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Short linear motif (SLiM)-mediated interactions offer a unique strategy for viral intervention due to their compact interfaces, ease of convergent evolution, and key functional roles. Consequently, many viruses extensively mimic host SLiMs to hijack or deregulate cellular pathways and the same motif-binding pocket is often targeted by numerous unrelated viruses. A toolkit of therapeutics targeting commonly mimicked SLiMs could provide prophylactic and therapeutic broad-spectrum antivirals and vastly improve our ability to treat ongoing and future viral outbreaks. In this opinion article, we discuss the therapeutic relevance of SLiMs, advocating their suitability as targets for broad-spectrum antiviral inhibitors.

Phosphorylation is the most common post-translational modification (PTM) in eukaryotes, occurring particularly frequently in intrinsically disordered proteins (IDPs). These proteins are highly flexible and dynamic by nature. Thus, it is intriguing that the addition of a single phosphoryl group to a disordered chain can impact its function so dramatically. Furthermore, as many IDPs carry multiple phosphorylation sites, the number of possible states increases, enabling larger complexities and novel mechanisms. Although a chemically simple and well-understood process, the impact of phosphorylation on the conformational ensemble and molecular function of IDPs, not to mention biological output, is highly complex and diverse. Since the discovery of the first phosphorylation site in proteins 75 years ago, we have come to a much better understanding of how this PTM works, but with the diversity of IDPs and their capacity for carrying multiple phosphoryl groups, the complexity grows. In this Essay, we highlight some of the basic effects of IDP phosphorylation, allowing it to serve as starting point when embarking on studies into this topic. We further describe how recent complex cases of multisite phosphorylation of IDPs have been instrumental in widening our view on the effect of protein phosphorylation. Finally, we put forward perspectives on the phosphorylation of IDPs, both in relation to disease and in context of other PTMs; areas where deep insight remains to be uncovered. Phosphorylation is the most common post-translational modification (PTM) in eukaryotes, occurring particularly frequently in intrinsically disordered proteins (IDPs). These proteins are highly flexible and dynamic by nature. Thus, it is intriguing that the addition of a single phosphoryl group to a disordered chain can impact its function so dramatically. Furthermore, as many IDPs carry multiple phosphorylation sites, the number of possible states increases, enabling larger complexities and novel mechanisms. Although a chemically simple and well-understood process, the impact of phosphorylation on the conformational ensemble and molecular function of IDPs, not to mention biological output, is highly complex and diverse. Since the discovery of the first phosphorylation site in proteins 75 years ago, we have come to a much better understanding of how this PTM works, but with the diversity of IDPs and their capacity for carrying multiple phosphoryl groups, the complexity grows. In this Essay, we highlight some of the basic effects of IDP phosphorylation, allowing it to serve as starting point when embarking on studies into this topic. We further describe how recent complex cases of multisite phosphorylation of IDPs have been instrumental in widening our view on the effect of protein phosphorylation. Finally, we put forward perspectives on the phosphorylation of IDPs, both in relation to disease and in context of other PTMs; areas where deep insight remains to be uncovered.

The cycling import receptor PEX5 and its membrane-located binding partner PEX14 are key constituents of the peroxisomal import machinery. Upon recognition of newly synthesized cargo proteins carrying a peroxisomal targeting signal type 1 (PTS1) in the cytosol, the PEX5/cargo complex docks at the peroxisomal membrane by binding to PEX14. The PEX14 N-terminal domain (NTD) recognizes (di)aromatic peptides, mostly corresponding to Wxxx(F/Y)-motifs, with nano-to micromolar affinity. Human PEX5 possesses eight of these conserved motifs distributed within its 320-residue disordered N-terminal region. Here, we combine biophysical (ITC, NMR, CD), biochemical and computational methods to characterize the recognition of these (di)aromatic peptides motifs and identify key features that are recognized by PEX14. Notably, the eight motifs present in human PEX5 exhibit distinct affinities and energetic contributions for the interaction with the PEX14 NTD. Computational docking and analysis of the interactions of the (di)aromatic motifs identify the specific amino acids features that stabilize a helical conformation of the peptide ligands and mediate interactions with PEX14 NTD. We propose a refined consensus motif ExWΦxE(F/Y)Φ for high affinity binding to the PEX14 NTD and discuss conservation of the (di)aromatic peptide recognition by PEX14 in other species.

Arabidopsis halleri is a hyperaccumulating pseudo-metallophyte and an emerging model to explore molecular basis of metal tolerance and hyperaccumulation. In this regard, understanding of interacting genes can be a crucial aspect as these interactions regulate several biological functions at molecular level in response to multiple signals. In this current study, we applied a weighted gene co-expression network analysis (WGCNA) on root and shoot RNA-seq data of A. halleri to predict the related scale-free organ specific co-expression networks, for the first time. A total of 19,653 genes of root and 18,081 genes of shoot were grouped into 14 modules and subjected to GO and KEGG enrichment analysis. "Photosynthesis" and "photosynthesis-antenna proteins" were identified as the most enriched and common pathway to both root and shoot. Whereas "glucosinolate biosynthesis," "autophagy," and "SNARE interactions in vesicular transport" were specific to root, and "circadian rhythm" was found to be enriched only in shoot. Later, hub and bottleneck genes were identified in each module by using cytoHubba plugin based on Cytoscape and scoring the relevance of each gene to the topology of the network. The modules with the most significant differential expression pattern across control and treatment (Cd-Zn treatment) were selected and their hub and bottleneck genes were screened to validate their possible involvement in heavy metal stress. Moreover, we combined the analysis of co-expression modules together with protein-protein interactions (PPIs), confirming some genes as potential candidates in plant heavy metal stress and as biomarkers. The results from this analysis shed the light on the pivotal functions to the hyperaccumulative trait of A. halleri, giving perspective to new paths for future research on this species.

RBCK1 deficiency is a rare congenital autoinflammatory disease that causes inflammatory disruption on the molecular level. This deficiency has three major clinical manifestations: increased sensitivity to bacterial infections, autoinflammation syndrome, and the accumulation of amylopectin in skeletal muscle. The amylopectinosis causes myopathy and cardiomyopathy. The pathogenesis of the disease is poorly investigated and may include unnoticed relationships. We performed gene expression analysis on patients with RBCK1 deficiency and three other autoinflammatory diseases. The identification of differentially expressed genes revealed a large number of downregulated genes that are involved in the activation of essential metabolic and immune pathways, including NF-kB and Pi3k-Akt-mTOR. Signaling pathways were analysed using the KEGG (Kyoto Encyclopedia of Genes and Genomes) and Gene Ontology resource. Predicted protein-protein interactions were retrieved from the STRING (Search Tool for the Retrieval of Interacting proteins database). Besides the primary involvement of RBCK1 in disease pathology, several downregulated pathways aggravate symptoms of myopathy, cardiomyopathy, and bacterial disease. The studied pathways may serve as new targets for the development of compensatory therapies for patients with RBCK1 deficiency. © 2022, Mathematical Biology and Bioinformatics. All rights reserved.

