Force Field Effects in Simulations of Flexible Peptides with Varying Polyproline II Propensity

Molecular Modelling in Bioactive Peptide Discovery and Characterisation

Molecular modelling is a vital tool in the discovery and characterisation of bioactive peptides, providing insights into their structural properties and interactions with biological targets. Many models predicting bioactive peptide function or structure rely on their intrinsic properties, including the influence of amino acid composition, sequence, and chain length, which impact stability, folding, aggregation, and target interaction. Homology modelling predicts peptide structures based on known templates. Peptide-protein interactions can be explored using molecular docking techniques, but there are challenges related to the inherent flexibility of peptides, which can be addressed by more computationally intensive approaches that consider their movement over time, called molecular dynamics (MD). Virtual screening of many peptides, usually against a single target, enables rapid identification of potential bioactive peptides from large libraries, typically using docking approaches. The integration of artificial intelligence (AI) has transformed peptide discovery by leveraging large amounts of data. AlphaFold is a general protein structure prediction tool based on deep learning that has greatly improved the predictions of peptide conformations and interactions, in addition to providing estimates of model accuracy at each residue which greatly guide interpretation. Peptide function and structure prediction are being further enhanced using Protein Language Models (PLMs), which are large deep-learning-derived statistical models that learn computer representations useful to identify fundamental patterns of proteins. Recent methodological developments are discussed in the context of canonical peptides, as well as those with modifications and cyclisations. In designing potential peptide therapeutics, the main outstanding challenge for these methods is the incorporation of diverse non-canonical amino acids and cyclisations.

Molecular Dynamics Insights into Peptide-Based Tetrodotoxin Delivery Nanostructures

Tetrodotoxin (TTX), a potent Site-1 sodium channel blocker (S1SCB), offers highly effective local anesthetic properties with minimal addiction potential. To fully leverage TTX's capabilities as a local anesthetic, it is crucial to develop a drug delivery system that balances its systemic toxicity with its therapeutic efficacy. Recent studies have shown that peptide mixtures, derived from fragments of Site-1 sodium channel proteins and enhanced with hydrophobic tails (designated MP1 and MP2), can self-assemble into nanostructures that exhibit remarkable sustained-release capabilities for TTX. Despite the profound impact that the addition of a hydrophobic tail has on altering the release behavior of the original peptides, the atomic-level interactions and mechanisms underlying this phenomenon remain poorly understood. In this study, a combination of ColabFold and molecular dynamics (MD) simulations were used to investigate the binding interactions between TTX and the nanostructures formed by MP1 and MP2 at an atomic level. Our findings agree with experimental observations and indicate that the MP1/MP2 nanostructure demonstrates greater stability and higher binding affinity for TTX compared to their non-modified counterparts, P1 and P2. The analysis of the simulations revealed that charged amino acids, specifically aspartic acid (ASP) and glutamic acid (GLU), on the peptides are crucial for strong TTX binding and serve as the primary functional sites. Additionally, the stability of the nanostructure significantly affects TTX binding affinity, elucidating why P1, P2, MP1, and MP2 exhibit different binding capabilities despite containing identical charged residues. The results reported here may provide fundamental information to drive future research and enhance the development of TTX-based drug delivery systems.

Survey of the Aβ-peptide structural diversity: molecular dynamics approaches

The review deals with the application of Molecular Dynamics (MD) to the structure modeling of beta-amyloids (Aβ), currently classified as intrinsically disordered proteins (IDPs). In this review, we strive to relate the main advances in this area but specifically focus on the approaches and methodology. All relevant papers on the Aβ modeling are cited in the Tables in Supplementary Data, including a concise description of the applied approaches, sorted according to the types of the studied systems: modeling of the monomeric Aβ and Aβ aggregates. Similar sections focused according to the type of modeled object are present in the review. In the final part of the review, novel methods of general IDP modeling not confined to Aβ are described.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12551-024-01253-y.

