5 research outputs found
Stoichiometric Selection of Tight-Binding Inhibitors by Wild-Type and Mutant Forms of Malarial ( Plasmodium
Combined Spatial Limitation around Residues 16 and 108 of Plasmodium falciparum Dihydrofolate Reductase Explains Resistance to Cycloguanil
Single-Molecule Analysis of SARS-CoV‑2 Double-Stranded Polynucleotides Using Solid-State Nanopore with AI-Assisted Detection and Classification: Implications for Understanding Disease Severity
This
study utilized solid-state nanopores, combined with artificial
intelligence (AI), to analyze the double-stranded polynucleotides
encoding angiotensin-converting enzyme 2, receptor-binding domain,
and N protein, important parts of SARS-CoV-2 infection. By examining
ionic current signals during DNA translocation, we revealed the dynamic
interactions and structural characteristics of these nucleotide sequences
and also quantified their abundance. Nanopores of sizes 3 and 10 nm
were efficiently fabricated and characterized, ensuring an optimal
experimental approach. Our results showed a clear relationship between
DNA capture rates and concentration, proving our method’s effectiveness.
Notably, longer DNA sequences had higher capture rates, suggesting
their importance for potential disease marker analysis. The 3 nm nanopore
demonstrated superior performance in our DNA analysis. Using dwell
time measurements and excluded currents, we were able to distinguish
the longer DNA fragments, paving the way for a DNA length-based analysis.
Overall, our research underscores the potential of nanopore technology,
enhanced with AI, in analyzing COVID-19-related DNA and its implications
for understanding disease severity. This provides insight into innovative
diagnostic and treatment strategies