Protein Folding Structure Prediction with Artificial Plant Optimization Algorithm Based Golden Section and Limited Memory Broyden–Fletcher–Goldfarb–Shanno

2013 ◽  
Vol 7 (1) ◽  
pp. 114-120 ◽  
Author(s):  
Dongmei Liu ◽  
Zhihua Cui
Keyword(s):  
Protein Folding ◽  
Optimization Algorithm ◽  
Structure Prediction ◽  
Golden Section ◽  
Limited Memory ◽  
Plant Optimization ◽  
Folding Structure

Protein folding, structure prediction and design

2014 ◽  
Vol 42 (2) ◽  
pp. 225-229 ◽  
Author(s):  
David Baker
Keyword(s):  
Protein Folding ◽  
Protein Structure ◽  
Protein Design ◽  
Structure Prediction ◽  
Experimental Studies ◽  
Folding Rate ◽  
Contact Order ◽  
Folding Structure ◽  
Protein Folding Rate ◽  
Rate Correlation

I describe how experimental studies of protein folding have led to advances in protein structure prediction and protein design. I describe the finding that protein sequences are not optimized for rapid folding, the contact order–protein folding rate correlation, the incorporation of experimental insights into protein folding into the Rosetta protein structure production methodology and the use of this methodology to determine structures from sparse experimental data. I then describe the inverse problem (protein design) and give an overview of recent work on designing proteins with new structures and functions. I also describe the contributions of the general public to these efforts through the Rosetta@home distributed computing project and the FoldIt interactive protein folding and design game.

Using Gravitropism Artificial Plant Optimization Algorithm to Solve Toy Model of Protein Folding

2013 ◽  
Vol 10 (6) ◽  
pp. 1540-1544 ◽  
Author(s):  
Zhihua Cui ◽  
Xu Liu ◽  
Dongmei Liu ◽  
Jianchao Zeng ◽  
Zhongzhi Shi
Keyword(s):  
Protein Folding ◽  
Optimization Algorithm ◽  
Plant Optimization
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