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Structural and Functional Analysis of Amino Acids and Proteins

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".

Deadline for manuscript submissions: 20 January 2025 | Viewed by 1525

Special Issue Editors

School of Computer Science & Technology, Soochow University, Suzhou 215000, China
Interests: bioinformatics; machine learning; deep learning; text mining

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Guest Editor
1. Suzhou Medical College of Soochow University, Suzhou, China
2. Center for Systems Biology, Soochow University, Suzhou, China
Interests: bioinformatics; systems biology; biomedical informatics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are excited to announce a new Special Issue, entitled "Structural and Functional Analysis of Amino Acids and Proteins". As fundamental knowledge in the field of life sciences, understanding protein structure and function is important for both biology and medicine. Amino acids are the building blocks of proteins, and understanding their structure and function is essential for unraveling various biochemical processes within organisms.

In recent decades, several methods have been developed for predicting proteins’ structure and function, employing sequence-to-function, a sequence-to-structure-to-function or network paradigms. The aim of this Special Issue is to highlight the recent advances in various analysis and prediction methods and their applications in biomedical field.

We are soliciting contributions (comprehensive reviews on general areas, mini reviews on specialized subjects, research work, short communications, technical notes) covering a broad range of topics on the structural and functional analysis of amino acids and proteins and their application, including (though not limited to) the following:

  • Protein structure and functions prediction;
  • Protein–protein interaction analysis or prediction;
  • Amino acids network construction and analysis;
  • Drug target discovery;
  • Biomarker discovery.

We hope that this Special Issue will provide researchers with a comprehensive understanding of the structural and functional analysis of amino acids and proteins. Whether you are a biological researcher, medical professional, or simply someone interested in life sciences, we believe this Special Issue will offer new knowledge and inspiration.

We look forward to receiving your contributions. 

Dr. Yang Yang
Dr. Wenying Yan
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • protein structure
  • protein function
  • amino acids network
  • deep learning
  • bioinformatics
  • protein–protein interaction
  • drug discovery
  • biomarker

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Published Papers (2 papers)

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Research

14 pages, 1758 KiB  
Article
PON-Tm: A Sequence-Based Method for Prediction of Missense Mutation Effects on Protein Thermal Stability Changes
by Jiahao Kuang, Zhihong Zhao, Yang Yang and Wenying Yan
Int. J. Mol. Sci. 2024, 25(15), 8379; https://doi.org/10.3390/ijms25158379 - 31 Jul 2024
Viewed by 346
Abstract
Proteins, as crucial macromolecules performing diverse biological roles, are central to numerous biological processes. The ability to predict changes in protein thermal stability due to mutations is vital for both biomedical research and industrial applications. However, existing experimental methods are often costly and [...] Read more.
Proteins, as crucial macromolecules performing diverse biological roles, are central to numerous biological processes. The ability to predict changes in protein thermal stability due to mutations is vital for both biomedical research and industrial applications. However, existing experimental methods are often costly and labor-intensive, while structure-based prediction methods demand significant computational resources. In this study, we introduce PON-Tm, a novel sequence-based method for predicting mutation-induced thermal stability variations in proteins. PON-Tm not only incorporates features predicted by a protein language model from protein sequences but also considers environmental factors such as pH and the thermostability of the wild-type protein. To evaluate the effectiveness of PON-Tm, we compared its performance to four well-established methods, and PON-Tm exhibited superior predictive capabilities. Furthermore, to facilitate easy access and utilization, we have developed a web server. Full article
(This article belongs to the Special Issue Structural and Functional Analysis of Amino Acids and Proteins)
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12 pages, 5199 KiB  
Article
EGG: Accuracy Estimation of Individual Multimeric Protein Models Using Deep Energy-Based Models and Graph Neural Networks
by Andrew Jordan Siciliano, Chenguang Zhao, Tong Liu and Zheng Wang
Int. J. Mol. Sci. 2024, 25(11), 6250; https://doi.org/10.3390/ijms25116250 - 6 Jun 2024
Viewed by 688
Abstract
Reliable and accurate methods of estimating the accuracy of predicted protein models are vital to understanding their respective utility. Discerning how the quaternary structure conforms can significantly improve our collective understanding of cell biology, systems biology, disease formation, and disease treatment. Accurately determining [...] Read more.
Reliable and accurate methods of estimating the accuracy of predicted protein models are vital to understanding their respective utility. Discerning how the quaternary structure conforms can significantly improve our collective understanding of cell biology, systems biology, disease formation, and disease treatment. Accurately determining the quality of multimeric protein models is still computationally challenging, as the space of possible conformations is significantly larger when proteins form in complex with one another. Here, we present EGG (energy and graph-based architectures) to assess the accuracy of predicted multimeric protein models. We implemented message-passing and transformer layers to infer the overall fold and interface accuracy scores of predicted multimeric protein models. When evaluated with CASP15 targets, our methods achieved promising results against single model predictors: fourth and third place for determining the highest-quality model when estimating overall fold accuracy and overall interface accuracy, respectively, and first place for determining the top three highest quality models when estimating both overall fold accuracy and overall interface accuracy. Full article
(This article belongs to the Special Issue Structural and Functional Analysis of Amino Acids and Proteins)
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