Drug designing against mycobacterium tuberculosis using computer-aided drug design (Record no. 4940)

MARC details
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fixed length control field 02713nam a22001817a 4500
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control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220107122808.0
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Transcribing agency
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Personal name Praseetha Prabhakaran (92213009)
9 (RLIN) 8320
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Title Drug designing against mycobacterium tuberculosis using computer-aided drug design
502 ## - DISSERTATION NOTE
Degree type Master of Science in Computational Science
Name of granting institution 2013-2015
Year degree granted EXT
-- T.K Manoj Kumar
-- Samir K Brahmachari (Professor)
Miscellaneous information "J.C Bose National Fellow, CSIR-IGIB, Academy Professor, AcSIR, Chief Mentor, OSDD"
520 ## - SUMMARY, ETC.
Summary, etc. <br/>Tuberculosis is a chronic infectious disease caused by the bacterium Mycobacterium tuberculosis, first identified by the renowned German physician Robert Koch in 1882. The treatment of tuberculosis remains a constraint for patients and a heavy burden for the entire health system. Multidrug resistant TB (MDR TB) is a form of TB that does not respond to the standard six month treatment of first line drugs. It can take two years to treat with drugs that are more toxic, and 100 times more expensive. Extensively drug resistant (XDR TB) is a form of TB caused by bacteria resistant to almost all the effective drugs. While tuberculosis had long been ceased as a medical problem of the first order, with the onset of AIDS (Acquired Immuno Deficiency Syndrome), infectious disease again requires special attention. The effectiveness of current therapeutic regimens for Mycobacterium tuberculosis(Mtb) is diminished by the need for prolonged therapy and the rise of drug resistant/tolerant strains. This global health threat, despite decades of basic research and a wealth of legacy knowledge, is due to a lack of systems level understanding that can innovate the process of fast acting and high efficacy drug discovery [1]. The work started with generating a library of compounds from various databases like Drug Bank, PubChem, ChEMBL, Chemspider etc and their docking by using softwares Autodock 4.2 tools (version 1.5.6) and Autodock Vina. Pymol (version 1.7.4) was installed and learnt to use for the visualization of molecules. We selected different compounds for their resemblance with any known drug or antibiotic and then performing docking. I was provided with a specific set of targets involved in Mycobacterium tuberculosis metabolism. We selected two proteins, in which one is involved in folate biosynthesis and other is involved in interconversion of dCTP and dUTP in Mycobacterium tuberculosis (PDB ID: 1NBU and 2QLP) were docked with the library of compounds generated through various databases.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element APPLIED COMPUTING
9 (RLIN) 8321
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Topical term or geographic name entry element PHYSICAL SCIENCES AND ENGINEERING
9 (RLIN) 8322
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Topical term or geographic name entry element CHEMISTRY
9 (RLIN) 8323
942 ## - ADDED ENTRY ELEMENTS (KOHA)
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    Dewey Decimal Classification     IIITM-K Kerala University of Digital Sciences, Innovation and Technology Knowledge Centre 02/03/2016   R-656 02/03/2016 02/03/2016 Project Reports