Secondary Structure Preferences Research Articles

Amino acid propensities for secondary structures and its variation across protein structures using exhaustive PDB data

Amino acid propensities for protein secondary structures are vital for protein structure prediction, understanding folding, and design, and have been studied using various theoretical and experimental methods. Traditional assessments of average propensities using statistical methods have been done on relatively smaller dataset for only a few secondary structures. They also involve averaging out the environmental factors and lack insights into consistency of preferences across diverse protein structures. While a few studies have explored variations in propensities across protein structural classes and folds, exploration of such variations across protein structures remains to be carried out. In this work, we have revised the average propensities for all six different secondary structures, namely α-helix, β-strand, 310-helix, π-helix, turn and coil, analyzing the most exhaustive dataset available till date using two robust secondary structure assignment algorithms, DSSP and STRIDE. The propensities evaluated here can serve as a standard reference. Moreover, we present here, for the first time, the propensities within individual protein structures and investigated how the preferences of residues and more interestingly, of their groups formed based on their structural features, vary across different unique structures. We devised a novel approach- the minimal set analysis, based on the propensity distribution of residues, which along with the group propensities led us to the conclusion that a residue's preference for a specific secondary structure is primarily dictated by its side chain's structural features. The findings in this study provide a more insightful picture of residues propensities and can be useful in protein folding and design studies.

Dipole Cooperativity and Polarization Frustration Determine the Secondary Structure Distribution of Short Alanine Peptides in Water.

The physical driving forces for secondary structure preferences of hydrated alanine peptide are investigated with B3LYP-D3(BJ) and the adaptive force matching (AFM) method. The AFM fit to the DFT surface, ALA2022, provides excellent agreement with the nuclear magnetic resonance scalar coupling constants from experiments. In turn, the model is used to gain insight into the physical driving forces behind secondary structure preferences of hydrated peptides. DFT calculations with and without the Conductor-like Screening Model (COSMO) show that the α helix is stabilized by solvent polarization due to dipole cooperativity. The two adjacent amide groups in β strand form a near-planar trapezoid that is not much larger than the size of water molecules. When the finite size of a water molecule is considered, the stabilization from solvent polarization for such a trapezoid is frustrated. Water molecules cannot find orientations to properly stabilize all four polar regions close to each other with such an awkward arrangement. This leads to quite substantial reduction in polarization stabilization. Although the polyproline II (PP-II) conformation is very similar to the β strand, the small twist in the backbone angles allowed much improved polarization stabilization. The improved polarization, when combined with favorable intrapeptide interactions, leads to the PP-II to be lowest in free energy. Other factors, such as the entropic TΔS and the ϕ, ψ coupling terms, are also studied but are found to play only a minor role. The insight shown in this work helps to better understand the structure of globular and intrinsic disordered proteins and facilitate future force field development.

ResidualBind: Uncovering Sequence-Structure Preferences of RNA-Binding Proteins with Deep Neural Networks.

Deep neural networks have demonstrated improved performance at predicting sequence specificities of DNA- and RNA-binding proteins. However, it remains unclear why they perform better than previous methods that rely on k-mers and position weight matrices. Here, we highlight a recent deep learning-based software package, called ResidualBind, that analyzes RNA-protein interactions using only RNA sequence as an input feature and performs global importance analysis for model interpretability. We discuss practical considerations for model interpretability to uncover learned sequence motifs and their secondary structure preferences.

Structure-Guided Design of a Potent and Specific Inhibitor against the Genomic Mutator APOBEC3A.

