Effect of chaperone–client interaction strength on Hsp70-mediated protein folding

Protein folding in crowding cellular environment often relies on the assistance of various chaperones. Hsp70 is one of the most ubiquitous chaperones in cells. Previous studies showed that the chaperone–client interactions at the open state tend to remodel the protein folding energy landscape and direct the protein folding as a foldase. In this work, we further investigate how the chaperone–client interaction strength modulates the foldase function of Hsp70 by using molecular simulations. The results showed that the time of substrate folding(including the whole folding step and substrate release step) has a non-monotonic dependence on the interaction strength. With the increasing of the chaperone–client interaction strength, the folding time decreases first, and then increases. More detailed analysis showed that when the chaperone–client interaction is too strong, even small number of chaperones–client contacts can maintain the substrate bound with the chaperone. The sampling of the transient chaperones–client complex with sparse inter-molecule contacts makes the client protein have chance to access the misfolded state even it is bound with chaperone. The current results suggest that the interaction strength is an important factor controlling the Hsp70 chaperoning function.

Respective Roles of Short-and Long-Range Interactions in Protein Folding

A new method was presented to discuss the respective roles of short- and long-range interactions in protein folding. It's based on an off-lattice model, which is also being called as toy model. Simulated annealing algorithm was used to search its native conformation. When it is applied to analysis proteins 1agt and 1aho, we find that helical segment cannot fold into native conformation without the influence of long-range interactions. That's to say that long-range interactions are the main determinants in protein folding. Key words toy model - protein folding - simulated annealing algorithm - short and long range interactions CLC number O 242.28 - Q71 Foundation item: Supported by the National Natural Science Foundation of China((60301009)Biography: WANG Long-hui (1976-), female, Ph. D candidate, research direction: machine learning, bioinformatics.

A Simulated Annealing Algorithm for Training Empirical Potential Functions of Protein Folding

In this paper are reported the local minimum problem by means of current greedy algorithm for training the empirical potential function of protein folding on 8623 non-native structures of 31 globular proteins and a solution of the problem based upon the simulated annealing algorithm. This simulated annealing algorithm is indispensable for developing and testing highly refined empirical potential functions.

Heuristic algorithm for off-lattice protein folding problem

Enlightened by the law of interactions among objects in the physical world, we propose a heuristic algorithm for solving the three-dimensional (3D) off-lattice protein folding problem. Based on a physical model, the problem is converted from a nonlinear constraint-satisfied problem to an unconstrained optimization problem which can be solved by the well-known gra- dient method. To improve the efficiency of our algorithm, a strategy was introduced to generate initial configuration. Computa- tional results showed that this algorithm could find states with lower energy than previously proposed ground states obtained by nPERM algorithm for all chains with length ranging from 13 to 55.

Mixed Search Algorithm for Protein Folding

Computer simulations of simple exact lattice models are an aid in the study of protein folding process. We proposed a new search strategy by two hierarchy optimization techniques, which is shown very efficient.

Application of topological soliton in modeling protein folding: Recent progress and perspective

Proteins are important biological molecules whose structures are closely related to their specific functions. Understanding how the protein folds under physical principles, known as the protein folding problem, is one of the main tasks in modern biophysics. Coarse-grained methods play an increasingly important role in the simulation of protein folding, especially for large proteins. In recent years, we proposed a novel coarse-grained method derived from the topological soliton model, in terms of the backbone Cα chain. In this review, we will first systematically address the theoretical method of topological soliton. Then some successful applications will be displayed, including the thermodynamics simulation of protein folding, the property analysis of dynamic conformations, and the multi-scale simulation scheme. Finally, we will give a perspective on the development and application of topological soliton.

High Performance Hydrophobic Interaction Chromatography-A New Approach to Separate Intermediates of Protein Folding──Ⅰ.Separation of Intermediates of Urea-unfolded α-Amylase

Based on the different hydrophobicities of the intermediates of proteins the various conformational intermediates of the refolding of a-amylase originally denatured with 8.0 mol/L urea solution were separated with high performance hydrophobic interaction chromatography(HPHIC). Compared to the separation of the same intermediates with weak anion exchange chromatography and size-exclusion chromatography the result obtained with HPHIC is the best It would be expected that HPHIC may be a strongly potential tool to separate intermediates of some proteins which cannot be, or cannot completely be refolded by HPHIC.

Nanosecond-time-resolved infrared spectroscopic study of fast relaxation kinetics of protein folding by means of laser-induced temperature-jump

Elucidating the initial kinetics of folding pathways is critical to the understanding of the protein folding mechanism. Transient infrared spectroscopy has proved a powerful tool to probe the folding kinetics. Herein we report the construction of a nanosecond laser-induced temperature-jump （T-jump） technique coupled to a nanosecond timeresolved transient mid-infrared （mid-IR） spectrometer system capable of investigating the protein folding kinetics with a temporal resolution of 50 ns after deconvolution of the instrumental response function. The mid-IR source is a liquid N2 cooled CO laser covering a spectral range of 5.0μm （2000 cm^-1）-6.5μm （1540 cm^-1）. The heating pulse was generated by a high pressure H2 Raman shifter at wavelength of 1.9μm. The maximum temperature-jump could reach as high as 26±1℃. The fast folding/unfolding dynamics of cytochrome C was investigated by the constructed system, providing an example.

