repositioning of different chemical classes for anti tb virtual screening
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Repositioning Of Different Chemical Classes For Anti TB Virtual Screening. Project Review By Ayisha Safeeda TCOF 3.5. Pesticide Repositioning For TB Drug Discovery. Aim - PowerPoint PPT PresentationTRANSCRIPT
Repositioning Of Different Chemical Classes For Anti TB Virtual Screening
Project Review By
Ayisha SafeedaTCOF 3.5
Pesticide Repositioning For TB Drug Discovery
Aim
To create a database of pesticide molecules showing anti
tubercular activity and do virtual screening to find the lead compounds.
Data Collection
Around thousand pesticides effective against mycobacterium tuberculosis have been collected from various literatures;
Journal of Sciences, Islamic Republic of Iran
Synthesis of some New Thiosemicarbazide and 1,3,4-Thiadiazole Heterocycles Bearing Benzo[b]Thiophene Nucleus as a Potent Antitubercular and Antimicrobial Agents
S.L. Vasoya, D.J. Paghdar, P.T. Chovatia, and H.S. Joshi*
Understanding Tuberculosis - New Approaches to Fighting Against Drug
Resistance
Cinnamic Derivatives in Tuberculosis
Prithwiraj De1,2, Damien Veau1,2, Florence Bedos-Belval1,2, Stefan Chassaing1,2 and Michel Baltas1,2
RASAYAN J.Chem. Vol4
Toxicity risk assessment of some novel quinoxalines
A.Puratchikody1, Mukesh Doble2 and N.Ramalakshmi3,
International Journal of Pharmaceutical Sciences and Drug Research 2010;
Pyrazoline Derivatives: A Worthy Insight into the Recent Advances and
potential pharmacological activities
Md. Azizur Rahman1*, Anees A. Siddiqui2
Etc.,
and databases like
ChEBI- The database and ontology of Chemical Entities of Biological Interest
pubchem
EPA, environmental protection agency search engine
Are also resourceful.
The SDF file of around 200 pesticide structures are created by drawing using the
tool Marvin sketch. around 400 molecules are downloaded from pubchem and
chEBI.
Model generation
AID 1332Pubchem bioassay dataset aid 1332 is used for model generation
Power MVThe 179 descriptors are generated using the tool power MV
Waikato environment for knowledge analysisWeka is a collection of machine learning algorithms for data mining task.
Random forest classifier is used to build the model but higher FP rate and
low accuracy leads to the use of cost sensitive classifier.
Not the end
The work, tuning and deriving the best model will continue…
The screened active molecules will go onto the clustering process
And selected molecules will further go for clinical trials
Building a modelaid1332
Screening processUsing pesticides
Clustering processActive molecules
are clustered
Target based drug discovery
Synthesis of selected molecules
& clinical trials
Acknowledgement
CSIR-OSDD research unit
Dr. U C A Jaleel
Prof Dr Samir K Brahmachari
Dr Bheemarao Ugarkar
All TCOF 3 members
family