Nucleic acid structure plays a critical role in governing the selectivity of DNA- and RNA-modifying enzymes. In the case of the APOBEC3 family of cytidine deaminases, these enzymes catalyze the conversion of cytosine (C) to uracil (U) in single-stranded DNA, primarily in the context of innate immunity. DNA deamination can also have pathological consequences, accelerating the evolution of viral genomes or, when the host genome is targeted by either APOBEC3A (A3A) or APOBEC3B (A3B), promoting tumor evolution leading to worse patient prognosis and chemotherapeutic resistance. For A3A, nucleic acid secondary structure has emerged as a critical determinant of substrate targeting, with a predilection for DNA that can form stem loop hairpins. Here, we report the development of a specific nanomolar-level, nucleic acid-based inhibitor of A3A. Our strategy relies on embedding the nucleobase 5-methylzebularine, a mechanism-based inhibitor, into a DNA dumbbell structure, which mimics the ideal substrate secondary structure for A3A. Structure-activity relationship studies using a panel of diverse inhibitors reveal a critical role for the stem and position of the inhibitor moiety in achieving potent inhibition. Moreover, we demonstrate that DNA dumbbell inhibitors, but not nonstructured inhibitors, show specificity against A3A relative to the closely related catalytic domain of A3B. Overall, our work demonstrates the feasibility of leveraging secondary structural preferences in inhibitor design, offering a blueprint for further development of modulators of DNA-modifying enzymes and potential therapeutics to circumvent APOBEC-driven viral and tumor evolution.

PRIESSTESS: interpretable, high-performing models of the sequence and structure preferences of RNA-binding proteins.

Modelling both primary sequence and secondary structure preferences for RNA binding proteins (RBPs) remains an ongoing challenge. Current models use varied RNA structure representations and can be difficult to interpret and evaluate. To address these issues, we present a universal RNA motif-finding/scanning strategy, termed PRIESSTESS (Predictive RBP-RNA InterpretablE Sequence-Structure moTif regrESSion), that can be applied to diverse RNA binding datasets. PRIESSTESS identifies dozens of enriched RNA sequence and/or structure motifs that are subsequently reduced to a set of core motifs by logistic regression with LASSO regularization. Importantly, these core motifs are easily visualized and interpreted, and provide a measure of RBP secondary structure specificity. We used PRIESSTESS to interrogate new HTR-SELEX data for 23 RBPs with diverse RNA binding modes and captured known primary sequence and secondary structure preferences for each. Moreover, when applying PRIESSTESS to 144 RBPs across 202 RNA binding datasets, 75% showed an RNA secondary structure preference but only 10% had a preference besides unpaired bases, suggesting that most RBPs simply recognize the accessibility of primary sequences.

Sequence-Controlled Secondary Structures and Stimuli Responsiveness of Bioinspired Polyampholytes.

A comprehensive study focusing on the influence of the sequence charge pattern on the secondary structure preferences of annealed polyampholytes and their responsiveness to external stimuli is presented. Two sequences are designed composed entirely of ionizable amino acids (charge fraction, f = 1) and an equal number of positive and negative charges (f+ = f- = 0.5) with distinct charge patterns consisting of lysine and glutamic acid monomers. The study reveals that the sequence charge pattern has a significant influence on the secondary structure preferences of polyampholytes at physiological pH. Furthermore, it shows that external stimuli such as pH, ionic strength, and solvent dielectric constant can be used to modulate the secondary structure of the two studied sequences. The observed secondary structure transformations for the two sequences are also substantially different from those determined for uniformly charged homo-polypeptides under matching conditions.

Going through changes: effect of phosphoserine on secondary structure preference and dipole-dipole interactions in model peptides

Intrinsically disordered proteins (IDPs) are enriched in polar and charged amino acids and lack a single, well-defined tertiary structure. IDPs are frequently the targets of post-translational modifications (PTMs) which can affect protein folding or stability, activity, susceptibility to degradation, and function. Phosphorylation is one of the most common PTMs and occurs on serine, threonine, and tyrosine residues. Hyperphosphorylation of some IDPs is associated with disease states, such as the tau protein in Alzheimer’s disease and α-synuclein in Parkinson’s disease.

Methods for Measuring Exchangeable Protons in Glycosaminoglycans.

