The inverted free energy landscape of an intrinsically disordered peptide by simulations and experiments

Intrinsically Disordered Membrane Anchors of Rheb, RhoA, and DiRas3 Small GTPases: Molecular Dynamics, Membrane Organization, and Interactions

Protein structure has been well established to play a key role in determining function; however, intrinsically disordered proteins and regions (IDPs and IDRs) defy this paradigm. IDPs and IDRs exist as an ensemble of structures rather than a stable 3D structure yet play essential roles in many cell-signaling processes. Nearly all Ras superfamily GTPases are tethered to membranes by a lipid tail at the end of a flexible IDR. The sequence of the IDR is a key determinant of membrane localization, and interaction between the IDR and the membrane has been shown to affect signaling in RAS proteins through the modulation of dynamic membrane organization. Here, we utilized atomistic molecular dynamics simulations to study the membrane interaction, conformational dynamics, and lipid sorting of three IDRs from small GTPases Rheb, RhoA, and DiRas3 in model membranes representing their physiological target membranes. We found that complementarity between the lipidated IDR sequence and target membrane lipid composition is a determinant of conformational plasticity. We also show that electrostatic interactions between anionic lipids and basic residues on IDRs are correlated with sampling of semistable conformational substates, and lack of these interactions is associated with greater conformational diversity. Finally, we show that small GTPase IDRs with a polybasic domain alter local lipid composition by segregating anionic lipids and, in some cases, excluding other lipids from their immediate vicinity in favor of anionic lipids.

Molecular Insight into the Effect of HIV-TAT Protein on Amyloid-β Peptides

Increased deposition of amyloid-β (Aβ) plaques in the brain is a frequent pathological feature observed in human immunodeficiency virus (HIV)-positive patients. Emerging evidence indicates that HIV regulatory proteins, particularly the transactivator of transcription (TAT) protein, could interact with Aβ peptide, accelerating the formation of Aβ plaques in the brain and potentially contributing to the onset of Alzheimer's disease in individuals with HIV infection. Nevertheless, the molecular mechanisms underlying these processes remain unclear. In the present study, we have used long all-atom molecular dynamics simulations to probe the direct interactions between the TAT protein and Aβ peptide at the molecular level. Sampling over 28.0 μs, our simulations show that TAT protein induces a shift in the Aβ monomer ensemble toward elongated conformations, exposing aggregation-prone regions on the surface and thereby inducing subsequent aggregation. TAT protein also appears to enhance the stability of preformed Aβ fibrils, while increasing the β-sheet content within these fibrils. Our atomistically detailed simulations qualitatively agree with previous in vitro and in vivo studies. Importantly, our simulations identify key interactions between Aβ and the TAT protein that drive the Aβ aggregation process and stabilize the preformed Aβ aggregates, which are particularly challenging to obtain through current experimental techniques.

CoVAMPnet: Comparative Markov State Analysis for Studying Effects of Drug Candidates on Disordered Biomolecules

Computational study of the effect of drug candidates on intrinsically disordered biomolecules is challenging due to their vast and complex conformational space. Here, we developed a comparative Markov state analysis (CoVAMPnet) framework to quantify changes in the conformational distribution and dynamics of a disordered biomolecule in the presence and absence of small organic drug candidate molecules. First, molecular dynamics trajectories are generated using enhanced sampling, in the presence and absence of small molecule drug candidates, and ensembles of soft Markov state models (MSMs) are learned for each system using unsupervised machine learning. Second, these ensembles of learned MSMs are aligned across different systems based on a solution to an optimal transport problem. Third, the directional importance of inter-residue distances for the assignment to different conformational states is assessed by a discriminative analysis of aggregated neural network gradients. This final step provides interpretability and biophysical context to the learned MSMs. We applied this novel computational framework to assess the effects of ongoing phase 3 therapeutics tramiprosate (TMP) and its metabolite 3-sulfopropanoic acid (SPA) on the disordered Aβ42 peptide involved in Alzheimer's disease. Based on adaptive sampling molecular dynamics and CoVAMPnet analysis, we observed that both TMP and SPA preserved more structured conformations of Aβ42 by interacting nonspecifically with charged residues. SPA impacted Aβ42 more than TMP, protecting α-helices and suppressing the formation of aggregation-prone β-strands. Experimental biophysical analyses showed only mild effects of TMP/SPA on Aβ42 and activity enhancement by the endogenous metabolization of TMP into SPA. Our data suggest that TMP/SPA may also target biomolecules other than Aβ peptides. The CoVAMPnet method is broadly applicable to study the effects of drug candidates on the conformational behavior of intrinsically disordered biomolecules.

Advanced computational approaches to understand protein aggregation

Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.

A computational odyssey: uncovering classical β-lactamase inhibitors in dry fruits

In the antibacterial arsenal, β-lactams have held a prominent position, but increasing resistance due to unauthorized use and genetic factors requires new strategies. Combining β-lactamase inhibitors with broad-spectrum β-lactams proves effective in combating this resistance. ESBL producers demand new inhibitors, leading to the exploration of plant-derived secondary metabolites for potent β-lactam antibiotics or alternative inhibitors. Using virtual screening, molecular docking, ADMET analysis, and molecular dynamic simulation, this study actively analyzed the inhibitory activity of figs, cashews, walnuts, and peanuts against SHV-1, NDM-1, KPC-2, and OXA-48 β-lactamases. Using AutoDock Vina, the docking affinities of various compounds for target enzymes were initially screened, revealing 12 bioactive compounds with higher affinities for the target enzymes compared to Avibactam and Tazobactam. Top-scoring metabolites, including Oleanolic acid, Protocatechuic acid, and Tannin, were subjected to MD simulation studies to further analyze the stability of the docked complexes using WebGro. The simulation coordinates, in terms of RMSD, RMSF, SASA, Rg, and hydrogen bonds formed, showed that these phytocompounds are stable enough to retain in the active sites at various orientations. The PCA and FEL analysis also showed the stability of the dynamic motion of Cα residues of phytochemical-bound enzymes. The pharmacokinetic analysis of the top phytochemicals was performed to analyze their bioavailability and toxicity. This study provides new insights into the therapeutic potential of phytochemicals of selected dry fruits and contributes to future experimental studies to identify βL inhibitors from plants.Communicated by Ramaswamy H. Sarma.

Intrinsically disordered membrane anchors of Rheb, RhoA and DiRas3 small GTPases: Molecular dynamics, membrane organization, and interactions

Protein structure has been well established to play a key role in determining function; however, intrinsically disordered proteins and regions (IDPs and IDRs) defy this paradigm. IDPs and IDRs exist as an ensemble of structures rather than a stable 3D structure yet play essential roles in many cell signaling processes. Nearly all Ras Superfamily GTPases are tethered to membranes by a lipid tail at the end of a flexible IDR. The sequence of these IDRs are key determinants of membrane localization, and interactions between the IDR and the membrane have been shown to affect signaling in RAS proteins through modulation of dynamic membrane organization. Here we utilized atomistic molecular dynamics simulations to study the membrane interactions, conformational dynamics, and lipid sorting of three IDRs from small GTPases Rheb, RhoA and DiRas3 in model membranes representing their physiological target membranes. We found that complementarity between lipidated IDR sequence and target membrane lipid composition is a determinant of conformational plasticity. We also show that electrostatic interactions between anionic lipids and basic residues on IDRs generate semi-stable conformational sub-states, and a lack of these residues leads to greater conformational diversity. Finally, we show that small GTPase IDRs with a polybasic domain alter local lipid composition by segregating anionic membrane lipids, and, in some cases, excluding other lipids from their immediate proximity in favor of anionic lipids.

