The nature of protein domain evolution: shaping the interaction network

High-throughput discovery and characterization of viral transcriptional effectors in human cells

Viruses encode transcriptional regulatory proteins critical for controlling viral and host gene expression. Given their multifunctional nature and high sequence divergence, it is unclear which viral proteins can affect transcription and which specific sequences contribute to this function. Using a high-throughput assay, we measured the transcriptional regulatory potential of over 60,000 protein tiles across ∼1,500 proteins from 11 coronaviruses and all nine human herpesviruses. We discovered hundreds of transcriptional effector domains, including a conserved repression domain in all coronavirus Spike homologs, dual activation-repression domains in viral interferon regulatory factors (VIRFs), and an activation domain in six herpesvirus homologs of the single-stranded DNA-binding protein that we show is important for viral replication and late gene expression in Kaposi's sarcoma-associated herpesvirus (KSHV). For the effector domains we identified, we investigated their mechanisms via high-throughput sequence and chemical perturbations, pinpointing sequence motifs essential for function. This work massively expands viral protein annotations, serving as a springboard for studying their biological and health implications and providing new candidates for compact gene regulation tools.

Phylogenetic and Evolutionary Analysis of Plant Small RNA 2'-O-Methyltransferase (HEN1) Protein Family

HUA ENHANCER 1 (HEN1) is a pivotal mediator in protecting sRNAs from 3'-end uridylation and 3' to 5' exonuclease-mediated degradation in plants. Here, we investigated the pattern of the HEN1 protein family evolutionary history and possible relationships in the plant lineages using protein sequence analyses and conserved motifs composition, functional domain identification, architecture, and phylogenetic tree reconstruction and evolutionary history inference. According to our results, HEN1 protein sequences bear several highly conserved motifs in plant species retained during the evolution from their ancestor. However, several motifs are present only in Gymnosperms and Angiosperms. A similar trend showed for their domain architecture. At the same time, phylogenetic analysis revealed the grouping of the HEN1 proteins in the three main super clads. In addition, the Neighbor-net network analysis result provides some nodes have multiple parents indicating a few conflicting signals in the data, which is not the consequence of sampling error, the effect of the selected model, or the estimation method. By reconciling the protein and species tree, we considered the gene duplications in several given species and found 170 duplication events in the evolution of HEN1 in the plant lineages. According to our analysis, the main HEN1 superclass mostly showed orthologous sequences that illustrate the vertically transmitting of HEN1 to the main lines. However, in both orthologous and paralogs, we predicted insignificant structural deviations. Our analysis implies that small local structural changes that occur continuously during the folds can moderate the changes created in the sequence. According to our results, we proposed a hypothetical model and evolutionary trajectory for the HEN1 protein family in the plant kingdom.

Consequences of Genetic Recombination on Protein Folding Stability

Genetic recombination is a common evolutionary mechanism that produces molecular diversity. However, its consequences on protein folding stability have not attracted the same attention as in the case of point mutations. Here, we studied the effects of homologous recombination on the computationally predicted protein folding stability for several protein families, finding less detrimental effects than we previously expected. Although recombination can affect multiple protein sites, we found that the fraction of recombined proteins that are eliminated by negative selection because of insufficient stability is not significantly larger than the corresponding fraction of proteins produced by mutation events. Indeed, although recombination disrupts epistatic interactions, the mean stability of recombinant proteins is not lower than that of their parents. On the other hand, the difference of stability between recombined proteins is amplified with respect to the parents, promoting phenotypic diversity. As a result, at least one third of recombined proteins present stability between those of their parents, and a substantial fraction have higher or lower stability than those of both parents. As expected, we found that parents with similar sequences tend to produce recombined proteins with stability close to that of the parents. Finally, the simulation of protein evolution along the ancestral recombination graph with empirical substitution models commonly used in phylogenetics, which ignore constraints on protein folding stability, showed that recombination favors the decrease of folding stability, supporting the convenience of adopting structurally constrained models when possible for inferences of protein evolutionary histories with recombination.

