Discussions
In this article, we are improving the speed and accuracy and proposing an alternative topological quantum computing optimization framework for the computation of topological invariants of knots, links, and tangles through a discrete stochastic optimization multithreading procedure that uses nonlinear finite element analysis and a ground structure approach, for quantum repeater networks, as applied to quantum homology inspired Chern-Simons topology evolutionary scalable and fast fragmentation algorithm in which the geometric concepts of proper time enter in the non-relativistic limit (20-38,39). (Figure 2/b), (Figure 2/c). In this computer-aided drug designing project, we generated the GisitorviffirnaTM, Roccustyrna_ gs1_TM, and Roccustyrna_fr1_TM PDB and MOL2 files which are consisting of the merged pharmacophoric elements of the small molecule 2‐ ({[fluoro ({[ (2E) ‐5‐oxabicyclo [2.1.0] pentan‐ 2‐ylidene]cyano‐lambda6‐sulfanyl}) methyl]phosphorylidene} amino) ‐4,6‐dihydro‐1H‐purin‐6‐one1Z) ‐2‐{ ((2S,3S,5R) ‐5‐ (2‐amino‐6‐oxo ‐6,9‐dihydro‐ 1H‐purin‐9‐yl) ‐3‐hydroxyoxolan‐2yl) methylidene} ‐2‐cyano‐1‐ ({ ((2S,4R,5R) ‐2‐methyl‐2‐ (methylamino) ‐1,6‐ diazabicyclo (3.2.0) heptan‐4‐yl) oxy} imino) ‐1lambda5,2lambda5‐ azaphosphiridin‐1‐ylium. (Figure 2/d). (Figure 1///) (Scheme 1). The focus of this work is to develop a Quantum Heuristic Fragmentation driven Chern-Simons fragmentation algorithm that is as independent to allow for a faster multi-cut solutions as possible from the chosen pharmacophoric fragmentation Scheme obtained by localization of the S3 partition function of {x sin^ (-1) (sqrt (3) ), x sin^ (-1) (sqrt (779) sqrt (θ^3) ), x sin^ (-1) (2 sqrt (114109) ), (sqrt (1 - sqrt (456457) sqrt (x)) x^ (1/4) (2 sqrt (456457) sqrt (x) + 3)) / (8 456457^ (3/4)) + (x - 3/3651656) sin^ (-1) (456457^ (1/4) x^ (1/4) ), 1/2 sqrt (x/456456754 - x^2) + (x - 1/912913508) sin^ (-1) (sqrt (456456754) sqrt (x) ), x sin^ (-1) (2^ (3/4) 57057^ (1/4) ), x sin^ (-1) (sqrt (sum 444546 θ)) ,sin^ (-1) (2^ (3/4) 431683182057^ (1/4) sqrt (sqrt (θ) / (sin^ (-1) (44545545)) )) } + constant 3d (equation61) N = 2 CS{θ sin^ (-1) (sqrt (3)) (equation62), θ sin^ (-1) (sqrt (779δυ = i¯ǫυ, (equation63) δ ¯υ = iǫ ¯ υ, (equation64) δυ = −γμǫDμυ – ǫ (equation65) συ −if (ϑ) ǫυ + i¯ǫF, (equation66) δ ¯ υ = −γμ¯ǫDμ ¯υ − ¯υσ¯ǫ −if (ϑ) ¯υ¯ǫ + i ¯ Fǫ, (equation67) δF = ǫ (−γμDμυ + συ + λυ) +i (if√(∣∣α1′(t) ⟩CQ1t∣ϕ(t) ⟩B|∇ |2 −ΔKΣ(dt−asin2θdϕ)) 2f (ϑ) ǫυ, (equation68) δ ¯ F = ¯ǫ (−γμDμ ¯ υ + ¯ υσ − ¯υ¯ λ) +i (if√(∣∣α1′(t) ⟩CQ1t∣ϕ(t) ⟩B|∇ |2 −ΔKΣ(dt−asin2θdϕ)) 2f (ϑ) ¯ǫ ¯ υ,) sqrt (θ^3)) - 3/5 sqrt (779) θ sqrt (θ^3) 2F1 (1/2, 5/6, 11/6, 779 θ^3), 1/6 sqrt (1/49394 - 9 θ) sqrt (θ) + (θ 1/889092) sin^ (-1) (3 sqrt (49394) sqrt (θ) ), θ sin^ (-1) (sqrt (sin^ (-1) (44545545)) ) } + constant (equations4-67) of new group contribution drug design methods. (32,35-38,40) For this reason, the Roccustyrna multi- targeting pharmacophoric element for each Turing pattern was kept as simple as possible and can be geometrically represented at a growing boundary as promising potent and selective anti-viral inhibitor with rationally calculated logical atomic spaces and subatomic subspaces to Higgs branch Representation allowing a vectorial negative docking energy representation against this drug target. (20,25,26) Harmonic resonant excitation by picking up poles of the one-loop determinant and Quantum principal analysis on flow-distributed oscillation waves and few chemical space Turing patterns were applied at a growing boundary for the design of my novel multi-chemo-structure the Roccustyrna small molecule against the crystal structure of COVID-19 main protease in a Lindenbaum-Tarski in a half complex plane generated QSAR automating modeling lead compound design approach. Post-quantum cryptography hopes to fix this problem by developing new cryptographic algorithms that rely on hard problems that, to the best of our knowledge, a quantum computer cannot break. A side channel of a cryptographic algorithm is a way to gather information besides looking at the encrypted data. In this hybrid drug designing approach, we have designed the combination of GisitorviffirnaTM, Roccustyrna_gs1_TM, and Roccustyrna_fr1_TM nano-structures by improving the speed and the accuracy of the known docking protocols as represented a system of intrinsically positioned cables filtered before evaluation and triangular bars kinematically stable and structurally valid symmetric formations of connected components, holes, and voids jointed at their ends in the (Coulomb branch) localization formula for ZS3 by hinged connections to form our combination of GisitorviffirnaTM, Roccustyrna_gs1_TM, and Roccustyrna_fr1_TM prototype rigid chemical scaffolds with therapeutic potential against novel respiratory 2019 coronavirus in comparative effectiveness persistent homologies by combined virtual screening and supervised machine learning (19,21,24,41,42). It was also observed in this parallel docking energy analysis that our QMMM designed Risitorviffirna interacted onto the (PDB:6WZU) protein targets with the highest docking energy negative score when compared to other FDA-approved and experimental drugs.GisitorviffirnaTM neo-ligand could also be hypothetically combined with Faldaprevir, Gemigliptin, Raltegravir, Ribavirin, Eflornithine, Cycloserine, Azathioprine, Umifenovir, Darunavir, Baricitinib, Hydroxychloroquine, Minocycline, Azithromycin, and the Linoleic acid, FDA approved drugs and the experimental EIDD2801MK4482) small molecule but not with Minocycline, Azithromycin, Remdesivir, GC376, Histrelin, Doxycycline, Cobicistat, Ritonavir, Colchicine, Bleomycin when targeted at the same (PDB:6WZU) protein targets (Figure 4/a).