Secondary Structure Propensities Research Articles

CORDAX web server: an online platform for the prediction and 3D visualization of aggregation motifs in protein sequences.

Proteins, the molecular workhorses of biological systems, execute a multitude of critical functions dictated by their precise three-dimensional structures. In a complex and dynamic cellular environment, proteins can undergo misfolding, leading to the formation of aggregates that take up various forms, including amorphous and ordered aggregation in the shape of amyloid fibrils. This phenomenon is closely linked to a spectrum of widespread debilitating pathologies, such as Alzheimer's disease, Parkinson's disease, type-II diabetes, and several other proteinopathies, but also hampers the engineering of soluble agents, as in the case of antibody development. As such, the accurate prediction of aggregation propensity within protein sequences has become pivotal due to profound implications in understanding disease mechanisms, as well as in improving biotechnological and therapeutic applications. We previously developed Cordax, a structure-based predictor that utilizes logistic regression to detect aggregation motifs in protein sequences based on their structural complementarity to the amyloid cross-beta architecture. Here, we present a dedicated web server interface for Cordax. This online platform combines several features including detailed scoring of sequence aggregation propensity, as well as 3D visualization with several customization options for topology models of the structural cores formed by predicted aggregation motifs. In addition, information is provided on experimentally determined aggregation-prone regions that exhibit sequence similarity to predicted motifs, scores, and links to other predictor outputs, as well as simultaneous predictions of relevant sequence propensities, such as solubility, hydrophobicity, and secondary structure propensity. The Cordax webserver is freely accessible at https://cordax.switchlab.org/.

HYPK: A marginally disordered protein sensitive to charge decoration

Intrinsically disordered proteins (IDPs) that lie close to the empirical boundary separating IDPs and folded proteins in Uversky's charge-hydropathy plot may behave as "marginal IDPs" and sensitively switch conformation upon changes in environment (temperature, crowding, and charge screening), sequence, or both. In our search for such a marginal IDP, we selected Huntingtin-interacting protein K (HYPK) near that boundary as a candidate; PKIα, also near that boundary, has lower secondary structure propensity; and Crk1, just across the boundary on the folded side, has higher secondary structure propensity. We used a qualitative Förster resonance energy transfer-based assay together with circular dichroism to simultaneously probe global and local conformation. HYPK shows several unique features indicating marginality: a cooperative transition in end-to-end distance with temperature, like Crk1 and folded proteins, but unlike PKIα; enhanced secondary structure upon crowding, in contrast to Crk1 and PKIα; and a cross-over from salt-induced expansion to compaction at high temperature, likely due to a structure-to-disorder transition not seen in Crk1 and PKIα. We then tested HYPK's sensitivity to charge patterning by designing charge-flipped variants including two specific sequences with identical amino acid composition that markedly differ in their predicted size and response to salt. The experimentally observed trends, also including mutants of PKIα, verify the predictions from sequence charge decoration metrics. Marginal proteins like HYPK show features of both folded and disordered proteins that make them sensitive to physicochemical perturbations and structural control by charge patterning.

SERT-StructNet: Protein secondary structure prediction method based on multi-factor hybrid deep model

Protein secondary structure prediction (PSSP) is a pivotal research endeavour that plays a crucial role in the comprehensive elucidation of protein functions and properties. Current prediction methodologies are focused on deep-learning techniques, particularly focusing on multi-factor features. Diverging from existing approaches, in this study, we placed special emphasis on the effects of amino acid properties and protein secondary structure propensity scores (SSPs) on secondary structure during the meticulous selection of multi-factor features. This differential feature-selection strategy results in a distinctive and effective amalgamation of the sequence and property features. To harness these multi-factor features optimally, we introduced a hybrid deep feature extraction model. The model initially employs mechanisms such as dilated convolution (D-Conv) and a channel attention network (SENet) for local feature extraction and targeted channel enhancement. Subsequently, a combination of recurrent neural network variants (BiGRU and BiLSTM), along with a transformer module, was employed to achieve global bidirectional information consideration and feature enhancement. This approach to multi-factor feature input and multi-level feature processing enabled a comprehensive exploration of intricate associations among amino acid residues in protein sequences, yielding a Q3 accuracy of 84.9% and an Sov score of 85.1%. The overall performance surpasses that of the comparable methods. This study introduces a novel and efficient method for determining the PSSP domain, which is poised to deepen our understanding of the practical applications of protein molecular structures.

