Multi-domain Proteins in the Three Kingdoms of Life: Orphan Domains and Other Unassigned Regions

Ensembles of interconverting protein complexes with multiple interaction domains

Many critical biological processes depend on protein complexes that exist as ensembles of subcomplexes rather than a discrete complex. The subcomplexes dynamically interconvert with one another, and the ability to accurately resolve the composition of the diverse molecular species in the ensemble is crucial for understanding the contribution of each subcomplex to the overall function of the protein complex. Advances in computational programs have made it possible to predict the various molecular species in these ensembles, but experimental approaches to identify the pool of subcomplexes and associated stoichiometries are often challenging. This review highlights some experimental approaches that can be used to resolve the diverse molecular species in protein complexes that exist as ensembles of sub complexes.

The emerging view on the origin and early evolution of eukaryotic cells

The origin of the eukaryotic cell, with its compartmentalized nature and generally large size compared with bacterial and archaeal cells, represents a cornerstone event in the evolution of complex life on Earth. In a process referred to as eukaryogenesis, the eukaryotic cell is believed to have evolved between approximately 1.8 and 2.7 billion years ago from its archaeal ancestors, with a symbiosis with a bacterial (proto-mitochondrial) partner being a key event. In the tree of life, the branch separating the first from the last common ancestor of all eukaryotes is long and lacks evolutionary intermediates. As a result, the timing and driving forces of the emergence of complex eukaryotic features remain poorly understood. During the past decade, environmental and comparative genomic studies have revealed vital details about the identity and nature of the host cell and the proto-mitochondrial endosymbiont, enabling a critical reappraisal of hypotheses underlying the symbiotic origin of the eukaryotic cell. Here we outline our current understanding of the key players and events underlying the emergence of cellular complexity during the prokaryote-to-eukaryote transition and discuss potential avenues of future research that might provide new insights into the enigmatic origin of the eukaryotic cell.

The fallacy of functional nomenclature in the kingdom of biological multifunctionality: physiological and evolutionary considerations on ion channels

Living organisms are multiscale complex systems that have evolved high degrees of multifunctionality and redundancy in the structure-function relationship. A number of factors, only in part determined genetically, affect the jobs of proteins. The overall structural organization confers unique molecular properties that provide the potential to perform a pattern of activities, some of which are co-opted by specific environments. The variety of multifunctional proteins is expanding, but most cases are handled individually and according to the still dominant 'one structure-one function' approach, which relies on the attribution of canonical names typically referring to the first task identified for a given protein. The present topical review focuses on the multifunctionality of ion channels as a paradigmatic example. Mounting evidence reports the ability of many ion channels (including members of voltage-dependent, ligand-gated and transient receptor potential families) to exert biological effects independently of their ion conductivity. 'Functionally based' nomenclature (the practice of naming a protein or family of proteins based on a single purpose) is a conceptual bias for three main reasons: (i) it increases the amount of ambiguity, deceiving our understanding of the multiple contributions of biomolecules that is the heart of the complexity; (ii) it is in stark contrast to protein evolution dynamics, largely based on multidomain arrangement; and (iii) it overlooks the crucial role played by the microenvironment in adjusting the actions of cell structures and in tuning protein isoform diversity to accomplish adaptational requirements. Biological information in protein physiology is distributed among different entwined layers working as the primary 'locus' of natural selection and of evolutionary constraints.

Bacterial Chaperone Domain Insertions Convert Human FKBP12 into an Excellent Protein-Folding Catalyst-A Structural and Functional Analysis

Many folding enzymes use separate domains for the binding of substrate proteins and for the catalysis of slow folding reactions such as prolyl isomerization. FKBP12 is a small prolyl isomerase without a chaperone domain. Its folding activity is low, but it could be increased by inserting the chaperone domain from the homolog SlyD of E. coli near the prolyl isomerase active site. We inserted two other chaperone domains into human FKBP12: the chaperone domain of SlpA from E. coli, and the chaperone domain of SlyD from Thermococcus sp. Both stabilized FKBP12 and greatly increased its folding activity. The insertion of these chaperone domains had no influence on the FKBP12 and the chaperone domain structure, as revealed by two crystal structures of the chimeric proteins. The relative domain orientations differ in the two crystal structures, presumably representing snapshots of a more open and a more closed conformation. Together with crystal structures from SlyD-like proteins, they suggest a path for how substrate proteins might be transferred from the chaperone domain to the prolyl isomerase domain.

Multidomain chimeric enzymes as a promising alternative for biocatalysts improvement: a minireview

Searching for new and better biocatalysts is an area of study in constant development. In nature, mechanisms generally occurring in evolution, such as genetic duplication, recombination, and natural selection processes, produce various enzymes with different architectures and properties. The recombination of genes that code proteins produces multidomain chimeric enzymes that contain two or more domains that sometimes enhance their catalytic properties. Protein engineering has mimicked this process to enhance catalytic activity and the global stability of enzymes, searching for new and better biocatalysts. Here, we present and discuss examples from both natural and synthetic multidomain chimeric enzymes and how additional domains heighten their stability and catalytic activity. Moreover, we also describe progress in developing new biocatalysts using synthetic fusion enzymes and revise some methodological strategies to improve their biological fitness.

Conflicting Interfacial Electrostatic Interactions as a Design Principle to Modulate Long-Range Interdomain Communication

The extent and molecular basis of interdomain communication in multidomain proteins, central to understanding allostery and function, is an open question. One simple evolutionary strategy could involve the selection of either conflicting or favorable electrostatic interactions across the interface of two closely spaced domains to tune the magnitude of interdomain connectivity. Here, we study a bilobed domain FF34 from the eukaryotic p190A RhoGAP protein to explore one such design principle that mediates interdomain communication. We find that while the individual structural units in wild-type FF34 are marginally coupled, they exhibit distinct intrinsic stabilities and low cooperativity, manifesting as slow folding. The FF3-FF4 interface harbors a frustrated network of highly conserved electrostatic interactions-a charge troika-that promotes the population of multiple, decoupled, and non-native structural modes on a rugged native landscape. Perturbing this network via a charge-reversal mutation not only enhances stability and cooperativity but also dampens the fluctuations globally and speeds up the folding rate by at least an order of magnitude. Our work highlights how a conserved but nonoptimal network of interfacial electrostatic interactions shapes the native ensemble of a bilobed protein, a feature that could be exploited in designing molecular systems with long-range connectivity and enhanced cooperativity.