Protein domains provide a new layer of information for classifying human variations in rare diseases

Introduction: Using the ACMG-AMP guidelines for the interpretation of sequence variants, it remains difficult to meet the criterion associated with the protein domain, PM1, which is assigned in only about 10% of cases, whereas the criteria related to variant frequency, PM2/BA1/BS1, is reported in 50% of cases. To improve the classification of human missense variants using protein domains information, we developed the DOLPHIN system (https://dolphin.mmg-gbit.eu). Methods: We used Pfam alignments of eukaryotes to define DOLPHIN scores to identify protein domain residues and variants that have a significant impact. In parallel, we enriched gnomAD variants frequencies for each domains' residue. These were validated using ClinVar data. Results: We applied this method to all potential human transcripts' variants, resulting in 30.0% being assigned a PM1 label, whereas 33.2% were eligible for a new benign support criterion, BP8. We also showed that DOLPHIN provides an extrapolated frequency for 31.8% of the variants, compared to the original frequency available in gnomAD for 7.6% of them. Discussion: Overall, DOLPHIN allows a simplified use of the PM1 criterion, an expanded application of the PM2/BS1 criteria and the creation of a new BP8 criterion. DOLPHIN could facilitate the classification of amino acid substitutions in protein domains that cover nearly 40% of proteins and represent the sites of most pathogenic variants.

Pathogen-driven gene expression patterns lead to a novel approach to the identification of common therapeutic targets

Developing a common medication strategy for disease control and management could be greatly beneficial. Investigating the differences between diseased and healthy states using differentially expressed genes aids in understanding disease pathophysiology and enables the exploration of protein-drug interactions. This study aimed to find the most common genes in diarrhea-causing bacteria such as Salmonella enterica serovar Typhimurium, Campylobacter jejuni, Escherichia coli, Shigella dysenteriae (CESS) to find new drugs. Thus, differential gene expression datasets of CESS were screened through computational algorithms and programming. Subsequently, hub and common genes were prioritized from the analysis of extensive protein-protein interactions. Binding predictions were performed to identify the common potential therapeutic targets of CESS. We identified a total of 827 dysregulated genes that are highly linked to CESS. Notably, no common gene interaction was found among all CESS bacteria, but we identified 3 common genes in both Salmonella-Escherichia and Escherichia-Campylobacter infections. Later, out of 73 protein complexes, molecular simulations confirmed 5 therapeutic candidates from the CESS. We have developed a new pipeline for identifying therapeutic targets for a common medication strategy against CESS. However, further wet-lab validation is needed to confirm their effectiveness.

Artificial intelligence channelizing protein-peptide interactions pipeline for host-parasite paradigm in IL-10 and IL-12 reciprocity by SHP-1

Identification of molecular targets in any cellular phenomena is a challenge and a path that one endeavors upon independently. We have identified a phosphatase SHP-1 as a point of intervention of IL-10 and IL-12 reciprocity in leishmaniasis. The therapeutic model that we have developed uniquely targets this protein but the pipeline in general can be used by the researchers for their unique targets. Naturally occurring peptides are well known for their biochemical participation in cellular functions hence we were motivated to use this uniqueness of physico-chemical properties of peptides conferred by amino acids through machine learning to channelize a mode of therapeutic exploration in infectious disease. Using computational approaches, we identified high order sequence conservation and similarity in SHP-1 sequence which was also evolutionarily conserved, complete structure of Mouse SHP-1 was predicted and validated, a unique motif of the same was identified against which library of synthetic peptides were designed and validated followed by screening the library by docking them with MuSHP-1 protein structure. Our findings showed 3 peptides had high binding affinity and in future can be validated using cell based and in vivo assays.

Inter-subunit crosstalk via PDZ synergistically governs allosteric activation of proapoptotic HtrA2

The mitochondrial serine protease High-temperature requirement A2 (HtrA2) is associated with various diseases including neurodegenerative disorders and cancer. Despite availability of structural details, the reports on HtrA2's mechanistic regulation that varies with the type of activation signals still remain non-concordant. To expound the role of regulatory PDZ (Postsynaptic density-95/Discs large/Zonula occludens-1) domains in multimodal activation of HtrA2, we generated heterotrimeric HtrA2 variants comprising different numbers of PDZs and/or active-site mutations. Sequential deletion of PDZs from the trimeric ensemble significantly affected its residual activity in a way that proffered a hypothesis advocating inter-molecular allosteric crosstalk via PDZs in HtrA2. Furthermore, structural and computational snapshots affirmed the role of PDZs in secondary structural element formation around the regulatory loops and coordinated reorganization of the N-terminal region. Therefore, apart from providing cues for devising structure-guided therapeutic strategies, this study establishes a physiologically relevant working model of complex allosteric regulation through a trans-mediated cooperatively shared energy landscape.

