Searching across hundreds of databases
This service exclusively searches for literature that cites resources. Please be aware that the total number of searchable documents is limited to those containing RRIDs and does not include all open-access literature.
Multi-drug resistant in Mycobacterium tuberculosis (M.tb) is considered as major bottleneck in the treatment and cure of tuberculosis (TB). Several anti-tubercular drugs fail in its efficacy due to drug-resistant M.tb developed mechanism for resistance. So, research across globe has been carried out to develop effective anti-TB drugs to improve the treatment of these strains. Traditional drug development methods have been proved unsuccessful as it fails to develop a broad-spectrum drug due to lack of structure based approach. Several studies have been conducted in this regard and identified several drug target sites that influence drug-resistant M.tb strains. In this study, the attempt was to study the interaction between the protein Arabinosyltransferase C with the two existing drugs (Ethambutol and Isoniazid) and five modified molecules derived from Ethambutol by calculating their binding affinity and mode of binding through molecular docking study using AutoDock 4. From the comparison study of the existing drug (EMB and INH) and the five proposed modified molecules (Emb1, Emb2, Emb3, Emb4 and Emb5), it is analysed that Emb1 and Emb3 with binding affinities -5.77 kcal/mol and -5.13 kcal/mol respectively can be considered as potential inhibitors of Arabinosyltransferase C in Mycobacterium tuberculosis which is responsible for cell wall synthesis. The facts provided may be further verified experimentally for future drug discovery process to make a stand against tuberculosis and contribute an advance research for worthy antimycobacterial strategies.
Welcome to the FDI Lab - SciCrunch.org Resources search. From here you can search through a compilation of resources used by FDI Lab - SciCrunch.org and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that FDI Lab - SciCrunch.org has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on FDI Lab - SciCrunch.org then you can log in from here to get additional features in FDI Lab - SciCrunch.org such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
You can save any searches you perform for quick access to later from here.
We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.
If you are logged into FDI Lab - SciCrunch.org you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the facets that you can filter your papers by.
From here we'll present any options for the literature, such as exporting your current results.
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.
Year:
Count:
The SciCrunch Infrastructure was developed as a cooperative data platform to be used by diverse communities in making data more FAIR.
scicrunch.org
