Current Limitations to Protein Threading Approaches

Smith, Temple F.; Conte, Loredana Lo; Bienkowska, Jadwiga; Gaitatzes, Chrysanthe; Rogers, Robert; Lathrop, Richard H.

doi:10.1089/cmb.1997.4.217

Cited by 43 publications

(16 citation statements)

References 24 publications

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“…The methods in this class include threading and 3D template matching (Bowie et al 1991; Godzik and Skolnick 1992; Jones et al 1992; Kelley et al 2000; Shi et al 2001; Fischer 2003. For review, see Jones 1997; Levitt 1997; Smith et al 1997; Torda 1997; David et al 2000).…”

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confidence: 99%

Alignment of protein sequences by their profiles

2004

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The accuracy of an alignment between two protein sequences can be improved by including other detectably related sequences in the comparison. We optimize and benchmark such an approach that relies on aligning two multiple sequence alignments, each one including one of the two protein sequences. Thirteen different protocols for creating and comparing profiles corresponding to the multiple sequence alignments are implemented in the SALIGN command of MODELLER. A test set of 200 pairwise, structure-based alignments with sequence identities below 40% is used to benchmark the 13 protocols as well as a number of previously described sequence alignment methods, including heuristic pairwise sequence alignment by BLAST, pairwise sequence alignment by global dynamic programming with an affine gap penalty function by the ALIGN command of MODELLER, sequence-profile alignment by PSI-BLAST, Hidden Markov Model methods implemented in SAM and LOBSTER, pairwise sequence alignment relying on predicted local structure by SEA, and multiple sequence alignment by CLUSTALW and COMPASS. The alignment accuracies of the best new protocols were significantly better than those of the other tested methods. For example, the fraction of the correctly aligned residues relative to the structure-based alignment by the best protocol is 56%, which can be compared with the accuracies of 26%, 42%, 43%, 48%, 50%, 49%, 43%, and 43% for the other methods, respectively. The new method is currently applied to large-scale comparative protein structure modeling of all known sequences.

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confidence: 99%

Alignment of protein sequences by their profiles

2004

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“…A threading method typically consists of four components [81]: (1) a library of representative 3D protein structures as templates; (2) an energy function for measuring the fitness between a query sequence and a template structure in the library; (3) a threading algorithm for searching the lowest energy among the possible alignments for a given sequencetemplate pair; (4) a criterion for estimating the confidence level of the predicted structure. The following discussion addresses each aspect in detail.…”

Section: Threading Componentsmentioning

confidence: 99%

Computational Methods for Remote Homolog Identification

Wan

2005

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As more and more protein sequences are available, homolog identification becomes increasingly important for functional, structural, and evolutional studies of proteins. Many homologous proteins were separated a very long time ago in their evolutionary history and thus their sequences share low sequence identity. These remote homologs have become a research focus in bioinformatics over the past decade, and some significant advances have been achieved. In this paper, we provide a comprehensive review on computational techniques used in remote homolog identification based on different methods, including sequence-sequence comparison, and sequence-structure comparison, and structure-structure comparison. Other miscellaneous approaches are also summarized. Pointers to the online resources of these methods and their related databases are provided. Comparisons among different methods in terms of their technical approaches, their strengths, and limitations are followed. Studies on proteins in SARS-CoV are shown as an example for remote homolog identification application.

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“…Protein sequence-structure threading (usually simply referred to as threading) is a family of computational approaches that, given a protein sequence, attempt to select, among all known 3D structures, the structure that is best compatible with this sequence [535,775,783]. Metaphorically, the sequence is "threaded" through a variety of structures and the method determines which one fits better than the others [125,405,575,649,651].…”

Section: Threadingmentioning

confidence: 99%