Identification and relative expression analysis of CaFRK gene family in pepper

Fructokinase is the main catalytic enzyme for fructose phosphorylation and can also act as a glucose receptor and signal molecule to regulate the metabolism of plants, which plays an important role in plant growth and development. In this study, the CaFRK gene family and their molecular characteristics are systematically identified and analyzed, and the specific expression of CaFRKs under different tissues, abiotic stresses and hormone treatments were explored. Nine FRK genes were authenticated in pepper genome database, which were dispersedly distributed on eight reference chromosomes and predicted to localize in the cytoplasm. Many cis-acting elements that respond to light, different stresses, hormones and tissue-specific expression were found in the promoters of CaFRKs. FRK proteins of four species including Capsicum annuum, Arabidopsis thaliana, Solanum lycopersicum and Oryza sativa were divided into four groups via phylogenetic analysis. The collinearity analysis showed that there were two collinear gene pairs between CaFRKs and AtFRKs. In addition, it was significantly found that CaFRK9 expressed far higher in flower than other tissues, and the relative expression of CaFRK9 was gradually enhanced with the development of flower buds in fertile accessions, 8B, R1 and F1. Nevertheless, CaFRK9 hardly expressed in all stages of cytoplasmic male sterile lines. Based on the quantitative real-time PCR, most of CaFRK genes showed significant up-regulation under low-temperature, NaCl and PEG6000 treatments. On the contrary, the expression levels of most CaFRKs revealed a various trend in response to hormone treatments (IAA, ABA, GA3, SA and MeJA). This study systematically analyzed CaFRK gene family and studied its expression pattern, which lay the foundation of CaFRK genes cloning and functional verification response to abiotic stresses, and provides new insights into exploring the CaFRK genes on the pollen development in pepper.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03196-1.

Conserved Structure and Evolution of DPF Domain of PHF10-The Specific Subunit of PBAF Chromatin Remodeling Complex

Transcription activation factors and multisubunit coactivator complexes get recruited at specific chromatin sites via protein domains that recognize histone modifications. Single PHDs (plant homeodomains) interact with differentially modified H3 histone tails. Double PHD finger (DPF) domains possess a unique structure different from PHD and are found in six proteins: histone acetyltransferases MOZ and MORF; chromatin remodeling complex BAF (DPF1–3); and chromatin remodeling complex PBAF (PHF10). Among them, PHF10 stands out due to the DPF sequence, structure, and functions. PHF10 is ubiquitously expressed in developing and adult organisms as four isoforms differing in structure (the presence or absence of DPF) and transcription regulation functions. Despite the importance of the DPF domain of PHF10 for transcription activation, its structure remains undetermined. We performed homology modeling of the human PHF10 DPF domain and determined common and distinct features in structure and histone modifications recognition capabilities, which can affect PBAF complex chromatin recruitment. We also traced the evolution of DPF1–3 and PHF10 genes from unicellular to vertebrate organisms. The data reviewed suggest that the DPF domain of PHF10 plays an important role in SWI/SNF-dependent chromatin remodeling during transcription activation.

Mix and match: Patchwork domain evolution of the land plant-specific Ca2+-permeable mechanosensitive channel MCA

Multidomain proteins can have a complex evolutionary history that may involve de novo domain evolution, recruitment and / or recombination of existing domains and domain losses. Here, the domain evolution of the plant-specific Ca²⁺-permeable mechanosensitive channel protein, MID1-COMPLEMENTING ACTIVITY (MCA), was investigated. MCA, a multidomain protein, possesses a Ca²⁺-influx-MCA^func domain and a PLAC8 domain. Profile Hidden Markov Models (HMMs) of domains were assessed in 25 viridiplantae proteomes. While PLAC8 was detected in plants, animals, and fungi, MCA^func was found in streptophytes but not in chlorophytes. Full MCA proteins were only found in embryophytes. We identified the MCA^func domain in all streptophytes including charophytes where it appeared in E3 ubiquitin ligase-like proteins. Our Maximum Likelihood (ML) analyses suggested that the MCA^func domain evolved early in the history of streptophytes. The PLAC8 domain showed similarity to Plant Cadmium Resistance (PCR) genes, and the coupling of MCA^func and PLAC8 seemed to represent a single evolutionary event. This combination is unique in MCA, and does not exist in other plant mechanosensitive channels. Within angiosperms, gene duplications increased the number of MCAs. Considering their role in mechanosensing in roots, MCA might be instrumental for the rise of land plants. This study provides a textbook example of de novo domain emergence, recombination, duplication, and losses, leading to the convergence of function of proteins in plants.

