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Threading (protein sequence)

About: Threading (protein sequence) is a research topic. Over the lifetime, 1333 publications have been published within this topic receiving 89650 citations.


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Journal ArticleDOI
TL;DR: The iterative threading assembly refinement (I-TASSER) server is an integrated platform for automated protein structure and function prediction based on the sequence- to-structure-to-function paradigm.
Abstract: The iterative threading assembly refinement (I-TASSER) server is an integrated platform for automated protein structure and function prediction based on the sequence-to-structure-to-function paradigm. Starting from an amino acid sequence, I-TASSER first generates three-dimensional (3D) atomic models from multiple threading alignments and iterative structural assembly simulations. The function of the protein is then inferred by structurally matching the 3D models with other known proteins. The output from a typical server run contains full-length secondary and tertiary structure predictions, and functional annotations on ligand-binding sites, Enzyme Commission numbers and Gene Ontology terms. An estimate of accuracy of the predictions is provided based on the confidence score of the modeling. This protocol provides new insights and guidelines for designing of online server systems for the state-of-the-art protein structure and function predictions. The server is available at http://zhanglab.ccmb.med.umich.edu/I-TASSER.

5,792 citations

Journal ArticleDOI
TL;DR: The PSIPRED protein structure prediction server allows users to submit a protein sequence, perform a prediction of their choice and receive the results of the prediction both textually via e-mail and graphically via the web.
Abstract: The PSIPRED protein structure prediction server allows users to submit a protein sequence, perform a prediction of their choice and receive the results of the prediction both textually via e-mail and graphically via the web. The user may select one of three prediction methods to apply to their sequence: PSIPRED, a highly accurate secondary structure prediction method; MEMSAT 2, a new version of a widely used transmembrane topology prediction method; or GenTHREADER, a sequence profile based fold recognition method.

3,381 citations

Book ChapterDOI
TL;DR: This chapter investigates the anatomy and taxonomy of protein structures, based on the results of three-dimensional X-ray crystallography of globular proteins.
Abstract: Publisher Summary This chapter investigates the anatomy and taxonomy of protein structures. A protein is a polypeptide chain made up of amino acid residues linked together in a definite sequence. Amino acids are “handed,” and naturally occurring proteins contain only L-amino acids. A simple mnemonic for that purpose is the “corncrib.” The sequence of side chains determines all that is unique about a particular protein, including its biological function and its specific three-dimensional structure. The major possible routes to knowledge of three-dimensional protein structure are prediction from the amino acid sequence and analysis of spectroscopic measurements such as circular dichroism, laser Raman spectroscopy, and nuclear magnetic resonance. The analysis and discussion of protein structure is based on the results of three-dimensional X-ray crystallography of globular proteins. The basic elements of protein structures are discussed. The most useful level at which protein structures are to be categorized is the domain, as there are many cases of multiple-domain proteins in which each separate domain resembles other entire smaller proteins. The simplest type of stable protein structure consists of polypeptide backbone wrapped more or less uniformly around the outside of a single hydrophobic core. The outline of the taxonomy is also provided in the chapter.

3,201 citations

Journal ArticleDOI
TL;DR: Analysis of the structural families generated by CATH reveals the prominent features of protein structure space and a database of well-characterised protein structure families will facilitate the assignment of structure-function/evolution relationships to both known and newly determined protein structures.

2,551 citations

Journal ArticleDOI
01 Dec 2004-Proteins
TL;DR: A new scoring function, the template modeling score (TM‐score), to assess the quality of protein structure templates and predicted full‐length models by extending the approaches used in Global Distance Test (GDT) 1 and MaxSub, which suggests that the TM‐score is a useful complement to the fully automated assessment ofprotein structure predictions.
Abstract: We have developed a new scoring function, the template modeling score (TM-score), to assess the quality of protein structure templates and predicted full-length models by extending the approaches used in Global Distance Test (GDT) 1 and MaxSub. 2 First, a protein size-dependent scale is exploited to eliminate the inherent protein size dependence of the previous scores and appropri- ately account for random protein structure pairs. Second, rather than setting specific distance cutoffs and calculating only the fractions with errors below the cutoff, all residue pairs in alignment/modeling are evaluated in the proposed score. For compari- son of various scoring functions, we have con- structed a large-scale benchmark set of structure templates for 1489 small to medium size proteins using the threading program PROSPECTOR_3 and built the full-length models using MODELLER and TASSER. The TM-score of the initial threading align- ments, compared to the GDT and MaxSub scoring functions, shows a much stronger correlation to the quality of the final full-length models. The TM-score is further exploited as an assessment of all 'new fold' targets in the recent CASP5 experiment and shows a close coincidence with the results of human-expert visual assessment. These data suggest that the TM- score is a useful complement to the fully automated assessment of protein structure predictions. The executable program of TM-score is freely download- able at http://bioinformatics.buffalo.edu/TM-score. aligned, the resulting full-length model might be of poorer quality. The template assessment problem becomes particu- larly relevant during the development of efficient fold recognition algorithms, since different sequence-structure alignment schemes or parameters can result in various levels of alignment confidence with an associated loss or gain of alignment coverage. 3- 6 Therefore, a single assess- ment score that has an appropriate balance of alignment accuracy and coverage and that is strongly related to the quality of the final full-length model is essential. Equally important, it must differentiate between a random and a statistically significant prediction. Highly related to the above problems, several interest- ing scoring functions have been developed for the purpose of sequence-dependent comparison of two structures of different lengths (in contrast to sequence-independent

1,754 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202336
202288
202117
202027
201921
201820