S-nitrosylation project

From Icbwiki

Jump to: navigation, search
Area of possible s-nitrosylation, with 5 angstrom sphere centered around the S atom of the Cys residue.
Area of possible s-nitrosylation, with 5 angstrom sphere centered around the S atom of the Cys residue.

The Campagne laboratory has been involved in an ongoing collaboration with the laboratory of Dr. Steven Gross to investigate the s-nitrosylation of cysteine residues. This page outlines the methods and results to date.

Contents

Introduction

Using a high throughput proteomic method, Steven Gross' group identified a set of relatively short primary amino acid sequences which contained at least one cysteine residue which was capable of being s-nitrosylated. The SWISSPROT accession number for each sequence was also identified. We investigated the properties of these sequences with the aim of providing additional biological insight into the s-nitrosylation process. Another aim of the project was to leverage knowledge about these sequences to develop an in-silico prediction tool.

Of particular interest to the Gross group was the difference seen in pKa values between cysteine residues that were s-nitrosylated, and those which were not.

Materials and methods

Data sets

Two sets of positively identified sequences were provided by the Gross laboratory. To date, only the first has been analyzed. They are both available here:

These sequences were used to identify possible structures using a BLAST search. The structural hits can be found here:

in-silico pKa calculation

One aspect of the suspected mechanism of S-nitrosylation of cysteine residues is related to the target residue's pKa value. This value can be determined using a molecular dynamics simulation, however this may prove expensive with the high throughput proteomics method used to obtain the sequences.

As an alternative, the pKa values of the nitrosylated cysteine residues was calculated in-silico.

The Molecular Biology Toolkit

The S-nitroslyation code uses the Molecular Biology Toolkit extensively. It's a great framework for manipulating protein structures.

Structure analysis

Using the Molecular Biology Toolkit, a number of structural analyses were performed on the data.

Statistical approaches

A number of statistical approaches were performed using Support Vector Machines and multi-variate statistics to identify any significant differences between the sequences contained in the positive and negative S-nitrosylated datasets.

Subversion Access

This project's Subversion repository can be checked out through SVN with the following instruction set:

 svn co https://pbtech-vc.med.cornell.edu/public/svn/icb/trunk/SNitro

Browse S-nitrosylation in the Subversion repository.

Personal tools