Microbial mediated drug metabolism

A recent publication out from our lab. 
A novel approach for the prediction of species-specific biotransformation of xenobiotic/drug molecules by the human gut microbiota

Abstract
The human gut microbiota is constituted of a diverse group of microbial species harbouring an enormous metabolic potential, which can alter the metabolism of orally administered drugs leading to individual/population-specific differences in drug responses. Considering the large heterogeneous pool of human gut bacteria and their metabolic enzymes, investigation of species-specific contribution to xenobiotic/drug metabolism by experimental studies is a challenging task. Therefore, we have developed a novel computational approach to predict the metabolic enzymes and gut bacterial species, which can potentially carry out the biotransformation of a xenobiotic/drug molecule. A substrate database was constructed for metabolic enzymes from 491 available human gut bacteria. The structural properties (fingerprints) from these substrates were extracted and used for the development of random forest models, which displayed average accuracies of up to 98.61% and 93.25% on cross-validation and blind set, respectively. After the prediction of EC subclass, the specific metabolic enzyme (EC) is identified using a molecular similarity search. The performance was further evaluated on an independent set of FDA-approved drugs and other clinically important molecules. To our knowledge, this is the only available approach implemented as ‘DrugBug’ tool for the prediction of xenobiotic/drug metabolism by metabolic enzymes of human gut microbiota.

Please explore and write back to me (ashoks773@gmail.com) in case of any problem. Comments are welcome.

Prediction of anti-inflammatory proteins/peptides: an insilico approach

Time to predict the anti-inflammatory nature of peptides and proteins using a recent machine learning based tool 'AntiInflam'.

A recent publication out from our lab. Please explore and write back to (sudheer@iiserb.ac.in) in case

of any problem. Comments are welcome. 

https://www.ncbi.nlm.nih.gov/pubmed/28057002

The prediction model for epitope mapping and similarity search are provided as a comprehensive webserver.

Available at http://metagenomics.iiserb.ac.in/antiinflam/ 

Prediction of Biofilm Inhibiting Peptides: An In silico Approach

Time to predict the biofilm inhibiting peptides using a recent machine learning based tool 'BioFin'.

A recent publication out from our lab. Please explore and write back to (sudheer@iiserb.ac.in) in case

of any problem. Comments are welcome. 

http://journal.frontiersin.org/article/10.3389/fmicb.2016.00949/full

The validated model and other tools developed for the prediction of biofilm inhibiting peptides are available

freely as a webserver at http://metagenomics.iiserb.ac.in/biofin/ and http://metabiosys.iiserb.ac.in/biofin/

ProInflam: a webserver for the prediction of proinflammatory antigenicity of peptides and proteins

Time to predict the proinflammatory antigenicity of peptides and proteins using a recent machine learning based tool 'ProInflam'.

A recent publication out from our lab. Please explore and write back to (sudheer@iiserb.ac.in) in case

of any problem. Comments are welcome. 

http://www.ncbi.nlm.nih.gov/pubmed/27301453

The prediction model for epitope mapping and similarity search are provided as a comprehensive webserver.

Available at http://metagenomics.iiserb.ac.in/proinflam/ and http://metabiosys.iiserb.ac.in/proinflam/

Prediction of peptidoglycan hydrolases- a new class of antibacterial proteins

Time to predict the peptidoglycan hydrolases using a recent machine learning based tool 'HyPe'.

A recent publication out from our lab. Please explore and write back to (ashok@iiserb.ac.in and drsanjivk@gmail.com) in case of any problem. Comments are welcome. 

https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-016-2753-8

The present tool helps in the identification and classification of novel peptidoglycan hydrolases from complete genomic or metagenomic ORFs. To our knowledge, this is the only tool available for the prediction of peptidoglycan hydrolases from genomic and metagenomic data.

Availability: http://metagenomics.iiserb.ac.in/hype/, http://metabiosys.iiserb.ac.in/hype/.

Metabolomics and drug discovery

Interesting article for those who are interested in the drug discovery using metabolomics approach. They have covered complete pipeline of drug discovery starting from the metaboloic data.

"Emerging applications of metabolomics in drug discovery and precision medicine" 

http://www.nature.com/nrd/journal/vaop/ncurrent/full/nrd.2016.32.html

Xenobiotics metabolism and gut microbes

The role of gut microbes in the metabolism of xenobiotics is known from almost three decades. It is one of the most important field now a days, as the activity and toxicity of xenobiotics is primarily dependent upon the gut microbial profile. The diverse and huge metabolic enzymes of gut microbes are the workhorses of this metabolic activity. The population specific differences in the gut microflora show well correlation with the activity of these gut microbes in modulating the biotransformation of these xenobiotics. 

Recently reports have shown the major impact of the gut microflora on the pharmacological properties of a drugs. Therefore, the gut metagenomic studies focusing on the gut metagenomic potential of these gut microbes will be crucial in the field of precision medicine. For more details you can go through the article published in nature reviews titled as "The microbial pharmacists within us: a metagenomic view of xenobiotic metabolism". The article is freely available at http://www.nature.com/nrmicro/journal/vaop/ncurrent/full/nrmicro.2016.17.html .