International audience; An increase in phosphorylation of the Tau protein is associated with Alzheimer's disease (AD) progression through unclear molecular mechanisms. In general, phosphorylation modifies the interaction of intrinsically disordered proteins, such as Tau, with other proteins; however, elucidating the structural basis of this regulation mechanism remains challenging. The bridging integrator-1 gene is an AD genetic determinant whose gene product, BIN1, directly interacts with Tau. The proline-rich motif recognized within a Tau(210-240) peptide by the SH3 domain of BIN1 (BIN1 SH3) is defined as 216PTPP219, and this interaction is modulated by phosphorylation. Phosphorylation of T217 within the Tau(210-240) peptide led to a 6-fold reduction in the affinity, while single phosphorylation at either T212, T231, or S235 had no effect on the interaction. Nonetheless, combined phosphorylation of T231 and S235 led to a 3-fold reduction in the affinity, although these phosphorylations are not within the BIN1 SH3-bound region of the Tau peptide. Using nuclear magnetic resonance (NMR) spectroscopy, these phosphorylations were shown to affect the local secondary structure and dynamics of the Tau(210-240) peptide. Models of the (un)phosphorylated peptides were obtained from molecular dynamics (MD) simulation validated by experimental data and showed compaction of the phosphorylated peptide due to increased salt bridge formation. This dynamic folding might indirectly impact the BIN1 SH3 binding by a decreased accessibility of the binding site. Regulation of the binding might thus not only be due to local electrostatic or steric effects from phosphorylation but also to the modification of the conformational properties of Tau.

Cellular function is based on protein–protein interactions. A large proportion of these interactions involves the binding of short linear motifs (SLiMs) by folded globular domains. These interactions are regulated by post-translational modifications, such as phosphorylation, that create and break motif binding sites or tune the affinity of the interactions. In addition, motif-based interactions are involved in targeting serine/threonine kinases and phosphatases to their substrate and contribute to the specificity of the enzymatic actions regulating which sites are phosphorylated. Here, we review how SLiM-based interactions assist in determining the specificity of serine/threonine kinases and phosphatases, and how phosphorylation, in turn, affects motif-based interactions. We provide examples of SLiM-based interactions that are turned on/off, or are tuned by serine/threonine phosphorylation and exemplify how this affects SLiM-based protein complex formation.

Pregnane x receptor (PXR) as a nuclear receptor is well-established in drug metabolism, however, it has pleiotropic functions in regulating inflammatory responses, glucose metabolism, and protects normal cells against carcinogenesis. Most studies focus on its transcriptional regulation, however, PXR can regulate gene expression at the translational level. Emerging evidences have shown that PXR has a broad protein-protein interaction network, by which is implicated in the cross signaling pathways. Furthermore, the interactions between PXR and some critical proteins (e.g., p53, Tip60, p300/CBP-associated factor) in DNA damage pathway highlight its potential roles in this field. A thorough understanding of how PXR maintains genome stability and prevents carcinogenesis will help clinical diagnosis and finally benefit patients. Meanwhile, due to the regulation of CYP450 enzymes CYP3A4 and multidrug resistance protein 1 (MDR1), PXR contributes to chemotherapeutic drug resistance. It is worthy of note that the co-factor of PXR such as RXRα, also has contributions to this process, which makes the PXR-mediated drug resistance more complicated. Although single nucleotide polymorphisms (SNPs) vary between individuals, the amino acid substitution on exon of PXR finally affects PXR transcriptional activity. In this review, we have summarized the updated mechanisms that PXR protects the human body against carcinogenesis, and major contributions of PXR with its co-factors have made on multidrug resistance. Furthermore, we have also reviewed the current promising antagonist and their clinic applications in reversing chemoresistance. We believe our review will bring insight into PXR-targeted cancer therapy, enlighten the future study direction, and provide substantial evidence for the clinic in future.

Peer reviewed: True, Acknowledgements: We thank Prapon Wilairat and Thanat Chookajorn for their comments on the scope of work during its initial stage. We thank David Ochou for additional insight into the use of the mirrortree approach and helpful discussion. We thank James Cotton for providing the assembly of Wolbachia of B. pahangi used in this analysis. We thank members of the Parasite Genomics team at the Wellcome Sanger Institute for their comments, discussions, and insights; in particular, we thank Matt Berriman, James Cotton, Eleanor Stanley, Martin Hunt, Hayley Bennett, and Anna Protasio. Computationally demanding data analyses were performed on high-performance computing facilities at Wellcome Sanger Institute and Khon Kaen University’s Office of Digital Technology., Infectious diseases caused by filarial nematodes are major health problems for humans and animals globally. Current treatment using anti-helminthic drugs requires a long treatment period and is only effective against the microfilarial stage. Most species of filarial nematodes harbor a specific strain of Wolbachia bacteria, which are essential for the survival, development, and reproduction of the nematodes. This parasite-bacteria obligate symbiosis offers a new angle for the cure of filariasis. In this study, we utilized publicly available genome data and putative protein sequences from seven filarial nematode species and their symbiotic Wolbachia to screen for protein-protein interactions that could be a novel target against multiple filarial nematode species. Genome-wide in silico screening was performed to predict molecular interactions based on co-evolutionary signals. We identified over 8,000 pairs of gene families that show evidence of co-evolution based on high correlation score and low false discovery rate (FDR) between gene families and obtained a candidate list that may be keys in filarial nematode-Wolbachia interactions. Functional analysis was conducted on these top-scoring pairs, revealing biological processes related to various signaling processes, adult lifespan, developmental control, lipid and nucleotide metabolism, and RNA modification. Furthermore, network analysis of the top-scoring genes with multiple co-evolving pairs suggests candidate genes in both Wolbachia and the nematode that may play crucial roles at the center of multi-gene networks. A number of the top-scoring genes matched well to known drug targets, suggesting a promising drug-repurposing strategy that could be applicable against multiple filarial nematode species.

Protein-protein interactions (PPIs) are essential to understanding biological pathways and their roles in development and disease. Computational tools have been successful at predicting PPIs in silico, but the lack of consistent and reliable frameworks for this task has led to network models that are difficult to compare and, overall, a low level of trust in the predicted PPIs. To better understand the underlying mechanisms underpinning these models, I designed B4PPI, an open-source framework for benchmarking that accounts for a range of biological and statistical pitfalls while facilitating reproducibility. I use B4PPI to shed light on the impact of network topology and understand how different algorithms deal with highly connected proteins. By studying functional genomics-based and sequence- based models (two of the most popular approaches) on human PPIs, I show their complementarity as the former performs best on lone proteins while the latter specialises in interactions involving hubs. I also show that algorithm design has little impact on performance with functional genomic data. I replicate these results between human and yeast data and demonstrate that models using functional genomics are better suited to PPI prediction across species. These analyses also highlight disparities in computing resources needed to train the prediction tools; some models run within seconds while others need hours. Longer runtimes require more energy and are responsible for more greenhouse gas emissions. Being able to quantify this impact is crucial as climate change profoundly affects nearly all aspects of life on earth, including human societies, economies and health. Various human activities are responsible for significant greenhouse gas emissions, including data centres and other sources of large-scale computation. Although many important scientific milestones have been achieved thanks to the development of high-performance computing, the resultant environmental impact has been underappreciated. I present a methodological framework to estimate the carbon footprint of any computational task in a standardised and reliable way, and metrics to contextualise greenhouse gas emissions are defined. I develop a freely available online tool, Green Algorithms, which enables a user to estimate and report the carbon footprint of their computation (available at www.green-algorithms.org). The tool easily integrates with computational processes as it requires minimal information and does not interfere with existing code while also accounting for a broad range of hardware configurations. Finally, I quantify the greenhouse gas emissions of algorithms used for particle physics simulations, weather forecasts, natural language processing and a wide range of bioinformatic tools. With rapidly increasing amounts of sequence and functional genomics data, this work on protein interactions provides a systematic foundation for future construction, comparison and application of PPI networks. It also integrates essential metrics of environmental efficiency developed by the Green Algorithms project, a simple generalisable framework and a freely available tool to quantify the carbon footprint of nearly any computation. This work also elucidates the carbon footprint of common analyses in bioinformatics and provides recommendations to empower scientists to move toward greener research.

