An unknown quantum state cannot be copied and broadcast freely due to the no-cloning theorem. Approximate cloning schemes have been proposed to achieve the optimal cloning characterized by the maximal fidelity between the original and its copies. Here, from the perspective of quantum Fisher information (QFI), we investigate the distribution of QFI in asymmetric cloning machines which produce two nonidentical copies. As one might expect, improving the QFI of one copy results in decreasing the QFI of the other copy. It is perhaps also unsurprising that asymmetric phase-covariant cloning outperforms universal cloning in distributing QFI since a priori information of the input state has been utilized. However, interesting results appear when we compare the distributabilities of fidelity (which quantifies the full information of quantum states), and QFI (which only captures the information of relevant parameters) in asymmetric cloning machines. Unlike the results of fidelity, where the distributability of symmetric cloning is always optimal for any d-dimensional cloning, we find that any asymmetric cloning outperforms symmetric cloning on the distribution of QFI for d ≤ 18, whereas some but not all asymmetric cloning strategies could be worse than symmetric ones when d > 18. In silico Drug discovery and development of novel multi-target molecules is an interdisciplinary, expensive and time-consuming procedure. Computer aided drug discovery advancements during the past decades have improved the way of pharmaceutical research design of novel bioactive huper-structured drug-gable molecules. Computer aided drug design helps in reducing the cost and time for drug discovery process which otherwise takes many years. Virtual screening and docking studies helped to obtain ligand molecules that can inhibit the important Proteins involved in the pathogenesis of Ebola virus. It is noticed that the chemical compounds might be the promising candidates drug-like small targeted compounds for further pre-clinical and clinical investigation, and that the NP and the octapeptides ATLQAIAS and ATLQAENV, as well as AVLQSGFR, might be pre-clinically translated and antisense converted to effective direct inhibitors against the Ebola Virus Fusion Conserved Proteoma. Meanwhile, we in silico generated conserved octapeptides mimotopic pharmaco-ligands based on the “distorted key energy binding fitness scoring” theory to in-silico anti-sense peptides by in-silico translate them and transform them into a scaffold energy hopping structure in order to design potent selective super-agonsist anti-peptide poly-mimic new superstructure which is explicitly elucidated. We also combined all existing methods for computational huper-structured drug design methodologies to induce catalysis of Ebola Virus EBOV NP and EBO16 peptides by inducing energetically targeted favorable hydrogen bonds, van der Waals, and electrostatic interactions to a high-energy reaction conserved motif-based transition state(s) and/or intermediate(s) of Ebola virus. In this present Research Scientific Project , for first time we developed a computational method for designing motif-like conserved residues and ligand binding virus proteins with two properties characteristic of naturally occurring binding sites in addition to specific energetically favorable interactions with our newly designed Distribution of quantum Ligand based predictions of a virion-attached pharmacophore cross-reacting asymmetric cloning synthetic Fisher information machines on EQHHRRTDN/GAAIGLAWIPYFGPAA peptide mimetic ligand modeling potential therapeutic properties against conserved conserved EBO16 over-expressed regions Ebola virus.
Distribution of quantum Fisher information; asymmetric cloning machines; Ligand based prediction; virion-attached pharmacophore; cross-reacting; synthetic EQHHRRTDN/GAAIGLAWIPYFGPAA; peptide mimetic; therapeutic properties; Ebola virus; conserved EBO16; over-expressed regions.