The ability to successfully predict the three-dimensional structure of a protein from its amino acid sequence has made considerable progress in the recent past. The progress is propelled by the improved accuracy of deep learning-based inter-residue contact map predictors coupled with the rising growth of protein sequence databases. Contact map encodes interatomic interaction information that can be exploited for highly accurate prediction of protein structures via contact map threading even for the query proteins that are not amenable to direct homology modeling. As such, contact-assisted threading has garnered considerable research effort. In this chapter, we provide an overview of existing contact-assisted threading methods while highlighting the recent advances and discussing some of the current limitations and future prospects in the application of contact-assisted threading for improving the accuracy of low-homology protein modeling.
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Contact-Assisted Threading in Low-Homology Protein Modeling.
Methods Mol Biol
March 2023
Department of Computer Science, Virginia Tech, Blacksburg, VA, USA.
The ability to successfully predict the three-dimensional structure of a protein from its amino acid sequence has made considerable progress in the recent past. The progress is propelled by the improved accuracy of deep learning-based inter-residue contact map predictors coupled with the rising growth of protein sequence databases. Contact map encodes interatomic interaction information that can be exploited for highly accurate prediction of protein structures via contact map threading even for the query proteins that are not amenable to direct homology modeling.
View Article and Find Full Text PDFDisCovER: distance- and orientation-based covariational threading for weakly homologous proteins.
Proteins
February 2022
Department of Computer Science, Virginia Tech, Blacksburg, Virginia, USA.
Threading a query protein sequence onto a library of weakly homologous structural templates remains challenging, even when sequence-based predicted contact or distance information is used. Contact-assisted or distance-assisted threading methods utilize only the spatial proximity of the interacting residue pairs for template selection and alignment, ignoring their orientation. Moreover, existing threading methods fail to consider the neighborhood effect induced by the query-template alignment.
View Article and Find Full Text PDFTemplate-based prediction of protein structure with deep learning.
BMC Genomics
December 2020
Department of Systems Biology, Columbia University, New York, NY, USA.
Background: Accurate prediction of protein structure is fundamentally important to understand biological function of proteins. Template-based modeling, including protein threading and homology modeling, is a popular method for protein tertiary structure prediction. However, accurate template-query alignment and template selection are still very challenging, especially for the proteins with only distant homologs available.
View Article and Find Full Text PDFEvaluating the significance of contact maps in low-homology protein modeling using contact-assisted threading.
Sci Rep
February 2020
Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, 36849, USA.
The development of improved threading algorithms for remote homology modeling is a critical step forward in template-based protein structure prediction. We have recently demonstrated the utility of contact information to boost protein threading by developing a new contact-assisted threading method. However, the nature and extent to which the quality of a predicted contact map impacts the performance of contact-assisted threading remains elusive.
View Article and Find Full Text PDFCATHER: a novel threading algorithm with predicted contacts.
Bioinformatics
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School of Mathematical Sciences, Nankai University, Tianjin 300071, China.
Motivation: Threading is one of the most effective methods for protein structure prediction. In recent years, the increasing accuracy in protein contact map prediction opens a new avenue to improve the performance of threading algorithms. Several preliminary studies suggest that with predicted contacts, the performance of threading algorithms can be improved greatly.
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