Literature DB >> 35838376

Combine Cryo-EM Density Map and Residue Contact for Protein Structure Prediction - A Case Study.

Maytha Alshammari1, Jing He1.   

Abstract

Cryo-electron microscopy is a major structure determination technique for large molecular machines and membrane-associated complexes. Although atomic structures have been determined directly from cryo-EM density maps with high resolutions, current structure determination methods for medium resolution (5 to 10 Å) cryo-EM maps are limited by the availability of structure templates. Secondary structure traces are lines detected from a cryo-EM density map for α-helices and β-strands of a protein. When combined with secondary structure sequence segments predicted from a protein sequence, it is possible to generate a set of likely topologies of α-traces and β-sheet traces. A topology describes the overall folding relationship among secondary structures; it is a critical piece of information for deriving the corresponding atomic structure. We propose a method for protein structure prediction that combines three sources of information: the secondary structure traces detected from the cryo-EM density map, predicted secondary structure sequence segments, and amino acid contact pairs predicted using MULTICOM. A case study shows that using amino acid contact prediction from MULTICOM improves the ranking of the true topology. Our observations convey that using a small set of highly voted secondary structure contact pairs enhances the ranking in all experiments conducted for this case.

Entities:  

Keywords:  amino acid; constraints; contact; cryo-electron microscopy; image; protein structure; secondary structure; topology

Year:  2020        PMID: 35838376      PMCID: PMC9279007          DOI: 10.1145/3388440.3414708

Source DB:  PubMed          Journal:  ACM BCB


  29 in total

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Authors:  W Wriggers; S Birmanns
Journal:  J Struct Biol       Date:  2001 Feb-Mar       Impact factor: 2.867

2.  A Dynamic Programming Algorithm for Finding the Optimal Placement of a Secondary Structure Topology in Cryo-EM Data.

Authors:  Abhishek Biswas; Desh Ranjan; Mohammad Zubair; Jing He
Journal:  J Comput Biol       Date:  2015-08-05       Impact factor: 1.479

3.  Identification of secondary structure elements in intermediate-resolution density maps.

Authors:  Matthew L Baker; Tao Ju; Wah Chiu
Journal:  Structure       Date:  2007-01       Impact factor: 5.006

4.  Identification of alpha-helices from low resolution protein density maps.

Authors:  A Dal Palù; J He; E Pontelli; Y Lu
Journal:  Comput Syst Bioinformatics Conf       Date:  2006

5.  JPred: a consensus secondary structure prediction server.

Authors:  J A Cuff; M E Clamp; A S Siddiqui; M Finlay; G J Barton
Journal:  Bioinformatics       Date:  1998       Impact factor: 6.937

6.  Accurate prediction of protein contact maps by coupling residual two-dimensional bidirectional long short-term memory with convolutional neural networks.

Authors:  Jack Hanson; Kuldip Paliwal; Thomas Litfin; Yuedong Yang; Yaoqi Zhou
Journal:  Bioinformatics       Date:  2018-12-01       Impact factor: 6.937

7.  Atomic structure of human adenovirus by cryo-EM reveals interactions among protein networks.

Authors:  Hongrong Liu; Lei Jin; Sok Boon S Koh; Ivo Atanasov; Stan Schein; Lily Wu; Z Hong Zhou
Journal:  Science       Date:  2010-08-27       Impact factor: 47.728

8.  2.9 Å Resolution Cryo-EM 3D Reconstruction of Close-Packed Virus Particles.

Authors:  Zheng Liu; Fei Guo; Feng Wang; Tian-Cheng Li; Wen Jiang
Journal:  Structure       Date:  2016-01-14       Impact factor: 5.006

9.  An Effective Computational Method Incorporating Multiple Secondary Structure Predictions in Topology Determination for Cryo-EM Images.

Authors:  Abhishek Biswas; Desh Ranjan; Mohammad Zubair; Stephanie Zeil; Kamal Al Nasr; Jing He
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2016-03-17       Impact factor: 3.710

10.  CCMpred--fast and precise prediction of protein residue-residue contacts from correlated mutations.

Authors:  Stefan Seemayer; Markus Gruber; Johannes Söding
Journal:  Bioinformatics       Date:  2014-07-26       Impact factor: 6.937

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