EpiCandIn: An open online resource for epidemiology of Candida infections in India.

Background & objectives Candida spp. cause candidiasis in humans under conditions disrupting the host defence. While Candida albicans is the most reported cause of candidiasis, there is a surge in the incidence of infections by non-albicans Candida species (NACs), such as C.

PBIT : A robust and comprehensive tool for screening pathogenic proteomes for drug targets and prioritizing vaccine candidates.

Rise of life-threatening superbugs, pandemics and epidemics warrants the need for cost-effective and novel pharmacological interventions. Availability of publicly available proteomes of pathogens supports development of high-throughput discovery platforms to prioritize potential drug-targets and develop testable hypothesis for pharmacological screening. The pipeline builder for identification of target (PBIT) was developed in 2016 and updated in 2021, with the purpose of accelerating the search for drug-targets by integration of methods like comparative and subtractive genomics, essentiality/virulence and druggability analysis.

Expanding the therapeutic options for Candida infections using novel inhibitors of secreted aspartyl proteases.

For widening the therapeutic options for Candida management, the druggability of Candida proteome was systematically investigated using an innovative pipeline of high-throughput data mining algorithms, followed by in vitro validation of the observations. Through this exercise, HIV-1 protease was found to share structural similarity with secreted aspartyl protease-3 (SAP3), a virulence protein of Candida. Using the molecular fingerprint of HIV-1 protease inhibitor GRL-09510, we performed virtual screening of peptidomimetic library followed by high-precision docking and MD simulations for discovery of SAP inhibitors.

CAMPR4: a database of natural and synthetic antimicrobial peptides.

There has been an exponential increase in the design of synthetic antimicrobial peptides (AMPs) for its use as novel antibiotics. Synthetic AMPs are substantially enriched in residues with physicochemical properties known to be critical for antimicrobial activity; such as positive charge, hydrophobicity, and higher alpha helical propensity. The current prediction algorithms for AMPs have been developed using AMP sequences from natural sources and hence do not perform well for synthetic peptides.