A library of coiled-coil domains: from regular bundles to peculiar twists

Genome-wide identification of the WD40 protein family and functional characterization of AaTTG1 in Artemisia annua

Sweet wormwood (Artemisia annua), an annual herb belonging to the Compositae family, is the main source of the potent anti-malarial drug artemisinin, which is mainly produced in glandular trichomes of A. annua leaves. The WD40 protein family is one of the largest protein families in eukaryotes and plays crucial roles in regulating plant growth and development, stress responses, and secondary metabolite biosynthesis. However, WD40 proteins have not been comprehensively identified in A. annua. In this study, we identified 236 WD40 proteins in the A. annua genome and examined their conserved domains, motifs, and cis-regulatory elements, gene structures, chromosomal distribution, duplication events of their encoding genes. Furthermore, we isolated and characterized TRANSPARENT TESTA GLABROUS 1 (AaTTG1), a homolog of Arabidopsis TTG1, and confirmed that AaTTG1 was localized to the nucleus and cytoplasm. Indeed, AaTTG1 can rescue the glabrous phenotype of the Arabidopsis ttg1 mutant and enhanced trichome production when heterologously expressed in wild-type Arabidopsis plants. Transgenic A. annua lines overexpressing AaTTG1 displayed a significantly higher density of glandular trichomes and higher artemisinin contents. Transgenic A. annua lines with inhibited AaTTG1 function had fewer glandular trichomes and lower artemisinin levels. Moreover, we demonstrated that AaTTG1 positively regulates glandular trichome development in A. annua through interactions with AaSPL9. This study thus provides fundamental insights into the role of WD40 proteins in A. annua and introduces a promising approach to enhance artemisinin production by manipulating glandular trichome development in this valuable medicinal plant.

Applicability of AlphaFold2 in the modeling of dimeric, trimeric, and tetrameric coiled-coil domains

Coiled coils are a common protein structural motif involved in cellular functions ranging from mediating protein-protein interactions to facilitating processes such as signal transduction or regulation of gene expression. They are formed by two or more alpha helices that wind around a central axis to form a buried hydrophobic core. Various forms of coiled-coil bundles have been reported, each characterized by the number, orientation, and degree of winding of the constituent helices. This variability is underpinned by short sequence repeats that form coiled coils and whose properties determine both their overall topology and the local geometry of the hydrophobic core. The strikingly repetitive sequence has enabled the development of accurate sequence-based coiled-coil prediction methods; however, the modeling of coiled-coil domains remains a challenging task. In this work, we evaluated the accuracy of AlphaFold2 in modeling coiled-coil domains, both in modeling local geometry and in predicting global topological properties. Furthermore, we show that the prediction of the oligomeric state of coiled-coil bundles can be achieved by using the internal representations of AlphaFold2, with a performance better than any previous state-of-the-art method (code available at https://github.com/labstructbioinf/dc2_oligo).

The structural logic of dynamic signaling in the Escherichia coli serine chemoreceptor

The experimental challenges posed by integral membrane proteins hinder molecular understanding of transmembrane signaling mechanisms. Here, we exploited protein crosslinking assays in living cells to follow conformational and dynamic stimulus signals in Tsr, the Escherichia coli serine chemoreceptor. Tsr mediates serine chemotaxis by integrating transmembrane serine-binding inputs with adaptational modifications of a methylation helix bundle to regulate a signaling kinase at the cytoplasmic tip of the receptor molecule. We created cysteine replacements at Tsr residues adjacent to hydrophobic packing faces of the bundle helices and crosslinked them with a cell-permeable, bifunctional thiol-reagent. We identified an extensively crosslinked dynamic junction midway through the methylation helix bundle that seemed uniquely poised to respond to serine signals. We explored its role in mediating signaling shifts between different packing arrangements of the bundle helices by measuring crosslinking in receptor molecules with apposed pairs of cysteine reporters in each subunit and assessing their signaling behaviors with an in vivo kinase assay. In the absence of serine, the bundle helices evinced compact kinase-ON packing arrangements; in the presence of serine, the dynamic junction destabilized adjacent bundle segments and shifted the bundle to an expanded, less stable kinase-OFF helix-packing arrangement. AlphaFold models of kinase-active Tsr showed a prominent bulge and kink at the dynamic junction that might antagonize stable structure at the receptor tip. Serine stimuli might inhibit kinase activity by shifting the bundle to a less stably-packed conformation that relaxes structural strain at the receptor tip, thereby allowing it to stabilize and freeze kinase activity.

