Preformed template fluctuations promote fibril formation: insights from lattice and all-atom models

Single-molecule Observation of Self-Propagating Amyloid Fibrils

The assembly of misfolded proteins into amyloid fibrils is associated with amyloidosis, including neurodegenerative diseases, such as Alzheimer’s, Parkinson’s, and prion diseases. The self-propagation of amyloid fibrils is widely observed in the aggregation pathways of numerous amyloidogenic proteins. This propensity with plasticity in primary nucleation allows amyloid fibril polymorphism, which is correlated with the pathology/phenotypes of patients. Because the interference with the nucleation and replication processes of amyloid fibrils can alter the amyloid structure and the outcome of the disease, these processes can be a target for developing clinical drugs. Single-molecule observation of amyloid fibril replication can be an experimental system to provide the kinetic parameters for simulation studies and confirm the effect of clinical drugs. Here, we review single-molecule observation of the amyloid fibril replication process using fluorescence microscopy and time-lapse atomic force microscopy, including high-speed atomic force microscopy. We discussed the amyloid fibril replication process and combined single-molecule observation results with molecular dynamics simulations.

Mini Abstract Structural dynamics in amyloid aggregation is related with various Alzheimer’s and Parkinson’s disease symptoms. Single-molecule observation using high-speed atomic force microscopy can directly visualize the structural dynamics of individual amyloid aggregate assemblies. Here, we review historical and recent studies of single-molecule observation of amyloid aggregation with supportive molecular dynamics simulation.

Computational Models for the Study of Protein Aggregation

Protein aggregation has been studied by many groups around the world for many years because it can be the cause of a number of neurodegenerative diseases that have no effective treatment. Obtaining the structure of related fibrils and toxic oligomers, as well as describing the pathways and main factors that govern the self-organization process, is of paramount importance, but it is also very difficult. To solve this problem, experimental and computational methods are often combined to get the most out of each method. The effectiveness of the computational approach largely depends on the construction of a reasonable molecular model. Here we discussed different versions of the four most popular all-atom force fields AMBER, CHARMM, GROMOS, and OPLS, which have been developed for folded and intrinsically disordered proteins, or both. Continuous and discrete coarse-grained models, which were mainly used to study the kinetics of aggregation, are also summarized.

Probing the local conformational flexibility in receptor recognition: mechanistic insight from an atomic-scale investigation

Inherent protein conformational flexibility is important for biomolecular recognition, but this critical property is often neglected in several studies. This event can lead to large deviations in the research results. In the current contribution, we disclose the effects of the local conformational flexibility on receptor recognition by using an atomic-scale computational method. The results indicated that both static and dynamic reaction modes have noticeable differences, and these originated from the structural features of the protein molecules. Dynamic interaction results displayed that the structural stability and conformational flexibility of the proteins had a significant influence on the recognition processes. This point related closely to the characteristics of the flexible loop regions where bixin located within the protein structures. The energy decomposition analyses and circular dichroism results validated the rationality of the recognition studies. More importantly, the conformational and energy changes of some residues around the bixin binding domain were found to be vital to biological reactions. These microscopic findings clarified the nature of the phenomenon that the local conformational flexibility could intervene in receptor recognition. Obviously, this report may provide biophysical evidence for the exploration of the structure-function relationships of the biological receptors in the human body.

Role of Resultant Dipole Moment in Mechanical Dissociation of Biological Complexes

Protein-peptide interactions play essential roles in many cellular processes and their structural characterization is the major focus of current experimental and theoretical research. Two decades ago, it was proposed to employ the steered molecular dynamics (SMD) to assess the strength of protein-peptide interactions. The idea behind using SMD simulations is that the mechanical stability can be used as a promising and an efficient alternative to computationally highly demanding estimation of binding affinity. However, mechanical stability defined as a peak in force-extension profile depends on the choice of the pulling direction. Here we propose an uncommon choice of the pulling direction along resultant dipole moment (RDM) vector, which has not been explored in SMD simulations so far. Using explicit solvent all-atom MD simulations, we apply SMD technique to probe mechanical resistance of ligand-receptor system pulled along two different vectors. A novel pulling direction—when ligand unbinds along the RDM vector—results in stronger forces compared to commonly used ligand unbinding along center of masses vector. Our observation that RDM is one of the factors influencing the mechanical stability of protein-peptide complex can be used to improve the ranking of binding affinities by using mechanical stability as an effective scoring function.

