Coarse-grained ͑CG͒ models provide a computationally efficient method for rapidly investigating the long time-and length-scale processes that play a critical role in many important biological and soft matter processes. Recently, Izvekov and Voth introduced a new multiscale coarse-graining ͑MS-CG͒ method ͓J. Phys. Chem. B 109, 2469 ͑2005͒; J. Chem. Phys. 123, 134105 ͑2005͔͒ for determining the effective interactions between CG sites using information from simulations of atomically detailed models. The present work develops a formal statistical mechanical framework for the MS-CG method and demonstrates that the variational principle underlying the method may, in principle, be employed to determine the many-body potential of mean force ͑PMF͒ that governs the equilibrium distribution of positions of the CG sites for the MS-CG models. A CG model that employs such a PMF as a "potential energy function" will generate an equilibrium probability distribution of CG sites that is consistent with the atomically detailed model from which the PMF is derived. Consequently, the MS-CG method provides a formal multiscale bridge rigorously connecting the equilibrium ensembles generated with atomistic and CG models. The variational principle also suggests a class of practical algorithms for calculating approximations to this many-body PMF that are optimal. These algorithms use computer simulation data from the atomically detailed model. Finally, important generalizations of the MS-CG method are introduced for treating systems with rigid intramolecular constraints and for developing CG models whose equilibrium momentum distribution is consistent with that of an atomically detailed model.

The multiscale coarse-graining (MS-CG) method obtains CG interactions from atomistic configurations, as demonstrated previously for a variety of soft matter and biological systems. In this article, recent advances in MS-CG algorithms are described, and a recently developed computer program MSCGFM for MS-CG calculations is introduced. The algorithms enhance the efficiency and stability of MS-CG computations, and these algorithms are incorporated into the MSCGFM program. As a result of these efforts, MS-CG calculations on large scale systems such as peptide and proteins can become tractable, and the numerical stability of solutions for ill-posed MS-CG problems can be regularized efficiently. Various parallelization strategies are also discussed.

Biomolecular conformational transitions are essential to biological functions. Most experimental methods report on the long-lived functional states of biomolecules, but information about the transition pathways between these stable states is generally scarce. Such transitions involve short-lived conformational states that are difficult to detect experimentally. For this reason, computational methods are needed to produce plausible hypothetical transition pathways that can then be probed experimentally. Here we propose a simple and computationally efficient method, called ANMPathway, for constructing a physically reasonable pathway between two endpoints of a conformational transition. We adopt a coarse-grained representation of the protein and construct a two-state potential by combining two elastic network models (ENMs) representative of the experimental structures resolved for the endpoints. The two-state potential has a cusp hypersurface in the configuration space where the energies from both the ENMs are equal. We first search for the minimum energy structure on the cusp hypersurface and then treat it as the transition state. The continuous pathway is subsequently constructed by following the steepest descent energy minimization trajectories starting from the transition state on each side of the cusp hypersurface. Application to several systems of broad biological interest such as adenylate kinase, ATP-driven calcium pump SERCA, leucine transporter and glutamate transporter shows that ANMPathway yields results in good agreement with those from other similar methods and with data obtained from all-atom molecular dynamics simulations, in support of the utility of this simple and efficient approach. Notably the method provides experimentally testable predictions, including the formation of non-native contacts during the transition which we were able to detect in two of the systems we studied. An open-access web server has been created to deliver ANMPathway results.

The multiscale coarse-graining (MS-CG) method is a method for determining the effective potential energy function for a coarse-grained (CG) model of a system using the data obtained from molecular dynamics simulation of the corresponding atomically detailed model. The MS-CG method, as originally formulated for systems at constant volume, has previously been given a rigorous statistical mechanical basis for the canonical ensemble. Here, we propose and test a version of the MS-CG method suitable for the isothermal-isobaric ensemble. The method shows how to construct an effective potential energy function for a CG system that generates the correct volume fluctuations as well as correct distribution functions in the configuration space of the CG sites. The formulation of the method requires introduction of an explicitly volume dependent term in the potential energy function of the CG system. The theory is applicable to simulations with isotropic volume fluctuations and cases where both the atomistic and CG models do not have any intramolecular constraints, but it is straightforward to extend the theory to more general cases. The present theory deals with systems that have short ranged interactions. (The extension to Coulombic forces using Ewald methods requires additional considerations.) We test the theory for constant pressure MS-CG simulations of a simple model of a solution. We show that both the volume dependent and the coordinate dependent parts of the potential are transferable to larger systems than the one used to obtain these potentials.