SimuLab 5: Protein Folding

As you saw in Sect .2.3 from the studies of the polymers they collapse in dense globule as the temperature decreases. This collapse is characterized by a steep but not infinite slope of the potential energy vs. temperature.This behavior is characteristic of the fluid near its critical point where no distinct phases exist. The globule is amorphous and its shape changes all the time. Proteins although they also collapse at low temperature into a dense globule and unfold at high temperature they do it in a quite different way. The main difference is that the protein globule always has the same structure which is called `native structure'. Beeing in this structure allows protein to act like a nanoscale robot which binds to other specific targets such as small molecules ligands, other proteins and DNA. For example hemoglobin binds to O2 and C O2. Other special protein topoizomerazes which can cut DNA and glue them back together in order to distentangle DNA strand in mitosis. Miosine acts like micromotor sliding along acting chains during muscle contraction. All this amazing properties are possible because protein, a string of different aminoacids, somehow folds itself into native state. Imagine a shoelace which can tangle into a knot and disentangle by itself without human intervention! Scientists have discover that Aminoacid sequence completely determine the native structure. Some Aminoacids are hydropholic and attract to each other. Other are hydrophilic, they attract to surrounding water. The main problem of the protein science is, given the chemical sequence of protein, to determine its three dimensional shape in the native structure. Or viceversa, knowing the three dimensional shape, design the chemical sequence that would fold into it. There is an entire spectrum of different repulsive and attractive properties of aminoacid which in our simple universe could be encoded by 3 20 x 20 matrices of rAB, RAB and eAB where A and B stand for different aminoacids. This would allow to design powerful drugs and there are many scientific groups around the globe that competes wich each other to do it first. So fare nobody fully succeed in it, however the first insights are already obtained, and there is a hope that someday a powerful computer, given the potentials of interaction between different aminoacids, would be able to predict native structures and design proteins for specific tastes. Our program Universal, made in collaboration with the group of Prof. Shaknovich in Harvard University, represents the first steps in this direction. The main drawback of our program is that the aminoacids are presented by structureless balls, this allows us to do simulations much faster than other groups who represents the aminoacids by all atoms interacting with each other with realistic interatomic potentials. Instead of specifying complex potentials between aminoacids, we take the known native state of small protein CHR3 domaim which consists of 57 aminoacids and postulate that aminoacids who are between 75 A0 of distance in the native state attract each other while the others who are further away repulse. This give us a 57 x 57 matrix of rAB, RAB and eAB. The protein designed like this unfolds at high temperature and fold into the perfect native state at low temperature. Of course this is not the full solution of the protein folding problem (which would be if we use only 20 x 20 matrices and do not directly use the structure of native state) but a significant step in this direction. Several scientific papers have being published and submitted to important journals by our graduate students J. Borreguero, F. Ding and postdoctoral research associate N. V. Dokholyan. Thus experimenting with our simulab of protein folding you will do the cutting the edge research.


You will be able to:

a) Observe the protein folding;

b) Compare the folding to freezing supercooled liquid;

c) Appreciate that folding resembles first order phase transition with latent heat released;

d) Appreciate that folding occurs via nucleation;

e) Construct a folding curve.

Answers to the question

Simulab 5

A2.30: See Fig .2.8

time temperature Potential Energy Total energy
1000 0.816 -66.84
2000 0.826 -70.78
3000 0.7937 -67.09
4000 0.790 -68.16
5000 0.807 -72.48
6000 0.750 -64.76
7000 0.772 -69.05
8000 0.759 -67.97
9000 0.775 -71.61
10000 0.787 -74.96
11000 0.762 -72.07
12000 0.750 -71.05
13000 0.740 -70.22
14000 0.751 -72.76
15000 0.885 -95.98
16000 0.983 -116.1
17000 0.950 -115.1
18000 0.950 -119.3
19000 0.919 -117.8
20000 0.920 -121.5

figures/proteinEvstime.png figures/proteinTvstime.png
Figure 2.8: Plot of energies as function of time for the protein problem. The dashed lines shows the transition to the folding state.