Kinetics and mechanical stability of the fibril state control fibril formation time of polypeptide chains: A computational study

Fibril formation resulting from protein misfolding and aggregation is a hallmark of several neurodegenerative diseases such as Alzheimer's and Parkinson's diseases. Despite much progress in the understanding of the protein aggregation process, the factors governing fibril formation rates and fibril stability have not been fully understood. Using lattice models, we have shown that the fibril formation time is controlled by the kinetic stability of the fibril state but not by its energy. Having performed all-atom explicit solvent molecular dynamics simulations with the GROMOS43a1 force field for full-length amyloid beta peptides Aβ₄₀ and Aβ₄₂ and truncated peptides, we demonstrated that kinetic stability can be accessed via mechanical stability in such a way that the higher the mechanical stability or the kinetic stability, the faster the fibril formation. This result opens up a new way for predicting fibril formation rates based on mechanical stability that may be easily estimated by steered molecular dynamics.

Mutations Alter RNA-Mediated Conversion of Human Prions

Prion diseases are connected with self-replication and self-propagation of misfolded proteins. The rate-limiting factor is the formation of the initial seed. We have recently studied the early stages in the conversion between functional PrP^C and the infectious scrapie PrP^SC form, triggered by the binding of RNA. Here, we study how this process is modulated by the prion sequence. We focus on residues 129 and 178, which are connected to the hereditary neurodegenerative disease fatal familial insomnia.

Out-of-Register Aβ42 Assemblies as Models for Neurotoxic Oligomers and Fibrils

We propose a variant of the recently found S-shaped Aβ_1-42-motif that is characterized by out-of-register C-terminal β-strands. We show that chains with this structure can form not only fibrils that are compatible with the NMR signals but also barrel-shaped oligomers that resemble the ones formed by the much smaller cylindrin peptides. By running long all-atom molecular dynamics simulations at physiological temperatures with an explicit solvent, we study the stability of these constructs and show that they are plausible models for neurotoxic oligomers. After analyzing the transitions between different assemblies, we suggest a mechanism for amyloid formation in Alzheimer's disease.

Molecular Dynamics Simulations Reveal Key Roles of the Interleukin-6 Alpha Receptor in the Assembly of the Human Interleukin-6 Receptor Complex

Human interleukin-6 (hIL-6) is a pleiotropic cytokine with three distinct receptor epitopes, termed sites I, II, and III, which function to assemble a signaling complex. hIL-6 signals via a glycoprotein 130 (gp130) homodimer after initially forming a heterodimer with the nonsignaling α-receptor (IL-6Rα). The molecular description of the assembly of the hIL-6 signaling complex remains elusive because available structures provide descriptions of hIL-6 in its free and fully bound receptor forms, but not for intermediate steps that are crucial in the stepwise assembly of the signaling complex. In this report, molecular dynamics simulations provide atomic details describing the functional role of the initial hIL-6/IL-6Rα complex in facilitating subsequent interactions with gp130, which have not been previously shown. IL-6Rα binding to hIL-6 rigidifies the flexible N-terminus of the hIL-6 AB-loop through interactions with the D2 domain of IL-6Rα. This rigidification combined with repositioning of residues involved in gp130 receptor recognition promotes gp130 binding at site III. Binding of gp130 receptors at sites II and III is coupled with the release of the hIL-6 N-terminal AB-loop interaction and a pivoting of IL-6Rα around the hIL-6 helix bundle to the state of the hIL-6/IL-6Rα/gp130 complex.