Understanding the structural basis of the binding specificity of c-di-AMP to M. smegmatis RecA using computational biology approach

Mycobacterium tuberculosis RecA (MtRecA), a protein involved in DNA repair, homologous recombination and SOS pathway, contributes to the development of multidrug resistance. ATP binding-site in RecA has been a drug target to disable RecA dependent DNA repair. For the first time, experiments have shown the existence and binding of c-di-AMP to a novel allosteric site in the C-terminal-Domain (CTD) of Mycobacterium smegmatis RecA (MsRecA), a close homolog of MtRecA. In addition, it was observed that the c-di-AMP was not binding to Escherichia coli RecA (EcRecA). This article analyses the possible interactions of the three RecA homologs with the various c-di-AMP conformations to gain insights into the structural basis of the natural preference of c-di-AMP to MsRecA and not to EcRecA, using the structural biology tools. The comparative analysis, based on amino acid composition, homology, motifs, residue types, docking, molecular dynamics simulations and binding free energy calculations, indeed, conclusively indicates strong binding of c-di-AMP to MsRecA. Having very similar results as MsRecA, it is highly plausible for c-di-AMP to strongly bind MtRecA as well. These insights from the in-silico studies adds a new therapeutic approach against TB through design and development of novel allosteric inhibitors for the first time against MtRecA.Communicated by Ramaswamy H. Sarma.

Recent advances in de novo computational design and redesign of intrinsically disordered proteins and intrinsically disordered protein regions

In the early 2000s, the concept of "unstructured biology" has emerged to be an important field in protein science by generating various new research directions. Many novel strategies and methods have been developed that are focused on effectively identifying/predicting intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs), identifying their potential functions, disorder based drug design etc. Due to the range of functions of IDPs/IDPRs and their involvement in various debilitating diseases they are of contemporary interest to the scientific community. Recent researches are focused on designing/redesigning specific IDPs/IDPRs de novo. These de novo design/redesigns of IDPs/IDPRs are carried out by altering compositional biases and specific sequence patterning parameters. The main focus of these researches is to influence specific molecular functions, phase behavior, cellular phenotypes etc. In this review, we first provide the differences of natively folded and natively unfolded or IDPs with respect to their potential energy landscapes. Here, we provide current understandings on the different computational design strategies and methods that have been utilized in de novo design and redesigns of IDPs and IDPRs. Finally, we conclude the review by discussing the challenges that have been faced during the computational design/design attempts of IDPs/IDPRs.

Protein Corona Formation and Aggregation of Amyloid β 1-40-Coated Gold Nanocolloids

Amyloid fibrillogenesis is a pathogenic protein aggregation process that occurs through a highly ordered process of protein-protein interactions. To better understand the protein-protein interactions involved in amyloid fibril formation, we formed nanogold colloid aggregates by stepwise additions of ∼2 nmol of amyloid β 1-40 peptide (Aβ1-40) at pH ∼3.7 and ∼25 °C. The processes of protein corona formation and building of gold colloid [diameters (d) of 20 and 80 nm] aggregates were confirmed by a red-shift of the surface plasmon resonance (SPR) band, λpeak, as the number of Aβ1-40 peptides [N(Aβ1-40)] increased. The normalized red-shift of λpeak, Δλ, was correlated with the degree of protein aggregation, and this process was approximated as the adsorption isotherm explained by the Langmuir-Freundlich model. As the coverage fraction (θ) was analyzed as a function of ϕ, which is the N(Aβ1-40) per total surface area of nanogold colloids available for adsorption, the parameters for explaining the Langmuir-Freundlich model were in good agreement for both 20 and 80 nm gold, indicating that ϕ could define the stage of the aggregation process. Surface-enhanced Raman scattering (SERS) imaging was conducted at designated values of ϕ and suggested that a protein-gold surface interaction during the initial adsorption stage may be dependent on the nanosize. The 20 nm gold case seems to prefer a relatively smaller contacting section, such as a -C-N or C═C bond, but a plane of the benzene ring may play a significant role for 80 nm gold. Regardless of the size of the particles, the β-sheet and random coil conformations were considered to be used to form gold colloid aggregates. The methodology developed in this study allows for new insights into protein-protein interactions at distinct stages of aggregation.

Comparative Performance of Computer Simulation Models of Intrinsically Disordered Proteins at Different Levels of Coarse-Graining

Coarse-graining is commonly used to decrease the computational cost of simulations. However, coarse-grained models are also considered to have lower transferability, with lower accuracy for systems outside the original scope of parametrization. Here, we benchmark a bead-necklace model and a modified Martini 2 model, both coarse-grained models, for a set of intrinsically disordered proteins, with the different models having different degrees of coarse-graining. The SOP-IDP model has earlier been used for this set of proteins; thus, those results are included in this study to compare how models with different levels of coarse-graining compare. The sometimes naive expectation of the least coarse-grained model performing best does not hold true for the experimental pool of proteins used here. Instead, it showed the least good agreement, indicating that one should not necessarily trust the otherwise intuitive notion of a more advanced model inherently being better in model choice.

Metastable alpha-rich and beta-rich conformations of small Aβ42 peptide oligomers

Probing the structures of amyloid-β (Aβ) peptides in the early steps of aggregation is extremely difficult experimentally and computationally. Yet, this knowledge is extremely important as small oligomers are the most toxic species. Experiments and simulations on Aβ42 monomer point to random coil conformations with either transient helical or β-strand content. Our current conformational description of small Aβ42 oligomers is funneled toward amorphous aggregates with some β-sheet content and rare high energy states with well-ordered assemblies of β-sheets. In this study, we emphasize another view based on metastable α-helix bundle oligomers spanning the C-terminal residues, which are predicted by the machine-learning AlphaFold2 method and supported indirectly by low-resolution experimental data on many amyloid polypeptides. This finding has consequences in developing novel chemical tools and to design potential therapies to reduce aggregation and toxicity.