Nutlin-3a is a reversible inhibitor of the p53/MDM2 interaction. We have synthesized the derivative Nutlin-3a-aa bearing an additional exocyclic methylene group in the piperazinone moiety. Nutlin-3a-aa is more active than Nutlin-3a against purified wild-type MDM2, and is more effective at increasing p53 levels and releasing transcription of p53 target genes from MDM2-induced repression. X-ray analysis of wild-type MDM2-bound Nutlin-3a-aa indicated that the orientation of its modified piperazinone ring was altered in comparison to the piperazinone ring of MDM2-bound Nutlin-3a, with the exocyclic methylene group of Nutlin-3a-aa pointing away from the protein surface. Our data point to the introduction of exocyclic methylene groups as a useful approach by which to tailor the conformation of bioactive molecules for improved biological activity. This work was generously supported by the Deutsche Forschungsgemeinschaft (BE 4572/3-1 to T.B.). We extend our thanks to Barbara Klüver, Katrin Eckhardt, Nadiya Brovchenko, and Domenique Herbstritt for experimental support. Parts of the data described in this manuscript have been published in the dissertation of Florian Nietzold (Leipzig University, 2019).31 In addition, this work was financially supported by the National Science Centre, Poland (NCN) under Grant Symphony 2014/12/W/NZ1/00457 (to T.A.H). We thank HZB for the allocation of synchrotron radiation beamtime. We acknowledge the MCB Structural Biology Core Facility (supported by the TEAM TECH CORE FACILITY/2017-4/6 grant from the Foundation for Polish Science) for valuable support. Open Access funding enabled and organized by Projekt DEAL.

SARS-CoV-2, a novel betacoronavirus strain, has caused a pandemic that has claimed the lives of nearly 6.7M people worldwide. Vaccines and medicines are being developed around the world to reduce the disease spread, fatality rates, and control the new variants. Understanding the protein-protein interaction mechanism of SARS-CoV-2 in humans, and their comparison with the previous SARS-CoV and MERS strains, is crucial for these efforts. These interactions might be used to assess vaccination effectiveness, diagnose exposure, and produce effective biotherapeutics. Here, we present the HuCoPIA database, which contains approximately 100,000 protein-protein interactions between humans and three strains (SARS-CoV-2, SARS-CoV, and MERS) of betacoronavirus. The interactions in the database are divided into common interactions between all three strains and those unique to each strain. It also contains relevant functional annotation information of human proteins. The HuCoPIA database contains SARS-CoV-2 (41,173), SARS-CoV (31,997), and MERS (26,862) interactions, with functional annotation of human proteins like subcellular localization, tissue-expression, KEGG pathways, and Gene ontology information. We believe HuCoPIA will serve as an invaluable resource to diverse experimental biologists, and will help to advance the research in better understanding the mechanism of betacoronaviruses.

Protein–protein interactions (PPIs) mediate numerous essential functions and regulatory events in living organisms. The physical interactome of a protein can be abnormally altered in response to external and internal cues, thus modulating cell physiology and contributing to human disease. In particular, neurodegenerative diseases due to the accumulation of aberrantly folded and aggregated proteins may lead to alterations in protein interactomes. Identifying changes in the interactomes of normal and disease states of proteins could help to understand molecular disease mechanisms, but current interactomics methods are limited in the ability to pinpoint structure-specific PPIs and their interaction interfaces on a proteome-wide scale. Here, we adapted limited proteolysis–mass spectrometry (LiP–MS) to systematically identify putative structure-specific PPIs by probing protein structural alterations within cellular extracts upon treatment with specific structural states of a given protein. We demonstrate the feasibility of our method to detect well-characterized PPIs, including antibody–target protein interactions and interactions with membrane proteins, and show that it pinpoints PPI interfaces. We then applied the LiP–MS approach to study the structure-specific interactors of the Parkinson’s disease hallmark protein alpha-synuclein (aSyn). We identified several previously known interactors of both aSyn monomer and amyloid fibrils and provide a resource of novel putative structure-specific interactors for further studies. This approach is applicable to identify structure-specific interactomes of any protein, including posttranslationally modified and unmodified, or metabolite-bound and unbound structural states of proteins.

Almost all the cellular processes in a living system are controlled by proteins: They regulate gene expression, catalyze chemical reactions, transport small molecules across membranes, and transmit signal across membranes. Even, a viral infection is often initiated through virus-host protein interactions. Protein-protein interactions (PPIs) are the physical contacts between two or more proteins and they represent complex biological functions. Nowadays, PPIs have been used to construct PPI networks to study complex pathways for revealing the functions of unknown proteins. Scientists have used PPIs to find the molecular basis of certain diseases and also some potential drug targets. In this review, we will discuss how PPI networks are essential to understand the molecular basis of virus-host relationships and several databases which are dedicated to virus-host interaction studies. Here, we present a short but comprehensive review on PPIs, including the experimental and computational methods of finding PPIs, the databases dedicated to virus-host PPIs, and the associated various applications in protein interaction networks of some lethal viruses with their hosts.

Pyridoxal 5′-phosphate (PLP), the active form of vitamin B6, serves as a cofactor for scores of B6-dependent (PLP-dependent) enzymes involved in many cellular processes. One such B6 enzyme is dopa decarboxylase (DDC), which is required for the biosynthesis of key neurotransmitters, e.g., dopamine and serotonin. PLP-dependent enzymes are biosynthesized as apo-B6 enzymes and then converted to the catalytically active holo-B6 enzymes by Schiff base formation between the aldehyde of PLP and an active site lysine of the protein. In eukaryotes, PLP is made available to the B6 enzymes through the activity of the B6-salvage enzymes, pyridoxine 5′-phosphate oxidase (PNPO) and pyridoxal kinase (PLK). To minimize toxicity, the cell keeps the content of free PLP (unbound) very low through dephosphorylation and PLP feedback inhibition of PNPO and PLK. This has led to a proposed mechanism of complex formation between the B6-salvage enzymes and apo-B6 enzymes prior to the transfer of PLP, although such complexes are yet to be characterized at the atomic level, presumably due to their transient nature. A computational study, for the first time, was used to predict a likely PNPO and DDC complex, which suggested contact between the allosteric PLP tight-binding site on PNPO and the active site of DDC. Using isothermal calorimetry and/or surface plasmon resonance, we also show that PNPO binds both apoDDC and holoDDC with dissociation constants of 0.93 ± 0.07 μM and 2.59 ± 0.11 μM, respectively. Finally, in the presence of apoDDC, the tightly bound PLP on PNPO is transferred to apoDDC, resulting in the formation of about 35% holoDDC.

