PBITV3 : 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. Since then, it has been used for identification of drugs and vaccine targets, safety profiling of multiepitope vaccines and mRNA vaccine construction against a broad-spectrum of pathogens. This tool has now been updated with functionalities related to systems biology and immuno-informatics and validated by analyzing 48 putative antigens of Mycobacterium tuberculosis documented in literature. PBITv3 available as both online and offline tools will enhance drug discovery against emerging drug-resistant infectious agents. PBITv3 can be freely accessed at http://pbit.bicnirrh.res.in/.

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. Wet-lab validation of the four shortlisted peptidomimetics revealed that two molecules, when used in combination with fluconazole, could significantly reduce the dosage of fluconazole required for 50% inhibition of Candida albicans. The SAP inhibitory activity of these peptidomimetics was confirmed through SAP assays and found to be on par with pepstatin A, a known peptidomimetic inhibitor of aspartyl proteases.

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. In this version of CAMP database, along with updating sequence information of AMPs, we have created separate prediction algorithms for natural and synthetic AMPs. CAMPR4 holds 24243 AMP sequences, 933 structures, 2143 patents and 263 AMP family signatures. In addition to the data on sequences, source organisms, target organisms, minimum inhibitory and hemolytic concentrations, CAMPR4 provides information on N and C terminal modifications and presence of unusual amino acids, as applicable. The database is integrated with tools for AMP prediction and rational design (natural and synthetic AMPs), sequence (BLAST and clustal omega), structure (VAST) and family analysis (PRATT, ScanProsite, CAMPSign). The data along with the algorithms of CAMPR4 will aid to enhance AMP research. CAMPR4 is accessible at http://camp.bicnirrh.res.in/.