Alpha complexes in protein structure prediction

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Reducing the computational effort and increasing the accuracy of potential energy functions is of utmost importance in modeling biological systems, for instance in protein structure prediction, docking or design. Evaluating interactions between nonbonded atoms is the bottleneck of such computations. It is shown that local properties of a-complexes (subcomplexes of Delaunay tessellations) make it possible to identify nonbonded pairs of atoms whose contributions to the potential energy are not marginal and cannot be disregarded. Computational experiments indicate that using the local properties of a-complexes, the relative error (when compared to the potential energy contributions of all nonbonded pairs of atom) is well within 2%. Furthermore, the computational effort (assuming that a-complexes are given) is comparable to even the simplest and therefore also fastest cutoff approaches. The determination of a-complexes from scratch for every configuration encountered during the search for the native structure would make this approach hopelessly slow. However, it is argued that kinetic a-complexes can be used to reduce the computational effort of determining the potential energy when "moving" from one configuration to a neighboring one. As a consequence, relatively expensive (initial) construction of an a-complex is expected to be compensated by subsequent fast kinetic updates during the search process. Computational results presented in this paper are limited. However, they suggest that the applicability of a-complexes and kinetic a-complexes in protein related problems (e.g., protein structure prediction and protein-ligand docking) deserves furhter investigation.)
Original languageEnglish
Title of host publicationProceedings of the International Conference on Bioinformatics Models, Methods and Algorithms
Number of pages5
PublisherSCITEPRESS (Science and Technology Publications, Lda.)
Publication date2015
Pages178-182
ISBN (Electronic)978-989-758-070-3
DOIs
Publication statusPublished - 2015
EventInternational Conference on Bioinformatics Models, Methods and Algorithms, - Lisbon, Portugal
Duration: 12 Jan 201515 Jan 2015

Conference

ConferenceInternational Conference on Bioinformatics Models, Methods and Algorithms,
LandPortugal
ByLisbon
Periode12/01/201515/01/2015

    Research areas

  • Faculty of Science - Protein Structure Prediction, Force Field, Alpha-complexes, Kinetic Data Structures

ID: 131661236