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Protein Organization

Protein Organization

Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence.

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Updated: May 20, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Engineering protein therapeutics: predictive performances of a structure-based virtual affinity maturation protocol.

Michael Oberlin¹, Romano Kroemer, Vincent Mikol

¹SANOFI R&D, Centre de Recherche de Vitry/Alfortville, LGCR/SDI, 13 quai Jules Guesde-BP 14-94403 Vitry-sur-Seine Cedex, France.

Journal of Chemical Information and Modeling

|July 14, 2012

Summary

A new computational method enhances protein binding affinity by predicting beneficial mutations. This virtual affinity maturation protocol successfully identifies mutations that improve binding, with higher success rates for non-natural mutations.

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A Protocol for Computer-Based Protein Structure and Function Prediction

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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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Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Area of Science:

Computational biology
Structural biology
Biochemistry

Background:

Protein engineering relies on understanding mutation effects on binding affinity.
Virtual affinity maturation offers a computational approach to guide experimental design.

Purpose of the Study:

To implement and evaluate a structure-based virtual affinity maturation protocol.
To assess the protocol's predictive accuracy for point mutations affecting protein binding.

Main Methods:

Conformational sampling of interface residues using Dead End Elimination/A* algorithm.
Estimating binding free energy changes (ΔΔG) using MM/PBSA calculations.
Evaluating protocol performance on 173 mutations across 7 protein complexes.

Main Results:

A combined predictor (ΔΔG(*) and ΔΔE(pol*)) identified mutations, with a 45% success rate in enhancing binding.
Focusing on non-natural mutations (≥2 base changes) increased the success rate to 63%.
The protocol detected 89% of hot-spots in alanine scanning mutagenesis studies.

Conclusions:

The structure-based virtual affinity maturation protocol is a valuable tool for protein engineering.
The protocol demonstrates significant predictive power for identifying mutations that enhance binding affinity.
The method shows promise for accelerating the design of proteins with improved functional properties.