Characterizing the function of domain linkers in regulating the dynamics of multi-domain fusion proteins by microsecond molecular dynamics simulations and artificial intelligence

Multi-domain proteins are not only formed through natural evolution but can also be generated by recombinant DNA technology. Because many fusion proteins can enhance the selectivity of cell targeting, these artificially produced molecules, called multi-specific biologics, are promising drug candidates, especially for immunotherapy. Moreover, the rational design of domain linkers in fusion proteins is becoming an essential step toward a quantitative understanding of the dynamics in these biopharmaceutics. We developed a computational framework to characterize the impacts of peptide linkers on the dynamics of multi-specific biologics. Specifically, we first constructed a benchmark containing six types of linkers that represent various lengths and degrees of flexibility and used them to connect two natural proteins as a test system. We then projected the microsecond dynamics of these proteins generated from Anton onto a coarse-grained conformational space. We further analyzed the similarity of dynamics among different proteins in this low-dimensional space by a neural-network-based classification model. Finally, we applied hierarchical clustering to place linkers into different subgroups based on the classification results. The clustering results suggest that the length of linkers, which is used to spatially separate different functional modules, plays the most important role in regulating the dynamics of this fusion protein. Given the same number of amino acids, linker flexibility functions as a regulator of protein dynamics. In summary, we illustrated that a new computational strategy can be used to study the dynamics of multi-domain fusion proteins by a combination of long timescale molecular dynamics simulation, coarse-grained feature extraction, and artificial intelligence.

Linking molecular evolution to molecular grafting

Molecular grafting is a strategy for the engineering of molecular scaffolds into new functional agents, such as next-generation therapeutics. Despite its wide use, studies so far have focused almost exclusively on demonstrating its utility rather than understanding the factors that lead to either poor or successful grafting outcomes. Here, we examine protein evolution and identify parallels between the natural process of protein functional diversification and the artificial process of molecular grafting. We discuss features of natural proteins that are correlated to innovability-the capacity to acquire new functions-and describe their implications to molecular grafting scaffolds. Disulfide-rich peptides are used as exemplars because they are particularly promising scaffolds onto which new functions can be grafted. This article provides a perspective on why some scaffolds are more suitable for grafting than others, identifying opportunities on how molecular grafting might be improved.

Universal and taxon-specific trends in protein sequences as a function of age

Extant protein-coding sequences span a huge range of ages, from those that emerged only recently to those present in the last universal common ancestor. Because evolution has had less time to act on young sequences, there might be 'phylostratigraphy' trends in any properties that evolve slowly with age. A long-term reduction in hydrophobicity and hydrophobic clustering was found in previous, taxonomically restricted studies. Here we perform integrated phylostratigraphy across 435 fully sequenced species, using sensitive HMM methods to detect protein domain homology. We find that the reduction in hydrophobic clustering is universal across lineages. However, only young animal domains have a tendency to have higher structural disorder. Among ancient domains, trends in amino acid composition reflect the order of recruitment into the genetic code, suggesting that the composition of the contemporary descendants of ancient sequences reflects amino acid availability during the earliest stages of life, when these sequences first emerged.

Understanding the Targeting Mechanisms of Multi-Specific Biologics in Immunotherapy with Multiscale Modeling

Immunotherapeutics are frequently associated with adverse side effects due to the elicitation of global immune modulation. To lower the risk of these side effects, recombinant DNA technology is employed to enhance the selectivity of cell targeting by genetically fusing different biomolecules, yielding new species referred to as multi-specific biologics. The design of new multi-specific biologics is a central challenge for the realization of new immunotherapies. To understand the molecular determinants responsible for regulating the binding between multi-specific biologics and surface-bound membrane receptors, we developed a multiscale computational framework that integrates various simulation approaches covering different timescales and spatial resolutions. Our model system of multi-specific biologics contains two natural ligands of immune receptors, which are covalently tethered by a peptide linker. Using this method, a number of interesting features of multi-specific biologics were identified. Our study therefore provides an important strategy to design the next-generation biologics for immunotherapy.

