scholarly journals Protein folding while chaperone bound is dependent on weak interactions

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Kevin Wu ◽  
Frederick Stull ◽  
Changhan Lee ◽  
James C. A. Bardwell
Keyword(s):  
Protein Folding ◽  
Weak Interactions ◽  
Client Protein ◽  
Native State ◽  
Folding Rate ◽  
Sufficient Strength ◽  
Surprising Observation

Abstract It is generally assumed that protein clients fold following their release from chaperones instead of folding while remaining chaperone-bound, in part because binding is assumed to constrain the mobility of bound clients. Previously, we made the surprising observation that the ATP-independent chaperone Spy allows its client protein Im7 to fold into the native state while continuously bound to the chaperone. Spy apparently permits sufficient client mobility to allow folding to occur while chaperone bound. Here, we show that strengthening the interaction between Spy and a recently discovered client SH3 strongly inhibits the ability of the client to fold while chaperone bound. The more tightly Spy binds to its client, the more it slows the folding rate of the bound client. Efficient chaperone-mediated folding while bound appears to represent an evolutionary balance between interactions of sufficient strength to mediate folding and interactions that are too tight, which tend to inhibit folding.

scholarly journals The protein folding rate and the geometry and topology of the native state

2021 ◽  
Author(s):  
Jason J Wang ◽  
Eleni Panagiotou
Keyword(s):  
Protein Folding ◽  
Local Geometry ◽  
Native State ◽  
Folding Rate ◽  
New Developments ◽  
3 Dimensional ◽  
And Topology ◽  
Small Set ◽  
Protein Folding Rate ◽  
Topological Characteristics

Proteins fold in 3-dimensional conformations which are important for their function. Characterizing the global conformation of proteins rigorously and separating secondary structure effects from topological effects is a challenge. New developments in Applied Knot Theory allow to characterize the topological characteristics of proteins (knotted or not). By analyzing a small set of two-state and multi-state proteins with no knots or slipknots, our results show that 95.4% of the analyzed proteins have non-trivial topological characteristics, as reflected by the second Vassiliev measure, and that the logarithm of the experimental protein folding rate depends on both the local geometry and the topology of the protein's native state.

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

An Effective Cumulative Torsion Angles Model for Prediction of Protein Folding Rates

2020 ◽  
Vol 27 (4) ◽  
pp. 321-328 ◽  
Author(s):  
Yanru Li ◽  
Ying Zhang ◽  
Jun Lv
Keyword(s):  
Protein Folding ◽  
Size Structure ◽  
Conformational Space ◽  
Coefficient Of Determination ◽  
Folding Rate ◽  
Torsion Angles ◽  
Folding Rates ◽  
Protein Folding Rate ◽  
Optimal Set ◽  
Conformation Space

Background: Protein folding rate is mainly determined by the size of the conformational space to search, which in turn is dictated by factors such as size, structure and amino-acid sequence in a protein. It is important to integrate these factors effectively to form a more precisely description of conformation space. But there is no general paradigm to answer this question except some intuitions and empirical rules. Therefore, at the present stage, predictions of the folding rate can be improved through finding new factors, and some insights are given to the above question. Objective: Its purpose is to propose a new parameter that can describe the size of the conformational space to improve the prediction accuracy of protein folding rate. Method: Based on the optimal set of amino acids in a protein, an effective cumulative backbone torsion angles (CBTAeff) was proposed to describe the size of the conformational space. Linear regression model was used to predict protein folding rate with CBTAeff as a parameter. The degree of correlation was described by the coefficient of determination and the mean absolute error MAE between the predicted folding rates and experimental observations. Results: It achieved a high correlation (with the coefficient of determination of 0.70 and MAE of 1.88) between the logarithm of folding rates and the (CBTAeff)0.5 with experimental over 112 twoand multi-state folding proteins. Conclusion: The remarkable performance of our simplistic model demonstrates that CBTA based on optimal set was the major determinants of the conformation space of natural proteins.