Recent NMR studies of the exchangeable protons of GAGs in aqueous solution, including those of the amide, sulfamate, and hydroxyl moieties, have demonstrated potential for the detection of intramolecular hydrogen bonds providing insights into secondary structure preferences. GAG amide protons are observable by NMR over wide pH and temperature ranges; however, specific solution conditions are required to reduce the exchange rate of the sulfamate and hydroxyl protons and allow their detection by NMR. Building on the vast body of knowledge on detection of hydrogen bonds in peptides and proteins, a variety of methods can be used to identify hydrogen bonds in GAGs including temperature coefficient measurements, evaluation of chemical shift differences between oligo- and monosaccharides, and relative exchange rates measured through line shape analysis and EXSY spectra. Emerging strategies to allow direct detection of hydrogen bonds through heteronuclear couplings offer promise for the future. Molecular dynamic simulations are important in this effort both to predict and confirm hydrogen bond donors and acceptors.

Hydrophobic Amino Acids as Universal Elements of Protein-Induced DNA Structure Deformation

Interaction with the DNA minor groove is a significant contributor to specific sequence recognition in selected families of DNA-binding proteins. Based on a statistical analysis of 3D structures of protein–DNA complexes, we propose that distortion of the DNA minor groove resulting from interactions with hydrophobic amino acid residues is a universal element of protein–DNA recognition. We provide evidence to support this by associating each DNA minor groove-binding amino acid residue with the local dimensions of the DNA double helix using a novel algorithm. The widened DNA minor grooves are associated with high GC content. However, some AT-rich sequences contacted by hydrophobic amino acids (e.g., phenylalanine) display extreme values of minor groove width as well. For a number of hydrophobic amino acids, distinct secondary structure preferences could be identified for residues interacting with the widened DNA minor groove. These results hold even after discarding the most populous families of minor groove-binding proteins.

A topology-based investigation of protein interaction sites using Hydrophobic Cluster Analysis

Hydrophobic clusters, as defined by Hydrophobic Cluster Analysis (HCA), are conditioned binary patterns, made of hydrophobic and non-hydrophobic positions, whose limits fit well those of regular secondary structures. They were proved to be useful for predicting secondary structures in proteins from the only information of a single amino acid sequence and have permitted to assess, in a comprehensive way, the leading role of binary patterns in secondary structure preference towards a particular state. Here, we considered the available experimental 3D structures of protein globular domains to enlarge our previously reported hydrophobic cluster database (HCDB), almost doubling the number of hydrophobic cluster species (each species being defined by a unique binary pattern) that represent the most frequent structural bricks encountered within protein globular domains. We then used this updated HCDB to show that the hydrophobic amino acids of discordant clusters, i.e. those less abundant clusters for which the observed secondary structure is in disagreement with the binary pattern preference of the species to which they belong, are more exposed to solvent and are more involved in protein interfaces than the hydrophobic amino acids of concordant clusters. As amino acid composition differs between concordant/discordant clusters, considering binary patterns may be used to gain novel insights into key features of protein globular domain cores and surfaces. It can also provide useful information on possible conformational plasticity, including disorder to order transitions.

Toward Ab Initio Protein Folding: Inherent Secondary Structure Propensity of Short Peptides from the Bioinformatics and Quantum-Chemical Perspective.

