scholarly journals Alignnment of RNA with Structures of Unlimited Complexity

10.29007/f883 ◽  
2018 ◽  
Author(s):  
Alessandro Dal Palù ◽  
Mathias Möhl ◽  
Sebastian Will
Keyword(s):  
Dynamic Programming ◽  
Efficient Solutions ◽  
Structure Alignment ◽  
Sequence Structure ◽  
Crossing Structures ◽  
Input Structure ◽  
Alignment Problem ◽  
Nested Structure ◽  
Complex Structural ◽  
Constraint Approach

Sequence-structure alignment of RNAs with arbitrary secondary structures is Max-SNP-hard. Therefore, the problem of RNA alignment is commonly restricted to nested structure, where dynamic programming yields efficient solutions. However, nested structure cannot model pseudoknots or even more complex structural dependencies. Nevertheless those dependencies are essential and conserved features of many RNAs. Only few existing approaches deal with crossings of limited complexity or arbitrary crossing structures. Here, we present a constraint approach for alignment of structures in the even more general class of structures with unlimited complexity. Our central contribution is a new RNA alignment propagator. It is based on an efficient O(n<sup>2</sup>) relaxation of the RNA alignment problem. Specifically, our approach Carna solves the alignment problem for sequences with given input structure of unlimited complexity. Carna is implemented using Gecode.

LOCAL SEQUENCE-STRUCTURE MOTIFS IN RNA

2004 ◽  
Vol 02 (04) ◽  
pp. 681-698 ◽  
Author(s):  
ROLF BACKOFEN ◽  
SEBASTIAN WILL
Keyword(s):  
Information Structure ◽  
Structure Alignment ◽  
General Definition ◽  
Local Alignment ◽  
Sequence Information ◽  
Sequence Structure ◽  
Worst Case ◽  
Rna Molecules ◽  
Alignment Algorithms ◽  
Local Sequence

Ribonuclic acid (RNA) enjoys increasing interest in molecular biology; despite this interest fundamental algorithms are lacking, e.g. for identifying local motifs. As proteins, RNA molecules have a distinctive structure. Therefore, in addition to sequence information, structure plays an important part in assessing the similarity of RNAs. Furthermore, common sequence-structure features in two or several RNA molecules are often only spatially local, where possibly large parts of the molecules are dissimilar. Consequently, we address the problem of comparing RNA molecules by computing an optimal local alignment with respect to sequence and structure information. While local alignment is superior to global alignment for identifying local similarities, no general local sequence-structure alignment algorithms are currently known. We suggest a new general definition of locality for sequence-structure alignments that is biologically motivated and efficiently tractable. To show the former, we discuss locality of RNA and prove that the defined locality means connectivity by atomic and non-atomic bonds. To show the latter, we present an efficient algorithm for the newly defined pairwise local sequence-structure alignment (lssa) problem for RNA. For molecules of lengthes n and m, the algorithm has worst-case time complexity of O(n2·m2· max (n,m)) and a space complexity of only O(n·m). An implementation of our algorithm is available at . Its runtime is competitive with global sequence-structure alignment.

scholarly journals Variable gap penalty for protein sequence–structure alignment

2006 ◽  
Vol 19 (3) ◽  
pp. 129-133 ◽  
Author(s):  
M.S. Madhusudhan ◽  
Marc A. Marti-Renom ◽  
Roberto Sanchez ◽  
Andrej Sali
Keyword(s):  
Protein Sequence ◽  
Structure Alignment ◽  
Sequence Structure

scholarly journals GADP-align: A genetic algorithm and dynamic programming-based method for structural alignment of proteins

Bioimpacts ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 271-279
Author(s):  
Soraya Mirzaei ◽  
Jafar Razmara ◽  
Shahriar Lotfi
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Programming ◽  
Protein Structure ◽  
Hybrid Method ◽  
Structural Alignment ◽  
Dynamic Programming Algorithm ◽  
Structure Alignment ◽  
Programming Algorithm ◽  
Programming Technique ◽  
Iterative Dynamic Programming

Introduction: Similarity analysis of protein structure is considered as a fundamental step to give insight into the relationships between proteins. The primary step in structural alignment is looking for the optimal correspondence between residues of two structures to optimize the scoring function. An exhaustive search for finding such a correspondence between two structures is intractable. Methods: In this paper, a hybrid method is proposed, namely GADP-align, for pairwise protein structure alignment. The proposed method looks for an optimal alignment using a hybrid method based on a genetic algorithm and an iterative dynamic programming technique. To this end, the method first creates an initial map of correspondence between secondary structure elements (SSEs) of two proteins. Then, a genetic algorithm combined with an iterative dynamic programming algorithm is employed to optimize the alignment. Results: The GADP-align algorithm was employed to align 10 ‘difficult to align’ protein pairs in order to evaluate its performance. The experimental study shows that the proposed hybrid method produces highly accurate alignments in comparison with the methods using exactly the dynamic programming technique. Furthermore, the proposed method prevents the local optimal traps caused by the unsuitable initial guess of the corresponding residues. Conclusion: The findings of this paper demonstrate that employing the genetic algorithm along with the dynamic programming technique yields highly accurate alignments between a protein pair by exploring the global alignment and avoiding trapping in local alignments.

Matching and Significance Evaluation of Combined Sequence-Structure Motifs in RNA

2002 ◽  
Vol 216 (2) ◽  
Author(s):  
Carsten Meyer ◽  
Robert Giegerich
Keyword(s):  
Dynamic Programming ◽  
Statistical Analysis ◽  
Secondary Structure ◽  
Pattern Matching ◽  
Powerful Method ◽  
Expected Number ◽  
Sequence Structure ◽  
Mixed Sequence ◽  
Canonical Pattern

The discipline of Algebraic Dynamic Programming is a powerful method to design and implement versatile pattern matching algorithms on sequences; here we consider mixed sequence and secondary structure motifs in RNA. A recurring challenge when designing new pattern matchers is to provide a statistical analysis of pattern significance. We demonstrate that by the use of so-called canonical pattern descriptions, the expected number of hits on a sequence of length

scholarly journals On the Difference in Quality between Current Heuristic and Optimal Solutions to the Protein Structure Alignment Problem

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Mauricio Arriagada ◽  
Aleksandar Poleksic
Keyword(s):  
Protein Structure ◽  
Heuristic Algorithms ◽  
Structure Alignment ◽  
Protein Structure Alignment ◽  
Optimal Solutions ◽  
Timely Manner ◽  
Matching Problem ◽  
Structural Match ◽  
Alignment Problem ◽  
The Difference

The importance of pairwise protein structural comparison in biomedical research is fueling the search for algorithms capable of finding more accurate structural match of two input proteins in a timely manner. In recent years, we have witnessed rapid advances in the development of methods for approximate and optimal solutions to the protein structure matching problem. Albeit slow, these methods can be extremely useful in assessing the accuracy of more efficient, heuristic algorithms. We utilize a recently developed approximation algorithm for protein structure matching to demonstrate that a deep search of the protein superposition space leads to increased alignment accuracy with respect to many well-established measures of alignment quality. The results of our study suggest that a large and important part of the protein superposition space remains unexplored by current techniques for protein structure alignment.

Sign in / Sign up

Export Citation Format

Share Document