Mesophiles vs. Thermophiles: Untangling the Hot Mess of Intrinsically Disordered Proteins and Growth Temperature of Bacteria

The dynamic structures and varying functions of intrinsically disordered proteins (IDPs) have made them fascinating subjects in molecular biology. Investigating IDP abundance in different bacterial species is crucial for understanding adaptive strategies in diverse environments. Notably, thermophilic bacteria have lower IDP abundance than mesophiles, and a negative correlation with optimal growth temperature (OGT) has been observed. However, the factors driving these trends are yet to be fully understood. We examined the types of IDPs present in both mesophiles and thermophiles alongside those unique to just mesophiles. The shared group of IDPs exhibits similar disorder levels in the two groups of species, suggesting that certain IDPs unique to mesophiles may contribute to the observed decrease in IDP abundance as OGT increases. Subsequently, we used quasi-independent contrasts to explore the relationship between OGT and IDP abundance evolution. Interestingly, we found no significant relationship between OGT and IDP abundance contrasts, suggesting that the evolution of lower IDP abundance in thermophiles may not be solely linked to OGT. This study provides a foundation for future research into the intricate relationship between IDP evolution and environmental adaptation. Our findings support further research on the adaptive significance of intrinsic disorder in bacterial species.

Domain Architecture Based Methods for Comparative Functional Genomics Toward Therapeutic Drug Target Discovery

Genes duplicate, mutate, recombine, fuse or fission to produce new genes, or when genes are formed from de novo, novel functions arise during evolution. Researchers have tried to quantify the causes of these molecular diversification processes to know how these genes increase molecular complexity over a period of time, for instance protein domain organization. In contrast to global sequence similarity, protein domain architectures can capture key structural and functional characteristics, making them better proxies for describing functional equivalence. In Prokaryotes and eukaryotes it has proven that, domain designs are retained over significant evolutionary distances. Protein domain architectures are now being utilized to categorize and distinguish evolutionarily related proteins and find homologs among species that are evolutionarily distant from one another. Additionally, structural information stored in domain structures has accelerated homology identification and sequence search methods. Tools for functional protein annotation have been developed to discover, protein domain content, domain order, domain recurrence, and domain position as all these contribute to the prediction of protein functional accuracy. In this review, an attempt is made to summarise facts and speculations regarding the use of protein domain architecture and modularity to identify possible therapeutic targets among cellular activities based on the understanding their linked biological processes.

Diversity and features of proteins with structural repeats

The review provides information on proteins with structural repeats, including their classification, characteristics, functions, and relevance in disease development. It explores methods for identifying structural repeats and specialized databases. The review also highlights the potential use of repeat proteins as drug design scaffolds and discusses their evolutionary mechanisms.

Multitasking Proteins and Their Involvement in Pathogenesis

The "one protein, one function" paradigm, similar to the "one gene, one enzyme" hypothesis that dominated our thinking for a long time, has proven to be too simplistic [...].

Using human genetics to improve safety assessment of therapeutics

Human genetics research has discovered thousands of proteins associated with complex and rare diseases. Genome-wide association studies (GWAS) and studies of Mendelian disease have resulted in an increased understanding of the role of gene function and regulation in human conditions. Although the application of human genetics has been explored primarily as a method to identify potential drug targets and support their relevance to disease in humans, there is increasing interest in using genetic data to identify potential safety liabilities of modulating a given target. Human genetic variants can be used as a model to anticipate the effect of lifelong modulation of therapeutic targets and identify the potential risk for on-target adverse events. This approach is particularly useful for non-clinical safety evaluation of novel therapeutics that lack pharmacologically relevant animal models and can contribute to the intrinsic safety profile of a drug target. This Review illustrates applications of human genetics to safety studies during drug discovery and development, including assessing the potential for on- and off-target associated adverse events, carcinogenicity risk assessment, and guiding translational safety study designs and monitoring strategies. A summary of available human genetic resources and recommended best practices is provided. The challenges and future perspectives of translating human genetic information to identify risks for potential drug effects in preclinical and clinical development are discussed.

The Modular Architecture of Metallothioneins Facilitates Domain Rearrangements and Contributes to Their Evolvability in Metal-Accumulating Mollusks

Protein domains are independent structural and functional modules that can rearrange to create new proteins. While the evolution of multidomain proteins through the shuffling of different preexisting domains has been well documented, the evolution of domain repeat proteins and the origin of new domains are less understood. Metallothioneins (MTs) provide a good case study considering that they consist of metal-binding domain repeats, some of them with a likely de novo origin. In mollusks, for instance, most MTs are bidomain proteins that arose by lineage-specific rearrangements between six putative domains: α, β1, β2, β3, γ and δ. Some domains have been characterized in bivalves and gastropods, but nothing is known about the MTs and their domains of other Mollusca classes. To fill this gap, we investigated the metal-binding features of NpoMT1 of Nautilus pompilius (Cephalopoda class) and FcaMT1 of Falcidens caudatus (Caudofoveata class). Interestingly, whereas NpoMT1 consists of α and β1 domains and has a prototypical Cd²⁺ preference, FcaMT1 has a singular preference for Zn²⁺ ions and a distinct domain composition, including a new Caudofoveata-specific δ domain. Overall, our results suggest that the modular architecture of MTs has contributed to MT evolution during mollusk diversification, and exemplify how modularity increases MT evolvability.

The mechanical cell - the role of force dependencies in synchronising protein interaction networks

The role of mechanical signals in the proper functioning of organisms is increasingly recognised, and every cell senses physical forces and responds to them. These forces are generated both from outside the cell or via the sophisticated force-generation machinery of the cell, the cytoskeleton. All regions of the cell are connected via mechanical linkages, enabling the whole cell to function as a mechanical system. In this Review, we define some of the key concepts of how this machinery functions, highlighting the critical requirement for mechanosensory proteins, and conceptualise the coupling of mechanical linkages to mechanochemical switches that enables forces to be converted into biological signals. These mechanical couplings provide a mechanism for how mechanical crosstalk might coordinate the entire cell, its neighbours, extending into whole collections of cells, in tissues and in organs, and ultimately in the coordination and operation of entire organisms. Consequently, many diseases manifest through defects in this machinery, which we map onto schematics of the mechanical linkages within a cell. This mapping approach paves the way for the identification of additional linkages between mechanosignalling pathways and so might identify treatments for diseases, where mechanical connections are affected by mutations or where individual force-regulated components are defective.

