Systems-level assessments of protein-protein interaction (PPI) network dysfunctions are currently out-of-reach because approaches enabling proteome-wide identification, analysis, and modulation of context-specific PPI changes in native (unengineered) cells and tissues are lacking. Herein, we take advantage of chemical binders of maladaptive scaffolding structures termed epichaperomes and develop an epichaperome-based ‘omics platform, epichaperomics, to identify PPI alterations in disease. We provide multiple lines of evidence, at both biochemical and functional levels, demonstrating the importance of these probes to identify and study PPI network dysfunctions and provide mechanistically and therapeutically relevant proteome-wide insights. As proof-of-principle, we derive systems-level insight into PPI dysfunctions of cancer cells which enabled the discovery of a context-dependent mechanism by which cancer cells enhance the fitness of mitotic protein networks. Importantly, our systems levels analyses support the use of epichaperome chemical binders as therapeutic strategies aimed at normalizing PPI networks.

The recurrent and recent global outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has turned into a global concern which has infected more than 42 million people all over the globe, and this number is increasing in hours. Unfortunately, no vaccine or specific treatment is available, which makes it more deadly. A vaccine-informatics approach has shown significant breakthrough in peptide-based epitope mapping and opens the new horizon in vaccine development. In this study, we have identified a total of 15 antigenic peptides [including thymus cells (T-cells) and bone marrow or bursa-derived cells] in the surface glycoprotein (SG) of SARS-CoV-2 which is nontoxic and nonallergenic in nature, nonallergenic, highly antigenic and non-mutated in other SARS-CoV-2 virus strains. The population coverage analysis has found that cluster of differentiation 4 (CD4⁺) T-cell peptides showed higher cumulative population coverage over cluster of differentiation 8 (CD8⁺) peptides in the 16 different geographical regions of the world. We identified 12 peptides ((LTDEMIAQY, WTAGAAAYY, WMESEFRVY, IRASANLAA, FGAISSVLN, VKQLSSNFG, FAMQMAYRF, FGAGAALQI, YGFQPTNGVGYQ, LPDPSKPSKR, QTQTNSPRRARS and VITPGTNTSN) that are |$80\hbox{--} 90\%$| identical with experimentally determined epitopes of SARS-CoV, and this will likely be beneficial for a quick progression of the vaccine design. Moreover, docking analysis suggested that the identified peptides are tightly bound in the groove of human leukocyte antigen molecules which can induce the T-cell response. Overall, this study allows us to determine potent peptide antigen targets in the SG on intuitive grounds, which opens up a new horizon in the coronavirus disease (COVID-19) research. However, this study needs experimental validation by in vitro and in vivo.

Inhibition of fibrillation process and disaggregation of mature fibrils using small peptide are the promising remedial strategies to combat neurodegenerative diseases. However, designing peptide-based drugs to target β-sheet-rich amyloid has been a major challenge. The current work describes, for the first time, the amyloid inhibitory potential of the two short peptides (selected on the basis of predisposition of their amino acid residues toward β-sheet formation) using combination of biophysical, imaging methods, and docking approaches. Results showed that peptides employed different mechanisms to inhibit the amyloid fibrillation. Furthermore, they were also effective in blocking the amyloid fibrillation pathway. In contrary to the insulin fibrillar mesh, significantly less fibrillar species appeared in the presence of peptides, as confirmed by transmission electron microscopy. Circular dichroism analysis indicated that although peptides did not stabilize the native state of insulin, they inhibited amyloid aggregation by reducing the formation of β-sheet rich structures. Hemolytic assay revealed the non-hemolytic nature of the species formed when insulin was co-incubated with the peptides. Therefore, despite the inherent potential to form β-sheet structure, these peptides inhibited the amyloid formation and potentially can be used as therapeutics for the treatment of amyloid-related diseases.

Tuberculosis (TB) is one of deadly transmissible disease that causes death worldwide; however, only 10% of people infected with Mycobacteriumtuberculosis develop disease, indicating that host genetic factors may play key role in determining susceptibility to TB disease. In this way, the analysis of gene expression profiling of TB infected individuals can give us a snapshot of actively expressed genes and transcripts under various conditions. In the present study, we have analyzed microarray data set and compared the gene expression profiles of patients with different datasets of healthy control, latent infection, and active TB. We observed the transition of genes from normal condition to different stages of the TB and identified and annotated those genes/pathways/processes that have important roles in TB disease during its cyclic interventions in the human body. We identified 488 genes that were differentially expressed at various stages of TB and allocated to pathways and gene set enrichment analysis. These pathways as well as GSEA’s importance were evaluated according to the number of DEGs presents in both. In addition, we studied the gene regulatory networks that may help to further understand the molecular mechanism of immune response against the TB infection and provide us a new angle for future biomarker and therapeutic targets. In this study, we identified 26 leading hubs which are deeply rooted from top to bottom in the gene regulatory network and work as the backbone of the network. These leading hubs contains 31 key regulator genes, of which 14 genes were up-regulated and 17 genes were down-regulated. The proposed approach is based on gene-expression profiling, and network analysis approaches predict some unknown TB-associated genes, which can be considered (or can be tested) as reliable candidates for further (in vivo/in vitro) studies.