Biology subjects

Linde, E.

Publications and source records attributed to Linde, E..

3 recordsLinked to original sources

bioRxiv2023

Pandemic preparedness through genomic surveillance: Overview of mutations in SARS-CoV-2 over the course of COVID-19 outbreak

Genomic surveillance is a vital strategy for preparedness against the spread of infectious diseases and to aid in development of new treatments. In an unprecedented effort, millions of samples from COVID-19 patients have been sequenced worldwide for SARS-CoV-2. Using more than 8 million sequences that are currently available in GenBanks SARS-CoV-2 database, we report a comprehensive overview of mutations in all 26 proteins and open reading frames (ORFs) from the virus. The results indicate that the spike protein, NSP6, nucleocapsid protein, envelope protein and ORF7b have shown the highest mutational propensities so far (in that order). In particular, the spike protein has shown rapid acceleration in mutations in the post-vaccination period. Monitoring the rate of non-synonymous mutations (Ka) provides a fairly reliable signal for genomic surveillance, successfully predicting surges in 2022. Further, the external proteins (spike, membrane, envelope, and nucleocapsid proteins) show a significant number of mutations compared to the NSPs. Interestingly, these four proteins showed significant changes in Ka typically 2 to 4 weeks before the increase in number of human infections ("surges"). Therefore, our analysis provides real time surveillance of mutations of SARS-CoV-2, accessible through the project website http://pandemics.okstate.edu/covid19/. Based on ongoing mutation trends of the virus, predictions of what proteins are likely to mutate next are also made possible by our approach. The proposed framework is general and is thus applicable to other pathogens. The approach is fully automated and provides the needed genomic surveillance to address a fast-moving pandemic such as COVID-19.

genomics↗

bioRxiv2023

Identification and evaluation of small-molecule inhibitors against the dNTPase SAMHD1 via a comprehensive screening funnel

Sterile alpha motif and histidine-aspartic acid domain containing protein-1 (SAMHD1) is a deoxynucleoside triphosphate (dNTP) triphosphohydrolase central to cellular nucleotide pool homeostasis. Recent literature has also demonstrated how SAMHD1 can detoxify chemotherapy metabolites thereby controlling their clinical responses. To further understand SAMHD1 biology and to investigate the potential of targeting this enzyme as a neoadjuvant to existing chemotherapies we set out to discover selective small molecule-based inhibitors of SAMHD1. Here we report a discovery pipeline encompassing a biochemical screening campaign and a set of complementary biochemical, biophysical, and cell-based readouts for further characterisation of the screen output. The identified hit compound TH6342 and its analogues, accompanied by their inactive negative control analogue TH7126, demonstrated specific, low M potency in inhibiting the hydrolysis of both natural substrates and nucleotide analogue therapeutics, shown using complementary enzyme-coupled and direct enzymatic activity assays. Their mode of inhibition was subsequently detailed by coupling kinetic studies with thermal shift assays, where TH6342 and analogues were shown to engage with pre-tetrameric SAMHD1 and deter the oligomerisation and allosteric activation of SAMHD1 without occupying nucleotide binding pockets. We further outline the development and application of multiple cellular assays for assessing cellular target engagement and associated functional effects, including CETSA and an in-cell dNTP hydrolase activity assay, which highlighted future optimisation strategies of this chemotype. In summary, with a novel mode of inhibition, TH6342 and analogues broaden the set of tool compounds available in deciphering SAMHD1 enzymology and functions, and furthermore, the discovery pipeline reported herein represents a thorough framework for future SAMHD1 inhibitor development. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=96 SRC="FIGDIR/small/524275v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@dc706forg.highwire.dtl.DTLVardef@59a9b4org.highwire.dtl.DTLVardef@9473e2org.highwire.dtl.DTLVardef@4427dc_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2022

Future COVID-19 surges prediction based on SARS-CoV-2 mutations surveillance

COVID19 has aptly revealed that airborne viruses such as SARS-CoV-2 with the ability to rapidly mutate, combined with high rates of transmission and fatality can cause a deadly world-wide pandemic in a matter of weeks.1 Apart from vaccines and post-infection treatment options, strategies for preparedness will be vital in responding to the current and future pandemics. Therefore, there is wide interest in approaches that allow predictions of increase in infections ("surges") before they occur. We describe here real time genomic surveillance particularly based on mutation analysis, of viral proteins as a methodology for a priori determination of surge in number of infection cases. The full results are available for SARS-CoV-2 at http://pandemics.okstate.edu/covid19/, and are updated daily as new virus sequences become available. This approach is generic and will also be applicable to other pathogens.

genomics↗