Proton transport plays an important role in biological energy transduction and sensory systems. Therefore it has attracted much attention in biological science and biomedical engineering in the past few decades. The present work proposes a multiscale/multiphysics model for the understanding of the molecular mechanism of proton transport in transmembrane proteins involving continuum, atomic and quantum descriptions, assisted with the evolution, formation and visualization of membrane channel surfaces. We describe proton dynamics quantum mechanically via a new density functional theory based on the Boltzmann statistics, while implicitly model numerous solvent molecules as a dielectric continuum to reduce the number of degrees of freedom. The density of all other ions in the solvent is assumed to obey the Boltzmann distribution in a dynamic manner. The impact of protein molecular structure and its charge polarization on the proton transport is considered explicitly at the atomic scale. A variational solute-solvent interface is designed to separate the explicit molecule and implicit solvent regions. We formulate a total free energy functional to put proton kinetic and potential energies, the free energy of all other ions, the polar and nonpolar energies of the whole system on an equal footing. The variational principle is employed to derive coupled governing equations for the proton transport system. Generalized Laplace-Beltrami equation, generalized Poisson-Boltzmann equation and generalized Kohn-Sham equation are obtained from the present variational framework. The variational solvent-solute interface is generated and visualized to facilitate the multiscale discrete/continuum/quantum descriptions. Theoretical formulations for the proton density and conductance are constructed based on fundamental laws of physics. A number of mathematical algorithms, including the Dirichlet to Neumann mapping (DNM), matched interface and boundary (MIB) method, Gummel iteration, and Krylov space techniques are utilized to implement the proposed model in a computationally efficient manner. The Gramicidin A (GA) channel is used to validate the performance of the proposed proton transport model and demonstrate the efficiency of the proposed mathematical algorithms. The proton channel conductances are studied over a number of applied voltages and reference concentrations. HCV infection has been declared as a principal health problem in more than 200 million individuals throughout the world. It is a positive-stranded RNA virus and classified as a hepacivirus of the flaviviridae family. Unlike other viral infections Hepatitis C Virus even with its high replication rate can stick within a human host for decades without any irritation or liver damage. Estimated 10 million people are believed to be infected by HCV alone in Pakistan. Eventually the infection causes severe complications in 60 to 70% of patients such as cirrhosis, fibrosis, liver failure and hepatocellular carcinoma. Prior to the development of HCV protease inhibitors combination therapy, patients with HCV infection were treated with pegylated interferon-α and ribavirin. The adverse side effects associated with this type of treatment such as anemia, flu-like symptoms, depression, gastrointestinal symptoms, fatigue and cutaneous reactions may lead to the discontinuation of treatment in certain number of patients. The growth in scientific knowledge of HCV life cycle and its replication leads to the development of inhibitors of HCV proteases. A polyprotein precursor encoded by HCV RNA genome containing structural proteins capsid (C), membrane (prM), envelope (E) and nonstructural (NS) proteins (NS1, NS2a, NS2b, NS3, NS4a, NS4b, NS5). NS3 protease when activated by NS4A causes the cleavage of polyprotein producing the non-structural proteins 4A, 4B, 5A, 5B and is thus very supportive in the replication of virus. That is why NS3/4A protease is a significant emerging target for the treatment of HCV infection. NS3 associates to the ER membrane only in the presence of NS4A. Main actively conserved protein target families can be distinguished by a simple look at physicochemical properties (molecular weight, log P, polar surface area, H-bond donor and acceptor counts) of their cognate ligands (Morphy, 2006). One can thus easily imagine that more sophisticated descriptors can be used to predict a global target profile for any given compound, provided that targets to be predicted are sufficiently well described by existing ligands. In this study, Variational solvent-solute interface Quantum dynamics in continuum for proton transport are generated of a sophisticated descriptor for the in silico identification and free energy evaluation of hybrid KPQRKTKRNT peptidomimetic leads as a potential inhibitor against helicase and HCV´sStructural NS3/4A protease regions.
Quantum dynamics; continuum for proton transport II: Variational solvent-solute interface; in Silico generation; sophisticated descriptor; in silico identification; free energy evaluation; hybrid KPQRKTKRNT peptidomimetic leads; simultaneous inhibition; helicase and HCV´sStructural; NS3/4A protease regions.