A total of 14 core active ingredients of STF were screened, as well as 20 corresponding targets, which were mainly enriched in cancer pathway, proteoglycan synthesis, PI3K-AKT signaling pathway, and focal adhesion. Molecular docking showed that the core active ingredients related to MDR, namely quercetin and diosgenin, could bind well to the target. In summary, STF may reverse the MDR of GC and exert synergistic effect with chemotherapeutic drugs. It mediates MDR mainly through the action of quercetin and diosgenin on the PI3K/AKT signaling pathway. These findings are the first to demonstrate the molecular mechanism of STF in reversing MDR in GC, thus providing a direction for follow-up basic research.Siteng Fang (STF) has been shown to inhibit migration, invasion, and adhesion as well as promote apoptosis in gastric cancer (GC) cells. However, whether it can reverse the multidrug resistance (MDR) of GC to chemotherapy drugs is unknown. Thus, we aimed to elucidate the mechanism of STF in reversing the MDR of GC. The chemical composition of STF and genes related to GC were obtained from the TCMNPAS Database, and the targets of the active ingredients were predicted using the Swiss Target Prediction Database. The obtained data were mapped to obtain the key active ingredients and core targets of STF in treating GC. The active component-target network and protein interaction network were constructed by Cytoscape and String database, and the key genes and core active ingredients were obtained. The biological functions and related signal pathways corresponding to the key targets were analyzed and then verified  Gastric cancer (GC) is one of five cancers with the highest incidence in China . AccordiSargentodoxa vine, and Chinaroot Greenbrier Rhizome Catbriar, is a small prescription of Weichang’an decoction. Its main efficacies are clearing away heat as well as detoxifying and eliminating pathogenic factors. Clinical research has demonstrated that STF improves the clinical efficacy of chemotherapy drugs and the quality of life of patients with GC  has been used for the treatment of GC, and clinical studies have shown that TCM can improve the effect of western medicine, reduce the size and clinical stage of tumor, reverse MDR to chemotherapy drugs, relieve adverse reactions to chemotherapy, and improve the quality of life of patients . Weichan with GC –8. In ad with GC . We haveActinidiae chinensis (mihoutaogen), wild grape (yeputaogen), Sargentodoxa vine (daxueteng), and Chinaroot Greenbier Rhizome Catbriar (baqia) were input into the retrieval module of chemical constituents. The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) Version 2.3, Traditional Chinese Medicine Integrated Database (TCMID) Version 2.0, and the Herbal Ingredients’ Targets (HIT) Database were screened simultaneously, with TCMNPAS linked to the databases, to determine the chemical composition of STF  . The Chin of STF . The actn of STF  pharmacoTo obtain the potential targets of the active ingredients of STF, the SMILES strings obtained from the TCMNPAS Database, were imported into the Swiss Target Prediction Database. Targets with 0 probability were deleted .Disease ID was obtained by inputting the disease keyword “gastric cancer” to the disease gene retrieval module of TCMNPAS. The background automatically connected to GeneCard Database to obtain disease gene and then downloaded and saved the results as GC related targets .https://bioinfogp.cnb.csic.es/tools/venny/index.html), and the intersection was regarded as the target protein of STF in treating GC. Cytoscape 3.7.0 (https://string-db.org), the species was set as “Homo sapiens”, and the minimum interaction score was set as 0.4. Finally, the protein interaction data were imported into Cytoscape 3.7.0 to analyze the network topology parameters. The proteins above the median of “Degree” were selected as the key targets, and the corresponding chemical components were the core active components.The targets of the active components of STF and GC-related targets were introduced into venny2.1.0 (pe 3.7.0  was usedScreening of Drug-Disease Key Targets was transferred into DAVID6.8 (https://david.ncifcrf.Gov) for Gene Ontology (GO) functional enrichment analysis and Kyoto Gene and Genome Encyclopedia (KEGG) pathway enrichment analysis. The species was set as “Homo sapiens”, and the result was set as P<0.05. GO functional enrichment analysis describes the possible molecular functions of target products, the biological processes involved, and the cellular environment. KEGG pathway enrichment analysis indicates the most significant biological process by classifying the known genome annotation information. Therefore, these methods can predict the potential active components involved in the action mechanism of STF in treating GC.The target obtained from section https://www.rcsb.org/). Subsequently, the SMILES strings of the active ingredient numbers, PDB IDs of the key targets, and 3D structure in PDB format obtained from 2.1 were inputted to the molecular docking module of TCMNPAS. The PSOVina algorithm was optimized based on the autodock Vina molecular docking algorithm and used PSOVina for docking (https://pymol.org) to obtain 3D images of molecular docking. When the binding energy is less than -5 kJ/mol, the ligand is regarded to bind well to the receptor.The protein IDs of the key targets were obtained from the utility module of TCMNPAS and converted into Protein Data Bank (PDB) IDs (every molecular model in the PDB has a unique accession or identification code). The 3D structure of the key proteins in PDB format were downloaded from the PDB Database  parameters, 21 active components were obtained Table 1.According to the prediction of Swiss Target Prediction Database, targets with 0 probability were removed; thus, six active components without target information were deleted. Finally, 709 potential targets of STF were obtained.A total of 515 differentially expressed targets related to GC were identified. APC, CASP10, IRF1, MUTYH, erbB2, FGFR2, PIK3CA, KLF6, KRAS, and CTNNB1 were identified as the proteins with the highest scores.Drug Targets and Gastric Cancer-Related Targets, 43 proteins involved in the mechanism of STF in treating GC were obtained (From the intersection of the proteins obtained in sections obtained Table 2 A total of 41 selected key targets were analyzed for GO functional and KEGG pathway enrichment analyses and screened at P<0.05. A total of 52 GO biological processes, 9 cell components, 13 molecular functions (Two of the screened active components, quercetin and diosgenin, were potentially associated with MDR, as discussed below, and the PI3K/AKT pathway was screened as one of the top 10 KEGG pathways related to MDR. These active components were subjected to molecular docking to the receptor proteins of the PI3K/AKT pathway. The results showed that the binding energies of quercetin and diosgenin with the target receptor protein were less than -5 kJ/mol, indicating that they could bind well to the target receptor Table 4.Actinidiae Chinensis, and studies had shown that in addition to anti-inflammatory, antioxidant, apoptosis-inducing, and antiangiogenesis effects, quercetin has chemosensitizing effect to enhance the sensitivity of drug-resistant cells to drugs. The effects of quercetin on GC cells have been studied by Sylwia Borska et al. (The aim of this study was to elucidate the molecular mechanism of STF in treating GC. A total of 14 core active components of STF were screened out, including kaempferol, quercetin, isoengelitin, methylprotodioscin, and diosgenin. The key signaling pathways included the PI3K/AKT signaling pathway, FOXO signal pathway, and ERBB signaling pathway. Basic studies have confirmed that quercetin, diosgenin, and the PI3K/AKT signaling pathway can regulate MDR to chemotherapeutic drugs. Quercetin is one of the active components of Radix a et al.  using EPa et al.  confirmea et al.  screeneda et al. . The PI3a et al. –29.in vitro, reduce the adhesion and invasion ability of SGC-7901 cells, inhibit cell migration, and induce apoptosis. Moreover, it can inhibit the growth of SGC-7901 GC cell xenograft tumor in nude mice in vivo; this effect may be related to the promotion of apoptosis, upregulation of the expression of apoptosis-related proteins caspase-8 and caspase-9, promotion of PARP editing, and downregulation of Livin protein expression (In addition, preliminary research on the mechanism of STF in treating GC showed that STF can inhibit the growth of GC MGC-803 cells by regulating the Smac/Survivin signaling pathway pression –34. STF In conclusion, this study preliminarily explored the potential molecular mechanism of STF in reversing the MDR of GC to chemotherapy through network pharmacology and molecular docking technology. The present study revealed quercetin and diosgenin as the core active components of STF as well as the PI3K/AKT signaling pathway as an important pathway involved in the effect STF in reversing the MDR of GC. Taken together, our results suggested that STF has the effect of reversing the MDR of GC and that it can play a synergistic effect with chemotherapy drugs. STF mainly reversed MDR through the action of quercetin and diosgenin on the PI3K/AKT signaling pathway. These findings provide a direction for future studies to further explore the mechanism of STF in treating GC. However, these conclusions were made based on theoretical simulations and thus still need to be verified by experiments. The authors’ team will conduct experiments as a follow-up to the present work.All data generated or analyzed during this study are included in this article.LG conceptualized and designed the study. LG acquired, analyzed and interpreted the data. LG and HS drafted/revised the work for intellectual content and context. LZ gave the final approval and overall responsibility for the published work. All authors contributed to the article and approved the submitted version.The research was funded by Shanghai Science and Technology Commission Development Foundation, award number is 16ZR1437500; Shanghai Health and Family Planning Commission of Medical Science and Technology Innovation Project, award number is ZYKC201701009.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.The reviewer QX declared a shared affiliation, with no collaboration, with one of the authors HS to the handling editor at the time of the review.