Enhancing Conformational Sampling for Intrinsically Disordered and Ordered Proteins by Variational Autoencoder

Intrinsically disordered proteins (IDPs) account for more than 50% of the human proteome and are closely associated with tumors, cardiovascular diseases, and neurodegeneration, which have no fixed three-dimensional structure under physiological conditions. Due to the characteristic of conformational diversity, conventional experimental methods of structural biology, such as NMR, X-ray diffraction, and CryoEM, are unable to capture conformational ensembles. Molecular dynamics (MD) simulation can sample the dynamic conformations at the atomic level, which has become an effective method for studying the structure and function of IDPs. However, the high computational cost prevents MD simulations from being widely used for IDPs conformational sampling. In recent years, significant progress has been made in artificial intelligence, which makes it possible to solve the conformational reconstruction problem of IDP with fewer computational resources. Here, based on short MD simulations of different IDPs systems, we use variational autoencoders (VAEs) to achieve the generative reconstruction of IDPs structures and include a wider range of sampled conformations from longer simulations. Compared with the generative autoencoder (AEs), VAEs add an inference layer between the encoder and decoder in the latent space, which can cover the conformational landscape of IDPs more comprehensively and achieve the effect of enhanced sampling. Through experimental verification, the Cα RMSD between VAE-generated and MD simulation sampling conformations in the 5 IDPs test systems was significantly lower than that of AE. The Spearman correlation coefficient on the structure was higher than that of AE. VAE can also achieve excellent performance regarding structured proteins. In summary, VAEs can be used to effectively sample protein structures.

Energy landscapes of Aβ monomers are sculpted in accordance with Ostwald's rule of stages

The transition from a disordered to an assembly-competent monomeric state (N*) in amyloidogenic sequences is a crucial event in the aggregation cascade. Using a well-calibrated model for intrinsically disordered proteins (IDPs), we show that the N* states, which bear considerable resemblance to the polymorphic fibril structures found in experiments, not only appear as excitations in the free energy landscapes of Aβ40 and Aβ42, but also initiate the aggregation cascade. For Aβ42, the transitions to the different N* states are in accord with Ostwald's rule of stages, with the least stable structures forming ahead of thermodynamically favored ones. The Aβ40 and Aβ42 monomer landscapes exhibit different extents of local frustration, which we show have profound implications in dictating subsequent self-assembly. Using kinetic transition networks, we illustrate that the most favored dimerization routes proceed via N* states. We argue that Ostwald's rule also holds for the aggregation of fused in sarcoma and polyglutamine proteins.

Simple and Effective Conformational Sampling Strategy for Intrinsically Disordered Proteins Using the UNRES Web Server

Intrinsically disordered proteins (IDPs) contain more charged amino acids than folded proteins, resulting in a lack of hydrophobic core(s) and a tendency to adopt rapidly interconverting structures rather than well-defined structures. The structural heterogeneity of IDPs, encoded by the amino acid sequence, is closely related to their unique roles in biological pathways, which require them to interact with different binding partners. Recently, Robustelli and co-workers have demonstrated that a balanced all-atom force field can be used to sample heterogeneous structures of disordered proteins ( Proc. Natl. Acad. Sci. U.S.A. 2018, 115, E4758-E4766). However, such a solution requires extensive computational resources, such as Anton supercomputers. Here, we propose a simple and effective solution to sample the conformational space of IDPs using a publicly available web server, namely, the UNited-RESidue (UNRES) web server. Our proposed solution requires no investment in computational resources and no prior knowledge of UNRES. UNRES Replica Exchange Molecular Dynamics (REMD) simulations were carried out on a set of eight disordered proteins at temperatures spanning from 270 to 430 K. Utilizing the latest UNRES force field designed for structured proteins, with proper selections of temperatures, we were able to produce comparable results to all-atom force fields as reported in work done by Robustelli and co-workers. In addition, NMR observables and the radius of gyration calculated from UNRES ensembles were directly compared with the experimental data to further evaluate the accuracy of the UNRES model at all temperatures. Our results suggest that carrying out the UNRES simulations at optimal temperatures using the UNRES web server can be a good alternative to sample heterogeneous structures of IDPs.

Influence of force field choice on the conformational landscape of rat and human islet amyloid polypeptide

Human islet amyloid polypeptide (hIAPP) is a naturally occurring, intrinsically disordered protein (IDP) whose abnormal aggregation into toxic soluble oligomers and insoluble amyloid fibrils is a pathological feature in type-2 diabetes. Rat IAPP (rIAPP) differs from hIAPP by only six amino acids yet has a reduced tendency to aggregate or form fibrils. The structures of the monomeric forms of IAPP are difficult to characterize due to their intrinsically disordered nature. Molecular dynamics simulations can provide a detailed characterization of the monomeric forms of rIAPP and hIAPP in near-physiological conditions. In this work, the conformational landscapes of rIAPP and hIAPP as a function of secondary structure content were predicted using well-tempered bias exchange metadynamics simulations. Several combinations of commonly used biomolecular force fields and water models were tested. The predicted conformational preferences of both rIAPP and hIAPP are typical of IDPs, exhibiting dominant random coil structures but showing a low propensity for transient α-helical conformations. Predicted nuclear magnetic resonance Cα chemical shifts reveal different preferences with each force field towards certain conformations, with AMBERff99SBnmr2/TIP4Pd showing the best agreement with the experiment. Comparisons of secondary structure content demonstrate residue-specific differences between hIAPP and rIAPP that may reflect their different aggregation propensities.

Remodeling of the Plasma Membrane by Surface-Bound Protein Monomers and Oligomers: The Critical Role of Intrinsically Disordered Regions

The plasma membrane (PM) of cells is a dynamic structure whose morphology and composition is in constant flux. PM morphologic changes are particularly relevant for the assembly and disassembly of signaling platforms involving surface-bound signaling proteins, as well as for many other mechanochemical processes that occur at the PM surface. Surface-bound membrane proteins (SBMP) require efficient association with the PM for their function, which is often achieved by the coordinated interactions of intrinsically disordered regions (IDRs) and globular domains with membrane lipids. This review focuses on the role of IDR-containing SBMPs in remodeling the composition and curvature of the PM. The ability of IDR-bearing SBMPs to remodel the Gaussian and mean curvature energies of the PM is intimately linked to their ability to sort subsets of phospholipids into nanoclusters. We therefore discuss how IDRs of many SBMPs encode lipid-binding specificity or facilitate cluster formation, both of which increase their membrane remodeling capacity, and how SBMP oligomers alter membrane shape by monolayer surface area expansion and molecular crowding.

An inducible amphipathic α-helix mediates subcellular targeting and membrane binding of RPE65

RPE65 retinol isomerase is an indispensable player in the visual cycle between the vertebrate retina and RPE. Although membrane association is critical for RPE65 function, its mechanism is not clear. Residues 107-125 are believed to interact with membranes but are unresolved in all RPE65 crystal structures, whereas palmitoylation at C112 also plays a role. We report the mechanism of membrane recognition and binding by RPE65. Binding of aa107-125 synthetic peptide with membrane-mimicking micellar surfaces induces transition from unstructured loop to amphipathic α-helical (AH) structure but this transition is automatic in the C112-palmitoylated peptide. We demonstrate that the AH significantly affects palmitoylation level, membrane association, and isomerization activity of RPE65. Furthermore, aa107-125 functions as a membrane sensor and the AH as a membrane-targeting motif. Molecular dynamic simulations clearly show AH-membrane insertion, supporting our experimental findings. Collectively, these studies allow us to propose a working model for RPE65-membrane binding, and to provide a novel role for cysteine palmitoylation.