Fuzzy supertertiary interactions within PSD-95 enable ligand binding

The scaffold protein PSD-95 links postsynaptic receptors to sites of presynaptic neurotransmitter release. Flexible linkers between folded domains in PSD-95 enable a dynamic supertertiary structure. Interdomain interactions within the PSG supramodule, formed by PDZ3, SH3, and Guanylate Kinase domains, regulate PSD-95 activity. Here we combined discrete molecular dynamics and single molecule Förster resonance energy transfer (FRET) to characterize the PSG supramodule, with time resolution spanning picoseconds to seconds. We used a FRET network to measure distances in full-length PSD-95 and model the conformational ensemble. We found that PDZ3 samples two conformational basins, which we confirmed with disulfide mapping. To understand effects on activity, we measured binding of the synaptic adhesion protein neuroligin. We found that PSD-95 bound neuroligin well at physiological pH while truncated PDZ3 bound poorly. Our hybrid structural models reveal how the supertertiary context of PDZ3 enables recognition of this critical synaptic ligand.

Conformational ensembles of intrinsically disordered proteins and flexible multidomain proteins

Intrinsically disordered proteins (IDPs) and multidomain proteins with flexible linkers show a high level of structural heterogeneity and are best described by ensembles consisting of multiple conformations with associated thermodynamic weights. Determining conformational ensembles usually involves the integration of biophysical experiments and computational models. In this review, we discuss current approaches to determine conformational ensembles of IDPs and multidomain proteins, including the choice of biophysical experiments, computational models used to sample protein conformations, models to calculate experimental observables from protein structure, and methods to refine ensembles against experimental data. We also provide examples of recent applications of integrative conformational ensemble determination to study IDPs and multidomain proteins and suggest future directions for research in the field.

Characterizing conformational ensembles of multi-domain proteins using anisotropic paramagnetic NMR restraints

It has been over two decades since paramagnetic NMR started to form part of the essential techniques for structural analysis of proteins under physiological conditions. Paramagnetic NMR has significantly expanded our understanding of the inherent flexibility of proteins, in particular, those that are formed by combinations of two or more domains. Here, we present a brief overview of techniques to characterize conformational ensembles of such multi-domain proteins using paramagnetic NMR restraints produced through anisotropic metals, with a focus on the basics of anisotropic paramagnetic effects, the general procedures of conformational ensemble reconstruction, and some representative reweighting approaches.

Wavelet invariants for statistically robust multi-reference alignment

We propose a nonlinear, wavelet-based signal representation that is translation invariant and robust to both additive noise and random dilations. Motivated by the multi-reference alignment problem and generalizations thereof, we analyze the statistical properties of this representation given a large number of independent corruptions of a target signal. We prove the nonlinear wavelet-based representation uniquely defines the power spectrum but allows for an unbiasing procedure that cannot be directly applied to the power spectrum. After unbiasing the representation to remove the effects of the additive noise and random dilations, we recover an approximation of the power spectrum by solving a convex optimization problem, and thus reduce to a phase retrieval problem. Extensive numerical experiments demonstrate the statistical robustness of this approximation procedure.

Tracing protein and proteome history with chronologies and networks: folding recapitulates evolution

INTRODUCTION

While the origin and evolution of proteins remain mysterious, advances in evolutionary genomics and systems biology are facilitating the historical exploration of the structure, function and organization of proteins and proteomes. Molecular chronologies are series of time events describing the history of biological systems and subsystems and the rise of biological innovations. Together with time-varying networks, these chronologies provide a window into the past.

AREAS COVERED

Here, we review molecular chronologies and networks built with modern methods of phylogeny reconstruction. We discuss how chronologies of structural domain families uncover the explosive emergence of metabolism, the late rise of translation, the co-evolution of ribosomal proteins and rRNA, and the late development of the ribosomal exit tunnel; events that coincided with a tendency to shorten folding time. Evolving networks described the early emergence of domains and a late 'big bang' of domain combinations.

EXPERT OPINION

Two processes, folding and recruitment appear central to the evolutionary progression. The former increases protein persistence. The later fosters diversity. Chronologically, protein evolution mirrors folding by combining supersecondary structures into domains, developing translation machinery to facilitate folding speed and stability, and enhancing structural complexity by establishing long-distance interactions in novel structural and architectural designs.

TopDomain: Exhaustive Protein Domain Boundary Metaprediction Combining Multisource Information and Deep Learning

Protein domains are independent, functional, and stable structural units of proteins. Accurate protein domain boundary prediction plays an important role in understanding protein structure and evolution, as well as for protein structure prediction. Current domain boundary prediction methods differ in terms of boundary definition, methodology, and training databases resulting in disparate performance for different proteins. We developed TopDomain, an exhaustive metapredictor, that uses deep neural networks to combine multisource information from sequence- and homology-based features of over 50 primary predictors. For this purpose, we developed a new domain boundary data set termed the TopDomain data set, in which the true annotations are informed by SCOPe annotations, structural domain parsers, human inspection, and deep learning. We benchmark TopDomain against 2484 targets with 3354 boundaries from the TopDomain test set and achieve F1 scores of 78.4% and 73.8% for multidomain boundary prediction within ±20 residues and ±10 residues of the true boundary, respectively. When examined on targets from CASP11-13 competitions, TopDomain achieves F1 scores of 47.5% and 42.8% for multidomain proteins. TopDomain significantly outperforms 15 widely used, state-of-the-art ab initio and homology-based domain boundary predictors. Finally, we implemented TopDomain_TMC, which accurately predicts whether domain parsing is necessary for the target protein.

Evotuning protocols for Transformer-based variant effect prediction on multi-domain proteins

Accurate variant effect prediction has broad impacts on protein engineering. Recent machine learning approaches toward this end are based on representation learning, by which feature vectors are learned and generated from unlabeled sequences. However, it is unclear how to effectively learn evolutionary properties of an engineering target protein from homologous sequences, taking into account the protein's sequence-level structure called domain architecture (DA). Additionally, no optimal protocols are established for incorporating such properties into Transformer, the neural network well-known to perform the best in natural language processing research. This article proposes DA-aware evolutionary fine-tuning, or 'evotuning', protocols for Transformer-based variant effect prediction, considering various combinations of homology search, fine-tuning and sequence vectorization strategies. We exhaustively evaluated our protocols on diverse proteins with different functions and DAs. The results indicated that our protocols achieved significantly better performances than previous DA-unaware ones. The visualizations of attention maps suggested that the structural information was incorporated by evotuning without direct supervision, possibly leading to better prediction accuracy.