Complement C4, a key molecule in the complement system that is one of chief constituents of innate immunity for immediate recognition and elimination of invading microbes, plays an essential role for the functions of both classical (CP) and lectin (LP) complement pathways. Complement C4 is the most polymorphic protein in complement system. A plethora of research data demonstrated that individuals with C4 deficiency are prone to microbial infections and autoimmune disorders. In this review, we will discuss the diversity of complement C4 proteins and its genetic structures. In addition, the current development of the regulation of complement C4 activation and its activation derivatives will be reviewed. Moreover, the review will provide the updates on the molecule interactions of complement C4 under the circumstances of bacterial and viral infections, as well as autoimmune diseases. Lastly, more evidence will be presented to support the paradigm that links microbial infections and autoimmune disorders under the condition of the deficiency of complement C4. We provide such an updated overview that would shed light on current research of complement C4. The newly identified targets of molecular interaction will not only lead to novel hypotheses on the study of complement C4 but also assist to propose new strategies for targeting microbial infections, as well as autoimmune disorders. Moreover, complement system functions as an effector on the clearance of soluble immune complexes and cell debris, which otherwise could induce an immune response against auto antigens and potentially trigger autoimmunity 2] recognizes antigen–antibody immune complexes or certain membrane-bound structures, e.g. C-reactive protein (CRP) or lipopolysaccharides (LPS), resulting in the transition from C1s zymogen to an active C1s repositions, which would be able to interact with sulfotyrosine residues on C4 (via recognition molecules as mannan binding lectin (MBL), ficolins, and collectin 10/11, leading to the activation of mannan-associated serine protease-2 (MASP-2), which relies heavily on its active sites, two complement control protein (CCP) domains, and the serine protease (SP) domain for the efficient binding and cleavage of C4  from the classical/lectin and alternative pathways are also strikingly similar, which is in agreement with their identical functions in the cleavage of the downstream complement proteins C3 and C5 (Complement component C4 (Mw = ~200 kDa), an essential component in complement system, plays an indispensable role in the activation of classical and lectin complement cascades. It is a disulfide-bonded three-chain glycoprotein, consisting of an α-chain 95 kDa), a β-chain 75 kDa), and a γ-chain (30 kDa) Figure 15 kDa, anes on C4 , 9. Simi5 kDa, a ge of C4 . As showge of C4 . C4b bintor CD46 , 15. iC4tor CD46 . Further3 and C5 .The complete or partial deficiency of complement C4 results in the increased risk of infection and autoimmune diseases. A plethora of studies demonstrated that complement C4 plays an essential role in defensing microbial infection. It is also well established that the complete or partial deficiency of complement C4 is associated with the increased susceptibility to infections –23. In aIn this review, we will look into the updated studies on the role of complement C4 in infectious diseases and autoimmune disorders. In this way, we aim to elucidate and update the functions of complement C4 in infectious diseases and autoimmune disorders, trying to highlight the important role of complement C4 as a potential intervention target for the management of those disorders.C4A and C4B genes) locus is located in the highly polymorphic major histocompatibility complex (MHC) class III gene region on chromosome 6, which could be a short form  or a long form , depending on the absence or the presence of the 6.36 kb endogenous retroviral sequence HERV-K(C4) in intron 9 of human C4 genes. Three quarters of C4 genes harbor the 6.36-kb endogenous retrovirus HERV-K (C4)  (RCCX) , and share >99% sequence identities. Five nucleotide variations located in exon 26 confer to four isotype-specific amino acid substitutions at positions 1101–1106 (PCPVLD for C4A and LSPVIH for C4B) and the major structural and functional differences between the C4A and C4B isotypes (The human complement C4 gene  (RCCX) –44. An e) (RCCX) . The dupted is 7 . It tookisotypes . C4A is isotypes –51. In aisotypes –55. C4A isotypes . It was isotypes . The indisotypes . Low copisotypes , 58–63. isotypes , 64, 65.isotypes . A comprin vivo or in vitro with monospecific antibody to individual complement components can have long-term effects on the production of those components. Antibody treatment induced specific suppression of C4 in peritoneal cell monolayers. Further studies revealed that long-term C4 suppression is actively maintained by a soluble suppressor factor (FsC4)  –70. MostDysregulation of classic and lectin complement pathways that complement C4 participates in can lead to complement-mediated autoimmune diseases. C4 nephritic factor (C4Nef), first described by Halbwachs et al. in 1980, is an autoantibody to C3 convertase (C4b2a). C4Nef can prolong the half-life of C3 convertase by stabilizing C4b2a and protects C4b2a against decay dissociation by C4 binding protein (C4BP). Multiple clinical studies demonstrated that C4NeF was associated with post-infectious acute glomerulonephritis, systemic lupus erythematosus, chronic proliferative glomerulonephritis and hypocomplementemic membranoproliferative glomerulonephritis (MPGN), and meningococcal disease –76.in vitro binding screening demonstrated that Neuropilin-1 (NRP1) acts as a receptor for complement split products, such as C4d, C3d, and iC3b. NRP1 is a highly conserved type 1 transmembrane protein that is involved in the tumorigenesis, the development of cardiovascular, and nervous systems through the interaction with vascular endothelial growth factor (VEGF) and semaphoring 3A (Sema3A). NRP1 is also expressed in murine immune cells and serves as a marker for mouse Treg cells. Interestingly, NRP1 was demonstrated to bind C4d in a concentration-dependent and saturable manner. These data demonstrated NRP1 functions as a receptor for C4d that is covalently bound to target surfaces during complement activation, suggesting that NRP1 might be involved in regulation of the process of infections and autoimmune disorders by targeting the split product from classical or lectin complement pathway  enables cell adhesion and penetration and impedes innate and adaptive immune responses. It was found that CIP was able to interact with the human C4b ligand and to interfere with the classical- and lectin-complement pathways (Staphylococcus aureus (S. aureus) strains can recruit complement regulator C4-binding protein (C4BP) to S. aureus surface to inhibit C4 complement effectors through binding significant amounts of the C4BP from serum. The complex (S. aureus-bound C4BP) functions as a cofactor for factor I-mediated C4b cleavage to iC4b and C4d, which was used as a strategy by S. aureus for immune evasion (Complement interfering protein (CIP) expressed on the surface of group pathways . Clinica evasion .B. pertussis. Endogenously secreted and recombinant Vag8 can inhibit complement deposition on the bacterial surface at the level of C4b. The binding of C1 inhibitor (C1-inh) to C1s, C1r, and MASP-2 was disrupted by the association of Vag8 with human C1-inh, which will free active proteases to cleave C2 and C4 away from the bacterial surface, revealing a mechanism of the unique complement evasion strategy of B. pertussis  and NKG2D on NK cells. However, when NK cells were co-cultured with Huh7.5 cells infected with cell culture-grown HCV, complement C4 and C3 synthesis was impaired. MICA/B expression in HCV-infected hepatocytes was found to be repressed during co-culture because the HCV-associated expressions of NS2 and NS5B proteins can disable a crucial receptor ligand in infected hepatoma cells, resulting in the disability of infected cells to respond to stimuli from NK cells to up-regulate the expression of complement C3 and C4  cells have been revealed to contribute to regulating complement synthesis. Studies using co-culture of NK cells (NK3.3) with human hepatoma cells (Huh7.5) expressing HCV core or NS5A protein revealed a significantly increased synthesis of complement C4 and C3 3 and C4 . This pivia a C3- and C4-dependent mechanism that applied both the canonical and bypass complement lectin activation pathways, which recognizes terminal mannose-containing carbohydrates on the viruses  and Dengue virus (DENV), was restricted through an antibody-independent fashion. N-linked glycans on the structural proteins of flaviviruses was recognized by mannose-binding lectin (MBL), resulting in neutralization and efficient clearance  viruses . A recen viruses .via the alternative pathway, which is complement C4-independent, causing the increase of sC5b-9 and the decrease of C3. In the