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Two proteins are connected by different linkers as a model of bispecific biologics

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Conformational dynamics of biologics are captured by microsecond MD simulations

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Coarse-grained simulations are used to test binding between biologics and receptors

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Biologics with long and flexible linkers are more efficient in targeting receptors

Red Imported Fire Ant (Solenopsis invicta) Chemosensory Proteins Are Expressed in Tissue, Developmental, and Caste-Specific Patterns

The red imported fire ant, Solenopsis invicta, is a eusocial invasive insect that has spread worldwide. Chemosensory proteins (CSPs) are ligand-binding proteins that participate in a diverse range of physiological processes that include olfaction and chemical transport. Here, we performed a systematic survey of the expression of the 21 gene S. invicta CSP family that includes at least two groups of apparent S. invicta-specific gene expansions. These data revealed caste, tissue, and developmental stage-specific differential expression of the SiCSPs. In general, moderate to high SiCSP expression was seen in worker antennae and abdomen tissues with lower expression in head/thorax regions. Male and female alates showed high antennal expression of fewer SiCSPs, with the female alate thorax showing comparatively high SiCSP expression. SiCSP expression was lower in male alates tissues compared to workers and female alates, albeit with some highly expressed SiCSPs. SiCSP expression was low during development including in eggs, larvae (early and late instars), and pupae. Global analyses revealed examples of conserved, divergent, and convergent SiCSP expression patterns linked to phylogenetic relationships. The developmental and caste-specific variation seen in SiCSP expression patterns suggests specific functional diversification of CSPs that may translate into differential chemical recognition and communication among individuals and/or reflect other cellular roles of CSPs. Our results support a model for CSPs acting as general ligand carriers involved in a wide range of physiological processes beyond olfaction. As compared to the expression patterns of the S. invicta odorant binding proteins (OBPs), an inverse correlation between SiOBP and SiCSP expression was seen, suggesting potential complementary and/or compensatory functions between these two classes of ligand carriers.

Deciphering the functional role of hypothetical proteins from Chloroflexus aurantiacs J-10-f1 using bioinformatics approach

Chloroflexus aurantiacus J-10-f1 is an anoxygenic, photosynthetic, facultative autotrophic gram negative bacterium found from hot spring at a temperature range of 50-60°C. It can sustain itself in dark only if oxygen is available thereby exhibiting a dark orange color, however display a dark green color when grown in sunlight. Genome of the organism contains total of 3853 proteins out of which 785 (~20%) proteins are uncharacterised or hypothetical proteins (HPs). Therefore in this work we have characterized the 785 hypothetical proteins of Chloroflexus aurantiacus J-10-f1 using bioinformatics tools and databases. HPs annotated by more than five domain prediction tools were filtered and named high confidence-hypothetical proteins (HC-HPs). These HC-HPs were further annotated by calculating their physiochemical properties, homologous, subcellular locations, signal peptides and transmembrane regions. We found most of the HC-HPs were involved in photosynthesis, carbohydrate metabolism, biofuel production and cellulose synthesis processes. Furthermore, few of these HC-HPs could provide resistance to bacteria at high temperature due to their thermophilic nature. Hence these HC-HPs have the potential to be used in industrial as well as in biomedical needs. To conclude, the bioinformatics approach used in this study provides an insight to better understand the nature and role of Chloroflexus aurantiacus J-10-f1 hypothetical proteins.

One gene, multiple ecological strategies: A biofilm regulator is a capacitor for sustainable diversity

Many organisms, including bacteria, live in fluctuating environments that require attachment and dispersal. These lifestyle decisions require processing of multiple external signals by several genetic pathways, but how they are integrated is largely unknown. We conducted multiple evolution experiments totaling >20,000 generations with Burkholderia cenocepacia populations grown in a model of the biofilm life cycle and identified parallel mutations in one gene, rpfR, that is a conserved central regulator. Because RpfR has multiple sensor and catalytic domains, different mutations can produce different ecological strategies that can coexist and even increase net growth. This study demonstrates that a single gene may coordinate complex life histories in biofilm-dwelling bacteria and that selection in defined environments can reshape niche breadth by single mutations.

