Precise parallel volumetric comparison of molecular surfaces and electrostatic isopotentials
Abstract Geometric comparisons of binding sites and their electrostatic properties can identify subtle variations that select different binding partners and subtle similarities that accommodate similar partners. Because subtle features are central for explaining how proteins achieve specificity, alg...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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BMC
2020-05-01
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| Series: | Algorithms for Molecular Biology |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13015-020-00168-z |
| _version_ | 1818289788424290304 |
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| author | Georgi D. Georgiev Kevin F. Dodd Brian Y. Chen |
| author_facet | Georgi D. Georgiev Kevin F. Dodd Brian Y. Chen |
| author_sort | Georgi D. Georgiev |
| collection | DOAJ |
| description | Abstract Geometric comparisons of binding sites and their electrostatic properties can identify subtle variations that select different binding partners and subtle similarities that accommodate similar partners. Because subtle features are central for explaining how proteins achieve specificity, algorithmic efficiency and geometric precision are central to algorithmic design. To address these concerns, this paper presents pClay, the first algorithm to perform parallel and arbitrarily precise comparisons of molecular surfaces and electrostatic isopotentials as geometric solids. pClay was presented at the 2019 Workshop on Algorithms in Bioinformatics (WABI 2019) and is described in expanded detail here, especially with regard to the comparison of electrostatic isopotentials. Earlier methods have generally used parallelism to enhance computational throughput, pClay is the first algorithm to use parallelism to make arbitrarily high precision comparisons practical. It is also the first method to demonstrate that high precision comparisons of geometric solids can yield more precise structural inferences than algorithms that use existing standards of precision. One advantage of added precision is that statistical models can be trained with more accurate data. Using structural data from an existing method, a model of steric variations between binding cavities can overlook 53% of authentic steric influences on specificity, whereas a model trained with data from pClay overlooks none. Our results also demonstrate the parallel performance of pClay on both workstation CPUs and a 61-core Xeon Phi. While slower on one core, additional processor cores rapidly outpaced single core performance and existing methods. Based on these results, it is clear that pClay has applications in the automatic explanation of binding mechanisms and in the rational design of protein binding preferences. |
| first_indexed | 2024-12-13T02:17:50Z |
| format | Article |
| id | doaj.art-19073bc1fba84f9299703f36334f8817 |
| institution | Directory Open Access Journal |
| issn | 1748-7188 |
| language | English |
| last_indexed | 2024-12-13T02:17:50Z |
| publishDate | 2020-05-01 |
| publisher | BMC |
| record_format | Article |
| series | Algorithms for Molecular Biology |
| spelling | doaj.art-19073bc1fba84f9299703f36334f88172022-12-22T00:02:51ZengBMCAlgorithms for Molecular Biology1748-71882020-05-0115112010.1186/s13015-020-00168-zPrecise parallel volumetric comparison of molecular surfaces and electrostatic isopotentialsGeorgi D. Georgiev0Kevin F. Dodd1Brian Y. Chen2Department of Computer Science and Engineering, Lehigh UniversityDepartment of Computer Science and Engineering, Lehigh UniversityDepartment of Computer Science and Engineering, Lehigh UniversityAbstract Geometric comparisons of binding sites and their electrostatic properties can identify subtle variations that select different binding partners and subtle similarities that accommodate similar partners. Because subtle features are central for explaining how proteins achieve specificity, algorithmic efficiency and geometric precision are central to algorithmic design. To address these concerns, this paper presents pClay, the first algorithm to perform parallel and arbitrarily precise comparisons of molecular surfaces and electrostatic isopotentials as geometric solids. pClay was presented at the 2019 Workshop on Algorithms in Bioinformatics (WABI 2019) and is described in expanded detail here, especially with regard to the comparison of electrostatic isopotentials. Earlier methods have generally used parallelism to enhance computational throughput, pClay is the first algorithm to use parallelism to make arbitrarily high precision comparisons practical. It is also the first method to demonstrate that high precision comparisons of geometric solids can yield more precise structural inferences than algorithms that use existing standards of precision. One advantage of added precision is that statistical models can be trained with more accurate data. Using structural data from an existing method, a model of steric variations between binding cavities can overlook 53% of authentic steric influences on specificity, whereas a model trained with data from pClay overlooks none. Our results also demonstrate the parallel performance of pClay on both workstation CPUs and a 61-core Xeon Phi. While slower on one core, additional processor cores rapidly outpaced single core performance and existing methods. Based on these results, it is clear that pClay has applications in the automatic explanation of binding mechanisms and in the rational design of protein binding preferences.http://link.springer.com/article/10.1186/s13015-020-00168-zSpecificity annotationMolecular representationsSolid modeling |
| spellingShingle | Georgi D. Georgiev Kevin F. Dodd Brian Y. Chen Precise parallel volumetric comparison of molecular surfaces and electrostatic isopotentials Algorithms for Molecular Biology Specificity annotation Molecular representations Solid modeling |
| title | Precise parallel volumetric comparison of molecular surfaces and electrostatic isopotentials |
| title_full | Precise parallel volumetric comparison of molecular surfaces and electrostatic isopotentials |
| title_fullStr | Precise parallel volumetric comparison of molecular surfaces and electrostatic isopotentials |
| title_full_unstemmed | Precise parallel volumetric comparison of molecular surfaces and electrostatic isopotentials |
| title_short | Precise parallel volumetric comparison of molecular surfaces and electrostatic isopotentials |
| title_sort | precise parallel volumetric comparison of molecular surfaces and electrostatic isopotentials |
| topic | Specificity annotation Molecular representations Solid modeling |
| url | http://link.springer.com/article/10.1186/s13015-020-00168-z |
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