acute stage of PUUV infection, the level of complement activation correlates with disease severity, indicating that complement activation may contribute to the pathogenesis of acute PUUV infection  hantavirus triggers complement system activation nfection .A recent study by Bottermann et al. revealed a novel antiviral mechanism that is C4-dependent and late-acting complement components-independent. C4 inhibits human adenovirus infection by the deposition of cleaved C4b on capsid, which inhibits it disassembly, preventing endosomal escape and cytosolic access . The mecl-fucose and mannose, which provides recognition sites for MLB binding and causes activation of lectin pathway (In the midst of pandemic with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)/COVID-19. The infection involves in multiple organs and cause striking elevations in pro-inflammatory cytokines and high risk of thrombosis. Numerous postmortem studies have revealed deposits of complement fragments on interalveolar endothelial cells, high incidence of venous thromboembolism (VTE), and diffused microvascular thrombi with endothelial swelling with a thrombotic microangiopathy (TMA). Preclinical studies with SARS-CoV-1 and MERS-CoV, which have significant homology to SARS-CoV-2, confirm that complement activation is not only linked to virus related organ damage but also is possible causative . In mous pathway . There iA recent study by Romano et al. revealed that anti–interleukin-6 receptor monoclonal antibody (Tocilizumab) could dramatically decrease serum level of complement C4 in rheumatoid arthritis patients. Neither circulating immunocomplexes nor any patients ever displaying clinical features of immunocomplex diseases was found. The study concluded that C4 consumption is because of the direct action of the drug rather than immunocomplex-induced complement activation .Histone H3 and H4 can be released from the damaged or lysed cells. One recent study by Qaddoori et al. revealed that histone H3 and H4 strongly bind to C4b region of complement C4, result in significant inhibition of classical and mannose-binding lectin pathways. Histone H3 and H4 did not affect the cleavage of C4 to C4a and C4b, indicating a possible natural feedback mechanism to prevent the excessive injury of host cells by the inhibition of complement activation by histones .A recent study by Vogt et al., using highly specific antibody against a cleavage neoepitope in C4d, identified pigment epithelium-derived factor (PEDF) from synovial fluid of rheumatoid arthritis patients as an activator of classical complement pathway, which belongs to the serine proteinase inhibitor family. C1q protein can bind PEDF, in particular, head regions of C1q, which is known to interact with other activators of the classical pathway. The results suggested PEDF activated classical complement and might mediate inflammatory processes in joint . The intUsing computational approach (protein-protein docking and molecular dynamics simulation), a recent study tried to understand Trypsin (Tryp)-mediated C4 activation by comparing with the co-crystalized structure of C4-MASP2. Comparative analysis of C4 alone, C4-Tryp, and C4-MASP2 discovered the impact of Tryp on C4 was like that of MASP2. These studies define the role of sessile loop in the interaction with serine domain, which could be beneficial to understand the interactions of complement C4 with other complement components .via the alternative pathway requires the presence of C4 and MBL proteins and the complement activation by Cryptococcus spp. can take place via multiple complement pathways , several early studies from the 1980s to 1990s of last century demonstrated that C4b generated from classical pathway activation could trigger the alternative pathway without involvement of complement C2 –118. It BL binds . It seemin vitro lectin pathway-mediated activation of C3 requires MASP-2, C2, and MASP-1/3. In a model of transient myocardial postischemic reperfusion injury (IRI), comparing to their wild-type littermates, infarct volumes of MASP-2-deficient mice were smaller. However, mice deficient in complement C4 were not protected, the observation implies the presence of a previously undocumented C4-bypass and lectin pathway-dependent mechanism. As monoclonal Antibody-based inhibitors of MASP-2 and MASP-2 deficiency can also protect mice from gastrointestinal IRI, suggesting the benefit of anti-MASP-2 antibody therapy in reperfusion injury and other lectin pathway-mediated disorders , are the pattern recognition molecules that drive lectin pathway activation on the surface of S. pneumoniae. pneumococcal opsonization in the absence of complement C4. This study corroborates the crucial function of MASP-2 in the lectin pathway and underlines the prominence of MBL-independent lectin pathway activation in the host defense against pneumococci -injury as well. The serpin C1-inhibitor and aprotinin, a Kunitz-type inhibitor can inhibit MASP-2. Recombinant tissue factor pathway inhibitor (rTFPI) was identified as a novel selective inhibitor of MASP-2, without disturbing the activity of MASP-1 or the classical pathway proteases C1s and C1r. Ex vivo assay revealed that Kunitz-2 domain in TFPI was necessary for the inhibition of MASP-2 activity. TFPI could be a therapeutic approach to constraint the tissue injury in the conditions of cerebral stroke, myocardial infarction, or solid organ transplantation .-16 M , complement C4 activation fragments may act as regulators to maintain homeostasis and to contain downstream anaphylatoxins’ proinflammatory effects, which may trigger hyper-inflammatory reactions. The activation of complement C4 and potential immune-regulation mechanisms of split products from complement C4 are illustrated in C4d, another cleavage product by complement C4 activation, has long been considered as a biomarker for disease activity in autoimmune disorders or antibody-mediated allograft rejection. A recent study identified Ig-like transcript (ILT) 4 and ITL5v2 as cellular receptors for C4d and interaction of C4d with ILT4 conferred a dose-dependent inhibition of TNFα and IL-6 secretion and attenuation of intracellular [Ca control . ILT4 ha control , 143, in control , and mai control . Mice la control  and exac control . It appeIt remains incompletely understood why total deficiencies of some complement components are associated with some autoimmune diseases . ComplemS. pneumonia  vaccination alone induced increases in anti-dsDNA IgA levels, which can be completely blocked by TLR2/4 antagonist, OxPAPC. Pam3CSK4, a TLR2 agonist, equally stimulated anti-dsDNA IgA production in C4KO mice, suggesting complement C4 plays a role in subduing autoantibody production stimulated by cross-reactive antigens and TLR2 agonists associated with neumonia .vs. SLE autoantigens peptide overlap and powerfully supports cross-reactivity as a major mechanism in EBV-associated SLE etiopathogenesis  peptide cross-reactome has been performed to search for peptides common to SLE-EBV and human SLE autoantigens. The study found EBV proteome can act as an immunological potential. Using publicly available databases, fifty-one SLE-related proteins were analyzed for hexapeptide sharing with EBV proteome and found 34 of hexapeptides are shared between human SLE autoantigens and EBV proteins. Interestingly, the study also revealed that peptide sharing mostly occurred with complement component C4 and Interleukin-10 (IL-10). This study demonstrated that the EBV ogenesis . Among pogenesis .+CD25+ Tregs and reduced expression of Foxp3 and TGF-β, which are crucial for the efficient development and function of Tregs cells. Thus, the study suggested that the association of the deficiency of complement C4 in the classical complement pathway with the development of autoimmune disorder might be via the role of Tregs deficiency  from College of Pharmacy and mini-grant (to HW) from College of Medicine, California Northstate University, Elk Grove, CA 95757, United States.