An algorithm to enumerate all possible protein conformations verifying a set of distance constraints.
Bottom Line:
Whereas the most common method currently employed is simulated annealing, there have been other methods previously proposed in the literature.Most of them, however, are designed to find one solution only.The pruning devices used here are directly related to features of protein conformations.
View Article:
PubMed Central - PubMed
Affiliation: LIX, Ecole Polytechnique, Palaiseau, 91128, France. cassioliandre@gmail.com.
ABSTRACT
Show MeSH
Background: The determination of protein structures satisfying distance constraints is an important problem in structural biology. Whereas the most common method currently employed is simulated annealing, there have been other methods previously proposed in the literature. Most of them, however, are designed to find one solution only. Results: In order to explore exhaustively the feasible conformational space, we propose here an interval Branch-and-Prune algorithm (iBP) to solve the Distance Geometry Problem (DGP) associated to protein structure determination. This algorithm is based on a discretization of the problem obtained by recursively constructing a search space having the structure of a tree, and by verifying whether the generated atomic positions are feasible or not by making use of pruning devices. The pruning devices used here are directly related to features of protein conformations. Conclusions: We described the new algorithm iBP to generate protein conformations satisfying distance constraints, that would potentially allows a systematic exploration of the conformational space. The algorithm iBP has been applied on three α-helical peptides. Related in: MedlinePlus |
Related In:
Results -
Collection
License 1 - License 2 getmorefigures.php?uid=PMC4384350&req=5
Mentions: When a distance is not uniquely defined, but rather defined by lower and upper bounds, i.e. di,j∈[li,j,ui,j], this distance is uniformly discretized by sampling b≥1 values in [li,j,ui,j], as depicted in Figure 5.(2)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \tilde d_{i}=\left\{ l_{i,i-3} + (t-1)\frac{(u_{i,i-3}-l_{i,i-3})}{b} : t=1,\ldots,b\right\}. $$\end{document}d~i=li,i−3+(t−1)(ui,i−3−li,i−3)b:t=1,…,b.Figure 5 |
View Article: PubMed Central - PubMed
Affiliation: LIX, Ecole Polytechnique, Palaiseau, 91128, France. cassioliandre@gmail.com.
Background: The determination of protein structures satisfying distance constraints is an important problem in structural biology. Whereas the most common method currently employed is simulated annealing, there have been other methods previously proposed in the literature. Most of them, however, are designed to find one solution only.
Results: In order to explore exhaustively the feasible conformational space, we propose here an interval Branch-and-Prune algorithm (iBP) to solve the Distance Geometry Problem (DGP) associated to protein structure determination. This algorithm is based on a discretization of the problem obtained by recursively constructing a search space having the structure of a tree, and by verifying whether the generated atomic positions are feasible or not by making use of pruning devices. The pruning devices used here are directly related to features of protein conformations.
Conclusions: We described the new algorithm iBP to generate protein conformations satisfying distance constraints, that would potentially allows a systematic exploration of the conformational space. The algorithm iBP has been applied on three α-helical peptides.