Data and code for the case studies reported in our publication: https://doi.org/10.1101/2022.09.02.506350. The data are divided in subfolder for each case study presented in the publication. They are provided as tar.gz files and each of them contains its own readme file with the command lines used to reproduce the analyses

Eukaryotic DNA mismatch repair (MMR) initiates through mispair recognition by the MutS homologs Msh2-Msh6 and Msh2-Msh3 and subsequent recruitment of the MutL homologs Mlh1-Pms1 (human MLH1-PMS2). In bacteria, MutL is recruited by interactions with the connector domain of one MutS subunit and the ATPase and core domains of the other MutS subunit. Analysis of the S. cerevisiae and human homologs have only identified an interaction between the Msh2 connector domain and Mlh1. Here we investigated whether a conserved Msh6 ATPase/core domain-Mlh1 interaction and an Msh2-Msh6 interaction with Pms1 also act in MMR. Mutations in MLH1 affecting interactions with both the Msh2 and Msh6 interfaces caused MMR defects, whereas equivalent pms1 mutations did not cause MMR defects. Mutant Mlh1-Pms1 complexes containing Mlh1 amino acid substitutions were defective for recruitment to mispaired DNA by Msh2-Msh6, did not support MMR in reconstituted Mlh1-Pms1-dependent MMR reactions in vitro, but were proficient in Msh2-Msh6-independent Mlh1-Pms1 endonuclease activity. These results indicate that Mlh1, the common subunit of the Mlh1-Pms1, Mlh1-Mlh2, and Mlh1-Mlh3 complexes, but not Pms1, is recruited by Msh2-Msh6 through interactions with both of its subunits.

The ongoing coronavirus disease 2019 (COVID-19) pandemic has highlighted the need to better understand virus-host interactions. We developed a network-based algorithm that expands the SARS-CoV-2-host protein interaction network and identifies host targets that modulate viral infection. To disrupt the SARS-CoV-2 interactome, we systematically probed for potent compounds that selectively target the identified host proteins with high expression in cells relevant to COVID-19. We experimentally tested seven chemical inhibitors of the identified host proteins for modulation of SARS-CoV-2 infection in human cells that express ACE2 and TMPRSS2. Inhibition of the epigenetic regulators bromodomain-containing protein 4 (BRD4) and histone deacetylase 2 (HDAC2), along with ubiquitin specific peptidase (USP10), enhanced SARS-CoV-2 infection. Such proviral effect was observed upon treatment with compounds JQ1, vorinostat, romidepsin, and spautin-1, when measured by cytopathic effect and validated by viral RNA assays, suggesting that HDAC2, BRD4 and USP10 host proteins have antiviral functions. Mycophenolic acid and merimepodib, two inhibitors of inosine monophosphate dehydrogenase (IMPDH 1 and IMPDH 2), showed modest antiviral effects with no toxicity in mock-infected control cells. The network-based approach enables systematic identification of host-targets that selectively modulate the SARS-CoV-2 interactome, as well as reveal novel chemical tools to probe virus-host interactions that regulate virus infection.SynopsisViruses exploit host machinery and therefore it is important to understand the virus-host dependencies to gain better insight of the key regulators of viral infection.Using a context-specific SARS-COV-2 PPI network, a computational framework was developed to identify host modulators of viral infection.Chromatin modifying host proteins HDAC2 and BRD4, along with deubiquitinating enzyme USP10, act as antiviral proteins.IMPDH inhibitors mycophenolic acid and merimipodib showed modest antiviral response to SARS-COV-2 infection, and no toxic effects.Cell context specificity is a critical factor when identifying selective modulators of viral infection and potential antiviral therapeutics.Topology-based network models cannot distinguish between host-proteins, the inhibition of which leads to either virus suppressive or enhancing effects.

Single-molecule force spectroscopy provides access to the mechanics of biomolecules. Recently, magnetic and laser optical tweezers were applied in the studies of chaperones and their interaction with protein clients. Various aspects of the chaperone–client interactions can be revealed based on the mechanical probing strategies. First, when a chaperone is probed under load, one can examine the inner workings of the chaperone while it interacts with and works on the client protein. Second, when protein clients are probed under load, the action of chaperones on folding clients can be studied in great detail. Such client folding studies have given direct access to observing actions of chaperones in real-time, like foldase, unfoldase, and holdase activity. In this review, we introduce the various single molecule mechanical techniques and summarize recent single molecule mechanical studies on heat shock proteins, chaperone-mediated folding on the ribosome, SNARE folding, and studies of chaperones involved in the folding of membrane proteins. An outlook on significant future developments is given., This work was supported by the German Research Foundation, Sonderforschungsbereich 1035, Projektnummer 201302640, Project A5 (to M.R.). G.Z. was supported by the Research Grant from the Grant Provided by Slovak Research and Development Agency (Grant No. APVV-18–0285), the Slovak Grant Agency VEGA No. 1/0024/22, KEGA No. 005UPJŠ-4/2021, and the Project BioPickmol, ITMS2014+: 313011AUW6 supported by the Operational Programme Integrated Infrastructure, funded by the ERDF.

Innate immune responses, including the production of type I and III interferons, play a crucial role in the first line of defense against RSV infection. However, only a poor induction of type I IFNs is observed during RSV infection, suggesting that RSV has evolved mechanisms to prevent type I IFN expression by the infected host cell. Human respiratory syncytial virus (RSV) is the leading cause of severe acute lower respiratory tract infections in infants worldwide. Nonstructural protein NS1 of RSV modulates the host innate immune response by acting as an antagonist of type I and type III interferon (IFN) production and signaling in multiple ways. Likely, NS1 performs this function by interacting with different host proteins. In order to obtain a comprehensive overview of the NS1 interaction partners, we performed three complementary protein-protein interaction screens, i.e., BioID, MAPPIT, and KISS. To closely mimic a natural infection, the BioID proximity screen was performed using a recombinant RSV in which the NS1 protein is fused to a biotin ligase. Remarkably, MED25, a subunit of the Mediator complex, was identified in all three performed screening methods as a potential NS1-interacting protein. We confirmed the interaction between MED25 and RSV NS1 by coimmunoprecipitation, not only upon overexpression of NS1 but also with endogenous NS1 during RSV infection. We also demonstrate that the replication of RSV can be enhanced in MED25 knockout A549 cells, suggesting a potential antiviral role of MED25 during RSV infection. Mediator subunits function as transcriptional coactivators and are involved in transcriptional regulation of their target genes. Therefore, the interaction between RSV NS1 and cellular MED25 might be beneficial for RSV during infection by affecting host transcription and the host immune response to infection. IMPORTANCE Innate immune responses, including the production of type I and III interferons, play a crucial role in the first line of defense against RSV infection. However, only a poor induction of type I IFNs is observed during RSV infection, suggesting that RSV has evolved mechanisms to prevent type I IFN expression by the infected host cell. A unique RSV protein, NS1, is largely responsible for this effect, probably through interaction with multiple host proteins. A better understanding of the interactions that occur between RSV NS1 and host proteins may help to identify targets for an effective antiviral therapy. We addressed this question by performing three complementary protein-protein interaction screens and identified MED25 as an RSV NS1-interacting protein. We propose a role in innate anti-RSV defense for this Mediator complex subunit.

Orsellinic acid (OA) derivatives are produced by filamentous fungi using nonreducing polyketide synthases (nrPKSs). The chain-releasing thioesterase (TE) domains of such nrPKSs were proposed to also catalyze dimerization to yield didepsides, such as lecanoric acid. Here, we use combinatorial domain exchanges, domain dissections and reconstitutions to reveal that the TE domain of the lecanoric acid synthase Preu6 of Preussia isomera must collaborate with the starter acyl transferase (SAT) domain from the same nrPKS. We show that artificial SAT-TE fusion proteins are highly effective catalysts and reprogram the ketide homologation chassis to form didepsides. We also demonstrate that dissected SAT and TE domains of Preu6 physically interact, and SAT and TE domains of OA-synthesizing nrPKSs may co-evolve. Our work highlights an unexpected domain–domain interaction in nrPKSs that must be considered for the combinatorial biosynthesis of unnatural didepsides, depsidones, and diphenyl ethers.