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The early prediction of drug adverse effects is of great interest to pharmaceutical research, as toxicity is one of the leading reasons for drug attrition. Understanding the cell signaling and regulatory pathways affected by a drug candidate is crucial to the study of drug toxicity. In this study, we present a computational technique that employs the propagation of drug-protein interactions to connect compounds to biological pathways. Target profiles for drugs were built by retrieving drug target proteins from public repositories such as ChEMBL, DrugBank, IUPHAR, PharmGKB, and TTD. Subsequent enrichment test of the protein pool using Reactome revealed potential pathways affected by the drugs. Furthermore, an optional tissue filter utilizing the Human Protein Atlas was applied to identify tissue-specific pathways. The analysis pipeline was implemented in an open-source KNIME workflow called Path4Drug to allow automated data retrieval and reconstruction for any given drug present in ChEMBL. The pipeline was applied to withdrawn drugs and cardio- and hepatotoxic drugs with black box warnings to identify biochemical pathways they affect and to find pathways that can be potentially connected to the toxic events. To complement this approach, drugs used in cardiac therapy without any record of toxicity were also analyzed. The results provide already known associations as well as a large amount of additional potential connections. Consequently, our approach can link drugs to biological pathways by leveraging big data available in public resources. The developed tool is openly available and modifiable to support other systems biology analyses. The interaction between a chemical compound and the human body can be a complex cascade of different mechanisms. For understanding these mechanisms, the use of systems biology approaches, which are moving away from the one drug-one target concept, has seen a consequent rise in the last couple of years. Biological pathways are described as a sequence of interactions between biochemical molecules. Systems biology approaches such as pathway-level analysis of drug actions can reveal information about the underlying mechanisms induced by the drug. Furthermore, it can help to increase our understanding of the possible adverse events in connection to the compound .The National Research Council described the concept of toxicity pathways as a regular biological pathway that becomes perturbed beyond the normal homeostasis of the organism leading to toxicity . On thisDrugs usually affect multiple biological pathways. To understand the toxicological relevance of pathways affected by toxic drugs, drug-pathway connection data is needed. There are databases available capturing biological pathways: Reactome , KEGG K, and WikThe aim was to connect drugs to biological pathways through proteins they modify to obtain a complete overview of the drug’s systemic effect. Our approach uses broader drug-target profiles for uncovering unknown connections between drugs and biological pathways and eventually between toxic events and pathways, using statistical analysis.In the first instance, the focus was on drugs which have been withdrawn because of their toxic properties and black box warning cardio- and hepatotoxic compounds. Withdrawn drugs were once approved and later withdrawn from the market for toxicity or efficacy reasons. The FDA has introduced black box warnings to call attention to serious or life-threatening risks. With our method, we aimed to place cardio- and hepatotoxic events into their biological context and to gain more knowledge on two of the most often occurring organ-specific toxicities. A tissue-specific filtering system for the collected target proteins was also included to discover the organ level events’ characteristics. By completing an overrepresentation test with the retrieved tissue-specific target profiles, our aim was to define pathways relevant to the toxicity classes. We developed Path4Drug, an open-source KNIME workflow, which allows the analysis of other datasets as well, to support other pathway-oriented systems biology approaches.The input of the workflow is a drug or compound, and it should be provided as a ChEMBL identifier or a list of identifiers for multiple compounds. When a list compound IDs is provided, the workflow can sequentially run for each compound.Our analysis pipeline was based on a set of cardiotoxic and hepatotoxic compounds for identifying target proteins and biological pathways that can be involved specifically in one type of organ-level toxicity. The compounds were selected from drugs labeled as withdrawn or black box warning compounds by ChEMBL .First, drugs from four of the most common organ or organ system-specific toxicity classes across withdrawn and black box warning drugs–neuro-, nephro-, cardio- and liver toxicity - were extracted. Since the main aim comprised a comparison of toxicity classes, compounds that are present in more than one of the classes and therefore cannot be explicitly connected to one toxicity type were excluded. Thus, there is no overlap between the compound groups. The filtered list contained 57 cardio, 75 hepato-, 12 nephro-, and 28 neurotoxic compounds. The subsequent analysis was carried out with the two most populated classes, i.e., cardio- and hepatotoxic compounds.Additional compounds with cardiovascular toxicity from the withdrawn database were used as an external test set . Since tFurthermore, the workflow was also applied on approved cardiac therapy drugs that are still on the market and are not connected to toxicity, to compare the pathways they affect with those that are modulated by cardiotoxic compounds. Small molecules from the category “cardiac therapy” from ChEMBL were downloaded with a maximum phase of 4, which means they were approved. The already withdrawn ones and the ones with a black box warning were filtered out from the cardiac therapy list. The final set contains 27 compounds.Consequently, the cardiotoxic compounds had comparison groups, allowing the distinction of pathways between two tissue-specific toxicity classes and between therapy and toxic compounds of the same tissue-group, allowing identification of pathways that could play a specific role in cardiotoxicity.Path4Drug is a computational pipeline that employs drug-protein interactions to identify biological pathways perturbed by a drug. Path4Drug was implemented as a KNIME workflow (version: KNIME 4.1.2) to perform automated data retrieval and perturbed pathway prediction. KNIME is an open-source, graphical-analytics platform, and workflow management system, created for data science purposes . Figure Step 1Building protein target profilesst, 2020)  , DrugBant, 2020) , and Phat, 2020) . The tarhttps://www.ebi.ac.uk/chembl) is a database of bioactive molecules with drug-like properties, manually curated from public literature. The web services offered by ChEMBL  were used in the workflow to extract drug target protein data. At first, for each inputted drug, an assay search was performed across the database to query all proteins showing bioactivity value of pChEMBL 5 or above. pChEMBL is defined as: −log10  (ChEMBL (Potency) . After qWith the human targets, a second ChEMBL API call was performed to gain more information on the targets, such as the UniProt accession number. We were interested in protein-type targets, therefore, other types of targets were discarded from the analysis. In case the target type was a whole protein family, the accession numbers of all members were added to the protein pool. UniProt contains reviewed and unreviewed entries. Only the manually curated, reviewed ones were considered in our analysis.From the non-human targets, the non-mammalian ones were eliminated by using the organisms ChEMBL API call. Based on the hypothesis that mammalian targets act similarly to human ones, we intended to enrich the sparse human data with translated mammalian targets. This part of the workflow can be viewed as optional considering the inconsistent concordance rate of translational studies . HoweverIn addition to the above approach, ChEMBL’s mode of action API call was used to retrieve proven therapeutic targets. After accessing and filtering the mechanism of action target data, the received targets were also converted into UniProt accession numbers. As a result of both approaches, for each drug queried a collection of target proteins with UniProt accession numbers were extracted from ChEMBL.https://go.drugbank.com) pharmaceutical knowledgebase provides a download option for non-commercial usage of the openly available portion of their data in the form of one XML file. From that file, the target information was extracted for further processing. Since the processing of the whole XML is excessive, an excel file with the information needed was created and read into the workflow for further usage. Since the whole workflow starts with a ChEMBL identifier or a list of CHEMBL identifiers, the UniChem service (The DrugBank ( service  was utilhttp://db.idrblab.net/ttd/). The drug identifier cross-matching and the drug target mapping files provide information for building the target profiles. Neither does the drug ID cross-matching include ChEMBL identifiers, nor does the UniChem translation service support TTD. Hence PubChem compound IDs were chosen as a base for mapping, as these identifiers are present in both sources. As the drug and target file has no UniProt accession numbers, a python script provided by UniProt was modified and introduced to the workflow for translating the UniProt names to their accession numbers. The output is a list of ChEMBL IDs with their targets by UniProt accession numbers.Drug target protein dataset was downloaded from the Therapeutic Target Database (TTD) (https://www.pharmgkb.org). As PharmGKB IDs are supported by UniChem, a direct translation to ChEMBL IDs was feasible. From the relationship files, rows that symbolize a relationship