Nikita V. Dovidchenko

How to determine the size of folding nuclei of protofibrils from the concentration dependence of the rate and lag-time of aggregation. I. Modeling the amyloid protofibril formation

The question about the size of nuclei of formation of protofibrils (which constitute mature amyloid fibrils) formed by different proteins and peptides is yet open and debatable because of the absence of solid knowledge of underlying mechanisms of amyloid formation. In this work, a kinetic model of the process of formation of amyloid protofibrils is suggested, which allows calculation of the size of the nuclei using only kinetic data. In addition to the stage of primary nucleation, which is believed to be present in many protein aggregation processes, the given model includes both linear growth of protofibrils (proceeding only at the cost of attaching of monomers to the ends) and exponential growth of protofibrils at the cost of growth from the surface, branching, and fragmentation with the secondary nuclei. Theoretically, only the exponential growth is compatible with the existence of a pronounced lag-period (which can take much more time then the growth of aggregates themselves). The obtained analytical solution allows us to determine the size of the primary and secondary nuclei from the experimentally obtained concentration dependences of the time of growth and the new parameter-the ratio Lrel of the lag-time duration to the time of growth of amyloid protofibrils.

One of the possible mechanisms of amyloid fibrils formation based on the sizes of primary and secondary folding nuclei of Aβ40 and Aβ42

In the presented paper, theoretical as well as electron microscopy and X-ray diffraction experimental approaches were employed for studding the process of Aβ amyloid formation. Using quantitative estimates of a number of monomers which form the nuclei of amyloid fibrils the sizes of folding nuclei of amyloid fibrils for Aβ40 and 42 have been determined for the first time. We have shown that the size of the primary nucleus of Aβ42 peptide fibrils corresponds to 3 monomers, the size of the secondary nucleus for this peptide is 2 monomers. Applying the same analysis to Aβ40 we conclude that the size of the primary nucleus is 2 monomers, and the size of the secondary nucleus is one monomer. Summation of our theoretical and experimental results has allowed us to propose a new model of the structural organization of amyloid fibrils. Our model suggests that the generation of fibrils takes place along the following simplified pathway: a monomer→a ring oligomer→a mature fibril consisting of ring oligomers. These data shed more light upon our understanding of what sizes of the oligomers could represent main targets for future therapies (tetramers for Aβ42 and trimers for Aβ40), and aid in the development of inhibitors of Aβ40 and 42 oligomer formation.

A novel web server predicts amino acid residue protection against hydrogen–deuterium exchange

MOTIVATION To clarify the relationship between structural elements and polypeptide chain mobility, a set of statistical analyses of structures is necessary. Because at present proteins with determined spatial structures are much less numerous than those with amino acid sequence known, it is important to be able to predict the extent of proton protection from hydrogen-deuterium (HD) exchange basing solely on the protein primary structure. RESULTS Here we present a novel web server aimed to predict the degree of amino acid residue protection against HD exchange solely from the primary structure of the protein chain under study. On the basis of the amino acid sequence, the presented server offers the following three possibilities (predictors) for users choice. First, prediction of the number of contacts occurring in this protein, which is shown to be helpful in estimating the number of protons protected against HD exchange (sensitivity 0.71). Second, probability of H-bonding in this protein, which is useful for finding the number of unprotected protons (specificity 0.71). The last is the use of an artificial predictor. Also, we report on mass spectrometry analysis of HD exchange that has been first applied to free amino acids. Its results showed a good agreement with theoretical data (number of protons) for 10 globular proteins (correlation coefficient 0.73). We pioneered in compiling two datasets of experimental HD exchange data for 35 proteins. AVAILABILITY The H-Protection server is available for users at http://bioinfo.protres.ru/ogp/ SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Computational Approaches to Identification of Aggregation Sites and the Mechanism of Amyloid Growth

This chapter describes computational approaches to study amyloid formation. The first part addresses identification of potential amyloidogenic regions in the amino acid sequences of proteins and peptides. Next, we discuss nucleation and aggregation sites in protein folding and misfolding. The last part describes up-to-date kinetic models of amyloid fibrils formation. Numerous studies show that protein misfolding is initiated by specific amino acid segments with high amyloid-forming propensity. The ability to identify and, ultimately, block such segments is very important. To this end, many prediction algorithms have been developed which vary greatly in their effectiveness. We compared the predictions for 30 proteins by using different methods and found that, at best, only 50% of residues in amyloidogenic segments were predicted correctly. The best results were obtained by using the meta-servers that combine several independent approaches, and by the method PASTA2. Thus, correct prediction of amyloidogenic segments remains a difficult task. Additional data and new algorithms that are becoming available are expected to improve the accuracy of the prediction methods, particularly if they use 3D structural information on the target proteins. At the same time, our understanding of the kinetics of fibril formation is more advanced. The current kinetic models outlined in this chapter adequately describe the key features of amyloid nucleation and growth. However, the underlying structural details are less clear, not least because of the apparently different mechanisms of amyloid fibril formation which are discussed. Ultimately, the detailed understanding of the structural basis for amyloidogenesis should help develop rational therapies to block this pathogenic process.

