The combination of theoretical models of macromolecules that exist at different spatial and temporal scales has become increasingly important for addressing complex biochemical problems. This work describes the extension of concurrent multiscale approaches, introduces a general framework for carrying out calculations, and describes its implementation into the CHARMM macromolecular modeling package. This functionality, termed MSCALE, generalizes both the additive and subtractive multiscale scheme [e.g., quantummechanical/molecular mechanical (QM/MM) ONIOM-type] and extends its support to classical force fields, coarse grained modeling [e.g., elastic network model (ENM), Gaussian network model (GNM), etc.], and a mixture of them all. The MSCALE scheme is completely parallelized with each subsystem running as an independent but connected calculation. One of the most attractive features of MSCALE is the relative ease of implementation using the standard message passing interface communication protocol. This allows external access to the framework and facilitates the combination of functionality previously isolated in separate programs. This new facility is fully integrated with free energy perturbation methods, Hessian-based methods, and the use of periodicity and symmetry, which allows the calculation of accurate pressures. We demonstrate the utility of this new technique with four examples: (1) subtractive QM/MM and QM/QM calculations; (2) multiple force field alchemical free energy perturbation; (3) integration with the SANDER module of AMBER and the TINKER package to gain access to potentials not available in CHARMM; and (4) mixed resolution (i.e., coarse grain/all-atom)normal mode analysis. The potential of this new tool is clearly established, and in conclusion, an interesting mathematical problem is highlighted, and future improvements are proposed.
COBISS.SI-ID: 4653594
Parallelization is an effective way to reduce the computational time needed for molecular dynamics simulations. We describe a new parallelization method, the distributed-diagonal force decomposition method, with which we extend and improve the existing force decomposition methods. Our new method requires less data communication during molecular dynamics simulations than replicated data and current force decomposition methods, increasing the parallel efficiency. It also dynamically load-balances the processors' computational load throughout the simulation. The method is readily implemented in existing molecular dynamics codes and it has been incorporated into the CHARMM program, allowing its immediate use in conjunction with the many molecular dynamics simulation techniques that are already present in the program. We also present the design of the Force Decomposition Machine, a cluster of personal computers and networks that is tailored to running molecular dynamics simulations using the distributed diagonal force decomposition method. The design is expandable and provides various degrees of fault resilience. This approach is easily adaptable to computers with Graphics Processing Units because it is independent of the processor type being used.
COBISS.SI-ID: 4728602
Rational design is applied in the discovery of novel lead drugs. Its rapid development is mainly attributed to the tremendous advancements in the computer science, statistics, molecular biology, biophysics, biochemistry, medicinal chemistry, pharmacokinetics and pharmacodynamics experienced in the last few decades. The promising feature that characterizes the application of rational drug design is that it uses for developing potential leads in drug discovery all known theoretical and experimental knowledge of the system understudy. The utilization of the knowledge of the molecular basis of the system ultimately aims to reduce human power cost, time saving and laboratory expenses in the drug discovery. In this review paper various strategies applied for systems which include: (i) absence of knowledge of the receptor active site; (ii) the knowledge of a homology model of a receptor, (iii) the knowledge of the experimentally determined (i.e. X-ray crystallography, NMR spectroscopy) coordinates of the active site of the protein in absence and (iv) the presence of the ligand will be analyzed.
COBISS.SI-ID: 4671770