Close Icon
Scheduled maintenance work on Thursday 19th January 2016 between 00:00 and 06:00 hours (GMT)
One of our internet service providers will be performing maintenance upgrade work on their network which means you may experience an intermittent reduction in performance, with the possibility of our publishing platform services being offline temporarily. If you have any questions, please use the feedback button on this page. We apologise for any inconvenience this might cause and thank you for your patience.

Molecular BioSystems

Research at the interface of chemistry and biology: chemical biology, -omics sciences and systems biology.


Integrated machine learning, molecular docking and 3D-QSAR based approach for identification of potential inhibitors of trypanosomal N-myristoyltransferase

Corresponding authors
Molecular and Structural Biology Division, CSIR-Central Drug Research Institute, Lucknow 226031, India
Division of Parasitology, CSIR-Central Drug Research Institute, Lucknow, India
Academy of Scientific and Innovative Research (AcSIR), CSIR-Central Drug Research Institute, Campus, Lucknow 226031, India
Mol. BioSyst., 2016,12, 3711-3723

DOI: 10.1039/C6MB00574H
Received 08 Aug 2016, Accepted 12 Oct 2016
First published online 12 Oct 2016
Please wait while Download options loads

Supplementary Info