Likely Overstabilization of Charge-Charge Interactions in CHARMM36m(w): A Case for a99SB-disp Water

Recent years have witnessed drastic improvements in general-purpose explicit solvent protein force fields, partially driven by the need to study intrinsically disordered proteins (IDPs), and yet the state-of-the-art force fields such as CHARMM36m (c36m) and a99SB-disp still provide different performances in simulating disordered protein states, where c36m has a bias toward overcompaction for large IDPs. Here, we examine the performance of c36m and a99SB-disp in describing the stabilities of a set of 46 amino acid backbone and side chain pairs in various configurations. The free energy results show that c36m systematically predicts stronger interactions compared to a99SB-disp by an average of 0.2 kcal/mol for nonpolar pairs, 0.6 kcal/mol for polar pairs, and 0.8 kcal/mol for salt bridges. The most severe overstabilization in c36m is observed for charged pairs involving the Arg and Glu side chains by up to 2.9 kcal/mol. Importantly, the systematic overstabilization of c36m is only marginally alleviated by c36mw, an ad hoc patch to c36m that increases the dispersion interactions between TIP3P hydrogens and protein atoms. Guided by free energy decomposition, we evaluated if revising the charges alone could alleviate the severe overstabilization of salt bridges of c36m(w) vs a99SB-disp. The results suggested that the direct modification of protein-water interactions is also necessary. Toward this end, we proposed a tentative modification to c36m, referred to as c36mrb-disp, which combines modified Arg side chain charges, retuned backbone hydrogen bonding strength, and the a99SB-disp water model. The modified force field successfully reproduces the secondary structures of several intrinsically disordered peptides and proteins including (AAQAA)3, GB1p, and p53 transactivation domain, while maintaining the stability of a set of folded proteins. This work provides a set of useful systems for benchmarking and optimizing protein force fields and highlights the importance of balancing protein-protein and protein-water electrostatic interactions for accurately describing both folded and disordered proteins.

Reducing the assemblies of amyloid-beta multimers by sodium dodecyl sulfate surfactant at concentrations lower than critical micelle concentration: molecular dynamics simulation exploration

Amyloid-β peptide, the predominant proteinaceous component of senile plaques, is responsible for the incidence of Alzheimer's disease (AD), an age-associated neurodegenerative disorder. Specifically, the amyloid-β(1-42) (Aβ1-42) isoform, known for its high toxicity, is the predominant biomarker for the preliminary diagnosis of AD. The aggregation of the Aβ1-42 peptides can be affected by the components of the cellular medium through changing their structures and molecular interactions. In this study, we investigated the effect of sodium dodecyl sulfate (SDS) at much lower concentrations than the critical micelle concentration (CMC) on Aβ1-42 aggregation. For this purpose, we studied mono-, di-, tri- and tetramers of Aβ1-42 peptide in two different concentrations of SDS molecules (10 and 40 molecules) using a 300 ns molecular dynamics simulation for each system. The distance between the center of mass (COM) of Aβ1-42 peptides confirms that an increase in the number of SDS molecules decreases their aggregation probability due to greater interaction with SDS molecules. Besides, the less compactness parameter reveals the reduced aggregation probability of Aβ1-42 peptides. Based on the energetic FEL landscapes, SDS molecules with the concentration closer to the CMC are an effective inhibitory agent to prevent the formation of Aβ1-42 fibrils. Also, the aggregation direction of the peptide pairs can be predicted by determining the direction of the accumulation-deterrent forces.Communicated by Ramaswamy H. Sarma.

Computational Methods to Investigate Intrinsically Disordered Proteins and their Complexes

In 1999 Wright and Dyson highlighted the fact that large sections of the proteome of all organisms are comprised of protein sequences that lack globular folded structures under physiological conditions. Since then the biophysics community has made significant strides in unraveling the intricate structural and dynamic characteristics of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs). Unlike crystallographic beamlines and their role in streamlining acquisition of structures for folded proteins, an integrated experimental and computational approach aimed at IDPs/IDRs has emerged. In this Perspective we aim to provide a robust overview of current computational tools for IDPs and IDRs, and most recently their complexes and phase separated states, including statistical models, physics-based approaches, and machine learning methods that permit structural ensemble generation and validation against many solution experimental data types.

Wet Conformation of Prion-Like Domain and Intimate Correlation of Hydration and Conformational Fluctuations

Proteins with prion-like domains (PLDs) are involved in neurodegeneration-associated aggregation and are prevalent in liquid-like membrane-less organelles. These PLDs contain amyloidogenic stretches but can maintain dynamic disordered conformations, even in the condensed phase. However, the molecular mechanism underlying such intricate conformational properties of PLDs remains elusive. Here we employed molecular dynamics simulations to investigate the conformational properties of a prototypical PLD system (i.e., FUS PLD). According to our simulation results, PLD adopts a wet collapsed conformation, wherein most residues maintain sufficient hydration with the abundance of internal water. These internal water molecules can rapidly exchange between the protein interior and the bulk, enabling intensive coupling of the entire protein with its hydration environment. The dynamic exchange of water molecules is intimately correlated to the overall conformational fluctuations of PLD. Furthermore, the abundance of dynamic internal water suppresses the formation of aggregation-prone ordered structures. These results collectively elucidate the crucial role of internal water in sustaining the dynamic disordered conformation of the PLD and inhibiting its aggregation propensity.