The severity of the COVID-19 pandemic has necessitated the search for drugs against SARS-CoV-2. In this study, we explored via in silico approaches myxobacterial secondary metabolites against various receptor-binding regions of SARS-CoV-2 spike which are responsible in recognition and attachment to host cell receptors mechanisms, namely ACE2, GRP78, and NRP1. In general, cyclic depsipeptide chondramides conferred high affinities toward the spike RBD, showing strong binding to the known viral hot spots Arg403, Gln493 and Gln498 and better selectivity compared to most host cell receptors studied. Among them, chondramide C3 (1) exhibited a binding energy which remained relatively constant when docked against most of the spike variants. Chondramide C (2) on the other hand exhibited strong affinity against spike variants identified in the United Kingdom (N501Y), South Africa (N501Y, E484K, K417N) and Brazil (N501Y, E484K, K417T). Chondramide C6 (9) showed highest BE towards GRP78 RBD. Molecular dynamics simulations were also performed for chondramides 1 and 2 against SARS-CoV-2 spike RBD of the Wuhan wild-type and the South African variant, respectively, where resulting complexes demonstrated dynamic stability within a 120-ns simulation time. Protein-protein binding experiments using HADDOCK illustrated weaker binding affinity for complexed chondramide ligands in the RBD against the studied host cell receptors. The chondramide derivatives in general possessed favorable pharmacokinetic properties, highlighting their potential as prototypic anti-COVID-19 drugs limiting viral attachment and possibly minimizing viral infection. Communicated by Ramaswamy H. Sarma

Macrocyclic compounds are an attractive class of therapeutic ligands against challenging targets, such as protein-protein interactions. However, the development of macrocycles as drugs is hindered by the lack of large combinatorial macrocyclic libraries, which are cumbersome, expensive, and time consuming to make, screen, and deconvolute. Here, we established a strategy for synthesizing and screening combinatorial libraries on a picomolar scale by using acoustic droplet ejection to combine building blocks at nanoliter volumes, which reduced the reaction volumes, reagent consumption, and synthesis time. As a proof-of-concept, we assembled a 2700-member target-focused macrocyclic library that we could subsequently assay in the same microtiter synthesis plates, saving the need for additional transfers and deconvolution schemes. We screened the library against the MDM2-p53 protein-protein interaction and generated micromolar and sub-micromolar inhibitors. Our approach based on acoustic liquid transfer provides a general strategy for the development of macrocycle ligands.

Talin is a cell adhesion molecule that is indispensable for the development and function of multicellular organisms. Despite its central role for many cell biological processes, suitable methods to investigate the nanoscale organization of talin in its native environment are missing. Here, we overcome this limitation by combining single‐molecule resolved PAINT (points accumulation in nanoscale topography) imaging with the IRIS (image reconstruction by integrating exchangeable single‐molecule localization) approach, enabling the quantitative analysis of genetically unmodified talin molecules in cells. We demonstrate that a previously reported peptide can be utilized to specifically label the two major talin isoforms expressed in mammalian tissues with a localization precision of, The PIPKIγ‐peptide‐PAINT approach is introduced in this study to enable quantitative investigation of the cell adhesion protein talin with single‐molecule resolution in cells. The technique does not require genetic modifications and allows the analysis of endogenously expressed molecules. The first application reveals atypical adhesion structures in differentiating mesenchymal stem cells.

Structural maintenance of chromosomes flexible hinge domain-containing 1 (SMCHD1) is an epigenetic regulator that mediates gene expression silencing at targeted sites across the genome. Our current understanding of SMCHD1's molecular mechanism, and how substitutions within SMCHD1 lead to the diseases, facioscapulohumeral muscular dystrophy (FSHD) and Bosma arhinia microphthalmia syndrome (BAMS), are only emerging. Recent structural studies of its two component domains — the N-terminal ATPase and C-terminal SMC hinge — suggest that dimerization of each domain plays a central role in SMCHD1 function. Here, using biophysical techniques, we demonstrate that the SMCHD1 ATPase undergoes dimerization in a process that is dependent on both the N-terminal UBL (Ubiquitin-like) domain and ATP binding. We show that neither the dimerization event, nor the presence of a C-terminal extension past the transducer domain, affect SMCHD1's in vitro catalytic activity as the rate of ATP turnover remains comparable to the monomeric protein. We further examined the functional importance of the N-terminal UBL domain in cells, revealing that its targeted deletion disrupts the localization of full-length SMCHD1 to chromatin. These findings implicate UBL-mediated SMCHD1 dimerization as a crucial step for chromatin interaction, and thereby for promoting SMCHD1-mediated gene silencing.

How do proteins interact in the cellular environment? Which interactions stabilize liquid–liquid phase separated condensates? Are the concepts, which have been developed for specific protein complexes also applicable to higher-order assemblies? Recent discoveries prompt for a universal framework for protein interactions, which can be applied across the scales of protein communities. Here, we discuss how our views on protein interactions have evolved from rigid structures to conformational ensembles of proteins and discuss the open problems, in particular related to biomolecular condensates. Protein interactions have evolved to follow changes in the cellular environment, which manifests in multiple modes of interactions between the same partners. Such cellular context-dependence requires multiplicity of binding modes (MBM) by sampling multiple minima of the interaction energy landscape. We demonstrate that the energy landscape framework of protein folding can be applied to explain this phenomenon, opening a perspective toward a physics-based, universal model for cellular protein behaviors.

Analysis and prediction of amino acid residues controlling homotypic transmembrane domain interactions.

Serovars of the genus Salmonella primarily evolved as gastrointestinal pathogens in a wide range of hosts. Some serotypes later evolved further, adopting a more invasive lifestyle in a narrower host range associated with systemic infections. A system-level knowledge of these pathogens could identify the complex adaptations associated with the evolution of serovars with distinct pathogenicity, host range, and risk to human health. This promises to aid the design of interventions and serve as a knowledge base in the Salmonella research community. Here, we present SalmoNet2, a major update to SalmoNet1, the first multilayered interaction resource for Salmonella strains, containing protein-protein, transcriptional regulatory, and enzyme-enzyme interactions. The new version extends the number of Salmonella networks from 11 to 20. We now include a strain from the second species in the Salmonella genus, a strain from the Salmonella enterica subspecies arizonae and additional strains of importance from the subspecies enterica, including S. Typhimurium strain D23580, an epidemic multidrug-resistant strain associated with invasive nontyphoidal salmonellosis (iNTS). The database now uses strain specific metabolic models instead of a generalized model to highlight differences between strains. The update has increased the coverage of high-quality protein-protein interactions, and enhanced interoperability with other computational resources by adopting standardized formats. The resource website has been updated with tutorials to help researchers analyze their Salmonella data using molecular interaction networks from SalmoNet2. SalmoNet2 is accessible at http://salmonet.org/. IMPORTANCE Multilayered network databases collate interaction information from multiple sources, and are powerful both as a knowledge base and subject of analysis. Here, we present SalmoNet2, an integrated network resource containing protein-protein, transcriptional regulatory, and metabolic interactions for 20 Salmonella strains. Key improvements to the update include expanding the number of strains, strain-specific metabolic networks, an increase in high-quality protein-protein interactions, community standard computational formats to help interoperability, and online tutorials to help users analyze their data using SalmoNet2. ispartof: mSystems vol:7 issue:4 pages:e0149321- ispartof: location:United States status: published