Effects of Familial Alzheimer's Disease Mutations on the Folding Free Energy and Dipole-Dipole Interactions of the Amyloid β-Peptide

Familial Alzheimer's disease (FAD) mutations of the amyloid β-peptide (Aβ) are known to lead to early onset and more aggressive Alzheimer's disease. FAD mutations such as "Iowa" (D23N), "Arctic" (E22G), "Italian" (E22K), and "Dutch" (E22Q) have been shown to accelerate Aβ aggregation relative to the wild-type (WT). The mechanism by which these mutations facilitate increased aggregation is unknown, but each mutation results in a change in the net charge of the peptide. Previous studies have used nonpolarizable force fields to study Aβ, providing some insight into how this protein unfolds. However, nonpolarizable force fields have fixed charges that lack the ability to redistribute in response to changes in local electric fields. Here, we performed polarizable molecular dynamics simulations on the full-length Aβ42 of WT and FAD mutations and calculated folding free energies of the Aβ15-27 fragment via umbrella sampling. By studying both the full-length Aβ42 and a fragment containing mutations and the central hydrophobic cluster (residues 17-21), we were able to systematically study how these FAD mutations impact secondary and tertiary structure and the thermodynamics of folding. Electrostatic interactions, including those between permanent and induced dipoles, affected side-chain properties, salt bridges, and solvent interactions. The FAD mutations resulted in shifts in the electronic structure and solvent accessibility at the central hydrophobic cluster and the hydrophobic C-terminal region. Using umbrella sampling, we found that the folding of the WT and E22 mutants is enthalpically driven, whereas the D23N mutant is entropically driven, arising from a different unfolding pathway and peptide-bond dipole response. Together, the unbiased, full-length, and umbrella sampling simulations of fragments reveal that the FAD mutations perturb nearby residues and others in hydrophobic regions to potentially alter solubility. These results highlight the role electronic polarizability plays in amyloid misfolding and the role of heterogeneous microenvironments that arise as conformational change takes place.

Characterization of the Conformations of Amyloid Beta 42 in Solution That May Mediate Its Initial Hydrophobic Aggregation

Intrinsically disordered peptides, such as amyloid β42 (Aβ42), lack a well-defined structure in solution. Aβ42 can undergo abnormal aggregation and amyloidogenesis in the brain, forming fibrillar plaques, a hallmark of Alzheimer's disease. The insoluble fibrillar forms of Aβ42 exhibit well-defined, cross β-sheet structures at the molecular level and are less toxic than the soluble, intermediate disordered oligomeric forms. However, the mechanism of initial interaction of monomers and subsequent oligomerization is not well understood. The structural disorder of Aβ42 adds to the challenges of determining the structural properties of its monomers, making it difficult to understand the underlying molecular mechanism of pathogenic aggregation. Certain regions of Aβ42 are known to exhibit helical propensity in different physiological conditions. NMR spectroscopy has shown that the Aβ42 monomer at lower pH can adopt an α-helical conformation and as the pH is increased, the peptide switches to β-sheet conformation and aggregation occurs. CD spectroscopy studies of aggregation have shown the presence of an initial spike in the amount of α-helical content at the start of aggregation. Such an increase in α-helical content suggests a mechanism wherein the peptide can expose critical non-polar residues for interaction, leading to hydrophobic aggregation with other interacting peptides. We have used molecular dynamics simulations to characterize in detail the conformational landscape of monomeric Aβ42 in solution to identify molecular properties that may mediate the early stages of oligomerization. We hypothesized that conformations with α-helical structure have a higher probability of initiating aggregation because they increase the hydrophobicity of the peptide. Although random coil conformations were found to be the most dominant, as expected, α-helical conformations are thermodynamically accessible, more so than β-sheet conformations. Importantly, for the first time α-helical conformations are observed to increase the exposure of aromatic and hydrophobic residues to the aqueous solvent, favoring their hydrophobically driven interaction with other monomers to initiate aggregation. These findings constitute a first step toward characterizing the mechanism of formation of disordered, low-order oligomers of Aβ42.

A comprehensive review on preparation, structure-activities relationship, and calcium bioavailability of casein phosphopeptides

Calcium is one of the important elements for human health. Calcium deficiencies can lead to numerous diseases. Calcium chelating peptides have shown potential application in the management of calcium deficiencies. Casein phosphopeptides (CPP) are phosphoseryl-containing fragments of casein by enzymatic hydrolysis or fermentation during manufacture of milk products as well as during intestinal digestion. An increasing number of CPP with the ability to facilitate and enhance the bioavailability of calcium are being discovered and identified. In this review, 249 reported CPP derived from four types of bovine casein (αs1, αs2, β and κ) were collected, and the amino acid sequence and phosphoserine group information were sorted out. This review outlines the current enzyme hydrolysis, detection methods, purification, structure-activity relationship and mechanism of intestinal calcium absorption in vitro and in vivo as well as application of CPP.

A New Transfer Free Energy Based Implicit Solvation Model for the Description of Disordered and Folded Proteins

Most biological events occur on time scales that are difficult to access using conventional all-atom molecular dynamics simulations in explicit solvent. Implicit solvent techniques offer a promising solution to this problem, alleviating the computational cost associated with the simulation of large systems and accelerating the sampling compared to explicit solvent models. The substitution of water molecules by a mean field, however, introduces simplifications that may penalize accuracy and impede the prediction of certain physical properties. We demonstrate that existing implicit solvent models developed using a transfer free energy approach, while satisfactory at reproducing the folding behavior of globular proteins, fare less well in characterizing the conformational properties of intrinsically disordered proteins. We develop a new implicit solvent model that maximizes the degree of accuracy for both disordered and folded proteins. We show, by comparing the simulation outputs to experimental data, that in combination with the a99SB-disp force field, the implicit solvent model can describe both disordered (aβ40, PaaA2, and drkN SH3) and folded ((AAQAA)₃, CLN025, Trp-cage, and GTT) peptides. Our implicit solvent model permits a computationally efficient investigation of proteins containing both ordered and disordered regions, as well as the study of the transition between ordered and disordered protein states.

A Small Molecule Stabilizes the Disordered Native State of the Alzheimer's Aβ Peptide

The stabilization of native states of proteins is a powerful drug discovery strategy. It is still unclear, however, whether this approach can be applied to intrinsically disordered proteins. Here, we report a small molecule that stabilizes the native state of the Aβ42 peptide, an intrinsically disordered protein fragment associated with Alzheimer’s disease. We show that this stabilization takes place by a disordered binding mechanism, in which both the small molecule and the Aβ42 peptide remain disordered. This disordered binding mechanism involves enthalpically favorable local π-stacking interactions coupled with entropically advantageous global effects. These results indicate that small molecules can stabilize disordered proteins in their native states through transient non-specific interactions that provide enthalpic gain while simultaneously increasing the conformational entropy of the proteins.

