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Background: Mammalian cysteine‐rich secretory proteins (CRISPs) are predominantly expressed in the male reproductive tract. Knockout mice lacking two or more CRISPs show defects in sperm transport, sperm–egg interaction and Ca2+ homeostasis. CRISPs play redundant and specific roles via their binding partners. To understand this, a comprehensive analysis of CRISP interactome needs to be undertaken. Objectives: This study aimed to analyse CRISP4 binding partners on the plasma membrane of rat caudal spermatozoa. Materials and methods: Total proteins from rat caudal spermatozoa were subjected to immunoprecipitation using anti‐CRISP4 antibody followed by liquid chromatography–mass spectrophotometry analysis. Plasma membrane localised proteins were shortlisted, and a key target was validated by co‐immunoprecipitation and co‐localisation. Co‐transfection followed by co‐immunoprecipitation was carried out for studying the interaction of full‐length as well as deletion mutants of CRISPs with human plasma membrane calcium ATPase, isoform b (hPMCA4b). Calcium assays were performed using Fura‐2‐AM. The cholesterol binding ability of different CRISPs was evaluated in silico. Results: The membrane‐specific interactome of rat CRISP4 (rCRISP4) from caudal spermatozoa revealed PMCA4b as a novel binding partner, and their interaction was validated in rat spermatozoa. Human CRISP1 (hCRISP1) and hCRISP3 also interacted with PMCA4b via the N‐terminal domain. Interestingly, hCRISP1 and rCRISP4 delayed PMCA4b‐mediated calcium extrusion but hCRISP3 did not. In silico analysis demonstrated that hCRISP1 and rCRISP4 have higher binding affinity towards cholesterol than hCRISP3. The secretion profile of different CRISPs also showed that the ratio of secreted to cell‐associated proteins was highest for hCRISP3. Conclusion: Our study identifies PMCA4b as a target of multiple mammalian CRISPs and unravels a new role of CRISPs in regulating calcium homeostasis. Differences in the interaction of different CRISPs with cholesterol may regulate their enrichment in the lipid rafts and redistribution in the membrane post‐capacitation, thereby affecting their interaction with PMCA4b. [ABSTRACT FROM AUTHOR]

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/. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Over the recent years, FSHR has become an important target for development of fertility regulating agents, as impairment of FSH-FSHR interaction can lead to subfertility or infertility. In our previous study, we identified a 9-mer peptide (FSHβ (89–97)) that exhibited FSHR antagonist activity. The histopathological and biochemical observations indicated, in addition to FSHR antagonism, a striking resemblance to a PCOS-like state. These observations led us to hypothesize that use of FSHR antagonists can trigger a PCOS-like state. In the present study, to validate this hypothesis, we performed qRT-PCR validation using ovarian tissue samples from our previous study. Expression of three genes known to be differentially expressed in PCOS was evaluated and found to be similar to the PCOS state. To further test the hypothesis, theoretical simulations were carried out by using the human menstrual cycle model available in the literature. Model simulations for FSHR antagonism were indicative of increased testosterone levels, increased ratio of luteinizing hormone/follicle stimulating hormone, and stockpiling of secondary follicles, which are typical characteristics of PCOS. The findings of this study will be relevant while reviewing the utility of FSHR antagonists for fertility regulation and reproductive medicine. Abbreviations: FSH: Follicle-stimulating hormone; FSHR: Follicle-stimulating hormone receptor; cAMP: Cyclic adenosine 3'5' monophosphate; PKA: Protein kinase A; PI3K: Phosphoinositide 3-kinase; PKB: protein kinase B; ERK1/2: Extracellular signal-regulated protein kinase 1/2; MAPK: Mitogen-activated protein kinases; T: testosterone; E2: estradiol; PCOS: Polycystic ovarian syndrome; LH: luteinizing hormone; Lhcgr: luteinizing hormone/choriogonadotropin receptor; CYP17A1: cytochrome P450 family 17 subfamily A member 1; Inhba: inhibin subunit beta A; qRT-PCR: Real-Time quantitative reverse transcription polymerase chain reaction; FSHβ: Follicle-stimulating hormone β subunit; Ct: Cycle threshold; Rn18s: Rattus norvegicus 18S ribosomal RNA [ABSTRACT FROM AUTHOR]