Deeper Insight of the Conformational Ensemble of Intrinsically Disordered Proteins

It is generally known that, unlike structured proteins, intrinsically disordered proteins, IDPs, exhibit various structures and conformers, the so-called conformational ensemble, CoE. This study aims to better understand the conformers that make up the IDP ensemble by decomposing the CoE into groups separated by their radius of gyration, Rg. A common approach to studying CoE for IDPs is to use low-resolution techniques, such as small-angle scattering, and combine those with computer simulations on different length scales. Herein, the well-studied antimicrobial saliva protein histatin 5 was utilized as a model peptide for an IDP; the average intensity curves were obtained from small-angle X-ray scattering; and compared with fully atomistic, explicit water, molecular dynamics simulations; then, the intensity curve was decomposed with respect to the different Rg values; and their secondary structure propensities were investigated. We foresee that this approach can provide important information on the CoE and the individual conformers within; in that case, it will serve as an additional tool for understanding the IDP structure-function relationship on a more detailed level.

Exploring the Functional Landscape of the p53 Regulatory Domain: The Stabilizing Role of Post-Translational Modifications

This study focuses on the intrinsically disordered regulatory domain of p53 and the impact of post-translational modifications. Through fully atomistic explicit water molecular dynamics simulations, we show the wealth of information and detailed understanding that can be obtained by varying the number of phosphorylated amino acids and implementing a restriction in the conformational entropy of the N-termini of that intrinsically disordered region. The take-home message for the reader is to achieve a detailed understanding of the impact of phosphorylation with respect to (1) the conformational dynamics and flexibility, (2) structural effects, (3) protein interactivity, and (4) energy landscapes and conformational ensembles. Although our model system is the regulatory domain p53 of the tumor suppressor protein p53, this study contributes to understanding the general effects of intrinsically disordered phosphorylated proteins and the impact of phosphorylated groups, more specifically, how minor changes in the primary sequence can affect the properties mentioned above.

Insights into the mechanism of peptide fibril growth on gold surface

Understanding the formation of β-fibrils over the gold surface is of paramount interest in nano-bio-medicinal Chemistry. The intricate mechanism of self-assembly of neurofibrillogenic peptides and their growth over the gold surface remains elusive, as experiments are limited in unveiling the microscopic dynamic details, in particular, at the early stage of the peptide aggregation. In this work, we carried out equilibrium molecular dynamics and enhanced sampling simulations to elucidate the underlying mechanism of the growth of an amyloid-forming sequence of tau fragments over the gold surface. Our results disclose that the collective intermolecular interactions between the peptide chains and peptides with the gold surface facilitate the peptide adsorption, followed by integration, finally leading to the fibril formation.

Histatin 5-Inspired Short-Chain Peptides Selectively Combating Pathogenic Fungi with Multifaceted Mechanisms

Short-chain antifungal peptides (AFPs) inspired by histatin 5 have been designed to address the problem of antifungal drug resistance. These AFPs demonstrate remarkable antifungal activity, with a minimal inhibitory concentration as low as 2 µg mL-1. Notably, these AFPs display a strong preference for targeting fungi rather than bacteria and mammalian cells. This is achieved by binding the histidine-rich domains of the AFPs to the Ssa1/2 proteins in the fungal cell wall, as well as the reduced membrane-disrupting activity due to their low amphiphilicity. These peptides disrupt the nucleus and mitochondria once inside the cells, leading to reactive oxygen species production and cell damage. In a mouse model of vulvovaginal candidiasis, the AFPs demonstrate not only antifungal activity, but also promote the growth of beneficial Lactobacillus spp. This research provides valuable insights for the development of fungus-specific AFPs and offers a promising strategy for the treatment of fungal infectious diseases.