Modeling the Structure and Interactions of Intrinsically Disordered Peptides with Multiple Replica, Metadynamics-Based Sampling Methods and Force-Field Combinations

Intrinsically disordered proteins play a key role in many biological processes, including the formation of biomolecular condensates within cells. A detailed characterization of their configurational ensemble and structure-function paradigm is crucial for understanding their biological activity and for exploiting them as building blocks in material sciences. In this work, we incorporate bias-exchange metadynamics and parallel-tempering well-tempered metadynamics with CHARMM36m and CHARMM22* to explore the structural and thermodynamic characteristics of a short archetypal disordered sequence derived from a DEAD-box protein. The conformational landscapes emerging from our simulations are largely congruent across methods and force fields. Nevertheless, differences in fine details emerge from varying combinations of force-fields and sampling methods. For this protein, our analysis identifies features that help to explain the low propensity of this sequence to undergo self-association in vitro, which are common to all force-field/sampling method combinations. Overall, our work demonstrates the importance of using multiple force-field and sampling method combinations for accurate structural and thermodynamic information in the study of disordered proteins.

Molecular Basis of Small-Molecule Binding to α-Synuclein

Intrinsically disordered proteins (IDPs) are implicated in many human diseases. They have generally not been amenable to conventional structure-based drug design, however, because their intrinsic conformational variability has precluded an atomic-level understanding of their binding to small molecules. Here we present long-time-scale, atomic-level molecular dynamics (MD) simulations of monomeric α-synuclein (an IDP whose aggregation is associated with Parkinson’s disease) binding the small-molecule drug fasudil in which the observed protein–ligand interactions were found to be in good agreement with previously reported NMR chemical shift data. In our simulations, fasudil, when bound, favored certain charge–charge and π-stacking interactions near the C terminus of α-synuclein but tended not to form these interactions simultaneously, rather breaking one of these interactions and forming another nearby (a mechanism we term dynamic shuttling). Further simulations with small molecules chosen to modify these interactions yielded binding affinities and key structural features of binding consistent with subsequent NMR experiments, suggesting the potential for MD-based strategies to facilitate the rational design of small molecules that bind with disordered proteins.

Computer Simulations Aimed at Exploring Protein Aggregation and Dissociation

Protein aggregation can lead to well-defined structures that are functional, but is also the cause of the death of neuron cells in many neurodegenerative diseases. The complexity of the molecular events involved in the aggregation kinetics of amyloid proteins and the transient and heterogeneous characters of all oligomers prevent high-resolution structural experiments. As a result, computer simulations have been used to determine the atomic structures of amyloid proteins at different association stages as well as to understand fibril dissociation. In this chapter, we first review the current computer simulation methods used for aggregation with some atomistic and coarse-grained results aimed at better characterizing the early formed oligomers and amyloid fibril formation. Then we present the applications of non-equilibrium molecular dynamics simulations to comprehend the dissociation of protein assemblies.

Non-specific porins of Gram-negative bacteria as proteins containing intrinsically disordered regions with amyloidogenic potential

Features of the structure and functional activity of bacterial outer membrane porins, coupled with their dynamic "behavior," suggests that intrinsically disordered regions (IDPRs) are contained in their structure. Using bioinformatic analysis, the quantitative content of amyloidogenic regions in the amino acid sequence of non-specific porins inhabiting various natural niches was determined: from terrestrial bacteria of the genus Yersinia (OmpF and OmpC proteins of Y. pseudotuberculosis and Y. ruckeri) and from the marine bacterium Marinomonas primoryensis (MpOmp). It was found that OmpF and OmpC porins can be classified as moderately disordered proteins, while MpOmp can be classified as highly disordered protein. Mapping of IDPRs, performed using 3D structures of monomers of the proteins, showed that the regions of increased conformational plasticity fall on the regions, the functional importance of which has been reliably confirmed as a result of numerous experimental studies. The revealed correlation made it possible to explain the differences in the physicochemical characteristics and properties of not only porins from terrestrial and marine bacteria, but also non-specific porins of different types, OmpF and OmpC proteins. First of all, this concerns the flexible outer loops that form the pore vestibule, as well as regions of the barrel with an increased "ability" for aggregation, the so-called "hot spots" of aggregation. The abnormally high content of IDPRs in the MpOmp structure made it possible to suggest that the high adaptive potential of bacteria may correlate with an increase in the number of IDPRs and/or regions with increased conformational variability.

Intrinsically disordered proteins and membranes: a marriage of convenience for cell signalling?

The structure-function paradigm has guided investigations into the molecules involved in cellular signalling for decades. The peripheries of this paradigm, however, start to unravel when considering the co-operation between proteins and the membrane in signalling processes. Intrinsically disordered regions hold distinct advantages over folded domains in terms of their binding promiscuity, sensitivity to their particular environment and their ease of modulation through post-translational modifications. Low sequence complexity and bias towards charged residues are also favourable for the multivalent electrostatic interactions that occur at the surfaces of lipid bilayers. This review looks at the principles behind the successful marriage between protein disorder and membranes in addition to the role of this partnership in modifying and regulating signalling in cellular processes. The HVR (hypervariable region) of small GTPases is highlighted as a well-studied example of the nuanced role a short intrinsically disordered region can play in the fine-tuning of signalling pathways.

Exploring the Early Stages of the Amyloid Aβ(1-42) Peptide Aggregation Process: An NMR Study

Alzheimer’s disease (AD) is a neurodegenerative pathology characterized by the presence of neurofibrillary tangles and amyloid plaques, the latter mainly composed of Aβ(1–40) and Aβ(1–42) peptides. The control of the Aβ aggregation process as a therapeutic strategy for AD has prompted the interest to investigate the conformation of the Aβ peptides, taking advantage of computational and experimental techniques. Mixtures composed of systematically different proportions of HFIP and water have been used to monitor, by NMR, the conformational transition of the Aβ(1–42) from soluble α-helical structure to β-sheet aggregates. In the previous studies, 50/50 HFIP/water proportion emerged as the solution condition where the first evident Aβ(1–42) conformational changes occur. In the hypothesis that this solvent reproduces the best condition to catch transitional helical-β-sheet Aβ(1–42) conformations, in this study, we report an extensive NMR conformational analysis of Aβ(1–42) in 50/50 HFIP/water v/v. Aβ(1–42) structure was solved by us, giving evidence that the evolution of Aβ(1–42) peptide from helical to the β-sheet may follow unexpected routes. Molecular dynamics simulations confirm that the structural model we calculated represents a starting condition for amyloid fibrils formation.

