Biomedical subjects
Publications and source records attributed to U H Hansmann.
We study simulated annealing techniques for crystal structure determination from diffraction data. We demonstrate that for this problem the efficiency of simulated annealing can be systematically improved by an iterative simulation protocol. Our approach is tested for the example of 9-(methylamino)-1 H-phenalen-1-one-1, 4-dioxan-2-yl hydroperoxide solvate (C18H19NO5).
A simple spin system is studied as an analog for proteins. We investigate how the introduction of randomness and frustration into the system affects the designability and stability of ground-state configurations. We observe that the spin system exhibits proteinlike behavior in the vicinity of the transition between a ferromagnet and a spin glass. Our results illuminate some guiding principles in protein evolution.
We report on multicanonical simulations of the helix-coil transition of a polypeptide. The nature of this transition was studied by calculating partition function zeros and the finite size scaling of various quantities. New estimates for critical exponents are presented.
We study the free energy landscape of the small peptide Met-enkephalin. Our data were obtained from a generalized-ensemble Monte Carlo simulation taking the interactions among all atoms into account. We show that the free energy landscape resembles that of a funnel, indicating that this peptide is a good folder. Our work demonstrates that the energy landscape picture and folding concept, developed in the context of simplified protein models, can also be used to describe the folding in more realistic models.
Over the past three decades, a number of powerful simulation algorithms have been introduced to the protein folding problem. For many years, the emphasis has been placed on how to both overcome the multiple minima problem and find the conformation with the global minimum potential energy. Since the new view of the protein folding mechanism (based on the free energy landscape of the protein system) arose in the past few years, however, it is now of interest to obtain a global knowledge of the phase space, including the intermediate and denatured states of proteins. Monte Carlo methods have proved especially valuable for these purposes. As well as new, powerful optimization techniques, novel algorithms that can sample much a wider phase space than conventional methods have been established.
We perform a generalized-ensemble simulation of a small peptide taking the interactions among all atoms into account. From this simulation we obtain thermodynamic quantities over a wide range of temperatures. In particular, we show that the folding of a small peptide is a multistage process associated with two characteristic temperatures, the collapse temperature Ttheta and the folding temperature T. Our results give supporting evidence for the energy landscape picture and funnel concept. These ideas were previously developed in the context of studies of simplified protein models, and here are checked in an all-atom Monte Carlo simulation.
Multicanonical Monte Carlo simulations of the pentapeptide Met-enkephalin were used to study its low-energy conformations in detail. The resulting conformations are classified into six categories of similar structures based on the pattern of intrachain hydrogen bonds. Several thermodynamic quantities such as the distributions of hydrogen bonds and those of backbone dihedral angles were obtained as a function of temperature. From these results, it was concluded that at least four of the six categories are well-defined local minimum energy states. These four categories are in agreement with our prior results based on root-mean-square interatomic distances.