Intrinsic Conformational Dynamics of Glycine and Alanine in Polarizable Molecular Dynamics Force Fields: Comparison to Spectroscopic Data

Molecular dynamics (MD) is a great tool for elucidating conformational dynamics of proteins and peptides in water at the atomistic level that often surpasses the level of detail available experimentally. Structure predictions, however, are limited by the accuracy of the underlying MD force field. This limitation is particularly stark in the case of intrinsically disordered peptides and proteins, which are characterized by solvent-accessible and disordered peptide regions and domains. Recent studies show that most additive MD force fields, including CHARMM36m, do not reproduce the intrinsic conformational distributions of guest amino acid residues x in cationic GxG peptides in water in line with experimental data. Positing that a lack of polarizability in additive MD force fields may be the culprit for the reported discrepancies, we here examine the conformational dynamics of guest glycine and alanine residues in cationic GxG peptides in water using two polarizable MD force fields, CHARMM Drude and AMOEBA. Our results indicate that while AMOEBA captures the experimental data better than CHARMM Drude, neither of the two polarizable force fields offers an improvement of the Ramachandran distributions of glycine and alanine residues in cationic GGG and GAG peptides, respectively, over CHARMM36m.

Exploring the Role of Globular Domain Locations on an Intrinsically Disordered Region of p53: A Molecular Dynamics Investigation

The pre-tetramerization loop (PTL) of the human tumor suppressor protein p53 is an intrinsically disordered region (IDR) necessary for the tetramerization process, and its flexibility contributes to the essential conformational changes needed. Although the IDR can be accurately simulated in the traditional manner of molecular dynamics (MD) with the end-to-end distance (EEdist) unhindered, we sought to explore the effects of restraining the EEdist to the values predicted by electron microscopy (EM) and other distances. Simulating the PTL trajectory with a restrained EEdist , we found an increased agreement of nuclear magnetic resonance (NMR) chemical shifts with experiments. Additionally, we observed a plethora of secondary structures and contacts that only appear when the trajectory is restrained. Our findings expand the understanding of the tetramerization of p53 and provide insight into how mutations could make the protein impotent. In particular, our findings demonstrate the importance of restraining the EEdist in studying IDRs and how their conformations change under different conditions. Our results provide a better understanding of the PTL and the conformational dynamics of IDRs in general, which are useful for further studies regarding mutations and their effects on the activity of p53.

Structure Comparison of Beta Amyloid Peptide Aβ 1-42 Isoforms. Molecular Dynamics Modeling

Beta amyloid peptide Aβ 1-42 (Aβ42) has a unique dual role in the human organism, as both the peptide with an important physiological function and one of the most toxic biological compounds provoking Alzheimer's disease (AD). There are several known Aβ42 isoforms that we discuss here that are highly neurotoxic and lead to the early onset of AD. Aβ42 is an intrinsically disordered protein with no experimentally solved structure under physiological conditions. The objective of this research was to establish the appropriate molecular dynamics (MD) methodology and model a uniform set of structures for the Aβ42 isoforms that form the core of this study. For that purpose, force field selection and verification including convergence testing for MD simulations was made. Replica exchange MD and conventional MD modeling of several Aβ42 and Aβ16 isoforms that have neurotoxic and amyloidogenic effects impacting the severity of Alzheimer's disease were carried out with the optimal force field and solvent parameters. A standardized ensemble of structures for the Aβ42 and Aβ16 isoforms covering 30-50% of the conformational ensembles extracted from the free energy minima was calculated from MD trajectories. The resulting data set of modeled structures includes Aβ42 wild type, isoD7, pS8, D7H, and H6R-Aβ42 and Aβ16 wild type, isoD7, pS8, D7H, and H6R-Aβ16. The representative structures are given in the Supporting Information; they are open for public access. In the study, we also evaluated the differences between the structures of Aβ42 isoforms and speculate on their possible relevance to the known functions. Utilizing several representative structures for a single disordered protein for docking, with their subsequent averaging by conformations, would markedly increase the reliability of docking results.