Molecular dynamics simulations of early steps in RNA-mediated conversion of prions

The rate-limiting step in prion diseases is the initial transition of a prion protein from its native form into a mis-folded state in which the protein not only forms cell-toxic aggregates but also becomes infectious. Recent experiments implicate polyadenosine RNA as a possible agent for generating the initial seed. In order to understand the mechanism of RNA-mediated mis-folding and aggregation of prions, we dock polyadenosine RNA to mouse and human prion models. Changes in stability and secondary structure of the prions upon binding to polyadenosine RNA are evaluated by comparing molecular dynamics simulations of these complexes with that of the unbound prions.

Oligomerization of FVFLM peptides and their ability to inhibit beta amyloid peptides aggregation: consideration as a possible model

Preeclampsia, a pregnancy-specific disorder, shares typical pathophysiological features with protein misfolding disorders including Alzheimer's disease. Characteristic for preeclampsia is the involvement of multiple proteins of which fragments of SERPINA1 and β-amyloid co-aggregate in urine and placenta of preeclamptic women. To explore the biophysical basis of this interaction, we investigated the multidimensional efficacy of the FVFLM sequence in SERPINA1, as a model inhibitory agent of β-amyloid aggregation. After studying the oligomerization of FVFLM peptides using all-atom molecular dynamics simulations with the GROMOS43a1 force field and explicit water, we report that FVFLM can aggregate and its aggregation is spontaneous with a remarkably faster rate than that recorded for KLVFF (aggregation "hot-spot" from β-amyloid). The fast kinetics of FVFLM aggregation was found to be driven primarily by core-like aromatic interactions originating from the anti-parallel orientation of complementarily uncharged strands. The conspicuously stable aggregation mechanism observed for FVFLM peptides is found not to conform to the popular 'dock-lock' scheme. We also found high propensity of FVFLM for KLVFF binding. When present, FVFLM disrupts the β-amyloid aggregation pathway and we propose that FVFLM-like peptides might be used to prevent the assembly of full-length Aβ or other pro-amyloidogenic peptides into amyloid fibrils.

Fast and Accurate Accessible Surface Area Prediction Without a Sequence Profile

A fast accessible surface area (ASA) predictor is presented. In this new approach no residue mutation profiles generated by multiple sequence alignments are used as inputs. Instead, we use only single sequence information and global features such as single-residue and two-residue compositions of the chain. The resulting predictor is both highly more efficient than sequence alignment based predictors and of comparable accuracy to them. Introduction of the global inputs significantly helps achieve this comparable accuracy. The predictor, termed ASAquick, is found to perform similarly well for so-called easy and hard cases indicating generalizability and possible usability for de-novo protein structure prediction. The source code and a Linux executables for ASAquick are available from Research and Information Systems at http://mamiris.com and from the Battelle Center for Mathematical Medicine at http://mathmed.org .

The GOR Method of Protein Secondary Structure Prediction and Its Application as a Protein Aggregation Prediction Tool

The GOR method of protein secondary structure prediction is described. The original method was published by Garnier, Osguthorpe, and Robson in 1978 and was one of the first successful methods to predict protein secondary structure from amino acid sequence. The method is based on information theory, and an assumption that information function of a protein chain can be approximated by a sum of information from single residues and pairs of residues. The analysis of frequencies of occurrence of secondary structure for singlets and doublets of residues in a protein database enables prediction of secondary structure for new amino acid sequences. Because of these simple physical assumptions the GOR method has a conceptual advantage over other later developed methods such as PHD, PSIPRED, and others that are based on Machine Learning methods (like Neural Networks), give slightly better predictions, but have a "black box" nature. The GOR method has been continuously improved and modified for 30 years with the last GOR V version published in 2002, and the GOR V server developed in 2005. We discuss here the original GOR method and the GOR V program and the web server. Additionally we discuss new highly interesting and important applications of the GOR method to chameleon sequences in protein folding simulations, and for prediction of protein aggregation propensities. Our preliminary studies show that the GOR method is a promising and efficient alternative to other protein aggregation predicting tools. This shows that the GOR method despite being almost 40 years old is still important and has significant potential in application to new scientific problems.