The Structural Logic of Dynamic Signaling in the Escherichia coli Serine Chemoreceptor

The experimental challenges posed by integral membrane proteins hinder molecular understanding of transmembrane signaling mechanisms. Here, we exploited protein crosslinking assays in living cells to follow conformational and dynamic stimulus signals in Tsr, the Escherichia coli serine chemoreceptor. Tsr mediates serine chemotaxis by integrating transmembrane serine-binding inputs with adaptational modifications of a methylation helix bundle to regulate a signaling kinase at the cytoplasmic tip of the receptor molecule. We created a series of cysteine replacements at Tsr residues adjacent to hydrophobic packing faces of the bundle helices and crosslinked them with a cell-permeable, bifunctional thiol-reagent. We identified an extensively crosslinked dynamic junction midway through the methylation helix bundle that seemed uniquely poised to respond to serine signals. We explored its role in mediating signaling shifts between different packing arrangements of the bundle helices by measuring crosslinking in receptor molecules with apposed pairs of cysteine reporters in each subunit and assessing their signaling behaviors with an in vivo kinase assay. In the absence of serine, the bundle helices evinced compact kinase-ON packing arrangements; in the presence of serine, the dynamic junction destabilized adjacent bundle segments and shifted the bundle to an expanded, less stable kinase-OFF helix-packing arrangement. An AlphaFold 3 model of kinase-active Tsr showed a prominent bulge and kink at the dynamic junction that might antagonize stable structure at the receptor tip. Serine stimuli probably inhibit kinase activity by shifting the bundle to a less stably-packed conformation that relaxes structural strain at the receptor tip, thereby freezing kinase activity.

CoCoNat: A Deep Learning-Based Tool for the Prediction of Coiled-coil Domains in Protein Sequences

Coiled-coil domains (CCDs) are structural motifs observed in proteins in all organisms that perform several crucial functions. The computational identification of CCD segments over a protein sequence is of great importance for its functional characterization. This task can essentially be divided into three separate steps: the detection of segment boundaries, the annotation of the heptad repeat pattern along the segment, and the classification of its oligomerization state. Several methods have been proposed over the years addressing one or more of these predictive steps. In this protocol, we illustrate how to make use of CoCoNat, a novel approach based on protein language models, to characterize CCDs. CoCoNat is, at its release (August 2023), the state of the art for CCD detection. The web server allows users to submit input protein sequences and visualize the predicted domains after a few minutes. Optionally, precomputed segments can be provided to the model, which will predict the oligomerization state for each of them. CoCoNat can be easily integrated into biological pipelines by downloading the standalone version, which provides a single executable script to produce the output. Key features • Web server for the prediction of coiled-coil segments from a protein sequence. • Three different predictions from a single tool (segment position, heptad repeat annotation, oligomerization state). • Possibility to visualize the results online or to download the predictions in different formats for further processing. • Easy integration in automated pipelines with the local version of the tool.

AlphaFold2 captures the conformational landscape of the HAMP signaling domain

In this study, we present a conformational landscape of 5000 AlphaFold2 models of the Histidine kinases, Adenyl cyclases, Methyl-accepting proteins and Phosphatases (HAMP) domain, a short helical bundle that transduces signals from sensors to effectors in two-component signaling proteins such as sensory histidine kinases and chemoreceptors. The landscape reveals the conformational variability of the HAMP domain, including rotations, shifts, displacements, and tilts of helices, many combinations of which have not been observed in experimental structures. HAMP domains belonging to a single family tend to occupy a defined region of the landscape, even when their sequence similarity is low, suggesting that individual HAMP families have evolved to operate in a specific conformational range. The functional importance of this structural conservation is illustrated by poly-HAMP arrays, in which HAMP domains from families with opposite conformational preferences alternate, consistent with the rotational model of signal transduction. The only poly-HAMP arrays that violate this rule are predicted to be of recent evolutionary origin and structurally unstable. Finally, we identify a family of HAMP domains that are likely to be dynamic due to the presence of a conserved pi-helical bulge. All code associated with this work, including a tool for rapid sequence-based prediction of the rotational state in HAMP domains, is deposited at https://github.com/labstructbioinf/HAMPpred.