Structure of amino acid sequence-reversed wtRop protein: insights from atomistic molecular dynamics simulations

This study aims to the investigation of the advantages of designing new proteins presume upon a 'bias' sequence of amino acids, based on the reversed sequence of parent proteins, such as the retro ones. The structural simplicity of wtRop offers a very attractive model system to study these aspects. The current work is based on all-atom Molecular Dynamics (MD) simulations and corresponding experimental evidence on two different types of reversed wtRop protein, one with a fully reversed sequence of amino acids (rRop) and another with a partially reversed sequence (prRop), where only the five residues of the loop region (30ASP-34GLN) were not reversed. The exploration of the structure of the two retro proteins is performed highlighting the similarities and the differences with their parent protein, by employing various measures. Two models have been studied for both reversed proteins, a dimeric and a monomeric with the former one found to be more stable than the latter. Preferable equilibrium structures that the protein molecule can attain are explored, indicating the equilibration pathway. Simulation findings indicate a disruption of the α-helical structure and the appearance of additional secondary structures for both retro proteins. Reduced structural stability compared to their parent protein (wtRop) is also found. A corruption of the hydrophobic core is observed in the dimeric models. Furthermore, the simulations findings are consistent with the experimental characterization of prRop by circular dichroism spectroscopy (CD) which highlights an unstable, highly α-helical protein.Communicated by Ramaswamy H. Sarma.

Identification of Promising Sulfonamide Chalcones as Inhibitors of SARS-CoV-2 3CLpro through Structure-Based Virtual Screening and Experimental Approaches

3CLpro is a viable target for developing antiviral therapies against the coronavirus. With the urgent need to find new possible inhibitors, a structure-based virtual screening approach was developed. This study recognized 75 pharmacologically bioactive compounds from our in-house library of 1052 natural product-based compounds that satisfied drug-likeness criteria and exhibited good bioavailability and membrane permeability. Among these compounds, three promising sulfonamide chalcones were identified by combined theoretical and experimental approaches, with SWC423 being the most suitable representative compound due to its competitive inhibition and low cytotoxicity in Vero E6 cells (EC50 = 0.89 ± 0.32 μM; CC50 = 25.54 ± 1.38 μM; SI = 28.70). The binding and stability of SWC423 in the 3CLpro active site were investigated through all-atom molecular dynamics simulation and fragment molecular orbital calculation, indicating its potential as a 3CLpro inhibitor for further SARS-CoV-2 therapeutic research. These findings suggested that inhibiting 3CLpro with a sulfonamide chalcone such as SWC423 may pave the effective way for developing COVID-19 treatments.

Combining Experiments and Simulations to Examine the Temperature-Dependent Behavior of a Disordered Protein

Intrinsically disordered proteins are a class of proteins that lack stable folded conformations and instead adopt a range of conformations that determine their biochemical functions. The temperature-dependent behavior of such disordered proteins is complex and can vary depending on the specific protein and environment. Here, we have used molecular dynamics simulations and previously published experimental data to investigate the temperature-dependent behavior of histatin 5, a 24-residue-long polypeptide. We examined the hypothesis that histatin 5 undergoes a loss of polyproline II (PPII) structure with increasing temperature, leading to more compact conformations. We found that the conformational ensembles generated by the simulations generally agree with small-angle X-ray scattering data for histatin 5, but show some discrepancies with the hydrodynamic radius as probed by pulsed-field gradient NMR spectroscopy, and with the secondary structure information derived from circular dichroism. We attempted to reconcile these differences by reweighting the conformational ensembles against the scattering and NMR data. By doing so, we were in part able to capture the temperature-dependent behavior of histatin 5 and to link the observed decrease in hydrodynamic radius with increasing temperature to a loss of PPII structure. We were, however, unable to achieve agreement with both the scattering and NMR data within experimental errors. We discuss different possible reasons for this including inaccuracies in the force field, differences in conditions of the NMR and scattering experiments, and issues related to the calculation of the hydrodynamic radius from conformational ensembles. Our study highlights the importance of integrating multiple types of experimental data when modeling conformational ensembles of disordered proteins and how environmental factors such as the temperature influence them.

Prion Protein Octarepeat Domain Forms Transient β-Sheet Structures upon Residue-Specific Binding to Cu(II) and Zn(II) Ions

Misfolding of the cellular prion protein (PrP^C) is associated with the development of fatal neurodegenerative diseases called transmissible spongiform encephalopathies (TSEs). Metal ions appear to play a crucial role in PrP^C misfolding. PrP^C is a combined Cu(II) and Zn(II) metal-binding protein, where the main metal-binding site is located in the octarepeat (OR) region. Thus, the biological function of PrP^C may involve the transport of divalent metal ions across membranes or buffering concentrations of divalent metal ions in the synaptic cleft. Recent studies have shown that an excess of Cu(II) ions can result in PrP^C instability, oligomerization, and/or neuroinflammation. Here, we have used biophysical methods to characterize Cu(II) and Zn(II) binding to the isolated OR region of PrP^C. Circular dichroism (CD) spectroscopy data suggest that the OR domain binds up to four Cu(II) ions or two Zn(II) ions. Binding of the first metal ion results in a structural transition from the polyproline II helix to the β-turn structure, while the binding of additional metal ions induces the formation of β-sheet structures. Fluorescence spectroscopy data indicate that the OR region can bind both Cu(II) and Zn(II) ions at neutral pH, but under acidic conditions, it binds only Cu(II) ions. Molecular dynamics simulations suggest that binding of either metal ion to the OR region results in the formation of β-hairpin structures. As the formation of β-sheet structures can be a first step toward amyloid formation, we propose that high concentrations of either Cu(II) or Zn(II) ions may have a pro-amyloid effect in TSE diseases.