Signal transduction cascades efficiently transmit chemical and/or physical signals from the extracellular environment to intracellular compartments, thereby eliciting an appropriate cellular response. Most often, these signaling processes are mediated by specific protein-protein interactions involving hundreds of different receptors, enzymes, transcription factors, and signaling, adaptor and scaffolding proteins. Among them, 14-3-3 proteins are a family of highly conserved scaffolding molecules expressed in all eukaryotes, where they modulate the function of other proteins, primarily in a phosphorylation-dependent manner. Through these binding interactions, 14-3-3 proteins participate in key cellular processes, such as cell-cycle control, apoptosis, signal transduction, energy metabolism, and protein trafficking. To date, several hundreds of 14-3-3 binding partners have been identified, including protein kinases, phosphatases, receptors and transcription factors, which have been implicated in the onset of various diseases. As such, 14-3-3 proteins are promising targets for pharmaceutical interventions. However, despite intensive research into their protein-protein interactions, our understanding of the molecular mechanisms whereby 14-3-3 proteins regulate the functions of their binding partners remains insufficient. This review article provides an overview of the current state of the art of the molecular mechanisms whereby 14-3-3 proteins regulate their binding partners, focusing on recent structural studies of 14-3-3 protein complexes.

[Restricted], Cambridge Trust

During viral cell entry, the spike protein of SARS-CoV-2 binds to the α1-helix motif of human angiotensin-converting enzyme 2 (ACE2). Thus, alpha-helical peptides mimicking this motif may serve as inhibitors of viral cell entry. For this purpose, we employed the rigidified diproline-derived module ProM-5 to induce α-helicity in short peptide sequences inspired by the ACE2 α1-helix. Starting with Ac-QAKTFLDKFNHEAEDLFYQ-NH2 as a relevant section of α1, a series of peptides, N-capped with either Ac-βHAsp-[ProM-5] or Ac-βHAsp-PP, were prepared and their α-helicities were investigated. While ProM-5 clearly showed a pronounced effect, an even increased degree of helicity (up to 63 %) was observed in sequences in which non-binding amino acids were replaced by alanine. The binding affinities of the peptides towards the spike protein, as determined by means of microscale thermophoresis (MST), revealed only a subtle influence of the α-helical content and, noteworthy, led to the identification of an Ac-βHAsp-PP-capped peptide displaying a very strong binding affinity (KD=62 nM).

SETD3 was recently identified as the histidine methyltransferase responsible for N 3 -methylation of His73 of β-actin in humans. Overexpression of SETD3 is associated with several diseases, including breast cancer. Here, we report a development of actin-based peptidomimetics as inhibitors of recombinantly expressed human SETD3. Substitution of His73 by simple natural and unnatural amino acids led to selected β-actin peptides with high potency against SETD3 in MALDI-TOF MS assays. The selenomethionine-containing β-actin peptide was found to be the most potent SETD3 inhibitor (IC 50 = 161 nM). Supporting our inhibition assays, a combination of computational docking and molecular dynamics simulations revealed that the His73 binding pocket for β-actin in SETD3 is rigid and accommodates the inhibitor peptides with similar binding modes. Collectively, our work demonstrates that actin-based peptidomimetics can act as potent SETD3 inhibitors and provide a basis for further development of highly potent and selective inhibitors of SETD3.

The aim of this study was to investigate the mechanisms behind protein-protein interactions in a co-precipitate of whey protein isolate (WPI) and pea protein isolate (PPI). A co-precipitate and blend, consisting of 80% WPI and 20% PPI, were compared. Covalent disulphide interactions were studied by blocking of free thiols with N-Ethylmaleimide (NEM), while electrostatic interactions were studied in systems with 0.5 m NaCl and hydrophobic interactions with 0.2% SDS. Protein solubility, stability and secondary, tertiary and quaternary protein structures were analysed. Co-precipitation did not introduce different protein-protein interactions than the direct blending of proteins. SDS affected solubility (P < 0.05), secondary and tertiary structure. However, the effects of NEM and NaCl were significant greater (P < 0.05) on the same parameters and thermal stability, especially when combined (P < 0.01). Thus, the protein-protein interactions in a whey-pea co-precipitate and protein blend consisted of disulphide bonds and electrostatic interactions.

With the increased focus on intrinsically disordered proteins (IDPs) and their large interactomes, the question about their specificity — or more so on their multispecificity — arise. Here we recapitulate how specificity and multispecificity are quantified and address through examples if IDPs in this respect differ from globular proteins. The conclusion is that quantitatively, globular proteins and IDPs are similar when it comes to specificity. However, compared with globular proteins, IDPs have larger interactome sizes, a phenomenon that is further enabled by their flexibility, repetitive binding motifs and propensity to adapt to different binding partners. For IDPs, this adaptability, interactome size and a higher degree of multivalency opens for new interaction mechanisms such as facilitated exchange through trimer formation and ultra-sensitivity via threshold effects and ensemble redistribution. IDPs and their interactions, thus, do not compromise the definition of specificity. Instead, it is the sheer size of their interactomes that complicates its calculation. More importantly, it is this size that challenges how we conceptually envision, interpret and speak about their specificity.

In peptidotriazolamers every second peptide bond is replaced by a 1H-1,2,3-triazole. Such foldamers are expected to bridge the gap in molecular weight between small-molecule drugs and protein-based drugs. Amyloid beta (Abeta) aggregates play an important role in Alzheimer's disease. We studied the impact of amide bond replacements by 1,4-disubstituted 1H-1,2,3-triazoles on the inhibitory activity of the aggregation "hot spots" K16 LVFF20 and G39 VVIA42 in Abeta(1-42). We found that peptidotriazolamers act as modulators of the Abeta(1-42) oligomerization. Some peptidotriazolamers are able to interfere with the formation of toxic early Abeta oligomers, depending on the position of the triazoles, which is also supported by computational studies. Preliminary in vitro results demonstrate that a highly active peptidotriazolamer is also able to cross the blood-brain-barrier. © 2021 The Authors. ChemPlusChem published by Wiley-VCH GmbH.

COVID-19 pandemic defined a worldwide health crisis into a humanitarian crisis. Amid this global emergency, human civilization is under enormous strain since no proper therapeutic method is discovered yet. A wave of research effort has been put toward the invention of therapeutics and vaccines against COVID-19. Contrarily, the spread of this fatal virus has already infected millions of people and claimed many lives all over the world. Computational biology can attempt to understand the protein–protein interactions between the viral protein and host protein. Therefore, potential viral–host protein interactions can be identified which is known as crucial information toward the discovery of drugs. In this study, an approach was presented for predicting novel interactions from maximal biclusters. Additionally, the predicted interactions are verified from biological perspectives. For this, a study was conducted on the gene ontology and KEGG-pathway in relation to the newly predicted interactions.

Severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) has caused substantially more infections, deaths, and economic disruptions than the 2002‐2003 SARS‐CoV. The key to understanding SARS‐CoV‐2's higher infectivity lies partly in its host receptor recognition mechanism. Experiments show that the human angiotensin converting enzyme 2 (ACE2) protein, which serves as the primary receptor for both CoVs, binds to the receptor binding domain (RBD) of CoV‐2's spike protein stronger than SARS‐CoV's spike RBD. The molecular basis for this difference in binding affinity, however, remains unexplained from X‐ray structures. To go beyond insights gained from X‐ray structures and investigate the role of thermal fluctuations in structure, we employ all‐atom molecular dynamics simulations. Microseconds‐long simulations reveal that while CoV and CoV‐2 spike‐ACE2 interfaces have similar conformational binding modes, CoV‐2 spike interacts with ACE2 via a larger combinatorics of polar contacts, and on average, makes 45% more polar contacts. Correlation analysis and thermodynamic calculations indicate that these differences in the density and dynamics of polar contacts arise from differences in spatial arrangements of interfacial residues, and dynamical coupling between interfacial and non‐interfacial residues. These results recommend that ongoing efforts to design spike‐ACE2 peptide blockers will benefit from incorporating dynamical information as well as allosteric coupling effects.

