Laura Pedraza-González, Leonardo Barneschi, Daniele Padula, Luca De Vico, Massimo Olivucci
{"title":"Evolution of the Automatic Rhodopsin Modeling (ARM) Protocol","authors":"Laura Pedraza-González, Leonardo Barneschi, Daniele Padula, Luca De Vico, Massimo Olivucci","doi":"10.1007/s41061-022-00374-w","DOIUrl":null,"url":null,"abstract":"<div><p>In recent years, photoactive proteins such as rhodopsins have become a common target for cutting-edge research in the field of optogenetics. Alongside wet-lab research, computational methods are also developing rapidly to provide the necessary tools to analyze and rationalize experimental results and, most of all, drive the design of novel systems. The Automatic Rhodopsin Modeling (<b>ARM</b>) protocol is focused on providing exactly the necessary computational tools to study rhodopsins, those being either natural or resulting from mutations. The code has evolved along the years to finally provide results that are <b>reproducible</b> by any user, <b>accurate</b> and <b>reliable</b> so as to replicate experimental trends. Furthermore, the code is <b>efficient</b> in terms of necessary computing resources and time, and <b>scalable</b> in terms of both number of concurrent calculations as well as features. In this review, we will show how the code underlying ARM achieved each of these properties.</p></div>","PeriodicalId":54344,"journal":{"name":"Topics in Current Chemistry","volume":"380 3","pages":""},"PeriodicalIF":7.1000,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s41061-022-00374-w.pdf","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Topics in Current Chemistry","FirstCategoryId":"92","ListUrlMain":"https://link.springer.com/article/10.1007/s41061-022-00374-w","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 6
Abstract
In recent years, photoactive proteins such as rhodopsins have become a common target for cutting-edge research in the field of optogenetics. Alongside wet-lab research, computational methods are also developing rapidly to provide the necessary tools to analyze and rationalize experimental results and, most of all, drive the design of novel systems. The Automatic Rhodopsin Modeling (ARM) protocol is focused on providing exactly the necessary computational tools to study rhodopsins, those being either natural or resulting from mutations. The code has evolved along the years to finally provide results that are reproducible by any user, accurate and reliable so as to replicate experimental trends. Furthermore, the code is efficient in terms of necessary computing resources and time, and scalable in terms of both number of concurrent calculations as well as features. In this review, we will show how the code underlying ARM achieved each of these properties.
期刊介绍:
Topics in Current Chemistry is a journal that presents critical reviews of present and future trends in modern chemical research. It covers all areas of chemical science, including interactions with related disciplines like biology, medicine, physics, and materials science. The articles in this journal are organized into thematic collections, offering a comprehensive perspective on emerging research to non-specialist readers in academia or industry. Each review article focuses on one aspect of the topic and provides a critical survey, placing it in the context of the collection. Selected examples highlight significant developments from the past 5 to 10 years. Instead of providing an exhaustive summary or extensive data, the articles concentrate on methodological thinking. This approach allows non-specialist readers to understand the information fully and presents the potential prospects for future developments.