Literature DB >> 22814572

Information properties of naturally-occurring proteins: Fourier analysis and complexity phase plots.

Daniel J Graham1, Shelby Grzetic, Donald May, John Zumpf.   

Abstract

In previous work from this lab, the information in natural proteins was investigated with Ribonuclease A (RNase A) serving as the source. The signature traits were investigated at three structure levels: primary through tertiary. The present paper travels further by charting the primary structure information of about half a million molecules. This was feasible given abundant sequence archives for both living and viral systems. Notably, a method is presented for evaluating primary structure information, based on Fourier analysis and spectral complexity. Significantly, the results show certain complexity traits to be universal for living sources. Viruses, by contrast, encode protein collections which are case-specific and complexity-divergent. The results have ramifications for discriminating collections on the basis of sequence information. This discrimination offers new strategies for selecting drug targets.

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Year:  2012        PMID: 22814572     DOI: 10.1007/s10930-012-9432-7

Source DB:  PubMed          Journal:  Protein J        ISSN: 1572-3887            Impact factor:   2.371


  20 in total

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Authors:  Ronald T. Raines
Journal:  Chem Rev       Date:  1998-05-07       Impact factor: 60.622

Review 2.  Chemoinformatics methods for systematic comparison of molecules from natural and synthetic sources and design of hybrid libraries.

Authors:  Jürgen Bajorath
Journal:  Mol Divers       Date:  2002       Impact factor: 2.943

3.  Information content in organic molecules: quantification and statistical structure via Brownian processing.

Authors:  Daniel J Graham; Christopher Malarkey; Matthew V Schulmerich
Journal:  J Chem Inf Comput Sci       Date:  2004 Sep-Oct

Review 4.  Graphical representation of proteins.

Authors:  Milan Randić; Jure Zupan; Alexandru T Balaban; Drazen Vikić-Topić; Dejan Plavsić
Journal:  Chem Rev       Date:  2010-10-12       Impact factor: 60.622

5.  Prediction of mitochondrial proteins using discrete wavelet transform.

Authors:  Lin Jiang; Menglong Li; Zhining Wen; Kelong Wang; Yuanbo Diao
Journal:  Protein J       Date:  2006-06       Impact factor: 2.371

6.  A model for the recognition of protein kinases based on the entropy of 3D van der Waals interactions.

Authors:  Humberto Gonzalez-Díaz; Liane Saiz-Urra; Reinaldo Molina; Lourdes Santana; Eugenio Uriarte
Journal:  J Proteome Res       Date:  2007-02       Impact factor: 4.466

7.  Exploring structure-selectivity relationships of biogenic amine GPCR antagonists using similarity searching and dynamic compound mapping.

Authors:  Ingo Vogt; Hany E A Ahmed; Jens Auer; Jürgen Bajorath
Journal:  Mol Divers       Date:  2008-03-04       Impact factor: 2.943

8.  Using entropy of drug and protein graphs to predict FDA drug-target network: theoretic-experimental study of MAO inhibitors and hemoglobin peptides from Fasciola hepatica.

Authors:  Francisco Prado-Prado; Xerardo García-Mera; Paula Abeijón; Nerea Alonso; Olga Caamaño; Matilde Yáñez; Teresa Gárate; Mercedes Mezo; Marta González-Warleta; Laura Muiño; Florencio M Ubeira; Humberto González-Díaz
Journal:  Eur J Med Chem       Date:  2011-01-21       Impact factor: 6.514

9.  Phylogenetic analysis of protein sequences based on distribution of length about common sub-string.

Authors:  Guisong Chang; Tianming Wang
Journal:  Protein J       Date:  2011-03       Impact factor: 2.371

10.  Structural basis for lysidine formation by ATP pyrophosphatase accompanied by a lysine-specific loop and a tRNA-recognition domain.

Authors:  Kotaro Nakanishi; Shuya Fukai; Yoshiho Ikeuchi; Akiko Soma; Yasuhiko Sekine; Tsutomu Suzuki; Osamu Nureki
Journal:  Proc Natl Acad Sci U S A       Date:  2005-05-13       Impact factor: 11.205

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  2 in total

1.  A new bioinformatics approach to natural protein collections: permutation structure contrasts of viral and cellular systems.

Authors:  Daniel J Graham
Journal:  Protein J       Date:  2013-04       Impact factor: 4.000

2.  Net-Net Auto Machine Learning (AutoML) Prediction of Complex Ecosystems.

Authors:  Enrique Barreiro; Cristian R Munteanu; Maykel Cruz-Monteagudo; Alejandro Pazos; Humbert González-Díaz
Journal:  Sci Rep       Date:  2018-08-17       Impact factor: 4.379

  2 in total

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