Assignment of PolyProline II conformation and analysis of sequence--structure relationship

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.

An agnostic analysis of the human AlphaFold2 proteome using local protein conformations

Knowledge of the 3D structure of proteins is a valuable asset for understanding their precise biological mechanisms. However, the cost of production of 3D structures and experimental difficulties limit their obtaining. The proposal of 3D structural models is consequently an appealing alternative. The release of the AlphaFold Deep Learning approach has revolutionized the field. The recent near-complete human proteome proposal makes it possible to analyse large amounts of data and evaluate the results of the approach in greater depth. The 3D human proteome was thus analysed in light of the classic secondary structures, and many less-used protein local conformations (PolyProline II helices, type of γ-turns, of β-turns and of β-bulges, curvature of the helices, and a structural alphabet). Without questioning the global quality of the approach, this analysis highlights certain local conformations, which maybe poorly predicted and they could therefore be better addressed.

Systemic structural analysis of alterations reveals a common structural basis of driver mutations in cancer

A major effort in cancer research is to organize the complexities of the disease into fundamental traits. Despite conceptual progress in the last decades and the synthesis of hallmark features, no organizing principles governing cancer beyond cellular features exist. We analyzed experimentally determined structures harboring the most significant and prevalent driver missense mutations in human cancer, covering 73% (n = 168178) of the Catalog of Somatic Mutation in Cancer tumor samples (COSMIC). The results reveal that a single structural element-κ-helix (polyproline II helix)-lies at the core of driver point mutations, with significant enrichment in all major anatomical sites, suggesting that a small number of molecular traits are shared by most and perhaps all types of cancer. Thus, we uncovered the lowest possible level of organization at which carcinogenesis takes place at the protein level. This framework provides an initial scheme for a mechanistic understanding underlying the development of tumors and pinpoints key vulnerabilities.

Connection between MHC class II binding and aggregation propensity: The antigenic peptide 10 of Paracoccidioides brasiliensis as a benchmark study

The aggregation of epitopes that are also able to bind major histocompatibility complex (MHC) alleles raises questions around the potential connection between the formation of epitope aggregates and their affinities to MHC receptors. We first performed a general bioinformatic assessment over a public dataset of MHC class II epitopes, finding that higher experimental binding correlates with higher aggregation-propensity predictors. We then focused on the case of P10, an epitope used as a vaccine candidate against Paracoccidioides brasiliensis that aggregates into amyloid fibrils. We used a computational protocol to design variants of the P10 epitope to study the connection between the binding stabilities towards human MHC class II alleles and their aggregation propensities. The binding of the designed variants was tested experimentally, as well as their aggregation capacity. High-affinity MHC class II binders in vitro were more disposed to aggregate forming amyloid fibrils capable of binding Thioflavin T and congo red, while low affinity MHC class II binders remained soluble or formed rare amorphous aggregates. This study shows a possible connection between the aggregation propensity of an epitope and its affinity for the MHC class II cleft.

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.

A Perspective on the (Rise and Fall of) Protein β-Turns

The β-turn is the third defined secondary structure after the α-helix and the β-sheet. The β-turns were described more than 50 years ago and account for more than 20% of protein residues. Nonetheless, they are often overlooked or even misunderstood. This poor knowledge of these local protein conformations is due to various factors, causes that I discuss here. For example, confusion still exists about the assignment of these local protein structures, their overlaps with other structures, the potential absence of a stabilizing hydrogen bond, the numerous types of β-turns and the software's difficulty in assigning or visualizing them. I also propose some ideas to potentially/partially remedy this and present why β-turns can still be helpful, even in the AlphaFold 2 era.

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.

Shaking the β-Bulges

β-bulges are irregularities inside the β-sheets. They represent more than 3 percent of the protein residues, i.e., they are as frequent as 3.₁₀ helices. In terms of evolution, β-bulges are not more conserved than any other local protein conformations within homologous protein structures. In a first of its kind study, we have investigated the dynamical behaviour of β-bulges using the largest known set of protein molecular dynamics simulations. We observed that more than 50 percent of the existing β-bulges in protein crystal structures remained stable during dynamics while more than1/6^th were not stable at all and disappeared entirely. Surprisingly, 1.1 percent of β-bulges that appeared remained stable. β-bulges have been categorized in different subtypes. The most common β-bulges' types are the smallest insertion in β-strands (namely AC and AG); they are found as stable as the whole β-bulges dataset. Low occurring types (namely PC and AS), that have the largest insertions, are significantly more stable than expected. Thus, this pioneer study allowed to precisely quantify the stability of the β-bulges, demonstrating their structural robustness, with few unexpected cases raising structural questions.

Deciphering the Backbone Noncovalent Interactions that Stabilize Polyproline II Conformation and Reduce cis Proline Abundance in Polyproline Tracts

Proline (Pro) has a higher propensity to adopt cis amide geometry than the other natural amino acids, and a poly-Pro (poly-P) tract can adopt either a polyproline I (PPI, all cis amide) or a polyproline II (PPII, all trans amide) helical conformation. Recent studies have revealed a reduced abundance of cis amide geometry among the inner Pro residues of a poly-P tract. However, the forces that stabilize the polyproline helices and the reason for the higher trans amide propensity of the inner Pro residues of a poly-P tract are poorly understood. Herein, we have studied both Pro and non-Pro PPII helical sequences and identified the backbone noncovalent interactions that are crucial to the higher stability of the trans Pro-amide geometry and the preference for a PPII helical conformation. We show the presence of reciprocal CO···CO interactions that extend over the whole PPII helical region. Interestingly, the CO···CO interactions strengthen with the increase in the PPII helical chain length and the inner CO groups possess stronger CO···CO interactions, which could explain the reduced cis abundance of the inner Pro residues of a poly-P tract. We also identified a much stronger (∼0.9 kcal·mol^-1) n_O → σ*_Cα-Cβ interaction between the N-terminal CO oxygen lone pair and the antibonding orbital (σ*) of their C_α-C_β bonds. As the n_O → σ*_Cα-Cβ interaction is possible only in the trans isomers of Pro, this interaction should be crucial for the stabilization of a PPII helix. Finally, an unusual n_N(amide) → σ*_C-N interaction (∼0.3 kcal·mol^-1) was observed between the peptidic nitrogen lone pair (n_N) and the antibonding orbital (σ*_C-N) of the subsequent C-terminal peptide C-N bond. We propose a cumulative effect of these interactions in the stabilization of a PPII helix.