IDP Force Fields Applied to Model PPII-Rich 33-mer Gliadin Peptides

The 33-mer gliadin peptide and its deamidated metabolite, 33-mer DGP, are the immunodominant peptides responsible for the adaptive immune response in celiac disease (CD). CD is a complex autoimmune chronic disorder triggered by gluten ingestion that affects the small intestine and affects ∼1% of the global population. The 33-mers are polyproline II-rich (PPII) and intrinsically disordered peptides (IDPs), whose structures remain elusive. We sampled the conformational ensembles of both 33-mer peptides via molecular dynamics simulations employing two force fields (FFs) (Amber ff03ws and Amber ff99SB-disp) specifically validated for other IDPs. Our results show that both FFs allow the extensive exploration of the conformational landscape, which was not possible with the standard FF GROMOS53A6 reported before. Clustering analysis of the trajectories showed that the five largest clusters (78-88% of the total structures) present elongated, semielongated, and curved conformations in both FFs. Large average radius of gyration and solvent-exposed surfaces characterized these structures. While the structures sampled are similar, the Amber ff99SB-disp trajectories explored folded conformations with a higher probability. In addition, PPII secondary structure was preserved throughout the trajectories (58-73%) together with a non-negligible content of β structures (11-23%), in agreement with previous experimental results. This work represents the initial step in studying further the interaction of these peptides with other biologically relevant molecules, which could lead to finally disclose the molecular events that lead to CD.

WASCO: A Wasserstein-based statistical tool to compare conformational ensembles of intrinsically disordered proteins

The structural investigation of intrinsically disordered proteins (IDPs) requires ensemble models describing the diversity of the conformational states of the molecule. Due to their probabilistic nature, there is a need for new paradigms that understand and treat IDPs from a purely statistical point of view, considering their conformational ensembles as well-defined probability distributions. In this work, we define a conformational ensemble as an ordered set of probability distributions and provide a suitable metric to detect differences between two given ensembles at the residue level, both locally and globally. The underlying geometry of the conformational space is properly integrated, one ensemble being characterized by a set of probability distributions supported on the three-dimensional Euclidean space (for global-scale comparisons) and on the two-dimensional flat torus (for local-scale comparisons). The inherent uncertainty of the data is also taken into account to provide finer estimations of the differences between ensembles. Additionally, an overall distance between ensembles is defined from the differences at the residue level. We illustrate the interest of the approach with several examples of applications for the comparison of conformational ensembles: (i) produced from molecular dynamics (MD) simulations using different force fields, and (ii) before and after refinement with experimental data. We also show the usefulness of the method to assess the convergence of MD simulations, and discuss other potential applications such as in machine-learning-based approaches. The numerical tool has been implemented in Python through easy-to-use Jupyter Notebooks available at https://gitlab.laas.fr/moma/WASCO.

Comparative molecular dynamics simulations of pathogenic and non-pathogenic huntingtin protein monomers and dimers

Polyglutamine expansion at the N-terminus of the huntingtin protein exon 1 (Htt-ex1) is closely associated with a number of neurodegenerative diseases, which result from the aggregation of the increased polyQ repeat. However, the underlying structures and aggregation mechanism are still poorly understood. We performed microsecond-long all-atom molecular dynamics simulations to study the folding and dimerization of Htt-ex1 (about 100 residues) with non-pathogenic and pathogenic polyQ lengths, and uncovered substantial differences. The non-pathogenic monomer adopts a long α-helix that includes most of the polyQ residues, which forms the interaction interface for dimerization, and a PPII-turn-PPII motif in the proline-rich region. In the pathogenic monomer, the polyQ region is disordered, leading to compact structures with many intra-protein interactions and the formation of short β-sheets. Dimerization can proceed via different modes, where those involving the N-terminal headpiece bury more hydrophobic residues and are thus more stable. Moreover, in the pathogenic Htt-ex1 dimers the proline-rich region interacts with the polyQ region, which slows the formation of β-sheets.

