用OpenMP快速计算高分辨率溶剂排除蛋白表面

Sebastian Daberdaku, Carlo Ferrari
{"title":"用OpenMP快速计算高分辨率溶剂排除蛋白表面","authors":"Sebastian Daberdaku, Carlo Ferrari","doi":"10.1109/HPCS.2018.00127","DOIUrl":null,"url":null,"abstract":"The solvent-excluded surface of proteins is extremely useful when studying their properties and interactions as it represents the portion of the outer protein contour that is available to interact with the solvent and other molecules. Given their simplicity and ability to represent geometrical and physico- chemical properties of proteins, voxelised surface representations have received a lot of interest in bioinformatics and computational biology applications such as protein-protein docking, interaction interface prediction and ligand-binding pocket prediction. Computing voxelised surfaces for large proteins can be challenging, as space-demanding data structures with associated high computational costs are required. In this paper we present a fast, OpenMP-based parallel algorithm for the computation of high-resolution voxelised solvent-excluded protein surfaces. The methodology is based on a region-growing implementation of the approximate Euclidean Distance Transform algorithm with Hierarchical Queues. The geometrical relationship between the solvent-accessible and solvent-excluded surfaces allows us to obtain the latter very efficiently by computing distance map values only for a small subset of the overall voxels representing the protein. The algorithm computes the contribution to the overall outer surface for each atom in parallel. The proposed methodology was experimentally compared to two previous MPI- based parallel implementations showing overall better speedup and efficiency metrics as well as lower surface computation times.","PeriodicalId":308138,"journal":{"name":"2018 International Conference on High Performance Computing & Simulation (HPCS)","volume":"191 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Fast Computation of High-resolution Solvent Excluded Protein Surface with OpenMP\",\"authors\":\"Sebastian Daberdaku, Carlo Ferrari\",\"doi\":\"10.1109/HPCS.2018.00127\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The solvent-excluded surface of proteins is extremely useful when studying their properties and interactions as it represents the portion of the outer protein contour that is available to interact with the solvent and other molecules. Given their simplicity and ability to represent geometrical and physico- chemical properties of proteins, voxelised surface representations have received a lot of interest in bioinformatics and computational biology applications such as protein-protein docking, interaction interface prediction and ligand-binding pocket prediction. Computing voxelised surfaces for large proteins can be challenging, as space-demanding data structures with associated high computational costs are required. In this paper we present a fast, OpenMP-based parallel algorithm for the computation of high-resolution voxelised solvent-excluded protein surfaces. The methodology is based on a region-growing implementation of the approximate Euclidean Distance Transform algorithm with Hierarchical Queues. The geometrical relationship between the solvent-accessible and solvent-excluded surfaces allows us to obtain the latter very efficiently by computing distance map values only for a small subset of the overall voxels representing the protein. The algorithm computes the contribution to the overall outer surface for each atom in parallel. The proposed methodology was experimentally compared to two previous MPI- based parallel implementations showing overall better speedup and efficiency metrics as well as lower surface computation times.\",\"PeriodicalId\":308138,\"journal\":{\"name\":\"2018 International Conference on High Performance Computing & Simulation (HPCS)\",\"volume\":\"191 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on High Performance Computing & Simulation (HPCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPCS.2018.00127\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on High Performance Computing & Simulation (HPCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCS.2018.00127","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

在研究蛋白质的性质和相互作用时,不溶于溶剂的蛋白质表面是非常有用的,因为它代表了蛋白质外部轮廓的一部分,可以与溶剂和其他分子相互作用。由于其简单性和表示蛋白质几何和物理化学性质的能力,体素化表面表示在生物信息学和计算生物学应用中受到了很多关注,如蛋白质-蛋白质对接、相互作用界面预测和配体结合口袋预测。计算大型蛋白质的体素化表面可能具有挑战性,因为需要空间要求高的数据结构和相关的高计算成本。在本文中,我们提出了一个快速的,基于openmp的并行算法,用于计算高分辨率体素溶剂排除蛋白表面。该方法是基于区域增长的近似欧几里得距离变换算法的分层队列实现。溶剂可及表面和溶剂不可及表面之间的几何关系使我们能够通过仅计算代表蛋白质的一小部分整体体素的距离图值来非常有效地获得后者。该算法并行计算每个原子对整个外表面的贡献。实验结果表明,该方法与之前两种基于MPI的并行实现相比,总体上具有更好的加速和效率指标,并且表面计算时间更短。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast Computation of High-resolution Solvent Excluded Protein Surface with OpenMP
The solvent-excluded surface of proteins is extremely useful when studying their properties and interactions as it represents the portion of the outer protein contour that is available to interact with the solvent and other molecules. Given their simplicity and ability to represent geometrical and physico- chemical properties of proteins, voxelised surface representations have received a lot of interest in bioinformatics and computational biology applications such as protein-protein docking, interaction interface prediction and ligand-binding pocket prediction. Computing voxelised surfaces for large proteins can be challenging, as space-demanding data structures with associated high computational costs are required. In this paper we present a fast, OpenMP-based parallel algorithm for the computation of high-resolution voxelised solvent-excluded protein surfaces. The methodology is based on a region-growing implementation of the approximate Euclidean Distance Transform algorithm with Hierarchical Queues. The geometrical relationship between the solvent-accessible and solvent-excluded surfaces allows us to obtain the latter very efficiently by computing distance map values only for a small subset of the overall voxels representing the protein. The algorithm computes the contribution to the overall outer surface for each atom in parallel. The proposed methodology was experimentally compared to two previous MPI- based parallel implementations showing overall better speedup and efficiency metrics as well as lower surface computation times.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信