Many bacteria cycle between sessile and motile forms in which they must sense and respond to internal and external signals to coordinate appropriate physiology. Maintaining fitness requires genetic networks that have been honed in variable environments to integrate these signals. The identity of the major regulators and how their control mechanisms evolved remain largely unknown in most organisms. During four different evolution experiments with the opportunist betaproteobacterium Burkholderia cenocepacia in a biofilm model, mutations were most frequently selected in the conserved gene rpfR. RpfR uniquely integrates two major signaling systems—quorum sensing and the motile–sessile switch mediated by cyclic-di-GMP—by two domains that sense, respond to, and control the synthesis of the autoinducer cis-2-dodecenoic acid (BDSF). The BDSF response in turn regulates the activity of diguanylate cyclase and phosphodiesterase domains acting on cyclic-di-GMP. Parallel adaptive substitutions evolved in each of these domains to produce unique life history strategies by regulating cyclic-di-GMP levels, global transcriptional responses, biofilm production, and polysaccharide composition. These phenotypes translated into distinct ecology and biofilm structures that enabled mutants to coexist and produce more biomass than expected from their constituents grown alone. This study shows that when bacterial populations are selected in environments challenging the limits of their plasticity, the evolved mutations not only alter genes at the nexus of signaling networks but also reveal the scope of their regulatory functions.

Artificial protein sequences enable recognition of vicinal and distant protein functional relationships

High divergence in protein sequences makes the detection of distant protein relationships through homology-based approaches challenging. Grouping protein sequences into families, through similarities in either sequence or 3-D structure, facilitates in the improved recognition of protein relationships. In addition, strategically designed protein-like sequences have been shown to bridge distant structural domain families by serving as artificial linkers. In this study, we have augmented a search database of known protein domain families with such designed sequences, with the intention of providing functional clues to domain families of unknown structure. When assessed using representative query sequences from each family, we obtain a success rate of 94% in protein domain families of known structure. Further, we demonstrate that the augmented search space enabled fold recognition for 582 families with no structural information available a priori. Additionally, we were able to provide reliable functional relationships for 610 orphan families. We discuss the application of our method in predicting functional roles through select examples for DUF4922, DUF5131, and DUF5085. Our approach also detects new associations between families that were previously not known to be related, as demonstrated through new sub-groups of the RNA polymerase domain among three distinct RNA viruses. Taken together, designed sequences-augmented search databases direct the detection of meaningful relationships between distant protein families. In turn, they enable fold recognition and offer reliable pointers to potential functional sites that may be probed further through direct mutagenesis studies.

Pseudo-RNA-Binding Domains Mediate RNA Structure Specificity in Upstream of N-Ras

RNA-binding proteins (RBPs) commonly feature multiple RNA-binding domains (RBDs), which provide these proteins with a modular architecture. Accumulating evidence supports that RBP architectural modularity and adaptability define the specificity of their interactions with RNA. However, how multiple RBDs recognize their cognate single-stranded RNA (ssRNA) sequences in concert remains poorly understood. Here, we use Upstream of N-Ras (Unr) as a model system to address this question. Although reported to contain five ssRNA-binding cold-shock domains (CSDs), we demonstrate that Unr includes an additional four CSDs that do not bind RNA (pseudo-RBDs) but are involved in mediating RNA tertiary structure specificity by reducing the conformational heterogeneity of Unr. Disrupting the interactions between canonical and non-canonical CSDs impacts RNA binding, Unr-mediated translation regulation, and the Unr-dependent RNA interactome. Taken together, our studies reveal a new paradigm in protein-RNA recognition, where interactions between RBDs and pseudo-RBDs select RNA tertiary structures, influence RNP assembly, and define target specificity.

Evolution and Functional Divergence of the Fructokinase Gene Family in Populus

New kinase has emerged throughout evolution, but how new kinase evolve while maintaining their functions and acquiring new functions remains unclear. Fructokinase (FRK), the gateway kinase to fructose metabolism, plays essential roles in plant development, and stress tolerance. Here, we explored the evolution of FRK gene family in 20 plant species (from green algae to angiosperms) and their functional roles in Populus. We identified 125 putative FRK genes in the 20 plant species with an average of 6 members per species. Phylogenetic analysis separated these 125 genes into 8 clades including 3 conserved clades and 5 specific clades, the 5 of which only exist in green algae or angiosperms. Evolutionary analysis revealed that FRK genes in ancient land plants have the largest number of functional domains with the longest amino acid sequences, and the length of FRK genes became shorter during the transition to vascular plants. This was accompanied by loss, acquisition, and diversification of functional domains. In Populus, segmental duplication appears to be the main mechanism for the expansion of FRK genes. Specially, most FRK genes duplicated in salicoids are regulated by Populus-specific microRNAs. Furthermore, compared with common FRKs, Populus-specific FRKs have showed higher expression specificity and are associated with fewer growth and wood property traits, which suggests that these FRKs may have undergone functional divergence. Our study explores the specific roles of FRKs in the Populus genome and provides new insights for functional investigation of this gene family.