Motivation The crucial role of protein interactions and the difficulty in characterizing them experimentally strongly motivates the development of computational approaches for structural prediction. Even when protein–protein docking samples correct models, current scoring functions struggle to discriminate them from incorrect decoys. The previous incorporation of conservation and coevolution information has shown promise for improving protein–protein scoring. Here, we present a novel strategy to integrate atomic-level evolutionary information into different types of scoring functions to improve their docking discrimination. Results We applied this general strategy to our residue-level statistical potential from InterEvScore and to two atomic-level scores, SOAP-PP and Rosetta interface score (ISC). Including evolutionary information from as few as 10 homologous sequences improves the top 10 success rates of individual atomic-level scores SOAP-PP and Rosetta ISC by 6 and 13.5 percentage points, respectively, on a large benchmark of 752 docking cases. The best individual homology-enriched score reaches a top 10 success rate of 34.4%. A consensus approach based on the complementarity between different homology-enriched scores further increases the top 10 success rate to 40%. Availability and implementation All data used for benchmarking and scoring results, as well as a Singularity container of the pipeline, are available at http://biodev.cea.fr/interevol/interevdata/. Supplementary information Supplementary data are available at Bioinformatics online.

Wenwei Nong,1,* Liping Ma,2,* Biyang Lan,1 Ning Liu,1 Hongzhi Yang,1 Xiaoxia Lao,2 Qiaomei Deng,2 Zhihu Huang2 1Department of General Surgery, Affiliated Minzu Hospital of Guangxi Medical University, Nanning, People’s Republic of China; 2Department of Clinical Laboratory, Affiliated Minzu Hospital of Guangxi Medical University, Nanning, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhihu HuangAffiliated Minzu Hospital of Guangxi Medical University, Nanning, People’s Republic of ChinaEmail hoftiger@126.comBackground: Hepatitis B virus infection co-occurs in 33% of individuals with hepatocellular carcinoma worldwide. However, the molecular link between hepatitis B virus and hepatocellular carcinoma is unknown. Thus, we aimed to elucidate molecular linkages underlying pathogenesis through in-depth data mining analysis.Materials and Methods: Differentially expressed genes were identified from patients with chronic hepatitis B virus infection, hepatocellular carcinoma, or both. Gene set enrichment analysis revealed signaling pathways involving differentially expressed genes. Protein-protein interaction networks, protein crosstalk, and enrichment were analyzed to determine whether differentially expressed gene products might serve as a bridge from hepatitis B virus infection to hepatocellular carcinoma pathogenesis. Prognostic potential and transcriptional and post-transcriptional regulators of bridge genes were also examined.Results: We identified vital bridge factors in hepatitis B virus infection-associated hepatocellular carcinoma. Differentially expressed genes were clustered into modules based on relative protein function. Signaling pathways associated with cancer, inflammation, immune system, and microenvironment showed significant crosstalk between modules. Thirty-two genes were dysregulated in hepatitis B virus infection-mediated hepatocellular carcinoma. CPEB3, RAB26, SLCO1B1, ST3GAL6 and XK had higher connectivity in the modular network, suggesting significant associations with survival. CDC20 and NUP107 were identified as driver genes as well as markers of poor prognosis.Conclusion: Our results suggest that the sustained inflammatory environment created by hepatitis B virus infection is a risk factor for hepatocellular carcinoma. The identification of hepatitis B virus infection-related hepatocellular carcinoma bridge genes provides testable hypotheses about the pathogenesis of hepatocellular carcinoma.Keywords: signaling pathways, molecular processes, protein-protein interactions, chronic hepatitis B virus infection, hepatocellular carcinoma

Plants rapidly respond to environmental fluctuations through coordinated, multi-scalar regulation, enabling complex reactions despite their inherently sessile nature. In particular, protein post-translational signaling and protein–protein interactions combine to manipulate cellular responses and regulate plant homeostasis with precise temporal and spatial control. Understanding these proteomic networks are essential to addressing ongoing global crises, including those of food security, rising global temperatures, and the need for renewable materials and fuels. Technological advances in mass spectrometry-based proteomics are enabling investigations of unprecedented depth, and are increasingly being optimized for and applied to plant systems. This review highlights recent advances in plant proteomics, with an emphasis on spatially and temporally resolved analysis of post-translational modifications and protein interactions. It also details the necessity for generation of a comprehensive plant cell atlas while highlighting recent accomplishments within the field.

Among current novel druggable targets, protein–protein interactions (PPIs) are of considerable and growing interest. Diacylglycerol kinase α (DGKα) interacts with focal adhesion kinase (FAK) band 4.1-ezrin-radixin-moesin (FERM) domain to induce the phosphorylation of FAK Tyr397 site and promotes the malignant progression of esophageal squamous cell carcinoma (ESCC) cells. Chrysin is a multi-functional bioactive flavonoid, and possesses potential anticancer activity, whereas little is known about the anticancer activity and exact molecular mechanisms of chrysin in ESCC treatment. In this study, we found that chrysin significantly disrupted the DGKα/FAK signalosome to inhibit FAK-controlled signaling pathways and the malignant progression of ESCC cells both in vitro and in vivo, whereas produced no toxicity to the normal cells. Molecular validation specifically demonstrated that Asp435 site in the catalytic domain of DGKα contributed to chrysin-mediated inhibition of the assembly of DGKα/FAK complex. This study has illustrated DGKα/FAK complex as a target of chrysin for the first time, and provided a direction for the development of natural products-derived PPIs inhibitors in tumor treatment., Graphical abstract Chrysin disrupted the assembly of diacylglycerol kinase α (DGKα)/focal adhesion kinase (FAK) signalosome via interacting with the Asp 435 site of DGKα and subsequently inhibited the activation of FAK/AKT pathway to mediate its antitumor effect in esophageal squamous cell carcinoma cells.Image 1

To date, most research into the inhibition of oncogenic transcriptional regulator, Activator Protein 1 (AP-1), has focused on heterodimers of cJun and cFos. However, the Fra1 homologue remains an important cancer target. Here we describe library design coupled with computational and intracellular screening as an effective methodology to derive an antagonist that is selective for Fra1 relative to Jun counterparts. To do so the isCAN computational tool was used to rapidly screen >75 million peptide library members, narrowing the library size by >99.8% to one accessible to intracellular PCA selection. The resulting 131 072-member library was predicted to contain high quality binders with both a high likelihood of target engagement, while simultaneously avoiding homodimerization and off-target interaction with Jun homologues. PCA screening was next performed to enrich those members that meet these criteria. In particular, optimization was achieved via inclusion of options designed to generate the potential for compromised intermolecular contacts in both desired and non-desired species. This is an often-overlooked prerequisite in the conflicting design requirement of libraries that must be selective for their target in the context of a range of alternative potential interactions. Here we demonstrate that specificity is achieved via a combination of both hydrophobic and electrostatic contacts as exhibited by the selected peptide (Fra1W). In vitro analysis of the desired Fra1–Fra1W interaction further validates high Fra1 affinity (917 nM) yet selective binding relative to Fra1W homodimers or affinity for cJun. The isCAN → PCA based multidisciplinary approach provides a robust screening pipeline in generating target-specific hits, as well as new insight into rational peptide design in the search for novel bZIP family inhibitors., Here we describe library design coupled with computational and intracellular screening as an effective methodology to derive an antagonist that is selective for Fra1 relative to Jun counterparts.

