Abstract
AbstractIn 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.
Funder
National Science Foundation
National Institutes of Health
Ministero dell’Istruzione, dell’Università e della Ricerca
Open access funding provided by Università degli Studi di Siena within the CRUI-CARE Agreement
Publisher
Springer Science and Business Media LLC
Cited by
9 articles.
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