WebProAnalyst: an interactive tool for analysis of quantitative structure–activity relationships in protein families

WebProAnalyst is a web-accessible analysis tool () designed for scanning quantitative structure–activity relationships in protein families. The tool allows users to search correlations between protein activity and physicochemical characteristics (i.e. hydrophobicity or alpha-helical amphipathicity) in queried sequences. WebProAnalyst uses aligned amino acid sequences and data on protein activity (pK, Km, ED50, among others). WebProAnalyst implements methods of the known ProAnalyst package, including the multiple linear regression analysis and the sequence–activity correlation coefficient. In addition, WebProAnalyst incorporates a method based on neural networks. The WebProAnalyst reports a list of sites in protein family, the regression analysis parameters (including correlation values) for the relationships between the amino acid physicochemical characteristics in the site and the protein activity values. WebProAnalyst is useful in search of the amino acid residues that are important for protein function/activity. Furthermore, WebProAnalyst may be helpful in designing the protein-engineering experiments.

[1]  A. Hay,et al.  Selective proton permeability and pH regulation of the influenza virus M2 channel expressed in mouse erythroleukaemia cells. , 1996, The Journal of physiology.

[2]  M. Sansom,et al.  Influenza virus M2 protein: a molecular modelling study of the ion channel. , 1993, Protein engineering.

[3]  Mark Johnston,et al.  The promise of functional genomics: completing the encyclopedia of a cell. , 2004, Current opinion in microbiology.

[4]  Geoffrey J. Barton,et al.  Protein sequence alignments: a strategy for the hierarchical analysis of residue conservation , 1993, Comput. Appl. Biosci..

[5]  Mikhail S. Gelfand,et al.  SDPpred: a tool for prediction of amino acid residues that determine differences in functional specificity of homologous proteins , 2004, Nucleic Acids Res..

[6]  R. Lamb,et al.  Initial structural and dynamic characterization of the M2 protein transmembrane and amphipathic helices in lipid bilayers , 2003, Protein science : a publication of the Protein Society.

[7]  S. Wold,et al.  New chemical descriptors relevant for the design of biologically active peptides. A multivariate characterization of 87 amino acids. , 1998, Journal of medicinal chemistry.

[8]  B. Cravatt,et al.  Activity-based protein profiling: the serine hydrolases. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[9]  A. Fliri,et al.  Biological spectra analysis: Linking biological activity profiles to molecular structure. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[10]  J. Svendsen,et al.  Antibiotic activity of pentadecapeptides modelled from amino acid descriptors , 2001, Journal of peptide science : an official publication of the European Peptide Society.

[11]  E. Veerman,et al.  Synthetic histatin analogues with broad-spectrum antimicrobial activity. , 1997, The Biochemical journal.

[12]  O. Lichtarge,et al.  A family of evolution-entropy hybrid methods for ranking protein residues by importance. , 2004, Journal of molecular biology.

[13]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[14]  N. Draper,et al.  Applied Regression Analysis , 1967 .

[15]  V. I. Fomin,et al.  PROANAL version 2: multifunctional program for analysis of multiple protein sequence alignments and for studying the structure--activity relationships in protein families , 1995, Comput. Appl. Biosci..

[16]  Vladimir A. Ivanisenko,et al.  PDBSiteScan: a program for searching for active, binding and posttranslational modification sites in the 3D structures of proteins , 2004, Nucleic Acids Res..

[17]  J. Bradshaw,et al.  Neutron diffraction reveals the site of amantadine blockade in the influenza A M2 ion channel. , 1994, Virology.

[18]  U Norinder,et al.  A quantitative structure-activity relationship study of some substance P-related peptides. A multivariate approach using PLS and variable selection. , 2009, The journal of peptide research : official journal of the American Peptide Society.

[19]  V. I. Fomin,et al.  Algorithm and computer program Pro_Anal for analysis of relationship between structure and activity in a family of proteins or peptides , 1993, Comput. Appl. Biosci..

[20]  Vladimir A. Ivanisenko,et al.  PDBSite: a database of the 3D structure of protein functional sites , 2004, Nucleic Acids Res..