Conformational Transitions of the Amyloid-β Peptide Upon Copper(II) Binding and pH Changes

Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning

Proteins are inherently dynamic, and their conformational ensembles are functionally important in biology. Large-scale motions may govern protein structure-function relationship, and numerous transient but stable conformations of intrinsically disordered proteins (IDPs) can play a crucial role in biological function. Investigating conformational ensembles to understand regulations and disease-related aggregations of IDPs is challenging both experimentally and computationally. In this paper we first introduced an unsupervised deep learning-based model, termed Internal Coordinate Net (ICoN), which learns the physical principles of conformational changes from molecular dynamics (MD) simulation data. Second, we selected interpolating data points in the learned latent space that rapidly identify novel synthetic conformations with sophisticated and large-scale sidechains and backbone arrangements. Third, with the highly dynamic amyloid-β 1-42 (Aβ42) monomer, our deep learning model provided a comprehensive sampling of Aβ42's conformational landscape. Analysis of these synthetic conformations revealed conformational clusters that can be used to rationalize experimental findings. Additionally, the method can identify novel conformations with important interactions in atomistic details that are not included in the training data. New synthetic conformations showed distinct sidechain rearrangements that are probed by our EPR and amino acid substitution studies. This approach is highly transferable and can be used for any available data for training. The work also demonstrated the ability for deep learning to utilize learned natural atomistic motions in protein conformation sampling.

Modular Protein Fibers with Outstanding High-Strength and Acid-Resistance Performance Mediated by Copper Ion Binding and Imine Networking

Engineered protein fibers are promising biomaterials with diverse applications due to their tunable protein structure and outstanding mechanical properties. However, it remains challenging at the molecular level to achieve satisfied mechanical properties and environmental tolerance simultaneously, especially under extreme acid conditions. Herein, the construction of artificial fibers comprising chimeric proteins made of rigid amyloid peptide and flexible cationic elastin-like protein (ELP) module is reported. The amyloid peptide readily assembles into highly organized β-sheet structures that can be further strengthened by the coordination of Cu2+, while the flexible ELP module allows the formation of imine-based crosslinking networks. These double networks synergistically enhance the mechanical properties of the fibers, leading to a high tensile strength and toughness, overwhelming many reported recombinant spidroin fibers. Notably, the coordination of Cu2+ with serine residues could stabilize β-sheet structures in the fibers under acidic conditions, which makes the fibers robust against acid, thus enabling their successful utilization in gastric perforation suturing. This work highlights the customization of double networks at the molecular level to create tailored high-performance protein fibers for various application scenarios.

Modeling structural interconversion in Alzheimers' amyloid beta peptide with classical and intrinsically disordered protein force fields

A comprehensive understanding of the aggregation mechanism in amyloid beta 42 (Aβ42) peptide is imperative for developing therapeutic drugs to prevent or treat Alzheimer's disease. Because of the high flexibility and lack of native tertiary structures of Aβ42, molecular dynamics (MD) simulations may help elucidate the peptide's dynamics with atomic details and collectively improve ensembles not seen in experiments. We applied microsecond-timescale MD simulations to investigate the dynamics and conformational changes of Aβ42 by using a newly developed Amber force field (ff14IDPSFF). We compared the ff14IDPSFF and the regular ff14SB force field by examining the conformational changes of two distinct Aβ42 monomers in explicit solvent. Conformational ensembles obtained by simulations depend on the force field and initial structure, Aβ42^α-helix or Aβ42^β-strand. The ff14IDPSFF sampled a high ratio of disordered structures and diverse β-strand secondary structures; in contrast, ff14SB favored helicity during the Aβ42^α-helix simulations. The conformations obtained from Aβ42^β-strand simulations maintained a balanced content in the disordered and helical structures when simulated by ff14SB, but the conformers clearly favored disordered and β-sheet structures simulated by ff14IDPSFF. The results obtained with ff14IDPSFF qualitatively reproduced the NMR chemical shifts well. In-depth peptide and cluster analysis revealed some characteristic features that may be linked to early onset of the fibril-like structure. The C-terminal region (mainly M35-V40) featured in-registered anti-parallel β-strand (β-hairpin) conformations with tested systems. Our work should expand the knowledge of force field and structure dependency in MD simulations and reveals the underlying structural mechanism-function relationship in Aβ42 peptides. Communicated by Ramaswamy H. Sarma.