Force Field Benchmark of Amino Acids. 3. Hydration with Scaled Lennard-Jones Interactions

Classical protein force fields were reported with too weak protein-water interactions relative to protein-protein interactions, leading to more compact structures and artificial protein aggregation. Here we investigated the impacts of scaled Lennard-Jones (LJ) interactions on the hydration of amino acids and the simulation of folded and intrinsically disordered proteins (IDPs). The obtained optimal scaling parameters reproduce accurately hydration free energies of neutral amino acid side chain analogues and do not affect the compactness and structural stability of folded proteins significantly. The scaling leads to less compact IDPs and varies from case to case. Strengthening the interactions between protein and water oxygen or hydrogen atoms by increasing the interacting LJ well depth (ε) appears more effective than weakening protein-protein interactions by reducing the interacting dispersion coefficients (C₆). We demonstrate that weakening water-water interactions is a solution as well to obtaining more favorable protein-water interactions in an indirect way, although modern force fields like Amber ff19SB and a99SB-disp tend to use water models with strong water-water interactions. This is likely a compromise between strong protein-protein interactions and strong water-water interactions. Independent optimization of protein force fields and water models is therefore needed to make both interactions more close to reality, leading to good accuracy without bias or scaling.

Ubiquitin Interacting Motifs: Duality Between Structured and Disordered Motifs

Ubiquitin is a small protein at the heart of many cellular processes, and several different protein domains are known to recognize and bind ubiquitin. A common motif for interaction with ubiquitin is the Ubiquitin Interacting Motif (UIM), characterized by a conserved sequence signature and often found in multi-domain proteins. Multi-domain proteins with intrinsically disordered regions mediate interactions with multiple partners, orchestrating diverse pathways. Short linear motifs for binding are often embedded in these disordered regions and play crucial roles in modulating protein function. In this work, we investigated the structural propensities of UIMs using molecular dynamics simulations and NMR chemical shifts. Despite the structural portrait depicted by X-crystallography of stable helical structures, we show that UIMs feature both helical and intrinsically disordered conformations. Our results shed light on a new class of disordered UIMs. This group is here exemplified by the C-terminal domain of one isoform of ataxin-3 and a group of ubiquitin-specific proteases. Intriguingly, UIMs not only bind ubiquitin. They can be a recruitment point for other interactors, such as parkin and the heat shock protein Hsc70-4. Disordered UIMs can provide versatility and new functions to the client proteins, opening new directions for research on their interactome.

Integrating an Enhanced Sampling Method and Small-Angle X-Ray Scattering to Study Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) have been paid more and more attention over the past decades because they are involved in a multitude of crucial biological functions. Despite their functional importance, IDPs are generally difficult to investigate because they are very flexible and lack stable structures. Computer simulation may serve as a useful tool in studying IDPs. With the development of computer software and hardware, computational methods, such as molecular dynamics (MD) simulations, are popularly used. However, there is a sampling problem in MD simulations. In this work, this issue is investigated using an IDP called unique long region 11 (UL11), which is the conserved outer tegument component from herpes simplex virus 1. After choosing a proper force field and water model that is suitable for simulating IDPs, integrative modeling by combining an enhanced sampling method and experimental data like small-angle X-ray scattering (SAXS) is utilized to efficiently sample the conformations of UL11. The simulation results are in good agreement with experimental data. This work may provide a general protocol to study structural ensembles of IDPs.

Thermodynamics and kinetics of the amyloid-β peptide revealed by Markov state models based on MD data in agreement with experiment

The amlyoid-β peptide (Aβ) is closely linked to the development of Alzheimer's disease. Molecular dynamics (MD) simulations have become an indispensable tool for studying the behavior of this peptide at the atomistic level. General key aspects of MD simulations are the force field used for modeling the peptide and its environment, which is important for accurate modeling of the system of interest, and the length of the simulations, which determines whether or not equilibrium is reached. In this study we address these points by analyzing 30-μs MD simulations acquired for Aβ40 using seven different force fields. We assess the convergence of these simulations based on the convergence of various structural properties and of NMR and fluorescence spectroscopic observables. Moreover, we calculate Markov state models for the different MD simulations, which provide an unprecedented view of the thermodynamics and kinetics of the amyloid-β peptide. This further allows us to provide answers for pertinent questions, like: which force fields are suitable for modeling Aβ? (a99SB-UCB and a99SB-ILDN/TIP4P-D); what does Aβ peptide really look like? (mostly extended and disordered) and; how long does it take MD simulations of Aβ to attain equilibrium? (at least 20-30 μs). We believe the analyses presented in this study will provide a useful reference guide for important questions relating to the structure and dynamics of Aβ in particular, and by extension other similar disordered proteins.

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.

Secondary structure dependence of amyloid-β(1-40) on simulation techniques and force field parameters

Our recent studies revealed that none of the selected widely used force field parameters and molecular dynamics simulation techniques yield structural properties for the intrinsically disordered α-synuclein that are in agreement with various experiments via testing different force field parameters. Here, we extend our studies on the secondary structure properties of the disordered amyloid-β(1-40) peptide in aqueous solution. For these purposes, we conducted extensive replica exchange molecular dynamics simulations and obtained extensive molecular dynamics simulation trajectories from David E. Shaw group. Specifically, these molecular dynamics simulations were conducted using various force field parameters and obtained results are compared to our replica exchange molecular dynamics simulations and experiments. In this study, we calculated the secondary structure abundances and radius of gyration values for amyloid-β(1-40) that were simulated using varying force field parameter sets and different simulation techniques. In addition, the intrinsic disorder propensity, as well as sequence-based secondary structure predisposition of amyloid-β(1-40) and compared the findings with the results obtained from molecular simulations using various force field parameters and different simulation techniques. Our studies clearly show that the epitope region identification of amyloid-β(1-40) depends on the chosen simulation technique and chosen force field parameters. Based on comparison with experiments, we find that best computational results in agreement with experiments are obtained using the a99sb*-ildn, charmm36m, and a99sb-disp parameters for the amyloid-β(1-40) peptide in molecular dynamics simulations without parallel tempering or via replica exchange molecular dynamics simulations.

Recent advances in atomic molecular dynamics simulation of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) play important roles in cellular functions. The inherent structural heterogeneity of IDPs makes the high-resolution experimental characterization of IDPs extremely difficult. Molecular dynamics (MD) simulation could provide the atomic-level description of the structural and dynamic properties of IDPs. This perspective reviews the recent progress in atomic MD simulation studies of IDPs, including the development of force fields and sampling methods, as well as applications in IDP-involved protein-protein interactions. The employment of large-scale simulations and advanced sampling techniques allows more accurate estimation of the thermodynamics and kinetics of IDP-mediated protein interactions, and the holistic landscape of the binding process of IDPs is emerging.

A kinetic ensemble of the Alzheimer's Aβ peptide

The conformational and thermodynamic properties of disordered proteins are commonly described in terms of structural ensembles and free energy landscapes. To provide information on the transition rates between the different states populated by these proteins, it would be desirable to generalize this description to kinetic ensembles. Approaches based on the theory of stochastic processes can be particularly suitable for this purpose. Here, we develop a Markov state model and apply it to determine a kinetic ensemble of Aβ42, a disordered peptide associated with Alzheimer's disease. Through the Google Compute Engine, we generated 315-µs all-atom molecular dynamics trajectories. Using a probabilistic-based definition of conformational states in a neural network approach, we found that Aβ42 is characterized by inter-state transitions on the microsecond timescale, exhibiting only fully unfolded or short-lived, partially folded states. Our results illustrate how kinetic ensembles provide effective information about the structure, thermodynamics and kinetics of disordered proteins.