X-ray structure of the metastable SEPT14-SEPT7 coiled coil reveals a hendecad region crucial for heterodimerization

Septins are membrane-associated, GTP-binding proteins that are present in most eukaryotes. They polymerize to play important roles as scaffolds and/or diffusion barriers as part of the cytoskeleton. α-Helical coiled-coil domains are believed to contribute to septin assembly, and those observed in both human SEPT6 and SEPT8 form antiparallel homodimers. These are not compatible with their parallel heterodimeric organization expected from the current model for protofilament assembly, but they could explain the interfilament cross-bridges observed by microscopy. Here, the first structure of a heterodimeric septin coiled coil is presented, that between SEPT14 and SEPT7; the former is a SEPT6/SEPT8 homolog. This new structure is parallel, with two long helices that are axially shifted by a full helical turn with reference to their sequence alignment. The structure also has unusual knobs-into-holes packing of side chains. Both standard seven-residue (heptad) and the less common 11-residue (hendecad) repeats are present, creating two distinct regions with opposite supercoiling, which gives rise to an overall straight coiled coil. Part of the hendecad region is required for heterodimerization and therefore may be crucial for selective septin recognition. These unconventional sequences and structural features produce a metastable heterocomplex that nonetheless has enough specificity to promote correct protofilament assembly. For instance, the lack of supercoiling may facilitate unzipping and transitioning to the antiparallel homodimeric state.

CoCoNat: a novel method based on deep learning for coiled-coil prediction

MOTIVATION

Coiled-coil domains (CCD) are widespread in all organisms and perform several crucial functions. Given their relevance, the computational detection of CCD is very important for protein functional annotation. State-of-the-art prediction methods include the precise identification of CCD boundaries, the annotation of the typical heptad repeat pattern along the coiled-coil helices as well as the prediction of the oligomerization state.

RESULTS

In this article, we describe CoCoNat, a novel method for predicting coiled-coil helix boundaries, residue-level register annotation, and oligomerization state. Our method encodes sequences with the combination of two state-of-the-art protein language models and implements a three-step deep learning procedure concatenated with a Grammatical-Restrained Hidden Conditional Random Field for CCD identification and refinement. A final neural network predicts the oligomerization state. When tested on a blind test set routinely adopted, CoCoNat obtains a performance superior to the current state-of-the-art both for residue-level and segment-level CCD. CoCoNat significantly outperforms the most recent state-of-the-art methods on register annotation and prediction of oligomerization states.

AVAILABILITY AND IMPLEMENTATION

CoCoNat web server is available at https://coconat.biocomp.unibo.it. Standalone version is available on GitHub at https://github.com/BolognaBiocomp/coconat.

From primordial clocks to circadian oscillators

Circadian rhythms play an essential part in many biological processes, and only three prokaryotic proteins are required to constitute a true post-translational circadian oscillator1. The evolutionary history of the three Kai proteins indicates that KaiC is the oldest member and a central component of the clock2. Subsequent additions of KaiB and KaiA regulate the phosphorylation state of KaiC for time synchronization. The canonical KaiABC system in cyanobacteria is well understood3-6, but little is known about more ancient systems that only possess KaiBC. However, there are reports that they might exhibit a basic, hourglass-like timekeeping mechanism7-9. Here we investigate the primordial circadian clock in Rhodobacter sphaeroides, which contains only KaiBC, to elucidate its inner workings despite missing KaiA. Using a combination of X-ray crystallography and cryogenic electron microscopy, we find a new dodecameric fold for KaiC, in which two hexamers are held together by a coiled-coil bundle of 12 helices. This interaction is formed by the carboxy-terminal extension of KaiC and serves as an ancient regulatory moiety that is later superseded by KaiA. A coiled-coil register shift between daytime and night-time conformations is connected to phosphorylation sites through a long-range allosteric network that spans over 140 Å. Our kinetic data identify the difference in the ATP-to-ADP ratio between day and night as the environmental cue that drives the clock. They also unravel mechanistic details that shed light on the evolution of self-sustained oscillators.