Intrinsically disordered Pseudomonas chaperone FapA slows down the fibrillation of major biofilm-forming functional amyloid FapC.

Functional bacterial amyloids play a crucial role in the formation of biofilms, which mediate chronic infections and contribute to antimicrobial resistance. This study focuses on the FapC amyloid fibrillar protein from Pseudomonas, a major contributor to biofilm formation. We investigate the initial steps of FapC amyloid formation and the impact of the chaperone-like protein FapA on this process. Using solution nuclear magnetic resonance (NMR), we recently showed that both FapC and FapA are intrinsically disordered proteins (IDPs). Here, the secondary structure propensities (SSPs) are compared to alphafold (DeepMind, protein structure prediction tool/algorithm: https://alphafold.ebi.ac.uk/) models. We further demonstrate that the FapA chaperone interacts with FapC and significantly slows down the formation of FapC fibrils. Our NMR titrations reveal ~ 18% of the resonances show FapA-induced chemical shift perturbations (CSPs), which has not been previously observed, the largest being for A82, N201, C237, C240, A241, and G245. These sites may suggest a specific interaction site and/or hotspots of fibrillation inhibition/control interface at the repeat-1 (R1)/loop-2 (L2) and L2/R3 transition areas and at the C-terminus of FapC. Remarkably, ~ 90% of FapA NMR signals exhibit substantial CSPs upon titration with FapC, the largest being for S63, A69, A80, and I92. A temperature-dependent effect of FapA was observed on FapC by thioflavin T (ThT) and NMR experiments. This study provides a detailed understanding of the interaction between the FapA and FapC, shedding light on the regulation and slowing down of amyloid formation, and has important implications for the development of therapeutic strategies targeting biofilms and associated infections.

What are the minimal folding seeds in proteins? Experimental and theoretical assessment of secondary structure propensities of small peptide fragments.

Certain peptide sequences, some of them as short as amino acid triplets, are significantly overpopulated in specific secondary structure motifs in folded protein structures. For example, 74% of the EAM triplet is found in α-helices, and only 3% occurs in the extended parts of proteins (typically β-sheets). In contrast, other triplets (such as VIV and IYI) appear almost exclusively in extended parts (79% and 69%, respectively). In order to determine whether such preferences are structurally encoded in a particular peptide fragment or appear only at the level of a complex protein structure, NMR, VCD, and ECD experiments were carried out on selected tripeptides: EAM (denoted as pro-'α-helical' in proteins), KAM(α), ALA(α), DIC(α), EKF(α), IYI(pro-β-sheet or more generally, pro-extended), and VIV(β), and the reference α-helical CATWEAMEKCK undecapeptide. The experimental data were in very good agreement with extensive quantum mechanical conformational sampling. Altogether, we clearly showed that the pro-helical vs. pro-extended propensities start to emerge already at the level of tripeptides and can be fully developed at longer sequences. We postulate that certain short peptide sequences can be considered minimal "folding seeds". Admittedly, the inherent secondary structure propensity can be overruled by the large intramolecular interaction energies within the folded and compact protein structures. Still, the correlation of experimental and computational data presented herein suggests that the secondary structure propensity should be considered as one of the key factors that may lead to understanding the underlying physico-chemical principles of protein structure and folding from the first principles.

Solution-state NMR assignment and secondary structure analysis of the monomeric Pseudomonas biofilm-forming functional amyloid accessory protein FapA.

FapA is an accessory protein within the biofilm forming functional bacterial amyloid related fap-operon in Pseudomonas, and maybe a chaperone for FapC controlling its fibrillization. To allow further structural analysis, here we present a complete sequential assignment of 1Hamide, 13Cα, 13Cβ, and 15N NMR resonances for the functional form of the monomeric soluble FapA protein, comprising amino acids between 29 and 152. From these observed chemical shifts, the secondary structure propensities (SSPs) were determined. FapA predominantly adopts a random coil conformation, however, we also identified small propensities for α-helical and β-strand conformations. Notably, these observed SSPs are smaller compared to the ones we recently observed for the monomeric soluble FapC protein. These NMR results provide valuable insights into the activity of FapA in functional amyloid formation and regulation, that will also aid developing strategies targeting amyloid formation within biofilms and addressing chronic infections.

