In this work the quantum chemistry Tersoff potential in combination with classical trajectory calculations was used to investigate the interaction of the DNA molecule with a carbon nanotube (CNT). The so-called hybrid approach—the classical and quantum-chemical modeling, where the force fields and interaction between particles are based on a definite (but not unique) description method, has been outlined in some detail. In such approach the molecules are described as a set of spheres and springs, thereby the spheres imitate classical particles and the spring the interaction force fields provided by quantum chemistry laws. The Tersoff potential in hybrid molecular dynamics (MD) simulations correctly describes the nature of covalent bonding. The aim of the present work was to estimate the dynamical and structural behavior of the DNA-CNT system at ambient temperature conditions. The dynamical configurations were built up for the DNA molecule interacting with the CNT. The analysis of generated МD configurations for the DNA-CNT complex was carried out. For the DNA-CNT system the observations reveal an encapsulation-like behavior of the DNA chain inside the CNT chain. The discussions were made on possible use of the DNA-CNT complex as a candidate material in drug delivery and related systems. Cardiac cell therapy has been proposed as one of the new strategies against myocardial infarction. Although several reports showed improvement of the function of ischemic heart, the effects of cell therapy vary among the studies and the mechanisms of the beneficial effects are still unknown. Previously, it has been reported that clonal stem cell antigen-1-positive cardiac progenitor cells exerted a therapeutic effect when transplanted into the ischemic heart. Considerable efforts have been achieved to identify the cardiac progenitor-specific paracrine factor and to elucidate the mechanism of its beneficial effect. Basic concepts and applications of data science to the genetic analysis of pharmacologic outcomes have also in the past presented. Drug repositioning is a challenging computational problem involving the integration of heterogeneous sources of biomolecular data and the design of label ranking algorithms able to exploit the overall topology of the underlying pharmacological netResearch. As a result we for the first time generated aMeta-Dynamic Meta-node Hybrid Quantum Chemistry Potential and Classical Trajectory Molecular Dynamics Simulations of the DNA-CNT Interaction reconsrtructing approach for the in silico generation of a drug-construct consisting of annotated Anti-inflammatory anti-(JAM-A) peptide-mimic pharmacophores with a potential myocardial infarction therapeutic activity.
Meta-Dynamic; Meta-node; reconsrtructing approach; in silico; stochastic generation;novel; drug-construct; novel in-silico;drug-designmethodology pharmacophoric generation Anti-inflammatory (JAM-A) peptide-mimic conformational complexity pharmacophores Hybrid Quantum Chemistry Potential and Classical Trajectory Approach, Molecular Dynamics; Carbon Nanotube; DNA Molecule; Drug Delivery; DNA-CNT Interaction