between a drug and a target gene were extracted. The UniProt accession numbers of reviewed human proteins expressed by the target genes were queried via the EBI Protein API.Similar to TTD, compound mapping and relationship files were downloaded from the Pharmacogenomics Knowledgebase (PharmGKB) database (https://www.guidetopharmacology.org) offers web services for protein target search. The ChEMBL IDs were translated to IUPHAR IDs and used in the IUPHAR’s ligand-interactors API, which returned JSON file with target data. IUPHAR has one identifier for a protein regardless of the organism; for instance, Catechol-O-methyltransferase with the target ID 2472 represents the human, mouse, and rat proteins. With the EBI Protein ID mapping followed by filtering steps the human equivalent UniProt accession numbers of each target entry were obtained.IUPHAR (Guide for Pharmacology) ; ;  was usedStep 4Connecting drugs and biological pathwaysWith the list of tissue-specific target proteins for each drug, a statistical overrepresentation test was performed through the Reactome pathway analysis API service . ReactomThis statistical (hypergeometric distribution) test analyses whether certain pathways are overrepresented in the submitted data. Overrepresentation is described as the presence of more proteins for a pathway in the submitted list than it would be expected only by chance. The result of this test is a probability score. This probability score is expressed as a p-value and is corrected via the False-discovery rate (FDR) . The smaThe test is completed via a POST request in Reactome. Our request was carried out with a taxonomy identifier of 9606, whereby disease pathways were not included. The request body is equal to the protein pool we built in the first part of the workflow. The JSON file returned from the API call was processed to export the workflow`s a table containing the drug(s), associated pathways and statistical values .Additionally, another POST request can be performed by the workflow to retrieve the token of the analysis. With the token and preparation of a JAVA snippet for URL encoding, a GET request can be used to receive a link to the Reactome site´s analysis page or to download the detailed analysis report as a pdf.https://reactome.org) is also a repository for downloadable pathway-related data. The data contain ChEBI  compound relations to pathways based on compound-protein interactions. ChEBI (https://www.ebi.ac.uk/chebi/) is a dictionary of molecular entities focused on small chemical compounds . We filtered out the non-human pathways from the Reactome data, translated the ChEBI IDs to CHEMBL IDs, and used this data to see if novel connections were detected by our workflow.Reactome  are part of the liver pathway list for hepatotoxic compounds, and HERG (KCHN2) is part of the list for cardiotoxic compounds. Proteins, such as Prelamin-A/C (LMNA) are part of both lists see .In Reactome, the pathways are organized hierarchically. For the pathway comparison, the lower-level pathways were considered, which present a more detailed level of the pathway hierarchy. Higher-level pathways such as Cell Cycle or Autophagy are collective terms and were excluded from the analysis because of their generality. An FDR cut-off of 0.05 was applied to filter out less significant pathways. After applying these filtering steps, 382 pathways for 54 hepatotoxic compounds and 420 pathways for 38 cardiotoxic compounds were found. To find the most important pathways, we compared those affected by at least 10% of the cardiotoxic or 10% of the hepatotoxic compounds, and further those affected by at least 20% of the compounds.As To support our concept of applying this approach for identifying pathways that could play a role in cardiotoxicity, the workflow was in addition run with drugs used to treat cardiac disorders. Having these two groups allowed a comparison between a toxic and non-toxic group connected to the same tissue, supporting the interpretation of the findings of the toxicity group.For 14 drugs for the treatment of cardiac disorders, 34 tissue-specific target proteins were found. 14 of them overlap with the cardiotoxic class, and 20 are exclusive for the cardiac therapy group. The most often occurring targets for the cardiac therapy group are sub-units of the Sodium/potassium-transporting ATPase. The hERG potassium channel, which is a known off-target  is not oOur goal was to establish which pathways that are connected to cardiotoxic compounds can be specific for the toxicity class. For that purpose, we compared the distribution of pathway connections among the toxic and non-toxic groups.The cardiotoxic drugs can be connected to 420 pathways altogether. 221 of these pathways also can be connected to compounds used to treat cardiac disorders . HoweverA data science pipeline was constructed to connect compounds to pathways by building their tissue-specific target protein profiles and performing an overrepresentation-test with these proteins. The output of the overrepresentation test is a list of pathways that can be connected to the compounds. The application of an FDR cut-off ensured that our list contains only statistically significant pathways. As a use case hepato-and cardiotoxic compounds were analyzed.In the case of the hepatotoxic compounds, pathways of maresins and other SPMs  seem to be frequently affected. SPMs are keys for inflammation determination and for maintaining normal metabolic homeostasis in the liver . MaresinFor cardiotoxic compounds, we compared the list of pathway connections with those of hepatotoxic compounds and of drugs used to treat cardiac disorders. This should allow the estimation if the distinction of cardiotoxic from cardiotonic compounds is possible based on the pathway interaction profiles. This step was completed only for the cardiotoxic category because CHEMBL has the cardiac therapy category in their description list for drugs, making a comparison possible. There is no category across ChEMBL compounds, which can be unambiguously connected to treat liver disorders.The two pathways namely “Phase 3 - rapid repolarisation”, and “Voltage gated Potassium channels” were most frequently connected to the cardiotoxic compounds, significantly less connected to the cardiac therapy compounds, and not connected to hepatotoxic compounds.: “Phase 3—rapid depolarisation” refers to the third phase of the cardiac action potential, where the potassium ion efflux occurs. The involvement of these two pathways implicates that a change in the action potential causes toxicity by disturbing the potassium ion release. The role of potassium channels in QT prolongation is a known mechanism of cardiotoxicity .The third most common pathway among the cardiotoxic compounds is “Phase 0—rapid depolarisation”. It is related to the phase of the cardiac action potential, where the influx of sodium ions occurs. For this pathway, the difference of the association to cardiotoxic compounds and cardiac therapy compounds is rather insignificant. This might be, since class I antiarrhythmic agents dominantly affect this part of the cardiac action potential, which comes with the risk of re-entry arrhythmias. Thus, in this group of antiarrhythmic drugs, cardiotoxicity is a frequently observed side effect.Furthermore, almost every cardiotoxic compound, which can be connected to “Phase 0” can also be connected to “Phase 3”. There are two exceptions, one of them is encainide, which is an antiarrhythmic drug of the Ic class. Ic class antiarrhythmic agents are potent Sodium channel blockers . EncainiThere is no non-toxic drug, which can only be connected to “Phase 3” but not to “Phase 0”, which is another indicator for the crucial role of “Phase 3” in cardiotoxicity. Those cardiotoxic compounds that are not connected to “Phase 3”, “Phase 0” or “Voltage gated Potassium channels” pathways  have diverse pathways profiles see .To further verify the significance of these results, compounds with cardiovascular toxicity from the withdrawn database were tested. This test set is small since our dataset and the withdrawn database have considerable overlap in compound information. However, the profile of the four external compounds also implicates the significant involvement of the above discussed pathways, such as “Phase 3—rapid repolarisation” see .Our dataset was relatively small, but the Path4Drug workflow was built with the possibility to apply it to larger sets of drugs and increase the toxicological relevance of the findings. Based on these findings, one could define unfavorable pathway profiles and use them as a warning for possible toxic events. Furthermore, our workflow can be used to find other drug-target-pathway relations, regardless of toxicity to create an overview of the systemic effect of drugs and use this knowledge for instance for drug repurposing. Path4Drug is available on KNIME Hub and modifiable. Consequently, our workflow aims to support pathway-oriented analyses and pathway-driven toxicology approaches.


