Secondary structure assignment for conformationally irregular peptides: comparison between DSSP, STRIDE and KAKSI

Taxonomy-specific assessment of intrinsic disorder predictions at residue and region levels in higher eukaryotes, protists, archaea, bacteria and viruses

Intrinsic disorder predictors were evaluated in several studies including the two large CAID experiments. However, these studies are biased towards eukaryotic proteins and focus primarily on the residue-level predictions. We provide first-of-its-kind assessment that comprehensively covers the taxonomy and evaluates predictions at the residue and disordered region levels. We curate a benchmark dataset that uniformly covers eukaryotic, archaeal, bacterial, and viral proteins. We find that predictive performance differs substantially across taxonomy, where viruses are predicted most accurately, followed by protists and higher eukaryotes, while bacterial and archaeal proteins suffer lower levels of accuracy. These trends are consistent across predictors. We also find that current tools, except for flDPnn, struggle with reproducing native distributions of the numbers and sizes of the disordered regions. Moreover, analysis of two variants of disorder predictions derived from the AlphaFold2 predicted structures reveals that they produce accurate residue-level propensities for archaea, bacteria and protists. However, they underperform for higher eukaryotes and generally struggle to accurately identify disordered regions. Our results motivate development of new predictors that target bacteria and archaea and which produce accurate results at both residue and region levels. We also stress the need to include the region-level assessments in future assessments.

Phosphorylation at the D56 residue of MtrA in Mycobacterium tuberculosis enhances its DNA binding affinity by modulating inter-domain interaction

The response regulator, MtrA, plays a major role in adaptation to the host environment, cell division, replication, and dormancy activation of Mycobacterium tuberculosis (Mtb). The phosphorylation of the response regulator MtrA alters the downstream activity, typically involving changes in DNA binding activity. However, there is a substantial knowledge gap in understanding the phosphorylation-mediated structural changes in MtrA. Additionally, the active conformation of the protein has yet to be determined. Therefore, in this study, we have investigated the phosphorylation-induced conformational changes of MtrA using all-atom molecular dynamics simulations under various phosphorylation conditions. The results from this study demonstrate that the phosphorylation at D56 (pD56-MtrA) increases the compactness of the MtrA protein by stabilizing the inter-domain interaction between the regulatory domain and DNA binding domain. Notably, the higher occupancy H-bond (over 95 %) between Arg200-Asn100 in case of the pD56-MtrA condition, which is otherwise absent in the non-phosphorylated (uMtrA) condition, suggests the importance of this interaction in the active conformation of the protein. The dynamic cross-correlation analysis reveals that phosphorylation (especially pD56-MtrA) reduces the anti-correlated motions and increases correlated motions between different domains. Moreover, the higher DNA binding affinity of pD56-MtrA compared to uMtrA supported by molecular docking and MD simulation followed by MMPBSA analysis suggests that pD56-MtrA is the possible active conformation of the MtrA protein. Overall, this investigation elucidates the key structural changes in MtrA under different phosphorylated conditions, which might help in designing novel therapeutics against tuberculosis.

In silico study to identify novel NEK7 inhibitors from natural sources by a combination strategy

Cancer poses a significant global health challenge and significantly contributes to mortality. NEK7, related to the NIMA protein kinase family, plays a crucial role in spindle assembly and cell division. The dysregulation of NEK7 is closely linked to the onset and progression of various cancers, especially colon and breast cancer, making it a promising target for cancer therapy. Nevertheless, the shortage of high-quality NEK7 inhibitors highlights the need for new therapeutic strategies. In this study, we utilized a multidisciplinary approach, including virtual screening, molecular docking, pharmacokinetics, molecular dynamics simulations (MDs), and MM/PBSA calculations, to evaluate natural compounds as NEK7 inhibitors comprehensively. Through various docking strategies, we identified three natural compounds: (-)-balanol, digallic acid, and scutellarin. Molecular docking revealed significant interactions at residues such as GLU112 and ALA114, with docking scores of -15.054, -13.059, and -11.547 kcal/mol, respectively, highlighting their potential as NEK7 inhibitors. MDs confirmed the stability of these compounds at the NEK7-binding site. Hydrogen bond analysis during simulations revealed consistent interactions, supporting their strong binding capacity. MM/PBSA analysis identified other crucial amino acids contributing to binding affinity, including ILE20, VAL28, ILE75, LEU93, ALA94, LYS143, PHE148, LEU160, and THR161, crucial for stabilizing the complex. This research demonstrated that these compounds exceeded dabrafenib in binding energy, according to MM/PBSA calculations, underscoring their effectiveness as NEK7 inhibitors. ADME/T predictions showed lower oral toxicity for these compounds, suggesting their potential for further development. This study highlights the promise of these natural compounds as bases for creating more potent derivatives with significant biological activities, paving the way for future experimental validation.