COVID-19 is increasingly affecting human health and global economy. Understanding the fundamental mechanisms of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) is highly demanded to develop treatments for COVID-19. SARS-CoV and SARS-CoV-2 share 92.06% identity in their N protein RBDs' sequences, which results in very similar structures. However, the SARS-CoV-2 is more easily to spread. Utilizing multi-scale computational approaches, this work studied the fundamental mechanisms of the nucleocapsid (N) proteins of SARS-CoV and SARS-CoV-2, including their stabilities and binding strengths with RNAs at different pH values. Electrostatic potential on the surfaces of N proteins show that both the N proteins of SARS-CoV and SARS-CoV-2 have dominantly positive potential to attract RNAs. The binding forces between SARS-CoV N protein and RNAs at different distances are similar to that of SARS-CoV-2, both in directions and magnitudes. The electric filed lines between N proteins and RNAs are also similar for both SARS-CoV and SARS-CoV-2. The folding energy and binding energy dependence on pH revealed that the best environment for N proteins to perform their functions with RNAs is the weak acidic environment.

Pituitary prolactinoma is one of the most complicated and fatally pathogenic pituitary adenomas. Therefore, there is an urgent need to improve our understanding of the underlying molecular mechanism that drives the initiation, progression, and metastasis of pituitary prolactinoma. The aim of the present study was to identify the key genes and signaling pathways associated with pituitary prolactinoma using bioinformatics analysis. Transcriptome microarray dataset GSE119063 was acquired from Gene Expression Omnibus datasets, which included 5 pituitary prolactinoma samples and 4 normal pituitaries samples. We screened differentially expressed genes (DEGs) with limma and investigated their biological function by pathway and Gene Ontology (GO) enrichment analysis. A protein-protein interaction (PPI) network of the up and down DEGs were constructed and analyzed by HIPPIE and Cytoscape software. Module analyses were performed. In addition, a target gene - miRNA network and target gene - TF network of the up and down DEGs were constructed by NetworkAnalyst and Cytoscape software. The set of DEGs exhibited an intersection consisting of 989 genes (461 up-regulated and 528 down-regulated), which may be associated with pituitary prolactinoma. Pathway enrichment analysis showed that the 989 DEGs were significantly enriched in the retinoate biosynthesis II, signaling pathways regulating pluripotency of stem cells, ALK2 signaling events, vitamin D3 biosynthesis, cell cycle and aurora B signaling. Gene Ontology (GO) enrichment analysis also showed that sensory organ morphogenesis, extracellular matrix, hormone activity, nuclear division, condensed chromosome and microtubule binding. In the PPI network and modules, SOX2, PRSS45, CLTC, PLK1, B4GALT6, RUNX1 and GTSE1 were considered as hub genes. In the target gene miRNA network and target gene - TF network, LINC00598, SOX4, IRX1 and UNC13A were considered as hub genes. Using integrated bioinformatics analysis, we identified candidate genes in pituitary prolactinoma, which may improve our understanding of the mechanisms of the pathogenesis and integration; genes may be therapeutic targets and prognostic markers for pituitary prolactinoma.

Trabajo fin de máster presentado en la Université Paris-Cité para el Master Bioinformatique - Parcours In Silico Drug Design, en junio de 2022, The outbreak and spread of SARS-CoV-2 in 2019 caused massive lockdowns, triggering a global health and global economic crisis. The initial social distance strategies and lately vaccination are controlling the pandemics for current variants, but on the long term we need more therapeutic options. Hoffman et al. showed that TMPRSS2 was essential for the infection of the respiratory tract. In fact, TMPRSS2 competes for the priming of the binding furin site, a polybasic insertion only present on the SARS-CoV-2 spike protein. However, this region has not been resolved yet. In the absence of models of the molecular complex, it is essential to characterize the molecular complex between TMPRSS2 and the spike protein, to understand the molecular mechanisms of SARS-CoV-2 and to design new drugs. In this work, we have been able to model the furin binding site of the spike protein, a loop, which was absent in all experimental structures. Then, we characterized the spike-TMPRSS2 complex. Our results showed that loop morphology is fundamental in this process, demonstrating that priming can only occur with the open conformation of the spike protein. Finally, the characterization of this complex allowed us to find protein-protein inhibitors, being Antipain, a serine protease inhibitor, our best candidate to target this complex. In conclusion, this study has demonstrated the importance of loops in protein-protein interactions and opens the door to the inhibition of other respiratory diseases, avoiding drug resistance and the impact of new genetic variants.

Apoptosis is a mechanism of programmed cell death crucial in organism development, maintenance of tissue homeostasis, and several pathogenic processes. The B cell lymphoma 2 (BCL2) protein family lies at the core of the apoptotic process, and the delicate balance between its pro- and anti-apoptotic members ultimately decides the cell fate. BCL2 proteins can bind with each other and several other biological partners through the BCL2 homology domain 3 (BH3), which has been also classified as a possible Short Linear Motif and whose distinctive features remain elusive even after decades of studies. Here, we aim to provide an updated overview of the structural features characterizing BH3s and BH3-mediated interactions (with a focus on human proteins), elaborating on the plasticity of BCL2 proteins and the motif properties. We also discussed the implication of these findings for the discovery of interactors of the BH3-binding groove of BCL2 proteins and the design of mimetics for therapeutic purposes.

The difficulty of genetic transformation has restricted research on functional genomics in cotton. Thus, a rapid and efficient method for gene overexpression that does not rely on genetic transformation is needed. Virus-based vectors offer a reasonable alternative for protein expression, as viruses can infect the host systemically to achieve expression and replication without transgene integration. Previously, a novel four-component barley stripe mosaic virus (BSMV) was reported to overexpress large fragments of target genes in plants over a long period of time, which greatly simplified the study of gene overexpression. However, whether this system can infect cotton and stably overexpress target genes has not yet been studied. In this study, we verified that this new BSMV system can infect cotton through seed imbibition and systemically overexpress large fragments of genes (up to 2340 bp) in cotton. The target gene that was fused with GFP was expressed at a high level in the roots, stems, and cotyledons of cotton seedlings, and stable fluorescence signals were detected in the cotton roots and leaves even after 4 weeks. Based on the BSMV overexpression system, the subcellular localization marker line of endogenous proteins localized in the nucleus, endoplasmic reticulum, plasma membrane, Golgi body, mitochondria, peroxisomes, tonoplast, and plastids were quickly established. The overexpression of a cotton Bile Acid Sodium Symporter GhBASS5 using the BSMV system indicated that GhBASS5 negatively regulated salt tolerance in cotton by transporting Na+ from underground to the shoots. Furthermore, multiple proteins were co-delivered, enabling co-localization and the study of protein–protein interactions through co-transformation. We also confirmed that the BSMV system can be used to conduct DNA-free gene editing in cotton by delivering split-SpCas9/sgRNA. Ultimately, the present work demonstrated that this BSMV system could be used as an efficient overexpression system for future cotton gene function research.