Solution NMR Backbone Assignment of the C-Terminal Region of Human Dynein Light Intermediate Chain 2 (LIC2-C) Unveils Structural Resemblance with Its Homologue LIC1-C.

Dynein, a homodimeric protein complex, plays a pivotal role in retrograde transportation along microtubules within cells. It consists of various subunits, among which the light intermediate chain (LIC) performs diverse functions, including cargo adaptor binding. In contrast to the vertebrate LIC homolog LIC1, LIC2 has received relatively limited characterization thus far, despite partially orthogonal functional roles. In this study, we present a near-to-complete backbone NMR chemical shift assignment of the C-terminal region of the light intermediate chain 2 of human dynein 1 (LIC2-C). We perform a comparative analysis of the secondary structure propensity of LIC2-C with the one previously reported for LIC1-C and show that the two transient helices in LIC1 that interact with motor adaptors are also present in LIC2.

YGPS-P: A Yeast-Based Peptidome Screen for Studying Quality Control-Associated Proteolysis.

Quality control-associated proteolysis (QCAP) is a fundamental mechanism that maintains cellular homeostasis by eliminating improperly folded proteins. In QCAP, the exposure of normally hidden cis-acting protein sequences, termed degrons, triggers misfolded protein ubiquitination, resulting in their elimination by the proteasome. To identify the landscape of QCAP degrons and learn about their unique features we have developed an unbiased screening method in yeast, termed yGPS-P, which facilitates the determination of thousands of proteome-derived sequences that enhance proteolysis. Here we describe the fundamental features of the yGPS-P method and provide a detailed protocol for its use as a tool for degron search. This includes the cloning of a synthetic peptidome library in a fluorescence-based reporter system, and data acquisition, which entails the combination of Fluorescence-Activated Cell Sorting (FACS) and Next-Generation Sequencing (NGS). We also provide guidelines for data extraction and analysis and for the application of a machine-learning algorithm that established the evolutionarily conserved amino acid preferences and secondary structure propensities of QCAP degrons.

Solution-state NMR assignment and secondary structure propensity of the full length and minimalistic-truncated prefibrillar monomeric form of biofilm forming functional amyloid FapC from Pseudomonas aeruginosa.

Functional bacterial amyloids provide structural scaffolding to bacterial biofilms. In contrast to the pathological amyloids, they have a role in vivo and are tightly regulated. Their presence is essential to the integrity of the bacterial communities surviving in biofilms and may cause serious health complications. Targeting amyloids in biofilms could be a novel approach to prevent chronic infections. However, structural information is very scarce on them in both soluble monomeric and insoluble fibrillar forms, hindering our molecular understanding and strategies to fight biofilm related diseases. Here, we present solution-state NMR assignment of 250 amino acid long biofilm-forming functional-amyloid FapC from Pseudomonas aeruginosa. We studied full-length (FL) and shorter minimalistic-truncated (L2R3C) FapC constructs without the signal-sequence that is required for secretion. 91% and 100% backbone NH resonance assignments for FL and L2R3C constructs, respectively, indicate that soluble monomeric FapC is predominantly disordered, with sizeable secondary structural propensities mostly as PP2 helices, but also as α-helices and β-sheets highlighting hotspots for fibrillation initiation interface. A shorter construct showing almost identical NMR chemical shifts highlights the promise of utilizing it for more demanding solid-state NMR studies that require methods to alleviate signal redundancy due to almost identical repeat units. This study provides key NMR resonance assignments for future structural studies of soluble, pre-fibrillar and fibrillar forms of FapC.

1H, 15N, and 13C backbone and side chain resonance assignments of the cold shock domain of the Arabidopsis thaliana glycine-rich protein AtGRP2.