An Unbound Proline-Rich Signaling Peptide Frequently Samples Cis Conformations in Gaussian Accelerated Molecular Dynamics Simulations

Disordered proline-rich motifs are common across the proteomes of many species and are often involved in protein-protein interactions. Proline is a unique amino acid due to the covalent bond between the backbone nitrogen and the proline side chain. The resulting five-membered ring allows proline to sample the cis state about its peptide bond, which other residues cannot do as readily. Because proline-rich disordered sequences exist as ensembles that likely include structures with the proline peptide bond in cis, a robust methodology to accurately account for these conformations in the overall ensemble is crucial. Observing the cis conformations of proline in a disordered sequence is challenging both experimentally and computationally. Nitrogen-hydrogen NMR spectroscopy cannot directly observe proline residues, which lack an amide bond, and computational methods struggle to overcome the large kinetic barrier between the cis and trans states, since isomerization usually occurs on the order of seconds. In the current work, Gaussian accelerated molecular dynamics was used to overcome this free energy barrier and simulate proline isomerization in a tetrapeptide (KPTP) and in the 12-residue proline-rich SH3 binding peptide, ArkA. We found that Gaussian accelerated molecular dynamics, when combined with a lowered peptide bond dihedral angle potential energy barrier (15 kcal/mol), allowed sufficient sampling of the proline cis and trans states on a microsecond timescale. All ArkA prolines spend a significant fraction of time in cis, leading to a more compact ensemble with less polyproline II helix structure than an ArkA ensemble with all peptide bonds in trans. The ensemble containing cis prolines also matches more closely to in vitro circular dichroism data than the all-trans ensemble. The ability of the ArkA prolines to isomerize likely affects the peptide's ability to bind its partner SH3 domain, and should be studied further. This is the first molecular dynamics simulation study of proline isomerization in a biologically relevant proline-rich sequence that we know of, and a similar protocol could be applied to study multi-proline isomerization in other proline-containing proteins to improve conformational diversity and agreement with in vitro data.

Expanding the Disorder-Function Paradigm in the C-Terminal Tails of Erbbs

ErbBs are receptor tyrosine kinases involved not only in development, but also in a wide variety of diseases, particularly cancer. Their extracellular, transmembrane, juxtamembrane, and kinase folded domains were described extensively over the past 20 years, structurally and functionally. However, their whole C-terminal tails (CTs) following the kinase domain were only described at atomic resolution in the last 4 years. They were shown to be intrinsically disordered. The CTs are known to be tyrosine-phosphorylated when the activated homo- or hetero-dimers of ErbBs are formed. Their phosphorylation triggers interaction with phosphotyrosine binding (PTB) or Src Homology 2 (SH2) domains and activates several signaling pathways controling cellular motility, proliferation, adhesion, and apoptosis. Beyond this passive role of phosphorylated domain and site display for partners, recent structural and function studies unveiled active roles in regulation of phosphorylation and interaction: the CT regulates activity of the kinase domain; different phosphorylation states have different compaction levels, potentially modulating the succession of phosphorylation events; and prolines have an important role in structure, dynamics, and possibly regulatory interactions. Here, we review both the canonical role of the disordered CT domains of ErbBs as phosphotyrosine display domains and the recent findings that expand the known range of their regulation functions linked to specific structural and dynamic features.

The Effect of Multisite Phosphorylation on the Conformational Properties of Intrinsically Disordered Proteins

Intrinsically disordered proteins are involved in many biological processes such as signaling, regulation, and recognition. A common strategy to regulate their function is through phosphorylation, as it can induce changes in conformation, dynamics, and interactions with binding partners. Although phosphorylated intrinsically disordered proteins have received increased attention in recent years, a full understanding of the conformational and structural implications of phosphorylation has not yet been achieved. Here, we present all-atom molecular dynamics simulations of five disordered peptides originated from tau, statherin, and β-casein, in both phosphorylated and non-phosphorylated state, to compare changes in global dimensions and structural elements, in an attempt to gain more insight into the controlling factors. The changes are in qualitative agreement with experimental data, and we observe that the net charge is not enough to predict the impact of phosphorylation on the global dimensions. Instead, the distribution of phosphorylated and positively charged residues throughout the sequence has great impact due to the formation of salt bridges. In statherin, a preference for arginine-phosphoserine interaction over arginine-tyrosine accounts for a global expansion, despite a local contraction of the phosphorylated region, which implies that also non-charged residues can influence the effect of phosphorylation.

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

Five peptides previously suggested to possess polyproline II (PPII) structure have here been investigated by using atomistic molecular dynamics simulations to compare how well four different force fields known for simulating intrinsically disordered proteins relatively well (Amber ff99SB-disp, Amber ff99SB-ILDN, CHARM36IDPSFF, and CHARMM36m) can capture this secondary structure element. The results revealed that all force fields sample PPII structures but to different extents and with different propensities toward other secondary structure elements, in particular, the β-sheet and "random coils". A cluster analysis of the simulations of histatin 5 also revealed that the conformational ensembles of the force fields are quite different. We compared the simulations to circular dichroism and nuclear magnetic resonance spectroscopy experiments and conclude that further experiments and methods for interpreting them are needed to assess the accuracy of force fields in determining PPII structure.

Molecular Dynamics Simulations of Phosphorylated Intrinsically Disordered Proteins: A Force Field Comparison

Phosphorylation is a common post-translational modification among intrinsically disordered proteins and regions, which helps regulate function by changing the protein conformations, dynamics, and interactions with binding partners. To fully comprehend the effects of phosphorylation, computer simulations are a helpful tool, although they are dependent on the accuracy of the force field used. Here, we compared the conformational ensembles produced by Amber ff99SB-ILDN+TIP4P-D and CHARMM36m, for four phosphorylated disordered peptides ranging in length from 14-43 residues. CHARMM36m consistently produced more compact conformations with a higher content of bends, mainly due to more stable salt bridges. Based on comparisons with experimental size estimates for the shortest and longest peptide, CHARMM36m appeared to overestimate the compactness. The difference between the force fields was largest for the peptide showing the greatest separation between positively charged and phosphorylated residues, in line with the importance of charge distribution. For this peptide, the conformational ensemble did not change significantly upon increasing the ionic strength from 0 mM to 150 mM, despite a reduction of the salt-bridging probability in the CHARMM36m simulations, implying that salt concentration has negligible effects in this study.