Understanding a protein fold: the physics, chemistry, and biology of α-helical coiled coils

Protein science is being transformed by powerful computational methods for structure prediction and design: AlphaFold2 can predict many natural protein structures from sequence, and other AI methods are enabling the de novo design of new structures. This raises a question: how much do we understand the underlying sequence-to-structure/function relationships being captured by these methods? This perspective presents our current understanding of one class of protein assembly, the α-helical coiled coils. At first sight, these are straightforward: sequence repeats of hydrophobic (h) and polar (p) residues, (hpphppp)_n, direct the folding and assembly of amphipathic α helices into bundles. However, many different bundles are possible: they can have two or more helices (different oligomers); the helices can have parallel, antiparallel or mixed arrangements (different topologies); and the helical sequences can be the same (homomers) or different (heteromers). Thus, sequence-to-structure relationships must be present within the hpphppp repeats to distinguish these states. I discuss the current understanding of this problem at three levels: First, physics gives a parametric framework to generate the many possible coiled-coil backbone structures. Second, chemistry provides a means to explore and deliver sequence-to-structure relationships. Third, biology shows how coiled coils are adapted and functionalized in nature, inspiring applications of coiled coils in synthetic biology. I argue that the chemistry is largely understood; the physics is partly solved, though the considerable challenge of predicting even relative stabilities of different coiled-coil states remains; but there is much more to explore in the biology and synthetic biology of coiled coils.

Molecular Characterization of Tropomyosin and Its Potential Involvement in Muscle Contraction in Pacific Abalone

Tropomyosin (TPM) is a contractile protein responsible for muscle contraction through its actin-binding activity. The complete sequence of TPM in Haliotis discus hannai (Hdh-TPM) was 2160 bp, encoding 284 amino acids, and contained a TPM signature motif and a TPM domain. Gene ontology (GO) analysis based on the amino acid sequence predicted Hdh-TPM to have an actin-binding function in the cytoskeleton. The 3D analysis predicted the Hdh-TPM to have a coiled-coil α-helical structure. Phylogenetically, Hdh-TPM formed a cluster with other TPM/TPM1 proteins during analysis. The tissue-specific mRNA expression analysis found the higher expression of Hdh-TPM in the heart and muscles; however, during embryonic and larval development (ELD), the higher expression was found in the trochophore larvae and veliger larvae. Hdh-TPM expression was upregulated in fast-growing abalone. Increasing thermal stress over a long period decreased Hdh-TPM expression. Long-term starvation (>1 week) reduced the mRNA expression of Hdh-TPM in muscle; however, the mRNA expression of Hdh-TPM was significantly higher in the mantle, which may indicate overexpression. This study is the first comprehensive study to characterize the Hdh-TPM gene in Pacific abalone and to report the expression of Hdh-TPM in different organs, and during ELD, different growth patterns, thermal stress, seasonal changes, and starvation.

Bioinformatics Analysis of the Periodicity in Proteins with Coiled-Coil Structure—Enumerating All Decompositions of Sequence Periods

A coiled coil is a structural motif in proteins that consists of at least two α-helices wound around each other. For structural stabilization, these α-helices form interhelical contacts via their amino acid side chains. However, there are restrictions as to the distances along the amino acid sequence at which those contacts occur. As the spatial period of the α-helix is 3.6, the most frequent distances between hydrophobic contacts are 3, 4, and 7. Up to now, the multitude of possible decompositions of α-helices participating in coiled coils at these distances has not been explored systematically. Here, we present an algorithm that computes all non-redundant decompositions of sequence periods of hydrophobic amino acids into distances of 3, 4, and 7. Further, we examine which decompositions can be found in nature by analyzing the available data and taking a closer look at correlations between the properties of the coiled coil and its decomposition. We find that the availability of decompositions allowing for coiled-coil formation without putting too much strain on the α-helix geometry follows an oscillatory pattern in respect of period length. Our algorithm supplies the basis for exploring the possible decompositions of coiled coils of any period length.