In silico design of potential Mcl-1 peptide-based inhibitors

CONTEXT

BIM (Bcl-2 interacting mediator of apoptosis)-derived peptides that specifically target over-expressed Mcl-1 (myeloid cell leukemia-1) protein and induce apoptosis are potentially anti-cancer agents. Since the helicity of BIM-derived peptides has a crucial role in their functionality, a range of strategies have been used to increase the helicity including the introduction of unnatural residues and stapling methods that have some drawbacks such as the accumulation in the liver. To avoid these drawbacks, this study aimed to design a more helical peptide by utilizing bioinformatics algorithms and molecular dynamics simulations without exploiting unnatural residues and stapling methods. MM-PBSA results showed that the mutations of A4fE and A2eE in analogue 5 demonstrate a preference towards binding with Mcl-1. As evidenced by Circular dichroism results, the helicity increases from 18 to 34%, these findings could enhance the potential of analogue 5 as an anti-cancer agent targeting Mcl-1. The applied strategies in this research could shed light on the in silico peptide design. Moreover, analogue 5 as a drug candidate can be evaluated in vitro and in vivo studies.

METHODS

The sequence of the lead peptide was determined using the ApInAPDB database and PRALINE program. Contact finder and PDBsum web server softwares were used to determine the contact involved amino acids in complex with Mcl-1. All identified salt bridge contributing residues were unaltered to preserve the binding affinity. After proposing novel analogues, their secondary structures were predicted by Cham finder web server software and GOR, Neural Network, and Chou-Fasman algorithms. Finally, molecular dynamics simulations run for 100 ns were done using the GROMACS, version 5.0.7, with the CHARMM36 force field. MM-PBSA was used to assess binding affinity specificity in targeting Mcl-1 and Bcl-xL (B-cell lymphoma extra-large).

Complex Conformational Space of the RNA Polymerase II C-Terminal Domain upon Phosphorylation

Intrinsically disordered proteins (IDPs) have been closely studied during the past decade due to their importance in many biological processes. The disordered nature of this group of proteins makes it difficult to observe its full span of the conformational space using either experimental or computational studies. In this article, we explored the conformational space of the C-terminal domain (CTD) of RNA polymerase II (Pol II), which is also an intrinsically disordered low complexity domain, using enhanced sampling methods. We provided a detailed conformational analysis of model systems of CTD with different lengths; first with the last 44 residues of the human CTD sequence and finally the CTD model with 2-heptapeptide repeating units. We then investigated the effects of phosphorylation on CTD conformations by performing simulations at different phosphorylated states. We obtained broad conformational spaces in nonphosphorylated CTD models, and phosphorylation has complex effects on the conformations of the CTD. These complex effects depend on the length of the CTD, spacing between the multiple phosphorylation sites, ion coordination, and interactions with the nearby residues.

Analysis of Structural Changes in the Protein near the Phosphorylation Site

Modification of the protein after synthesis (PTM) often affects protein function as supported by numerous studies. However, there is no consensus about the degree of structural protein changes after modification. For phosphorylation of serine, threonine, and tyrosine, which is a common PTM in the biology of living organisms, we consider topical issues related to changes in the geometric parameters of a protein (Rg, RMSD, Cα displacement, SASA). The effect of phosphorylation on protein geometry was studied both for the whole protein and at the local level (i.e., in different neighborhoods of the modification site). Heterogeneity in the degree of protein structural changes after phosphorylation was revealed, which allowed for us to isolate a group of proteins having pronounced local structural changes in the neighborhoods of up to 15 amino acid residues from the modification site. This is a comparative study of protein structural changes in neighborhoods of 3-15 amino acid residues from the modified site. Amino acid phosphorylation in proteins with pronounced local changes caused switching from the inactive functional state to the active one.

