Mateusz Zalewski, Valentin Iglesias, Oriol Bárcenas, Salvador Ventura, Sebastian Kmiecik
{"title":"Aggrescan4D:根据 pH 值分析和设计蛋白质聚集倾向的综合工具。","authors":"Mateusz Zalewski, Valentin Iglesias, Oriol Bárcenas, Salvador Ventura, Sebastian Kmiecik","doi":"10.1002/pro.5180","DOIUrl":null,"url":null,"abstract":"<p><p>Aggrescan4D (A4D) is an advanced computational tool designed for predicting protein aggregation, leveraging structural information and the influence of pH. Building upon its predecessor, Aggrescan3D (A3D), A4D has undergone numerous enhancements aimed at assisting the improvement of protein solubility. This manuscript reviews A4D's updated functionalities and explains the fundamental principles behind its pH-dependent calculations. Additionally, it presents an antibody case study to evaluate its performance in comparison with other structure-based predictors. Notably, A4D integrates advanced protein engineering protocols with pH-dependent calculations, enhancing its utility in advising solubility-enhancing mutations. A4D considers the impact of structural flexibility on aggregation propensities, and includes a large set of precalculated predictions. These capabilities should help to open new avenues for both understanding and managing protein aggregation. A4D is accessible through a dedicated web server at https://biocomp.chem.uw.edu.pl/a4d/.</p>","PeriodicalId":20761,"journal":{"name":"Protein Science","volume":null,"pages":null},"PeriodicalIF":4.5000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11425640/pdf/","citationCount":"0","resultStr":"{\"title\":\"Aggrescan4D: A comprehensive tool for pH-dependent analysis and engineering of protein aggregation propensity.\",\"authors\":\"Mateusz Zalewski, Valentin Iglesias, Oriol Bárcenas, Salvador Ventura, Sebastian Kmiecik\",\"doi\":\"10.1002/pro.5180\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Aggrescan4D (A4D) is an advanced computational tool designed for predicting protein aggregation, leveraging structural information and the influence of pH. Building upon its predecessor, Aggrescan3D (A3D), A4D has undergone numerous enhancements aimed at assisting the improvement of protein solubility. This manuscript reviews A4D's updated functionalities and explains the fundamental principles behind its pH-dependent calculations. Additionally, it presents an antibody case study to evaluate its performance in comparison with other structure-based predictors. Notably, A4D integrates advanced protein engineering protocols with pH-dependent calculations, enhancing its utility in advising solubility-enhancing mutations. A4D considers the impact of structural flexibility on aggregation propensities, and includes a large set of precalculated predictions. These capabilities should help to open new avenues for both understanding and managing protein aggregation. A4D is accessible through a dedicated web server at https://biocomp.chem.uw.edu.pl/a4d/.</p>\",\"PeriodicalId\":20761,\"journal\":{\"name\":\"Protein Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11425640/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Protein Science\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1002/pro.5180\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Protein Science","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1002/pro.5180","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Aggrescan4D: A comprehensive tool for pH-dependent analysis and engineering of protein aggregation propensity.
Aggrescan4D (A4D) is an advanced computational tool designed for predicting protein aggregation, leveraging structural information and the influence of pH. Building upon its predecessor, Aggrescan3D (A3D), A4D has undergone numerous enhancements aimed at assisting the improvement of protein solubility. This manuscript reviews A4D's updated functionalities and explains the fundamental principles behind its pH-dependent calculations. Additionally, it presents an antibody case study to evaluate its performance in comparison with other structure-based predictors. Notably, A4D integrates advanced protein engineering protocols with pH-dependent calculations, enhancing its utility in advising solubility-enhancing mutations. A4D considers the impact of structural flexibility on aggregation propensities, and includes a large set of precalculated predictions. These capabilities should help to open new avenues for both understanding and managing protein aggregation. A4D is accessible through a dedicated web server at https://biocomp.chem.uw.edu.pl/a4d/.
期刊介绍:
Protein Science, the flagship journal of The Protein Society, is a publication that focuses on advancing fundamental knowledge in the field of protein molecules. The journal welcomes original reports and review articles that contribute to our understanding of protein function, structure, folding, design, and evolution.
Additionally, Protein Science encourages papers that explore the applications of protein science in various areas such as therapeutics, protein-based biomaterials, bionanotechnology, synthetic biology, and bioelectronics.
The journal accepts manuscript submissions in any suitable format for review, with the requirement of converting the manuscript to journal-style format only upon acceptance for publication.
Protein Science is indexed and abstracted in numerous databases, including the Agricultural & Environmental Science Database (ProQuest), Biological Science Database (ProQuest), CAS: Chemical Abstracts Service (ACS), Embase (Elsevier), Health & Medical Collection (ProQuest), Health Research Premium Collection (ProQuest), Materials Science & Engineering Database (ProQuest), MEDLINE/PubMed (NLM), Natural Science Collection (ProQuest), and SciTech Premium Collection (ProQuest).