Introduction Infection with SARS-CoV-2 leads to coronavirus disease 2019 (COVID-19), which can result in acute respiratory distress syndrome and multiple organ failure. However, its comprehensive influence on pathological immune responses in the respiratory epithelium and peripheral immune cells is not yet fully understood. Methods In this study, we analyzed multiple public scRNA-seq datasets of nasopharyngeal swabs and peripheral blood to investigate the gene regulatory networks (GRNs) of healthy individuals and COVID-19 patients with mild/moderate and severe disease, respectively. Cell-cell communication networks among cell types were also inferred. Finally, validations were conducted using bulk RNA-seq and proteome data. Results Similar and dissimilar regulons were identified within or between epithelial and immune cells during COVID-19 severity progression. The relative transcription factors (TFs) and their targets were used to construct GRNs among different infection sites and conditions. Between respiratory epithelial and peripheral immune cells, different TFs tended to be used to regulate the activity of a cell between healthy individuals and COVID-19 patients, although they had some TFs in common. For example, XBP1, FOS, STAT1, and STAT2 were activated in both the epithelial and immune cells of virus-infected individuals. In contrast, severe COVID-19 cases exhibited activation of CEBPD in peripheral immune cells, while CEBPB was exclusively activated in respiratory epithelial cells. Moreover, in patients with severe COVID-19, although some inflammatory genes, such as S100A8/A9, were found to be upregulated in both respiratory epithelial and peripheral immune cells, their relative regulators can differ in terms of cell types. The cell-cell communication analysis suggested that epidermal growth factor receptor signaling among epithelia contributes to mild/moderate disease, and chemokine signaling among immune cells contributes to severe disease. Conclusion This study identified cell type- and condition-specific regulons in a wide range of cell types from the initial infection site to the peripheral blood, and clarified the diverse mechanisms of maladaptive responses to SARS-CoV-2 infection.

Despite the advances in surface-display systems for directed evolution, variants with high affinity are not always enriched due to undesirable biases that increase target-unrelated variants during biopanning. Here, our goal was to design a library containing improved variants from the information of the "weakly enriched" library where functional variants were weakly enriched. Deep sequencing for the previous biopanning result, where no functional antibody mimetics were experimentally identified, revealed that weak enrichment was partly due to undesirable biases during phage infection and amplification steps. The clustering analysis of the deep sequencing data from appropriate steps revealed no distinct sequence patterns, but a Bayesian machine learning model trained with the selected deep sequencing data supplied nine clusters with distinct sequence patterns. Phage libraries were designed on the basis of the sequence patterns identified, and four improved variants with target-specific affinity (EC50 = 80-277 nM) were identified by biopanning. The selection and use of deep sequencing data without undesirable bias enabled us to extract the information on prospective variants. In summary, the use of appropriate deep sequencing data and machine learning with the sequence data has the possibility of finding sequence space where functional variants are enriched.

BACKGROUND & AIMS: NF-E2-related factor 2 (NRF2) is a transcription factor that regulates cytoprotective gene expression in response to oxidative and electrophilic stresses. NRF2 activity is mainly controlled by Kelch-like ECH-associated protein 1 (KEAP1). Constitutive NRF2 activation by NRF2 mutations or KEAP1 dysfunction results in a poor prognosis for esophageal squamous cell carcinoma (ESCC) through the activation of cytoprotective functions. However, the detailed contributions of NRF2 to ESCC initiation or promotion have not been clarified. Here, we investigated the fate of NRF2-activated cells in the esophageal epithelium. METHODS: We generated tamoxifen-inducible, squamous epithelium-specific Keap1 conditional knockout (Keap1-cKO) mice in which NRF2 was inducibly activated in a subset of cells at the adult stage. Histological, quantitative reverse-transcription polymerase chain reaction (qRT‒PCR), single-cell RNA-sequencing (RNA-seq) and carcinogen experiments were conducted to analyze the Keap1-cKO esophagus. RESULTS: KEAP1-deleted/NRF2-activated cells and cells with normal NRF2 expression (KEAP1-normal cells) coexisted in the Keap1-cKO esophageal epithelium in approximately equal numbers, and NRF2-activated cells formed dysplastic lesions. NRF2-activated cells exhibited weaker attachment to the basement membrane and gradually disappeared from the epithelium. In contrast, neighboring KEAP1-normal cells exhibited accelerated proliferation and started dominating the epithelium but accumulated DNA damage that triggered carcinogenesis upon carcinogen exposure. CONCLUSIONS: Constitutive NRF2 activation promotes the selective elimination of epithelial cells via cell competition, but this competition induces DNA damage in neighboring KEAP1-normal cells, which predisposes them to chemical-induced ESCC.