By combining bioinformatics with quantum-chemical calculations, we attempt to address quantitatively some of the physical principles underlying protein folding. The former allowed us to identify tripeptide sequences in existing protein three-dimensional structures with a strong preference for either helical or extended structure. The selected representatives of pro-helical and pro-extended sequences were converted into "isolated" tripeptides-capped at N- and C-termini-and these were subjected to an extensive conformational sampling and geometry optimization (typically thousands to tens of thousands of conformers for each tripeptide). For each conformer, the QM(DFT-D3)/COSMO-RS free-energy value was then calculated, Gconf(solv). The Δ Gconf(solv) is expected to provide an objective, unbiased, and quantitatively accurate measure of the conformational preference of the particular tripeptide sequence. It has been shown that irrespective of the helical vs extended preferences of the selected tripeptide sequences in context of the protein, most of the low-energy conformers of isolated tripeptides prefer the R-helical structure. Nevertheless, pro-helical tripeptides show slightly stronger helix preference than their pro-extended counterparts. Furthermore, when the sampling is repeated in the presence of a partner tripeptide to mimic the situation in a β-sheet, pro-extended tripeptides (exemplified by the VIV) show a larger free-energy benefit than pro-helical tripeptides (exemplified by the EAM). This effect is even more pronounced in a hydrophobic solvent, which mimics the less polar parts of a protein. This is in line with our bioinformatic results showing that the majority of pro-extended tripeptides are hydrophobic. The preference for a specific secondary structure by the studied tripeptides is thus governed by the plasticity to adopt to its environment. In addition, we show that most of the "naturally occurring" conformations of tripeptide sequences, i.e., those found in existing three-dimensional protein structures, are within ∼10 kcal·mol-1 from their global minima. In summary, our "ab initio" data suggest that complex protein structures may start to emerge already at the level of their small oligopeptidic units, which is in line with a hierarchical nature of protein folding.

Order in Disorder as Observed by the "Hydrophobic Cluster Analysis" of Protein Sequences.

Hydrophobic cluster analysis (HCA) is an original approach for protein sequence analysis, which provides access to the foldable repertoire of the protein universe, including yet unannotated protein segments (“dark proteome”). Foldable segments correspond to ordered regions, as well as to intrinsically disordered regions (IDRs) undergoing disorder to order transitions. In this review, how HCA can be used to give insight into this last category of foldable segments is illustrated, with examples matching known 3D structures. After reviewing the HCA principles, examples of short foldable segments are given, which often contain short linear motifs, typically matching hydrophobic clusters. These segments become ordered upon contact with partners, with secondary structure preferences generally corresponding to those observed in the 3D structures within the complexes. Such small foldable segments are sometimes larger than the segments of known 3D structures, including flanking hydrophobic clusters that may be critical for interaction specificity or regulation, as well as intervening sequences allowing fuzziness. Cases of larger conditionally disordered domains are also presented, with lower density in hydrophobic clusters than well‐folded globular domains or with exposed hydrophobic patches, which are stabilized by interaction with partners.

Computational Studies of Intrinsically Disordered Proteins.

Frequently elusive to experimental characterizations, intrinsically disordered proteins (IDPs) can be probed using molecular dynamics to provide detailed insight into their complex structure, dynamics, and function. However, previous computational studies were often found to disagree with experiment due to either force field biases or insufficient sampling. In this study, nine unstructured short peptides and the HIV-1 Rev protein were simulated and extended to microseconds to assess these limitations in IDP simulations. In short peptide simulations, a tested IDP-specific force field ff14IDPSFF outperforms its generic counterpart ff14SB as agreement of simulated NMR observables with experiment improves, though its advantages are not clear-cut in apo Rev simulations. It is worth noting that sampling is probably still not sufficient in the ff14SB simulations of apo Rev even if 10 ms have been collected. This indicates that enhanced sampling techniques would greatly benefit IDP simulations. Finally, detailed structural analyses of apo Rev conformations demonstrate different secondary structural preferences between ff14SB (helical) and ff14IDPSFF (random coil). A natural next step is to ask a more quantitative question: whether ff14SB is too ordered or ff14IDPSFF is too disordered in simulations of more complex IDPs such as Rev. This requires further quantitative analyses both experimentally and computationally.

SSMART: sequence-structure motif identification for RNA-binding proteins.