Molecular simulations of IDPs: From ensemble generation to IDP interactions leading to disorder-to-order transitions

Intrinsically disordered proteins (IDPs) lack a well-defined three-dimensional structure but do exhibit some dynamical and structural ordering. The structural plasticity of IDPs indicates that entropy-driven motions are crucial for their function. Many IDPs undergo function-related disorder-to-order transitions upon by their interaction with specific binding partners. Approaches that are based on both experimental and theoretical tools enable the biophysical characterization of IDPs. Molecular simulations provide insights into IDP structural ensembles and disorder-to-order transition mechanisms. However, such studies depend strongly on the chosen force field parameters and simulation techniques. In this chapter, we provide an overview of IDP characteristics, review all-atom force fields recently developed for IDPs, and present molecular dynamics-based simulation methods that allow IDP ensemble generation as well as the characterization of disorder-to-order transitions. In particular, we introduce metadynamics, replica exchange molecular dynamics simulations, and also kinetic models resulting from Markov State modeling, and provide various examples for the successful application of these simulation methods to IDPs.

Shear-Induced Amyloid Aggregation in the Brain: V. Are Alzheimer's and Other Amyloid Diseases Initiated in the Lower Brain and Brainstem by Cerebrospinal Fluid Flow Stresses?

Amyloid-β (Aβ) and tau oligomers have been identified as neurotoxic agents responsible for causing Alzheimer's disease (AD). Clinical trials using Aβ and tau as targets have failed, giving rise to calls for new research approaches to combat AD. This paper provides such an approach. Most basic AD research has involved quiescent Aβ and tau solutions. However, studies involving laminar and extensional flow of proteins have demonstrated that mechanical agitation of proteins induces or accelerates protein aggregation. Recent MRI brain studies have revealed high energy, chaotic motion of cerebrospinal fluid (CSF) in lower brain and brainstem regions. These and studies showing CSF flow within the brain have shown that there are two energetic hot spots. These are within the third and fourth brain ventricles and in the neighborhood of the circle of Willis blood vessel region. These two regions are also the same locations as those of the earliest Aβ and tau AD pathology. In this paper, it is proposed that cardiac systolic pulse waves that emanate from the major brain arteries in the lower brain and brainstem regions and whose pulse waves drive CSF flows within the brain are responsible for initiating AD and possibly other amyloid diseases. It is further proposed that the triggering of these diseases comes about because of the strengthening of systolic pulses due to major artery hardening that generates intense CSF extensional flow stress. Such stress provides the activation energy needed to induce conformational changes of both Aβ and tau within the lower brain and brainstem region, producing unique neurotoxic oligomer molecule conformations that induce AD.

Osmolytes dynamically regulate mutant Huntingtin aggregation and CREB function in Huntington's disease cell models

Osmolytes are organic solutes that change the protein folding landscape shifting the equilibrium towards the folded state. Herein, we use osmolytes to probe the structuring and aggregation of the intrinsically disordered mutant Huntingtin (mHtt) vis-a-vis the pathogenicity of mHtt on transcription factor function and cell survival. Using an inducible PC12 cell model of Huntington's disease (HD), we show that stabilizing polyol osmolytes drive the aggregation of Htt103QExon1-EGFP from a diffuse ensemble into inclusion bodies (IBs), whereas the destabilizing osmolyte urea does not. This effect of stabilizing osmolytes is innate, generic, countered by urea, and unaffected by HSP70 and HSC70 knockdown. A qualitatively similar result of osmolyte-induced mHtt IB formation is observed in a conditionally immortalized striatal neuron model of HD, and IB formation correlates with improved survival under stress. Increased expression of diffuse mHtt sequesters the CREB transcription factor to repress CREB-reporter gene activity. This repression is mitigated either by stabilizing osmolytes, which deplete diffuse mHtt or by urea, which negates protein-protein interaction. Our results show that stabilizing polyol osmolytes promote mHtt aggregation, alleviate CREB dysfunction, and promote survival under stress to support the hypothesis that lower molecular weight entities of disease protein are relevant pathogenic species in neurodegeneration.

A rationally designed bicyclic peptide remodels Aβ42 aggregation in vitro and reduces its toxicity in a worm model of Alzheimer's disease

Bicyclic peptides have great therapeutic potential since they can bridge the gap between small molecules and antibodies by combining a low molecular weight of about 2 kDa with an antibody-like binding specificity. Here we apply a recently developed in silico rational design strategy to produce a bicyclic peptide to target the C-terminal region (residues 31–42) of the 42-residue form of the amyloid β peptide (Aβ42), a protein fragment whose aggregation into amyloid plaques is linked with Alzheimer’s disease. We show that this bicyclic peptide is able to remodel the aggregation process of Aβ42 in vitro and to reduce its associated toxicity in vivo in a C. elegans worm model expressing Aβ42. These results provide an initial example of a computational approach to design bicyclic peptides to target specific epitopes on disordered proteins.

Effect of surface chemistry on islet amyloid polypeptide conformation

The formation of dense, linear arrays (fibrils) by biomolecules is the hallmark of a number of degenerative diseases, such as Alzheimer's and type-2 diabetes. Protein fibrils have also attracted interest as building blocks for new materials. It has long been recognized that surfaces can affect the fibrillation process. Recent work on the model fibril forming protein human islet amyloid polypeptide (hIAPP) has shown that while the protein concentration is highest at hydrophobic surfaces, the rate of fibril formation is lower than on other surfaces. To understand this, replica exchange molecular dynamics simulations were used to investigate the conformations that hIAPP adopts on surfaces of different hydrophobicities. The hydrophobic surface stabilizes α-helical structures which are significantly different to those found on the hydrophilic surface and in bulk solution. There is also a greatly reduced conformational ensemble on the hydrophobic surface due to long-lived contacts between hydrophobic residues on the protein and the surface. This new microscopic information will help us determine the mechanism of the enhancement of fibril formation on surfaces and provides new insight into the effect of nanointerfaces and protein conformation.

Development of Charge-Augmented Three-Point Water Model (CAIPi3P) for Accurate Simulations of Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) are molecules without a fixed tertiary structure, exerting crucial roles in cellular signalling, growth and molecular recognition events. Due to their high plasticity, IDPs are very challenging in experimental and computational structural studies. To provide detailed atomic insight in IDPs' dynamics governing their functional mechanisms, all-atom molecular dynamics (MD) simulations are widely employed. However, the current generalist force fields and solvent models are unable to generate satisfactory ensembles for IDPs when compared to existing experimental data. In this work, we present a new solvation model, denoted as the Charge-Augmented Three-Point Water Model for Intrinsically Disordered Proteins (CAIPi3P). CAIPi3P has been generated by performing a systematic scan of atomic partial charges assigned to the widely popular molecular scaffold of the three-point TIP3P water model. We found that explicit solvent MD simulations employing CAIPi3P solvation considerably improved the small-angle X-ray scattering (SAXS) scattering profiles for three different IDPs. Not surprisingly, this improvement was further enhanced by using CAIPi3P water in combination with the protein force field parametrized for IDPs. We also demonstrated the applicability of CAIPi3P to molecular systems containing structured as well as intrinsically disordered regions/domains. Our results highlight the crucial importance of solvent effects for generating molecular ensembles of IDPs which reproduce the experimental data available. Hence, we conclude that our newly developed CAIPi3P solvation model is a valuable tool for molecular simulations of intrinsically disordered proteins and assessing their molecular dynamics.

