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\begin{document}

\title{QSAR-QMMM Cryptographic Mining on Chern-Simons Topological Geometrics
for the generation of a Ligand Targeting COVID-19-SARS-COV-2 SPIKE D614G
Binding Sites.}



\author[1]{Ioannis Grigoriadis}%
\affil[1]{Biogenea Pharmaceuticals Ltd}%


\vspace{-1em}



  
  \date{June 15, 2024}


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\begin{abstract}
SARS coronavirus 2 (SARS-CoV-2) in the viral spike (S) encoding a
SARS-COV-2 SPIKE D614G mutation protein predominate over time in locales
revealing the dynamic aspects of its key viral processes where it is
found, implying that this change enhances viral transmission. It has
also been observed that retroviruses infected ACE2-expressing cells
pseudotyped with SG614 that is presently affecting a growing number of
countries markedly more efficiently than those with SD614. In this
paper, we strongly combine topology geometric methods targeting at the
atomistic level the protein apparatus of the SARS-COV-2 virus that are
simple in machine learning anti-viral characteristics, to propose
computer-aided rational drug design strategies efficient in computing
docking usage, and powerful enough to achieve very high accuracy levels
for this in-silico effort for the generation of the AI-Quantum designed
molecule of Combination of GisitorviffirnaTM, Roccustyrna\_gs1\_TM, and
Roccustyrna\_fr1\_TM ligands with Preferred IUPAC Names of
(7aR)-5-amino-N-{[}(S)-\{2-{[}(S)-{[}(E)-(amino methyl
idene)amino{]}(cyano)methyl{]}hydrazin-1-yl\}(aziridin-1-yl)phosphoryl{]}-1-{[}(2E)-2-{[}(fluoromethanimidoyl)imino{]}acetyl{]}-7-oxo-1H,7H,7aH-pyrazolo{[}4,3-d{]}pyrimidine-3-carboxamide;
N-\{{[}(2-amino- 6-oxo-6,9-dihydro-1H-purin-9-yl)amino{]}(\{1-{[}5-
(\{{[}cyano(\{1-{[}(diaminomethylidene)amino{]}ethenyl\})amino{]}oxy\}methyl)-3,4-dihydroxyoxolan-2-yl{]}-1H-1,2,4-triazol-3-yl\}formamido)phosphoryl\}-6-fluoro-3,4-dihydropyrazine-2-carboxamide;{[}3-(2-amino-5-sulfanylidene-1,2,4-triazolidin-3-yl)oxaziridin-2-yl{]}(\{3-sulfanylidene-1,2,4,6-tetraazabicyclo{[}3.1.0{]}hexan-6-yl\})phosphoroso1-(3,4,5-trifluorooxolan-2-yl)-1H-1,2,4-triazole-3-carboxylate
targeting the COVID-19-SARS-COV-2 SPIKE D614G mutation using
Chern-Simons Topology Euclidean Geometric in a Lindenbaum-Tarski
generated QSAR automating modeling and Artificial Intelligence-Driven
Predictive Neural Networks.%
\end{abstract}%



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\verb`RoccustyrnaiJN_qqchCcamOmgt7HK__ Grigoriadis_Ioannis_.doc`  available at \url{https://authorea.com/users/389434/articles/709336-qsar-qmmm-cryptographic-mining-on-chern-simons-topological-geometrics-for-the-generation-of-a-ligand-targeting-covid-19-sars-cov-2-spike-d614g-binding-sites}\selectlanguage{english}
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