Structural basis of SARS-CoV-2 spike protein induced by ACE2

Motivation

The recent emergence of the novel SARS-coronavirus 2 (SARS-CoV-2) and its international spread pose a global health emergency. The spike (S) glycoprotein binds ACE2 and promotes SARS-CoV-2 entry into host cells. The trimeric S protein binds the receptor using the receptor-binding domain (RBD) causing conformational changes in S protein that allow priming by host cell proteases. Unraveling the dynamic structural features used by SARS-CoV-2 for entry might provide insights into viral transmission and reveal novel therapeutic targets. Using structures determined by X-ray crystallography and cryo-EM, we performed structural analysis and atomic comparisons of the different conformational states adopted by the SARS-CoV-2-RBD.

Results

Here, we determined the key structural components induced by the receptor and characterized their intramolecular interactions. We show that κ-helix (polyproline-II) is a predominant structure in the binding interface and in facilitating the conversion to the active form of the S protein. We demonstrate a series of conversions between switch-like κ-helix and β-strand, and conformational variations in a set of short α-helices which affect the hinge region. These conformational changes lead to an alternating pattern in conserved disulfide bond configurations positioned at the hinge, indicating a possible disulfide exchange, an important allosteric switch implicated in viral entry of various viruses, including HIV and murine coronavirus. The structural information presented herein enables to inspect and understand the important dynamic features of SARS-CoV-2-RBD and propose a novel potential therapeutic strategy to block viral entry. Overall, this study provides guidance for the design and optimization of structure-based intervention strategies that target SARS-CoV-2.

Availability

We have implemented the proposed methods in an R package freely available at https://github.com/Grantlab/bio3d

Supplementary information

Supplementary data are available at Bioinformatics online.

PSIQUE: Protein Secondary Structure Identification on the Basis of Quaternions and Electronic Structure Calculations

The secondary structure is important in protein structure analysis, classification, and modeling. We have developed a novel method for secondary structure assignment, termed PSIQUE, based on the potential energy surface (PES) of polyalanine obtained using an infinitely long chain model and density functional theory calculations. First, uniform protein segments are determined in terms of a difference of quaternions between neighboring amino acids along the protein backbone. Then, the identification of the secondary structure motifs is carried out based on the minima found in the PES. PSIQUE shows good agreement with other secondary structure assignment methods. However, it provides better discrimination of subtle secondary structures (e.g., helix types) and termini and produces more uniform segments while also accounting for local distortions. Overall, PSIQUE provides a precise and reliable assignment of secondary structures, so it should be helpful for the detailed characterization of the protein structure.

Structural and dynamic characterization of the C-terminal tail of ErbB2: Disordered but not random

ErbB2 (or HER2) is a receptor tyrosine kinase overexpressed in some breast cancers and associated with poor prognosis. Treatments targeting the receptor extracellular and kinase domains have greatly improved disease outcome in the last 20 years. In parallel, the structures of these domains have been described, enabling better mechanistic understanding of the receptor function and targeted inhibition. However, the ErbB2 disordered C-terminal cytoplasmic tail (CtErbB2) remains very poorly characterized in terms of structure, dynamics, and detailed functional mechanism. Yet, it is where signal transduction is triggered via phosphorylation of tyrosine residues and carried out via interaction with adaptor proteins. Here, we report the first description, to our knowledge, of the ErbB2 disordered tail at atomic resolution using NMR, complemented by small-angle x-ray scattering. We show that although no part of CtErbB2 has any fully populated secondary or tertiary structure, it contains several transient α-helices and numerous transient polyproline II helices, populated up to 20 and 40%, respectively, and low but significant compaction. The presence of some structural elements suggests, along the lines of the results obtained for EGFR (ErbB1), that they may have a functional role in ErbB2's autoregulation processes. In addition, the transient formation of polyproline II helices is compliant with previously suggested interactions with SH3 domains. All in all, our in-depth structural study opens perspectives in the mechanistic understanding of ErbB2.

SCOT: Rethinking the classification of secondary structure elements

MOTIVATION

Secondary structure classification is one of the most important issues in structure-based analyses due to its impact on secondary structure prediction, structural alignment and protein visualization. There are still open challenges concerning helix and sheet assignments which are currently not addressed by a single multi-purpose software.

RESULTS

We introduce SCOT (Secondary structure Classification On Turns) as a novel secondary structure element assignment software which supports the assignment of turns, right-handed α-, 310- and π-helices, left-handed α- and 310-helices, 2.27- and polyproline II helices, β-sheets and kinks. We demonstrate that the introduction of helix Purity values enables a clear differentiation between helix classes. SCOT's unique strengths are highlighted by comparing it to six state-of-the-art methods (DSSP, STRIDE, ASSP, SEGNO, DISICL and SHAFT). The assignment approaches were compared concerning geometric consistency, protein structure quality and flexibility dependency and their impact on secondary structure element-based structural alignments. We show that only SCOT's combination of hydrogen bonds, geometric criteria and dihedral angles enables robust assignments independent of the structure quality and flexibility. We demonstrate that this combination and the elaborate kink detection lead to SCOT's clear superiority for protein alignments. As the resulting helices and strands are provided in a PDB conform output format, they can immediately be used for structure alignment algorithms. Taken together, the application of our new method and the straight-forward visualization using the accompanying PyMOL scripts enable the comprehensive analysis of regular backbone geometries in proteins.