AtGRP2 (Arabidopsis thaliana glycine-rich protein 2) is a 19-kDa RNA-binding glycine-rich protein that regulates key processes in A. thaliana. AtGRP2 is a nucleo-cytoplasmic protein with preferential expression in developing tissues, such as meristems, carpels, anthers, and embryos. AtGRP2 knockdown leads to an early flowering phenotype. In addition, AtGRP2-silenced plants exhibit a reduced number of stamens and abnormal development of embryos and seeds, suggesting its involvement in plant development. AtGRP2 expression is highly induced by cold and abiotic stresses, such as high salinity. Moreover, AtGRP2 promotes double-stranded DNA/RNA denaturation, indicating its role as an RNA chaperone during cold acclimation. AtGRP2 is composed of an N-terminal cold shock domain (CSD) followed by a C-terminal flexible region containing two CCHC-type zinc fingers interspersed with glycine-rich sequences. Despite its functional relevance in flowering time regulation and cold adaptation, the molecular mechanisms employed by AtGRP2 are largely unknown. To date, there is no structural information regarding AtGRP2 in the literature. Here, we report the 1H, 15N, and 13C backbone and side chain resonance assignments, as well as the chemical shift-derived secondary structure propensities, of the N-terminal cold shock domain of AtGRP2, encompassing residues 1-90. These data provide a framework for AtGRP2-CSD three-dimensional structure, dynamics, and RNA binding specificity investigation, which will shed light on its mechanism of action.

Early Selection of the Amino Acid Alphabet Was Adaptively Shaped by Biophysical Constraints of Foldability.

Whereas modern proteins rely on a quasi-universal repertoire of 20 canonical amino acids (AAs), numerous lines of evidence suggest that ancient proteins relied on a limited alphabet of 10 "early" AAs and that the 10 "late" AAs were products of biosynthetic pathways. However, many nonproteinogenic AAs were also prebiotically available, which begs two fundamental questions: Why do we have the current modern amino acid alphabet and would proteins be able to fold into globular structures as well if different amino acids comprised the genetic code? Here, we experimentally evaluate the solubility and secondary structure propensities of several prebiotically relevant amino acids in the context of synthetic combinatorial 25-mer peptide libraries. The most prebiotically abundant linear aliphatic and basic residues were incorporated along with or in place of other early amino acids to explore these alternative sequence spaces. The results show that foldability was likely a critical factor in the selection of the canonical alphabet. Unbranched aliphatic amino acids were purged from the proteinogenic alphabet despite their high prebiotic abundance because they generate polypeptides that are oversolubilized and have low packing efficiency. Surprisingly, we find that the inclusion of a short-chain basic amino acid also decreases polypeptides' secondary structure potential, for which we suggest a biophysical model. Our results support the view that, despite lacking basic residues, the early canonical alphabet was remarkably adaptive at supporting protein folding and explain why basic residues were only incorporated at a later stage of protein evolution.

Coarse-grained RNA simulations with concerted c2'/c3'-endo sugar pucker transitions.

All-atom molecular dynamic simulations are generally restricted by the time scale that can be sampled. To address this issue, various coarse-grained RNA models have been developed. These models often assume the ribose, a 5 membered ring, is fixed in only one conformation, typically the 3’-endo found in A-form helices. The models neglect the 2’-endo conformation that can be found in B-form helices and other RNA structures and is known to influence ion binding and catalytic function in addition to secondary structure propensity. Accordingly, we have developed a coarse-grained RNA force field to include transitions between the two sugar pucker states in order to accurately reproduce RNA structures and thermodynamics. To model the sugar pucker, we train a coarse-grained collective variable that distinguishes between the two states. Using this collective variable, we interpolate between two sets of force field parameters to properly reflect the structural differences between the two conformational states. The parameters of the entire model are optimized against RNA structures utilizing our contrastive divergence algorithm. Our coarse-grained RNA model opens up the opportunities to study complex RNA dynamics especially those coupled to sugar pucker transitions.

The influence of random-coil chemical shifts on the assessment of structural propensities in folded proteins and IDPs.

In studying secondary structural propensities of proteins by nuclear magnetic resonance (NMR) spectroscopy, secondary chemical shifts (SCSs) serve as the primary atomic scale observables. For SCS calculation, the selection of an appropriate random coil chemical shift (RCCS) dataset is a crucial step, especially when investigating intrinsically disordered proteins (IDPs). The scientific literature is abundant in such datasets, however, the effect of choosing one over all the others in a concrete application has not yet been studied thoroughly and systematically. Hereby, we review the available RCCS prediction methods and to compare them, we conduct statistical inference by means of the nonparametric sum of ranking differences and comparison of ranks to random numbers (SRD-CRRN) method. We try to find the RCCS predictors best representing the general consensus regarding secondary structural propensities. The existence and the magnitude of resulting differences on secondary structure determination under varying sample conditions (temperature, pH) are demonstrated and discussed for globular proteins and especially IDPs.