A critical review of five machine learning-based algorithms for predicting protein stability changes upon mutation

A number of machine learning (ML)-based algorithms have been proposed for predicting mutation-induced stability changes in proteins. In this critical review, we used hypothetical reverse mutations to evaluate the performance of five representative algorithms and found all of them suffer from the problem of overfitting. This approach is based on the fact that if a wild-type protein is more stable than a mutant protein, then the same mutant is less stable than the wild-type protein. We analyzed the underlying issues and suggest that the main causes of the overfitting problem include that the numbers of training cases were too small, and the features used in the models were not sufficiently informative for the task. We make recommendations on how to avoid overfitting in this important research area and improve the reliability and robustness of ML-based algorithms in general.

Domain-based Comparative Analysis of Bacterial Proteomes: Uniqueness, Interactions, and the Dark Matter

Background

Proteins may have none, single, double, or multiple domains, while a single domain may appear in multiple proteins. Their distribution patterns may have impacts on bacterial physi-ology and lifestyle.Objective: This study aims to understand how domains are distributed and duplicated in bacterial prote-omes, in order to better understand bacterial physiology and lifestyles.

Methods

In this study, we used 16712 Hidden Markov Models to screen 944 bacterial reference prote-omes versus a threshold E-value<0.001. The number of non-redundant domains and duplication rates of redundant domains for each species were calculated. The unique domains, if any, were also identified for each species. In addition, the properties of no-domain proteins were investigated in terms of physico-chemical properties.

Results

The increasing number of non-redundant domains for a bacterial proteome follows the trend of an asymptotic function. The domain duplication rate is positively correlated with proteome size and in-creases more rapidly. The high percentage of single-domain proteins is more associated with small pro-teome size. For each proteome, unique domains were also obtained. Moreover, no-domain proteins show differences with the other three groups for several physicochemical properties analysed in this study.

Conclusion

The study confirmed that a low domain duplication rate and a high percentage of single-domain proteins are more likely to be associated with bacterial host-dependent or restricted niche-adapted lifestyle. In addition, the unique lifestyle and physiology were revealed based on the analysis of species-specific domains and core domain interactions or co-occurrences.

Directed evolution of the metalloproteinase inhibitor TIMP-1 reveals that its N- and C-terminal domains cooperate in matrix metalloproteinase recognition

Tissue inhibitors of metalloproteinases (TIMPs) are natural inhibitors of matrix metalloproteinases (MMPs), enzymes that contribute to cancer and many inflammatory and degenerative diseases. The TIMP N-terminal domain binds and inhibits an MMP catalytic domain, but the role of the TIMP C-terminal domain in MMP inhibition is poorly understood. Here, we employed yeast surface display for directed evolution of full-length human TIMP-1 to develop MMP-3-targeting ultrabinders. By simultaneously incorporating diversity into both domains, we identified TIMP-1 variants that were up to 10-fold improved in binding MMP-3 compared with WT TIMP-1, with inhibition constants (K_i ) in the low picomolar range. Analysis of individual and paired mutations from the selected TIMP-1 variants revealed cooperative effects between distant residues located on the N- and C-terminal TIMP domains, positioned on opposite sides of the interaction interface with MMP-3. Crystal structures of MMP-3 complexes with TIMP-1 variants revealed conformational changes in TIMP-1 near the cooperative mutation sites. Affinity was strengthened by cinching of a reciprocal "tyrosine clasp" formed between the N-terminal domain of TIMP-1 and proximal MMP-3 interface and by changes in secondary structure within the TIMP-1 C-terminal domain that stabilize interdomain interactions and improve complementarity to MMP-3. Our protein engineering and structural studies provide critical insight into the cooperative function of TIMP domains and the significance of peripheral TIMP epitopes in MMP recognition. Our findings suggest new strategies to engineer TIMP proteins for therapeutic applications, and our directed evolution approach may also enable exploration of functional domain interactions in other protein systems.

