Bioinformatics tools in protein analysis: Structure prediction, interaction modelling, and function relationship

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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Publication Details

Journal
European Journal of Sustainable Development Research
Published
2025-05-05
DOI
https://doi.org/10.29333/ejosdr/16340
Citations
4
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
3.22
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article

Bioinformatics tools in protein analysis: Structure prediction, interaction modelling, and function relationship

Adaobi Mary-Ann Okafor, Taiwo Temitope Ogunjobi, Dorcas Oyedolapo Atanda, Otoh Dayo Umoren et al.
4 citations
European Journal of Sustainable Development Research
Bioinformatics and Genomic Networks
3.22
article

Bioinformatics tools in protein analysis: Structure prediction, interaction modelling, and function relationship

Adaobi Mary-Ann Okafor, Taiwo Temitope Ogunjobi, Dorcas Oyedolapo Atanda, Otoh Dayo Umoren, Emmanuel Oluwadamilare Ojo, Okunbi Favour Onasokhare, Chimaobi Divine Gigam-Ozuzu, Adoyi Daniel Adidu, Ijeoma Chineme Okorie, Jumoke Victoria Olorunleke, Felix Iyanu Ogunleye, Emmanuella Osaruese Irimoren, Chinyere Eucharia Agbo
article en
4 citations

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.

European Journal of Sustainable Development ResearchVol. 9(3)
University of Port Harcourt (NG), University of Nigeria (NG), Lagos State University (NG), Federal University of Technology (NG), University of Ibadan (NG), Kaduna State University (NG), Mountain Top University (NG), Ladoke Akintola University of Technology (NG), Obafemi Awolowo University (NG), National Open University of Nigeria (NG)
Openalex Percentile: Top 8%
Bioinformatics and Genomic Networks
3.22
DOIOpen Access PDFOpenAlex
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