Impact of Cu(II) and Al(III) on the conformational landscape of amyloidβ1-42

Metal ions have been found to play an important role in the formation of extracellular β-amyloid plaques, a major hallmark of Alzheimer's disease. In the present study, the conformational landscape of Aβ42 with Al(iii) and Cu(ii) has been explored using Gaussian accelerated molecular dynamics. Both metals reduce the flexibility of the peptide and entail a higher structural organization, although to different degrees. As a general trend, Cu(ii) binding leads to an increased α-helix content and to the formation of two α-helices that tend to organize in a U-shape. By contrast, most Al(iii) complexes induce a decrease in helical content, leading to more extended structures that favor the appearance of transitory β-strands.

Characterization of putative transcriptional regulator (PH0140) and its distal homologue

In this study, a phylogenetic tree was constructed using 1854 sequences of various Lrp/AnsC (FFRPs) and ArsR proteins from pathogenic and non-pathogenic organisms. Despite having sequence similarities, FFRPs and ArsR proteins functioning differently as a transcriptional regulator and de-repressor in the presence of exogenous amino acids and metal ions, respectively. To understand these functional differences, the structures of various FFRPs and ArsR proteins (134 sequences) were modeled. Several ArsR proteins exhibited high similarity to the FFRPs while in few proteins, unusual structural folds were observed. However, the Helix-turn-Helix (HTH) domains are common among them and the ligand-binding domains are structurally dissimilar suggest the differences in their binding preferences. Despite low sequence conservation, most of these proteins revealed negatively charged surfaces in the active site pockets. Representative structures (PH0140 and TtArsR protein) from FFRPs and ArsR protein families were considered and evaluated for their functional differences using molecular modeling studies. Our earlier study has explained the binding preference of exogenous Tryptophan and the related transcriptional regulatory mechanism of PH0140 protein. In this study, a Cu²⁺ ion-induced de-repression mechanism of the TtArsR-DNA complex was characterized through docking and molecular dynamics. Further, the proteins were purified and their efficiency for sensing Tryptophan and Cu²⁺ ions were analyzed using cyclic voltammetry. Overall, the study explores the structural evolution and functional difference of FFRPs and ArsR proteins that present the possibilities of PH0140 and TtArsR as potential bio-sensory molecules.

Amyloid Oligomers: A Joint Experimental/Computational Perspective on Alzheimer's Disease, Parkinson's Disease, Type II Diabetes, and Amyotrophic Lateral Sclerosis

Protein misfolding and aggregation is observed in many amyloidogenic diseases affecting either the central nervous system or a variety of peripheral tissues. Structural and dynamic characterization of all species along the pathways from monomers to fibrils is challenging by experimental and computational means because they involve intrinsically disordered proteins in most diseases. Yet understanding how amyloid species become toxic is the challenge in developing a treatment for these diseases. Here we review what computer, in vitro, in vivo, and pharmacological experiments tell us about the accumulation and deposition of the oligomers of the (Aβ, tau), α-synuclein, IAPP, and superoxide dismutase 1 proteins, which have been the mainstream concept underlying Alzheimer's disease (AD), Parkinson's disease (PD), type II diabetes (T2D), and amyotrophic lateral sclerosis (ALS) research, respectively, for many years.

Enhanced sampling and free energy calculations for protein simulations

Molecular dynamics simulation is a powerful computational technique to study biomolecular systems, which complements experiments by providing insights into the structural dynamics relevant to biological functions at atomic scale. It can also be used to calculate the free energy landscapes of the conformational transitions to better understand the functions of the biomolecules. However, the sampling of biomolecular configurations is limited by the free energy barriers that need to be overcome, leading to considerable gaps between the timescales reached by MD simulation and those governing biological processes. To address this issue, many enhanced sampling methodologies have been developed to increase the sampling efficiency of molecular dynamics simulations and free energy calculations. Usually, enhanced sampling algorithms can be classified into methods based on collective variables (CV-based) and approaches which do not require predefined CVs (CV-free). In this chapter, the theoretical basis of free energy estimation is briefly reviewed first, followed by the reviews of the most common CV-based and CV-free methods including the presentation of some examples and recent developments. Finally, the combination of different enhanced sampling methods is discussed.