Mantis: flexible and consensus-driven genome annotation

Background

The rapid development of the (meta-)omics fields has produced an unprecedented amount of high-resolution and high-fidelity data. Through the use of these datasets we can infer the role of previously functionally unannotated proteins from single organisms and consortia. In this context, protein function annotation can be described as the identification of regions of interest (i.e., domains) in protein sequences and the assignment of biological functions. Despite the existence of numerous tools, challenges remain in terms of speed, flexibility, and reproducibility. In the big data era, it is also increasingly important to cease limiting our findings to a single reference, coalescing knowledge from different data sources, and thus overcoming some limitations in overly relying on computationally generated data from single sources.

Results

We implemented a protein annotation tool, Mantis, which uses database identifiers intersection and text mining to integrate knowledge from multiple reference data sources into a single consensus-driven output. Mantis is flexible, allowing for the customization of reference data and execution parameters, and is reproducible across different research goals and user environments. We implemented a depth-first search algorithm for domain-specific annotation, which significantly improved annotation performance compared to sequence-wide annotation. The parallelized implementation of Mantis results in short runtimes while also outputting high coverage and high-quality protein function annotations.

Conclusions

Mantis is a protein function annotation tool that produces high-quality consensus-driven protein annotations. It is easy to set up, customize, and use, scaling from single genomes to large metagenomes. Mantis is available under the MIT license at https://github.com/PedroMTQ/mantis.

Computing Cellulase Kinetics with a Two-Domain Linear Interaction Energy Approach

While heterogeneous enzyme reactions play an essential role in both nature and green industries, computational predictions of their catalytic properties remain scarce. Recent experimental work demonstrated the applicability of the Sabatier principle for heterogeneous biocatalysis. This provides a simple relationship between binding strength and the catalytic rate and potentially opens a new way for inexpensive computational determination of kinetic parameters. However, broader implementation of this approach will require fast and reliable prediction of binding free energies of complex two-phase systems, and computational procedures for this are still elusive. Here, we propose a new framework for the assessment of the binding strengths of multidomain proteins, in general, and interfacial enzymes, in particular, based on an extended linear interaction energy (LIE) method. This two-domain LIE (2D-LIE) approach was successfully applied to predict binding and activation free energies of a diverse set of cellulases and resulted in robust models with high accuracy. Overall, our method provides a fast computational screening tool for cellulases that have not been experimentally characterized, and we posit that it may also be applicable to other heterogeneously acting biocatalysts.

Investigating the trade-off between folding and function in a multidomain Y-family DNA polymerase

The way in which multidomain proteins fold has been a puzzling question for decades. Until now, the mechanisms and functions of domain interactions involved in multidomain protein folding have been obscure. Here, we develop structure-based models to investigate the folding and DNA-binding processes of the multidomain Y-family DNA polymerase IV (DPO4). We uncover shifts in the folding mechanism among ordered domain-wise folding, backtracking folding, and cooperative folding, modulated by interdomain interactions. These lead to ‘U-shaped’ DPO4 folding kinetics. We characterize the effects of interdomain flexibility on the promotion of DPO4–DNA (un)binding, which probably contributes to the ability of DPO4 to bypass DNA lesions, which is a known biological role of Y-family polymerases. We suggest that the native topology of DPO4 leads to a trade-off between fast, stable folding and tight functional DNA binding. Our approach provides an effective way to quantitatively correlate the roles of protein interactions in conformational dynamics at the multidomain level.

Functional Disassociation Between the Protein Domains of MSMEG_4305 of Mycolicibacterium smegmatis (Mycobacterium smegmatis) in vivo

MSMEG_4305 is a two-domain protein of Mycolicibacterium smegmatis (Mycobacterium smegmatis) (Mycolicibacterium smegmatis). The N-terminal domain of MSMEG_4305 encodes an RNase H type I. The C-terminal domain is a presumed CobC, predicted to be involved in the aerobic synthesis of vitamin B12. Both domains reach their maximum at distinct pH, approximately 8.5 and 4.5, respectively. The presence of the CobC domain influenced RNase activity in vitro in homolog Rv2228c. Here, we analyzed the role of MSMEG_4305 in vitamin B12 synthesis and the functional association between both domains in vivo in M. smegmatis. We used knock-out mutant of M. smegmatis, deficient in MSMEG_4305. Whole-cell lysates of the mutants strain contained a lower concentration of vitamin B12, as it determined with immunoenzimatic assay. We observed growth deficits, related to vitamin B12 production, on media containing sulfamethazine and propionate. Removal of the CobC domain of MSMEG_4305 in ΔrnhA background hardly affected the growth rate of M. smegmatis in vivo. The strain carrying truncation showed no fitness deficit in the competitive assay and it did not show increased level of RNA/DNA hybrids in its genome. We show that homologs of MSMEG_4305 are present only in the Actinomycetales phylogenetic branch (according to the old classification system). The domains of MSMEG_4305 homologs accumulate mutations at a different rate, while the linker region is highly variable. We conclude that MSMEG_4305 is a multidomain protein that most probably was fixed in the phylogenetic tree of life due to genetic drift.

Decomposing Structural Response Due to Sequence Changes in Protein Domains with Machine Learning

How protein domain structure changes in response to mutations is not well understood. Some mutations change the structure drastically, while most only result in small changes. To gain an understanding of this, we decompose the relationship between changes in domain sequence and structure using machine learning. We select pairs of evolutionarily related domains with a broad range of evolutionary distances. In contrast to earlier studies, we do not find a strictly linear relationship between sequence and structural changes. We train a random forest regressor that predicts the structural similarity between pairs with an average accuracy of 0.029 lDDT ( local Distance Difference Test) score, and a correlation coefficient of 0.92. Decomposing the feature importance shows that the domain length, or analogously, size is the most important feature. Our model enables assessing deviations in relative structural response, and thus prediction of evolutionary trajectories, in protein domains across evolution.