Protein structural codes and nucleation sites for protein folding

One of the long-standing controversial arguments in protein folding is Levinthal＇s paradox. We have recently proposed a new nucleation hypothesis and shown that the nucleation residues are the most conserved sequences in protein. To avoid the complicated effect of tertiary interactions, we limit our search for structural codes to the nucleation residues. Starting with the hypotheses of secondary structure nucleation and conservation of residues important for folding, we have analysed 762 folds classified as unique by SCOP. Segments of 17 residues around the top 20% conserved amino acids are analysed, resulting in approximately 100 clusters each for the main secondary structure classes of helix, sheet and coil. Helical clusters have the longest correlation range, coils the shortest （four residues）. Strong specific sequence-structure correlation is observed for coil but not for helix and sheet, suggesting a mapping relationship between the sequence and the structure for coil. We propose that the central sequences in these clusters form ＇structural codes＇, a useful basis set for identifying nucleation sites, protein fragments stable in isolation, and secondary structural patterns in proteins （particularly turns and loops）.

Quantum intelligence on protein folding pathways

We study the protein folding problem on the base of our quantum approach by considering the model of protein chain with nine amino-acid residues.We introduce the concept of distance space and its projections on a XY-plane,and two characteristic quantities,one is called compactness of protein structure and another is called probability ratio involving shortest path.The concept of shortest path enables us to reduce the 388×388 density matrix to a 2×2 one from which the von Neumann entropy reflecting certain quantum coherence feature is naturally defined.We observe the time evolution of average distance and compactness solved from the classical random walk and quantum walk,we also compare the features of the time-dependence of Shannon entropy and von Neumann entropy.All the results not only reveal the fast quantum folding time but also unveil the existence of quantum intelligence hidden behind in choosing protein folding pathways.

Prediction of protein folding rates from primary sequence by fusing multiple sequential features

We have developed a web-server for predicting the folding rate of a protein based on its amino acid sequence information alone. The web- server is called Pred-PFR (Predicting Protein Folding Rate). Pred-PFR is featured by fusing multiple individual predictors, each of which is established based on one special feature derived from the protein sequence. The ensemble pre-dictor thus formed is superior to the individual ones, as demonstrated by achieving higher correlation coefficient and lower root mean square deviation between the predicted and observed results when examined by the jack-knife cross-validation on a benchmark dataset constructed recently. As a user-friendly web- server, Pred-PFR is freely accessible to the public at www.csbio.sjtu.edu.cn/bioinf/Folding Rate/.

Protein folding, protein homeostasis,and cancer

Proteins fold into their functional 3-dimensional structures from a linear amino acid sequence. In vitro this process is spontaneous; while in vivo it is orchestrated by a specialized set of proteins, called chaperones. Protein folding is an ongoing cellular process, as cellular proteins constantly undergo synthesis and degradation. Here emerging links between this process and cancer are reviewed. This perspective both yields insights into the current struggle to develop novel cancer chemotherapeutics and has implications for future chemotherapy discovery.

Quasi-physical Algorithm for Protein Folding in an Off-Lattice Model

<正> We study a three-dimensional off-lattlce protein folding model,which involves two species of residuesinteracting through Lennard-Jones potentials.By incorporating an extra energy contribution into the original potentialfunction,we replace the original constrained problem with an unconstrained minimization of a mixed potential function.As such an efficient quasi-physical algorithm for solving the protein folding problem is presented.We apply the proposedalgorithm to sequences with up to 55 residues and compare the computational results with the putative lowest energyfound by several of the most famous algorithms,showing the advantages of our method.The dynamic behavior of thequasi-physical algorithm is also discussed.

The Rise and Fall of the Hydrophobic Effect in Protein Folding and Protein-Protein Association, and Molecular Recognition

In the beginning everything was explained in Biochemistry in terms of hydrogen-bonds (HB). Then, the devastating blow, known as the HB-inventory argument came;hydrogen bonding with water molecules compete with intramolecular hydrogen-bonds. As a result, the HBs paradigm fell from grace. The void created was immediately filled by Kauzmann’s idea of hydrophobic (HφO) effect which reigned supreme in biochemical literature for over 50 years (1960-2010). Cracks in the HB-inventory argument on one hand, and doubts about the adequacy of Kauzmann’s model for the HφO effect, have led to a comeback of the HBs, along with a host of new hydrophilic (HφI) effects. The HφO effects lost much of its power - which it never really had - in explaining protein folding and protein-protein association. Instead, the more powerful and richer repertoire of HφI effects took over the reins. The interactions also offered simple and straightforward answers to the problems of protein folding, and protein-protein association.