RNA-binding proteins (RBPs) regulate every aspect of RNA metabolism and function. There are hundreds of RBPs encoded in the eukaryotic genomes, and each recognize its RNA targets through a specific mixture of RNA sequence and structure properties. For most RBPs, however, only a primary sequence motif has been determined, while the structure of the binding sites is uncharacterized. We developed SSMART, an RNA motif finder that simultaneously models the primary sequence and the structural properties of the RNA targets sites. The sequence-structure motifs are represented as consensus strings over a degenerate alphabet, extending the IUPAC codes for nucleotides to account for secondary structure preferences. Evaluation on synthetic data showed that SSMART is able to recover both sequence and structure motifs implanted into 3'UTR-like sequences, for various degrees of structured/unstructured binding sites. In addition, we successfully used SSMART on high-throughput in vivo and in vitro data, showing that we not only recover the known sequence motif, but also gain insight into the structural preferences of the RBP. SSMART is freely available at https://ohlerlab.mdc-berlin.de/software/SSMART_137/. Supplementary data are available at Bioinformatics online.

Primary and Secondary Structure Preference of Hydrogen Exchange

Primary and Secondary Structure Preference of Hydrogen Exchange

MobiDB 3.0: more annotations for intrinsic disorder, conformational diversity and interactions in proteins.

The MobiDB (URL: mobidb.bio.unipd.it) database of protein disorder and mobility annotations has been significantly updated and upgraded since its last major renewal in 2014. Several curated datasets for intrinsic disorder and folding upon binding have been integrated from specialized databases. The indirect evidence has also been expanded to better capture information available in the PDB, such as high temperature residues in X-ray structures and overall conformational diversity. Novel nuclear magnetic resonance chemical shift data provides an additional experimental information layer on conformational dynamics. Predictions have been expanded to provide new types of annotation on backbone rigidity, secondary structure preference and disordered binding regions. MobiDB 3.0 contains information for the complete UniProt protein set and synchronization has been improved by covering all UniParc sequences. An advanced search function allows the creation of a wide array of custom-made datasets for download and further analysis. A large amount of information and cross-links to more specialized databases are intended to make MobiDB the central resource for the scientific community working on protein intrinsic disorder and mobility.

Effects of forcefield and sampling method in all-atom simulations of inherently disordered proteins: Application to conformational preferences of human amylin

Although several computational modelling studies have investigated the conformational behaviour of inherently disordered protein (IDP) amylin, discrepancies in identifying its preferred solution conformations still exist between various forcefields and sampling methods used. Human islet amyloid polypeptide has long been a subject of research, both experimentally and theoretically, as the aggregation of this protein is believed to be the lead cause of type-II diabetes. In this work, we present a systematic forcefield assessment using one of the most advanced non-biased sampling techniques, Replica Exchange with Solute Tempering (REST2), by comparing the secondary structure preferences of monomeric amylin in solution. This study also aims to determine the ability of common forcefields to sample a transition of the protein from a helical membrane bound conformation into the disordered solution state of amylin. Our results demonstrated that the CHARMM22* forcefield showed the best ability to sample multiple conformational states inherent for amylin. It is revealed that REST2 yielded results qualitatively consistent with experiments and in quantitative agreement with other sampling methods, however far more computationally efficiently and without any bias. Therefore, combining an unbiased sampling technique such as REST2 with a vigorous forcefield testing could be suggested as an important step in developing an efficient and robust strategy for simulating IDPs.

Protein folding, misfolding and aggregation: The importance of two-electron stabilizing interactions.