T cell exhaustion is a state of T cell dysfunction during chronic infection and cancer. Antibody-targeting immune checkpoint inhibitors to reverse T cell exhaustion is a promising approach for cancer immunotherapy. However, molecular mechanisms of T cell exhaustion remain incompletely understood. Here, we performed a transcriptome analysis by integrating seven exhaustion datasets caused by multiple diseases in both humans and mice. In this study, an overlap of 21 upregulated and 37 downregulated genes was identified in human and mouse exhausted CD8+ T cells. These genes were significantly enriched in exhaustion response-related pathways, such as signal transduction, immune system processes, and regulation of cytokine production. Gene expression network analysis revealed that the well-documented exhaustion genes were defined as hub genes in upregulated genes. In addition, a weighted gene co-expression analysis identified 175 overlapping genes that were significantly correlated with the exhaustion trait in both humans and mice. This study found that overlapping six genes were significantly upregulated and highly related to T cell exhaustion. Finally, we revealed that CD200R1 and ADGRG1, less described previously in exhaustion, contributed to T cell exhaustion. Overall, our findings reveal the mechanisms of T cell exhaustion and provide an important reference to the immunology community.

<p>Antibody mimetics are proteins smaller than antibodies that have antigen-binding properties. Here, we used a combination of informatic selection and experimental verification to identify from a public database several candidate scaffold proteins. From those candidates, we selected a protein with high thermal stability, bacterial expression, and mutation tolerance and used molecular engineering and phage display selection techniques to develop the scaffold into an antibody mimetic with binding affinity for galactin-3, a biomarker of cancer and heart disease.</p>

Poly-ubiquitin (poly-Ub) is involved in various cellular processes through the linkage-specific recognition of Ub-binding domains (UBD). In this study, using molecular dynamics (MD) simulation together with an enhanced sampling method, we demonstrated that K63-linked di-Ub recognizes the NZF domain of TAB2, a zinc finger UBD, in an ensemble of highly dynamic structures that form from the weak interactions between UBD and the flexible linker connecting the two Ubs. However, the K63 di-Ub/TAB2 NZF complex showed a much more compact and stable ensemble than the non-native complexes, linear di-Ub/TAB2 NZF and K33 di-Ub/TAB2 NZF, that were modeled from linear di-Ub/HOIL-1L NZF and K33 di-Ub/TRABID NZF1, respectively. We further demonstrated the importance of the length and position of the Ub-Ub linker in the results of MD simulations of K63 di-Ub/TAB2 NZF by changing the Ub linkage from the native K63 to four different non-native linkages, linear, K6, K11, and K48, while maintaining inter-molecular contacts in the native complex. No systems with non-native linkage maintained the native binding configuration. These simulation results provide an atomistic picture of the linkage specific recognition of poly-Ubs leading to the biological functions such as cellular colocalization of various component proteins in the signal transduction pathways.

The Protein Data Bank Japan (PDBj), a member of the worldwide Protein Data Bank (wwPDB), accepts and processes the deposited data of experimentally determined biological macromolecular structures. In addition to archiving the PDB data in collaboration with the other wwPDB partners, PDBj also provides a wide range of original and unique services and tools, which are continuously improved and updated. Here, we report the new RDB PDBj Mine 2, the WebGL molecular viewer Molmil, the ProMode-Elastic server for normal mode analysis, a virtual reality system for the eF-site protein electrostatic molecular surfaces, the extensions of the Omokage search for molecular shape similarity, and the integration of PDBj and BMRB searches.

BACKGROUND: N-terminal acetylation is one of the most common protein modifications in eukaryotes and occurs co-translationally when the N-terminus of the nascent polypeptide is still attached to the ribosome. This modification has been shown to be involved in a wide range of biological phenomena such as protein half-life regulation, protein-protein and protein-membrane interactions, and protein subcellular localization. Thus, accurately predicting which proteins receive an acetyl group based on their protein sequence is expected to facilitate the functional study of this modification. As the occurrence of N-terminal acetylation strongly depends on the context of protein sequences, attempts to understand the sequence determinants of N-terminal acetylation were conducted initially by simply examining the N-terminal sequences of many acetylated and unacetylated proteins and more recently by machine learning approaches. However, a complete understanding of the sequence determinants of this modification remains to be elucidated. RESULTS: We obtained curated N-terminally acetylated and unacetylated sequences from the UniProt database and employed a decision tree algorithm to identify the sequence determinants of N-terminal acetylation for proteins whose initiator methionine (iMet) residues have been removed. The results suggested that the main determinants of N-terminal acetylation are contained within the first five residues following iMet and that the first and second positions are the most important discriminator for the occurrence of this phenomenon. The results also indicated the existence of position-specific preferred and inhibitory residues that determine the occurrence of N-terminal acetylation. The developed predictor software, termed NT-AcPredictor, accurately predicted the N-terminal acetylation, with an overall performance comparable or superior to those of preceding predictors incorporating machine learning algorithms. CONCLUSION: Our machine learning approach based on a decision tree algorithm successfully provided several sequence determinants of N-terminal acetylation for proteins lacking iMet, some of which have not previously been described. Although these sequence determinants remain insufficient to comprehensively predict the occurrence of this modification, indicating that further work on this topic is still required, the developed predictor, NT-AcPredictor, can be used to predict N-terminal acetylation with an accuracy of more than 80%.