AVAILABILITY AND IMPLEMENTATION

https://this-group.rocks.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Impact of protein dynamics on secondary structure prediction

Protein 3D structures support their biological functions. As the number of protein structures is negligible in regards to the number of available protein sequences, prediction methodologies relying only on protein sequences are essential tools. In this field, protein secondary structure prediction (PSSPs) is a mature area, and is considered to have reached a plateau. Nonetheless, proteins are highly dynamical macromolecules, a property that could impact the PSSP methods. Indeed, in a previous study, the stability of local protein conformations was evaluated demonstrating that some regions easily changed to another type of secondary structure. The protein sequences of this dataset were used by PSSPs and their results compared to molecular dynamics to investigate their potential impact on the quality of the secondary structure prediction. Interestingly, a direct link is observed between the quality of the prediction and the stability of the assignment to the secondary structure state. The more stable a local protein conformation is, the better the prediction will be. The secondary structure assignment not taken from the crystallized structures but from the conformations observed during the dynamics slightly increase the quality of the secondary structure prediction. These results show that evaluation of PSSPs can be done differently, but also that the notion of dynamics can be included in development of PSSPs and other approaches such as de novo approaches.

A disordered encounter complex is central to the yeast Abp1p SH3 domain binding pathway

Protein-protein interactions are involved in a wide range of cellular processes. These interactions often involve intrinsically disordered proteins (IDPs) and protein binding domains. However, the details of IDP binding pathways are hard to characterize using experimental approaches, which can rarely capture intermediate states present at low populations. SH3 domains are common protein interaction domains that typically bind proline-rich disordered segments and are involved in cell signaling, regulation, and assembly. We hypothesized, given the flexibility of SH3 binding peptides, that their binding pathways include multiple steps important for function. Molecular dynamics simulations were used to characterize the steps of binding between the yeast Abp1p SH3 domain (AbpSH3) and a proline-rich IDP, ArkA. Before binding, the N-terminal segment 1 of ArkA is pre-structured and adopts a polyproline II helix, while segment 2 of ArkA (C-terminal) adopts a 310 helix, but is far less structured than segment 1. As segment 2 interacts with AbpSH3, it becomes more structured, but retains flexibility even in the fully engaged state. Binding simulations reveal that ArkA enters a flexible encounter complex before forming the fully engaged bound complex. In the encounter complex, transient nonspecific hydrophobic and long-range electrostatic contacts form between ArkA and the binding surface of SH3. The encounter complex ensemble includes conformations with segment 1 in both the forward and reverse orientation, suggesting that segment 2 may play a role in stabilizing the correct binding orientation. While the encounter complex forms quickly, the slow step of binding is the transition from the disordered encounter ensemble to the fully engaged state. In this transition, ArkA makes specific contacts with AbpSH3 and buries more hydrophobic surface. Simulating the binding between ApbSH3 and ArkA provides insight into the role of encounter complex intermediates and nonnative hydrophobic interactions for other SH3 domains and IDPs in general.

Sequence-Dependent Correlated Segments in the Intrinsically Disordered Region of ChiZ

How sequences of intrinsically disordered proteins (IDPs) code for their conformational dynamics is poorly understood. Here, we combined NMR spectroscopy, small-angle X-ray scattering (SAXS), and molecular dynamics (MD) simulations to characterize the conformations and dynamics of ChiZ1-64. MD simulations, first validated by SAXS and secondary chemical shift data, found scant α-helices or β-strands but a considerable propensity for polyproline II (PPII) torsion angles. Importantly, several blocks of residues (e.g., 11–29) emerge as “correlated segments”, identified by their frequent formation of PPII stretches, salt bridges, cation-π interactions, and sidechain-backbone hydrogen bonds. NMR relaxation experiments showed non-uniform transverse relaxation rates (R₂s) and nuclear Overhauser enhancements (NOEs) along the sequence (e.g., high R₂s and NOEs for residues 11–14 and 23–28). MD simulations further revealed that the extent of segmental correlation is sequence-dependent; segments where internal interactions are more prevalent manifest elevated “collective” motions on the 5–10 ns timescale and suppressed local motions on the sub-ns timescale. Amide proton exchange rates provides corroboration, with residues in the most correlated segment exhibiting the highest protection factors. We propose the correlated segment as a defining feature for the conformations and dynamics of IDPs.

κ-helix and the helical lock and key model: a pivotal way of looking at polyproline II

Motivation

Polyproline II (PPII) is a common conformation, comparable to α-helix and β-sheet. PPII, recently termed with a more generic name—κ-helix, adopts a left-handed structure with 3-fold rotational symmetry. Lately, a new type of binding mechanism—the helical lock and key model was introduced in SH3-domain complexes, where the interaction is characterized by a sliding helical pattern. However, whether this binding mechanism is unique only to SH3 domains is unreported.

Results

Here, we show that the helical binding pattern is a universal feature of the κ-helix conformation, present within all the major target families—SH3, WW, profilin, MHC-II, EVH1 and GYF domains. Based on a geometric analysis of 255 experimentally solved structures, we found that they are characterized by a distinctive rotational angle along the helical axis. Furthermore, we found that the range of helical pitch varies between different protein domains or peptide orientations and that the interaction is also represented by a rotational displacement mimicking helical motion. The discovery of rotational interactions as a mechanism, reveals a new dimension in the realm of protein–protein interactions, which introduces a new layer of information encoded by the helical conformation. Due to the extensive involvement of the conformation in functional interactions, we anticipate our model to expand the current molecular understanding of the relationship between protein structure and function.

Availability and implementation

We have implemented the proposed methods in an R package freely available at https://github.com/Grantlab/bio3d.

Supplementary information

Supplementary data are available at Bioinformatics online.

Prediction of polyproline II secondary structure propensity in proteins

Background: The polyproline II helix (PPIIH) is an extended protein left-handed secondary structure that usually but not necessarily involves prolines. Short PPIIHs are frequently, but not exclusively, found in disordered protein regions, where they may interact with peptide-binding domains. However, no readily usable software is available to predict this state. Results: We developed PPIIPRED to predict polyproline II helix secondary structure from protein sequences, using bidirectional recurrent neural networks trained on known three-dimensional structures with dihedral angle filtering. The performance of the method was evaluated in an external validation set. In addition to proline, PPIIPRED favours amino acids whose side chains extend from the backbone (Leu, Met, Lys, Arg, Glu, Gln), as well as Ala and Val. Utility for individual residue predictions is restricted by the rarity of the PPIIH feature compared to structurally common features. Conclusion: The software, available at http://bioware.ucd.ie/PPIIPRED, is useful in large-scale studies, such as evolutionary analyses of PPIIH, or computationally reducing large datasets of candidate binding peptides for further experimental validation.