Myofilament-associated proteins with intrinsic disorder (MAPIDs) and their resolution by computational modeling

The cardiac sarcomere is a cellular structure in the heart that enables muscle cells to contract. Dozens of proteins belong to the cardiac sarcomere, which work in tandem to generate force and adapt to demands on cardiac output. Intriguingly, the majority of these proteins have significant intrinsic disorder that contributes to their functions, yet the biophysics of these intrinsically disordered regions (IDRs) have been characterized in limited detail. In this review, we first enumerate these myofilament-associated proteins with intrinsic disorder (MAPIDs) and recent biophysical studies to characterize their IDRs. We secondly summarize the biophysics governing IDR properties and the state-of-the-art in computational tools toward MAPID identification and characterization of their conformation ensembles. We conclude with an overview of future computational approaches toward broadening the understanding of intrinsic disorder in the cardiac sarcomere.

Concentration-Dependent Effects of Cholesterol on the Dimerization of Amyloid-β Peptides in Lipid Bilayers

Membrane disruption mediated by the accumulation of amyloid-β (Aβ) on cell membranes is central to the pathogenesis of Alzheimer's disease (AD). Cholesterol, an important component of membranes, is well-recognized as a risk factor in AD. It can affect the aggregation and pore formation of Aβ on membranes whereas the specific effects are rather complex, particularly regarding the non-linear response to cholesterol concentrations. Yet, the mechanistic understanding of the role of cholesterol in Aβ-membrane interactions remains incomplete. Herein, we employed microsecond-scale molecular dynamics simulations to investigate the effects of cholesterol on Aβ dimerization in a lipid bilayer containing different molar ratios of cholesterol (0, 20, and 40 mol %). Cholesterol reduces the time required for the formation of stable dimers and exerts dual effects on Aβ-membrane interactions. First, cholesterol promotes the extraction of the C-terminal region from the membrane to water. Consequently, at the ratios of 0 and 20 mol %, peptides are anchored at the membrane-water interface, but they are repelled to water at a ratio of 40 mol % with high structural flexibility. Second, cholesterol weakens Aβ-membrane interactions, thereby enhancing inter-peptide interactions. The former is favorable for dimerization while the latter is not. The balance between two factors eventually leads to a non-monotonic effect on the degree of dimerization, whereby the number of inter-peptide contacts is the largest at a cholesterol ratio of 20 mol %. These results provide atomistic insights into the regulation mechanism of Aβ42 aggregation by cholesterol and help to understand the pathological link between cholesterol and AD.

Empagliflozin induces apoptotic-signaling pathway in embryonic vasculature: In vivo and in silico approaches via chick’s yolk sac membrane model

The present investigation was conducted to evaluate the vascular-toxicity of empagliflozin (EMP) in embryonic vasculature. Firstly, the vascular-toxicity of the drug as well as its interaction with apoptotic regulator proteins was predicted via in silico approach. In the next step, the apoptotic-signaling pathway in embryonic vasculature was evaluated using a chick’s YSM model. In silico simulation confirmed vascular-toxicity of EMP. There was also an accurate affinity between EMP, Bax and Bcl-2 (−7.9 kcal/mol). Molecular dynamics assay revealed complex stability in the human body conditions. Furthermore, EMP is suggested to alter Bcl-2 more than BAX. Morphometric quantification of the vessels showed that the apoptotic activity of EMP in embryonic vasculature was related to a marked reduction in vessel area, vessel diameter and mean capillary area. Based on the qPCR and immunohistochemistry assays, enhanced expression level of BAX and reduced expression level of Bcl-2 confirmed apoptotic responses in the vessels of the YSM. We observed that induction of an apoptotic signal can cause the embryonic defect of the vascular system following EMP treatment. The acquired data also raised suspicions that alteration in apoptotic genes and proteins in the vasculature are two critical pathways in vascular-toxicity of EMP.