Germline H255Y and K508R missense mutations in the folliculin (FLCN) gene have been identified in patients with bilateral multifocal (BMF) kidney tumours and clinical manifestations of Birt-Hogg-Dubé (BHD) syndrome, or with BMF kidney tumours as the only manifestation; however, their impact on FLCN function remains to be determined. In order to determine if FLCN H255Y and K508R missense mutations promote aberrant kidney cell proliferation leading to pathogenicity, we generated mouse models expressing these mutants using BAC recombineering technology and investigated their ability to rescue the multi-cystic phenotype of Flcn-deficient mouse kidneys. Flcn H255Y mutant transgene expression in kidney-targeted Flcn knockout mice did not rescue the multi-cystic kidney phenotype. However, expression of the Flcn K508R mutant transgene partially, but not completely, abrogated the phenotype. Notably, expression of the Flcn K508R mutant transgene in heterozygous Flcn knockout mice resulted in development of multi-cystic kidneys and cardiac hypertrophy in some mice. These results demonstrate that both FLCN H255Y and K508R missense mutations promote aberrant kidney cell proliferation, but to different degrees. Based on the phenotypes of our preclinical models, the FLCN H255Y mutant protein has lost it tumour suppressive function leading to the clinical manifestations of BHD, whereas the FLCN K508R mutant protein may have a dominant negative effect on the function of wild-type FLCN in regulating kidney cell proliferation and, therefore, act as an oncoprotein. These findings may provide mechanistic insight into the role of FLCN in regulating kidney cell proliferation and facilitate the development of novel therapeutics for FLCN-deficient kidney cancer.

Recent advances in DNA sequencing techniques have identified rare single-nucleotide variants with less than 1% minor allele frequency. Despite the growing interest and physiological importance of rare variants in genome sciences, less attention has been paid to the allele frequency of variants in protein sciences. To elucidate the characteristics of genetic variants on protein interaction sites, from the viewpoints of the allele frequency and the structural position of variants, we mapped about 20,000 human SNVs onto protein complexes. We found that variants are less abundant in protein interfaces, and specifically the core regions of interfaces. The tendency to "avoid" the interfacial core is stronger among common variants than rare variants. As amino acid substitutions, the trend of mutating amino acids among rare variants is consistent in different interfacial regions, reflecting the fact that rare variants result from random mutations in DNA sequences, whereas amino acid changes of common variants vary between the interfacial core and rim regions, possibly due to functional constraints on proteins. This study illustrated how the allele frequency of variants relates to the protein structural regions and the functional sites in general and will lead to deeper understanding of the potential deleteriousness of rare variants at the structural level. Exceptional cases of the observed trends will shed light on the limitations of structural approaches to evaluate the functional impacts of variants.

Functional sites on proteins play an important role in various molecular interactions and reactions between proteins and other molecules. Thus, mutations in functional sites can severely affect the overall phenotype. Progress of genome sequencing projects has yielded a wealth of information on single nucleotide variants (SNVs), especially those with less than 1% minor allele frequency (rare variants). To understand the functional influence of genetic variants at a protein level, we investigated the relationship between SNVs and protein functional sites in terms of minor allele frequency and the structural position of variants. As a result, we observed that SNVs were less abundant at ligand binding sites, which is consistent with a previous study on SNVs and protein interaction sites. Additionally, we found that non-rare variants tended to be located slightly apart from enzyme active sites. Examination of non-rare variants revealed that most of the mutations resulted in moderate changes of the physico-chemical properties of amino acids, suggesting the existence of functional constraints. In conclusion, this study shows that the mapping of genetic variants on protein structures could be a powerful approach to evaluate the functional impact of rare genetic variations.

