5,946 research outputs found
Fr-TM-align: a new protein structural alignment method based on fragment alignments and the TM-score
©2008 Pandit and Skolnick; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This article is available from: http://www.biomedcentral.com/1471-2105/9/531doi:10.1186/1471-2105-9-531Background: Protein tertiary structure comparisons are employed in various fields of
contemporary structural biology. Most structure comparison methods involve generation of an
initial seed alignment, which is extended and/or refined to provide the best structural superposition
between a pair of protein structures as assessed by a structure comparison metric. One such
metric, the TM-score, was recently introduced to provide a combined structure quality measure
of the coordinate root mean square deviation between a pair of structures and coverage. Using the
TM-score, the TM-align structure alignment algorithm was developed that was often found to have
better accuracy and coverage than the most commonly used structural alignment programs;
however, there were a number of situations when this was not true.
Results: To further improve structure alignment quality, the Fr-TM-align algorithm has been
developed where aligned fragment pairs are used to generate the initial seed alignments that are
then refined using dynamic programming to maximize the TM-score. For the assessment of the
structural alignment quality from Fr-TM-align in comparison to other programs such as CE and TMalign,
we examined various alignment quality assessment scores such as PSI and TM-score. The
assessment showed that the structural alignment quality from Fr-TM-align is better in comparison
to both CE and TM-align. On average, the structural alignments generated using Fr-TM-align have
a higher TM-score (~9%) and coverage (~7%) in comparison to those generated by TM-align. Fr-
TM-align uses an exhaustive procedure to generate initial seed alignments. Hence, the algorithm is
computationally more expensive than TM-align.
Conclusion: Fr-TM-align, a new algorithm that employs fragment alignment and assembly provides
better structural alignments in comparison to TM-align. The source code and executables of Fr-
TM-align are freely downloadable at: http://cssb.biology.gatech.edu/skolnick/files/FrTMalign/
Sequence alignment, mutual information, and dissimilarity measures for constructing phylogenies
Existing sequence alignment algorithms use heuristic scoring schemes which
cannot be used as objective distance metrics. Therefore one relies on measures
like the p- or log-det distances, or makes explicit, and often simplistic,
assumptions about sequence evolution. Information theory provides an
alternative, in the form of mutual information (MI) which is, in principle, an
objective and model independent similarity measure. MI can be estimated by
concatenating and zipping sequences, yielding thereby the "normalized
compression distance". So far this has produced promising results, but with
uncontrolled errors. We describe a simple approach to get robust estimates of
MI from global pairwise alignments. Using standard alignment algorithms, this
gives for animal mitochondrial DNA estimates that are strikingly close to
estimates obtained from the alignment free methods mentioned above. Our main
result uses algorithmic (Kolmogorov) information theory, but we show that
similar results can also be obtained from Shannon theory. Due to the fact that
it is not additive, normalized compression distance is not an optimal metric
for phylogenetics, but we propose a simple modification that overcomes the
issue of additivity. We test several versions of our MI based distance measures
on a large number of randomly chosen quartets and demonstrate that they all
perform better than traditional measures like the Kimura or log-det (resp.
paralinear) distances. Even a simplified version based on single letter Shannon
entropies, which can be easily incorporated in existing software packages, gave
superior results throughout the entire animal kingdom. But we see the main
virtue of our approach in a more general way. For example, it can also help to
judge the relative merits of different alignment algorithms, by estimating the
significance of specific alignments.Comment: 19 pages + 16 pages of supplementary materia
Back-translation for discovering distant protein homologies
Frameshift mutations in protein-coding DNA sequences produce a drastic change
in the resulting protein sequence, which prevents classic protein alignment
methods from revealing the proteins' common origin. Moreover, when a large
number of substitutions are additionally involved in the divergence, the
homology detection becomes difficult even at the DNA level. To cope with this
situation, we propose a novel method to infer distant homology relations of two
proteins, that accounts for frameshift and point mutations that may have
affected the coding sequences. We design a dynamic programming alignment
algorithm over memory-efficient graph representations of the complete set of
putative DNA sequences of each protein, with the goal of determining the two
putative DNA sequences which have the best scoring alignment under a powerful
scoring system designed to reflect the most probable evolutionary process. This
allows us to uncover evolutionary information that is not captured by
traditional alignment methods, which is confirmed by biologically significant
examples.Comment: The 9th International Workshop in Algorithms in Bioinformatics
(WABI), Philadelphia : \'Etats-Unis d'Am\'erique (2009
- …