Short half-life is one of the key challenges in the field of therapeutic peptides. Various studies have reported enhancement in the stability of peptides using methods like chemical modifications, D-amino acid substitution, cyclization, replacement of labile aminos acids, etc. In order to study this scattered data, there is a pressing need for a repository dedicated to the half-life of peptides. To fill this lacuna, we have developed PEPlife (http://crdd.osdd.net/raghava/peplife), a manually curated resource of experimentally determined half-life of peptides. PEPlife contains 2229 entries covering 1193 unique peptides. Each entry provides detailed information of the peptide, like its name, sequence, half-life, modifications, the experimental assay for determining half-life, biological nature and activity of the peptide. We also maintain SMILES and structures of peptides. We have incorporated web-based modules to offer user-friendly data searching and browsing in the database. PEPlife integrates numerous tools to perform various types of analysis such as BLAST, Smith-Waterman algorithm, GGSEARCH, Jalview and MUSTANG. PEPlife would augment the understanding of different factors that affect the half-life of peptides like modifications, sequence, length, route of delivery of the peptide, etc. We anticipate that PEPlife will be useful for the researchers working in the area of peptide-based therapeutics.

Brassinosteroids (BRs) are a group of naturally occurring plant steroid hormones that can induce plant tolerance to various plant stresses by regulating ROS production in cells, but the underlying mechanisms of this scavenging activity by BRs are not well understood. This study investigated the effects of 28-homobrassinolide (28-HBL) seed priming on Brassica juncea seedlings subjected to the combined stress of extreme temperatures (low, 4 °C or high, 44 °C) and salinity (180 mM), either alone or supplemented with 28-HBL treatments (0, 10-6, 10-9, 10-12 M). The combined temperature and salt stress treatments significantly reduced shoot and root lengths, but these improved when supplemented with 28-HBL although the response was dose-dependent. The combined stress alone significantly increased H2O2 content, but was inhibited when supplemented with 28-HBL. The activities of superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APOX), glutathione reductase (GR), dehydroascorbate reductase (DHAR) and monodehydroascorbate reductase (MDHAR) increased in response to 28-HBL. Overall, the 28-HBL seed priming treatment improved the plant's potential to combat the toxic effects imposed by the combined temperature and salt stress by tightly regulating the accumulation of ROS, which was reflected in the improved redox state of antioxidants.

CancerPDF (Cancer Peptidome Database of bioFluids) is a comprehensive database of endogenous peptides detected in the human biofluids. The peptidome patterns reflect the synthesis, processing and degradation of proteins in the tissue environment and therefore can act as a gold mine to probe the peptide-based cancer biomarkers. Although an extensive data on cancer peptidome has been generated in the recent years, lack of a comprehensive resource restrains the facility to query the growing community knowledge. We have developed the cancer peptidome resource named CancerPDF, to collect and compile all the endogenous peptides isolated from human biofluids in various cancer profiling studies. CancerPDF has 14,367 entries with 9,692 unique peptide sequences corresponding to 2,230 unique precursor proteins from 56 high-throughput studies for ~27 cancer conditions. We have provided an interactive interface to query the endogenous peptides along with the primary information such as m/z, precursor protein, the type of cancer and its regulation status in cancer. To add-on, many web-based tools have been incorporated, which comprise of search, browse and similarity identification modules. We consider that the CancerPDF will be an invaluable resource to unwind the potential of peptidome-based cancer biomarkers. The CancerPDF is available at the web address http://crdd.osdd.net/raghava/cancerpdf/ .

Dengue virus (DENV) infection has increased worldwide, with over 400 million infections annually, and has become a serious public health concern. Several drug candidates, new and repurposed, have failed to meet the primary efficacy endpoints. We have recently shown that Aqueous Extract of the stem of Cocculus hirsutus (AQCH) was effective in vitro and in vivo against DENV and was safe in humans. We now report that an active ingredient of AQCH, Sinococuline, protects against the antibody-mediated secondary-DENV infection in the AG129 mouse model. DENV infection markers were assessed, viz. serum viremia and vital organs pathologies-viral load, proinflammatory cytokines and intestinal vascular leakage. The treatment with Sinococuline at 2.0 mg/kg/day; BID (twice a day), was the most effective in protecting the severely DENV-infected AG129 mice. Also, this dose effectively reduced serum viremia and tissue-viral load and inhibited the elevated expression levels of proinflammatory cytokines (TNF-α and IL-6) in several vital organs. Based on these findings, it could be explored further for pre-clinical and clinical developments for the treatment of dengue.

In this study, an attempt has been made to identify expression-based gene biomarkers that can discriminate early and late stage of clear cell renal cell carcinoma (ccRCC) patients. We have analyzed the gene expression of 523 samples to identify genes that are differentially expressed in the early and late stage of ccRCC. First, a threshold-based method has been developed, which attained a maximum accuracy of 71.12% with ROC 0.67 using single gene NR3C2. To improve the performance of threshold-based method, we combined two or more genes and achieved maximum accuracy of 70.19% with ROC of 0.74 using eight genes on the validation dataset. These eight genes include four underexpressed (NR3C2, ENAM, DNASE1L3, FRMPD2) and four overexpressed (PLEKHA9, MAP6D1, SMPD4, C11orf73) genes in the late stage of ccRCC. Second, models were developed using state-of-art techniques and achieved maximum accuracy of 72.64% and 0.81 ROC using 64 genes on validation dataset. Similar accuracy was obtained on 38 genes selected from subset of genes, involved in cancer hallmark biological processes. Our analysis further implied a need to develop gender-specific models for stage classification. A web server, CancerCSP, has been developed to predict stage of ccRCC using gene expression data derived from RNAseq experiments.