Cellular fate depends on the spatiotemporal separation and integration of signaling processes that can be provided by phosphorylation events. In this study, we identify the crucial points in signaling crosstalk that can be triggered by discrete phosphorylation events on a single target protein. We integrated the data on individual human phosphosites with the evidence on their corresponding kinases, the functional consequences of phosphorylation on activity of the target protein and corresponding pathways. Our results show that there is a substantial fraction of phosphosites that can play critical roles in crosstalk between alternative and redundant pathways and regulatory outcome of phosphorylation can be linked to a type of phosphorylated residue. These regulatory phosphosites can serve as hubs in the signal flow and their functional roles are directly connected to their specific properties. Namely, phosphosites with similar regulatory functions are phosphorylated by the same kinases and participate in regulation of similar biochemical pathways. Such sites are more likely to cluster in sequence and space unlike sites with antagonistic outcomes of their phosphorylation on a target protein. In addition, we found that in silico phosphorylation of sites with similar functional consequences has comparable outcomes on a target protein stability. An important role of phosphorylation sites in biological crosstalk is evident from the analysis of their evolutionary conservation.

Phosphorylation offers a dynamic way to regulate protein activity and subcellular localization, which is achieved through its reversibility and fast kinetics. Adding or removing a dianionic phosphate group somewhere on a protein often changes the protein's structural properties, its stability and dynamics. Moreover, the majority of signaling pathways involve an extensive set of protein-protein interactions, and phosphorylation can be used to regulate and modulate protein-protein binding. Losses of phosphorylation sites, as a result of disease mutations, might disrupt protein binding and deregulate signal transduction. In this paper we focus on the effects of phosphorylation on protein stability, dynamics, and binding. We describe several physico-chemical mechanisms of protein regulation through phosphorylation and pay particular attention to phosphorylation in protein complexes and phosphorylation in the context of disorder-order and order-disorder transitions. Finally we assess the role of multiple phosphorylation sites in a protein molecule, their possible cooperativity and function.

Genetic variations resulting in a change of amino acid sequence can have a dramatic effect on stability, hydrogen bond network, conformational dynamics, activity and many other physiologically important properties of proteins. The substitutions of only one residue in a protein sequence, so-called missense mutations, can be related to many pathological conditions and may influence susceptibility to disease and drug treatment. The plausible effects of missense mutations range from affecting the macromolecular stability to perturbing macromolecular interactions and cellular localization. Here we review the individual cases and genome-wide studies that illustrate the association between missense mutations and diseases. In addition, we emphasize that the molecular mechanisms of effects of mutations should be revealed in order to understand the disease origin. Finally, we report the current state-of-the-art methodologies that predict the effects of mutations on protein stability, the hydrogen bond network, pH dependence, conformational dynamics and protein function.

Phosphorylation offers a dynamic way to regulate protein activity, subcellular localization, and stability. The majority of signaling pathways involve an extensive set of protein-protein interactions, and phosphorylation is widely used to regulate protein-protein binding by affecting the stability, kinetics and specificity of interactions. Previously it was found that phosphorylation sites tend to be located on protein-protein binding interfaces and may orthosterically modulate the strength of interactions. Here we studied the effect of phosphorylation on protein binding in relation to intrinsic disorder for different types of human protein complexes with known structure of the binding interface. Our results suggest that the processes of phosphorylation, binding and disorder-order transitions are coupled to each other, with about one quarter of all disordered interface Ser/Thr/Tyr sites being phosphorylated. Namely, residue site disorder and interfacial states significantly affect the phosphorylation of serine and to a lesser extent of threonine. Tyrosine phosphorylation might not be directly associated with binding through disorder, and is often observed in ordered interface regions which are not predicted to be disordered in the unbound state. We analyze possible mechanisms of how phosphorylation might regulate protein-protein binding via intrinsic disorder, and specifically focus on how phosphorylation could prevent disorder-order transitions upon binding.

Many studies have shown that missense mutations might play an important role in carcinogenesis. However, the extent to which cancer mutations might affect biomolecular interactions remains unclear. Here, we map glioblastoma missense mutations on the human protein interactome, model the structures of affected protein complexes and decipher the effect of mutations on protein-protein, protein-nucleic acid and protein-ion binding interfaces. Although some missense mutations over-stabilize protein complexes, we found that the overall effect of mutations is destabilizing, mostly affecting the electrostatic component of binding energy. We also showed that mutations on interfaces resulted in more drastic changes of amino acid physico-chemical properties than mutations occurring outside the interfaces. Analysis of glioblastoma mutations on interfaces allowed us to stratify cancer-related interactions, identify potential driver genes, and propose two dozen additional cancer biomarkers, including those specific to functions of the nervous system. Such an analysis also offered insight into the molecular mechanism of the phenotypic outcomes of mutations, including effects on complex stability, activity, binding and turnover rate. As a result of mutated protein and gene network analysis, we observed that interactions of proteins with mutations mapped on interfaces had higher bottleneck properties compared to interactions with mutations elsewhere on the protein or unaffected interactions. Such observations suggest that genes with mutations directly affecting protein binding properties are preferably located in central network positions and may influence critical nodes and edges in signal transduction networks.

