The emergence of antifungal drug resistance in Candida species has led to increased morbidity and mortality in immunocompromised patients. Understanding species distribution and antifungal drug resistance patterns is an essential step for novel drug development. A systematic review was performed addressing this challenge in India with keywords inclusive of ‘Candida’, ‘Antifungal Drug Resistance’, ‘Candidemia’, ‘Candidiasis’ and ‘India’. A total of 106 studies (January 1978-March 2020) from 20 Indian states were included. Of over 11,429 isolates, Candida albicans was the major species accounting for 37.95% of total isolates followed by C. tropicalis (29.40%), C. glabrata (11.68%) and C. parapsilosis (8.36%). Rates of antifungal resistance were highest in non-albicans Candida (NAC) species - C. haemuloni (47.16%), C. krusei (28.99%), C. lipolytica (28.89%) and C. glabrata (20.69%). Approximately 10.34% isolates of C. albicans were observed to be drug-resistant. Candida species were frequently resistant to certain azoles (ketoconazole-22.2%, miconazole–22.1% and fluconazole–21.8%). In conclusion, the present systematic review illustrates the overall distribution and antifungal resistance pattern of Candida species among the Indian population that could be helpful in the future for the formation of treatment recommendations for the region but also elsewhere.

The recent outbreaks of Zika virus and the absence of a specific therapy have necessitated to identify T-cell-stimulating antigenic peptides as potential subunit vaccine candidates. The translated ssRNA (+) genome of Zika virus was explored in EMBOSS antigenic and VaxiJen to predict 63 peptides as potential antigens. Three MHC-II binding peptide prediction tools, viz. NetMHCIIpan, PREDIVAC and immune epitope database (IEDB) were employed in consensus on 63 antigenic peptides to propose 14 T-helper cell epitopes. Similarly, analysis on 63 antigenic peptides through NetMHC, NetCTL and IEDB MHC-I binding peptide prediction tool led to identification of 14 CTL epitopes. Seven T-cell epitopes, C:44-66, M:135-149, NS2A:124-144, NS3:421-453, NS3:540-554, NS4B:90-134 and NS4B:171-188, are observed to share overlapping MHC-I and MHC-II binding motifs and hence, are being proposed to constitute minimum T-cell antigens to elicit protective T-cell immune response against Zika. Three of them, C:44-66, NS3:421-453 and NS3:540-554 are identified to be conserved across all the selected strains of Zika virus. Moreover, the 21 T-cell epitopes are non-self to humans and exhibited good coverage in variable populations of 14 geographical locations. Therefore, 21 T-cell epitopes are proposed as potential subunit vaccines against Zika virus.

The emergence of multidrug‐resistant strains of Candida albicans has become a global threat mostly due to co‐infection with immune‐compromised patients leading to invasive candidiasis. The life‐threatening form of the disease can be managed quickly and effectively by drug repurposing. Thus, the study used in silico approaches to evaluate Food and Drug Administration (FDA) approved drugs against three drug targets—TRR1, TOM40, and YHB1. The tertiary structures of three drug targets were modeled, refined, and evaluated for their structural integrity based on PROCHECK, ERRAT, and PROSA. High‐throughput virtual screening of FDA‐approved drugs (8815), interaction analysis, and energy profiles had revealed that DB01102 (Arbutamine), DB01611 (Hydroxychloroquine), and DB09319 (Carindacillin) exhibited better binding affinity with TRR1, TOM40, and YHB1, respectively. Notably, the molecular dynamic simulation explored that Gln45, Thr119, and Asp288 of TRR1; Thr107 and Ser121 of TOM40; Arg193, Glu213, and Ser228 of YHB1 are crucial residues for stable drug‐target interaction. Additionally, it also prioritized Arbutamine‐TRR1 as the best drug‐target complex based on MM‐PBSA (−52.72 kcal/mol), RMSD (2.43 Å), and radius of gyration (−21.49 Å) analysis. In‐depth, PCA results supported the findings of molecular dynamic simulations. Interestingly, the conserved region (>70%) among the TRR1 sequences from pathogenic Candida species indicated the effectiveness of Arbutamine against multiple species of Candida as well. Thus, the study dispenses new insight and enriches the understanding of developing an advanced technique to consider potential antifungals against C. albicans. Nonetheless, a detailed experimental validation is needed to investigate the efficacy of Arbutamin against life‐threatening candidiasis.

Psoriasis is a systemic hyperproliferative inflammatory skin disorder, although rarely fatal but significantly reduces quality of life. Understanding the full genetic component of the disease association may provide insight into biological pathways as well as targets and biomarkers for diagnosis, prognosis and therapy. Studies related to psoriasis associated genes and genetic markers are scattered and not easily amendable to data-mining. To alleviate difficulties, we have developed dbGAPs an integrated knowledgebase representing a gateway to psoriasis associated genomic data. The database contains annotation for 202 manually curated genes associated with psoriasis and its subtypes with cross-references. Functional enrichment of these genes, in context of Gene Ontology and pathways, provide insight into their important role in psoriasis etiology and pathogenesis. The dbGAPs interface is enriched with an interactive search engine for data retrieval along with unique customized tools for Single Nucleotide Polymorphism (SNP)/indel detection and SNP/indel annotations. dbGAPs is accessible at http://www.bmicnip.in/dbgaps/.