Research on Protein Folding Rate Based on Conformational Quantum Transition
|School||Inner Mongolia University|
|Keywords||Protein folding rate Contact order Torsion state The quantum transition Quadratic discriminant analysis Correlation coefficient The rate-temperature dependence|
From Levinthal’s paradox in 1969 it is widely accepted that the deeper understanding of protein folding mechanism is a kernel problem for the successful computational prediction of protein structure. The study of protein folding rate is also an important step for the understanding of the complicate relations between protein folding mechanisms and the sequence-structure-function. The problem of protein folding mechanisms pushes forward the progress of folding experiments. Twenty years ago, two key issues plagued the laboratory workers. One is how to measure folding event in a time scale shorter than milliseconds. Another is how to follow the trail of all events in a folded monomer. Now, the matured application of the experimental methods such as laser temperature-jump technique, the single molecule experimental techniques and so on and the accumulation of accurate experimental data of protein folding kinetics bring unprecedented new opportunities for the theoretical study of protein folding.The conformation of a protein is fully determined by bond lengths, bond angles, and torsion angles (dihedral angles). The torsion angles are most easily changed even at room temperature and commonly accepted as the main variables of protein conformation. So, the quantum theory of conformational transitions assumes that the torsion state is important for multi-atom system.Unlike the classical theory of folding kinetics the protein folding is regarded as a quantum transition between torsion states on polypeptide chain. According to quantum theory of conformational dynamics, the dynamical contact order (DCO), a characteristic of the contact described by the moment of inertia and the torsion potential energy of the polypeptide chain between contact residues, is put forward. Consequently, the protein folding rate can be quantitatively studied from the point of view of dynamics. Through the comparison between theoretical calculations and experimental data on the folding rate of 80 proteins, the point of view on protein folding as a quantum conformational transition is validated, and the following conclusions have been obtained:1) The correlation between the protein folding rate and the contact inertial moment does exist. That there is significant positive correlation between the series connection factor of moment of inertia and the protein folding rate, a negative correlation between the parallel connection factor of moment of inertia and the protein folding rate; 2) The multi-state protein folding can be regarded as the similar quantum conformational transition as two-state protein but with intermediate delay and the order of magnitude of the delay time is estimated; 3) The folding can be classified into two types, exergonic and endergonic, the protein folding speed limit is decided by exergonic folding, and most of the two-state proteins with higher folding rate are exergonic and most of the multi-state proteins with low folding rate are endergonic. Following the point of protein folding as a quantum transition we study the classification and recognition of folding kinetics. In according to that the torsion state is the most important factor of protein conformation, we study how the folding kinetic order and folding rate is correlated with the torsion state number of all contact residues in given polypeptide chain. Using parameters of torsion modes between contact residues and chain length, our results indicate that the two-state folding proteins and multi-state folding proteins can effectively be distinguish by quadratic discriminant analysis algorithms. The total precision of classification is more than 82%, the Matthews correlation coefficient is more than 0.62 based on experimental data of 63 proteins and 80 proteins. Using torsion state number of contact residues and chain length as independent variables the dual linear regression analysis is carried out. The protein folding rate is predicted on two data sets. The correlation coefficient between predicted and experimental values is 0.72 and 0.86, respectively.All results support the view that the protein folding mechanisms should be better understood based on quantum theory. This work joins the growing list of research that links quantum phenomena to biological processes. If it holds up it’s like discovering a brave new world of complexity in the realm of biology. It can only be a matter of time before the floodgates open for quantum biologists.