Linking Alzheimer’s Disease and Type 2 Diabetes: Characterization and Inhibition of Cytotoxic Aβ and IAPP Hetero-Aggregates

The cytotoxic self-aggregation of β-amyloid (Aβ) peptide and islet amyloid polypeptide (IAPP) is implicated in the pathogenesis of Alzheimer’s disease (AD) and Type 2 diabetes (T2D), respectively. Increasing evidence, particularly the co-deposition of Aβ and IAPP in both brain and pancreatic tissues, suggests that Aβ and IAPP cross-interaction may be responsible for a pathological link between AD and T2D. Here, we examined the nature of IAPP-Aβ40 co-aggregation and its inhibition by small molecules. In specific, we characterized the kinetic profiles, morphologies, secondary structures and toxicities of IAPP-Aβ40 hetero-assemblies and compared them to those formed by their homo-assemblies. We demonstrated that monomeric IAPP and Aβ40 form stable hetero-dimers and hetero-assemblies that further aggregate into β-sheet-rich hetero-aggregates that are toxic (cell viability <50%) to both PC-12 cells, a neuronal cell model, and RIN-m5F cells, a pancreatic cell model for β-cells. We then selected polyphenolic candidates to inhibit IAPP or Aβ40 self-aggregation and examined the inhibitory effect of the most potent candidate on IAPP-Aβ40 co-aggregation. We demonstrated that epigallocatechin gallate (EGCG) form inter-molecular hydrogen bonds with each of IAPP and Aβ40. We also showed that EGCG reduced hetero-aggregate formation and resulted in lower β-sheets content and higher unordered structures in IAPP-Aβ40-EGCG samples. Importantly, we showed that EGCG is highly effective in reducing the toxicity of IAPP-Aβ40 hetero-aggregates on both cell models, specifically at concentrations that are equivalent to or are 2.5-fold higher than the mixed peptide concentrations. To the best of our knowledge, this is the first study to report the inhibition of IAPP-Aβ40 co-aggregation by small molecules. We conclude that EGCG is a promising candidate to prevent co-aggregation and cytotoxicity of IAPP-Aβ40, which in turn, contribute to the pathological link between AD and T2D.

Structural modeling of human AKAP3 protein and in silico analysis of single nucleotide polymorphisms associated with sperm motility

AKAP3 is a member of the A-kinase anchoring proteins and it is a constituent of the sperm fibrous sheath. AKAP3 is needed for the formation of sperm flagellum structure, sperm motility, and male fertility. This study aims to model the AKAP3 tertiary structure and identify the probable impact of four mutations characterized in infertile men on the AKAP3 structure. The T464S, I500T, E525K, and I661T substitutions were analyzed using in silico methods. The secondary structure and three-dimensional model of AKAP3 were determined using PSI-BLAST based secondary structure prediction and Robetta servers. The TM-score was used to quantitatively measure the structural similarities between native and mutated models. All of the desired substitutions were classified as benign. I-Mutant results showed all of the substitutions decreased AKAP3 stability; however, the I500T and I661T were more effective. Superposition and secondary structure comparisons between native and mutants showed no dramatic deviations. Our study provided an appropriate model for AKAP3. Destabilization of AKAP3 caused by these substitutions did not appear to induce structural disturbances. As AKAP3 is involved in male infertility, providing more structural insights and the impact of mutations that cause protein functional diversity could elucidate the etiology of male fertility problems at molecular level.

Amyloid-β peptide dimers undergo a random coil to β-sheet transition in the aqueous phase but not at the neuronal membrane

Mounting evidence suggests that the neuronal cell membrane is the main site of oligomer-mediated neuronal toxicity of amyloid-β peptides in Alzheimer's disease. To gain a detailed understanding of the mutual interference of amyloid-β oligomers and the neuronal membrane, we carried out microseconds of all-atom molecular dynamics (MD) simulations on the dimerization of amyloid-β (Aβ)42 in the aqueous phase and in the presence of a lipid bilayer mimicking the in vivo composition of neuronal membranes. The dimerization in solution is characterized by a random coil to β-sheet transition that seems on pathway to amyloid aggregation, while the interactions with the neuronal membrane decrease the order of the Aβ42 dimer by attenuating its propensity to form a β-sheet structure. The main lipid interaction partners of Aβ42 are the surface-exposed sugar groups of the gangliosides GM1. As the neurotoxic activity of amyloid oligomers increases with oligomer order, these results suggest that GM1 is neuroprotective against Aβ-mediated toxicity.