Astragalus membranaceus (AM) is a well-known herbal medicine, and modern pharmacological studies have confirmed its antioxidant, immunomodulatory, and antiapoptotic effects. Clinical studies have shown that AM and its active components can attenuate cisplatin-induced kidney damage, but the molecular mechanism has not been fully expounded.  Cisplatin is a frequently used and effective chemotherapy drug in clinical practice, but severe side effects limit its use, among which nephrotoxicity is considered the most serious and prolonged damage to the body.  First, the components and targets information of AM were collected from the TCMSP, and the relevant targets of cisplatin-induced kidney damage were accessed from the GeneCards and OMIM databases. Then, the core targets were selected by the Venn diagram and network topology analysis, which was followed by GO and KEGG pathway enrichment analysis. Finally, we construct a component-target-pathway network. Furthermore, molecular docking was carried out to identify the binding activity between active components and key targets. α, and p53. Furthermore, GO and KEGG pathway enrichment analysis suggested that MAPK, Toll-like receptor, and PI3K-Akt signaling pathways may be of significance in the treatment of cisplatin-induced kidney damage by AM. Molecular docking indicated that quercetin and kaempferol had high binding affinities with many core targets.  A total of 20 active components and 200 targets of AM and 646 targets related to cisplatin-induced kidney damage were obtained. 91 intersection targets were found between AM and cisplatin-induced kidney damage. Then, 16 core targets were identified, such as MAPK1, TNF- In summary, the active components, key targets, and signaling pathways of AM in the treatment of cisplatin-induced kidney damage were predicted in this study, which contributed to the development and application of AM. Cisplatin, a heavy metallic compound with powerful anticancer effects, is synergistic with many antitumor drugs without cross-resistance, thus being one of the most frequently used and effective chemotherapy drugs at present . HoweverAstragalus membranaceus (AM), also known as “Huang Qi” in traditional Chinese medicine, is the dried root of membranous Astragalus or Astragalus mongolicus, which has been widely used in the clinical setting [Shennong's Herbal Classic . Modern pharmacological studies have shown that AM contains flavonoids, saponins, and other active ingredients, which have a wide range of pharmacological effects, such as antioxidant, immune regulation, antiapoptosis, and antitumor [ setting . AM, whintitumor –16. A rentitumor . Also, antitumor . HoweverRecently, network pharmacology has been a potent tool for gaining insights into the mechanisms of drugs . This mehttps://tcmspw.com/, February 20, 2021) [https://www.uniprot.org/, February 15, 2021) to get the gene symbol of targets.Information of the active components and targets associated with AM was collected from the TCMSP database  . The TCM0, 2021) . Among t0, 2021) . In the 0, 2021) , 25. In https://omim.org) and the GeneCards (https://www.genecards.org) databases [By using the keywords of “cisplatin-induced kidney damage,” “cisplatin-induced nephrotoxicity,” “cisplatin kidney damage,” and “cisplatin-induced kidney injury,” gene symbols of disease-related targets were obtained from the OMIM (atabases –28. The https://bioinfogp.cnb.csic.es/tools/venny/) was used for intersection targets between AM and cisplatin-induced kidney damage. The intersection targets were used to constitute the protein-protein interaction (PPI) network using the STRING database  [https://cytoscape.org/) [The VENNY 2.1 online platform   with conpe.org/) . Degree The core targets obtained above were inputted into the STRING database to get the PPI network. All settings were the same as above. Then, the PPI network was extracted in TSV format and inputted into Cytoscape 3.8.0 for further analysis.https://david.ncifcrf.gov/, March 5, 2021) [To investigate the multiple mechanisms of AM against cisplatin-induced kidney damage at the systematic level further, we used DAVID 6.8   to perfo5, 2021) , 33.To investigate the relationship between active components, targets, and pathways, we constructed the network of active component-target-pathway (C-T-P network). We imported active components, targets, and pathways into Cytoscape 3.8.0 as three types of nodes and connected associated nodes with edges to construct the active components-targets-pathways network.https://pubchem.ncbi.nlm.nih.gov/, March 10, 2021) and stored in SDF format. Afterward, the core target conformations were obtained from the Protein Data Bank database . The following were the screening conditions: (1) The biological source of protein structure is human; (2) The protein structure is acquired by X-crystal diffraction; (3) The resolution of protein crystals is less than 3 Å; and (4) Protein structures with unique ligands are preferred. The structures of the ligands and the protein receptors were prepared by using Discovery Studio . Then, we used the flexible docking procedure CDOCKER built-in DS for molecular docking with CHARMM force field (Chemistry at HARvard Macromolecular Mechanics).We used molecular docking to predict the binding activity between the active ingredient and the core target. The structural formula of active components was obtained from PubChem , interleukin-6 (IL-6), angiotensin-converting enzyme, and transforming growth factor-beta 1.We found 534 relevant targets of cisplatin-induced kidney damage in GeneCards and 121 targets in OMIM databases. After deleting duplicate targets, 646 disease targets were finally obtained. The top 5 targets for relevance score were cellular tumor antigen p53 (p53), tumor necrosis factor-alpha  (The 16 core targets were introduced into the STRING database to get the PPI network . The DC  (VEGFA) .For the purpose of figuring out the mechanism of AM against cisplatin-induced kidney damage more systematically, the 16 core targets were inputted into DAVID 6.8 to GO and KEGG enrichment analysis. There were 186 items related to biological processes, mainly including MAPK cascade, positive regulation of smooth muscle cell proliferation, inflammatory response, negative regulation of the apoptotic process, and so on. In the cell composition, the extracellular region is the main classification of these targets. Additionally, there were 23 terms enriched in the molecular function category, mainly including protein serine/threonine kinase activity, cytokine activity, transcription factor binding, growth factor activity, and so on. We selected the top 10 items according to the gene ratio, which are presented in For the aim at clarifying what the relationships between components, core targets, and pathways are, the significant pathways and biological processes, core targets, and active components of AM were used to build the C-T-P network . The tarTo identify potential drug-target interactions, we performed molecular docking to predict the binding affinities between the active components and core targets in the C-T-P network. Docking results are shown in Cisplatin-induced kidney damage is a renal impairment caused by cisplatin, which is extremely harmful to human beings. It is reported that about 25–30% of patients developed symptoms of AKI after receiving cisplatin chemotherapy . BesidesWe obtained 20 active components and 200 corresponding targets from the TCMSP database and then constructed a component-target network, which mainly included quercetin, formononetin, isorhamnetin, and kaempferol. Modern pharmacological studies showed that quercetin has an anti-cisplatin-induced kidney injury effect, which is related to its antioxidant activity and the ability to inhibit kidney inflammation and renal tubular cell apoptosis . In a reα, p53, and caspase-3 [α, and interleukin-1 beta (IL-1β) played an essential role in cisplatin-induced kidney damage [α, which induced an exogenous apoptotic pathway through its tumor necrosis factor receptor 1 (TNFR1) [α can activate proinflammatory cytokines and chemokines such as NF-κB and trigger oxidative stress, which ultimately aggravates kidney damage [α further helped induce the expression of receptor-interacting protein 1 (RIP1), RIP3, and mixed lineage kinase domain-like protein (MLKL) in proximal tubular cells and enhanced the necrotic signaling pathway through positive feedback [We obtained 91 intersection targets between AM and cisplatin-induced kidney damage and further screened out 16 core targets of AM in the treatment of cisplatin-induced kidney damage. The targets are mainly associated with oxidative stress, apoptosis, inflammation, and cell proliferation. According to quantities of studies, apoptosis induced by TNF-aspase-3 , 44 and y damage , 46. It  (TNFR1) , and TNFy damage . The stufeedback . As mentfeedback . After efeedback . In addifeedback . A recenfeedback –55. Anotfeedback . All of α can activate the MAPK pathway [α, and ERK1/2, thus improving cisplatin-induced renal injury [α and IL-1β, leading to increased inflammatory cell infiltration and inflammatory responses in renal tissue [Subsequently, GO and KEGG enrichment analyses were applied to 16 core targets. The result suggested that the PI3K-Akt signaling pathway, MAPK signaling pathway, and Toll-like receptor signaling pathway were suggested to have a significant role in the treatment of cisplatin-induced kidney damage by AM. It has been reported that the MAPK pathway is central to the regulation of inflammation and oxidative stress in cisplatin renal injury and that TNF- pathway . Besides pathway . Meanwhi pathway –69. Therl injury , 70. Whal tissue , 72. MeaIn the C-T-P network, each pathway corresponds to a plurality of targets, and each target is connected with a plurality of pathways that are connected with each other through a common target. It was suggested that AM synergistically treats cisplatin-induced kidney damage through a multicomponent, multitarget, and multipathway mechanism.In summary, the present research aimed to figure out the molecular mechanism of AM against cisplatin-induced kidney damage by network pharmacology and molecular docking. Screening of active ingredients and molecular docking studies showed that quercetin, kaempferol, and formononetin were significant active ingredients to AM against cisplatin-induced kidney damage. The C-T-P network suggested that the MAPK pathway, PI3K-Akt signaling pathway, and Toll-like receptor signaling pathway had important roles in AM treatment of cisplatin-induced kidney damage. In addition, one of the significant findings is that AM treats cisplatin-induced kidney injury to multicomponent, multitarget, and multipathway synergistic effects. Unfortunately, this study has no corresponding experimental validation that is what we need to do in the future. In a nutshell, this study provided a rationale for further research of cisplatin-induced renal injury and a new orientation of development and application of AM.