Differences in the free energies between the excited states of Aβ40 and Aβ42 monomers encode their aggregation propensities

The early events in the aggregation of the intrinsically disordered peptide, amyloid-β (Aβ), involve transitions from the disordered free energy ground state to assembly-competent states. Are the fingerprints of order found in the amyloid fibrils encoded in the conformations that the monomers access at equilibrium? If so, could the enhanced aggregation rate of Aβ42 compared to Aβ40 be rationalized from the sparsely populated high free energy states of the monomers? Here, we answer these questions in the affirmative using coarse-grained simulations of the self-organized polymer-intrinsically disordered protein (SOP-IDP) model of Aβ40 and Aβ42. Although both the peptides have practically identical ensemble-averaged properties, characteristic of random coils (RCs), the conformational ensembles of the two monomers exhibit sequence-specific heterogeneity. Hierarchical clustering of conformations reveals that both the peptides populate high free energy aggregation-prone ([Formula: see text]) states, which resemble the monomers in the fibril structure. The free energy gap between the ground (RC) and the [Formula: see text] states of Aβ42 peptide is smaller than that for Aβ40. By relating the populations of excited states of the two peptides to the fibril formation time scales using an empirical formula, we explain nearly quantitatively the faster aggregation rate of Aβ42 relative to Aβ40. The [Formula: see text] concept accounts for fibril polymorphs, leading to the prediction that the less stable [Formula: see text] state of Aβ42, encoding for the U-bend fibril, should form earlier than the structure with the S-bend topology, which is in accord with Ostwald's rule rationalizing crystal polymorph formation.

Shear-induced aggregation of amyloid β (1-40) in a parallel plate geometry

Protein aggregation is induced by various environmental or external factors and associated with various neurodegenerative diseases. Among various external factors, shear stress is inevitable for both in vivo and in vitro applications of proteins. In this study, Aβ (1-40) peptide, a derivative of the amyloid precursor protein, was subjected to constant (300, 500, 700 s^-1) and varying (ramp) shear in a parallel plate geometry to explore the implications of shear in terms of macro (viscosity) and micro (secondary structure, morphology) characteristics. Aβ (1-40) solution followed a shear thickening flow behaviour with performance index value 'n' of 2.12. The fibrillation process resulting from the shear force was evaluated in terms of dissipation energy, which was found to exceed the free energy of unfolding. This resulted in the formation of β-sheet rich structures, which were confirmed by CD and FTIR analyses and enhanced Th-T fluorescence. The apparent rate of aggregation (k) was found to increase with the shear rate, and inversely related to the solution viscosity. The maximum k value was 0.21 ± 0.3 min^-1 at 700 s^-1. The molecular weights of aggregates were determined using gel filtration, which were proportionally related to the solution viscosity. The average molecular weights were estimated to be 70, 62 and 52 KDa for samples sheared at 300, 500 and 700 s^-1, respectively. The present study has deciphered the interplay of viscosity, a fluid property, with the aggregation process and its corresponding change in the secondary structures of the peptide. These findings provide useful insights for understanding various proteopathies under shear force.Communicated by Ramaswamy H. Sarma.

Dynamical Behavior and Conformational Selection Mechanism of the Intrinsically Disordered Sic1 Kinase-Inhibitor Domain

Intrinsically Disordered Peptides and Proteins (IDPs) in solution can span a broad range of conformations that often are hard to characterize by both experimental and computational methods. However, obtaining a significant representation of the conformational space is important to understand mechanisms underlying protein functions such as partner recognition. In this work, we investigated the behavior of the Sic1 Kinase-Inhibitor Domain (KID) in solution by Molecular Dynamics (MD) simulations. Our results point out that application of common descriptors of molecular shape such as Solvent Accessible Surface (SAS) area can lead to misleading outcomes. Instead, more appropriate molecular descriptors can be used to define 3D structures. In particular, we exploited Weighted Holistic Invariant Molecular (WHIM) descriptors to get a coarse-grained but accurate definition of the variegated Sic1 KID conformational ensemble. We found that Sic1 is able to form a variable amount of folded structures even in absence of partners. Among them, there were some conformations very close to the structure that Sic1 is supposed to assume in the binding with its physiological complexes. Therefore, our results support the hypothesis that this protein relies on the conformational selection mechanism to recognize the correct molecular partners.

Structures of the intrinsically disordered Aβ, tau and α-synuclein proteins in aqueous solution from computer simulations

Intrinsically disordered proteins (IDPs) play many biological roles in the human proteome ranging from vesicular transport, signal transduction to neurodegenerative diseases. The Aβ and tau proteins, and the α-synuclein protein, key players in Alzheimer's and Parkinson's diseases, respectively are fully disordered at the monomer level. The structural heterogeneity of the monomeric and oligomeric states and the high self-assembly propensity of these three IDPs have precluded experimental structural determination. Simulations have been used to determine the atomic structures of these IDPs. In this article, we review recent computer models to capture the equilibrium ensemble of Aβ, tau and α-synuclein proteins at different association steps in aqueous solution and present new results of the PEP-FOLD framework on α-synuclein monomer.

Deciphering calcium-binding behaviors of casein phosphopeptides by experimental approaches and molecular simulation

Casein phosphopeptides (CPPs) as premium additives in functional foods can facilitate the transport and adsorption of calcium. The atomic resolution decipherment of calcium-CPP binding behaviors is critical for understanding the calcium bioavailability enhancement potential of CPPs. In the present study, the experimental methods (UV-vis, FTIR and isothermal titration calorimetry) and molecular dynamics simulation were combined to reveal the calcium-binding behaviors of β-casein phosphopeptides (1-25) (P5) with the best capability in carrying calcium ions. We found that it could carry approximately six calcium ions, and the calcium-binding sites were primarily located at the carbonyl group of Glu-2 and the phosphate group of phosphorylated Ser-15, Ser-18, and Ser-19. An interesting finding was that calcium ions could be bound by three coordinated modes, including unidentate, bidentate and tridentate geometries, resulting in the strong binding abilities. The binding process of calcium ions to P5 was spontaneous with the binding free energies of -5.2 kcal mol-1. Hydrophobic interactions were considered to be the major driving force for the calcium ion binding. The present study provides novel molecular insights into the binding process between Ca2+ and calcium-binding peptides.