Assigning secondary structure in proteins using AI

Knowledge about protein structure assignment enriches the structural and functional understanding of proteins. Accurate and reliable structure assignment data is crucial for secondary structure prediction systems. Since the 1980s, various methods based on hydrogen bond analysis and atomic coordinate geometry, followed by machine learning, have been employed in protein structure assignment. However, the assignment process becomes challenging when missing atoms are present in the protein files. Our method proposed a multi-class classifier program named DLFSA for assigning protein secondary structure elements (SSE) using convolutional neural networks (CNNs). A fast and efficient GPU-based parallel procedure extracts fragments from protein files. The model implemented in this work is trained with a subset of the protein fragments and achieves 88.1% and 82.5% train and test accuracy, respectively. The model uses only C_α coordinates for secondary structure assignments. The model has been successfully tested on a few full-length proteins also. Results from the fragment-based studies demonstrate the feasibility of applying deep learning solutions for structure assignment problems.

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.

Electronic Circular Dichroism of the Cas9 Protein and gRNA:Cas9 Ribonucleoprotein Complex

The Streptococcus pyogenes Cas9 protein (SpCas9), a component of CRISPR-based immune system in microbes, has become commonly utilized for genome editing. This nuclease forms a ribonucleoprotein (RNP) complex with guide RNA (gRNA) which induces Cas9 structural changes and triggers its cleavage activity. Here, electronic circular dichroism (ECD) spectroscopy was used to confirm the RNP formation and to determine its individual components. The ECD spectra had characteristic features differentiating Cas9 and gRNA, the former showed a negative/positive profile with maxima located at 221, 209 and 196 nm, while the latter revealed positive/negative/positive/negative pattern with bands observed at 266, 242, 222 and 209 nm, respectively. For the first time, the experimental ECD spectrum of the gRNA:Cas9 RNP complex is presented. It exhibits a bisignate positive/negative ECD couplet with maxima at 273 and 235 nm, and it differs significantly from individual spectrum of each RNP components. Additionally, the Cas9 protein and RNP complex retained biological activity after ECD measurements and they were able to bind and cleave DNA in vitro. Hence, we conclude that ECD spectroscopy can be considered as a quick and non-destructive method of monitoring conformational changes of the Cas9 protein as a result of Cas9 and gRNA interaction, and identification of the gRNA:Cas9 RNP complex.

Insight into molecular characteristics of SARS-CoV-2 spike protein following D614G point mutation, a molecular dynamics study

Undoubtedly, the SARS-CoV-2 has become a major concern for all societies due to its catastrophic effects on public health. In addition, mutations and changes in the structure of the virus make it difficult to design effective treatment. Moreover, the amino acid sequence of a protein is a major factor in the formation of the second and tertiary structure in a protein. Amino acid replacement can have noticeable effects on the folding of a protein, especially if an asymmetric change (substitution of polar residue with non-polar, charged with an uncharged, positive charge with a negative charge, or large residue with small residue) occurs. D614G as a spike mutant of SARS-CoV-2 previously identified as an associated risk factor with a high mortality rate of this virus. Using structural bioinformatics, our group determined that D614G mutation could cause extensive changes in SARS-CoV-2 behavior including the secondary structure, receptor binding pattern, 3D conformation, and stability of it.

Communicated by Ramaswamy H. Sarma

Quantitative description and classification of protein structures by a novel robust amino acid network: interaction selective network (ISN)

To quantitatively categorize protein structures, we developed a quantitative coarse-grained model of protein structures with a novel amino acid network, the interaction selective network (ISN), characterized by the links based on interactions in both the main and side chains. We found that the ISN is a novel robust network model to show the higher classification probability in the plots of average vertex degree (k) versus average clustering coefficient (C), both of which are typical network parameters for protein structures, and successfully distinguished between “all-α” and “all-β” proteins. On the other hand, one of the typical conventional networks, the α-carbon network (CAN), was found to be less robust than the ISN, and another typical network, atomic distance network (ADN), failed to distinguish between these two protein structures. Considering that the links in the CAN and ADN are defined by the interactions only between the main chain atoms and by the distance of the closest atom pair between the two amino acid residues, respectively, we can conclude that reflecting structural information from both secondary and tertiary structures in the network parameters improves the quantitative evaluation and robustness in network models, resulting in a quantitative and more robust description of three-dimensional protein structures in the ISN.