DISPOT: a simple knowledge-based protein domain interaction statistical potential

MOTIVATION

The complexity of protein-protein interactions (PPIs) is further compounded by the fact that an average protein consists of two or more domains, structurally and evolutionary independent subunits. Experimental studies have demonstrated that an interaction between a pair of proteins is not carried out by all domains constituting each protein, but rather by a select subset. However, determining which domains from each protein mediate the corresponding PPI is a challenging task.

RESULTS

Here, we present domain interaction statistical potential (DISPOT), a simple knowledge-based statistical potential that estimates the propensity of an interaction between a pair of protein domains, given their structural classification of protein (SCOP) family annotations. The statistical potential is derived based on the analysis of >352 000 structurally resolved PPIs obtained from DOMMINO, a comprehensive database of structurally resolved macromolecular interactions.

AVAILABILITY AND IMPLEMENTATION

DISPOT is implemented in Python 2.7 and packaged as an open-source tool. DISPOT is implemented in two modes, basic and auto-extraction. The source code for both modes is available on GitHub: https://github.com/korkinlab/dispot and standalone docker images on DockerHub: https://hub.docker.com/r/korkinlab/dispot. The web server is freely available at http://dispot.korkinlab.org/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Multiple Forms of Multifunctional Proteins in Health and Disease

Protein science has moved from a focus on individual molecules to an integrated perspective in which proteins emerge as dynamic players with multiple functions, rather than monofunctional specialists. Annotation of the full functional repertoire of proteins has impacted the fields of biochemistry and genetics, and will continue to influence basic and applied science questions - from the genotype-to-phenotype problem, to our understanding of human pathologies and drug design. In this review, we address the phenomena of pleiotropy, multidomain proteins, promiscuity, and protein moonlighting, providing examples of multitasking biomolecules that underlie specific mechanisms of human disease. In doing so, we place in context different types of multifunctional proteins, highlighting useful attributes for their systematic definition and classification in future research directions.

Multidomain protein structure prediction using information about residues interacting on multimeric protein interfaces

Protein functions can be predicted based on their three-dimensional structures. However, many multidomain proteins have unstable structures, making it difficult to determine the whole structure in biological experiments. Additionally, multidomain proteins are often decomposed and identified based on their domains, with the structure of each domain often found in public databases. Recent studies have advanced structure prediction methods of multidomain proteins through computational analysis. In existing methods, proteins that serve as templates are used for three-dimensional structure prediction. However, when no protein template is available, the accuracy of the prediction is decreased. This study was conducted to predict the structures of multidomain proteins without the need for whole structure templates.

We improved structure prediction methods by performing rigid-body docking from the structure of each domain and reranking a structure closer to the correct structure to have a higher value. In the proposed method, the score for the domain-domain interaction obtained without a structural template of the multidomain protein and score for the three-dimensional structure obtained during docking calculation were newly incorporated into the score function. We successfully predicted the structures of 50 of 55 multidomain proteins examined in the test dataset.

Interaction residue pair information of the protein-protein complex interface contributes to domain reorganizations even when a structural template for a multidomain protein cannot be obtained. This approach may be useful for predicting the structures of multidomain proteins with important biochemical functions.

The modular nature of protein evolution: domain rearrangement rates across eukaryotic life

BACKGROUND

Modularity is important for evolutionary innovation. The recombination of existing units to form larger complexes with new functionalities spares the need to create novel elements from scratch. In proteins, this principle can be observed at the level of protein domains, functional subunits which are regularly rearranged to acquire new functions.

RESULTS

In this study we analyse the mechanisms leading to new domain arrangements in five major eukaryotic clades (vertebrates, insects, fungi, monocots and eudicots) at unprecedented depth and breadth. This allows, for the first time, to directly compare rates of rearrangements between different clades and identify both lineage specific and general patterns of evolution in the context of domain rearrangements. We analyse arrangement changes along phylogenetic trees by reconstructing ancestral domain content in combination with feasible single step events, such as fusion or fission. Using this approach we explain up to 70% of all rearrangements by tracing them back to their precursors. We find that rates in general and the ratio between these rates for a given clade in particular, are highly consistent across all clades. In agreement with previous studies, fusions are the most frequent event leading to new domain arrangements. A lineage specific pattern in fungi reveals exceptionally high loss rates compared to other clades, supporting recent studies highlighting the importance of loss for evolutionary innovation. Furthermore, our methodology allows us to link domain emergences at specific nodes in the phylogenetic tree to important functional developments, such as the origin of hair in mammals.

CONCLUSIONS

Our results demonstrate that domain rearrangements are based on a canonical set of mutational events with rates which lie within a relatively narrow and consistent range. In addition, gained knowledge about these rates provides a basis for advanced domain-based methodologies for phylogenetics and homology analysis which complement current sequence-based methods.

The deep(er) roots of Eukaryotes and Akaryotes

Background: Locating the root node of the "tree of life" (ToL) is one of the hardest problems in phylogenetics, given the time depth. The root-node, or the universal common ancestor (UCA), groups descendants into organismal clades/domains. Two notable variants of the two-domains ToL (2D-ToL) have gained support recently. One 2D-ToL posits that eukaryotes (organisms with nuclei) and akaryotes (organisms without nuclei) are sister clades that diverged from the UCA, and that Asgard archaea are sister to other archaea. The other 2D-ToL proposes that eukaryotes emerged from within archaea and places Asgard archaea as sister to eukaryotes. Williams et al. ( Nature Ecol. Evol. 4: 138-147; 2020) re-evaluated the data and methods that support the competing two-domains proposals and concluded that eukaryotes are the closest relatives of Asgard archaea. Critique: The poor resolution of the archaea in their analysis, despite employing amino acid alignments from thousands of proteins and the best-fitting substitution models, contradicts their conclusions. We argue that they overlooked important aspects of estimating evolutionary relatedness and assessing phylogenetic signal in empirical data. Which 2D-ToL is better supported depends on which kind of molecular features are better for resolving common ancestors at the roots of clades - protein-domains or their component amino acids. We focus on phylogenetic character reconstructions necessary to describe the UCA or its closest descendants in the absence of reliable fossils.     Clarifications: It is well known that different character types present different perspectives on evolutionary history that relate to different phylogenetic depths. We show that protein structural-domains support more reliable phylogenetic reconstructions of deep-diverging clades in the ToL. Accordingly, Eukaryotes and Akaryotes are better supported clades in a 2D-ToL.