Genome-Wide Identification and Expressional Profiling of the Metal Tolerance Protein Gene Family in Brassica napus

The Cation Diffusion Facilitator (CDF) family, also named Metal Tolerance Protein (MTP), is one of the gene families involved in heavy metal transport in plants. However, a comprehensive study of MTPs in Brassica napus has not been reported yet. In the present study, we identified 33 BnMTP genes from the rapeseed genome using bioinformatic analyses. Subsequently, we analyzed the phylogenetic relationship, gene structure, chromosome distribution, conserved domains, and motifs of the BnMTP gene family. The 33 BnMTPs were phylogenetically divided into three major clusters (Zn-CDFs, Fe/Zn-CDFs, and Mn-CDFs) and seven groups (group 1, 5, 6, 7, 8, 9, and 12). The structural characteristics of the BnMTP members were similar in the same group, but different among groups. Evolutionary analysis indicated that the BnMTP gene family mainly expanded through whole-genome duplication (WGD) and segmental duplication events. Moreover, the prediction of cis-acting elements and microRNA target sites suggested that BnMTPs might be involved in plant growth, development, and stress responses. In addition, we found the expression of 24 BnMTPs in rapeseed leaves or roots could respond to heavy metal ion treatments. These results provided an important basis for clarifying the biological functions of BnMTPs, especially in heavy metal detoxification, and will be helpful in the phytoremediation of heavy metal pollution in soil.

Localpdb- a Python package to manage protein structures and their annotations

Motivation

The wealth of protein structures collected in the Protein Data Bank enabled large-scale studies of their function and evolution. Such studies, however, require the generation of customized datasets combining the structural data with miscellaneous accessory resources providing functional, taxonomic and other annotations. Unfortunately, the functionality of currently available tools for the creation of such datasets is limited and their usage frequently requires laborious surveying of various data sources and resolving inconsistencies between their versions.

Results

To address this problem, we developed localpdb, a versatile Python library for the management of protein structures and their annotations. The library features a flexible plugin system enabling seamless unification of the structural data with diverse auxiliary resources, full version control and powerful functionality of creating highly customized datasets. The localpdb can be used in a wide range of bioinformatic tasks, in particular those involving large-scale protein structural analyses and machine learning.

Availability and implementation

localpdb is freely available at https://github.com/labstructbioinf/localpdb. Documentation along with the usage examples can be accessed at https://labstructbioinf.github.io/localpdb/.

CoCoPRED: coiled-coil protein structural feature prediction from amino acid sequence using deep neural networks

MOTIVATION

Coiled-coil is composed of two or more helices that are wound around each other. It widely exists in proteins and has been discovered to play a variety of critical roles in biology processes. Generally, there are three types of structural features in coiled-coil: coiled-coil domain (CCD), oligomeric state and register. However, most of the existing computational tools only focus on one of them.

RESULTS

Here, we describe a new deep learning model, CoCoPRED, which is based on convolutional layers, bidirectional long short-term memory, and attention mechanism. It has three networks, i.e. CCD network, oligomeric state network, and register network, corresponding to the three types of structural features in coiled-coil. This means CoCoPRED has the ability of fulfilling comprehensive prediction for coiled-coil proteins. Through the 5-fold cross-validation experiment, we demonstrate that CoCoPRED can achieve better performance than the state-of-the-art models on both CCD prediction and oligomeric state prediction. Further analysis suggests the CCD prediction may be a performance indicator of the oligomeric state prediction in CoCoPRED. The attention heads in CoCoPRED indicate that registers a, b and e are more crucial for the oligomeric state prediction.

AVAILABILITY AND IMPLEMENTATION

CoCoPRED is available at http://www.csbio.sjtu.edu.cn/bioinf/CoCoPRED. The datasets used in this research can also be downloaded from the website.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Open Reading Frame 1 Protein of the Human Long Interspersed Nuclear Element 1 Retrotransposon Binds Multiple Equivalents of Lead

The human long interspersed nuclear element 1 (LINE1) has been implicated in numerous diseases and has been suggested to play a significant role in genetic evolution. Open reading frame 1 protein (ORF1p) is one of the two proteins encoded in this self-replicating mobile genetic element, both of which are essential for retrotransposition. The structure of the three-stranded coiled-coil domain of ORF1p was recently solved and showed the presence of tris-cysteine layers in the interior of the coiled-coil that could function as metal binding sites. Here, we demonstrate that ORF1p binds Pb(II). We designed a model peptide, GRCSL16CL23C, to mimic two of the ORF1p Cys3 layers and crystallized the peptide both as the apo-form and in the presence of Pb(II). Structural comparison of the ORF1p with apo-(GRCSL16CL23C)3 shows very similar Cys3 layers, preorganized for Pb(II) binding. We propose that exposure to heavy metals, such as lead, could influence directly the structural parameters of ORF1p and thus impact the overall LINE1 retrotransposition frequency, directly relating heavy metal exposure to genetic modification.