Replica exchange molecular dynamics simulation of the coordination of Pt(ii)-Phenanthroline to amyloid-β

We report replica exchange molecular dynamics (REMD) simulations of the complex formed between amyloid-β peptides and platinum bound to a phenanthroline ligand, Pt(phen). After construction of an AMBER-style forcefield for the Pt complex, REMD simulation employing temperatures between 270 and 615 K was used to provide thorough sampling of the conformational freedom available to the peptide. We find that the full length peptide Aβ42, in particular, frequently adopts a compact conformation with a large proportion of α- and 3,10-helix content, with smaller amounts of β-strand in the C-terminal region of the peptide. Helical structures are more prevalent than in the metal-free peptide, while turn and strand conformations are markedly less common. Non-covalent interactions, including salt-bridges, hydrogen bonds, and π-stacking between aromatic residues and the phenanthroline ligand, are common, and markedly different from those seen in the amyloid-β peptides alone.

Effects of in vivo conditions on amyloid aggregation

One of the grand challenges of biophysical chemistry is to understand the principles that govern protein misfolding and aggregation, which is a highly complex process that is sensitive to initial conditions, operates on a huge range of length- and timescales, and has products that range from protein dimers to macroscopic amyloid fibrils. Aberrant aggregation is associated with more than 25 diseases, which include Alzheimer's, Parkinson's, Huntington's, and type II diabetes. Amyloid aggregation has been extensively studied in the test tube, therefore under conditions that are far from physiological relevance. Hence, there is dire need to extend these investigations to in vivo conditions where amyloid formation is affected by a myriad of biochemical interactions. As a hallmark of neurodegenerative diseases, these interactions need to be understood in detail to develop novel therapeutic interventions, as millions of people globally suffer from neurodegenerative disorders and type II diabetes. The aim of this review is to document the progress in the research on amyloid formation from a physicochemical perspective with a special focus on the physiological factors influencing the aggregation of the amyloid-β peptide, the islet amyloid polypeptide, α-synuclein, and the hungingtin protein.

Intrinsically disordered proteins in various hypotheses on the pathogenesis of Alzheimer's and Parkinson's diseases

Amyloid-β (Aβ) and α-synuclein (αS) are two intrinsically disordered proteins (IDPs) at the centers of the pathogenesis of Alzheimer's and Parkinson's diseases, respectively. Different hypotheses have been proposed for explanation of the molecular mechanisms of the pathogenesis of these two diseases, with these two IDPs being involved in many of these hypotheses. Currently, we do not know, which of these hypothesis is more accurate. Experiments face challenges due to the rapid conformational changes, fast aggregation processes, solvent and paramagnetic effects in studying these two IDPs in detail. Furthermore, pathological modifications impact their structures and energetics. Theoretical studies using computational chemistry and computational biology have been utilized to understand the structures and energetics of Aβ and αS. In this chapter, we introduce Aβ and αS in light of various hypotheses, and discuss different experimental and theoretical techniques that are used to study these two proteins along with their weaknesses and strengths. We suggest that a promising solution for studying Aβ and αS at the center of varying hypotheses could be provided by developing new techniques that link quantum mechanics, statistical mechanics, thermodynamics, bioinformatics to machine learning. Such new developments could also lead to development in experimental techniques.