UnderstandingRamachandranplot for dipeptide: A density functional theory and information‐theoreticapproach study

AbstractThe Ramachandran plot in biochemistry visualizes the propensity of amino acid residues to assume different secondary structures. It can be obtained by different approaches such as bioinformatics and molecular dynamics. In this work, we systematically scan the two single bonds around the α‐carbon of a peptide to generate the three‐dimensional potential energy surface and then project it onto the coordinate plane to generate the Ramachandran plot. Using the two schemes of the total energy partition and information‐theoretic approach in density functional theory, we analyze the plot and find out that the dominant contributor to determine the local minima of secondary structures, especially β‐sheets, in the Ramachandran plot is the electrostatic interaction, whereas steric and exchange‐correlation contributions play minor yet indispensable roles, especially for determining α‐helixes. As the generalization of our prior studies for systems with one rotatable bond, our current results confirm what we yielded before from the viewpoint of energetic contributions, and at meanwhile provide an in‐depth understanding about the nature and origin of secondary structure propensities from the Ramachandran plot.

Conserved degronome features governing quality control associated proteolysis

The eukaryotic proteome undergoes constant surveillance by quality control systems that either sequester, refold, or eliminate aberrant proteins by ubiquitin-dependent mechanisms. Ubiquitin-conjugation necessitates the recognition of degradation determinants, termed degrons, by their cognate E3 ubiquitin-protein ligases. To learn about the distinctive properties of quality control degrons, we performed an unbiased peptidome stability screen in yeast. The search identify a large cohort of proteome-derived degrons, some of which exhibited broad E3 ligase specificity. Consequent application of a machine-learning algorithm establishes constraints governing degron potency, including the amino acid composition and secondary structure propensities. According to the set criteria, degrons with transmembrane domain-like characteristics are the most probable sequences to act as degrons. Similar quality control degrons are present in viral and human proteins, suggesting conserved degradation mechanisms. Altogether, the emerging data indicate that transmembrane domain-like degron features have been preserved in evolution as key quality control determinants of protein half-life.

1H, 15N and 13C backbone resonance assignments of the acidic domain of the human MDM2 protein.

The human MDM2 protein regulates the tumor suppressor protein p53 by restricting its transcriptional activity and by promoting p53 degradation. MDM2 is ubiquitously expressed, with its overexpression implicated in many forms of cancer. The inhibitory effects of MDM2 on p53 have been shown to involve its N-terminal p53-binding domain and its C-terminal RING domain. The presence of an intact central acidic domain of MDM2 has also been shown to regulate p53 ubiquitination, with this domain shown to directly interact with the p53 DNA-binding domain to regulate the DNA binding activity of p53. To date, little structural information has been obtained for the MDM2 acidic domain. Thus, to gain insight into the structure and function relationship of this region, we have applied solution-state NMR spectroscopy to characterize the segment of MDM2 spanning residues 215-300. These boundaries for the acidic domain were determined on the basis of consensus observed in multiple sequence alignment. Here, we report the 1H, 15N and 13C backbone and 13Cβ chemical shift assignments and steady-state {1H}-15N heteronuclear NOE enhancement factors as a function of residue for the acidic domain of MDM2. We show that this domain exhibits the hallmarks of being a disordered protein, on the basis both of assigned chemical shifts and residue-level backbone dynamics, with localized variation in secondary structure propensity inferred from chemical shift analysis.

Toward Accurate Coarse-Grained Simulations of Disordered Proteins and Their Dynamic Interactions.

