Biological Physics: Selected Projects

Transport and properties of blood proteins
Transport of nutrients to peripheral tissues and healing of damaged blood vessels are among the most important functions of blood. These functions involve the action of a series of proteins some of which are found in large amounts in the blood circulation. Fibrinogen is a multiprotein complex which, when activated, aggregate to form firbin, a net-shaped molecular formation which is fundamental for the coagulation of blood following, i.e, a wound or when an extraneous body comes into contact with blood (i.e., graft implants). Thus, adsorption of fibrinogen on material surfaces play an important role in viability of those materials for implants. In collaboration with experimental groups in the field, we use atomistic molecular dynamics simulations to characterize the adsorption process of fibrinogen on material surfaces. Another important molecule in the blood is albumin, which mediate transport of lipids and other molecules in blood. Albumin is a multidomain protein which provides several binding sites used to bind a range of different target molecules. Target molecules (lipids, drugs, etc.) bind to albumin which act as a transporter, and are then released where needed by blood circulation. Here we use molecular dynamics simulations to study the binding modes of several lipids to Albumin and the kinetics of lipid release/uptake. If you are interested, please contact Giovanni Settanni.

Knots in polymers, proteins and DNA

Although globular homopolymers are typically highly knotted, less than one in a hundred protein structures contain a knot ( ). Nevertheless, intriguing counter-examples exist, like the most complicated protein knot, which was discovered recently during a diploma thesis in our group (see figure on the left). Apart from analyzing biological data, we perform Monte Carlo simulations of simplified protein and DNA models to learn more about entanglements in viral DNA, chromatin and proteins. On this topic, we collaborate with theory groups at MIT and an experimental group at the MPI for Polymer Research. If you are interested in interdisciplinary investigations at the frontier of physics, mathematics and molecular biology, please contact Peter Virnau.

Lipid Membranes

All living things depend on membranes. Their basic structure is provided by lipid bilayers, which self-assemble spontaneously in water due to the amphiphilic character of lipid molecules - they contain both hydrophilic and hydrophobic units. In our group, we are interested in generic properties of such amphiphilic bilayers.

We have established a coarse-grained lipid model, which reproduces the main phases and phase transitions of phospholipid membranes at temperatures close to room temperature. As particular highlights, we have (i) recovered and investigated the mysterious modulated "ripple phase" in one-component membranes, which had intrigued researchers for many decades, and (ii) discovered and investigated nanoscale structures, so-called "lipid rafts" in multicomponent membranes. Rafts are small structural entities in biomembranes which are believed to play an important role for many cellular functions. The question whether they can exist in pure lipid membranes had been discussed controversially in the past. We found that ripple states and rafts seem to be stabilized by very similar mechanisms: A propensity for global phase separation, which is suppressed by elastic interactions in the membrane. This is analyzed by computer simulations and elastic theories.

The same approach is used to study  lipid-mediated interaction mechanisms membrane proteins. In the past, we have focused on  a comparison between analytical predictions and simulation data for "proteins" that can be represented by simple cylindrical inclusions (see Figure). In the future, we also plan to investigate flexible proteins and their interaction with rafts. For more information, please contact Friederike Schmid.

Statistical physics of molecular recognition

Selective interactions between biomolecules play an essential role in biological systems. Without selective recognition of antigens by corresponding antibodies, for example, the immune system could not work efficiently. One of the most salient features of molecular recognition is the fact that biomolecules often discriminate very accurately between many different but structurally similar interaction partners which are also present in a heterogeneous biological system.

Our studies aim at an understanding of the basic and universal mechanisms of recognition processes between biomolecules in an heterogeneous environment. In order to identify and investigate these basics mechanisms we develop idealised coarse-grained models. These models neglect those details which are particular for a specific system and are thus constructed to represent generic types of recognition processes. The thermostatic and dynamical properties of the models are then analysed with numerical and analytical methods from statistical physics. For more information, please contact  Friederike Schmid.

Statistical mechanical modeling and simulations of repeat proteins

Repeat protein domains are formed by tandem arrays of repeating structural units, constitute about 20% of the eukaryotic proteome, mediating protein-protein interactions and acting as mechano-transductors. As such they may represent the basis for the construction of mechanical nanodevices. In collaboration with experimental groups in the field, we have been working on simplified models of repeat proteins which explains both the thermodynamics and the kinetics of folding of this class of proteins. We have also been carrying out atomistic molecular dynamics (MD) simulations of several repeat protein systems to study their folding behavior and their mechanical characteristics when subjected to external pulling forces. If you are interested, please contact Giovanni Settanni.

Protein and peptide folding
Our activity focuses on the development and application of methods for the identification of the folding transition state of peptides  and, more in general, for the complete characterization and representation of the dynamics of peptides by using atomistic molecular dynamics simulations . This research effort is based on the application of concepts like kinetic networks (figure on the left) and Markov models to the trajectory data of peptides collected by MD simulations. Results from this line of research are validated against available experimental data on the kinetics of folding of peptides (folding/unfolding rates, phi values). If you are interested, please contact Giovanni Settanni.