Exploring the effect of inhibitor AKB-9778 on VE-PTP by molecular docking and molecular dynamics simulation

Diabetic macular edema, also known as diabetic eye disease, is mainly caused by the overexpression of vascular endothelial protein tyrosine phosphatase (VE-PTP) at hypoxia/ischemic. AKB-9778 is a known VE-PTP inhibitor that can effectively interact with the active site of VE-PTP to inhibit the activity of VE-PTP. However, the binding pattern of VE-PTP with AKB-9778 and the dynamic implications of AKB-9778 on VE-PTP system at the molecular level are poorly understood. Through molecular docking, it was found that the AKB-9778 was docked well in the binding pocket of VE-PTP by the interactions of hydrogen bond and Van der Waals. Furthermore, after molecular dynamic simulations on VE-PTP system and VE-PTP ^AKB-9778 system, a series of postdynamic analyses found that the flexibility and conformation of the active site undergone an obvious transition after VE-PTP binding with AKB-9778. Moreover, by constructing the RIN, it was found that the different interactions in the active site were the detailed reasons for the conformational differences between these two systems. Thus, the finding here might provide a deeper understanding of AKB-9778 as VE-PTP Inhibitor.

Effects of force fields on the conformational and dynamic properties of amyloid β(1-40) dimer explored by replica exchange molecular dynamics simulations

The conformational space and structural ensembles of amyloid beta (Aβ) peptides and their oligomers in solution are inherently disordered and proven to be challenging to study. Optimum force field selection for molecular dynamics (MD) simulations and the biophysical relevance of results are still unknown. We compared the conformational space of the Aβ(1-40) dimers by 300 ns replica exchange MD simulations at physiological temperature (310 K) using: the AMBER-ff99sb-ILDN, AMBER-ff99sb*-ILDN, AMBER-ff99sb-NMR, and CHARMM22* force fields. Statistical comparisons of simulation results to experimental data and previously published simulations utilizing the CHARMM22* and CHARMM36 force fields were performed. All force fields yield sampled ensembles of conformations with collision cross sectional areas for the dimer that are statistically significantly larger than experimental results. All force fields, with the exception of AMBER-ff99sb-ILDN (8.8 ± 6.4%) and CHARMM36 (2.7 ± 4.2%), tend to overestimate the α-helical content compared to experimental CD (5.3 ± 5.2%). Using the AMBER-ff99sb-NMR force field resulted in the greatest degree of variance (41.3 ± 12.9%). Except for the AMBER-ff99sb-NMR force field, the others tended to under estimate the expected amount of β-sheet and over estimate the amount of turn/bend/random coil conformations. All force fields, with the exception AMBER-ff99sb-NMR, reproduce a theoretically expected β-sheet-turn-β-sheet conformational motif, however, only the CHARMM22* and CHARMM36 force fields yield results compatible with collapse of the central and C-terminal hydrophobic cores from residues 17-21 and 30-36. Although analyses of essential subspace sampling showed only minor variations between force fields, secondary structures of lowest energy conformers are different.

A distance geometry-based description and validation of protein main-chain conformation

Understanding the protein main-chain conformational space forms the basis for the modelling of protein structures and for the validation of models derived from structural biology techniques. Presented here is a novel idea for a three-dimensional distance geometry-based metric to account for the fine details of protein backbone conformations. The metrics are computed for dipeptide units, defined as blocks of Cαi-1-O i-1-Cαi -O i -Cαi+1 atoms, by obtaining the eigenvalues of their Euclidean distance matrices. These were computed for ∼1.3 million dipeptide units collected from nonredundant good-quality structures in the Protein Data Bank and subjected to principal component analysis. The resulting new Euclidean orthogonal three-dimensional space (DipSpace) allows a probabilistic description of protein backbone geometry. The three axes of the DipSpace describe the local extension of the dipeptide unit structure, its twist and its bend. By using a higher-dimensional metric, the method is efficient for the identification of Cα atoms in an unlikely or unusual geometrical environment, and its use for both local and overall validation of protein models is demonstrated. It is also shown, for the example of trypsin proteases, that the detection of unusual conformations that are conserved among the structures of this protein family may indicate geometrically strained residues of potentially functional importance.