Polyproline II Helix as a Recognition Motif of Plant Peptide Hormones and Flagellin Peptide flg22

Background:

Plant peptide hormones play a crucial role in plant growth and development. A group of these peptide hormones are signaling peptides with 5 - 23 amino acids. Flagellin peptide (flg22) also elicits an immune response in plants. The functions are expressed through recognition of the peptide hormones and flg22. This recognition relies on membrane localized receptor kinases with extracellular leucine rich repeats (LRR-RKs). The structures of plant peptide hormones - AtPep1, IDA, IDL1, RGFs 1- 3, TDIF/CLE41 - and of flg22 complexed with LRR domains of corresponding LRRRKs and co-receptors SERKs have been determined. However, their structures are well not analyzed and characterized in detail. The structures of PIP, CEP, CIF, and HypSys are still unknown.

Objective:

Our motivation is to clarify structural features of these plant, small peptides and Flg22 in their bound states.

Methods:

In this article, we performed secondary structure assignments and HELFIT analyses (calculating helix axis, pitch, radius, residues per turn, and handedness) based on the atomic coordinates from the crystal structures of AtPep1, IDA, IDL1, RGFs 1- 3, TDIF/CLE41 - and of flg22. We also performed sequence analysis of the families of PIP, CEP, CIF, and HypSys in order to predict their secondary structures.

Results:

Following AtPep1 with 23 residues adopts two left handed polyproline helices (PPIIs) with six and four residues. IDA, IDL1, RGFs 1 - 2, and TDIF/CLE41 with 12 or 13 residues adopt a four residue PPII; RGF3 adopts two PPIIs with four residues. Flg22 with 22 residues also adopts a six residue PPII. The other peptide hormones – PIP, CEP, CIF, and HypSys – that are rich in proline or hydroxyproline presumably prefer PPII.

Conclusion:

The present analysis indicates that PPII helix in the plant small peptide hormones and in flg22 is crucial for recognition of the LRR domains in receptors.

Membrane-associated mucins of the ocular surface: New genes, new protein functions and new biological roles in human and mouse

The mucosal glycocalyx of the ocular surface constitutes the point of interaction between the tear film and the apical epithelial cells. Membrane-associated mucins (MAMs) are the defining molecules of the glycocalyx in all mucosal epithelia. Long recognized for their biophysical properties of hydration, lubrication, anti-adhesion and repulsion, MAMs maintain the wet ocular surface, lubricate the blink, stabilize the tear film and create a physical barrier to the outside world. However, it is increasingly appreciated that MAMs also function as cell surface receptors that transduce information from the outside to the inside of the cell. A number of excellent review articles have provided perspective on the field as it has progressed since 1987, when molecular cloning of the first MAM was reported. The current article provides an update for the ocular surface, placing it into the broad context of findings made in other organ systems, and including new genes, new protein functions and new biological roles. We discuss the epithelial tissue-equivalent with mucosal differentiation, the key model system making these advances possible. In addition, we make the first systematic comparison of MAMs in human and mouse, establishing the basis for using knockout mice for investigations with the complexity of an in vivo system. Lastly, we discuss findings from human genetics/genomics, which are providing clues to new MAM roles previously unimagined. Taken together, this information allows us to generate hypotheses for the next stage of investigation to expand our knowledge of MAM function in intracellular signaling and roles unique to the ocular surface.

Position β57 of I-Ag7 controls early anti-insulin responses in NOD mice, linking an MHC susceptibility allele to type 1 diabetes onset

The class II region of the major histocompatibility complex (MHC) locus is the main contributor to the genetic susceptibility to type 1 diabetes (T1D). The loss of an aspartic acid at position 57 of diabetogenic HLA-DQβ chains supports this association; this single amino acid change influences how TCRs recognize peptides in the context of HLA-DQ8 and I-Ag7 using a mechanism termed the P9 switch. Here, we built register-specific insulin peptide MHC tetramers to examine CD4+ T cell responses to Ins12-20 and Ins13-21 peptides during the early prediabetic phase of disease in nonobese diabetic (NOD) mice. A single-cell analysis of anti-insulin CD4+ T cells performed in 6- and 12-week-old NOD mice revealed tissue-specific gene expression signatures. TCR signaling and clonal expansion were found only in the islets of Langerhans and produced either classical TH1 differentiation or an unusual Treg phenotype, independent of TCR usage. The early phase of the anti-insulin response was dominated by T cells specific for Ins12-20, the register that supports a P9 switch mode of recognition. The presence of the P9 switch was demonstrated by TCR sequencing, reexpression, mutagenesis, and functional testing of TCRαβ pairs in vitro. Genetic correction of the I-Aβ57 mutation in NOD mice resulted in the disappearance of D/E residues in the CDR3β of anti-Ins12-20 T cells. These results provide a mechanistic molecular explanation that links the characteristic MHC class II polymorphism of T1D with the recognition of islet autoantigens and disease onset.

Discrete analyses of protein dynamics

Protein structures are highly dynamic macromolecules. This dynamics is often analysed through experimental and/or computational methods only for an isolated or a limited number of proteins. Here, we explore large-scale protein dynamics simulation to observe dynamics of local protein conformations using different perspectives. We analysed molecular dynamics to investigate protein flexibility locally, using classical approaches such as RMSf, solvent accessibility, but also innovative approaches such as local entropy. First, we focussed on classical secondary structures and analysed specifically how β-strand, β-turns, and bends evolve during molecular simulations. We underlined interesting specific bias between β-turns and bends, which are considered as the same category, while their dynamics show differences. Second, we used a structural alphabet that is able to approximate every part of the protein structures conformations, namely protein blocks (PBs) to analyse (i) how each initial local protein conformations evolve during dynamics and (ii) if some exchange can exist among these PBs. Interestingly, the results are largely complex than simple regular/rigid and coil/flexible exchange. AbbreviationsN_eqnumber of equivalentPBProtein BlocksPDBProtein DataBankRMSfroot mean square fluctuationsCommunicated by Ramaswamy H. Sarma.