Posttranslational modifications offer a dynamic way to regulate protein activity, subcellular localization, and stability. Here we estimate the effect of phosphorylation on protein binding and function for different types of complexes from human proteome. We find that phosphorylation sites tend to be located on binding interfaces in heterooligomeric and weak transient homooligomeric complexes. Analysis of molecular mechanisms of phosphorylation shows that phosphorylation may modulate the strength of interactions directly on interfaces and that binding hotspots tend to be phosphorylated in heterooligomers. Although the majority of complexes do not show significant estimated stability differences upon phosphorylation or dephosphorylation, for about one-third of all complexes it causes relatively large changes in binding energy. We discuss the cases where phosphorylation mediates the complex formation and regulates the function. We show that phosphorylation sites are more likely to be evolutionary conserved than other interfacial residues.

We investigated fragmental sequences that were inserted into proteins during long molecular evolution and relevant to the association of homo-oligomers. Seventeen insertions in 12 SCOP (structure classification of proteins) families were examined and were classified into large and small insertions. The large insertions are composed of interface-like residues and effectively increase the interface area. In contrast, small insertions are composed of the residues that are not commonly found at the interfaces and have a small interface area: their roles in the oligomerization process are unclear. We found that the small insertions were located in the middle of protein sequences and therefore must involve residues with strong turn and less interface-like propensities. From a structural viewpoint, small insertions were found to mask hydrophobic patches or act as spacers to fill cavities present at interfaces. The presence or absence of small insertions coincides with the annotated oligomeric states for homologs in the SwissProt database, and the calculation of the association scores predicts that small insertions contribute to the stability of oligomers. These results support the significant role of small, nonhydrophobic insertions in protein oligomerization.

Many soluble and membrane proteins form homooligomeric complexes in a cell which are responsible for the diversity and specificity of many pathways, may mediate and regulate gene expression, activity of enzymes, ion channels, receptors, and cell adhesion processes. The evolutionary and physical mechanisms of oligomerization are very diverse and its general principles have not yet been formulated. Homooligomeric states may be conserved within certain protein subfamilies and might be important in providing specificity to certain substrates while minimizing interactions with other unwanted partners. Moreover, recent studies have led to a greater awareness that transitions between different oligomeric states may regulate protein activity and provide the switch between different pathways. In this paper we summarize the biological importance of homooligomeric assemblies, physico-chemical properties of their interfaces, experimental and computational methods for their identification and prediction. We particularly focus on homooligomer evolution and describe the mechanisms to develop new specificities through the formation of different homooligomeric complexes. Finally, we discuss the possible role of oligomeric transitions in the regulation of protein activity and compile a set of experimental examples with such regulatory mechanisms.

Despite similarities in their sequence and structure, there are a number of homologous proteins that adopt various oligomeric states. Comparisons of these homologous protein pairs, in terms of residue substitutions at the protein-protein interfaces, have provided fundamental characteristics that describe how proteins interact with each other. We have prepared a dataset composed of pairs of related proteins with different homo-oligomeric states. Using the protein complexes, the interface residues were identified, and using structural alignments, the shadow-interface residues have been defined as the surface residues that align with the interface residues. Subsequently, we investigated residue substitutions between the interfaces and the shadow interfaces. Based on the degree of the contributions to the interactions, the aligned sites of the interfaces and shadow interfaces were divided into primary and secondary sites; the primary sites are the focus of this work. The primary sites were further classified into two groups (i.e. exposed and buried) based on the degree to which the residue is buried within the shadow interfaces. Using these classifications, two simple mechanisms that mediate the oligomeric states were identified. In the primary-exposed sites, the residues on the shadow interfaces are replaced by more hydrophobic or aromatic residues, which are physicochemically favored at protein-protein interfaces. In the primary-buried sites, the residues on the shadow interfaces are replaced by larger residues that protrude into other proteins. These simple rules are satisfied in 23 out of 25 Structural Classification of Proteins (SCOP) families with a different-oligomeric-state pair, and thus represent a basic strategy for modulating protein associations and dissociations.