Biomolecules

BackgroundThe endocannabinoid system (ECS) is a complex signaling network that regulates diverse physiological processes, including pain, mood, metabolism, and immune response, through coordinated interactions among receptors, enzymes, and lipid-derived ligands. Despite extensive research on individual ECS components, the systems-level organization and network resilience of the ECS remain underexplored. Here, we present a systems-level analysis of the ECS that integrates protein-protein and protein-chemical interactions into a unified network framework. MethodsWe constructed integrated ECS networks that combine protein-protein and protein-chemical interactions, utilizing data from multiple public databases. Network analyses were performed in Python using NetworkX to assess molecular connectivity and interaction topology. We utilized centrality measures to identify major hubs, employed community detection algorithms to examine the clustering of nodes, and performed targeted perturbations by sequentially removing the top-ranked nodes based on degree and betweenness centrality to assess network robustness. ResultsCentrality analyses identified the primary cannabinoid receptors, cannabinoid receptor 1 (CNR1) and cannabinoid receptor 2 (CNR2), as major hubs with extensive connectivity to endogenous and exogenous ligands. Non-canonical receptors, including transient receptor potential vanilloid 1 (TRPV1) and G-protein coupled receptor 55 (GPR55), also emerged as highly ranked nodes across multiple centrality measures, underscoring their integrative roles within the ECS signaling pathway. Community detection revealed biologically meaningful modules centered around receptor and metabolic clusters, with CNR1, CNR2, anandamide (AEA), 2-arachidonoylglycerol (2-AG), and major phytocannabinoids maintaining key network connectivity. Perturbation analyses demonstrated that removal of top hubs, particularly CNR1, caused pronounced losses in edge connectivity and disrupted signaling pathways among cannabinoids. However, the redistribution of influence toward CNR2 and GPR55 under multi-node removal conditions revealed compensatory plasticity and resilience within the ECS network. ConclusionThis systems-level study highlights the hierarchical and robust architecture of the ECS. The identification of hub nodes, functional communities, and compensatory mechanisms provides insight into how the ECS maintains signaling integrity in the face of perturbation. These findings establish a network-based framework for studying cannabinoid biology and may inform future therapeutic strategies targeting the ECS and its interacting molecular pathways.

Angiogenesis, the formation of new vessels from existing vessels, is mediated by vascular endothelial growth factor (VEGF) and platelet-derived growth factor (PDGF). Despite discoveries supporting the cross-family interactions between VEGF and PDGF families, sharing the binding partners between them makes it challenging to identify growth factors that predominantly affect angiogenesis. Systems biology offers promises to untangle this complexity. Thus, in this study, we developed a mass-action kinetics-based computational model for cross-family interactions between VEGFs (VEGF-A, VEGF-B, and PlGF) and PDGFs (PDGF-AA, PDGF-AB, and PDGF-BB) with their receptors (VEGFR1, VEGFR2, NRP1, PDGFR, and PDGFR{beta}). The model, parametrized with our literature mining and surface resonance plasmon assays, was validated by comparing the concentration of VEGFR1 complexes with a previously constructed angiogenesis model. The model predictions include five outcomes: 1) the percentage of free or bound ligands and 2) receptors, 3) the concentration of free ligands, 4) the percentage of ligands occupying each receptor, and 5) the concentration of ligands that is bound to each receptor. We found that at equimolar ligand concentrations (1 nM), PlGF and VEGF-A were the main binding partners of VEGFR1 and VEGFR2, respectively. Varying the density of receptors resulted in the following five outcomes: 1) Increasing VEGFR1 density depletes the free PlGF concentration, 2) increasing VEGFR2 density decreases PDGF:PDGFR complexes, 3) increased NRP1 density generates a biphasic concentration of the free PlGF, 4) increased PDGFR density increases PDGFs:PDGFR binding, and 5) increasing PDGFR{beta} density increases VEGF-A:PDGFR{beta}. Our model offers a reproducible, fundamental framework for exploring cross-family interactions that can be extended to the tissue level or intracellular molecular level. Also, our model may help develop therapeutic strategies in pathological angiogenesis by identifying the dominant complex in the cell signaling. Author summaryNew blood vessel formation from existing ones is essential for growth, healing, and reproduction. However, when this process is disrupted--either too much or too little--it can contribute to diseases such as cancer and peripheral arterial disease. Two key families of proteins, vascular endothelial growth factors (VEGFs) and platelet-derived growth factors (PDGFs), regulate this process. Traditionally, scientists believed that VEGFs only bind to VEGF receptors and PDGFs to PDGF receptors. However, recent findings show that these proteins can interact with each others receptors, making it more challenging to understand and control blood vessel formation. To clarify these complex interactions, we combined computer modeling with biological data to map out which proteins bind to which receptors and to what extent. Our findings show that when VEGFs and PDGFs are present in equal amounts, VEGFs are the primary binding partners for VEGF receptors. We also explored how changes in receptor levels affect these interactions in disease-like conditions. This work provides a foundational computational model for studying cross-family interactions, which can be expanded to investigate tissue-level effects and processes inside cells. Ultimately, our model may help develop better treatments for diseases linked to abnormal blood vessel growth by identifying key protein-receptor interactions.

Alzheimers disease (AD) is a multifactorial disorder that affects cognitive functioning, behavior, and neuronal properties. The neuronal dysfunction is primarily responsible for cognitive decline in AD patients, with many causal factors including plaque accumulation of A{beta}42. Neural hyperactivity induced by A{beta}42 deposition cause abnormalities in neural networks, leading to alterations in synaptic activity and interneuron dysfunction. Even though neuroimaging techniques elucidated the underlying mechanism in the neural connectivity, precise understanding in cellular level is still elusive. Previously, a few multielectrode array studies examined the neuronal network modulation in vitro cultures revealing relevance of ion channels and the chemical modulators in the presence of A{beta}42. In this study, we investigated neuronal connectivity and dynamic changes with high density multielectrode array, particularly in relation to network-wide parameter changes over time. By comparing the neuronal network between normal and A{beta}42 treated neuronal cultures, it was possible to discover the direct pathological effect of the A{beta}42 oligomer altering the network characteristics. The application of graph theory and center of activity trajectory analysis assessed the consolidation and disassociation of neural networks under A{beta}42 oligomer exposure over time. This result can enhance our understanding of how neural networks are affected during AD progression.

Multiple paracrine factors regulate barrier properties of human brain capillary endothelial cells (BCECs). Understanding precise mode of action of these factors remains a challenging task because of the limited availability of functionally competent BCECs and use of serum-containing medium. In the present study we employed defined protocol for producing BCECs from human inducible pluripotent stem cells. We found that autocrine secretion of basic fibroblast growth factor (bFGF) is necessary for the establishment a tight BCECs barrier, as revealed by measurements of trans-endothelial electric resistance (TEER). In contrast, exogenous bFGF in concentrations exceeding 4 ng/ml inhibited TEER and proliferation of BCECs in a concentration-dependent manner. Exogenous bFGF did not significantly affect expression and distribution of tight junction proteins claudin-5, occludin and ZO-1. Treatment with FGF receptor blocker PD173074 (15 M) suppressed inhibitory effects of bFGF and induced nuclear translocation of protein ZO-1. Inhibition of phosphoinositide 3-Kinase (PI-3K) with LY294002 (25 M) significantly potentiated inhibitory effect of bFGF on TEER indicating that PI-3K signalling pathway partially suppress inhibitory effects of bFGF on TEER. In conclusion we show that autocrine bFGF secretion is necessary for the proper barrier function of BCECs, whereas exogenous bFGF suppresses barrier resistance in a concentration-dependent manner. Our findings demonstrate a dual role for bFGF in the regulation of BCEC barrier function.

The Y1 mouse adrenocortical carcinoma cell line presents amplification of the KRas oncogene and high-basal levels of KRAS-GTP mediated by the GEF SOS. In this research, we developed a dynamic model based on ordinary differential equations of the KRAS-GTP activation mediated by SOS in Y1 cells, which showed that SOS only is not sufficient to reach the high-basal levels of KRAS-GTP experimentally observed for this cell line. Interestingly, a modification in this system, which added another GEF in the model, made the model reach the expected levels of KRAS activation, leading to the hypothesis that there was a missing element in this system. To find this missing element, a PCR panel of RasGEFs was performed and the GEF Rasgrp4 was found highly expressed in parental Y1 cell lines, indicating that this was the missing element in the system. Finally, tumor growth assays in Balb/c-NUDE mice with the Y1 cell versus RASGRP4 CRISPR depleted Y1 cells, showed reduced tumor growth and frequency for the RASGRP4 depleted cells.

Allostery is an intrinsic dynamic phenomenon that underlies functional long-distance interactions in proteins, which we study here by stochastic calculus approach to elastic network models (ENMs). We show that once you drop the usually accepted high friction limit and include hydrodynamic interactions in ENMs, a simple measure that uses the pairwise difference in the time-delayed correlations of residue fluctuations provides insight about functional sites and their dynamical behaviour in allosteric communication. We present this with three exemplary cases Aspartate Carbamoyl transferase, Insulin Receptor and DNA-dependent Protein Kinase. We show that proteins possess characteristic pathways operating at different time-delay windows with slow to faster motions underlying the protein function. As these pathways help communication between key residues of functionality, they can also be used to identify their locations without any prior knowledge other than the protein crystal structure.

Prions are unconventional pathogen without nucleotide genome and their pathogenic properties are defined by the primary structure and the conformation of the constituent abnormal isoform (PrPSc) of prion protein (PrP). A polymorphic codon 129 of human PrP that is valine (V129) or methionine (M129) is particularly influential on properties of PrPSc, affecting transmission efficiencies and clinicopathological features. However, how the single residue is so influential has not been elucidated because the detailed structures of PrPSc have not been determined yet due to its incompatibility with high-resolution structural analysis. Previously we created an in-register parallel {beta}-sheet local structural model of human PrPSc encompassing residues 107 to 143 that seemed more compatible with V129 than M129, based on knowledge from -synuclein amyloids and an NMR-based model of the amyloid of Y145Stop mutant of PrP in the literature. Here, we created an M129-compatible local structural model of PrPSc. Severe destabilization of the model by G127V mutation was consistent with the protective effects of V127 polymorphism of human PrP against prions. It was highly sensitive to the length of the hydrophobic side chain of codon 129 and replacement of M129 with leucine or valine destabilized the structures. Interestingly, the U-shaped {beta}-arch which comprises M129 flexibly changed hydrophobic interaction networks inside the {beta}-arch depending on the interactions with the surrounding structures, whereas the previous model with V129 maintained the similar network patterns irrespective of the surroundings. The differences between the two models may explain influences of the codon 129 polymorphism on transmissions and properties of human prions.

Human HSPB1, a member of the small heat shock protein (sHSP) family, functions as an ATP-independent molecular chaperone crucial for protein quality control and is implicated in several pathologies, including Charcot-Marie-Tooth neuropathy. This study investigates the coevolution of the disordered N-terminal and C-terminal regions (NTR and CTR) with the structured Alpha-Crystallin domain (ACD) of human HSPB1, focusing on interactions that regulate its chaperone activity. Using a manually curated dataset of HSPB1 orthologs, the composition of critical motifs within the NTR (6VPFSLL11) and CTR (179ITIPV183) that interact with the ACD was analyzed and evolutionary rates per site for the human HSPB1 sequence were estimated. Additionally, structural modeling with AlphaFold 2 was employed to assess the prevalence of these contacts in human HSPB1 models. The results reveal that while the disordered regions globally evolve faster than the structured ACD, specific residues within the 6VPFSLL11 and 179ITIPV183 motifs exhibit reduced evolutionary rates, reflecting evolutionary constraints imposed by the conservation of the proteins function. Structural modeling further indicates that coevolutionary-like information about the interaction between the 6VPFSLL11 motif and the ACD is encoded in the multiple sequence alignment used by Alphafold 2. Altogether, these findings suggest that the disordered regions and the ACD of human HSPB1 likely coevolved, preserving interactions crucial for its chaperone activity self-regulation. This evolutionary mechanism may also be extended to other sHSP featuring interacting motifs in the NTR, CTR, or both, and provides a framework to elucidate why pathogenic variants occurring in regions involved in these contacts contribute to disease.

Cellular actin polymerization is a tightly regulated process, typically controlled by proteins with specialized domains such as the Wiskott-Aldrich syndrome protein homology 2 (WH2) domain. Here, we identify SH3BGRL family proteins as modulators of actin dynamics, uniquely characterized by their thioredoxin (Trx) fold structure and the absence of the canonical CXXC enzymatic site essential for redox activity. The Trx fold is generally associated with enzymatic activity; however, in this context, it functions non-enzymatically to enhance actin filament nucleation and inhibit depolymerization. The family member SH3BGRL-2 was previously identified as part of the spectrin-actin complex in porcine erythrocytes. Further structural analysis reveals that human SH3BGRL proteins share structural homology with the C-terminal region of Saccharomyces cerevisiae YFR016c/Aip5, a known actin nucleation factor reported to bind G-actin. Notably, our results show that human SH3BGRL proteins do not bind G-actin directly. While they do not interact with G-actin, SH3BGRL proteins significantly increase actin assembly rates by accelerating filament nucleation without affecting barbed end elongation, as demonstrated in pyrene-actin bulk-polymerization assays and total internal reflection fluorescence microscopy (TIRFM) based single-filament studies. Furthermore, using all-atom molecular dynamics (MD) simulations and in vitro assays that directly probe the pointed end of the actin filament, we show that SH3BGRL proteins inhibit the depolymerization of existing filaments by interacting with the pointed end of the actin filament, also in the presence of the well-characterized pointed end capping protein tropomodulin. Our results indicate that all SH3BGRL family proteins promote actin nucleation by stabilizing energetically unstable actin dimers and trimers and inhibit depolymerization by direct association with the pointed end, suggesting a direct role for the Trx fold in actin dynamics.

AlphaFold is a new, highly accurate machine learning protein structure prediction method that outperforms other methods. Recently this method was used to predict the structure of 98.5% of human proteins. We analyze here the structure of these AlphaFold-predicted human proteins for the presence of knots. We found that the human proteome contains 65 robustly knotted proteins, including the most complex type of a knot yet reported in proteins. That knot type, denoted 63 in mathematical notation, would necessitate a more complex folding path than any knotted proteins characterized to date. In some cases AlphaFold structure predictions are not highly accurate, which either makes their topology hard to verify or results in topological artifacts. Other structures that we found, which are knotted, potentially knotted, and structures with artifacts (knots) we deposited in a database available at: https://knotprot.cent.uw.edu.pl/alphafold.

In an effort to gain insight into cellular systems impacted by neurotrophic trans-banglene (t-BG), global proteomic profiling and Western blot analyses were employed. Expression level changes in response to t-BG treatment were compared to those observed with nerve growth factor (NGF), a natural neurotrophic protein and functional analog to t-BG. Findings from these studies did not point to direct interception of NGF/TrkA signaling by t-BG. Instead, significant alterations in iron-binding and iron-regulating proteins were observed. Intracellular iron measurements by FerroOrange indicate lower ferrous (Fe2+) iron levels in t-BG treated cells but not in NGF treated cells. These results highlight a potential connection between iron regulation and neurotrophic activity.

Ras proteins activate their effectors through physical interactions in response to the various extracellular stimuli at the plasma membrane. Oncogenic Ras forms dimer and nanoclusters at the plasma membrane, boosting the downstream MAPK signal. It was reported that K-Ras4B can dimerize through two major interfaces: (i) the effector lobe interface, mapped to Switch I and effector binding regions; (ii) the allosteric lobe interface involving 3 and 4 helices. Recent experiments showed that constitutively active, oncogenic mutant K-Ras4BG12D dimers are enriched in the plasma membrane. Here, we perform molecular dynamics simulations of K-Ras4BG12D homodimers aiming to quantify the two major interfaces in atomic level. To examine the effect of mutations on dimerization, two double mutations, K101D/R102E on the allosteric lobe and R41E/K42D on the effector lobe interfaces were added to the K-Ras4BG12D dimer simulations. We observed that the effector lobe K-Ras4BG12D dimer is stable, while the allosteric lobe dimer alters its helical interface during the simulations, presenting multiple conformations. The K101D/R102E mutations slightly weakens the allosteric lobe interface. However, the R41E/K42D mutations disrupt the effector lobe interface. Using the homo-oligomers prediction server, we obtained trimeric, tetrameric, and pentameric complexes with the allosteric lobe K-Ras4BG12D dimers. However, the allosteric lobe dimer with the K101D/R102E mutations is not capable of generating multiple higher order structures. Our detailed interface analysis may help to develop inhibitor design targeting functional Ras dimerization and high order oligomerization at the membrane signaling platform.

Tumor Necrosis Factor Superfamily (TNFSF) comprises 20 members of membrane/soluble signaling proteins regulating cell survival, cell proliferation/differentiation, and innate/adaptive immunity. Targeting signaling of TNFSF members is used clinically to treat several autoimmune and oncological diseases, and bone loss. They and their cognate receptors are in clinical trials as targets for treatment of autoimmune, inflammatory, oncological and other diseases. Recently, some representatives of S100 family of pleiotropic calcium-binding proteins were shown to interact with TNFSF members TNF and TRAIL, thereby suppressing their activity. In this work, we explored selectivity of interactions between soluble forms of 13 TNFSF members and 21 non-fused S100 proteins using surface plasmon resonance spectroscopy. A total of 27 interactions were found between CD70, CD30L, 4-1BBL, TWEAK, APRIL, LIGHT, VEGI and AITRL and Ca2+-loaded forms of S100A1/A2/A4/A5/A6/A12/A16/B/P proteins, with equilibrium dissociation constants from 2 nM to 24 M. Removal of calcium leads to disruption of the interactions. Molecular docking indicates presence of well-conserved binding sites of the both interaction partners. Mutagenesis of S100P evidences involvement of its hinge region in binding of CD30L, VEGI and AITRL, as well as F89 residue in VEGI recognition. The revealed network of interactions is potentially important for regulation of the cellular communication mediated by TNFSF/S100 proteins, which could be exploited for targeted therapy of socially significant diseases.

Endothelial cells (ECs) line the vascular system and are key players in vascular homeostasis, yet their metabolic diversity across tissues, vascular beds, and growth states remains poorly understood. This study examines metabolic differences between proliferating and quiescent ECs and compares blood and lymphatic endothelium using proteomics and metabolomics. Our findings indicate that metabolism in quiescent ECs is not dormant but reorganized in a cell-specific manner, with decreased heme intermediates in human umbilical vein ECs and increased branched-chain amino acid catabolism across all quiescent ECs. Consistent with the differences identified in the omics data, perturbation studies revealed that inhibiting enzymes involved in heme, glutamate, fatty acid, and nucleotide biosynthesis led to distinct phenotypic responses in blood and lymphatic ECs. These findings highlight the importance of metabolic pathways in sustaining both proliferating and quiescent ECs and reveal how ECs from different vascular beds rely on distinct metabolic processes to maintain their functional states.

We identified a germline TP53 c.758C>T (p.T253I) mutation in the TP53 tumor suppressor gene in a pediatric adrenocortical carcinoma (ACC) patient. Characteristic to pathogenic p53 mutations, we observed upregulation of total p53 protein levels in the patients ACC and concurrent suppression of the wild-type (WT) TP53 allele. As ACC can be associated with Li-Fraumeni Syndrome (LFS) and the mutation has not yet been linked to LFS, we sought to characterize the functionality of the T253I mutation. We acquired p53-/- HEK293 cells and stably transduced them with GFP-tagged wild type (T253) or T253I p53 as well as two established pathogenic p53 mutants (C176Y and R213X). Compared to p53 WT, levels of T253I p53 increased while MDM2 levels decreased, suggesting a loss of MDM2-mediated regulation of T253I p53. Additionally, T253I showed a reduction in DNA damage responsive events, diminished DNA binding capabilities, and blunted transactivation capacity. These experimental data lead us to conclude that T253I represents a pathologic variant in TP53 that may predispose to LFS-associated tumors.

Bacteriophage anti-CRISPR (Acr) proteins have the potential to reduce off-target effects of genome editing by inactivating the CRISPR-Cas bacterial defense. The current challenge lays in their functional annotation, as Acr proteins have high structural diversity and low sequence similarity, thus rendering common homology-based methods unfit. Recent solutions use deep learning models such as graph convolutional networks that take protein networks as the data input. In an effort to understand whether these new solutions are fit for niche, sparsely annotated proteins, we focus on 3 Acr proteins (AcrIF1, AcrIIA1, and AcrVIA1) as a case study. For each, we create protein contact networks (PCNs) and residue interaction graphs (RIGs) based on existing network theory and methodology. We characterize and analyze these protein networks by comparing how each network architecture affects values of small-worldliness. We reexamine a previous method that focused on using node degree, closeness centralities, and residue solvent accessibility to predict functional residues within a protein via a Jackknife technique. We discuss the implications of the construction of these networks based on how the structure information is acquired. We demonstrate that functional residues within small proteins cannot be reliably predicted with the Jackknife technique, even when provided with a curated dataset containing representative standardized values for degree and closeness centrality. We show that functional residues within these small proteins have low degrees within both PCNs and RIGs, thus making them susceptible to the known degree bias towards high degree nodes present in using graph convolutional networks. We discuss how understanding the data can be used to further improve deep learning approaches for small proteins. Author summaryA bacterias CRISPR-Cas defense system acts as security guard against viruses like bacteriophages. By storing pieces of viral DNA as records, it can recognize and defend the bacteria against threats. Scientists have adapted this effective record keeping process to perform targeted genome editing. Some bacteriophages have genes that encode for anti-CRISPR (Acr) proteins. The proteins act as a criminal accomplice to the viral DNA, sneaking them in past the bacterias security in a variety of ways. There has been increased interest in using these Acr proteins to limit unintended or off-target effects of targeted genome editing. However, Acr proteins are difficult to identify. We changed parts of a previous method that used graph representations of protein structure to determine important amino acids that help that protein perform its function. We applied these methods to three Acr proteins to determine whether we observed similar patterns in these graphs. We explain how features of these graph representations of protein structures can affect graph neural networks that use them as input to learn more about proteins.

Aim & ObjectivesThe aim of the present study is to evaluate the regeneration efficacy of rhEGF impregnated in collagen membrane for the management of Millers class I & class II gingival recession defects. Patients and methods18 patients with 30 Millers class I & class II gingival recession defects were treated with one of the following interventions and randomly allocated into each of the following experimental groups; Test group: rhEGF impregnated in collagen membrane, Control group: plain collagen membrane. Clinical measurements at baseline, 3 months and 6 months included decreased probing depth, recession depth and increase in width of keratinized gingiva. ResultsThere was an improvement in tissue biotype in test group and statistically significant increase in KGW from baseline to 3 months which remained constant from 3 months to 6 months(p[≤]0.001) in both the groups. Similarly, RD shows constant increase from baseline to 6 months in test group whereas there is reduction in control group (p[≤]0.003). There was significant difference in clinical parameters in both test and control groups. All the patients had an uneventful healing phase. ConclusionThe beneficial effects of rhEGF resulted in healthy wound healing process with less scarring offers more potential properties showed promising results over collagen membrane. Further larger samples are required to confirm the efficacy of rhEGF in root coverage for soft tissue regeneration.

Thrombin, a central serine protease in hemostasis, exhibits dual functionality in coagulation processes--favoring fibrinogen cleavage in its native form while shifting towards protein C activation when complexed with thrombomodulin (TM). Thrombin also plays roles in cancer-associated thrombosis and may be involved in metastasis and tumorigenesis. The W215A/E217A (WE) double mutant of thrombin presents a unique case, with its fibrinogen cleavage activity diminished by 19,000-fold, contrasting a modest 7-fold reduction in protein C activation in the presence of TM. The differential substrate specificity of this mutant raises fundamental questions about the underlying molecular mechanisms. In this study, we employed all-atom microsecond-scale molecular dynamics (MD) simulations, complemented by Root Mean Square Fluctuation (RMSF) analysis, clustering algorithms, PCA-based free-energy surfaces, and logistic regression modeling, to dissect the structural and allosteric changes driving thrombins substrate specificity. Our results unveil distinct conformational states within the catalytic triad, each optimized for specific substrate interactions. We demonstrate that the WE mutations synergize with TM456 binding, resulting in altered hydrogen bond networks and distinct free energy landscapes. A key finding of our research is the identification of ARG125 as a pivotal element in these interactions, consistently forming critical hydrogen bonds across different thrombin variants. The persistent role of ARG125 not only elucidates aspects of thrombins functional plasticity but also positions it as a promising target for novel therapies. This comprehensive analysis enhances our understanding of thrombins structural dynamics, paving the way for more effective and targeted therapeutics.

Synapses contain highly complex proteomes which control synaptic transmission, cognition and behaviour. Genes encoding synaptic proteins are associated with neuronal disorders many of which show clinical co-morbidity. Our hypothesis is that there is mechanistic overlap that is emergent from the network properties of the molecular complex. To test this requires a detailed and comprehensive molecular network model. We integrated 57 published synaptic proteomic datasets obtained between 2000 and 2019 that describe over 7000 proteins. The complexity of the postsynaptic proteome is reaching an asymptote with a core set of ~3000 proteins, with less data on the presynaptic terminal, where each new study reveals new components in its landscape. To complete the network, we added direct protein-protein interaction data and functional metadata including disease association. The resulting amalgamated molecular interaction network model is embedded into a SQLite database. The database is highly flexible allowing the widest range of queries to derive custom network models based on meta-data including species, disease association, synaptic compartment, brain region, and method of extraction. This network model enables us to perform in-depth analyses that dissect molecular pathways of multiple diseases revealing shared and unique protein components. We can clearly identify common and unique molecular profiles for co-morbid neurological disorders such as Schizophrenia and Bipolar Disorder and even disease comorbidities which span biological systems such as the intersection of Alzheimers Disease with Hypertension.

The highly conserved Hsp90 chaperones control stability and activity of many essential signaling and regulatory proteins including many protein kinases, E3 ligases and transcription factors. Thereby, Hsp90s couple cellular homeostasis of the proteome to cell fate decisions. High-throughput mass spectrometry revealed 178 and 169 posttranslational modifications (PTMs) for human cytosolic Hsp90 and Hsp90{beta}, but for only a few of the modifications the physiological consequences are investigated in some detail. In this study, we explored the suitability of the yeast model system for the identification of key regulatory residues in human Hsp90. Replacement of three tyrosine residues known to be phosphorylated by phosphomimetic glutamate and by non-phosphorylatable phenylalanine individually and in combination influenced yeast growth and the maturation of 7 different Hsp90 clients in distinct ways. Furthermore, wild-type and mutant Hsp90 differed in their ability to stabilize known clients when expressed in HepG2 HSP90AA1-/- cells. The purified mutant proteins differed in their interaction with the cochaperones Aha1, Cdc37, Hop and p23 and in their support of the maturation of glucocorticoid receptor ligand binding domain in vitro. In vivo and in vitro data correspond well to each other confirming that the yeast system is suitable for the identification of key regulatory sites in human Hsp90s. Our findings indicate that even closely related clients are affected differently by the amino acid replacements in the investigated positions, suggesting that PTMs could bias Hsp90s client specificity.