The paper describes a novel framework, constructed using Constraint Logic Programming (CLP) and parallelism, to determine the association between parts of the primary sequence of a protein and α-helices extracted from 3D low-resolution descriptions of large protein complexes. The association is determined by extracting constraints from the 3D information, regarding length, relative position and connectivity of helices, and solving these constraints with the guidance of a secondary structure prediction algorithm. Parallelism is employed to enhance performance on large proteins. The framework provides a fast, inexpensive alternative to determine the exact tertiary structure of unknown proteins.

A Constraint Logic Programming approach to associate 1D and 3D structural components for large protein complexes / DAL PALU', Alessandro; J., He; E., Pontelli; Y., Lu. - In: INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS. - ISSN 1748-5673. - 1:4(2007), pp. 352-371. [10.1504/IJDMB.2007.012965]

A Constraint Logic Programming approach to associate 1D and 3D structural components for large protein complexes

DAL PALU', Alessandro;
2007-01-01

Abstract

The paper describes a novel framework, constructed using Constraint Logic Programming (CLP) and parallelism, to determine the association between parts of the primary sequence of a protein and α-helices extracted from 3D low-resolution descriptions of large protein complexes. The association is determined by extracting constraints from the 3D information, regarding length, relative position and connectivity of helices, and solving these constraints with the guidance of a secondary structure prediction algorithm. Parallelism is employed to enhance performance on large proteins. The framework provides a fast, inexpensive alternative to determine the exact tertiary structure of unknown proteins.
2007
A Constraint Logic Programming approach to associate 1D and 3D structural components for large protein complexes / DAL PALU', Alessandro; J., He; E., Pontelli; Y., Lu. - In: INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS. - ISSN 1748-5673. - 1:4(2007), pp. 352-371. [10.1504/IJDMB.2007.012965]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/1642735
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