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ANGDelMut
A web-based tool for predicting and analyzing functional loss mechanisms of deleterious angiogenin mutations causing amyotrophic lateral sclerosis
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Information

1. What is ANGDelMut?
ANGDelMut is a web-based tool for predicting and analyzing the functional loss mechanisms of deleterious angiogenin mutations associated with amyotrophic lateral sclerosis (ALS). The ANG gene is one of the most frequently mutated genes found in ALS patients across diverse ethnic groups. Human ANG encodes a 14.1 kDa monomeric protein (ANG) that induces neovascularization, maintains physiology and health of motor neurons by inducing angiogenesis, stimulates neurite outgrowth and path-finding, protects motor neurons from hypoxia-induced death, and hence acts as a neuroprotective factor. Missense mutations in ANG result in loss of either ribonucleolytic activity or nuclear translocation activity or both of these functions, and in turn cause ALS (Padhi et al. (2012) PLoS ONE; Padhi et al. (2013) Scientific Reports; Padhi et al. (2013) FEBS Letters). However, no web-based tool is available to predict whether a newly identified ANG mutation will be ALS causative. More importantly, no web-implemented method is currently available to elucidate the mechanisms of loss-of-function(s) of ANG mutants. In light of this observation, ANGDelMut web-tool is created, which predicts whether an ANG mutation is deleterious or benign based on a series of molecular dynamics (MD) simulations and analyses.
                                                                         
                 Figure. A brief overview of the methodology employed in ANGDelMut to predict deleterious Angiogenin mutations causing ALS.

                                                
                                                                        Figure. ANGDelMut protocol with the help of an ANG mutation.

Steps involved in the ANGDelMut web-tool for predicting deleterious ANG mutations causing ALS, with a brief understanding of the mechanisms of loss-of-functions. Step 1 involves submission of the missense ANG mutation to the web-tool by the user and preparation of mutated ANG protein, Step 2 involves processing of the mutated protein and performing implicit solvent MD simulations for about 25 ns, Step 3 involves analysis of several attributes from the MD simulated trajectory, namely, the RMSD versus time, conformational switching of His114 residue, presence of hydrogen bond interaction path from the site of mutation to His114, local folding of nuclear localization signal residues 31RRR33 and change in SASA versus time, Step 4 involves uploading the PDB file extracted from MD simulation trajectory and a text file containing the RMSD data into the web-tool.
What are the requirements to run ANGDelMut?
The following hardware and software is required to run this database.
At least 64 MB of available random-access memory (RAM) (256 MB recommended).
An Internet Explorer 7.0 or higher (IE8.0 or higher recommended), Firefox 3.x, Chrome 9, 10.
JavaScript and cookies enabled, Recommend ActiveX enabled for Internet Explorer.
Flash player installed.

2. How ANGDelMut is designed?
The ANGDelMut web-based tool is developed in MySQL and hosted on an APACHE http server located in the computer service centre of the Indian Institute of Technology Delhi. The ANGDelMut algorithm is executed in four steps, namely, Mutation selection, Implicit-solvent molecular dynamics simulation, Analysis of simulation trajectory, and Uploading output data.

3. How do I use ANGDelMut?
The homepage of ANGDelMut has all the query related links. We have provided a user manual to help the user to start-up quickly and easily.

4. What will be in next version of ANGDelMut?
At present, ANGDelMut employs a methodology to accurately predict whether an ANG (RNASE5) mutation will be ALS causative or not. In future, we are aiming to incorporate the functional consequence data for the entire RNASE family of proteins and their mutations in order to understand the ALS pathophysiology in great detail.

5. Other related tools/databases
Users interested for obtaining a cohesive and comprehensive picture of neurodegenerative disorders (NDDs) are suggested to visit NeuroDNet - an open source platform for constructing and analyzing neurodegenerative disease associated gene networks.

Credit:Computational and Systems Biology Group, Indian Institute of Technology Delhi, India. 2013 IIT Delhi. All rights reserved.
*Please submit any comments or questions to - delmutserver@gmail.com or adi.uoh@gmail.com