Eugen Hruska

I'm a Physics graduate student at Rice University with specialisation in biophysics. In my research at Clementi's Group I'm utilizing computer simulations and tools from statistical physics to determine proteins behavior.

My interest in biophysics evolved since high school. During my high school time I was engangaged in many Science Competitions. The Physics and Biology competitions captivated me most. Accordingly, I did my bachelor degrees in Physics and Biochemistry.

image of Eugen Hruska

Research interest

Proteins are significant both from theoretical and practical point of view. On one side, proteins are involved in most biological processes, such as enzymatic catalysis, photosynthesis and diseases. A fast and cheap method to determine how proteins behave would help in many applications. The current experimental methods are both slow and expensive. Unfortunately have trouble to determine properties of proteins.

From theoretical point of view, proteins are a challenge too. Proteins can have too many different possible shapes. This doesn't allow to predict the behavior of protein in a simple way. Only recently have powerful computers like Anton allowed to fold small proteins by brute force approach (Fig. 1). Brute force means that the protein is simulated exactly as it is in real world. The achieve reasonable accuracy it takes months or years to simulate miliseconds of protein behavior. Most protein don't fold in this short time. Only for fast-folding proteins the whole protein behavior can be simulated. This allowed to improve our understanding how proteins behave. Still, protein which fold on long timescales are out of reach.


Fig. 1. Results from Anton supercomputer, folding of several small proteins.
How fast-folding proteins fold, Shaw et al., Science, 2011

Many protein fold on much longer timescales than miliseconds. To determine the behavior of these slow folding proteins one might have to use more complicated approaches than brute force. One way is to use equations which describes the motion of proteins (Fig. 2.). In Clementi's group I determine which of the more complicated approaches is the most promising. The results from one method investigated in our group are shown in Fig. 3. The color indicated the probability that the protein will have a certain shape. These results were achieved faster than with brute force approach.

Fig. 2. Equation describing motion of proteins

Energy landcape

Fig. 3. Free energy landscape of peptide
Fast recovery of free energy landscapes via diffusion-map-directed molecular dynamics, Preto, Clementi, PCCP, 2014

Contact details:

email: eugen.hruska at rice edu

Research address:
Eugen Hruska
Anderson Biological Lab 319
Houston, TX 77005

Last modified: 04.20.2016 by Eugen Hruska