TulsiPIN: An Interologous Protein Interactome of Ocimum tenuiflorum

Ocimum tenuiflorum, commonly known as holy basil or tulsi, is globally recognized for its multitude of medicinal properties. However, a comprehensive study revealing the complex interplay among its constituent proteins at subcellular level is still lacking. To bridge this gap, in this work, a genome-scale interologous protein-protein interaction (PPI) network, TulsiPIN, is developed using 36 template plants, which consists of 13 660 nodes and 327 409 binary interactions. A high confidence network, hc-TulsiPIN, consisting of 7719 nodes having 95 532 interactions is inferred using domain-domain interaction information along with interolog-based statistics, and its reliability is assessed using pathway enrichment, functional homogeneity, and protein colocalization of PPIs. Examination of topological features revealed that hc-TulsiPIN possesses conventional properties, like small-world, scale-free, and modular architecture. A total of 1625 vital proteins are predicted by statistically evaluating hc-TulsiPIN with two ensembles of corresponding random networks, each consisting of 10 000 realizations of Erdoős-Rényi and Barabási-Albert models. Also, numerous regulatory proteins like transcription factors, transcription regulators, and protein kinases are profiled. Using 36 guide genes participating in 9 secondary metabolite biosynthetic pathways, a subnetwork consisting of 171 proteins and 612 interactions was constructed, and 127 of these proteins could be successfully characterized. Detailed information of TulsiPIN is available at https://cuhpcbbtulsipin.shinyapps.io/tulsipin_v0/ .

Cotranslational Folding of Proteins on the Ribosome

Many proteins in the cell fold cotranslationally within the restricted space of the polypeptide exit tunnel or at the surface of the ribosome. A growing body of evidence suggests that the ribosome can alter the folding trajectory in many different ways. In this review, we summarize the recent examples of how translation affects folding of single-domain, multiple-domain and oligomeric proteins. The vectorial nature of translation, the spatial constraints of the exit tunnel, and the electrostatic properties of the ribosome-nascent peptide complex define the onset of early folding events. The ribosome can facilitate protein compaction, induce the formation of intermediates that are not observed in solution, or delay the onset of folding. Examples of single-domain proteins suggest that early compaction events can define the folding pathway for some types of domain structures. Folding of multi-domain proteins proceeds in a domain-wise fashion, with each domain having its role in stabilizing or destabilizing neighboring domains. Finally, the assembly of protein complexes can also begin cotranslationally. In all these cases, the ribosome helps the nascent protein to attain a native fold and avoid the kinetic traps of misfolding.

Protein Domain Level Cancer Drug Targets in the Network of MAPK Pathways

Proteins in the MAPK pathways considered as potential drug targets for cancer treatment. Pathways along with the cross-talks increase their scope to view them as a network of MAPK pathways. Side effect causing targeted domains act as a proxy for drug targets due to its structural similarity and frequent reuse of their variants. We proposed to identify non-repeatable protein domains as the drug targets to disrupt the signal transduction than targeting the whole protein. Network based approach is used to understand the contribution of 52 domains in non-hub, non-essential, and intra-pathway cancerous nodes and to identify potential drug target domains. 34 distinct domains in the cancerous proteins are playing vital roles in making cancer as a complex disease and pose challenges to identify potential drug targets. Distribution of domain families follows the power law in the network. Single promiscuous domains are contributing to the formation of hubs like Pkinease, Pkinease Tyr, and Ras. Hub nodes are positively correlated with the domain coverage and targeting them would disrupt functional properties of the proteins. EIF 4EBP, alpha Kinase, Sel1, ROKNT, and KH 1 are the domains identified as potential domain targets for the disruption of the signaling mechanism involved in cancer.

Unraveling the Mechanical Unfolding Pathways of a Multidomain Protein: Phosphoglycerate Kinase

Phosphoglycerate kinase (PGK) is a highly conserved enzyme that is crucial for glycolysis. PGK is a monomeric protein composed of two similar domains and has been the focus of many studies for investigating interdomain interactions within the native state and during folding. Previous studies used traditional biophysical methods (such as circular dichroism, tryptophan fluorescence, and NMR) to measure signals over a large ensemble of molecules, which made it difficult to observe transient changes in stability or structure during unfolding and refolding of single molecules. Here, we unfold single molecules of PGK using atomic force spectroscopy and steered molecular dynamic computer simulations to examine the conformational dynamics of PGK during its unfolding process. Our results show that after the initial forced separation of its domains, yeast PGK (yPGK) does not follow a single mechanical unfolding pathway; instead, it stochastically follows two distinct pathways: unfolding from the N-terminal domain or unfolding from the C-terminal domain. The truncated yPGK N-terminal domain unfolds via a transient intermediate, whereas the structurally similar isolated C-terminal domain has no detectable intermediates throughout its mechanical unfolding process. The N-terminal domain in the full-length yPGK displays a strong unfolding intermediate 13% of the time, whereas the truncated domain (yPGKNT) transitions through the intermediate 81% of the time. This effect indicates that the mechanical properties of yPGK cannot be simply deduced from the mechanical properties of its constituents. We also find that Escherichia coli PGK is significantly less mechanically stable as compared to yPGK, contrary to bulk unfolding measurements. Our results support the growing body of observations that the folding behavior of multidomain proteins is difficult to predict based solely on the studies of isolated domains.

Domain selective labeling for NMR studies of multidomain proteins by domain ligation using highly active sortase A

Structural study of multidomain proteins using NMR is an emerging issue for understanding biological functions. To this end, domain-specific labeling is expected to be a key technology for facilitating the NMR-assignment process and for collecting distance information via spin labeling. To obtain domain-specific labeled samples, use of sortase A as a protein ligation tool is a viable approach. Sortase A enables ligation of separately expressed proteins (domains) through the Leu-Pro-X-Thr-Gly linker. However, the ligation reaction mediated by sortase A is not efficient. Poor yield and long reaction times hamper large-scale preparation using sortase A. Here we report the application of highly active sortases to NMR analyses. Optimal yields can be achieved within several hours when the ligation reaction are mediated by highly active sortases at 4 °C. We propose that this protocol can contribute to structural analyses of multidomain proteins by NMR.