Effect of Inactivating Mutations on Peptide Conformational Ensembles: The Plant Polypeptide Hormone Systemin

As part of their basal immune mechanism against insect/herbivore attacks, plants have evolved systemic response mechanisms. Such a systemic wound response in tomato was found to involve an 18 amino acid polypeptide called systemin, the first polypeptide hormone to be discovered in plants. Systematic alanine scanning and deletion studies showed differential modulation in its activity, particularly a major loss of function due to alanine substitution at positions 13 and 17 and less extentive loss of function due to substitution at position 12. We have studied the conformational ensembles of wild-type systemin along with its 17 variants by carrying out a total of 5.76 μs of replica-exchange molecular dynamics simulation in an implicit solvent environment. In our simulations, wild-type systemin showed a lack of α-helical and β-sheet structures, in conformity with earlier circular dichroism and NMR data. On the other hand, two regions containing diproline segments showed a tendency to adopt polyproline II structures. Examination of conformational ensembles of the 17 variants revealed a change in the population distributions, suggesting a less flexible structure for alanine substitutions at positions 12 and 13 but not for position 17. Combined with the experimental observations that positions 1-14 of systemin are important for the formation of the peptide-receptor complex, this leads to the hypothesis that loss of conformational flexibility may play a role in the loss of activity of systemin due to the P12A and P13A substitutions, while T17A deactivation probably occurs for a different reason, most likely the loss of the threonine phosphorylation site. We also indicate possible structural reasons why the substitution of the prolines at positions 12 and 13 leads to a loss of conformational freedom in the peptide.

Amyloid Properties of Asparagine and Glutamine in Prion-like Proteins

Sequences rich in glutamine (Q) and asparagine (N) are intrinsically disordered in monomeric form, but can aggregate into highly ordered amyloids, as seen in Q/N-rich prion domains (PrDs). Amyloids are fibrillar protein aggregates rich in β-sheet structures that can self-propagate through protein-conformational chain reactions. Here, we present a comprehensive theoretical study of N/Q-rich peptides, including sequences found in the yeast Sup35 PrD, in parallel and antiparallel β-sheet aggregates, and probe via fully atomistic molecular dynamics simulations all their possible steric-zipper interfaces in order to determine their protofibril structure and their relative stability. Our results show that polyglutamine aggregates are more stable than polyasparagine aggregates. Enthalpic contributions to the free energy favor the formation of polyQ protofibrils, while entropic contributions favor the formation of polyN protofibrils. The considerably larger phase space that disordered polyQ must sample on its way to aggregation probably is at the root of the associated slower kinetics observed experimentally. When other amino acids are present, such as in the Sup35 PrD, their shorter side chains favor steric-zipper formation for N but not Q, as they preclude the in-register association of the long Q side chains.

Asparagine Repeat Peptides: Aggregation Kinetics and Comparison with Glutamine Repeats

Amino acid repeat runs are common occurrences in eukaryotic proteins, with glutamine (Q) and asparagine (N) as particularly frequent repeats. Abnormal expansion of Q-repeat domains causes at least nine neurodegenerative disorders, most likely because expansion leads to protein misfolding, aggregation, and toxicity. The linkage between Q-repeats and disease has motivated several investigations into the mechanism of aggregation and the role of Q-repeat length in aggregation. Curiously, glutamine repeats are common in vertebrates, whereas N-repeats are virtually absent in vertebrates, but common in invertebrates. One hypothesis for the lack of N-repeats in vertebrates is biophysical; that is, there is strong selective pressure in higher organisms against aggregation-prone proteins. If true, then asparagine and glutamine repeats must differ substantially in their aggregation properties despite their chemical similarities. In this work, aggregation of peptides with asparagine repeats of variable length (12-24) were characterized and compared to that of similar peptides with glutamine repeats. As with glutamine, aggregation of N-repeat peptides was strongly length-dependent. Replacement of glutamine with asparagine caused a subtle shift in the conformation of the monomer, which strongly affected the rate of aggregation. Specifically, N-repeat peptides adopted β-turn structural elements, leading to faster self-assembly into globular oligomers and much more rapid conversion into fibrillar aggregates, compared to Q-repeat peptides. These biophysical differences may account for the differing biological roles of N- versus Q-repeat domains.