Prediction of Residue Status to Be Protected or Not Protected From Hydrogen Exchange Using Amino Acid Sequence Only

We have outlined here some structural aspects of local flexibility. Important functional properties are related to flexible segments. We try to predict regions that have been shown to exhibit the highest probability of being folded in the equilibrium intermediate or native state and will be protected from hydrogen exchange using amino acid sequence only. Our approach FoldUnfold for the prediction of unstructured regions has been applied to seven different proteins. For 80% of the residues considered in this paper we can predict correctly their status: will they be protected or not from hydrogen exchange. An additional goal of our study is to assess whether properties inferred using the bioinformatics approach are easily applicable to predict behavior of proteins in solution.

Determination of Size of Folding Nuclei of Fibrils Formed from Recombinant Aβ(1-40) Peptide.

We have developed a highly efficient method for purification of the recombinant product Aβ(1-40) peptide. The concentration dependence of amyloid formation by recombinant Aβ(1-40) peptide was studied using fluorescence spectroscopy and electron microscopy. We found that the process of amyloid formation is preceded by lag time, which indicates that the process is nucleation-dependent. Further exponential growth of amyloid fibrils is followed by branching scenarios. Based on the experimental data on the concentration dependence, the sizes of the folding nuclei of fibrils were calculated. It turned out that the size of the primary nucleus is one “monomer” and the size of the secondary nucleus is zero. This means that the nucleus for new aggregates can be a surface of the fibrils themselves. Using electron microscopy, we have demonstrated that fibrils of these peptides are formed by the association of rounded ring structures.

Mechanisms of amyloid fibril formation

Amyloid and amyloid-like aggregates are elongated unbranched fibrils consisting of β-structures of separate monomers positioned perpendicular to the fibril axis and stacked strictly above each other. In their physicochemical properties, amyloid fibrils are reminiscent of synthetic polymers rather than usual proteins because they are stable to the action of denaturing agents and proteases. Their mechanical stability can be compared to a spider’s web, that in spite of its ability to stretch, is stronger than steel. It is not surprising that a large number of diseases are accompanied with amyloid fibril depositing in different organs. Pathologies provoked by depositing of incorrectly folded proteins include Alzheimer’s, Parkinson’s, and Huntington’s diseases. In addition, this group of diseases involves mucoviscidosis, some types of diabetes, and hereditary cataracts. Each type of amyloidosis is characterized by aggregation of a certain type of protein that is soluble in general, and thus leads to specific distortions of functions of the corresponding organs. Therefore, it is important to understand the process of transformation of “native” proteins to amyloid fibrils to clarify how these molecules acquire such strength and what key elements of this process determine the pathway of erroneous protein folding. This review presents our analysis of complied information on the mechanisms of formation and biochemical properties of amyloid fibrils.

Prediction of amino acid residues protected from hydrogen-deuterium exchange in a protein chain

We have investigated the possibility to predict protection of amino acid residues from hydrogen-deuterium exchange. A database containing experimental hydrogen-deuterium exchange data for 14 proteins for which these data are known has been compiled. Different structural parameters related to flexibility of amino acid residues and their amide groups have been analyzed to answer the question whether these parameters can be used for predicting the protection of amino acid residues from hydrogen-deuterium exchange. A method for prediction of protection of amino acid residues, which uses only the amino acid sequence of a protein, has been elaborated.

PREDICTION OF LOOP REGIONS IN PROTEIN SEQUENCE

We suggest an algorithm that inputs a protein sequence and outputs a decomposition of the protein chain into a regular part including secondary structures and a nonregular part corresponding to loop regions. We have analyzed loop regions in a protein dataset of 3,769 globular domains and defined the optimal parameters for this prediction: the threshold between regular and nonregular regions and the optimal window size for averaging procedures using the scale of the expected number of contacts in a globular state and entropy scale as the number of degrees of freedom for the angles phi, psi, and chi for each amino acid. Comparison with known methods demonstrates that our method gives the same results as the well-known ALB method based on physical properties of amino acids (the percentage of true predictions is 64% against 66%), and worse prediction for regular and nonregular regions than PSIPRED (Protein Structure Prediction Server) without alignment of homologous proteins (the percentage of true predictions is 73%). The potential advantage of the suggested approach is that the predicted set of loops can be used to find patterns of rigid and flexible loops as possible candidates to play a structure/function role as well as a role of antigenic determinants.

Prediction of Number and Position of Domain Boundaries in Multi-Domain Proteins by Use of Amino Acid Sequence Alone

Prediction of protein domain boundaries is an important step for the prediction of three-dimensional structure. The simple method PDP has been elaborated for prediction of the number and position of domain boundaries in multi-domain proteins by use of amino acid sequence alone. The method uses an optimized scale based on the statistics of appearance of amino acid residues at domain boundaries. Our method demonstrates promising results in comparison to other methods that do not use homologous sequences. From the database of proteins that are targets from CASP6 (Critical Assessment of Techniques for Protein Structure Prediction) our program correctly assigned the number of domains for approximately 80% of one domain proteins and approximately 50% for two-domain proteins. Our method offers three main advantages: it is very simple, it is fast, and it uses a minimal number of parameters in comparison with other methods.