scholarly journals Experimental Evidence for Information Redundancy in Amino Acid Sequences: Implication for Protein Folding and Evolution.

2001 ◽  
Vol 41 (5) ◽  
pp. 224-229
Author(s):  
Satoshi AKANUMA ◽  
Yutaka KURODA
Keyword(s):  
Protein Folding ◽  
Amino Acid ◽  
Experimental Evidence ◽  
Amino Acid Sequences ◽  
Information Redundancy

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

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.

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.

Genetic Identification of Amino Acid Sequences Influencing Protein Folding

1973 ◽  
pp. 275-291
Author(s):  
JONATHAN KING ◽  
MYEONG-HEE YU ◽  
JAVED SIDDIQI ◽  
CAMERON HAASE
Keyword(s):  
Protein Folding ◽  
Amino Acid ◽  
Amino Acid Sequences ◽  
Genetic Identification

COVARIATION ANALYSIS OF LOCAL AMINO ACID SEQUENCES IN RECURRENT PROTEIN LOCAL STRUCTURES

2005 ◽  
Vol 03 (06) ◽  
pp. 1391-1409 ◽  
Author(s):  
LU-YONG WANG
Keyword(s):  
Protein Folding ◽  
Amino Acid ◽  
Local Structure ◽  
Structural Information ◽  
Statistical Significance ◽  
Amino Acid Sequences ◽  
Structural Motifs ◽  
Systematic Analysis ◽  
Local Structures ◽  
Covariation Analysis

Local structural information is supposed to be frequently encoded in local amino acid sequences. Previous research only indicated that some local structure positions have specific residue preferences in some particular local structures. However, correlated pairwise replacements for interacting residues in recurrent local structural motifs from unrelated proteins have not been studied systematically. We introduced a new method fusing statistical covariation analysis and local structure-based alignment. Systematic analysis of structure-based multiple alignments of recurrent local structures from unrelated proteins in representative subset of Protein Databank indicates that covarying residue pairs with statistical significance exist in local structural motifs, in particular β-turns and helix caps. These residue pairs are mostly linked through polar functional groups with direct or indirect hydrogen bonding. Hydrophobic interaction is also a major factor in constraining pairwise amino acid residue replacement in recurrent local structures. We also found correlated residue pairs that are not clearly linked with through-space interactions. The physical constrains underlying these covariations are less clear. Overall, covarying residue pairs with statistical significance exist in local structures from unrelated proteins. The existence of sequence covariations in local structural motifs from unrelated proteins indicates that many relics of local relations are still retained in the tertiary structures after protein folding. It supports the notion that some local structural information is encoded in local sequences and the local structural codes could play important roles in determining native state protein folding topology.

scholarly journals Probing Protein Folding with Sequence-Reversed α-Helical Bundles

2021 ◽  
Vol 22 (4) ◽  
pp. 1955
Author(s):  
Aikaterini Kefala ◽  
Maria Amprazi ◽  
Efstratios Mylonas ◽  
Dina Kotsifaki ◽  
Mary Providaki ◽  
...  
Keyword(s):  
Protein Folding ◽  
Amino Acid ◽  
Amino Acid Sequences ◽  
Size Exclusion ◽  
Heptad Repeat ◽  
Amino Acid Residues ◽  
Helical Bundles ◽  
X Ray Scattering ◽  
Exclusion Chromatography ◽  
Heptad Repeats

Recurrent protein folding motifs include various types of helical bundles formed by α-helices that supercoil around each other. While specific patterns of amino acid residues (heptad repeats) characterize the highly versatile folding motif of four-α-helical bundles, the significance of the polypeptide chain directionality is not sufficiently understood, although it determines sequence patterns, helical dipoles, and other parameters for the folding and oligomerization processes of bundles. To investigate directionality aspects in sequence-structure relationships, we reversed the amino acid sequences of two well-characterized, highly regular four-α-helical bundle proteins and studied the folding, oligomerization, and structural properties of the retro-proteins, using Circular Dichroism Spectroscopy (CD), Size Exclusion Chromatography combined with Multi-Angle Laser Light Scattering (SEC-MALS), and Small Angle X-ray Scattering (SAXS). The comparison of the parent proteins with their retro-counterparts reveals that while the α-helical character of the parents is affected to varying degrees by sequence reversal, the folding states, oligomerization propensities, structural stabilities, and shapes of the new molecules strongly depend on the characteristics of the heptad repeat patterns. The highest similarities between parent and retro-proteins are associated with the presence of uninterrupted heptad patterns in helical bundles sequences.

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.

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