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Biology subjects

Srikrishnan, S.

Publications and source records attributed to Srikrishnan, S..

2 recordsLinked to original sources

Targeting an evolutionarily conserved "E-L-L" motif in the spike protein to develop a small molecule fusion inhibitor against SARS-CoV-2

As newer variants of SARS-CoV-2 continue to pose major threats to global human health and economy, identifying novel druggable antiviral targets is the key towards sustenance. Here, we identify an evolutionary conserved "E-L-L" motif present within the HR2 domain of all human and non-human coronavirus spike (S) proteins that play a crucial role in stabilizing the post-fusion six-helix bundle (6-HB) structure and thus, fusion-mediated viral entry. Mutations within this motif reduce the fusogenicity of the S protein without affecting its stability or membrane localization. We found that posaconazole, an FDA-approved drug, binds to this "E-L-L" motif resulting in effective inhibition of SARS-CoV-2 infection in cells. While posaconazole exhibits high efficacy towards blocking S protein-mediated viral entry, mutations within the "E-L-L" motif rendered the protein completely resistant to the drug, establishing its specificity towards this motif. Our data demonstrate that posaconazole restricts early stages of infection through specific inhibition of membrane fusion and viral genome release into the host cell and is equally effective towards all major variants of concerns of SARS-CoV-2 including beta, kappa, delta, and omicron. Together, we show that this conserved essential "E-L-L" motif is an ideal target for the development of prophylactic and therapeutic interventions against SARS-CoV-2.

biochemistry↗

Transcriptomic-based quantification of the epithelial-hybrid-mesenchymal spectrum across biological contexts

Epithelial-mesenchymal plasticity (EMP) underlies embryonic development, wound healing, and cancer metastasis and fibrosis. Cancer cells exhibiting EMP often have more aggressive behavior, characterized by drug resistance, and tumor-initiating and immuno-evasive traits. Thus, the EMP status of cancer cells can be a critical indicator of patient prognosis. Here, we compare three distinct transcriptomic-based metrics - each derived using a different gene list and algorithm - that quantify the EMP spectrum. Our results for 96 cancer-related RNA-seq datasets reveal a high degree of concordance among these metrics in quantifying the extent of EMP. Moreover, each metric, despite being trained on cancer expression profiles, recapitulates the expected changes in EMP scores for non-cancer contexts such as lung fibrosis and cellular reprogramming into induced pluripotent stem cells. Thus, we offer a scoring platform to quantify the extent of EMP in vitro and in vivo for diverse biological applications including cancer.

bioinformatics↗