Jesse W Sandberg, Ezry Santiago-McRae, Jahmal Ennis, Grace Brannigan
{"title":"The density-threshold affinity: Calculating lipid binding affinities from unbiased coarse-grained molecular dynamics simulations.","authors":"Jesse W Sandberg, Ezry Santiago-McRae, Jahmal Ennis, Grace Brannigan","doi":"10.1016/bs.mie.2024.03.008","DOIUrl":null,"url":null,"abstract":"<p><p>Many membrane proteins are sensitive to their local lipid environment. As structural methods for membrane proteins have improved, there is growing evidence of direct, specific binding of lipids to protein surfaces. Unfortunately the workhorse of understanding protein-small molecule interactions, the binding affinity for a given site, is experimentally inaccessible for these systems. Coarse-grained molecular dynamics simulations can be used to bridge this gap, and are relatively straightforward to learn. Such simulations allow users to observe spontaneous binding of lipids to membrane proteins and quantify localized densities of individual lipids or lipid fragments. In this chapter we outline a protocol for extracting binding affinities from these localized distributions, known as the \"density threshold affinity.\" The density threshold affinity uses an adaptive and flexible definition of site occupancy that alleviates the need to distinguish between \"bound'' lipids and bulk lipids that are simply diffusing through the site. Furthermore, the method allows \"bead-level\" resolution that is suitable for the case where lipids share binding sites, and circumvents ambiguities about a relevant reference state. This approach provides a convenient and straightforward method for comparing affinities of a single lipid species for multiple sites, multiple lipids for a single site, and/or a single lipid species modeled using multiple forcefields.</p>","PeriodicalId":18662,"journal":{"name":"Methods in enzymology","volume":"701 ","pages":"47-82"},"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.2024.03.008","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/4/4 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 0
Abstract
Many membrane proteins are sensitive to their local lipid environment. As structural methods for membrane proteins have improved, there is growing evidence of direct, specific binding of lipids to protein surfaces. Unfortunately the workhorse of understanding protein-small molecule interactions, the binding affinity for a given site, is experimentally inaccessible for these systems. Coarse-grained molecular dynamics simulations can be used to bridge this gap, and are relatively straightforward to learn. Such simulations allow users to observe spontaneous binding of lipids to membrane proteins and quantify localized densities of individual lipids or lipid fragments. In this chapter we outline a protocol for extracting binding affinities from these localized distributions, known as the "density threshold affinity." The density threshold affinity uses an adaptive and flexible definition of site occupancy that alleviates the need to distinguish between "bound'' lipids and bulk lipids that are simply diffusing through the site. Furthermore, the method allows "bead-level" resolution that is suitable for the case where lipids share binding sites, and circumvents ambiguities about a relevant reference state. This approach provides a convenient and straightforward method for comparing affinities of a single lipid species for multiple sites, multiple lipids for a single site, and/or a single lipid species modeled using multiple forcefields.
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.