Leishmania donovani (Ld) infected, uninfected and treated BALB/c mice’s tissues and biofluids to elucidate the host metabolome changes using gas chromatography–mass spectrometry. Univariate and multivariate data treatments provided numerous significant differential hits in several tissues like the brain, liver, spleen and bone marrow. Differential modulations were also observed in serum, urine and fecal samples of Ld-infected mice, which could be further targeted for biomarker and diagnostic validations. Several metabolic pathways were found to be upregulated/downregulated in infected  and treated  samples. Results also illustrated several metabolites with different pattern of modulations in control, infected and treated samples as well as in different tissues/biofluids; for e.g. glutamic acid identified in the serum samples of infected mice. Identified metabolites include a range of amino acids, saccharides, energy-related molecules, etcetera. Furthermore, potential biomarkers have been identified in various tissues—arginine and fumaric acid in brain, choline in liver, 9-(10) EpOME in spleen and bone marrow, N-acetyl putrescine in bone marrow, etcetera. Among biofluids, glutamic acid in serum, hydrazine and deoxyribose in urine and 3-Methyl-2-oxo pentanoic acid in feces are some of the potential biomarkers identified. These metabolites could be further looked into for their role in disease complexity or as a prognostic marker. The presented profiling approach allowed us to attain a metabolic portrait of the individual tissue/biofluid modulations during VL in the host and represent a valuable system readout for further studies. Our outcomes provide an improved understanding of perturbations of the host metabolome interface during VL, including identification of many possible potential diagnostic and therapeutic targets.Pathophysiology of visceral leishmaniasis (VL) is not fully understood and it has been widely accepted that the parasitic components and host immune response both contribute to the perpetuation of the disease. Host alterations during leishmaniasis is a feebly touched area that needs to be explored more to better understand the VL prognosis and diagnosis, which are vital to reduce mortality and post-infection sequelae. To address this, we performed untargeted metabolomics of  Leishmania to different visceral organs like liver and spleen further affecting bone marrow and brain  is a systemic disease that shows varied clinical manifestations and homing of the pathogen i.e. nd brain . The int anaemia . Apart f anaemia . On a ce anaemia . How the anaemia . Studies anaemia . Present anaemia . Therefoin vitro, but it is still lagging in the in vivo assessment, so as to address the detailed trend of composition and heterogeneity of host during VL  patterns; indicative of the physiological state of disease. This is an established approach in clinical infection studies and parasitology . Earlieruring VL . This stL. donovani, BHU1260, was derived from the splenic aspirate of a VL patient at the Kala Azar Medical Centre of the Institute of Medical Sciences, Banaras Hindu University, Varanasi, India. L. donovani strain was grown in M199 medium (pH 7.4), which was supplemented with 10% fetal bovine serum (FBS)  and maintained at 23°C.M199, FBS, Molecular grade water, methanol, chloroform, ribitol (adonitol), methoxyamine HCl, pyridine and primers from Sigma-Aldrich, St. Louis, MO, USA. BSTFA was obtained from Supelco Sigma, Bellefonte, Pennsylvania, United States. SYBR™ green PCR master mix was obtained from Applied Biosystems Foster City California, United States. Ketamax 50 was obtained from Troikaa Pharmaceuticals Ahmedabad, Gujrat, India. DNeasy blood and tissue kit was provided by Qiagen Hilden, Germany. A strain of All animal experiments were duly approved by the Animal Ethics Committee of the National Institute of Immunology, New Delhi .in vivo experiments, 6 to 10 weeks inbred BALB/c mice were used. They were grouped as control and infected. In the infected group, stationary phase Leishmania promastigotes were introduced through intra-cardiac injection with 50 µl 1× PBS containing 1 × 106 parasites on day 0 of the study  in an LC (Roche Diagnostics). The 12 µl reaction mixture contained 1 µl LC FastStart DNA Master SYBR Green I, 2 mM MgCl2, 10 µM each of the primers, and 100 ng of the template. Time and temperatures for PCR configuration were as follows: denaturation was done for 8 s at 95°C, amplification of 40 cycles was done at 95°C for 10 s, followed by 72°C for 8 s. The melting cycle was set at 95°C for 10 s, 67°C for 30 s and 95°C for 10 s followed by cooling at 40°C for 60 s. Slope (°C/s) was kept constant at 20 except in the last step of melting where the slope was 0.1. For fluorescence signal acquisition, channel F1 was used and the gain was set at 5. For normalization of fluorescent data, the F1/1 ratio was applied.Detection of lsewhere . For thiMice were sacrificed on the 21st day along with the control mice for brain, liver, spleen and bone marrow tissues. Blood (200 µl) from mice was collected just before the sacrifice for serum. Urine and feces were collected on the 21st day of infection  along with that of the control mice. The treated mice were sacrificed on the 27th day (after following 5 days of treatment). The blood, tissues and other biofluids were collected in a similar manner as described for control and infected mice.Sample preparation of brain , bone maGas–Chromatography was performed with GCMS-QP2010 Ultra (Make—Shimadzu) using Rxi-5 siloxane ms (dimensions: 30 m × 0.25 mm 1 d × 0.25 µm) column for separation. MS conditions were as follows: Ion source temperature was 230.0°C, interface temperature was 270.0°C, solvent cut time was 6.50 min, detector gain mode was kept relative, +0.00 kV was gained by detector whereas the threshold was 1,000. The program start time was 7 min and the end time was 50 min. The acquisition mode was set to scan mode. The event time was 0.20 s and the scan speed was 3,333. The m/z start value was 40 whereas the end value was 650.00.www.xcmsonline.scripps.edu). Within the software, a single job was created using the GC/single quad centwave setting where the polarity was set to negative. After the job was completed, the analysed result was available for download in a zip folder format. The following data columns—mass/charge (‘mz’), retention time ‘rt’ and original intensity (‘into’) were copied from the provided excel sheet and saved in a.txt file, which was then converted to a.csv file for further processing and analysis of data in the MetaboAnalyst software . MetaboAnalyst schematics include data normalization, followed by statistical analysis, ‘peak to pathway’ and enrichment analysis  was set to 0.25 and retention time tolerance to 5 s. Peaks of the same group were summed if they belonged to one sample. Peaks appearing in less than half of all samples in each group were ignored. The aligned peaks were reorganized into a single data matrix with the samples in rows and the variables (peaks) in columns for further analysis. Data normalization was done to reduce any systematic bias and to improve overall data consistency so that meaningful biological comparisons can be made. A combination of row-wise normalization by a pooled or average sample of the control group and auto data scaling was used for data normalization. This was observed to be the most suitable method that helped achieve a Gaussian curve, required for further analysis .versus magnitude of change (fold change) is represented by a volcano plot, which is essentially a variant of the scatter plot. Features having a fold change threshold of 2 (x-axis) and t-test threshold of (y-axis) 0.1 were considered for further analysis  analysis .Mus musculus (KEGG). The significant metabolites identified were then proceeded