Predicting the Affinity of Peptides to Major Histocompatibility Complex Class II by Scoring Molecular Dynamics Simulations

Predicting the binding affinity of peptides able to interact with major histocompatibility complex (MHC) molecules is a priority for researchers working in the identification of novel vaccines candidates. Most available approaches are based on the analysis of the sequence of peptides of known experimental affinity. However, for MHC class II receptors, these approaches are not very accurate, due to the intrinsic flexibility of the complex. To overcome these limitations, we propose to estimate the binding affinity of peptides bound to an MHC class II by averaging the score of the configurations from finite-temperature molecular dynamics simulations. The score is estimated for 18 different scoring functions, and we explored the optimal manner for combining them. To test the predictions, we considered eight peptides of known binding affinity. We found that six scoring functions correlate with the experimental ranking of the peptides significantly better than the others. We then assessed a set of techniques for combining the scoring functions by linear regression and logistic regression. We obtained a maximum accuracy of 82% for the predicted sign of the binding affinity using a logistic regression with optimized weights. These results are potentially useful to improve the reliability of in silico protocols to design high-affinity binding peptides for MHC class II receptors.

Super Secondary Structure Consisting of a Polyproline II Helix and a β-Turn in Leucine Rich Repeats in Bacterial Type III Secretion System Effectors

Leucine rich repeats (LRRs) are present in over 100,000 proteins from viruses to eukaryotes. The LRRs are 20–30 residues long and occur in tandem. LRRs form parallel stacks of short β-strands and then assume a super helical arrangement called a solenoid structure. Individual LRRs are separated into highly conserved segment (HCS) with the consensus of LxxLxLxxNxL and variable segment (VS). Eight classes have been recognized. Bacterial LRRs are short and characterized by two prolines in the VS; the consensus is xxLPxLPxx with Nine residues (N-subtype) and xxLPxxLPxx with Ten residues (T-subtype). Bacterial LRRs are contained in type III secretion system effectors such as YopM, IpaH3/9.8, SspH1/2, and SlrP from bacteria. Some LRRs in decorin, fribromodulin, TLR8/9, and FLRT2/3 from vertebrate also contain the motifs. In order to understand structural features of bacterial LRRs, we performed both secondary structures assignments using four programs—DSSP-PPII, PROSS, SEGNO, and XTLSSTR—and HELFIT analyses (calculating helix axis, pitch, radius, residues per turn, and handedness), based on the atomic coordinates of their crystal structures. The N-subtype VS adopts a left handed polyproline II helix (PPII) with four, five or six residues and a type I β-turn at the C-terminal side. Thus, the N-subtype is characterized by a super secondary structure consisting of a PPII and a β-turn. In contrast, the T-subtype VS prefers two separate PPIIs with two or three and two residues. The HELFIT analysis indicates that the type I β-turn is a right handed helix. The HELFIT analysis determines three unit vectors of the helix axes of PPII (P), β-turn (B), and LRR domain (A). Three structural parameters using these three helix axes are suggested to characterize the super secondary structure and the LRR domain.

A helical lock and key model of polyproline II conformation with SH3

Motivation

More than half of the human proteome contains the proline-rich motif, PxxP. This motif has a high propensity for adopting a left-handed polyproline II (PPII) helix and can potentially bind SH3 domains. SH3 domains are generally grouped into two classes, based on whether the PPII binds in a positive (N-to-C terminal) or negative (C-to-N terminal) orientation. Since the discovery of this structural motif, over six decades ago, a systematic understanding of its binding remains poor and the consensus amino acid sequence that binds SH3 domains is still ill defined.

Results

Here, we show that the PPII interaction with SH3 domains is governed by the helix backbone and its prolines, and their rotation angle around the PPII helical axis. Based on a geometric analysis of 131 experimentally solved SH3 domains in complex with PPIIs, we observed a rotary translation along the helical screw axis, and separated them by 120° into three categories we name α (0–120°), β (120–240°) and γ (240–360°). Furthermore, we found that PPII helices are distinguished by a shifting PxxP motif preceded by positively charged residues which act as a structural reading frame and dictates the organization of SH3 domains; however, there is no one single consensus motif for all classified PPIIs. Our results demonstrate a remarkable apparatus of a lock with a rotating and translating key with no known equivalent machinery in molecular biology. We anticipate our model to be a starting point for deciphering the PPII code, which can unlock an exponential growth in our understanding of the relationship between protein structure and function.

Availability and implementation

We have implemented the proposed methods in the R software environment and in an R package freely available at https://github.com/Grantlab/bio3d.

Supplementary information

Supplementary data are available at Bioinformatics online.

The free energy landscape of the oncogene protein E7 of human papillomavirus type 16 reveals a complex interplay between ordered and disordered regions

When present, structural disorder makes it very challenging to characterise the conformational properties of proteins. This is particularly the case of proteins, such as the oncogene protein E7 of human papillomavirus type 16, which contain both ordered and disordered domains, and that can populate monomeric and oligomeric states under physiological conditions. Nuclear magnetic resonance (NMR) spectroscopy is emerging as a powerful method to study these complex systems, most notably in combination with molecular dynamics simulations. Here we use NMR chemical shifts and residual dipolar couplings as structural restraints in replica-averaged molecular dynamics simulations to determine the free energy landscape of E7. This landscape reveals a complex interplay between a folded but highly dynamical C-terminal domain and a disordered N-terminal domain that forms transient secondary and tertiary structures, as well as an equilibrium between a high-populated (98%) dimeric state and a low-populated (2%) monomeric state. These results provide compelling evidence of the complex conformational heterogeneity associated with the behaviour and interactions of this disordered protein associated with disease.

