Anti-flavi: A Web Platform to Predict Inhibitors of Flaviviruses Using QSAR and Peptidomimetic Approaches.

ABSTRACT: Flaviviruses are arboviruses, which comprises more than 70 viruses, covering broad geographic ranges, and responsible for significant mortality and morbidity globally. Due to the lack of efficient inhibitors targeting flaviviruses, the designing of novel and efficient anti-flavi agents is an important problem. Therefore, in the current study, we have developed a dedicated prediction algorithm anti-flavi, to identify inhibition ability of chemicals and peptides against flaviviruses through quantitative structure-activity relationship based method. We extracted the non-redundant 2168 chemicals and 117 peptides from ChEMBL and AVPpred databases, respectively, with reported IC₅₀ values. The regression based model developed on training/testing datasets of 1952 chemicals

SUBMITTER: Rajput A 

PROVIDER: S-EPMC6305493 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature