Comprehensive in silico analysis of prolactin receptor (PRLR) gene nonsynonymous single nucleotide polymorphisms (nsSNPs) reveals multifaceted impact on protein structure, function, and interactions

This study delves into the functional and structural implications of non-synonymous single nucleotide polymorphisms (nsSNPs) within the Prolactin Receptor (PRLR) gene. Thirteen deleterious nsSNPs were identified through bioinformatics tools, with SIFT predicting 168 out of 395 nsSNPs as detrimental, exhibiting tolerance index (TI) scores ranging from 0 to 0.05. Polyphen2 assigned likelihood scores >0.99 to all 13 nsSNPs, indicating high probability of harm, while Panther scores classified most nsSNPs as 'probably damaging', with specific mutations like W218R scoring 0.74, suggesting a higher impact. Stability analysis using DDG I-Mutant and DDG Mupro consistently predicted decreased stability for all mutations, with CUPSAT indicating mutations like V125G and W218R significantly decreasing stability. Structural analysis through DynaMut predicted destabilization for all mutations except L196I and L292H. MutPred2 highlighted structural alterations for all nsSNPs except L196I, L293V, R315W, and S353N. Domain analysis revealed key mutations within essential functional domains, with five nsSNPs located within Fibronectin type-III domains. Bayesian analysis through ConSurf identified 9 critical residues, with 11 nsSNPs exhibiting notably high conservation. STRING analysis unveiled a complex interaction network, indicating involvement in vital biological processes like lactation. Molecular dynamics (MD) simulations, spanning 100 nanoseconds, elucidated structural dynamics induced by detrimental missense SNPs. Post-translational modification (PTM) analysis identified specific mutations, such as R351, involved in methylation, while S353 was implicated in phosphorylation and glycosylation. These findings offer comprehensive insights into the molecular and phenotypic effects of deleterious nsSNPs in the PRLR gene, crucial for selective breeding.Communicated by Ramaswamy H. Sarma.

14-3-3τ as a Modulator of Early α-Synuclein Multimerization and Amyloid Formation

The aggregation of α-synuclein (αS) plays a key role in Parkinson's disease (PD) etiology. While the onset of PD is age-related, the cellular quality control system appears to regulate αS aggregation throughout most human life. Intriguingly, the protein 14-3-3τ has been demonstrated to delay αS aggregation and the onset of PD in various models. However, the molecular mechanisms behind this delay remain elusive. Our study confirms the delay in αS aggregation by 14-3-3τ, unveiling a concentration-dependent relation. Utilizing microscale thermophoresis (MST) and single-molecule burst analysis, we quantified the early αS multimers and concluded that these multimers exhibit properties that classify them as nanoscale condensates that form in a cooperative process, preceding the critical nucleus for fibril formation. Significantly, the αS multimer formation mechanism changes dramatically in the presence of scaffold protein 14-3-3τ. Our data modeling suggests that 14-3-3τ modulates the multimerization process, leading to the creation of mixed multimers or co-condensates, comprising both αS and 14-3-3τ. These mixed multimers form in a noncooperative process. They are smaller, more numerous, and distinctively not on the pathway to amyloid formation. Importantly, 14-3-3τ thus acts in the very early stage of αS multimerization, ensuring that αS does not aggregate but remains soluble and functional. This offers long-sought novel entries for the pharmacological modulation of PD.

Drugs Form Ternary Complexes with Human Liver Fatty Acid Binding Protein (FABP1) and FABP1 Binding Alters Drug Metabolism

Liver fatty acid binding protein (FABP1) binds diverse endogenous lipids and is highly expressed in the human liver. Binding to FABP1 alters the metabolism and homeostasis of endogenous lipids in the liver. Drugs have also been shown to bind to rat FABP1, but limited data is available for human FABP1 (hFABP1). FABP1 has a large binding pocket and up to two fatty acids can bind to FABP1 simultaneously. We hypothesized that drug binding to hFABP1 results in formation of ternary complexes and that FABP1 binding alters drug metabolism. To test these hypotheses, native protein mass spectrometry (MS) and fluorescent 11-(dansylamino)undecanoic acid (DAUDA) displacement assays were used to characterize drug binding to hFABP1, and diclofenac oxidation by cytochrome P450 2C9 (CYP2C9) was studied in the presence and absence of hFABP1. DAUDA binding to hFABP1 involved high (Kd,1=0.2 µM) and low affinity (Kd,2 >10 µM) binding sites. Nine drugs bound to hFABP1 with Kd values ranging from 1 to 20 µM. None of the tested drugs completely displaced DAUDA from hFABP1 and fluorescence spectra showed evidence of ternary complex formation. Formation of DAUDA-hFABP1-diclofenac ternary complex was verified with native MS. Docking predicted diclofenac binding in the portal region of FABP1 with DAUDA in the binding cavity. The kcat of diclofenac hydroxylation by CYP2C9 was decreased by ~50% (p<0.01) in the presence of FABP1. Together, these results suggest that drugs form ternary complexes with hFABP1 and that hFABP1 binding in the liver will alter drug metabolism and clearance. Significance Statement Many commonly prescribed drugs bind FABP1 forming ternary complexes with FABP1 and the fluorescent fatty acid DAUDA. These findings suggests that drugs will bind to apo-FABP1 and fatty acid bound FABP1 in the human liver. The high expression of FABP1 in the liver, together with drug binding to FABP1 may alter drug disposition processes in vivo.

Comprehensive Characterization of fucAO Operon Activation in Escherichia coli

Wildtype Escherichia coli cells cannot grow on L-1,2-propanediol, as the fucAO operon within the fucose (fuc) regulon is thought to be silent in the absence of L-fucose. Little information is available concerning the transcriptional regulation of this operon. Here, we first confirm that fucAO operon expression is highly inducible by fucose and is primarily attributable to the upstream operon promoter, while the fucO promoter within the 3'-end of fucA is weak and uninducible. Using 5'RACE, we identify the actual transcriptional start site (TSS) of the main fucAO operon promoter, refuting the originally proposed TSS. Several lines of evidence are provided showing that the fucAO locus is within a transcriptionally repressed region on the chromosome. Operon activation is dependent on FucR and Crp but not SrsR. Two Crp-cAMP binding sites previously found in the regulatory region are validated, where the upstream site plays a more critical role than the downstream site in operon activation. Furthermore, two FucR binding sites are identified, where the downstream site near the first Crp site is more important than the upstream site. Operon transcription relies on Crp-cAMP to a greater degree than on FucR. Our data strongly suggest that FucR mainly functions to facilitate the binding of Crp to its upstream site, which in turn activates the fucAO promoter by efficiently recruiting RNA polymerase.

Prediction of interactions between cell surface proteins by machine learning

Cells detect changes in their external environments or communicate with each other through proteins on their surfaces. These cell surface proteins form a complicated network of interactions in order to fulfill their functions. The interactions between cell surface proteins are highly dynamic and, thus, challenging to detect using traditional experimental techniques. Here, we tackle this challenge using a computational framework. The primary focus of the framework is to develop new tools to identify interactions between domains in the immunoglobulin (Ig) fold, which is the most abundant domain family in cell surface proteins. These interactions could be formed between ligands and receptors from different cells or between proteins on the same cell surface. In practice, we collected all structural data on Ig domain interactions and transformed them into an interface fragment pair library. A high-dimensional profile can then be constructed from the library for a given pair of query protein sequences. Multiple machine learning models were used to read this profile so that the probability of interaction between the query proteins could be predicted. We tested our models on an experimentally derived dataset that contains 564 cell surface proteins in humans. The cross-validation results show that we can achieve higher than 70% accuracy in identifying the PPIs within this dataset. We then applied this method to a group of 46 cell surface proteins in Caenorhabditis elegans. We screened every possible interaction between these proteins. Many interactions recognized by our machine learning classifiers have been experimentally confirmed in the literature. In conclusion, our computational platform serves as a useful tool to help identify potential new interactions between cell surface proteins in addition to current state-of-the-art experimental techniques. The tool is freely accessible for use by the scientific community. Moreover, the general framework of the machine learning classification can also be extended to study the interactions of proteins in other domain superfamilies.

Interfacial residues in protein-protein complexes are in the eyes of the beholder

Interactions between proteins are vital in almost all biological processes. The characterization of protein-protein interactions helps us understand the mechanistic basis of biological processes, thereby enabling the manipulation of proteins for biotechnological and clinical purposes. The interface residues of a protein-protein complex are assumed to have the following two properties: (a) they always interact with a residue of a partner protein, which forms the basis for distance-based interface residue identification methods, and (b) they are solvent-exposed in the isolated form of the protein and become buried in the complex form, which forms the basis for Accessible Surface Area (ASA)-based methods. The study interrogates this popular assumption by recognizing interface residues in protein-protein complexes through these two methods. The results show that a few residues are identified uniquely by each method, and the extent of conservation, propensities, and their contribution to the stability of protein-protein interaction varies substantially between these residues. The case study analyses showed that interface residues, unique to distance, participate in crucial interactions that hold the proteins together, whereas the interface residues unique to the ASA method have a potential role in the recognition, dynamics, and specificity of the complex and can also be a hotspot. Overall, the study recommends applying both distance and ASA methods so that some interface residues missed by either method but crucial to the stability, recognition, dynamics, and function of protein-protein complexes are identified in a complementary manner.

Bordetella filamentous hemagglutinin and adenylate cyclase toxin interactions on the bacterial surface are consistent with FhaB-mediated delivery of ACT to phagocytic cells

Bordetella species that cause respiratory infections in mammals include B. pertussis, which causes human whooping cough, and B. bronchiseptica, which infects nearly all mammals. Both bacterial species produce filamentous hemagglutinin (FhaB) and adenylate cyclase toxin (ACT), prominent surface-associated and secreted virulence factors that contribute to persistence in the lower respiratory tract by inhibiting clearance by phagocytic cells. FhaB and ACT proteins interact with themselves, each other, and host cells. Using immunoblot analyses, we showed that ACT binds to FhaB on the bacterial surface before it can be detected in culture supernatants. We determined that SphB1, a surface protease identified based on its requirement for FhaB cleavage, is also required for ACT cleavage, and we determined that the presence of ACT blocks SphB1-dependent and -independent cleavage of FhaB, but the presence of FhaB does not affect SphB1-dependent cleavage of ACT. The primary SphB1-dependent cleavage site on ACT is proximal to ACT's active site, in a region that is critical for ACT activity. We also determined that FhaB-bound ACT on the bacterial surface can intoxicate host cells producing CR3, the receptor for ACT. In addition to increasing our understanding of FhaB, ACT, and FhaB-ACT interactions on the Bordetella surface, our data are consistent with a model in which FhaB functions as a novel toxin delivery system by binding to ACT and allowing its release upon binding of ACT to its receptor, CR3, on phagocytic cells.IMPORTANCEBacteria need to control the variety, abundance, and conformation of proteins on their surface to survive. Members of the Gram-negative bacterial genus Bordetella include B. pertussis, which causes whooping cough in humans, and B. bronchiseptica, which causes respiratory infections in a broad range of mammals. These species produce two prominent virulence factors, the two-partner secretion (TPS) effector FhaB and adenylate cyclase toxin (ACT), that interact with themselves, each other, and host cells. Here, we determined that ACT binds FhaB on the bacterial surface before being detected in culture supernatants and that ACT bound to FhaB can be delivered to eukaryotic cells. Our data are consistent with a model in which FhaB delivers ACT specifically to phagocytic cells. This is the first report of a TPS system facilitating the delivery of a separate polypeptide toxin to target cells and expands our understanding of how TPS systems contribute to bacterial pathogenesis.

A λ-dynamics investigation of insulin Wakayama and other A3 variant binding affinities to the insulin receptor

Insulin Wakayama is a clinical insulin variant where a conserved valine at the third residue on insulin's A chain (ValA3) is replaced with a leucine (LeuA3), impairing insulin receptor (IR) binding by 140-500 fold. This severe impact on binding from such a subtle modification has posed an intriguing problem for decades. Although experimental investigations of natural and unnatural A3 mutations have highlighted the sensitivity of insulin-IR binding to minor changes at this site, an atomistic explanation of these binding trends has remained elusive. We investigate this problem computationally using λ-dynamics free energy calculations to model structural changes in response to perturbations of the ValA3 side chain and to calculate associated relative changes in binding free energy (ΔΔGbind). The Wakayama LeuA3 mutation and seven other A3 substitutions were studied in this work. The calculated ΔΔGbind results showed high agreement compared to experimental binding potencies with a Pearson correlation of 0.88 and a mean unsigned error of 0.68 kcal/mol. Extensive structural analyses of λ-dynamics trajectories revealed that critical interactions were disrupted between insulin and the insulin receptor as a result of the A3 mutations. This investigation also quantifies the effect that adding an A3 Cδ atom or losing an A3 Cγ atom has on insulin's binding affinity to the IR. Thus, λ-dynamics was able to successfully model the effects of subtle modifications to insulin's A3 side chain on its protein-protein interactions with the IR and shed new light on a decades-old mystery: the exquisite sensitivity of hormone-receptor binding to a subtle modification of an invariant insulin residue.

Modulators targeting protein-protein interactions in Mycobacterium tuberculosis

Tuberculosis (TB) is a chronic infectious disease caused by Mycobacterium tuberculosis (M. tuberculosis), mainly transmitted through droplets to infect the lungs, and seriously affecting patients' health and quality of life. Clinically, anti-TB drugs often entail side effects and lack efficacy against resistant strains. Thus, the exploration and development of novel targeted anti-TB medications are imperative. Currently, protein-protein interactions (PPIs) offer novel avenues for anti-TB drug development, and the study of targeted modulators of PPIs in M. tuberculosis has become a prominent research focus. Furthermore, a comprehensive PPI network has been constructed using computational methods and bioinformatics tools. This network allows for a more in-depth analysis of the structural biology of PPIs and furnishes essential insights for the development of targeted small-molecule modulators. Furthermore, this article provides a detailed overview of the research progress and regulatory mechanisms of PPI modulators in M. tuberculosis, the causative agent of TB. Additionally, it summarizes potential targets for anti-TB drugs and discusses the prospects of existing PPI modulators.

Hepatitis B virus evades the immune system by suppressing the NF-κB signaling pathway with DENND2A

Overcoming hepatitis B virus (HBV) is a challenging problem because HBV deceives the host immune system. We have found that DENN domain-containing 2A (DENND2A) was essential for HBV maintenance, although its role remains unclear. In this study, we elucidate its function by screening a novel DENND2A-binding peptide, DENP4-3S. DENP4-3S exhibits homology to SAM and SH3 domain-containing protein 1 (SASH1), a scaffold protein involved in Toll-like receptor signaling that promotes proinflammatory cytokine production. We confirmed that DENND2A interacts with SASH1 specifically. Overexpression and knockdown experiments showed that overexpression of DENND2A suppressed the transcriptional activity of NF-κB, and the knockdown of DENND2A promoted it and the production of cytokines and interferons. Here, we constructed a fusion protein (10M-DEN3SN) consisting of an anti-asialoglycoprotein receptor antibody and DENP4-3S to deliver the peptide to hepatocytes specifically. 10M-DEN3SN inhibited the interaction between DENND2A and SASH1, and rescued SASH1 trapped by DENND2A, leading to the upregulation of NF-κB and its downstream signaling. In addition, 10M-DEN3SN suppressed HBV proliferation in PXB chimeric mice. These results with the DENND2A-binding peptide delivered into hepatocytes suggested the involvement of DENND2A, SASH, and NF-κB signaling pathway in the HBV infection and onset of hepatitis. In conclusion, this study indicates that HBV utilizes DENND2A and SASH1 to evade the immune system.IMPORTANCEHepatitis B virus (HBV) is a serious liver infection with no established cure, causing an abnormal host immune response. Here, we identified a novel peptide that interacts with DENN domain-containing 2A (DENND2A), a host factor essential for HBV maintenance. The resulting peptide showed sequence homology, revealing an interaction between DENND2A and the immune system regulator SASH1. This study suggests that DENND2A contributes to HBV infection by suppressing the cellular immune system by inhibiting SASH1. The DENND2A-binding peptide, incorporated into our hepatocyte-specific peptide delivery system, inhibited the DENND2A-SASH1 interaction and promoted the production of cytokines and interferons in cultured hepatocytes. As a consequence, the peptide suppressed HBV proliferation in humanized mice. We report new insights into the role of DENND2A and SASH1 in HBV maintenance and highlight the importance of the immune system.

In silico mutation of aromatic with aliphatic amino acid residues in Clostridium perfringens epsilon toxin (ETX) reduces its binding efficiency to Caprine Myelin and lymphocyte (MAL) protein receptors

Enterotoxaemia (ET) is a severe disease that affects domestic ruminants, including sheep and goats, and is caused by Clostridium perfringens type B and D strains. The disease is characterized by the production of Epsilon toxin (ETX), which has a significant impact on the farming industry due to its high lethality. The binding of ETX to the host cell receptor is crucial, but still poorly understood. Therefore, the structural features of goat Myelin and lymphocytic (MAL) protein were investigated and defined in this study. We induced the mutations in aromatic amino acid residues of ETX and substituted them with aliphatic residues at domains I and II. Subsequently, protein-protein interactions (PPI) were performed between ETX (wild)-MAL and ETX (mutated)-MAL protein predicting the domain sites of ETX structure. Further, molecular dynamics (MD) simulation studies were performed for both complexes to investigate the dynamic behavior of the proteins. The binding efficiency between 'ETX (wild)-MAL protein' and 'ETX (mutated)-MAL protein complex' interactions were compared and showed that the former had stronger interactions and binding efficiency due to the higher stability of the complex. The MD analysis showed destabilization and higher fluctuations in the PPI of the mutated heterodimeric ETX-MAL complex which is otherwise essential for its functional conformation. Such kind of interactions with mutated functional domains of ligands provided much-needed clarity in understanding the pre-pore complex formation of epsilon toxin with the MAL protein receptor of goats. The findings from this study would provide an impetus for designing a novel vaccine for Enterotoxaemia in goats.Communicated by Ramaswamy H. Sarma.

Proteomics, modeling, and fluorescence assays delineate cytochrome b5 residues involved in binding and stimulation of cytochrome P450 17A1 17,20-lyase

Cytochrome b5 (b5) is known to stimulate some catalytic activities of cytochrome P450 (P450, CYP) enzymes, although mechanisms still need to be defined. The reactions most strongly enhanced by b5 are the 17,20-lyase reactions of P450 17A1 involved in steroid biosynthesis. We had previously used a fluorescently labeled human b5 variant (Alexa 488-T70C-b5) to characterize human P450 17A1-b5 interactions, but subsequent proteomic analyses indicated that lysines in b5 were also modified with Alexa 488 maleimide in addition to Cys-70, due to disulfide dimerization of the T70C mutant. A series of b5 variants were constructed with Cys replacements for the identified lysine residues and labeled with the dye. Fluorescence attenuation and the function of b5 in the steroid lyase reaction depended on the modified position. Apo-b5 (devoid of heme group) studies revealed the lack of involvement of the b5 heme in the fluorescence attenuation. A structural model of b5 with P450 17A1 was predicted using AlphaFold-Multimer algorithms/Rosetta docking, based upon the individual structures, which predicted several new contacts not previously reported, that is, interactions of b5 Glu-48:17A1 Arg-347, b5 Glu-49:17A1 Arg-449, b5 Asp-65:17A1 Arg-126, b5 Asp-65:17A1 Arg-125, and b5 Glu-61:17A1 Lys-91. Fluorescence polarization assays with two modified b5 variants yielded Kd values (for b5-P450 17A1) of 120 to 380 nM, the best estimate of binding affinity. We conclude that both monomeric and dimeric b5 can bind to P450 17A1 and stimulate activity. Results with the mutants indicate that several Lys residues in b5 are sensitive to the interaction with P450 17A1, including Lys-88 and Lys-91.

In silico models of the macromolecular NaV1.5-KIR2.1 complex

In cardiac cells, the expression of the cardiac voltage-gated Na+ channel (NaV1.5) is reciprocally regulated with the inward rectifying K+ channel (KIR2.1). These channels can form macromolecular complexes that pre-assemble early during forward trafficking (transport to the cell membrane). In this study, we present in silico 3D models of NaV1.5-KIR2.1, generated by rigid-body protein-protein docking programs and deep learning-based AlphaFold-Multimer software. Modeling revealed that the two channels could physically interact with each other along the entire transmembrane region. Structural mapping of disease-associated mutations revealed a hotspot at this interface with several trafficking-deficient variants in close proximity. Thus, examining the role of disease-causing variants is important not only in isolated channels but also in the context of macromolecular complexes. These findings may contribute to a better understanding of the life-threatening cardiovascular diseases underlying KIR2.1 and NaV1.5 malfunctions.

A journey into the regulatory secrets of the de novo purine nucleotide biosynthesis

De novo purine nucleotide biosynthesis (DNPNB) consists of sequential reactions that are majorly conserved in living organisms. Several regulation events take place to maintain physiological concentrations of adenylate and guanylate nucleotides in cells and to fine-tune the production of purine nucleotides in response to changing cellular demands. Recent years have seen a renewed interest in the DNPNB enzymes, with some being highlighted as promising targets for therapeutic molecules. Herein, a review of two newly revealed modes of regulation of the DNPNB pathway has been carried out: i) the unprecedent allosteric regulation of one of the limiting enzymes of the pathway named inosine 5'-monophosphate dehydrogenase (IMPDH), and ii) the supramolecular assembly of DNPNB enzymes. Moreover, recent advances that revealed the therapeutic potential of DNPNB enzymes in bacteria could open the road for the pharmacological development of novel antibiotics.

Network pharmacology, molecular simulation, and binding free energy calculation-based investigation of Neosetophomone B revealed key targets for the treatment of cancer

In the current study, Neosetophomone B (NSP-B) was investigated for its anti-cancerous potential using network pharmacology, quantum polarized ligand docking, molecular simulation, and binding free energy calculation. Using SwissTarget prediction, and Superpred, the molecular targets for NSP-B were predicted while cancer-associated genes were obtained from DisGeNet. Among the total predicted proteins, only 25 were reported to overlap with the disease-associated genes. A protein-protein interaction network was constructed by using Cytoscape and STRING databases. MCODE was used to detect the densely connected subnetworks which revealed three sub-clusters. Cytohubba predicted four targets, i.e., fibroblast growth factor , FGF20, FGF22, and FGF23 as hub genes. Molecular docking of NSP-B based on a quantum-polarized docking approach with FGF6, FGF20, FGF22, and FGF23 revealed stronger interactions with the key hotspot residues. Moreover, molecular simulation revealed a stable dynamic behavior, good structural packing, and residues' flexibility of each complex. Hydrogen bonding in each complex was also observed to be above the minimum. In addition, the binding free energy was calculated using the MM/GBSA (Molecular Mechanics/Generalized Born Surface Area) and MM/PBSA (Molecular Mechanics/Poisson-Boltzmann Surface Area) approaches. The total binding free energy calculated using the MM/GBSA approach revealed values of -36.85 kcal/mol for the FGF6-NSP-B complex, -43.87 kcal/mol for the FGF20-NSP-B complex, and -37.42 kcal/mol for the FGF22-NSP-B complex, and -41.91 kcal/mol for the FGF23-NSP-B complex. The total binding free energy calculated using the MM/PBSA approach showed values of -30.05 kcal/mol for the FGF6-NSP-B complex, -39.62 kcal/mol for the FGF20-NSP-B complex, -34.89 kcal/mol for the FGF22-NSP-B complex, and -37.18 kcal/mol for the FGF23-NSP-B complex. These findings underscore the promising potential of NSP-B against FGF6, FGF20, FGF22, and FGF23, which are reported to be essential for cancer signaling. These results significantly bolster the potential of NSP-B as a promising candidate for cancer therapy.

Proteomic analysis of meropenem-induced outer membrane vesicles released by carbapenem-resistant Klebsiella pneumoniae

Carbapenem-resistant Klebsiella pneumoniae (CRKP) is an important multidrug resistance (MDR) pathogen that threatens human health and is the main source of hospital-acquired infection. Outer membrane vesicles (OMVs) are extracellular vesicles derived from Gram-negative bacteria and contain materials involved in bacterial survival and pathogenesis. They also contribute to cellular communication to nearby or distant recipient cells and influence their functions and phenotypes. In this study, we sought to understand the mechanism of bacterial response to meropenem pressure and explore the relationship between pathogenic proteins and the high pathogenicity of bacteria. We performed whole-genome PacBio sequencing on a clinical CRKP strain, and its OMVs were characterized using nanoparticle tracking analysis, transmission electron microscopy, and proteomic analysis. Thousands of vesicle proteins have been identified in mass spectrometry-based high-throughput proteomics analyses of K. pneumoniae OMVs. Protein functionality analysis showed that the OMVs were predominantly involved in metabolic, intracellular compartments, nucleic acid binding, survival, defense, and antibiotic resistance, such as Chromosome partition protein MukB, 3-methyl-2-oxobutanoate hydroxymethyltransferase, methionine-tRNA ligase, Heat shock protein 60 family chaperone GroEL, and Gamma-glutamyl phosphate reductase. Additionally, a protein-protein interaction network demonstrated that OMVs from meropenem-treated K. pneumoniae showed the highest connectivity in DNA polymerase I, phenylalanine-tRNA ligase beta subunit, DNA-directed RNA polymerase subunit beta, methionine-tRNA ligase, DNA-directed RNA polymerase subunit beta, and DNA-directed RNA polymerase subunit alpha. The OMVs proteome expression profile indicates increased secretion of stress proteins released from meropenem-treated K. pneumoniae, which provides clues for revealing the biogenesis and pathophysiological functions of Gram-negative bacteria OMVs. The significant differentially expressed proteins identified in this study are of great significance for exploring effective control strategies for CRKP infection.IMPORTANCEMeropenem is one of the main antibiotics used in the clinical treatment of carbapenem-resistant Klebsiella pneumoniae (CRKP). This study demonstrated that some important metabolic changes occurred in meropenem-induced CRKP-outer membrane vesicles (OMVs), The OMVs proteome expression profile indicates increased secretion of stress proteins released from meropenem-induced Klebsiella pneumoniae. Furthermore, this is the first study to discuss the protein-protein interaction network of the OMVs released by CRKP, especially under antibiotic stress.

Interactions of drosophila cryptochrome

In this study, we investigate the intricate regulatory mechanisms underlying the circadian clock in Drosophila, focusing on the light-induced conformational changes in the cryptochrome (DmCry). Upon light exposure, DmCry undergoes conformational changes that prompt its binding to Timeless and Jetlag proteins, initiating a cascade crucial for the starting of a new circadian cycle. DmCry is subsequently degraded, contributing to the desensitization of the resetting mechanism. The transient and short-lived nature of DmCry protein-protein interactions (PPIs), leading to DmCry degradation within an hour of light exposure, presents a challenge for comprehensive exploration. To address this, we employed proximity-dependent biotinylation techniques, combining engineered BioID (TurboID) and APEX (APEX2) enzymes with mass spectrometry. This approach enabled the identification of the in vitro DmCry interactome in Drosophila S2 cells, uncovering several novel PPIs associated with DmCry. Validation of these interactions through a novel co-immunoprecipitation technique enhances the reliability of our findings. Importantly, our study suggests the potential of this method to reveal additional circadian clock- or magnetic field-dependent PPIs involving DmCry. This exploration of the DmCry interactome not only advances our understanding of circadian clock regulation but also establishes a versatile framework for future investigations into light- and time-dependent protein interactions in Drosophila.

A significance score for protein-protein interaction models through random docking

Comparing accuracies of structural protein-protein interaction (PPI) models for different complexes on an absolute scale is a challenge, requiring normalization of scores across structures of different sizes and shapes. To help address this challenge, we have developed a statistical significance metric for docking models, called random-docking (RD) p-value. This score evaluates a PPI model based on how likely a random docking process is to produce a model of better or equal accuracy. The binding partners are randomly docked against each other a large number of times, and the probability of sampling a model of equal or greater accuracy from this reference distribution is the RD p-value. Using a subset of top predicted models from CAPRI (Critical Assessment of PRediction of Interactions) rounds over 2017-2020, we find that the ease of achieving a given root mean squared deviation or DOCKQ score varies considerably by target; achieving the same relative metric can be thousands of times easier for one complex compared to another. In contrast, RD p-values inherently normalize scores for models of different complexes, making them globally comparable. Furthermore, one can calculate RD p-values after generating a reference distribution that accounts for prior information about the interface geometry, such as residues involved in binding, by giving the random-docking process access the same information. Thus, one can decouple improvements in prediction accuracy that arise solely from basic modeling constraints from those due to the rest of the method. We provide efficient code for computing RD p-values at https://github.com/Grigoryanlab/RDP.

Sifting Through the Noise: A Computational Pipeline for Accurate Prioritization of Protein-Protein Binding Candidates in High-Throughput Protein Libraries

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High-throughput experimental approaches narrow down possible binding partners, but often include false positives. Furthermore, they provide no information about what the binding region is (e.g. the binding epitope). We introduce a novel computational pipeline based on an AlphaFold2 (AF) Competition Assay (AF-CBA) to identify proteins that bind a target of interest from a pull-down experiment, along with the binding epitope. Our focus is on proteins that bind the Extraterminal (ET) domain of Bromo and Extraterminal domain (BET) proteins, but we also introduce nine additional systems to show transferability to other peptide-protein systems. We describe a series of limitations to the methodology based on intrinsic deficiencies to AF and AF-CBA, to help users identify scenarios where the approach will be most useful. Given the speed and accuracy of the methodology, we expect it to be generally applicable to facilitate target selection for experimental verification starting from high-throughput protein libraries.

Drugs Form Ternary Complexes with Human Liver Fatty Acid Binding Protein (FABP1) and FABP1 Binding Alters Drug Metabolism

Liver fatty acid binding protein (FABP1) binds diverse endogenous lipids and is highly expressed in the human liver. Binding to FABP1 alters the metabolism and homeostasis of endogenous lipids in the liver. Drugs have also been shown to bind to rat FABP1, but limited data is available for human FABP1 (hFABP1). FABP1 has a large binding pocket and multiple fatty acids can bind to FABP1 simultaneously. We hypothesized that drug binding to hFABP1 results in formation of ternary complexes and that FABP1 binding alters drug metabolism. To test these hypotheses native protein mass spectrometry (MS) and fluorescent 11-(dansylamino)undecanoic acid (DAUDA) displacement assays were used to characterize drug binding to hFABP1 and diclofenac oxidation by cytochrome P450 2C9 (CYP2C9) was studied in the presence and absence of hFABP1. DAUDA binding to hFABP1 involved high (Kd,1=0.2 µM) and low affinity (Kd,2 >10 µM) binding sites. Nine drugs bound to hFABP1 with Kd values ranging from 1 to 20 µM. None of the tested drugs completely displaced DAUDA from hFABP1 and fluorescence spectra showed evidence of ternary complex formation. Formation of DAUDA-diclofenac-hFABP1 ternary complex was verified with native MS. Docking placed diclofenac in the portal region of FABP1 with DAUDA in the binding cavity. Presence of hFABP1 decreased the kcat and Km,u of diclofenac with CYP2C9 by ~50% suggesting that hFABP1 binding in the liver will alter drug metabolism and clearance. Together, these results suggest that drugs form ternary complexes with hFABP1 and that hFABP1 interacts with CYP2C9.

Corrigendum: Revisiting bacterial cytolethal distending toxin structure and function

[This corrects the article DOI: 10.3389/fcimb.2023.1289359.].

Inhibition of Aurora-A/N-Myc Protein-Protein Interaction Using Peptidomimetics: Understanding the Role of Peptide Cyclization

Using N-Myc61-89 as a starting template we showcase the systematic use of truncation and maleimide constraining to develop peptidomimetic inhibitors of the N-Myc/Aurora-A protein-protein interaction (PPI); a potential anticancer drug discovery target. The most promising of these - N-Myc73-94-N85C/G89C-mal - is shown to favour a more Aurora-A compliant binding ensemble in comparison to the linear wild-type sequence as observed through fluorescence anisotropy competition assays, circular dichroism (CD) and nuclear magnetic resonance (NMR) experiments. Further in silico investigation of this peptide in its Aurora-A bound state, by molecular dynamics (MD) simulations, imply (i) the bound conformation is more stable as a consequence of the constraint, which likely suppresses dissociation and (ii) the constraint may make further stabilizing interactions with the Aurora-A surface. Taken together this work unveils the first orthosteric N-Myc/Aurora-A inhibitor and provides useful insights on the biophysical properties and thus design of constrained peptides, an attractive therapeutic modality.

The effects of the chemical modification on immobilized lipase features are affected by the enzyme crowding in the support

In this article, we have analyzed the interactions between enzyme crowding on a given support and its chemical modification (ethylenediamine modification via the carbodiimide route and picryl sulfonic (TNBS) modification of the primary amino groups) on the enzyme activity and stability. Lipase from Thermomyces lanuginosus (TLL) and lipase B from Candida antarctica (CALB) were immobilized on octyl-agarose beads at two very different enzyme loadings, one of them exceeding the capacity of the support, one well under this capacity. Chemical modifications of the highly loaded and lowly loaded biocatalysts gave very different results in terms of activity and stability, which could increase or decrease enzyme activity depending on the enzyme support loading. For example, both lowly loaded biocatalysts increased their activity after modification while the effect was the opposite for the highly loaded biocatalysts. Additionally, the modification with TNBS of highly loaded CALB biocatalyst increased its stability while decrease the activity.

Human-virus protein-protein interactions maps assist in revealing the pathogenesis of viral infection

Many significant viral infections have been recorded in human history, which have caused enormous negative impacts worldwide. Human-virus protein-protein interactions (PPIs) mediate viral infection and immune processes in the host. The identification, quantification, localization, and construction of human-virus PPIs maps are critical prerequisites for understanding the biophysical basis of the viral invasion process and characterising the framework for all protein functions. With the technological revolution and the introduction of artificial intelligence, the human-virus PPIs maps have been expanded rapidly in the past decade and shed light on solving complicated biomedical problems. However, there is still a lack of prospective insight into the field. In this work, we comprehensively review and compare the effectiveness, potential, and limitations of diverse approaches for constructing large-scale PPIs maps in human-virus, including experimental methods based on biophysics and biochemistry, databases of human-virus PPIs, computational methods based on artificial intelligence, and tools for visualising PPIs maps. The work aims to provide a toolbox for researchers, hoping to better assist in deciphering the relationship between humans and viruses.

A naturally occurring G11S mutation in the 3C-like protease from the SARS-CoV-2 virus dramatically weakens the dimer interface

The 3C-like protease (3CLpro ) is crucial to the replication of SARS-CoV-2, the causative agent of COVID-19, and is the target of several successful drugs including Paxlovid and Xocova. Nevertheless, the emergence of viral resistance underlines the need for alternative drug strategies. 3CLpro only functions as a homodimer, making the protein-protein interface an attractive drug target. Dimerization is partly mediated by a conserved glycine at position 11. However, some naturally occurring SARS-CoV-2 sequences contain a serine at this position, potentially disrupting the dimer. We have used concentration-dependent activity assays and mass spectrometry to show that indeed the G11S mutation reduces the stability of the dimer by 600-fold. This helps to set a quantitative benchmark for the minimum potency required of any future protein-protein interaction inhibitors targeting 3CLpro and raises interesting questions regarding how coronaviruses bearing such weakly dimerizing 3CLpro enzymes are capable of replication.

Mapping interactions of calmodulin and neuronal NO synthase by crosslinking and mass spectrometry

Neuronal nitric oxide synthase (nNOS) is a homodimeric cytochrome P450-like enzyme that catalyzes the conversion of L-arginine to nitric oxide in the presence of NADPH and molecular oxygen. The binding of calmodulin (CaM) to a linker region between the FAD/FMN-containing reductase domain, and the heme-containing oxygenase domain is needed for electron transfer reactions, reduction of the heme, and NO synthesis. Due to the dynamic nature of the reductase domain and low resolution of available full-length structures, the exact conformation of the CaM-bound active complex during heme reduction is still unresolved. Interestingly, hydrogen-deuterium exchange and mass spectrometry studies revealed interactions of the FMN domain and CaM with the oxygenase domain for iNOS, but not nNOS. This finding prompted us to utilize covalent crosslinking and mass spectrometry to clarify interactions of CaM with nNOS. Specifically, MS-cleavable bifunctional crosslinker disuccinimidyl dibutyric urea was used to identify thirteen unique crosslinks between CaM and nNOS as well as 61 crosslinks within the nNOS. The crosslinks provided evidence for CaM interaction with the oxygenase and reductase domain residues as well as interactions of the FMN domain with the oxygenase dimer. Cryo-EM studies, which gave a high-resolution model of the oxygenase domain, along with crosslink-guided docking provided a model of nNOS that brings the FMN within 15 Å of the heme in support for a more compact conformation than previously observed. These studies also point to the utility of covalent crosslinking and mass spectrometry in capturing transient dynamic conformations that may not be captured by hydrogen-deuterium exchange and mass spectrometry experiments.

Measuring Protein-Protein Interactions and Quantifying Their Dissociation Constants with Mass Photometry

Protein-protein interactions underlie most biological processes, and determining the affinity and abundance of binding partners for each interaction is often a challenging task because these interactions often involve multiple ligands and binding sites. Standard methods for determining the affinity of protein interactions often require a large amount of starting material in addition to potentially disruptive labeling or immobilization of the binding partners. Mass photometry is a bioanalytical technique that measures the mass of single biomolecules in solution, quickly and with minimal sample requirements. This article describes how mass photometry can be used to determine the mass distribution of binding partners, the complexes they form, the relative abundance of each species, and, accordingly, the dissociation constant (KD ) of their interactions. © 2024 Refeyn Ltd. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Using mass photometry to measure protein-protein binding and quantify the KD of this interaction.

Sirtuin 2 promotes human cytomegalovirus replication by regulating cell cycle progression

IMPORTANCE

This study expands the growing understanding that protein acetylation is a highly regulated molecular toggle of protein function in both host anti-viral defense and viral replication. We describe a pro-viral role for the human enzyme SIRT2, showing that its deacetylase activity supports HCMV replication. By integrating quantitative proteomics, flow cytometry cell cycle assays, microscopy, and functional virology assays, we investigate the temporality of SIRT2 functions and substrates. We identify a pro-viral role for the SIRT2 deacetylase activity via regulation of CDK2 K6 acetylation and the G1-S cell cycle transition. These findings highlight a link between viral infection, protein acetylation, and cell cycle progression.

Evolutionary paths that link orthogonal pairs of binding proteins

Some protein binding pairs exhibit extreme specificities that functionally insulate them from homologs. Such pairs evolve mostly by accumulating single-point mutations, and mutants are selected if their affinity exceeds the threshold required for function1-4. Thus, homologous and high-specificity binding pairs bring to light an evolutionary conundrum: how does a new specificity evolve while maintaining the required affinity in each intermediate5,6? Until now, a fully functional single-mutation path that connects two orthogonal pairs has only been described where the pairs were mutationally close thus enabling experimental enumeration of all intermediates2. We present an atomistic and graph-theoretical framework for discovering low molecular strain single-mutation paths that connect two extant pairs, enabling enumeration beyond experimental capability. We apply it to two orthogonal bacterial colicin endonuclease-immunity pairs separated by 17 interface mutations7. We were not able to find a strain-free and functional path in the sequence space defined by the two extant pairs. But including mutations that bridge amino acids that cannot be exchanged through single-nucleotide mutations led us to a strain-free 19-mutation trajectory that is completely viable in vivo. Our experiments show that the specificity switch is remarkably abrupt, resulting from only one radical mutation on each partner. Furthermore, each of the critical specificity-switch mutations increases fitness, demonstrating that functional divergence could be driven by positive Darwinian selection. These results reveal how even radical functional changes in an epistatic fitness landscape may evolve.

Systematic analysis of alternative exon-dependent interactome remodeling reveals multitasking functions of gene regulatory factors

Alternative splicing significantly expands biological complexity, particularly in the vertebrate nervous system. Increasing evidence indicates that developmental and tissue-dependent alternative exons often control protein-protein interactions; yet, only a minor fraction of these events have been characterized. Using affinity purification-mass spectrometry (AP-MS), we show that approximately 60% of analyzed neural-differential exons in proteins previously implicated in transcriptional regulation result in the gain or loss of interaction partners, which in some cases form unexpected links with coupled processes. Notably, a neural exon in Chtop regulates its interaction with the Prmt1 methyltransferase and DExD-Box helicases Ddx39b/a, affecting its methylation and activity in promoting RNA export. Additionally, a neural exon in Sap30bp affects interactions with RNA processing factors, modulating a critical function of Sap30bp in promoting the splicing of <100 nt "mini-introns" that control nuclear RNA levels. AP-MS is thus a powerful approach for elucidating the multifaceted functions of proteins imparted by context-dependent alternative exons.

Prediction of protein assemblies by structure sampling followed by interface-focused scoring

Proteins often function as part of permanent or transient multimeric complexes, and understanding function of these assemblies requires knowledge of their three-dimensional structures. While the ability of AlphaFold to predict structures of individual proteins with unprecedented accuracy has revolutionized structural biology, modeling structures of protein assemblies remains challenging. To address this challenge, we developed a protocol for predicting structures of protein complexes involving model sampling followed by scoring focused on the subunit-subunit interaction interface. In this protocol, we diversified AlphaFold models by varying construction and pairing of multiple sequence alignments as well as increasing the number of recycles. In cases when AlphaFold failed to assemble a full protein complex or produced unreliable results, additional diverse models were constructed by docking of monomers or subcomplexes. All the models were then scored using a newly developed method, VoroIF-jury, which relies only on structural information. Notably, VoroIF-jury is independent of AlphaFold self-assessment scores and therefore can be used to rank models originating from different structure prediction methods. We tested our protocol in CASP15 and obtained top results, significantly outperforming the standard AlphaFold-Multimer pipeline. Analysis of our results showed that the accuracy of our assembly models was capped mainly by structure sampling rather than model scoring. This observation suggests that better sampling, especially for the antibody-antigen complexes, may lead to further improvement. Our protocol is expected to be useful for modeling and/or scoring protein assemblies.

Startle Disease: New Molecular Insights into an Old Neurological Disorder

Startle disease (SD) is characterized by enhanced startle responses, generalized muscle stiffness, unexpected falling, and fatal apnea episodes due to disturbed feedback inhibition in the spinal cord and brainstem of affected individuals. Mutations within the glycine receptor (GlyR) subunit and glycine transporter 2 (GlyT2) genes have been identified in individuals with SD. Impaired inhibitory neurotransmission in SD is due to pre- and/or postsynaptic GlyR or presynaptic GlyT2 dysfunctions. Previous research has focused on mutated GlyRs and GlyT2 that impair ion channel/transporter function or trafficking. With insights provided by recently solved cryo-electron microscopy and X-ray structures of GlyRs, a detailed picture of structural transitions important for receptor gating has emerged, allowing a deeper understanding of SD at the molecular level. Moreover, studies on novel SD mutations have demonstrated a higher complexity of SD, with identification of additional clinical signs and symptoms and interaction partners representing key players for fine-tuning synaptic processes. Although our knowledge has steadily improved during the last years, changes in synaptic localization and GlyR or GlyT2 homeostasis under disease conditions are not yet completely understood. Combined proteomics, interactomics, and high-resolution microscopy techniques are required to reveal alterations in receptor dynamics at the synaptic level under disease conditions.

Allosteric inhibition of myosin by phenamacril: a synergistic mechanism revealed by computational and experimental approaches

BACKGROUND

Myosin plays a crucial role in cellular processes, while its dysfunction can lead to organismal malfunction. Phenamacril (PHA), a highly species-specific and non-competitive inhibitor of myosin I (FgMyoI) from Fusarium graminearum, has been identified as an effective fungicide for controlling plant diseases caused by partial Fusarium pathogens, such as wheat scab and rice bakanae. However, the molecular basis of its action is still unclear.

RESULTS

This study used multiple computational approaches first to elucidate the allosteric inhibition mechanism of FgMyoI by PHA at the atomistic level. The results indicated the increase of adenosine triphosphate (ATP) binding affinity upon PHA binding, which might impede the release of hydrolysis products. Furthermore, simulations revealed a broadened outer cleft and a significantly more flexible interface for actin binding, accompanied by a decrease in signaling transduction from the catalytic center to the actin-binding interface. These various effects might work together to disrupt the actomyosin cycle and hinder the ability of motor to generate force. Our experimental results further confirmed that PHA reduces the enzymatic activity of myosin and its binding with actin.

CONCLUSION

Therefore, our findings demonstrated that PHA might suppress the function of myosin through a synergistic mechanism, providing new insights into myosin allostery and offering new avenues for drug/fungicide discovery targeting myosin. © 2023 Society of Chemical Industry.

Exploiting the endogenous yeast nuclear proteome to identify short linear motifs in vivo

Peptide-domain interactions mediated by short linear motifs (SLiMs) play crucial roles in cellular biology. The simplicity of SLiMs poses challenges in their computational identification. Existing high-throughput methods for discovering SLiMs lack cellular context as they are typically performed in vitro. We developed a functional selection method using yeast to identify peptides that interact with the endogenous yeast nuclear proteome. Remarkably, peptides selected for in yeast also mediated nuclear import in human cells. Notably, the identified peptides did not resemble classical nuclear localization sequences. This platform has the potential to identify and investigate motifs that interact with the nuclear proteome of yeast and human and to aid in the identification and understanding of alternative protein nuclear import mechanisms.

Revisiting bacterial cytolethal distending toxin structure and function

Cytolethal distending toxins (CDTs) are intracellular-acting bacterial genotoxins generated by a diverse group of mucocutaneous human pathogens. CDTs must successfully bind to the plasma membrane of host cells in order to exert their modulatory effects. Maximal toxin activity requires all three toxin subunits, CdtA, CdtB, and CdtC, which, based primarily on high-resolution structural data, are believed to preassemble into a tripartite complex necessary for toxin activity. However, biologically active toxin has not been experimentally demonstrated to require assembly of the three subunits into a heterotrimer. Here, we experimentally compared concentration-dependent subunit interactions and toxin cellular activity of the Campylobacter jejuni CDT (Cj-CDT). Co-immunoprecipitation and dialysis retention experiments provided evidence for the presence of heterotrimeric toxin complexes, but only at concentrations of Cj-CdtA, Cj-CdtB, and Cj-CdtC several logs higher than required for Cj-CDT-mediated arrest of the host cell cycle at the G2/M interface, which is triggered by the endonuclease activity associated with the catalytic Cj-CdtB subunit. Microscale thermophoresis confirmed that Cj-CDT subunit interactions occur with low affinity. Collectively, our data suggest that at the lowest concentrations of toxin sufficient for arrest of cell cycle progression, mixtures of Cj-CdtA, Cj-CdtB, and Cj-CdtC consist primarily of non-interacting, subunit monomers. The lack of congruence between toxin tripartite structure and cellular activity suggests that the widely accepted model that CDTs principally intoxicate host cells as preassembled heterotrimeric structures should be revisited.

ADP release can explain spatially-dependent kinesin binding times

The self-organization of cells relies on the profound complexity of protein-protein interactions. Challenges in directly observing these events have hindered progress toward understanding their diverse behaviors. One notable example is the interaction between molecular motors and cytoskeletal systems that combine to perform a variety of cellular functions. In this work, we leverage theory and experiments to identify and quantify the rate-limiting mechanism of the initial association between a cargo-bound kinesin motor and a microtubule track. Recent advances in optical tweezers provide binding times for several lengths of kinesin motors trapped at varying distances from a microtubule, empowering the investigation of competing models. We first explore a diffusion-limited model of binding. Through Brownian dynamics simulations and simulation-based inference, we find this simple diffusion model fails to explain the experimental binding times, but an extended model that accounts for the ADP state of the molecular motor agrees closely with the data, even under the scrutiny of penalizing for additional model complexity. We provide quantification of both kinetic rates and biophysical parameters underlying the proposed binding process. Our model suggests that most but not every motor binding event is limited by their ADP state. Lastly, we predict how these association rates can be modulated in distinct ways through variation of environmental concentrations and spatial distances.

Interactome analysis implicates class II transactivator (CIITA) in depression and other neuroinflammatory disorders

PURPOSE

Inappropriate inflammatory responses within the nervous system (neuroinflammation) have been implicated in several neurological conditions. Class II transactivator (CIITA), a principal regulator of the major histocompatibility complex II (MHCII), is known to play essential roles in inflammation. Hence, CIITA and its interactors could be potentially involved in multiple neurological disorders. However, the molecular mechanisms underlying CIITA-mediated neuroinflammation (NI) are yet to be understood.

MATERIALS AND METHODS

In this regard, we analyzed the potential involvement of CIITA and its interactome in the regulation of neuroinflammation. In the present study, using various computational tools, we aimed (1) to identify NI-related proteins, (2) to filter the critical interactors in the CIITA-NI network, and (3) to analyze the protein-disease interactions and the associated molecular pathways through which CIITA could influence neuroinflammation.

RESULTS

CIITA was found to interact with P T GS2, GSK3B, and NR3C1 and may influence depressive disorders. Further, the IL4/IL13 pathway was found to be potentially underlying the CIITA-interactomemediated effects on neurological disorders. Moreover, CIITA was found to be connected to genes associated with depressive disorder through IL4, wherein CIITA was found to be potentially involved in depressive disorders through IL-4/IL-13 and hippo pathways. However, the present study is based on the existing data on protein interactomes and could be re-evaluated as newer interactions are discovered. Also, the functional mechanisms of CIITA's roles in neuroinflammation must be evaluated further.

CONCLUSION

Notwithstanding these limitations, the results presented here, could form a basis for further experimental studies to assess CIITA as a potential therapeutic target in managing depression and other neuroinflammatory disorders.

Writers and readers of H3K9me2 form distinct protein networks during the cell cycle that include candidates for H3K9 mimicry

Histone H3 lysine 9 methylation (H3K9me), which is written by the Euchromatic Histone Lysine Methyltransferases EHMT1 and EHMT2 and read by the heterochromatin protein 1 (HP1) chromobox (CBX) protein family, is dysregulated in many types of cancers. Approaches to inhibit regulators of this pathway are currently being evaluated for therapeutic purposes. Thus, knowledge of the complexes supporting the function of these writers and readers during the process of cell proliferation is critical for our understanding of their role in carcinogenesis. Here, we immunopurified each of these proteins and used mass spectrometry to define their associated non-histone proteins, individually and at two different phases of the cell cycle, namely G1/S and G2/M. Our findings identify novel binding proteins for these writers and readers, as well as corroborate known interactors, to show the formation of distinct protein complex networks in a cell cycle phase-specific manner. Furthermore, there is an organizational switch between cell cycle phases for interactions among specific writer-reader pairs. Through a multi-tiered bioinformatics-based approach, we reveal that many interacting proteins exhibit histone mimicry, based on an H3K9-like linear motif. Gene ontology analyses, pathway enrichment, and network reconstruction inferred that these comprehensive EHMT and CBX-associated interacting protein networks participate in various functions, including transcription, DNA repair, splicing, and membrane disassembly. Combined, our data reveals novel complexes that provide insight into key functions of cell cycle-associated epigenomic processes that are highly relevant for better understanding these chromatin-modifying proteins during cell cycle and carcinogenesis.

Assessing the dynamics and macromolecular interactions of the intrinsically disordered protein YY1

YY1 is a ubiquitously expressed, intrinsically disordered transcription factor involved in neural development. The oligomeric state of YY1 varies depending on the environment. These structural changes may alter its DNA binding ability and hence its transcriptional activity. Just as YY1's oligomeric state can impact its role in transcription, so does its interaction with other proteins such as FOXP2. The aim of this work is to study the structure and dynamics of YY1 so as to determine the influence of oligomerisation and associations with FOXP2 on its DNA binding mechanism. The results confirm that YY1 is primarily a disordered protein, but it does consist of certain specific structured regions. We observed that YY1 quaternary structure is a heterogenous mixture of oligomers, the overall size of which is dependent on ionic strength. Both YY1 oligomerisation and its dynamic behaviour are further subject to changes upon DNA binding, whereby increases in DNA concentration result in a decrease in the size of YY1 oligomers. YY1 and the FOXP2 forkhead domain were found to interact with each other both in isolation and in the presence of YY1-specific DNA. The heterogeneous, dynamic multimerisation of YY1 identified in this work is, therefore likely to be important for its ability to make heterologous associations with other proteins such as FOXP2. The interactions that YY1 makes with itself, FOXP2 and DNA form part of an intricate mechanism of transcriptional regulation by YY1, which is vital for appropriate neural development.

How different viruses perturb host cellular machinery via short linear motifs

The virus interacts with its hosts by developing protein-protein interactions. Most viruses employ protein interactions to imitate the host protein: A viral protein with the same amino acid sequence or structure as the host protein attaches to the host protein's binding partner and interferes with the host protein's pathways. Being opportunistic, viruses have evolved to manipulate host cellular mechanisms by mimicking short linear motifs. In this review, we shed light on the current understanding of mimicry via short linear motifs and focus on viral mimicry by genetically different viral subtypes by providing recent examples of mimicry evidence and how high-throughput methods can be a reliable source to study SLiM-mediated viral mimicry.

High moisture extrusion of plant proteins: advances, challenges, and opportunities

High moisture extrusion is a widely used technology for producing fibrous meat analogues in an efficient and scalable manner. Extrusion of soy, wheat gluten, and pea is well-documented and related products are already available in the market. There has been growing interest to diversify the protein sources used for meat analogues due to concerns over food waste, monocropping and allergenicity. Optimizing the extrusion process for plant proteins (e.g., hemp, mung bean, fava bean) tends to be time consuming and relies on the operators' intuition and experience to control the process well. Simulating the extrusion process has been challenging so far due to the diverse inputs and configurations involved during extrusion. This review details the mechanism for fibrous structure formation and provides an overview of the extrusion parameters used for texturizing a broad range of plant protein sources. Referring to these data reduces the resources needed for optimizing the extrusion process for novel proteins and may be useful for future extrusion modeling efforts. The review also highlights potential challenges and opportunities for extruding plant proteins, which may help to accelerate the development and commercialization of related products.

Extracellular proteins as potential biomarkers in Sepsis-related cerebral injury

Background

Sepsis can cause brain damage known as septic encephalopathy (SAE), which is linked to higher mortality and poorer outcomes. Objective clinical markers for SAE diagnosis and prognosis are lacking. This study aimed to identify biomarkers of SAE by investigating genes and extracellular proteins involved in sepsis-induced brain injury.

Methods

Extracellular protein differentially expressed genes (EP-DEGs) from sepsis patients' brain tissue (GSE135838) were obtained from Gene Expression Omnibus (GEO) and evaluated by protein annotation database. The function and pathways of EP-DEGs were examined using GO and KEGG. Protein-protein interaction (PPI) networks were built and crucial EP-DEGs were screened using STRING, Cytoscape, MCODE, and Cytohubba. The diagnostic and prognostic accuracy of key EP-DEGs was assessed in 31 sepsis patients' blood samples and a rat cecal ligation and puncture (CLP)-induced sepsis model. Cognitive and spatial memory impairment was evaluated 7-11 days post-CLP using behavioral tests. Blood and cerebrospinal fluid from 26 rats (SHAM n=14, CLP n=12) were collected 6 days after CLP to analyze key EP-DEGs.

Results

Thirty-one EP-DEGs from DEGs were examined. Bone marrow leukocytes, neutrophil movement, leukocyte migration, and reactions to molecules with bacterial origin were all enhanced in EP-DEGs. In comparison to the sham-operated group, sepsis rats had higher levels of MMP8 and S100A8 proteins in their venous blood (both p<0.05) and cerebrospinal fluid (p=0.0506, p<0.0001, respectively). Four important extracellular proteins, MMP8, CSF3, IL-6, and S100A8, were identified in clinical peripheral blood samples. MMP8 and S100A8 levels in the peripheral blood of sepsis patients were higher in SAE than in non-SAE. In comparison to MMP8, S100A8 had a higher area under the curve (AUC: 0.962, p<0.05) and a higher sensitivity and specificity (80% and 100%, respectively) than MMP8 (AUC: 0.790, p<0.05). High levels of S100A8 strongly correlated with 28-day mortality and the Glasgow Coma Scale (GCS) scores.

Conclusion

The extracellular proteins MMP8, CSF3, IL-6, and S100A8 may be crucial in the pathophysiology of SAE. S100A8 and MMP8 are possible biomarkers for SAE's onset and progression. This research may help to clarify the pathogenesis of SAE and improve the diagnosis and prognosis of the disease.

SARS-CoV-2 variants evolve convergent strategies to remodel the host response

SARS-CoV-2 variants of concern (VOCs) emerged during the COVID-19 pandemic. Here, we used unbiased systems approaches to study the host-selective forces driving VOC evolution. We discovered that VOCs evolved convergent strategies to remodel the host by modulating viral RNA and protein levels, altering viral and host protein phosphorylation, and rewiring virus-host protein-protein interactions. Integrative computational analyses revealed that although Alpha, Beta, Gamma, and Delta ultimately converged to suppress interferon-stimulated genes (ISGs), Omicron BA.1 did not. ISG suppression correlated with the expression of viral innate immune antagonist proteins, including Orf6, N, and Orf9b, which we mapped to specific mutations. Later Omicron subvariants BA.4 and BA.5 more potently suppressed innate immunity than early subvariant BA.1, which correlated with Orf6 levels, although muted in BA.4 by a mutation that disrupts the Orf6-nuclear pore interaction. Our findings suggest that SARS-CoV-2 convergent evolution overcame human adaptive and innate immune barriers, laying the groundwork to tackle future pandemics.

Parallel nonfunctionalization of CK1δ/ε kinase ohnologs following a whole-genome duplication event

Whole genome duplication (WGD) followed by speciation allows us to examine the parallel evolution of ohnolog pairs. In the yeast family Saccharomycetaceae, HRR25 is a rare case of repeated ohnolog maintenance. This gene has reverted to a single copy in S. cerevisiae where it is now essential, but has been maintained as pairs in at least 7 species post WGD. In S. cerevisiae, HRR25 encodes the casein kinase (CK) 1δ/ε and plays a role in a variety of functions through its kinase activity and protein-protein interactions (PPIs). We hypothesized that the maintenance of duplicated HRR25 ohnologs could be a result of repeated subfunctionalization. We tested this hypothesis through a functional complementation assay in S. cerevisiae, testing all pairwise combinations of 25 orthologs (including 7 ohnolog pairs). Contrary to our expectations, we observed no cases of pair-dependent complementation, which would have supported the subfunctionalization hypothesis. Instead, most post-WGD species have one ohnolog that failed to complement, suggesting their nonfunctionalization or neofunctionalization. The ohnologs incapable of complementation have undergone more rapid protein evolution, lost most PPIs that were observed for their functional counterparts and singletons from post and non-WGD species, and have non-conserved cellular localization, consistent with their ongoing loss of function. The analysis in N. castelli shows that the non-complementing ohnolog is expressed at a lower level and has become non-essential. Taken together, our results indicate that HRR25 orthologs are undergoing gradual nonfunctionalization.

Computational design of N-linked glycans for high throughput epitope profiling

Efficient identification of epitopes is crucial for drug discovery and design as it enables the selection of optimal epitopes, expansion of lead antibody diversity, and verification of binding interface. Although high-resolution low throughput methods like x-ray crystallography can determine epitopes or protein-protein interactions accurately, they are time-consuming and can only be applied to a limited number of complexes. To overcome these limitations, we have developed a rapid computational method that incorporates N-linked glycans to mask epitopes or protein interaction surfaces, thereby providing a mapping of these regions. Using human coagulation factor IXa (fIXa) as a model system, we computationally screened 158 positions and expressed 98 variants to test experimentally for epitope mapping. We were able to delineate epitopes rapidly and reliably through the insertion of N-linked glycans that efficiently disrupted binding in a site-selective manner. To validate the efficacy of our method, we conducted ELISA experiments and high-throughput yeast surface display assays. Furthermore, x-ray crystallography was employed to verify the results, thereby recapitulating through the method of N-linked glycans a coarse-grained mapping of the epitope.

Amber-codon suppression for spatial localization and in vivo photoaffinity capture of the interactome of the Pseudomonas aeruginosa rare lipoprotein A lytic transglycosylase

The 11 lytic transglycosylases of Pseudomonas aeruginosa have overlapping activities in the turnover of the cell-wall peptidoglycan. Rare lipoprotein A (RlpA) is distinct among the 11 by its use of only peptidoglycan lacking peptide stems. The spatial localization of RlpA and its interactome within P. aeruginosa are unknown. We employed suppression of introduced amber codons at sites in the rlpA gene for the introduction of the unnatural-amino-acids Νζ -[(2-azidoethoxy)carbonyl]-l-lysine (compound 1) and Nζ -[[[3-(3-methyl-3H-diazirin-3-yl)propyl]amino]carbonyl]-l-lysine (compound 2). In live P. aeruginosa, full-length RlpA incorporating compound 1 into its sequence was fluorescently tagged using strained-promoted alkyne-azide cycloaddition and examined by fluorescence microscopy. RlpA is present at low levels along the sidewall length of the bacterium, and at higher levels at the nascent septa of replicating bacteria. In intact P. aeruginosa, UV photolysis of full-length RlpA having compound 2 within its sequence generated a transient reactive carbene, which engaged in photoaffinity capture of neighboring proteins. Thirteen proteins were identified. Three of these proteins-PBP1a, PBP5, and MreB-are members of the bacterial divisome. The use of the complementary methodologies of non-canonical amino-acid incorporation, photoaffinity proximity analysis, and fluorescent microscopy confirm a dominant septal location for the RlpA enzyme of P. aeruginosa, as a divisome-associated activity. This accomplishment adds to the emerging recognition of the value of these methodologies for identification of the intracellular localization of bacterial proteins.

Prospective Functions of miRNA Variants May Predict Breast Cancer Among Saudi Females

Background Growing knowledge supports the importance of microRNAs (miRNAs) in modulating the initiation and development of breast cancer (BC) and underlying mechanisms. BC is a significant public health in females worldwide, where it remains the leading cause of death among Saudi females. Here, we evaluate the susceptibility of the miRNA genetic variants to the risk of BC in Saudi females. Methods One hundred fifty-four females, including 76 females diagnosed with BC and 78 healthy controls, were analyzed using TaqMan™ (Thermo Fischer Scientific, Waltham, MA) genotyping assays for the miR-196a2 rs11614913 C>T, miR-146a rs2910164 C>G, and miR-499 rs3746444 A>G. We utilized the SNPStats software (https://www.snpstats.net) (Institut Català d'Oncologia, Barcelona, Spain) to choose the best interactive inheritance model for the examined miRNAs. Results The examined miRNA single-nucleotide polymorphisms (SNPs) showed no clear association with the risk of BC (P > 0.05). As for genotypic distributions, significant associations were found for the rs2910164 SNP in most interactive models of inheritance: 2.50 (95% confidence interval {CI}, 1.2-5.17; P = 0.0135) in the codominant model, 2.34 (95% CI, 1.11-4.8; P = 0.0197) in the dominant model, and 2.40 (95% CI, 1.22-4.73; P = 0.0113) in overdominant model. The rs2910164 C/G heterozygosity showed overexpression in cases compared to controls (73.7% versus 53.9%; chi-squared (χ2) = 6.5; P = 0.0109), but the homozygous rs2910164 G/G showed a significant protective effect (21.1% versus 38.5%; χ2 = 17.4; P = 0.019). The heterozygosity did not affect the risk to the BC in the two miRNAs (rs11614913 C>T and rs3746444 A>G). Conclusion Despite lacking associations with the examined miRNAs, the heterozygous genotype rs2910164 C/G can identify at-risk females. More studies should be replicated using a panel of miRNA genes to discover significant associations with the risk of BC.

Rational design of small-molecule responsive protein switches

Small-molecule responsive protein switches are powerful tools for controlling cellular processes. These switches are designed to respond rapidly and specifically to their inducer. They have been used in numerous applications, including the regulation of gene expression, post-translational protein modification, and signal transduction. Typically, small-molecule responsive protein switches consist of two proteins that interact with each other in the presence or absence of a small molecule. Recent advances in computational protein design already contributed to the development of protein switches with an expanded range of small-molecule inducers and increasingly sophisticated switch mechanisms. Further progress in the engineering of small-molecule responsive switches is fueled by cutting-edge computational design approaches, which will enable more complex and precise control over cellular processes and advance synthetic biology applications in biotechnology and medicine. Here, we discuss recent milestones and how technological advances are impacting the development of chemical switches.

Uncovering the Molecular Drivers of NHEJ DNA Repair-Implicated Missense Variants and Their Functional Consequences

Variants in non-homologous end joining (NHEJ) DNA repair genes are associated with various human syndromes, including microcephaly, growth delay, Fanconi anemia, and different hereditary cancers. However, very little has been done previously to systematically record the underlying molecular consequences of NHEJ variants and their link to phenotypic outcomes. In this study, a list of over 2983 missense variants of the principal components of the NHEJ system, including DNA Ligase IV, DNA-PKcs, Ku70/80 and XRCC4, reported in the clinical literature, was initially collected. The molecular consequences of variants were evaluated using in silico biophysical tools to quantitatively assess their impact on protein folding, dynamics, stability, and interactions. Cancer-causing and population variants within these NHEJ factors were statistically analyzed to identify molecular drivers. A comprehensive catalog of NHEJ variants from genes known to be mutated in cancer was curated, providing a resource for better understanding their role and molecular mechanisms in diseases. The variant analysis highlighted different molecular drivers among the distinct proteins, where cancer-driving variants in anchor proteins, such as Ku70/80, were more likely to affect key protein-protein interactions, whilst those in the enzymatic components, such as DNA-PKcs, were likely to be found in intolerant regions undergoing purifying selection. We believe that the information acquired in our database will be a powerful resource to better understand the role of non-homologous end-joining DNA repair in genetic disorders, and will serve as a source to inspire other investigations to understand the disease further, vital for the development of improved therapeutic strategies.

An amino acid-resolution interactome for motile cilia illuminates the structure and function of ciliopathy protein complexes

Motile cilia are ancient, evolutionarily conserved organelles whose dysfunction underlies motile ciliopathies, a broad class of human diseases. Motile cilia contain myriad different proteins that assemble into an array of distinct machines, so understanding the interactions and functional hierarchies among them presents an important challenge. Here, we defined the protein interactome of motile axonemes using cross-linking mass spectrometry (XL/MS) in Tetrahymena thermophila. From over 19,000 XLs, we identified 4,757 unique amino acid interactions among 1,143 distinct proteins, providing both macromolecular and atomic-scale insights into diverse ciliary machines, including the Intraflagellar Transport system, axonemal dynein arms, radial spokes, the 96 nm ruler, and microtubule inner proteins, among others. Guided by this dataset, we used vertebrate multiciliated cells to reveal novel functional interactions among several poorly-defined human ciliopathy proteins. The dataset therefore provides a powerful resource for studying the basic biology of an ancient organelle and the molecular etiology of human genetic disease.