Proline 411 biases the conformation of the intrinsically disordered plant UVR8 photoreceptor C27 domain altering the functional properties of the peptide

UVR8 (UV RESISTANCE LOCUS 8) is a UV-B photoreceptor responsible for initiating UV-B signalling in plants. UVR8 is a homodimer in its signalling inactive form. Upon absorption of UV radiation, the protein monomerizes into its photoactivated state. In the monomeric form, UVR8 binds the E3 ubiquitin ligase COP1 (CONSTITUTIVELY PHOTOMORPHOGENIC 1), triggering subsequent UV-B-dependent photomorphogenic development in plants. Recent in vivo experiments have shown that the UVR8 C-terminal region (aa 397-423; UVR8^C27) alone is sufficient to regulate the activity of COP1. In this work, CD spectroscopy and NMR experiments showed that the UVR8^C27 domain was non-structured but gained secondary structure at higher temperatures leading to increased order. Bias-exchange metadynamics simulations were also performed to evaluate the free energy landscape of UVR8^C27. An inverted free energy landscape was revealed, with a disordered structure in the global energy minimum. Flanking the global energy minimum, more structured states were found at higher energies. Furthermore, stabilization of the low energy disordered state was attributed to a proline residue, P411, as evident from P411A mutant data. P411 is also a key residue in UVR8 binding to COP1. UVR8^C27 is therefore structurally competent to function as a molecular switch for interaction of UVR8 with different binding partners since at higher free energies different structural conformations are being induced in this peptide. P411 has a key role for this function.

Exploring Peptide⁻Solvent Interactions: A Computational Study

The dilemma of reconciling the contradictory evidence regarding the conformation of long solvated peptide chains is the so-called "reconciliation problem". Clues regarding the stability of certain conformations likely lie in the electronic structure at the peptide⁻solvent interface, but the peptide⁻solvent interaction is not fully understood. Here, we study the influence of aqueous solvent on peptide conformations by using classical molecular dynamics (MD) and quantum mechanical/molecular mechanical (QM/MM) energy calculations. The model systems include an 11-residue peptide, X 2 A 7 O 2 (XAO), where X, A, and O denote diaminobutyric acid, alanine, and ornithine, respectively, and a 9-mer (Arg-Pro-Pro-Gly-Phe-Ser-Ala-Phe-Lys). Spectroscopic and MD data present conflicting evidence regarding the structure of XAO in water; some results indicate that XAO adopts a polyproline II (P II ) conformation, whereas other findings suggest that XAO explores a range of conformations. To investigate this contradiction, we present here the results of MD simulations of XAO and the 9-mer in aqueous solution, combined with QM/MM energy calculations.

Temperature-induced collapse of a disordered peptide observed by three sampling methods in molecular dynamics simulations

The conformational ensembles of a disordered peptide, polyglutamine Q15, over a wide temperature range were sampled using multiple replicates of conventional molecular dynamics (cMD) simulations as well as two enhanced sampling methods, temperature replica exchange (TREMD) and replica exchange with solute tempering (REST). The radius of gyration, asphericity, secondary structure, and hydrogen bonding patterns were used for the comparison of the sampling methods. Overall, the three sampling methods generated similar conformational ensembles, with progressive collapse at higher temperatures. Although accumulating the longest simulation time (90 μs), cMD at room temperature missed a small subspace that was sampled by both TREMD and REST. This subspace was high in α-helical content and separated from the main conformational space by an energy barrier. REST used less simulation time than TREMD (36 μs versus 42 μs), and this gap is expected to widen significantly for larger disordered proteins. We conclude that REST is the method of choice for conformational sampling of intrinsically disordered proteins.

Bioinspired Load-Bearing Hydrogel Based on Engineered Sea Anemone Skin-Derived Collagen-Like Protein

With the help of recombinant DNA technology, many protein candidates have been investigated and engineered for biomaterial applications. Particularly, several repeat sequences with unique secondary structures have been selected as minimal building blocks for biosynthesis to improve the mechanical properties of biomaterials. However, most of these structural proteins have been limited to silk, elastin, collagen, and resilin for decades. In the present work, new repeat sequence found in sea anemone are characterized and biosynthesized into a recombinant protein (named anegen) for potential use as a load-bearing biomaterial. Because its repeat sequence unit has a unique polyproline II structure, which is prevalently found in the triple-helix of collagen, it is assumed to be a promising structural protein candidate that can provide conformational flexibility and elasticity. Because anegen has ≈10% tyrosine residues, inspiration is taken from di-tyrosine crosslinking in the hinge structures of insects, which can be initiated by light activation. It is found that the anegen hydrogel shows higher mechanical properties than a gelatin hydrogel and endures a compression series without deformation. Moreover, the mechanical properties of the anegen hydrogel are controllable through different crosslinking conditions in a wide range of material applications. Importantly, the anegen hydrogel exhibited suitable cell retainability and cell morphology as an implantable biomaterial. Thus, based on its mechanical properties and biocompatibility, the anegen hydrogel can be used as a potential load-bearing and cell-loading scaffolding biomaterial in the tissue and biomedical engineering fields.

Exploring hydrophobicity limits of polyproline helix with oligomeric octahydroindole-2-carboxylic acid

The polyproline-II helix is the most extended naturally occurring helical structure and is widely present in polar, exposed stretches and "unstructured" denatured regions of polypeptides. Can it be hydrophobic? In this study, we address this question using oligomeric peptides formed by a hydrophobic proline analogue, (2S,3aS,7aS)-octahydroindole-2-carboxylic acid (Oic). Previously, we found the molecular principles underlying the structural stability of the polyproline-II conformation in these oligomers, whereas the hydrophobicity of the peptide constructs remains to be examined. Therefore, we investigated the octan-1-ol/water partitioning and inclusion in detergent micelles of the oligo-Oic peptides. The results showed that the hydrophobicity is remarkably enhanced in longer oligomeric sequences, and the oligo-Oic peptides with 3 to 4 residues and higher are specific towards hydrophobic environments. This contrasts significantly to the parent oligoproline peptides, which were moderately hydrophilic. With these findings, we have demonstrated that the polyproline-II structure is compatible with nonpolar media, whereas additional manipulations of the terminal functionalities feature solubility in extremely nonpolar solvents such as hexane.

