Parth Rathee, Sreerag N Moorkkannur, Rajeev Prabhakar
{"title":"Structural studies of catalytic peptides using molecular dynamics simulations.","authors":"Parth Rathee, Sreerag N Moorkkannur, Rajeev Prabhakar","doi":"10.1016/bs.mie.2024.01.019","DOIUrl":null,"url":null,"abstract":"<p><p>Many self-assembling peptides can form amyloid like structures with different sizes and morphologies. Driven by non-covalent interactions, their aggregation can occur through distinct pathways. Additionally, they can bind metal ions to create enzyme like active sites that allow them to catalyze diverse reactions. Due to the non-crystalline nature of amyloids, it is quite challenging to elucidate their structures using experimental spectroscopic techniques. In this aspect, molecular dynamics (MD) simulations provide a useful tool to derive structures of these macromolecules in solution. They can be further validated by comparing with experimentally measured structural parameters. However, these simulations require a multi-step process starting from the selection of the initial structure to the analysis of MD trajectories. There are multiple force fields, parametrization protocols, equilibration processes, software and analysis tools available for this process. Therefore, it is complicated for non-experts to select the most relevant tools and perform these simulations effectively. In this chapter, a systematic methodology that covers all major aspects of modeling of catalytic peptides is provided in a user-friendly manner. It will be helpful for researchers in this critical area of research.</p>","PeriodicalId":18662,"journal":{"name":"Methods in enzymology","volume":"697 ","pages":"151-180"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Methods in enzymology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/bs.mie.2024.01.019","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/2/6 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 0
Abstract
Many self-assembling peptides can form amyloid like structures with different sizes and morphologies. Driven by non-covalent interactions, their aggregation can occur through distinct pathways. Additionally, they can bind metal ions to create enzyme like active sites that allow them to catalyze diverse reactions. Due to the non-crystalline nature of amyloids, it is quite challenging to elucidate their structures using experimental spectroscopic techniques. In this aspect, molecular dynamics (MD) simulations provide a useful tool to derive structures of these macromolecules in solution. They can be further validated by comparing with experimentally measured structural parameters. However, these simulations require a multi-step process starting from the selection of the initial structure to the analysis of MD trajectories. There are multiple force fields, parametrization protocols, equilibration processes, software and analysis tools available for this process. Therefore, it is complicated for non-experts to select the most relevant tools and perform these simulations effectively. In this chapter, a systematic methodology that covers all major aspects of modeling of catalytic peptides is provided in a user-friendly manner. It will be helpful for researchers in this critical area of research.
期刊介绍:
The critically acclaimed laboratory standard for almost 50 years, Methods in Enzymology is one of the most highly respected publications in the field of biochemistry. Each volume is eagerly awaited, frequently consulted, and praised by researchers and reviewers alike. Now with over 500 volumes the series contains much material still relevant today and is truly an essential publication for researchers in all fields of life sciences, including microbiology, biochemistry, cancer research and genetics-just to name a few. Five of the 2013 Nobel Laureates have edited or contributed to volumes of MIE.