Conformational Heterogeneity of RNA Stem-Loop Hairpins Bound to FUS-RNA Recognition Motif with Disordered RGG Tail Revealed by Unbiased Molecular Dynamics Simulations

RNA-protein complexes use diverse binding strategies, ranging from structurally well-defined interfaces to completely disordered regions. Experimental characterization of flexible segments is challenging and can be aided by atomistic molecular dynamics (MD) simulations. Here, we used an extended set of microsecond-scale MD trajectories (400 μs in total) to study two FUS-RNA constructs previously characterized by nuclear magnetic resonance (NMR) spectroscopy. The FUS protein contains a well-structured RNA recognition motif domain followed by a presumably disordered RGG tail that binds RNA stem-loop hairpins. Our simulations not only provide several suggestions complementing the experiments but also reveal major methodological difficulties in studies of such complex RNA-protein interfaces. Despite efforts to stabilize the binding via system-specific force-field adjustments, we have observed progressive distortions of the RNA-protein interface inconsistent with experimental data. We propose that the dynamics is so rich that its converged description is not achievable even upon stabilizing the system. Still, after careful analysis of the trajectories, we have made several suggestions regarding the binding. We identify substates in the RNA loops, which can explain the NMR data. The RGG tail localized in the minor groove remains disordered, sampling countless transient interactions with the RNA. There are long-range couplings among the different elements contributing to the recognition, which can lead to allosteric communication throughout the system. Overall, the RNA-FUS systems form dynamical ensembles that cannot be fully represented by single static structures. Thus, albeit imperfect, MD simulations represent a viable tool to investigate dynamic RNA-protein complexes.

Molecular dynamics simulations of the adsorption of an intrinsically disordered protein: Force field and water model evaluation in comparison with experiments

This study investigates possible structural changes of an intrinsically disordered protein (IDP) when it adsorbs to a solid surface. Experiments on IDPs primarily result in ensemble averages due to their high dynamics. Therefore, molecular dynamics (MD) simulations are crucial for obtaining more detailed information on the atomistic and molecular levels. An evaluation of seven different force field and water model combinations have been applied: (A) CHARMM36IDPSFF + CHARMM-modified TIP3P, (B) CHARMM36IDPSFF + TIP4P-D, (C) CHARMM36m + CHARMM-modified TIP3P, (D) AMBER99SB-ILDN + TIP3P, (E) AMBER99SB-ILDN + TIP4P-D, (F) AMBERff03ws + TIP4P/2005, and (G) AMBER99SB-disp + disp-water. The results have been qualitatively compared with those of small-angle X-ray scattering, synchrotron radiation circular dichroism spectroscopy, and attenuated total reflectance Fourier transform infrared spectroscopy. The model IDP corresponds to the first 33 amino acids of the N-terminal of the magnesium transporter A (MgtA) and is denoted as KEIF. With a net charge of +3, KEIF is found to adsorb to the anionic synthetic clay mineral Laponite^® due to the increase in entropy from the concomitant release of counterions from the surface. The experimental results show that the peptide is largely disordered with a random coil conformation, whereas the helical content (α- and/or 3₁₀-helices) increased upon adsorption. MD simulations corroborate these findings and further reveal an increase in polyproline II helices and an extension of the peptide conformation in the adsorbed state. In addition, the simulations provided atomistic resolution of the adsorbed ensemble of structures, where the arginine residues had a high propensity to form hydrogen bonds with the surface. Simulations B, E, and G showed significantly better agreement with experiments than the other simulations. Particularly noteworthy is the discovery that B and E with TIP4P-D water had superior performance to their corresponding simulations A and D with TIP3P-type water. Thus, this study shows the importance of the water model when simulating IDPs and has also provided an insight into the structural changes of surface-active IDPs induced by adsorption, which may play an important role in their function.