Conformational heterogeneity in tails of DNA-binding proteins is augmented by proline containing repeats

A cationic terminal extension or tail is a common feature of many DNA-binding proteins. We show that a particular type of tail rich in proline, alanine and lysine belongs to the class of 'flexible disorder' and consists of characteristic pentapeptide repeats. Our designed peptides, (AAKKA)_1-4 and (PAKKA)_1-4, represent the tails of several bacterial DNA-binding proteins. Enhanced conformational sampling of these representative peptides using accelerated molecular dynamic simulations supported by circular dichroism spectroscopy and nuclear magnetic resonance studies demonstrates the role of frequent and interspersed prolines in augmenting conformational heterogeneity of the peptide backbone. Analysis of circular variance of backbone dihedral angles indicates alternating regions of relative rigidity and flexibility along the peptide sequence due to prolines. Preferred placement of lysines in the regions of higher backbone flexibility might improve DNA-binding by conformational selection. Our results could be relevant for rational de novo design of disordered peptides.

Conformational Plasticity of the Cell-Penetrating Peptide SAP As Revealed by Solid-State 19F-NMR and Circular Dichroism Spectroscopies

The cell-penetrating peptide SAP, which was designed as an amphipathic poly-l-proline helix II (PPII), was suggested to self-assemble into regular fibrils that are relevant for its internalization. Herein we have analyzed the structure of SAP in the membrane-bound state by solid-state ¹⁹F-NMR, which revealed other structural states, in addition to the expected surface-aligned PPII. Trifluoromethyl-bicyclopentyl-glycine (CF₃-Bpg) and two rigid isomers of trifluoromethyl-4,5-methanoprolines (CF₃-MePro) were used as labels for ¹⁹F-NMR analysis. The equilibria between different conformations of SAP were studied and were found to be shifted by the substituents at Pro-11. Synchrotron-CD results suggested that substituting Pro-11 by CF₃-MePro governed the coil-to-PPII equilibrium in solution and in the presence of a lipid bilayer. Using CD and ¹⁹F-NMR, we examined the slow kinetics of the association of SAP with membranes and the dependence of the SAP conformational dynamics on the lipid composition. The peptide did not bind to lipids in the solid ordered phase and aggregated only in the liquid ordered "raft"-like bilayers. Self-association could not be detected in solution or in the presence of liquid disordered membranes. Surface-bound amphipathic SAP in a nonaggregated state was structured as a mixture of nonideal extended conformations reflecting the equilibrium already present in solution, i.e., before binding to the membrane.

Engineering protein stability with atomic precision in a monomeric miniprotein

Miniproteins simplify the protein-folding problem, allowing the dissection of forces that stabilize protein structures. Here we describe PPα-Tyr, a designed peptide comprising an α-helix buttressed by a polyproline II helix. PPα-Tyr is water soluble and monomeric, and it unfolds cooperatively with a midpoint unfolding temperature (T_M) of 39 °C. NMR structures of PPα-Tyr reveal proline residues docked between tyrosine side chains, as designed. The stability of PPα is sensitive to modifications in the aromatic residues: replacing tyrosine with phenylalanine, i.e., changing three solvent-exposed hydroxyl groups to protons, reduces the T_M to 20 °C. We attribute this result to the loss of CH-π interactions between the aromatic and proline rings, which we probe by substituting the aromatic residues with nonproteinogenic side chains. In analyses of natural protein structures, we find a preference for proline-tyrosine interactions over other proline-containing pairs, and observe abundant CH-π interactions in biologically important complexes between proline-rich ligands and SH3 and similar domains.

Computational and Experimental Investigation of the Structure of Peptide Monolayers on Gold Nanoparticles

The self-assembly and self-organization of small molecules on the surface of nanoparticles constitute a potential route toward the preparation of advanced proteinlike nanosystems. However, their structural characterization, critical to the design of bionanomaterials with well-defined biophysical and biochemical properties, remains highly challenging. Here, a computational model for peptide-capped gold nanoparticles (GNPs) is developed using experimentally characterized Cys-Ala-Leu-Asn-Asn (CALNN)- and Cys-Phe-Gly-Ala-Ile-Leu-Ser-Ser (CFGAILSS)-capped GNPs as a benchmark. The structure of CALNN and CFGAILSS monolayers is investigated using both structural biology techniques and molecular dynamics simulations. The calculations reproduce the experimentally observed dependence of the monolayer secondary structure on the peptide capping density and on the nanoparticle size, thus giving us confidence in the model. Furthermore, the computational results reveal a number of new features of peptide-capped monolayers, including the importance of sulfur movement for the formation of secondary structure motifs, the presence of water close to the gold surface even in tightly packed peptide monolayers, and the existence of extended 2D parallel β-sheet domains in CFGAILSS monolayers. The model developed here provides a predictive tool that may assist in the design of further bionanomaterials.

Molecular Dynamics Simulation of Tau Peptides for the Investigation of Conformational Changes Induced by Specific Phosphorylation Patterns

The Tau protein plays an important role due to its biomolecular interactions in neurodegenerative diseases. The lack of stable structure and various posttranslational modifications such as phosphorylation at various sites in the Tau protein pose a challenge for many experimental methods that are traditionally used to study protein folding and aggregation. Atomistic molecular dynamics (MD) simulations can help around deciphering relationship between phosphorylation and various intermediate and stable conformations of the Tau protein which occur on longer timescales. This chapter outlines protocols for the preparation, execution, and analysis of all-atom MD simulations of a 21-amino acid-long phosphorylated Tau peptide with the aim of generating biologically relevant structural and dynamic information. The simulations are done in explicit solvent and starting from nearly extended configurations of the peptide. The scaled MD method implemented in AMBER14 was chosen to achieve enhanced conformational sampling in addition to a conventional MD approach, thereby allowing the characterization of folding for such an intrinsically disordered peptide at 293 K. Emphasis is placed on the analysis of the simulation trajectories to establish correlations with NMR data (i.e., chemical shifts and NOEs). Finally, in-depth discussions are provided for commonly encountered problems.

Thermal compaction of the intrinsically disordered protein tau: entropic, structural, and hydrophobic factors

The first quantitative assessment of the entropic, hydrophobic, and structural factors producing the thermal compaction of tau, an intrinsically disordered protein.