scholarly journals FOLD-RATE: prediction of protein folding rates from amino acid sequence

2006 ◽  
Vol 34 (Web Server) ◽  
pp. W70-W74 ◽  
Author(s):  
M. M. Gromiha ◽  
A. M. Thangakani ◽  
S. Selvaraj
Keyword(s):  
Protein Folding ◽  
Amino Acid ◽  
Amino Acid Sequence ◽  
Folding Rates ◽  
Rate Prediction

Swfoldrate: Predicting protein folding rates from amino acid sequence with sliding window method

2012 ◽  
Vol 81 (1) ◽  
pp. 140-148 ◽  
Author(s):  
Xiang Cheng ◽  
Xuan Xiao ◽  
Zhi-cheng Wu ◽  
Pu Wang ◽  
Wei-zhong Lin
Keyword(s):  
Protein Folding ◽  
Amino Acid ◽  
Amino Acid Sequence ◽  
Sliding Window ◽  
Folding Rates ◽  
Window Method ◽  
Sliding Window Method

PREDICTING PROTEIN FOLDING RATE FROM AMINO ACID SEQUENCE

2011 ◽  
Vol 09 (01) ◽  
pp. 1-13 ◽  
Author(s):  
JIANXIU GUO ◽  
NINI RAO
Keyword(s):  
Protein Folding ◽  
Amino Acid ◽  
Amino Acid Sequence ◽  
Structural Information ◽  
Protein Structures ◽  
Amino Acid Sequences ◽  
Folding Rate ◽  
Jackknife Test ◽  
Folding Rates ◽  
Protein Folding Rate

Predicting protein folding rate from amino acid sequence is an important challenge in computational and molecular biology. Over the past few years, many methods have been developed to reflect the correlation between the folding rates and protein structures and sequences. In this paper, we present an effective method, a combined neural network — genetic algorithm approach, to predict protein folding rates only from amino acid sequences, without any explicit structural information. The originality of this paper is that, for the first time, it tackles the effect of sequence order. The proposed method provides a good correlation between the predicted and experimental folding rates. The correlation coefficient is 0.80 and the standard error is 2.65 for 93 proteins, the largest such databases of proteins yet studied, when evaluated with leave-one-out jackknife test. The comparative results demonstrate that this correlation is better than most of other methods, and suggest the important contribution of sequence order information to the determination of protein folding rates.

Predicting Protein Folding Rate From Amino Acid Sequence

2011 ◽  
Vol 37 (12) ◽  
pp. 1331-1338 ◽  
Author(s):  
Jian-Xiu GUO ◽  
Ni-Ni RAO ◽  
Guang-Xiong LIU ◽  
Jie LI ◽  
Yun-He WANG
Keyword(s):  
Protein Folding ◽  
Amino Acid ◽  
Amino Acid Sequence ◽  
Folding Rate ◽  
Protein Folding Rate

Protein Folding Kinetic Order Prediction from Amino Acid Sequence Based on Horizontal Visibility Network

2016 ◽  
Vol 11 (2) ◽  
pp. 173-185 ◽  
Author(s):  
Zhi-Qin Zhao ◽  
Zu-Guo Yu ◽  
Vo Anh ◽  
Jing-Yang Wu ◽  
Guo-Sheng Han
Keyword(s):  
Protein Folding ◽  
Amino Acid ◽  
Amino Acid Sequence ◽  
Horizontal Visibility ◽  
Kinetic Order

scholarly journals Prediction of protein folding class using global description of amino acid sequence.

1995 ◽  
Vol 92 (19) ◽  
pp. 8700-8704 ◽  
Author(s):  
I. Dubchak ◽  
I. Muchnik ◽  
S. R. Holbrook ◽  
S. H. Kim
Keyword(s):  
Protein Folding ◽  
Amino Acid ◽  
Amino Acid Sequence

The Influence of Dipeptide Composition on Protein Folding Rates

2011 ◽  
Vol 378-379 ◽  
pp. 157-160
Author(s):  
Jian Xiu Guo ◽  
Ni Ni Rao
Keyword(s):  
Protein Folding ◽  
Amino Acid ◽  
Amino Acid Sequences ◽  
Dipeptide Composition ◽  
Coupling Effects ◽  
Jackknife Test ◽  
Folding Rates ◽  
Important Challenge ◽  
The Relationship

Understanding the relationship between amino acid sequences and folding rates of proteins is an important challenge in computational and molecular biology. All existing algorithms for predicting protein folding rates have never taken into account the sequence coupling effects. In this work, a novel algorithm was developed for predicting the protein folding rates from amino acid sequences. The prediction was achieved on the basis of dipeptide composition, in which the sequence coupling effects are explicitly included through a series of conditional probability elements. Based on a non-redundant dataset of 99 proteins, the proposed method was found to provide an excellent agreement between the predicted and experimental folding rates of proteins when evaluated with the jackknife test. The correlation coefficient was 87.7% and the standard error was 2.04, which indicated the important contribution from sequence coupling effects to the determination of protein folding rates.

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