Simulating Polyproline II-Helix-Rich Peptides with the Latest Kirkwood-Buff Force Field: A Direct Comparison with AMBER and CHARMM

We simulated the dynamics of a set of peptides characterized by ensembles rich in PPII-helical content, to assess the ability of the most recent Kirkwood-Buff force field (KBFF20) to sample this conformational peculiarity. KBFF has been previously shown to capably reproduce experimental dimensions of disordered proteins, while being limited in confidently sampling structured proteins. Further development of the force field bridged this gap. It is however still unknown what are the main differences between KBFF and AMBER/CHARMM force fields. A direct comparison is now possible as both AMBER/CHARMM force fields have been used to sample peptides rich in PPII-helical content. We found that KBFF20 samples' PPII-helical content qualitatively matches both AMBER and CHARMM force fields, with the main difference being the KBFF ability to populate the α_R region of the Ramachandran plot in the set of simulated peptides. Overall, KBFF20 is a well-balanced force field, able to sample the dynamics of both structured and unstructured proteins.

Conformational ensembles of intrinsically disordered proteins and flexible multidomain proteins

Intrinsically disordered proteins (IDPs) and multidomain proteins with flexible linkers show a high level of structural heterogeneity and are best described by ensembles consisting of multiple conformations with associated thermodynamic weights. Determining conformational ensembles usually involves the integration of biophysical experiments and computational models. In this review, we discuss current approaches to determine conformational ensembles of IDPs and multidomain proteins, including the choice of biophysical experiments, computational models used to sample protein conformations, models to calculate experimental observables from protein structure, and methods to refine ensembles against experimental data. We also provide examples of recent applications of integrative conformational ensemble determination to study IDPs and multidomain proteins and suggest future directions for research in the field.

Self-Diffusive Properties of the Intrinsically Disordered Protein Histatin 5 and the Impact of Crowding Thereon: A Combined Neutron Spectroscopy and Molecular Dynamics Simulation Study

Intrinsically disordered proteins (IDPs) are proteins that, in comparison with globular/structured proteins, lack a distinct tertiary structure. Here, we use the model IDP, Histatin 5, for studying its dynamical properties under self-crowding conditions with quasi-elastic neutron scattering in combination with full atomistic molecular dynamics (MD) simulations. The aim is to determine the effects of crowding on the center-of-mass diffusion as well as the internal diffusive behavior. The diffusion was found to decrease significantly, which we hypothesize can be attributed to some degree of aggregation at higher protein concentrations, (≥100 mg/mL), as indicated by recent small-angle X-ray scattering studies. Temperature effects are also considered and found to, largely, follow Stokes–Einstein behavior. Simple geometric considerations fail to accurately predict the rates of diffusion, while simulations show semiquantitative agreement with experiments, dependent on assumptions of the ratio between translational and rotational diffusion. A scaling law that previously was found to successfully describe the behavior of globular proteins was found to be inadequate for the IDP, Histatin 5. Analysis of the MD simulations show that the width of the distribution with respect to diffusion is not a simplistic mirroring of the distribution of radius of gyration, hence, displaying the particular features of IDPs that need to be accounted for.

Changes in the Local Conformational States Caused by Simple Na+ and K+ Ions in Polyelectrolyte Simulations: Comparison of Seven Force Fields with and without NBFIX and ECC Corrections

Electrostatic interactions have a determining role in the conformational and dynamic behavior of polyelectrolyte molecules. In this study, anionic polyelectrolyte molecules, poly(glutamic acid) (PGA) and poly(aspartic acid) (PASA), in a water solution with the most commonly used K+ or Na+ counterions, were investigated using atomistic molecular dynamics (MD) simulations. We performed a comparison of seven popular force fields, namely AMBER99SB-ILDN, AMBER14SB, AMBER-FB15, CHARMM22*, CHARMM27, CHARMM36m and OPLS-AA/L, both with their native parameters and using two common corrections for overbinding of ions, the non-bonded fix (NBFIX), and electronic continuum corrections (ECC). These corrections were originally introduced to correct for the often-reported problem concerning the overbinding of ions to the charged groups of polyelectrolytes. In this work, a comparison of the simulation results with existing experimental data revealed several differences between the investigated force fields. The data from these simulations and comparisons with previous experimental data were then used to determine the limitations and strengths of these force fields in the context of the structural and dynamic properties of anionic polyamino acids. Physical properties, such as molecular sizes, local structure, and dynamics, were studied using two types of common counterions, namely potassium and sodium. The results show that, in some cases, both the macroion size and dynamics depend strongly on the models (parameters) for the counterions due to strong overbinding of the ions and charged side chain groups. The local structures and dynamics are more sensitive to dihedral angle parameterization, resulting in a preference for defined monomer conformations and the type of correction used. We also provide recommendations based on the results.