Simplified Protein Models: Predicting Folding Pathways and Structure Using Amino Acid Sequences

Adhikari, Aashish N.; Freed, Karl F.; Sosnick, Tobin R.

doi:10.1103/PhysRevLett.111.028103

Title: Simplified Protein Models: Predicting Folding Pathways and Structure Using Amino Acid Sequences

Full Record
Other Related Research

Authors:: Adhikari, Aashish N.; Freed, Karl F.; Sosnick, Tobin R.

Publication Date:: Thu Jul 11 00:00:00 EDT 2013

Sponsoring Org.:: USDOE

OSTI Identifier:: 1103786

Resource Type:: Publisher's Accepted Manuscript

Journal Name:: Physical Review Letters

Additional Journal Information:: Journal Volume: 111; Journal Issue: 2; Journal ID: ISSN 0031-9007

Publisher:: American Physical Society

Country of Publication:: United States

Language:: English

Citation Formats


                    Adhikari, Aashish N., Freed, Karl F., and Sosnick, Tobin R. Simplified Protein Models: Predicting Folding Pathways and Structure Using Amino Acid Sequences.  United States: N. p., 2013. 
Web.  doi:10.1103/PhysRevLett.111.028103.

Copy to clipboard


                    Adhikari, Aashish N., Freed, Karl F., & Sosnick, Tobin R. Simplified Protein Models: Predicting Folding Pathways and Structure Using Amino Acid Sequences.  United States.  https://doi.org/10.1103/PhysRevLett.111.028103

Copy to clipboard


                    Adhikari, Aashish N., Freed, Karl F., and Sosnick, Tobin R. Thu .  
"Simplified Protein Models: Predicting Folding Pathways and Structure Using Amino Acid Sequences".  United States.  https://doi.org/10.1103/PhysRevLett.111.028103.

Copy to clipboard


                    
@article{osti_1103786,

  title        = {Simplified Protein Models: Predicting Folding Pathways and Structure Using Amino Acid Sequences},

  author       = {Adhikari, Aashish N. and Freed, Karl F. and Sosnick, Tobin R.},

  abstractNote = {},

  doi          = {10.1103/PhysRevLett.111.028103},

  journal      = {Physical Review Letters},

  number       = 2,

  volume       = 111,

  place        = {United States},

  year         = {Thu Jul 11 00:00:00 EDT 2013},

  month        = {Thu Jul 11 00:00:00 EDT 2013}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Accepted Manuscript (Publisher)

Publisher's Version of Record
https://doi.org/10.1103/PhysRevLett.111.028103

Other availability

Search WorldCat to find libraries that may hold this journal

Citation Metrics:

Cited by: 26 works

Citation information provided by
Web of Science

Save / Share:

Export Metadata

Save to My Library

Similar Records in DOE PAGES and OSTI.GOV collections:

Fast computational methods for predicting protein structure from primary amino acid sequence

Patent Agarwal, Pratul Kumar

The present invention provides a method utilizing primary amino acid sequence of a protein, energy minimization, molecular dynamics and protein vibrational modes to predict three-dimensional structure of a protein. The present invention also determines possible intermediates in the protein folding pathway. The present invention has important applications to the design of novel drugs as well as protein engineering. The present invention predicts the three-dimensional structure of a protein independent of size of the protein, overcoming a significant limitation in the prior art.
Full Text Available
Protein location prediction using atomic composition and global features of the amino acid sequence

Journal Article Cherian, Betsy Sheena, E-mail: betsy.skb@gmail.com ; Nair, Achuthsankar S. - Biochemical and Biophysical Research Communications

Subcellular location of protein is constructive information in determining its function, screening for drug candidates, vaccine design, annotation of gene products and in selecting relevant proteins for further studies. Computational prediction of subcellular localization deals with predicting the location of a protein from its amino acid sequence. For a computational localization prediction method to be more accurate, it should exploit all possible relevant biological features that contribute to the subcellular localization. In this work, we extracted the biological features from the full length protein sequence to incorporate more biological information. A new biological feature, distribution of atomic composition is effectivelymore »« less
https://doi.org/10.1016/J.BBRC.2009.12.118
Prediction of protein antigenic determinants from amino acid sequences

Journal Article Hopp, T P ; Woods, K R - Proc. Natl. Acad. Sci. U.S.A.; (United States)

A method is presented for locating protein antigenic determinants by analyzing amino acid sequences in order to find the point of greatest local hydrophilicity. This is accomplished by assigning each amino acid a numerical value (hydrophilicity value) and then repetitively averaging these values along the peptide chain. The point of highest local average hydrophilicity is invariably located in, or immediately adjacent to, an antigenic determinant. It was found that the prediction success rate depended on averaging group length, with hexapeptide averages yielding optimal results. The method was developed using 12 proteins for which extensive immunochemical analysis has been carried outmore »« less
https://doi.org/10.1073/pnas.78.6.3824
3-d structure-based amino acid sequence alignment of esterases, lipases and related proteins

Technical Report Gentry, M K ; Doctor, B P ; Cygler, M ; ...

Acetylcholinesterase and butyrylcholinesterase, enzymes with potential as pretreatment drugs for organophosphate toxicity, are members of a larger family of homologous proteins that includes carboxylesterases, cholesterol esterases, lipases, and several nonhydrolytic proteins. A computer-generated alignment of 18 of the proteins, the acetylcholinesases, butyrylcholinesterases, carboxylesterases, some esterases, and the nonenzymatic proteins has been previously presented. More recently, the three-dimensional structures of two enzymes enzymes in this group, acetylcholinesterase from Torpedo californica and lipase from Geotrichum candidum, have been determined. Based on the x-ray structures and the superposition of these two enzymes, it was possible to obtain an improved amino acid sequence alignmentmore »« less
Relation between protein structure, sequence homology and composition of amino acids

Technical Report Mayoraz, E ; Muchnik, I ; Dubchak, I

A method of quantitative comparison of two classifications rules applied to protein folding problem is presented. Classification of proteins based on sequence homology and based on amino acid composition were compared and analyzed according to this approach. The coefficient of correlation between these classification methods and the procedure of estimation of robustness of the coefficient are discussed.

Similar Records