Bioinformatics tools in protein analysis: Structure prediction, interaction modelling, and function relationship
Taiwo Temitope Ogunjobi 1 * , Ijeoma Chineme Okorie 2 , Chimaobi Divine Gigam-Ozuzu 3 , Jumoke Victoria Olorunleke 4 , Felix Iyanu Ogunleye 5 , Emmanuella Osaruese Irimoren 6 , Dorcas Oyedolapo Atanda 7 , Adaobi Mary-Ann Okafor 8 , Chinyere Eucharia Agbo 8 , Favour Onasokhare Okunbi 9 , Otoh Dayo Umoren 10 , Adoyi Daniel Adidu 11 , Emmanuel Oluwadamilare Ojo 12
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1 Department of Biochemistry, Faculty of Basic Medical Sciences, Ladoke Akintola University of Technology, Ogbomosho, Oyo State, NIGERIA2 Dapartment of Mathematics Sciences, Faculty of Science, NDA, Kaduna, Kaduna State, NIGERIA3 Department of Plant Science and Biotechnology, School of Natural and Applied, Science, University of Port Harcourt, Choba, Rivers State, NIGERIA4 Department of Pharmaceutical Microbiology, College of Pharmacy, Obafemi Awolowo University, Ile-Ife, Osun State, NIGERIA5 Department of Biomedical Technology, School of Basic Medical Science, Federal University of Technology Akure, Akure, Ondo State, NIGERIA6 Department of Anatomy, Faculty of Basic Medical Sciences, University of Benin, Benin City, Edo State, NIGERIA7 Department of Biochemistry, Faculty of Sciences, Lagos State University, Ojo, Lagos State, NIGERIA8 Department of Nutrition and Dietetics, Faculty of Agriculture, University of Nigeria Nsukka, Nsukka, Enugu State, NIGERIA9 Department of Microbiology, Faculty of Biological Sciences, Mountain Top University, Pakuro, Ogun State, NIGERIA10 Department of Biological Sciences, Faculty of Science, National Open University of Nigeria, Abuja, NIGERIA11 Department of Pharmacology and Therapeutics, Faculty of Basic Medical Sciences, University of Ibadan, Ibadan, NIGERIA12 Department of Biochemistry, Faculty of Sciences, Obafemi Awolowo University, Ile-Ife, Osun State, NIGERIA* Corresponding Author

Abstract

Protein analysis has been completely transformed by the swift growth of bioinformatics, which has improved protein structure prediction, simulated interactions, and clarified functional interactions. To improve our knowledge of proteomics, this review carefully examines the application of diverse bioinformatics methods in protein analysis. We evaluate computational methods such as molecular dynamics simulations and machine learning algorithms critically, with an emphasis on their applicability to modeling protein-protein interactions and protein tertiary structure prediction. Our findings show that these methods are useful for predicting protein functions and interactions, which are important for drug discovery and development. We also talk about the important implications of these developments for our knowledge of complex biological systems and disease mechanisms at the molecular level. This review also provides insights into the existing and future potential of bioinformatics tools, emphasizing their vital role in revolutionizing protein analysis. We additionally offer future strategies to improve our knowledge and management of complex disorders, particularly highlighting the need for integrated, multi-scale approaches and additional research on underrepresented proteins.

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Review Article

EUR J SUSTAIN DEV RES, Volume 9, Issue 3, 2025, Article No: em0298

https://doi.org/10.29333/ejosdr/16340

Publication date: 01 Jul 2025

Online publication date: 05 May 2025

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Article Downloads: 35

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