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Conformational Search for the Building Block of Proteins Based on the Gradient Gravitational Search Algorithm
Rojalin Pradhan1, Sibarama Panigrahi1,2, Prabhat K Sahu1
1Computational Modeling Research Laboratory, School of Chemistry (Autonomous), Sambalpur University, Jyoti Vihar, Burla768019, India.
Journal of Chemical Information and Modeling
|January 10, 2023
Summary
This study introduces ConfGGS, a novel conformational search technique for amino acids and protein fragments. ConfGGS demonstrates high accuracy and efficiency compared to other algorithms, aiding in protein structure prediction.
Area of Science:
- Computational chemistry
- Structural biology
- Bioinformatics
Background:
- Proteins, essential biological molecules, derive their function from diverse 3D structures.
- Amino acid conformations are fundamental to protein folding and function.
- Accurate protein structure prediction is crucial for understanding biological processes.
Purpose of the Study:
- To develop and evaluate a new conformational search algorithm, ConfGGS, for amino acids and protein fragments.
- To compare the efficiency and accuracy of ConfGGS against existing optimization algorithms.
- To assess the utility of ConfGGS in predicting protein structures, including disordered and disulfide-bonded fragments.
Main Methods:
- Conformational search of 20 amino acids using CHARMM, AMBER, and OPLS-AA force fields with the ConfGGS algorithm.
- Comparison of ConfGGS with DE/Best, DE/Rand, and PSO algorithms based on computational time and accuracy metrics (MAE, MSD).
- Application of ConfGGS to predict structures of specific protein fragments (HIV-1 protease, α-synuclein segments, disulfide-bonded fragment) and comparison with experimental data and AlphaFold.
Main Results:
- ConfGGS demonstrated efficiency and accuracy in conformational searches of amino acids.
- The ConfGGS technique, particularly with the CHARMM force field, achieved good agreement with experimental structures for protein fragments.
- Validation using MolProbity confirmed the accuracy of ConfGGS-predicted structures, showing better agreement than AlphaFold in some cases.
Conclusions:
- ConfGGS is an effective and accurate method for conformational searching of amino acids and protein fragments.
- The algorithm shows promise for improving protein structure prediction, especially for challenging sequences.
- Further development and application of ConfGGS could advance structural biology and drug discovery.
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