arXiv subjects

Jooyoung Lee

Publications and source records attributed to Jooyoung Lee.

41 records · Page 3Linked to original sources

arXiv2003

Design of a Protein Potential Energy Landscape by Parameter Optimization

We propose an automated protocol for designing the energy landscape of a protein energy function by optimizing its parameters. The parameters are optimized so that not only the global minimum energy conformation becomes native-like, but also the conformations distinct from the native structure have higher energies than those close to the native one. We successfully apply our protocol to the parameter optimization of the UNRES potential energy, using the training set of betanova, 1fsd, the 36-residue subdomain of chicken villin headpiece (PDB ID 1vii), and the 10-55 residue fragment of staphylococcal protein A (PDB ID 1bdd). The new protocol of the parameter optimization shows better performance than earlier methods where only the difference between the lowest energies of native-like and non-native conformations was adjusted without considering various degrees of native-likeness of the conformations. We also perform jackknife tests on other proteins not included in the training set and obtain promising results. The results suggest that the parameters we obtained using the training set of the four proteins are transferable to other proteins to some extent.

cond-mat.soft↗

arXiv2003

Full Optimization of Linear Parameters of a United Residue Protein Potential

We apply the general protocol of parameter optimization (Lee, J. et al. Phys. Chem. B 2001, 105, 7291) to the UNRES potential. In contrast to the earlier works where only the relative weights of various interaction terms were optimized, we optimize all linear parameters of the potential. The method exploits the high efficiency of the conformal space annealing method in finding distinct low energy conformations. For a given training set of proteins, the parameters are modified to make the native-like conformations energetically more favorable than the non-native ones. Linear approximation is used to estimate the energy change due to the parameter modification. The parameter change is followed by local energy reminimization and new conformational searches to find the energies of native-like and non-native local minima of the energy function with new parameters. These steps are repeated until the potential predicts a native-like conformation as one of the low energy conformations for each protein in the training set. We consider a training set of crambin (PDB ID 1ejg), 1fsd, and the 10-55 residue fragment of staphylococcal protein A (PDB ID 1bdd). As the first check for the feasibility of our protocol, we optimize the parameters separately for these proteins and find an optimal set of parameters for each of them. Next we apply the method simultaneously to these three proteins. By refining all linear parameters, we obtain an optimal set of parameters from which the native-like conformations of the all three proteins are retrieved as the global minima, without introducing additional multi-body energy terms.

cond-mat.soft↗

arXiv2003

Unbiased Global Optimization of Lennard-Jones Clusters for N <= 201 by Conformational Space Annealing Method

We apply the conformational space annealing (CSA) method to the Lennard-Jones clusters and find all known lowest energy configurations up to 201 atoms, without using extra information of the problem such as the structures of the known global energy minima. In addition, the robustness of the algorithm with respect to the randomness of initial conditions of the problem is demonstrated by ten successful independent runs up to 183 atoms. Our results indicate that the CSA method is a general and yet efficient global optimization algorithm applicable to many systems.

cond-mat.stat-mech↗

arXiv2003

Conformational space annealing and an off-lattice frustrated model protein

A global optimization method, conformational space annealing (CSA), is applied to study a 46-residue protein with the sequence B_9N_3(LB)_4N_3B_9N_3(LB)_5L, where B, L and N designate hydrophobic, hydrophilic, and neutral residues, respectively. The 46-residue BLN protein is folded into the native state of a four-stranded beta-barrel. It has been a challenging problem to locate the global minimum of the 46-residue BLN protein since the system is highly frustrated and consequently its energy landscape is quite rugged. The CSA successfully located the global minimum of the 46-mer for all 100 independent runs. The CPU time for CSA is about seventy times less than that for simulated annealing (SA), and its success rate (100 %) to find the global minimum is about eleven times higher. The amount of computational efforts used for CSA is also about ten times less than that of the best global optimization method yet applied to the 46-residue BLN protein, the quantum thermal annealing with renormalization. The 100 separate CSA runs produce the global minimum 100 times as well as other 5950 final conformations corresponding to a total of 2361 distinct local minima of the protein. Most of the final conformations have relatively small RMSD values from the global minimum, independent of their diverse energy values. Very close to the global minimum, there exist quasi-global-minima which are frequently obtained as one of the final answers from SA runs. We find that there exist two largest energy gaps between the quasi-global-minima and the other local minima. Once a SA run is trapped in one of these quasi-global-minima, it cannot be folded into the global minimum before crossing over the two large energy barriers, clearly demonstrating the reason for the poor success rate of SA.

cond-mat.stat-mech↗

arXiv2003

Folding Mechanism of Small Proteins

Extensive Monte Carlo folding simulations for four proteins of various structural classes are carried out, using a single atomistic potential. In all cases, collapse occurs at a very early stage, and proteins fold into their native-like conformations at appropriate temperatures. The results demonstrate that the folding mechanism is controlled not only by thermodynamic factors but also by kinetic factors: The way a protein folds into its native structure, is also determined by the convergence point of early folding trajectories, which cannot be obtained by the free energy surface.

cond-mat.stat-mech↗