Intrinsically disordered proteins (IDPs) play crucial roles in cellular regulatory networks and are now recognized to often remain highly dynamic even in specific interactions and assemblies. Accurate description of these dynamic interactions is extremely challenging using atomistic simulations because of the prohibitive computational cost. Efficient coarse-grained approaches could offer an effective solution to overcome this bottleneck if they could provide an accurate description of key local and global properties of IDPs in both unbound and bound states. The recently developed hybrid-resolution (HyRes) protein model has been shown to be capable of providing a semiquantitative description of the secondary structure propensities of IDPs. Here, we show that greatly improved description of global structures and transient interactions can be achieved by introducing a solvent-accessible surface area-based implicit solvent term followed by reoptimization of effective interaction strengths. The new model, termed HyRes II, can semiquantitatively reproduce a wide range of local and global structural properties of a set of IDPs of various lengths and complexities. It can also distinguish the level of compaction between folded proteins and IDPs. In particular, applied to the disordered N-terminal transactivation domain (TAD) of tumor suppressor p53, HyRes II is able to recapitulate various nontrivial structural properties compared to experimental results, some of them to a level of accuracy that is almost comparable to results from atomistic explicit solvent simulations. Furthermore, we demonstrate that HyRes II can be used to simulate the dynamic interactions of TAD with the DNA-binding domain of p53, generating structural ensembles that are highly consistent with existing NMR data. We anticipate that HyRes II will provide an efficient and relatively reliable tool toward accurate coarse-grained simulations of dynamic protein interactions.

Integrative Conformational Ensembles of Sic1 Using Different Initial Pools and Optimization Methods

Intrinsically disordered proteins play key roles in regulatory protein interactions, but their detailed structural characterization remains challenging. Here we calculate and compare conformational ensembles for the disordered protein Sic1 from yeast, starting from initial ensembles that were generated either by statistical sampling of the conformational landscape, or by molecular dynamics simulations. Two popular, yet contrasting optimization methods were used, ENSEMBLE and Bayesian Maximum Entropy, to achieve agreement with experimental data from nuclear magnetic resonance, small-angle X-ray scattering and single-molecule Förster resonance energy transfer. The comparative analysis of the optimized ensembles, including secondary structure propensity, inter-residue contact maps, and the distributions of hydrogen bond and pi interactions, revealed the importance of the physics-based generation of initial ensembles. The analysis also provides insights into designing new experiments that report on the least restrained features among the optimized ensembles. Overall, differences between ensembles optimized from different priors were greater than when using the same prior with different optimization methods. Generating increasingly accurate, reliable and experimentally validated ensembles for disordered proteins is an important step towards a mechanistic understanding of their biological function and involvement in various diseases.

Possible Co-Evolution of Polyglutamine and Polyproline in Huntingtin Protein: Proline-Rich Domain as Transient Folding Chaperone.

Huntington's disease is an inherited neurodegenerative disorder caused by the overduplication of CAG repeats in the Huntingtin gene. Recent findings revealed that among the orthologs, the expansion of CAG repeats (polyQ) in the Huntingtin gene occurs in tandem with the duplication of CCG repeats (polyP). However, the molecular mechanism of this possible co-evolution remains unknown. We examined the structures of Huntingtin exon 1 (HttEx1) from six species along with five designed mutants. We found that the polyP segments "chaperone" the rest of the HttEx1 by forming ad hoc polyP binding grooves. Such a process elongates the otherwise poorly solvated polyQ domain, while modulating its secondary structure propensity from β-strands to α-helices. This chaperoning effect is achieved mostly through transient hydrogen bond interactions between polyP and the rest of HttEx1, resulting in a striking golden ratio of ∼2:1 between the chain lengths of polyQ and polyP.

Backbone resonance assignments and dynamics of S. cerevisiae SERF.

Abnormal protein aggregation and precipitation are associated with the perturbation of cellular function and underlie a variety of neurodegenerative diseases. S. cerevisiae SERF (ScSERF), a homolog of modifier of aggregation-4 (MOAG-4) and small EDRK-rich factor protein (SERF1a) is highly conserved and discovered as an enhancer of amyloid formation of Aβ40 and α-synuclein both in vitro and in vivo. However, the detailed molecular mechanism whereby ScSERF and its homologs accelerate amyloid formation is not well known yet. Herein, we present the 1H, 15N and 13C NMR assignments of the 68 amino acids long ScSERF. Although ScSERF displays a very high degree of disorder, secondary chemical shifts of Cα, Cβ, 15N{1H}-NOE values and the residue-specific secondary structure propensity (SSP) scores indicate the segment spanning residues 36E-65K has a strong helical propensity. This work sets the stage for further detailed structural and dynamic investigations of ScSERF and the molecular mechanism it utilizes in accelerating amyloid formation.