Unraveling the structural landscape of intra-chain domain interfaces: Implication in the evolution of domain-domain interactions

Intra-chain domain interactions are known to play a significant role in the function and stability of multidomain proteins. These interactions are mediated through a physical interaction at domain-domain interfaces (DDIs). With a motivation to understand evolution of interfaces, we have investigated similarities among DDIs. Even though interfaces of protein-protein interactions (PPIs) have been previously studied by structurally aligning interfaces, similar analyses have not yet been performed on DDIs of either multidomain proteins or PPIs. For studying the structural landscape of DDIs, we have used iAlign to structurally align intra-chain domain interfaces of domains. The interface alignment of spatially constrained domains (due to inter-domain linkers) showed that ~88% of these could identify a structural matching interface having similar C-alpha geometry and contact pattern despite that aligned domain pairs are not structurally related. Moreover, the mean interface similarity score (IS-score) is 0.307, which is higher compared to the average random IS-score (0.207) suggesting domain interfaces are not random. The structural space of DDIs is highly connected as ~84% of all possible directed edges among interfaces are found to have at most path length of 8 when 0.26 is IS-score threshold. At this threshold, ~83% of interfaces form the largest strongly connected component. Thus, suggesting that structural space of intra-chain domain interfaces is degenerate and highly connected, as has been found in PPI interfaces. Interestingly, searching for structural neighbors of inter-chain interfaces among intra-chain interfaces showed that ~86% could find a statistically significant match to intra-chain interface with a mean IS-score of 0.311. This implies that domain interfaces are degenerate whether formed within a protein or between proteins. The interface degeneracy is most likely due to limited possible ways of packing secondary structures. In principle, interface similarities can be exploited to accurately model domain interfaces in structure prediction of multidomain proteins.

Why do eukaryotic proteins contain more intrinsically disordered regions?

Intrinsic disorder is more abundant in eukaryotic than prokaryotic proteins. Methods predicting intrinsic disorder are based on the amino acid sequence of a protein. Therefore, there must exist an underlying difference in the sequences between eukaryotic and prokaryotic proteins causing the (predicted) difference in intrinsic disorder. By comparing proteins, from complete eukaryotic and prokaryotic proteomes, we show that the difference in intrinsic disorder emerges from the linker regions connecting Pfam domains. Eukaryotic proteins have more extended linker regions, and in addition, the eukaryotic linkers are significantly more disordered, 38% vs. 12-16% disordered residues. Next, we examined the underlying reason for the increase in disorder in eukaryotic linkers, and we found that the changes in abundance of only three amino acids cause the increase. Eukaryotic proteins contain 8.6% serine; while prokaryotic proteins have 6.5%, eukaryotic proteins also contain 5.4% proline and 5.3% isoleucine compared with 4.0% proline and ≈ 7.5% isoleucine in the prokaryotes. All these three differences contribute to the increased disorder in eukaryotic proteins. It is tempting to speculate that the increase in serine frequencies in eukaryotes is related to regulation by kinases, but direct evidence for this is lacking. The differences are observed in all phyla, protein families, structural regions and type of protein but are most pronounced in disordered and linker regions. The observation that differences in the abundance of three amino acids cause the difference in disorder between eukaryotic and prokaryotic proteins raises the question: Are amino acid frequencies different in eukaryotic linkers because the linkers are more disordered or do the differences cause the increased disorder?

Intrinsic disorder is essential for various functions in eukaryotic cells and is a signature of eukaryotic proteins. Here, we try to understand the origin of the difference in disorder between eukaryotic and prokaryotic proteins. We show that eukaryotic proteins contain more extended linker regions and that these linker regions are significantly more disordered. Further, we show, for the first time, that the difference in disorder originates from a systematic difference in amino acid frequencies between eukaryotic and prokaryotic proteins. Three amino acids contribute to the difference in disorder; serine and proline are more abundant in eukaryotic linkers, while isoleucine is less frequent. These shifts in frequencies are observed in all phyla, protein families, structural regions and type of protein but are most pronounced in disordered and linker regions. It is tempting to speculate that the increase in serine frequencies in eukaryotes is related to regulation by kinases, but direct evidence for this is lacking. Anyhow the widespread of the shifts in abundance indicates that the differences are ancient and caused be some yet not fully understood selective difference acting on eukaryotic and prokaryotic proteins.

Fold combinations in multi-domain proteins

Domain-domain interactions in multi-domain proteins play an important role in the combined function of individual domains for the overall biological activity of the protein. The functions of the tethered domains are often coupled and hence, limited numbers of domain architectures with defined folds are known in nature. Therefore, it is of interest to document the available fold-fold combinations and their preference in multi-domain proteins. Hence, we analyzed all multi-domain proteins with known structures in the protein databank and observed that only about 860 fold-fold combinations are present among them. Analyses of multi-domain proteins represented in sequence database result in recognition of 29,860 fold-fold combinations and it accounts for only 2.8% of the theoretically possible 1,036,080 (1439C2) fold-fold combinations. The observed preference for fold-fold combinations in multi-domain proteins is interesting in the context of multiple functions through structural adaptation by gene fusion.

Comparative and Functional Algal Genomics

Over 100 whole-genome sequences from algae are published or soon to be published. The rapidly increasing availability of these fundamental resources is changing how we understand one of the most diverse, complex, and understudied groups of photosynthetic eukaryotes. Genome sequences provide a window into the functional potential of individual algae, with phylogenomics and functional genomics as tools for contextualizing and transferring knowledge from reference organisms into less well-characterized systems. Remarkably, over half of the proteins encoded by algal genomes are of unknown function, highlighting the volume of functional capabilities yet to be discovered. In this review, we provide an overview of publicly available algal genomes, their associated protein inventories, and their quality, with a summary of the statuses of protein function understanding and predictions.

Backbone and side-chain chemical shift assignments of full-length, apo, human Pin1, a phosphoprotein regulator with interdomain allostery

Pin1 is a human peptidyl-prolyl cis-trans isomerase important for the regulation of phosphoproteins that are implicated in many diseases including cancer and Alzheimer's. Further biophysical study of Pin1 will elucidate the importance of the two-domain system to regulate its own activity. Here, we report near-complete backbone and side-chain ¹H, ¹³C and ¹⁵N NMR chemical shift assignments of full-length, apo Pin1 for the purpose of studying interdomain allostery and dynamics.