PFP-RFSM: Protein fold prediction by using random forests and sequence motifs

Protein tertiary structure is indispensible in revealing the biological functions of proteins. De novo perdition of protein tertiary structure is dependent on protein fold recognition. This study proposes a novel method for prediction of protein fold types which takes primary sequence as input. The proposed method, PFP-RFSM, employs a random forest classifier and a comprehensive feature representation, including both sequence and predicted structure descriptors. Particularly, we propose a method for generation of features based on sequence motifs and those features are firstly employed in protein fold prediction. PFP-RFSM and ten representative protein fold predictors are validated in a benchmark dataset consisting of 27 fold types. Experiments demonstrate that PFP-RFSM outperforms all existing protein fold predictors and improves the success rates by 2%-14%. The results suggest sequence motifs are effective in classification and analysis of protein sequences.

Thermodynamic Principle Revisited: Theory of Protein Folding

Anfinsen’s thermodynamic hypothesis is reviewed and misunderstandings are clarified. It really should be called the thermodynamic principle of protein folding. Energy landscape is really just the mathematical graph of the Gibbs free energy function G(X;U ,EN), a very high dimensional hyper surface. Without knowing it any picture of the Gibbs free energy landscape has no theoretical base, including the funnel shape claims. New insight given by newly obtained analytic Gibbs free energy function G(X;U ,EN) of protein folding derived via quantum statistical mechanics are discussed. Disputes such as target-based or cause-based;what is the folding force, hydrophobic effect or hydrophilic force? Single molecule or ensemble of molecules to be used for the statistical physics study of protein folding, are discussed. Classical observations of 1970’s and 1980’s about global geometric characteristics of native structures of globular proteins turn out to have grabbed the essence of protein folding, but unfortunately have been largely forgotten.

Does mRNA structure contain genetic information for regulating co-translational protein folding？

Currently many facets of genetic information are illdefined. In particular, how protein folding is genetically regulated has been a long-standing issue for genetics and protein biology. And a generic mechanistic model with supports of genomic data is still lacking. Recent technological advances have enabled much needed genome-wide experiments. While putting the effect of codon optimality on debate, these studies have supplied mounting evidence suggesting a role of m RNA structure in the regulation of protein folding by modulating translational elongation rate. In conjunctions with previous theories, this mechanistic model of protein folding guided by m RNA structure shall expand our understandings of genetic information and offer new insights into various biomedical puzzles.

Advances in the study of protein folding and endoplasmic reticulum-associated degradation in mammal cells

The endoplasmic reticulum is a key site for protein production and quality control.More than one-third of proteins are synthesized and folded into the correct three-dimensional conformation in the endoplasmic reticulum.However,during protein folding,unfolded and/or misfolded proteins are prone to occur,which may lead to endoplasmic reticulum stress.Organisms can monitor the quality of the proteins produced by endoplasmic reticulum quality control(ERQC)and endoplasmic reticulum-associated degradation(ERAD),which maintain endoplasmic reticulum protein homeostasis by degrading abnormally folded proteins.The underlying mechanisms of protein folding and ERAD in mammals have not yet been fully explored.Therefore,this paper reviews the process and function of protein folding and ERAD in mammalian cells,in order to help clinicians better understand the mechanism of ERAD and to provide a scientific reference for the treatment of diseases caused by abnormal ERAD.

Electrostatic and hydrophobic interaction cooperative nanochaperone regulates protein folding

Natural molecular chaperones utilize spatially ordered multiple molecular forces to effectively regulate protein folding.However,synthesis of such molecules is a big challenge.The concept of“aggregate science”provides insights to construct chemical entities(aggregates)beyond molecular levels to mimic both the structure and function of natural chaperone.Inspired by this concept,herein we fabricate a novel multi-interaction(i.e.,electrostatic and hydrophobic interaction)cooperative nanochaperone(multi-co-nChap)to regulating protein folding.This multi-co-nChap is fabricated by rationally introducing electrostatic interactions to the surface(corona)and confined hydrophobic microdomains(shell)of traditional single-hydrophobic interaction nanochaperone.We demonstrate that the corona electrostatic attraction facilitates the diffusion of clients into the hydrophobic microdomains,while the shell electrostatic interaction balances the capture and release of clients.By finely synergizing corona electrostatic attraction with shell electrostatic repulsion and hydrophobic interaction,the optimized multi-co-nChap effectively facilitated de novo folding of nascent polypeptides.Moreover,the synergy between corona electrostatic attraction,shell electrostatic attraction and shell hydrophobic interaction significantly enhanced the capability of multi-co-nChap to protect native proteins from denaturation at harsh temperatures.This work provides important insights for understanding and design of nanochaperone,which is a kind of ordered aggregate with chaperone-like activity that beyond the level of single molecule.