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Typical drug discovery and development processes are costly, time consuming and often biased by expert opinion. Aptamers are short, single-stranded oligonucleotides (RNA/DNA) that bind to target proteins and other types of biomolecules. Compared with small-molecule drugs, aptamers can bind to their targets with high affinity (binding strength) and specificity (uniquely interacting with the target only). The conventional development process for aptamers utilizes a manual process known as Systematic Evolution of Ligands by Exponential Enrichment (SELEX), which is costly, slow, dependent on library choice and often produces aptamers that are not optimized. To address these challenges, in this research, we create an intelligent approach, named DAPTEV, for generating and evolving aptamer sequences to support aptamer-based drug discovery and development. Using the COVID-19 spike protein as a target, our computational results suggest that DAPTEV is able to produce structurally complex aptamers with strong binding affinities. Author summaryCompared with small-molecule drugs, aptamer drugs are short RNAs/DNAs that can specifically bind to targets with high strength. With the interest of discovering novel aptamer drugs as an alternative to address the long-lasting COVID-19 pandemic, in this research, we developed an artificial intelligence (AI) framework for the in silico design of novel aptamer drugs that can prevent the SARS-CoV-2 virus from entering human cells. Our research is valuable as we explore a novel approach for the treatment of SARS-CoV-2 infection and the AI framework could be applied to address future health crises.
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BackgroundAntibodies raised against human seasonal coronaviruses (sCoVs), which are responsible for the common cold, are known to cross-react with SARS-CoV-2 antigens. This prompts questions about their protective role against SARS-CoV-2 infections and COVID-19 severity. However, the relationship between sCoV exposure and SARS-CoV-2 correlates of protection are not clearly identified. MethodsWe performed a cross-sectional analysis of cross-reactivity and cross-neutralization to SARS-CoV-2 antigens (S-RBD, S-trimer, N) using pre-pandemic serum from four different groups: pediatrics and adolescents, persons 21 to 70 years of age, older than 70 years of age, and persons living with HCV or HIV. FindingsAntibody cross-reactivity to SARS-CoV-2 antigens varied between 1.6% and 15.3% depending on the cohort and the isotype-antigen pair analyzed. We also show a range of neutralizing activity (0-45%) in serum that interferes with SARS-CoV-2 spike attachment to ACE2. While the abundance of sCoV antibodies did not directly correlate with neutralization, we show that neutralizing activity is rather dependent on relative ratios of IgGs in sera directed to all four sCoV spike proteins. More specifically, we identified antibodies to NL63 and OC43 as being the most important predictors of neutralization. InterpretationOur data support that exposure to sCoVs triggers antibody responses that influence the efficiency of SARS-CoV-2 spike binding to ACE2, and may also impact COVID-19 disease severity through other latent variables. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSThere is a growing body of evidence showing that within the population there are varying levels of pre-existing immunity to SARS-CoV-2 infection and possibly COVID-19 disease severity. This immunity is believed to be attributable to prior infection by four prevalent seasonal coronaviruses (sCoVs) responsible for the common cold. Pre-existing immunity can be assessed in part by antibodies directed to sCoVs that also cross-react to SARS-CoV-2 antigens. The SARS-CoV-2 spike and, more specifically, the receptor binding domain are the primary targets for neutralizing antibodies. It is unclear if cross-reactive antibodies to SARS-CoV-2 are neutralizing and are also responsible for the broad spectrum of COVID-19 disease severity, from asymptomatic to critical, observed in the infected population. Added-value of this studyHere we carried out a detailed analysis of sCoV prevalence in samples acquired before the pandemic from individuals of various age groups and in people living with HIV and HCV. We then analyzed the frequency of all the different types of antibodies that cross-react to three SARS-CoV-2 antigens. We found a high level of people with cross-reactive antibodies, surprisingly we also detected that some people have antibodies that block the SARS-CoV-2 spike from binding to its human receptor, ACE2. By using machine learning, we were able to accurate predict which individuals can neutralize SARS-CoV-2 spike-ACE2 interactions based on their relative ratios of antibodies against the four sCoVs. Implications of all the available evidenceWe demonstrate that it not absolute levels of sCoVs antibodies that are predictive of neutralization but the relative ratios to all four sCoVs, with NL63 being the most weighted for this prediction. Machine learning also highlighted the existence of latent variables that contribute to the neutralization and that may be related to the type of cellular immune response triggered by the infection to certain sCoVs. This study is one of the first to identify a functional relationship between prior-exposure to sCoV and the establishment of a certain degree of immunity to SARS-CoV-2 by way of a cross-reactive antibody response. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=179 SRC="FIGDIR/small/21260079v3_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@e74392org.highwire.dtl.DTLVardef@1052bd5org.highwire.dtl.DTLVardef@80d88eorg.highwire.dtl.DTLVardef@10976cb_HPS_FORMAT_FIGEXP M_FIG C_FIG
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Delirium is an acute change in attention and cognition occurring in ~65% of severe SARS-CoV-2 cases. It is also common following surgery and an indicator of brain vulnerability and risk for the development of dementia. In this work we analyzed the underlying role of metabolism in delirium-susceptibility in the postoperative setting using metabolomic profiling of cerebrospinal fluid and blood taken from the same patients prior to planned orthopaedic surgery. Significant concentration differences in several amino acids, acylcarnitines and polyamines were found in delirium-prone patients leading us to a hypothesis about the significance of monoamine oxidase B (MAOB) in predisposition to delirium. Subsequent computational structural comparison between MAOB and angiotensin converting enzyme 2 as well as protein-protein docking analysis showed possibly strong binding of SARS-CoV-2 spike protein to MAOB resulting in a hypothesis that SARS-CoV-2 influences MAOB activity possibly lead to many observed neurological and platelet-based complications of SARS-CoV-2 infection. This proposition is possibly of significance for diagnosis, treatment and prevention of vulnerabilities causing delirium, dementias and severe COVID-19 response.