Integrating NMR, SAXS, and Atomistic Simulations: Structure and Dynamics of a Two-Domain Protein

Multidomain proteins with two or more independently folded functional domains are prevalent in nature. Whereas most multidomain proteins are linked linearly in sequence, roughly one-tenth possess domain insertions where a guest domain is implanted into a loop of a host domain, such that the two domains are connected by a pair of interdomain linkers. Here, we characterized the influence of the interdomain linkers on the structure and dynamics of a domain-insertion protein in which the guest LysM domain is inserted into a central loop of the host CVNH domain. Expanding upon our previous crystallographic and NMR studies, we applied SAXS in combination with NMR paramagnetic relaxation enhancement to construct a structural model of the overall two-domain system. Although the two domains have no fixed relative orientation, certain orientations were found to be preferred over others. We also assessed the accuracies of molecular mechanics force fields in modeling the structure and dynamics of tethered multidomain proteins by integrating our experimental results with microsecond-scale atomistic molecular dynamics simulations. In particular, our evaluation of two different combinations of the latest force fields and water models revealed that both combinations accurately reproduce certain structural and dynamical properties, but are inaccurate for others. Overall, our study illustrates the value of integrating experimental NMR and SAXS studies with long timescale atomistic simulations for characterizing structural ensembles of flexibly linked multidomain systems.

Grammar of protein domain architectures

Genomes appear similar to natural language texts, and protein domains can be treated as analogs of words. To investigate the linguistic properties of genomes further, we calculated the complexity of the “protein languages” in all major branches of life and identified a nearly universal value of information gain associated with the transition from a random domain arrangement to the current protein domain architecture. An exploration of the evolutionary relationship of the protein languages identified the domain combinations that discriminate between the major branches of cellular life. We conclude that there exists a “quasi-universal grammar” of protein domains and that the nearly constant information gain we identified corresponds to the minimal complexity required to maintain a functional cell.

From an abstract, informational perspective, protein domains appear analogous to words in natural languages in which the rules of word association are dictated by linguistic rules, or grammar. Such rules exist for protein domains as well, because only a small fraction of all possible domain combinations is viable in evolution. We employ a popular linguistic technique, n-gram analysis, to probe the “proteome grammar”—that is, the rules of association of domains that generate various domain architectures of proteins. Comparison of the complexity measures of “protein languages” in major branches of life shows that the relative entropy difference (information gain) between the observed domain architectures and random domain combinations is highly conserved in evolution and is close to being a universal constant, at ∼1.2 bits. Substantial deviations from this constant are observed in only two major groups of organisms: a subset of Archaea that appears to be cells simplified to the limit, and animals that display extreme complexity. We also identify the n-grams that represent signatures of the major branches of cellular life. The results of this analysis bolster the analogy between genomes and natural language and show that a “quasi-universal grammar” underlies the evolution of domain architectures in all divisions of cellular life. The nearly universal value of information gain by the domain architectures could reflect the minimum complexity of signal processing that is required to maintain a functioning cell.

Messages From the Past: New Insights in Plant Lectin Evolution

Lectins are a large and diverse class of proteins, found in all kingdoms of life. Plants are known to express different types of carbohydrate-binding proteins, each containing at least one particular lectin domain which enables them to specifically recognize and bind carbohydrate structures. The group of plant lectins is heterogeneous in terms of structure, biological activity and function. Lectins control various aspects of plant development and defense. Some lectins facilitate recognition of exogenous danger signals or play a role in endogenous signaling pathways, while others are considered as storage proteins or involved in symbiotic relationships. In this study, we revisit the origin of the different plant lectin families in view of the recently reshaped tree of life. Due to new genomic sampling of previously unknown microbial lineages, the tree of life has expanded and was reshaped multiple times. In addition, more plant genomes especially from basal Phragmoplastophyta, bryophytes, and Salviniales (e.g., Chara braunii, Marchantia polymorpha, Physcomitrella patens, Azolla filiculoides, and Salvinia cucullata) have been analyzed, and annotated genome sequences have become accessible. We searched 38 plant genome sequences including core eudicots, monocots, gymnosperms, fern, lycophytes, bryophytes, charophytes, chlorophytes, glaucophytes, and rhodophytes for lectin motifs, performed an extensive comparative analysis of lectin domain architectures, and determined the phylogenetic and evolutionary history of lectins in the plant lineage. In conclusion, we describe the conservation of particular domains in plant lectin sequences obtained from algae to higher plants. The strong conservation of several lectin motifs highlights their significance for plants.

A novel phylogenetic tree based on the presence of protein domains in selected actinobacteria

Protein functional domains are semi-autonomous parts of proteins capable of functioning independently. One protein may contain several domains and one domain may be present in different protein sequences. Thus, protein domains represent the niche specific adaptive nature of an organism. We hypothesized that the presence and absence of protein domains in an organism could be used to make a phylogenetic tree, which may better depict the biotope (niche). Here, we selected 100 actinobacteria and built a phylogenetic tree depending upon the presence and absence of protein domains. Strains of different genera from the same niche were found to cluster together suggesting niche specific domain acquisition among selected strains. Thus, the domain based phylogeny clustered the selected actinobacteria mainly according to their niche rather than their taxonomic classification.

An Overlapping Region between the Two Terminal Folding Units of the Outer Surface Protein A (OspA) Controls Its Folding Behavior

Although many naturally occurring proteins consist of multiple domains, most studies on protein folding to date deal with single-domain proteins or isolated domains of multi-domain proteins. Studies of multi-domain protein folding are required for further advancing our understanding of protein folding mechanisms. Borrelia outer surface protein A (OspA) is a β-rich two-domain protein, in which two globular domains are connected by a rigid and stable single-layer β-sheet. Thus, OspA is particularly suited as a model system for studying the interplays of domains in protein folding. Here, we studied the equilibria and kinetics of the urea-induced folding-unfolding reactions of OspA probed with tryptophan fluorescence and ultraviolet circular dichroism. Global analysis of the experimental data revealed compelling lines of evidence for accumulation of an on-pathway intermediate during kinetic refolding and for the identity between the kinetic intermediate and a previously described equilibrium unfolding intermediate. The results suggest that the intermediate has the fully native structure in the N-terminal domain and the single layer β-sheet, with the C-terminal domain still unfolded. The observation of the productive on-pathway folding intermediate clearly indicates substantial interactions between the two domains mediated by the single-layer β-sheet. We propose that a rigid and stable intervening region between two domains creates an overlap between two folding units and can energetically couple their folding reactions.