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Vilar, S.

Publications and source records attributed to Vilar, S..

2 recordsLinked to original sources

One Year of SARS-CoV-2: How Much Has the Virus Changed?

SARS-CoV-2 coronavirus has caused a world-wide crisis with profound effects on both healthcare and the economy. In order to combat the COVID-19 pandemic, research groups have shared viral genome sequence data through the GISAID initiative. We collected and computationally profiled [~]223,000 full SARS-CoV-2 proteome sequences from GISAID over one year for emergent nonsynonymous mutations. Our analysis shows that SARS-CoV-2 proteins are mutating at substantially different rates, with most viral proteins exhibiting little mutational variability. As anticipated, our calculations capture previously reported mutations occurred in the first period of the pandemic, such as D614G (Spike), P323L (NSP12), and R203K/G204R (Nucleocapsid), but also identify recent mutations like A222V and L18F (Spike) and A220V (Nucleocapsid). Our comprehensive temporal and geographical analyses show two periods with different mutations in the SARS-CoV-2 proteome: December 2019 to June 2020 and July to November 2020. Some mutation rates differ also by geography; the main mutations in the second period occurred in Europe. Furthermore, our structure-based molecular analysis provides an exhaustive assessment of mutations in the context of 3D protein structure. Emerging sequence-to-structure data is beginning to reveal the site-specific mutational tolerance of SARS-CoV2 proteins as the virus continues to spread around the globe.

bioinformatics↗

The Kinase Chemogenomic Set (KCGS): An open science resource for kinase vulnerability identification

We describe the assembly and annotation of a chemogenomic set of protein kinase inhibitors as an open science resource for studying kinase biology. The set only includes inhibitors that show potent kinase inhibition and a narrow spectrum of activity when screened across a large panel of kinase biochemical assays. Currently, the set contains 187 inhibitors that cover 215 human kinases. The kinase chemogenomic set (KCGS) is the most highly annotated set of selective kinase inhibitors available to researchers for use in cell-based screens.

cell biology↗