The folding free energy landscape of the C-terminal ␤ hairpin of protein G has been explored in this study with explicit solvent under periodic boundary condition and OPLSAA force field. A highly parallel replica exchange method that combines molecular dynamics trajectories with a temperature exchange Monte Carlo process is used for sampling with the help of a new efficient algorithm P3ME͞RESPA. The simulation results show that the hydrophobic core and the ␤ strand hydrogen bond form at roughly the same time. The free energy landscape with respect to various reaction coordinates is found to be rugged at low temperatures and becomes a smooth funnel-like landscape at about 360 K. In contrast to some very recent studies, no significant helical content has been found in our simulation at all temperatures studied. The ␤ hairpin population and hydrogen-bond probability are in reasonable agreement with the experiment at biological temperature, but both decay more slowly than the experiment with temperature.U nderstanding protein folding is one of the most challenging problems remaining in molecular biology (1-5). Recent advances in experimental techniques that probe proteins at different stages during the folding process have shed light on the nature of the physical mechanisms and relevant interactions that determine the kinetics of folding, binding, function, and thermodynamic stability (2-5). However, many of the details of protein folding pathways remain unknown. Computer simulations performed at various levels of complexity ranging from simple lattice models, models with continuum solvent, to all atom models with explicit solvent can be used to supplement experiment and fill in some of the gaps in our knowledge about folding pathways. Much of today's theoretical understanding has been tested in minimalist lattice or off-lattice models. All-atom simulations of protein unfolding at high temperatures have also revealed many important features about the protein folding process, even though they are limited by the fact that the free energy landscape explored at high temperature might be very different from the landscape at biological temperatures. Allatom protein folding in explicit solvent still remains a challenge in computational biology.The free energy landscape of native proteins in explicit solvent is believed to be partially rugged and funnel-like (6) because of the energy barriers caused by van der Waals repulsions and torsional energy barriers. At room temperature (RT), protein systems get trapped in many local minima. This trapping limits the capacity to effectively sample configurational space. Many methods have been proposed to enhance the conformation space sampling (7). In this work, we use the replica exchange or parallel tempering method (8) to increase barrier crossing events.As one of the smallest naturally occurring systems, which exhibits many features of a full size protein and also is a faster folder (it folds in 6 s), the C-terminal ␤ hairpin of protein G has received much attention recently on bo...

In this work we demonstrate the use of a rigorous formalism for the extraction of state-to-state transition functions as a way to study the kinetics of protein folding in the context of a Markov chain. The approach is illustrated by its application to two different systems: a blocked alanine dipeptide in a vacuum and the C-terminal β-hairpin motif from protein G in water. The first system displays some of the desired features of the approach, whereas the second illustrates some of the challenges that must be overcome to apply the method to more complex biomolecular systems. For both example systems, Boltzmann weighted conformations produced by a replica exchange Monte Carlo procedure were used as starting states for kinetic trajectories. The alanine dipeptide displays Markovian behavior in a state space defined with respect to φ-ψ torsion angles. In contrast, Markovian behavior was not observed for the β-hairpin in a state space where all possible native hydrogen bonding patterns were resolved. This may be due to our choice of state definitions or sampling limitations. Furthermore, the use of different criteria for hydrogen bonding results in the apparent observation of different mechanisms from the same underlying data: one set of criteria indicate a zipping type of process, but another indicates more of a collapse followed by almost simultaneous formation of a large number of contacts. Analysis of long-lived states observed during the simulations of the β-hairpin suggests that important aspects of the folding process that are not captured by order parameters in common use include the formation of non-native hydrogen bonds and the degree and nature of salt bridge formation. † Part of the special issue "Hans C. Andersen Festschrift".

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, IBM announced the start of a five-year effort to build a massively parallel computer, to be applied to the study of biomolecular phenomena such as protein folding. The project has two main goals: to advance our understanding of the mechanisms behind protein folding via large-scale simulation, and to explore novel ideas in massively parallel machine architecture and software. This project should enable biomolecular simulations that are orders of magnitude larger than current technology permits. Major areas of investigation include: how to most effectively utilize this novel platform to meet our scientific goals, how to make such massively parallel machines more usable, and how to achieve performance targets, with reasonable cost, through novel machine architectures. This paper provides an overview of the Blue Gene project at IBM Research. It includes some of the plans that have been made, the intended goals, and the anticipated challenges regarding the scientific work, the software application, and the hardware design.