Faculty Publications

Document Type

Article

Keywords

Protein structure, Structure modeling, Structure prediction, Model quality

Journal/Book/Conference Title Title

Algorithms for Molecular Biology

Volume

10

Issue

27

Abstract

Background

Progress in the field of protein three-dimensional structure prediction depends on the development of new and improved algorithms for measuring the quality of protein models. Perhaps the best descriptor of the quality of a protein model is the GDT function that maps each distance cutoff θ to the number of atoms in the protein model that can be fit under the distance θ from the corresponding atoms in the experimentally determined structure. It has long been known that the area under the graph of this function (GDT_A) can serve as a reliable, single numerical measure of the model quality. Unfortunately, while the well-known GDT_TS metric provides a crude approximation of GDT_A, no algorithm currently exists that is capable of computing accurate estimates of GDT_A.

Methods

We prove that GDT_A is well defined and that it can be approximated by the Riemann sums, using available methods for computing accurate (near-optimal) GDT function values.

Results

In contrast to the GDT_TS metric, GDT_A is neither insensitive to large nor oversensitive to small changes in model’s coordinates. Moreover, the problem of computing GDT_A is tractable. More specifically, GDT_A can be computed in cubic asymptotic time in the size of the protein model.

Conclusions

This paper presents the first algorithm capable of computing the near-optimal estimates of the area under the GDT function for a protein model. We believe that the techniques implemented in our algorithm will pave ways for the development of more practical and reliable procedures for estimating 3D model quality.

Department

Department of Computer Science

Comments

First published in Algorithms for Molecular Biology, v.10, n. 27 (2015), published by BMC. DOI: https://doi.org/10.1186/s13015-015-0058-0

Original Publication Date

10-2015

DOI of published version

10.1186/s13015-015-0058-0

Repository

UNI ScholarWorks, University of Northern Iowa, Rod Library

Date Digital

2015

Copyright

©2015 Alexsandar Poleksic. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Language

EN

File Format

application/pdf

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