[show abstract][hide abstract] ABSTRACT: Ab initio protein structure prediction is a challenging problem that requires both an accurate energetic representation of a protein structure and an efficient conformational sampling method for successful protein modeling. In this article, we present an ab initio structure prediction method which combines a recently suggested novel way of fragment assembly, dynamic fragment assembly (DFA) and conformational space annealing (CSA) algorithm. In DFA, model structures are scored by continuous functions constructed based on short- and long-range structural restraint information from a fragment library. Here, DFA is represented by the full-atom model by CHARMM with the addition of the empirical potential of DFIRE. The relative contributions between various energy terms are optimized using linear programming. The conformational sampling was carried out with CSA algorithm, which can find low energy conformations more efficiently than simulated annealing used in the existing DFA study. The newly introduced DFA energy function and CSA sampling algorithm are implemented into CHARMM. Test results on 30 small single-domain proteins and 13 template-free modeling targets of the 8th Critical Assessment of protein Structure Prediction show that the current method provides comparable and complementary prediction results to existing top methods.
Proteins Structure Function and Bioinformatics 04/2011; 79(8):2403-17. · 3.34 Impact Factor
[show abstract][hide abstract] ABSTRACT: De novo prediction of protein structures, the prediction of structures from amino acid sequences which are not similar to those of hitherto resolved structures, has been one of the major challenges in molecular biophysics. In this paper, we develop a new method of de novo prediction, which combines the fragment assembly method and the simulation of physical folding process: structures which have consistently assembled fragments are dynamically searched by Langevin molecular dynamics of conformational change. The benchmarking test shows that the prediction is improved when the candidate structures are cross-checked by an empirically derived score function.
Biochemical and Biophysical Research Communications 06/2008; 369(2):500-6. · 2.41 Impact Factor
[show abstract][hide abstract] ABSTRACT: A new multi-body energy function is constructed to reproduce protein structure from sequence. As a benchmark test of the method, low energy structures of α, α/β, and β proteins are searched with the Langevin molecular dynamics calculation. Similarities among thus generated structures and the native ones showed that the present approach is a step forward in constructing the method which has the physical analogy for the folding process.
Chemical Physics Letters 01/2005; 402:102-106. · 2.15 Impact Factor
[show abstract][hide abstract] ABSTRACT: Non-exponential relaxation in a simplified lattice model of folding is studied with Monte Carlo (MC) calculation. As folding proceeds, population of the native conformation approaches its equilibrium value with the stretched exponential form. As temperature increases, relaxation becomes less stretched, and for 2 sequences out of 5 tested ones, the relaxation becomes faster than exponential at high temperature. Energy landscape of the model is analyzed and flow of trajectories is followed to explain temperature dependence of kinetics. Measurement of stretched or shrunken kinetics of folding should help to understand nature of intermediates and ruggedness of the landscape.
Chemical Physics Letters - CHEM PHYS LETT. 01/2001; 347(1):247-254.