Complexity in Protein Folding: Simulation Meets Experiment

2012 ◽  
Vol 2 (1) ◽  
pp. 4-11
Author(s):  
Amedeo Caflisch ◽  
Peter Hamm
Author(s):  
Morad Behandish ◽  
Pouya Tavousi ◽  
Horea T. Ilieş ◽  
Kazem Kazerounian

A realistic computer simulation of protein folding requires a comprehensive account of interaction energetics, placing a substantial demand on processing power. This paper presents an improved computational framework for protein folding software package PROTOFOLD, that enables efficient computation of solvation free energy effects in addition to Coulombic and van der Waals interactions. Efficient data structures have been utilized to speed-up the sequential running times from O(n2) to O(n), n being the number of atoms. It turns out, however, that an accurate evaluation of molecular surface areas characterizing the solvation effects imposes a computational bottleneck to the entire simulation. Massive computational power offered by Graphics Processing Units (GPU) was exploited to develop a simple and efficient Single-Instruction Multiple-Thread (SIMT) algorithm for the latter step. The running times were monitored for different steps of the folding simulation for different molecular sizes. Significant performance improvements were observed, yielding promising results where numerous iterative runs are needed.


2002 ◽  
Vol 42 (supplement2) ◽  
pp. S51
Author(s):  
T. Ando ◽  
T. Meguro ◽  
I. Yamato

1990 ◽  
Vol 8 (4) ◽  
pp. 232
Author(s):  
Toshihiro Yamada ◽  
Mitsunori Ikeguchi ◽  
Junta Doi

2006 ◽  
Vol 106 (5) ◽  
pp. 1898-1916 ◽  
Author(s):  
Valerie Daggett

Author(s):  
Pouya Tavousi ◽  
Morad Behandish ◽  
Kazem Kazerounian ◽  
Horea T. Ilieş

Protein structure prediction remains one of the significant challenges in computational biology. We have previously shown that our kinetostatic compliance method can overcome some of the key difficulties faced by other de novo structural prediction methods, such as the very small time steps required by the molecular dynamics approaches, or the very large number of samples required by the sampling based techniques. In this paper we extend the previous free energy formulation by adding the solvent effects, which contribute predominantly to the folding phenomena. We show that the addition of the solvation effects, which complement the existing Coulombic and van der Waals interactions, lead to a physically effective energy function. Furthermore, we achieve significant computational speed-up by employing efficient algorithms and data structures that effectively reduce the time complexity from O(n2) to O(n), n being the number of atoms. Our simulations are consistent with the general behavior observed in protein folding, and show that the hydrophobic atoms tend to pack inside the core of the molecule in an aqueous solvent, while a vacuum environment produces no such effect.


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