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International Journal of Zoology and Applied Biosciences Research Article

Biochemical estimation of amino acids and computational modeling of protein structure

Vijai Krishna V, Sibi S, Sathish R, Florence A and Chandra Lekha SB

Year : 2025 | Pages: 141-145

doi: https://doi.org/10.55126/ijzab.2025.v10.i06.SP032

Received on: 18/09/2025

Revised on: 21/10/2025

Accepted on: 27/10/2025

Published on: 15/11/2025

  • Vijai Krishna V, Sibi S, Sathish R, Florence A and Chandra Lekha SB( 2025).

    Biochemical estimation of amino acids and computational modeling of protein structure

    . International Journal of Zoology and Applied Biosciences, 10( 6), 141-145.

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Abstract

The accurate estimation of amino acids and the subsequent modeling of protein structures are essential for understanding protein functionality and biochemical interactions. This study integrates wet-lab quantification of amino acids with computational protein structure prediction to establish a workflow that bridges biochemical characterization with in silico modeling. Amino acid estimation was conducted using ninhydrin-based colorimetry and high-performance liquid chromatography (HPLC), while the physicochemical properties of the derived amino acid composition were analyzed using ExPASy ProtParam. Protein tertiary structure modeling was performed using AlphaFold2 and SWISS-MODEL, followed by structural validation using PROCHECK and ProSA-web. The integrated approach revealed consistency between biochemical composition and predicted structural features, demonstrating its applicability for functional annotation and molecular docking studies. This combined analytical-modeling pipeline provides a robust approach for advancing protein characterization, drug-target identification, and biomolecular research.

Keywords

Amino acid estimation, Biochemical analysis, Protein quantification, Spectrophotometric, ProSA-web.

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    © The Author(s) 2025. This article is published by International Journal of Zoology and Applied Biosciences under the terms of the Creative Commons Attribution 4.0 International License (creativecommons.org), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.