Proteins associated with neurodegenerative diseases are highly pleiomorphic and may adopt an all-α-helical fold in one environment, assemble into all-β-sheet or collapse into a coil in another, and rapidly polymerize in yet another one via divergent aggregation pathways that yield broad diversity of aggregates’ morphology. A thorough understanding of this behaviour may be necessary to develop a treatment for Alzheimer’s and related disorders. Unfortunately, our present comprehension of folding and misfolding is limited for want of a physicochemical theory of protein secondary and tertiary structure. Here we demonstrate that electronic configuration and hyperconjugation of the peptide amide bonds ought to be taken into account to advance such a theory. To capture the effect of polarization of peptide linkages on conformational and H-bonding propensity of the polypeptide backbone, we introduce a function of shielding tensors of the Cα atoms. Carrying no information about side chain-side chain interactions, this function nonetheless identifies basic features of the secondary and tertiary structure, establishes sequence correlates of the metamorphic and pH-driven equilibria, relates binding affinities and folding rate constants to secondary structure preferences, and manifests common patterns of backbone density distribution in amyloidogenic regions of Alzheimer’s amyloid β and tau, Parkinson’s α-synuclein and prions. Based on those findings, a split-intein like mechanism of molecular recognition is proposed to underlie dimerization of Aβ, tau, αS and PrPC, and divergent pathways for subsequent association of dimers are outlined; a related mechanism is proposed to underlie formation of PrPSc fibrils. The model does account for: (i) structural features of paranuclei, off-pathway oligomers, non-fibrillar aggregates and fibrils; (ii) effects of incubation conditions, point mutations, isoform lengths, small-molecule assembly modulators and chirality of solid-liquid interface on the rate and morphology of aggregation; (iii) fibril-surface catalysis of secondary nucleation; and (iv) self-propagation of infectious strains of mammalian prions.

SsHMM: extracting intuitive sequence-structure motifs from high-throughput RNA-binding protein data.

RNA-binding proteins (RBPs) play an important role in RNA post-transcriptional regulation and recognize target RNAs via sequence-structure motifs. The extent to which RNA structure influences protein binding in the presence or absence of a sequence motif is still poorly understood. Existing RNA motif finders either take the structure of the RNA only partially into account, or employ models which are not directly interpretable as sequence-structure motifs. We developed ssHMM, an RNA motif finder based on a hidden Markov model (HMM) and Gibbs sampling which fully captures the relationship between RNA sequence and secondary structure preference of a given RBP. Compared to previous methods which output separate logos for sequence and structure, it directly produces a combined sequence-structure motif when trained on a large set of sequences. ssHMM’s model is visualized intuitively as a graph and facilitates biological interpretation. ssHMM can be used to find novel bona fide sequence-structure motifs of uncharacterized RBPs, such as the one presented here for the YY1 protein. ssHMM reaches a high motif recovery rate on synthetic data, it recovers known RBP motifs from CLIP-Seq data, and scales linearly on the input size, being considerably faster than MEMERIS and RNAcontext on large datasets while being on par with GraphProt. It is freely available on Github and as a Docker image.

A-to-I RNA editing is developmentally regulated and generally adaptive for sexual reproduction in Neurospora crassa

Although fungi lack adenosine deaminase acting on RNA (ADAR) enzymes, adenosine to inosine (A-to-I) RNA editing was reported recently in Fusarium graminearum during sexual reproduction. In this study, we profiled the A-to-I editing landscape and characterized its functional and adaptive properties in the model filamentous fungus Neurospora crassa A total of 40,677 A-to-I editing sites were identified, and approximately half of them displayed stage-specific editing or editing levels at different sexual stages. RNA-sequencing analysis with the Δstc-1 and Δsad-1 mutants confirmed A-to-I editing occurred before ascus development but became more prevalent during ascosporogenesis. Besides fungal-specific sequence and secondary structure preference, 63.5% of A-to-I editing sites were in the coding regions and 81.3% of them resulted in nonsynonymous recoding, resulting in a significant increase in the proteome complexity. Many genes involved in RNA silencing, DNA methylation, and histone modifications had extensive recoding, including sad-1, sms-3, qde-1, and dim-2. Fifty pseudogenes harbor premature stop codons that require A-to-I editing to encode full-length proteins. Unlike in humans, nonsynonymous editing events in N. crassa are generally beneficial and favored by positive selection. Almost half of the nonsynonymous editing sites in N. crassa are conserved and edited in Neurospora tetrasperma Furthermore, hundreds of them are conserved in F. graminearum and had higher editing levels. Two unknown genes with editing sites conserved between Neurospora and Fusarium were experimentally shown to be important for ascosporogenesis. This study comprehensively analyzed A-to-I editing in N. crassa and showed that RNA editing is stage-specific and generally adaptive, and may be functionally related to repeat induced point mutation and meiotic silencing by unpaired DNA.