Edaravone inhibits the conformational transition of amyloid-β42: insights from molecular dynamics simulations

Previous work has shown that edaravone inhibits fibrillogenesis of amyloid-β protein (Aβ). However, the detailed mechanism by which edaravone inhibits the conformational transition of the Aβ42 monomer is not known at the molecular level. Here, explicit-solvent molecular dynamics (MD) simulations were coupled with molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) method to address the issue. MD simulations confirmed that edaravone inhibits the conformational transition of the Aβ42 monomer in a dose-dependent manner. It was found that the direct interactions between edaravone and Aβ42 are responsible for its inhibiting effects. The analysis of binding free energy using the MM-PBSA method demonstrated that the nonpolar interactions provide favourable contributions (about -71.7 kcal/mol). Conversely, the polar interactions are unfavourable for the binding process. A total of 14 residues were identified as greatly contributing to the binding free energy between edaravone and the Aβ42 monomer. In addition, the intra-peptide hydrophobic interactions were weakened and the salt bridge D23-K28 was interrupted by edaravone. Therefore, the conformational transition was inhibited. Our studies provide molecular-level insights into how edaravone molecules inhibit the conformational transition of the Aβ42 monomer, which may be useful for designing amyloid inhibitors.Communicated by Ramaswamy H. Sarma.

Transition Metal Ion Interactions with Disordered Amyloid-β Peptides in the Pathogenesis of Alzheimer's Disease: Insights from Computational Chemistry Studies

Monomers and oligomers of the amyloid-β peptide aggregate to form the fibrils found in the brains of Alzheimer's disease patients. These monomers and oligomers are largely disordered and can interact with transition metal ions, affecting the mechanism and kinetics of amyloid-β aggregation. Due to the disordered nature of amyloid-β, its rapid aggregation, as well as solvent and paramagnetic effects, experimental studies face challenges in the characterization of transition metal ions bound to amyloid-β monomers and oligomers. The details of the coordination chemistry between transition metals and amyloid-β obtained from experiments remain debated. Furthermore, the impact of transition metal ion binding on the monomeric or oligomeric amyloid-β structures and dynamics are still poorly understood. Computational chemistry studies can serve as an important complement to experimental studies and can provide additional knowledge on the binding between amyloid-β and transition metal ions. Many research groups conducted first-principles calculations, ab initio molecular dynamics simulations, quantum mechanics/classical mechanics simulations, and classical molecular dynamics simulations for studying the interplay between transition metal ions and amyloid-β monomers and oligomers. This review summarizes the current understanding of transition metal interactions with amyloid-β obtained from computational chemistry studies. We also emphasize the current view of the coordination chemistry between transition metal ions and amyloid-β. This information represents an important foundation for future metal ion chelator and drug design studies aiming to combat Alzheimer's disease.

Stability of Cu(ii) complexes with FomA protein fragments containing two His residues in the peptide chain

The coordination process of Cu(ii) ions with FomA protein fragments ofFusobacterium nucleatumcontaining two histydyl residues was determined.

Aβ under stress: the effects of acidosis, Cu2+-binding, and oxidation on amyloid β-peptide dimers

In light of the high affinity of Cu2+ for Alzheimer's Aβ1-42 and its ability to subsequently catalyze the formation of radicals, we examine the effects of Cu2+ binding, Aβ oxidation, and an acidic environment on the conformational dynamics of the smallest Aβ1-42 oligomer, the Aβ1-42 dimer. Transition networks calculated from Hamiltonian replica exchange molecular dynamics (H-REMD) simulations reveal that the decreased pH considerably increased the β-sheet content, whereas Cu2+ binding increased the exposed hydrophobic surface area, both of which can contribute to an increased oligomerization propensity and toxicity.

Pathways of Amyloid-β Aggregation Depend on Oligomer Shape

One of the main research topics related to Alzheimer's disease is the aggregation of the amyloid-β peptide, which was shown to follow different pathways for the two major alloforms of the peptide, Aβ40 and the more toxic Aβ42. Experimental studies emphasized that oligomers of specific sizes appear in the early aggregation process in different quantities and might be the key toxic agents for each of the two alloforms. We use transition networks derived from all-atom molecular dynamics simulations to show that the oligomers leading to the type of oligomer distributions observed in experiments originate from compact conformations. Extended oligomers, on the other hand, contribute more to the production of larger aggregates thus driving the aggregation process. We further demonstrate that differences in the aggregation pathways of the two Aβ alloforms occur as early as during the dimer stage. The higher solvent-exposure of hydrophobic residues in Aβ42 oligomers contributes to the different aggregation pathways of both alloforms and also to the increased cytotoxicity of Aβ42.