Biology subjects

Shanker, V.

Publications and source records attributed to Shanker, V..

3 recordsLinked to original sources

bioRxiv2024

Identification of Covalent Cyclic Peptide Inhibitors Targeting Protein-Protein Interactions Using Phage Display

Peptide macrocycles are promising therapeutics for a variety of disease indications due to their overall metabolic stability and potential to make highly selective binding interactions with targets. Recent advances in covalent macrocycle peptide discovery, driven by phage and mRNA display methods, have enabled the rapid identification of highly potent and selective molecules from large libraires of diverse macrocycles. However, there are currently limited examples of macrocycles that can be used to disrupt protein-protein interactions and even fewer examples that function by formation of a covalent bond to a target protein. In this work, we describe a directed counter-selection method that enables identification of covalent macrocyclic ligands targeting a protein-protein interaction using a phage display screening platform. This method utilizes binary and ternary screenings of a chemically modified phage display library, employing the stable and weakly reactive aryl fluorosulfate electrophile. We demonstrate the utility of this approach using the SARS-CoV-2 Spike-ACE2 protein-protein interaction and identify multiple covalent macrocyclic inhibitors that disrupt this interaction. The resulting compounds displayed antiviral activity against live virus that was irreversible after washout due to the covalent binding mechanism. These results highlight the potential of this screening platform for developing covalent macrocyclic drugs that disrupt protein-protein interactions with long lasting effects.

microbiology↗

bioRxiv2020

Discordant transcriptional signatures of mitochondrial genes in Parkinson's disease human myeloid cells

An increasing number of identified Parkinsons disease (PD) risk loci contain genes highly expressed in innate immune cells, yet their potential role in pathological mechanisms is not obvious. We have generated transcriptomic profiles of CD14+ monocytes from 230 individuals with sporadic PD and age-matched healthy subjects. We identified dysregulation of genes involved in mitochondrial and proteasomal function. We also generated transcriptomic profiles of primary microglia from autopsied brains of 55 PD and control subjects and observed discordant transcriptomic signatures of mitochondrial genes in PD monocytes and microglia. We further identified PD susceptibility genes, whose expression, relative to each risk allele, is altered in monocytes. These findings reveal that transcriptomic mitochondrial alterations are detectable in PD monocytes and are distinct from brain microglia, and facilitates efforts to understand the roles of myeloid cells in PD.

neuroscience↗

bioRxiv2018

Identification of Key Differentially Expressed MicroRNAs in Cancer Patients Through Pan-cancer Analysis

A number of microRNAs (miRNAs) functioning in gene silencing have been associated with cancer progression. However, common expression patterns of abnormally expressed miRNAs and their potential roles in multiple cancer types have not yet been evaluated. To minimize the difference of patients, we collected miRNA sequencing data of 575 patients with tumor and adjacent non-tumorous tissues from 14 cancer types from The Cancer Genome Atlas (TCGA), and performed differential expression analysis using DESeq2 and edgeR. The results showed that cancer types can be grouped based on the distribution of miRNAs with different expression patterns. We found 81 significantly differentially expressed miRNAs (SDEmiRNAs) unique to one of the 14 cancers may affect patient survival rate, and 21 key SDEmiRNAs (nine overexpressed and 12 under-expressed) associated with at least eight cancers and enriched in more than 60% of patients per cancer, including four newly identified SDEmiRNAs (hsa-mir-4746, hsa-mir-3648, hsa-mir-3687, and hsa-mir-1269a). The downstream effect of these 21 SDEmiRNAs on cellular functions was evaluated through enrichment and pathway analysis of 7,186 protein-coding gene targets from literature mining with known differential expression profiles in cancers. It enables identification of their functional similarity in cell proliferation control across a wide range of cancers and to build common regulatory networks over cancer-related pathways. This is validated by construction of a regulatory network in PI3K pathway. This study provides evidence of the value of further analysis on SDEmiRNAs as potential biomarkers and therapeutic targets for cancer diagnosis and treatment.

bioinformatics↗