The Influences of Palindromes in mRNA on Protein Folding Rates

2020 ◽  
Vol 27 (4) ◽  
pp. 303-312 ◽  
Author(s):  
Ruifang Li ◽  
Hong Li ◽  
Sarula Yang ◽  
Xue Feng
Keyword(s):  
Protein Folding ◽  
Regression Analysis ◽  
Linear Regression ◽  
Linear Regression Analysis ◽  
Folding Rate ◽  
Folding Rates ◽  
Negative Linear Correlation ◽  
Protein Folding Rate ◽  
The Relationship ◽  
Structure Environment

Background: It is currently believed that protein folding rates are influenced by protein structure, environment and temperature, amino acid sequence and so on. We have been working for long to determine whether and in what ways mRNA affects the protein folding rate. A large number of palindromes aroused our attention in our previous research. Whether these palindromes do have important influences on protein folding rates and what’s the mechanism? Very few related studies are focused on these problems. Objective: In this article, our motivation is to find out if palindromes have important influences on protein folding rates and what’s the mechanism. Method: In this article, the parameters of the palindromes were defined and calculated, the linear regression analysis between the values of each parameter and the experimental protein folding rates were done. Furthermore, to compare the results of different kinds of proteins, proteins were classified into the two-state proteins and the multi-state proteins. For the two kinds of proteins, the above linear regression analysis were performed respectively. Results : Protein folding rates were negatively correlated to the palindrome frequencies for all proteins. An extremely significant negative linear correlation appeared in the relationship between palindrome densities and protein folding rates. And the repeatedly used bases by different palindromes simultaneously have an important effect on the relationship between palindrome density and protein folding rate. Conclusion: The palindromes have important influences on protein folding rates, and the repeatedly used bases in different palindromes simultaneously play a key role in influencing the protein folding rates.

Self-Similarity of Protein Folding Flows

2012 ◽  
Vol 7 (4) ◽  
pp. 136-141
Author(s):  
I. Kalgin ◽  
Sergey Chekmarev
Keyword(s):  
Protein Folding ◽  
Sh3 Domain ◽  
Atomic Level ◽  
The Self ◽  
Coarse Grained ◽  
Folding Kinetics ◽  
Native State ◽  
Self Similarity ◽  
Folding Dynamics ◽  
Fractal Character

The problem of how a protein folds into its functional (native) state is one of the central problems of molecular biology, which attracts the attention of researchers from biology, physics and chemistry for many years. Of particular interest are general properties of the folding process, because the mechanisms of folding of different proteins can be essentially different. Previously, in the study of folding of fyn SH3 domain, we found that despite all the diversity and complexity of individual folding trajectories, the folding flows possess a well pronounced property of self-similarity, with a fractal character of the flow distributions. In the present paper, we study this phenomenon for another protein – beta3s, which is essentially different from the SH3 domain in its structure and folding kinetics. Also, in contrast to the fyn SH3 domain, for which a coarse-grained representation was used, we perform simulations on the atomic level of resolution. We show that the self-similarity and fractality of folding flows are observed is this case too, which suggests that these properties are characteristic of the protein folding dynamics

scholarly journals Folding Rate Optimization Promotes Frustrated Interactions in Entangled Protein Structures

2019 ◽  
Vol 21 (1) ◽  
pp. 213
Author(s):  
Federico Norbiato ◽  
Flavio Seno ◽  
Antonio Trovato ◽  
Marco Baiesi
Keyword(s):  
Amino Acids ◽  
Structural Biology ◽  
Weak Interactions ◽  
Protein Structures ◽  
Protein Sequences ◽  
Control Case ◽  
Folding Rate ◽  
Empirical Observation ◽  
Rate Optimization ◽  
Kinetic Traps

Many native structures of proteins accomodate complex topological motifs such as knots, lassos, and other geometrical entanglements. How proteins can fold quickly even in the presence of such topological obstacles is a debated question in structural biology. Recently, the hypothesis that energetic frustration might be a mechanism to avoid topological frustration has been put forward based on the empirical observation that loops involved in entanglements are stabilized by weak interactions between amino-acids at their extrema. To verify this idea, we use a toy lattice model for the folding of proteins into two almost identical structures, one entangled and one not. As expected, the folding time is longer when random sequences folds into the entangled structure. This holds also under an evolutionary pressure simulated by optimizing the folding time. It turns out that optmized protein sequences in the entangled structure are in fact characterized by frustrated interactions at the closures of entangled loops. This phenomenon is much less enhanced in the control case where the entanglement is not present. Our findings, which are in agreement with experimental observations, corroborate the idea that an evolutionary pressure shapes the folding funnel to avoid topological and kinetic traps.

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