The functional roles of the unstructured N- and C-terminal regions in αB-crystallin and other mammalian small heat-shock proteins

Small heat-shock proteins (sHsps), such as αB-crystallin, are one of the major classes of molecular chaperone proteins. In vivo, under conditions of cellular stress, sHsps are the principal defence proteins that prevent large-scale protein aggregation. Progress in determining the structure of sHsps has been significant recently, particularly in relation to the conserved, central and β-sheet structured α-crystallin domain (ACD). However, an understanding of the structure and functional roles of the N- and C-terminal flanking regions has proved elusive mainly because of their unstructured and dynamic nature. In this paper, we propose functional roles for both flanking regions, based around three properties: (i) they act in a localised crowding manner to regulate interactions with target proteins during chaperone action, (ii) they protect the ACD from deleterious amyloid fibril formation and (iii) the flexibility of these regions, particularly at the extreme C-terminus in mammalian sHsps, provides solubility for sHsps under chaperone and non-chaperone conditions. In the eye lens, these properties are highly relevant as the crystallin proteins, in particular the two sHsps αA- and αB-crystallin, are present at very high concentrations.

The Biology Complicated by Genetic Analysis

Genetics is used as a tool to study living systems because of a key assumption that the phenotypes of loss-of-function mutations on a gene indicate the gene's normal/native functions. I propose that inactivation of a gene not only suppresses the gene's native functions but may also create spurious functions that cause phenotypes irrelevant to the gene's native functions. Such spurious functions represent the otherwise dormant physical/chemical potentials of a living system, do not follow the existing rules built by natural selection, and can hardly be integrated with other functions using empirical data. Thus, the rationale of using loss-of-function phenotypic data to understand a living system is challenged. Fortunately, spurious functions are expected to be evolutionarily unstable while native functions should be conserved, suggesting a means of separating them. I argue that current biology is confused by the undiscerned use of genetic data and suggest a solution.

Natural diversity of cellulases, xylanases, and chitinases in bacteria

BACKGROUND

Glycoside hydrolases (GH) targeting cellulose, xylan, and chitin are common in the bacterial genomes that have been sequenced. Little is known, however, about the architecture of multi-domain and multi-activity glycoside hydrolases. In these enzymes, combined catalytic domains act synergistically and thus display overall improved catalytic efficiency, making these proteins of high interest for the biofuel technology industry.

RESULTS

Here, we identify the domain organization in 40,946 proteins targeting cellulose, xylan, and chitin derived from 11,953 sequenced bacterial genomes. These bacteria are known to be capable, or to have the potential, to degrade polysaccharides, or are newly identified potential degraders (e.g., Actinospica, Hamadaea, Cystobacter, and Microbispora). Most of the proteins we identified contain a single catalytic domain that is frequently associated with an accessory non-catalytic domain. Regarding multi-domain proteins, we found that many bacterial strains have unique GH protein architectures and that the overall protein organization is not conserved across most genera. We identified 217 multi-activity proteins with at least two GH domains for cellulose, xylan, and chitin. Of these proteins, 211 have GH domains targeting similar or associated substrates (i.e., cellulose and xylan), whereas only six proteins target both cellulose and chitin. Fifty-two percent of multi-activity GHs are hetero-GHs. Finally, GH6, -10, -44 and -48 domains were mostly C-terminal; GH9, -11, -12, and -18 were mostly N-terminal; and GH5 domains were either N- or C-terminal.

CONCLUSION

We identified 40,946 multi-domain/multi-activity proteins targeting cellulase, chitinase, and xylanase in bacterial genomes and proposed new candidate lineages and protein architectures for carbohydrate processing that may play a role in biofuel production.

Computational Prediction of Protein-Protein Interaction Networks: Algo-rithms and Resources

Protein interactions play an important role in the discovery of protein functions and pathways in biological processes. This is especially true in case of the diseases caused by the loss of specific protein-protein interactions in the organism. The accuracy of experimental results in finding protein-protein interactions, however, is rather dubious and high throughput experimental results have shown both high false positive beside false negative information for protein interaction. Computational methods have attracted tremendous attention among biologists because of the ability to predict protein-protein interactions and validate the obtained experimental results. In this study, we have reviewed several computational methods for protein-protein interaction prediction as well as describing major databases, which store both predicted and detected protein-protein interactions, and the tools used for analyzing protein interaction networks and improving protein-protein interaction reliability.