Biology subjects

Prescott, L.

Publications and source records attributed to Prescott, L..

3 recordsLinked to original sources

bioRxiv2022

Alphavirus nsP2 protease structure and cleavage prediction: Possible relevance to the pathogenesis of viral arthritis

Alphaviruses are a diverse genus of arboviruses capable of infecting many vertebrates including humans. Human infection is common in equatorial and subtropical regions and is often accompanied by arthralgia or encephalitis depending on viral lineage. No antivirals or vaccines have been approved, and many alphavirus lineages have only recently been discovered and classified. Alphavirus nsP2 protease is an important virulence factor yet is commonly thought to be a simple papain-like protease which only cleaves viral polyproteins. Here, I reveal novel molecular mechanisms of these proteases via sequence and predicted structure alignment and propose novel cellular mechanisms for the pathogenesis of viral arthritis by predicting which human proteins are likely cleaved by these proteases. In addition to the known primary cysteine mechanism in all alphaviruses and a secondary serine mechanism documented in chikungunya virus (CHIKV), I discovered secondary cysteine and threonine mechanisms exist in many other alphaviruses and that these secondary mechanisms coevolve with their viral polyprotein cleavages. As for cleavage prediction, neural networks trained on 93 different putative viral polyprotein cleavages achieved a Matthews correlation coefficient of 0.965, and, when applied to the human proteome, predicted that hundreds of proteins may be vulnerable. Notable pathways likely affected by cleavages include the cytoskeleton and extracellular matrix, antiproteases, protein translation/folding/glycosylation/ubiquitination, cellular differentiation, inflammation, and vesicle trafficking, hinting that this viral protease is a more important virulence factor than previously believed.

bioinformatics↗

bioRxiv2021

SARS-CoV-2 PLpro whole human proteome cleavage prediction and enrichment/depletion analysis

A novel coronavirus (SARS-CoV-2) has caused a pandemic that has killed millions of people, worldwide vaccination and herd immunity are still far away, and few therapeutics are approved by regulatory agencies for widespread use. The coronavirus 3-chymotrypsin-like protease (3CLpro) is a commonly investigated target in COVID-19, however less work has been directed toward the equally important papain-like protease (PLpro). PLpro is less characterized due to its fewer and more diverse cleavages in coronavirus proteomes and the assumption that it mainly modulates host pathways with its deubiquitinating activity. Here, I extend my previous work on 3CLpro human cleavage prediction and enrichment/depletion analysis to PLpro.[1] Using three sets of neural networks trained on different taxonomic ranks of dataset with a maximum of 463 different putative PLpro cleavages, Matthews correlation coefficients of 0.900, 0.948, and 0.966 were achieved for Coronaviridae, Betacoronavirus, and Sarbecovirus, respectively. I predict that more than 1,000 human proteins may be cleaved by PLpro depending on diversity of the training dataset and that many of these proteins are distinct from those previously predicted to be cleaved by 3CLpro. PLpro cleavages are similarly nonrandomly distributed and result in many annotations shared with 3CLpro cleavages including ubiquitination, poly(A) tail and 5 cap RNA binding proteins, helicases, and endogenous viral proteins. Combining PLpro with 3CLpro cleavage predictions, additional novel enrichment analysis was performed on known substrates of cleaved E3 ubiquitin ligases with results indicating that many pathways including viral RNA sensing are affected indirectly by E3 ligase cleavage independent of traditional PLpro deubiquitinating activity. As with 3CLpro, PLpro whole proteome cleavage prediction revealed many novel potential therapeutic targets against coronaviruses, although experimental verification is similarly required.

bioinformatics↗

bioRxiv2020

SARS-CoV-2 3CLpro Whole Human Proteome Cleavage Prediction and Enrichment/Depletion Analysis

A novel coronavirus (SARS-CoV-2) has devastated the globe as a pandemic that has killed more than 1,600,000 people. Widespread vaccination is still uncertain, so many scientific efforts have been directed toward discovering antiviral treatments. Many drugs are being investigated to inhibit the coronavirus main protease, 3CLpro, from cleaving its viral polyprotein, but few publications have addressed this proteases interactions with the host proteome or their probable contribution to virulence. Too few host protein cleavages have been experimentally verified to fully understand 3CLpros global effects on relevant cellular pathways and tissues. Here, I set out to determine this proteases targets and corresponding potential drug targets. Using a neural network trained on cleavages from 388 coronavirus proteomes with a Matthews correlation coefficient of 0.983, I predict that a large proportion of the human proteome is vulnerable to 3CLpro, with 4,460 out of approximately 20,000 human proteins containing at least one putative cleavage site. These cleavages are nonrandomly distributed and are enriched in the epithelium along the respiratory tract, brain, testis, plasma, and immune tissues and depleted in olfactory and gustatory receptors despite the prevalence of anosmia and ageusia in COVID-19 patients. Affected cellular pathways include cytoskeleton/motor/cell adhesion proteins, nuclear condensation and other epigenetics, host transcription and RNAi, ribosomal stoichiometry and nascent-chain detection and degradation, coagulation, pattern recognition receptors, growth factors, lipoproteins, redox, ubiquitination, and apoptosis. This whole proteome cleavage prediction demonstrates the importance of 3CLpro in expected and nontrivial pathways affecting virulence, lead me to propose more than a dozen potential therapeutic targets against coronaviruses, and should therefore be applied to all viral proteases and subsequently experimentally verified.

bioinformatics↗