A Statistical Model for Predicting Protein Folding Rates from Amino Acid Sequence with Structural Class Information

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.

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Predicting Protein Folding Rate From Amino Acid Sequence

PROGRESS IN BIOCHEMISTRY AND BIOPHYSICS ◽

10.3724/sp.j.1206.2010.00380 ◽

2011 ◽

Vol 37 (12) ◽

pp. 1331-1338 ◽

Cited By ~ 3

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

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

Current Bioinformatics ◽

10.2174/1574893611666160125221326 ◽

2016 ◽

Vol 11 (2) ◽

pp. 173-185 ◽

Cited By ~ 2

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

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

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.92.19.8700 ◽

1995 ◽

Vol 92 (19) ◽

pp. 8700-8704 ◽

Cited By ~ 291

Author(s):

I. Dubchak ◽

I. Muchnik ◽

S. R. Holbrook ◽

S. H. Kim

Keyword(s):

Protein Folding ◽

Amino Acid ◽

Amino Acid Sequence

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The Influence of Dipeptide Composition on Protein Folding Rates

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.378-379.157 ◽

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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Study on the Influence of mRNA, the Genetic Language, on Protein Folding Rates

Frontiers in Genetics ◽

10.3389/fgene.2021.635250 ◽

2021 ◽

Vol 12 ◽

Author(s):

Ruifang Li ◽

Hong Li ◽

Xue Feng ◽

Ruifeng Zhao ◽

Yongxia Cheng

Keyword(s):

Protein Folding ◽

Amino Acid ◽

Protein Structures ◽

Gc Content ◽

Amino Acid Sequences ◽

Information Redundancy ◽

Folding Rate ◽

Folding Rates ◽

Related Information ◽

Linear Regressions

Many works have reported that protein folding rates are influenced by the characteristics of amino acid sequences and protein structures. However, few reports on the problem of whether the corresponding mRNA sequences are related to the protein folding rates can be found. An mRNA sequence is regarded as a kind of genetic language, and its vocabulary and phraseology must provide influential information regarding the protein folding rate. In the present work, linear regressions on the parameters of the vocabulary and phraseology of mRNA sequences and the corresponding protein folding rates were analyzed. The results indicated that D2 (the adjacent base-related information redundancy) values and the GC content values of the corresponding mRNA sequences exhibit significant negative relations with the protein folding rates, but D1 (the single base information redundancy) values exhibit significant positive relations with the protein folding rates. In addition, the results show that the relationships between the parameters of the genetic language and the corresponding protein folding rates are obviously different for different protein groups. Some useful parameters that are related to protein folding rates were found. The results indicate that when predicting protein folding rates, the information from protein structures and their amino acid sequences is insufficient, and some information for regulating the protein folding rates must be derived from the mRNA sequences.

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