, and interactions.

Main Results:

  • Newly developed tools can identify hotspots and analyze mutation effects on ligand binding, interactions, and electrostatic potential.
  • Progress has been made in targeting protein dynamics, ligand transport, and allosteric communication.
  • The evaluated tools offer capabilities for various aspects of protein engineering.

Conclusions:

  • Computational tools are essential for modern protein engineering.
  • Further development is needed to address challenges and enhance the applicability of these tools.
  • These tools assist in guiding protein engineering efforts for biotechnological applications.