for enrichment analysis using Over Representation Analysis (ORA), done in reference to HMDB using the Small Molecule Pathway Database (SMPDB). The fold enrichment factor of a pathway used here for comparison was calculated as the ratio between the number of significant pathway hits and the expected number of compound hits within the pathway  and the used pathway library was  pathway .Direction targeting Spearman rank correlation was used as a distance measure, that calculates the ranks of individual features rather than their actual values. A predefined profile of 1-2-1 was used to target features that showed anomaly during infection and remained more or less constant in control and treated samples. For this, all three groups of datasets—control, infected and treated samples were used for comparison .Leishmania infection in several tissues like the brain, liver, spleen, bone marrow and biofluids like urine, serum and feces  plot, where the correlation among the datasets was obtained through a two-dimensional (2D) graph  showed differential and significant features. On comparison of control and infected groups, seven significant features were identified with the help of a t-test as the overall peak groups and individual features identified in serum samples were significantly less. Approximately 22 features were found to be upregulated while 18 were downregulated in the volcano plot  as focussing on pathway enrichment during infection is crucial to identify the systemic changes that occur during VL progression.Significantly identified metabolites of MSEA from the control De-novo triacylglycerol biosynthesis, cardiolipin biosynthesis and glycerolipid metabolic pathways followed a similar pattern for all samples. In serum and brain, no significant changes were detected in fatty-acid related metabolic pathways (The identified results were further filtered through HMDB (Human Metabolome database) to get a more vivid picture of modified pathways during VL. Metabolite abundance was found to be altered for multiple central metabolic pathways including amino acids, glycolysis, TCA, fatty acid synthesis and several other pathways , a causative agent of visceral leishmaniasis (VL) is well known for its host alteration in several aspects  metabolic pathways. Also, tissue-specific pathway changes were noticed, indicating their possible role in affecting the specific functionality of the tissue during VL. It is well known that utilization of arginine by both, host and pathogen represents a metabolic bottleneck which is decisive in shaping the fate of a pathogenic infection. For e.g. Arginase (important enzyme of parasite) competes with iNOS (important defense of macrophage to generate NO) for arginine; as many pathogens including Leishmania exploit this to block NO production by increasing expression of arginase, to limit arginine availability for metabolism via iNOS  reduces brain edema formation and improves cortical blood flow . Fumaric pathway . It is a pathway . Liver c pathway . Decreas pathway . EpOME .SD, TS, and CS designed the experiments. SD and TS performed, analyzed the data, and wrote the article. All authors revised the manuscript. All authors contributed to the article and approved the submitted version.SD was a recipient of DST INSPIRE faculty award (grant no. DST/INSPIRE/04/2015/002785) by DST (Department of Science and Technology), India. TS (JRF) was supported by a research grant of DST INSPIRE faculty award. CS is Professor of Eminence at the National Institute of Immunology and funded by Institutional Core funding and recipient of JC Bose fellowship from DST. The work was financially supported by DST Inspire Faculty award by DST, India.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


To analyze the pharmacological mechanism of the treatment of dry age-related macular degeneration (dry AMD) based on a network pharmacological approach of Shuang Di Shou Zhen Tablets (SDSZT) and to provide a new reference for the current lack of effective treatment of dry AMD. Rehmanniae Radix Praeparata, Ligustrum lucidum, Mori Fructus, Paeonia albiflora, Rhizoma Dioscoreae, Alisma orientale, Schisandra chinensis, Radix Polygoni Multiflori Preparata, Ophiopogon japonicus, and Radix Rehmanniae were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Traditional Chinese Medicine Integrated Database (TCMID). The active ingredients of traditional Chinese medicine were screened according to Absorption, Distribution, Metabolism, and Excretion (ADME), the gene names of the targets of each active ingredient were obtained from the Uniprot database, the main targets of dry AMD were obtained from GeneCards and DisGeNET database, and the protein interaction analysis was performed on the String database. The Metascape database was used to analyze the “drug-component-target” and the biological processes and networks involved, and then, Cytoscape 3.8.1 was used to construct the “ SDSZT component-dry AMD target-pathway” network.  The main chemical constituents and their targets of β-glutamine, β-carotene, etc. And, the core targets are RAC-alpha serine/threonine-protein kinase (AKT1), prostaglandin G/H synthase 1 (PTGS1), tumor necrosis factor (TNF), transcription factor AP-1 (JUN), apoptosis regulator Bcl-2 (BCL2), caspase-3 (CASP3), phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit gamma isoform (PIK3CG), androgen receptor (AR), apoptosis regulator BAX (BAX), etc. The biological pathways for the treatment of age-related macular degeneration by SDSZT mainly act on pathways in cancer, fluid shear stress and atherosclerosis, and TNF signaling pathway, and the main function of SDSZT is to regulate intracellular cytokine receptor binding.  The main active ingredients of SDSZT for dry AMD treatment are quercetin, kaempferol, luteolin,  This study initially reveals the multiconstituent, multitarget, and multipathway mechanism of action of SDSZT in the treatment of dry AMD and provides the basis for the clinical application of SDSZT. Age-related macular degeneration (AMD) is one of the most common eye diseases in ophthalmology and is one of the leading causes of blindness in the elderly population . It can The advantages of traditional medicine in treating AMD should not be overlooked. The treatment mechanism of traditional Chinese medicine is not only to a single target, but is also based on the holistic view of traditional Chinese medicine to provide a multitarget, multifaceted, and comprehensive treatment of the disease, with high safety. Network pharmacology is the use of known drug components, component targets, and known targets of disease to predict the likelihood of a drug's potential to treat a disease, and the network is able to comprehensively respond to possible mechanisms of drug interventions. Through multipathway modulation of signaling pathways, network pharmacology, as a new tool for drug research, can effectively tap into the active ingredients of traditional Chinese medicine, discard toxic ingredients, and treat the corresponding diseases with maximum stability and precision.Rehmanniae Radix Praeparata, Ligustrum lucidum, Mori Fructus, Paeonia albiflora, Rhizoma Dioscoreae, Alisma orientale, Schisandra chinensis, Radix Polygoni Multiflori Preparata, Ophiopogon japonicus, and Radix Rehmanniae, of which Rehmanniae Radix Praeparata and Ligustrum lucidum are popular herbs for research on their antioxidant, anti-inflammatory, and lipid metabolizing components in recent years [Shuang Di Shou Zhen Tablet (SDSZT) is a self-made ophthalmic medicine for Longhua Hospital, Shanghai. For many years, SDSZTs have been used in ophthalmology clinics to treat age-related eye diseases . In preliminary clinical observations, it was found that treatment with vitamin C and vitamin E combined with SDSZT resulted in a smaller number of Amsler table deformation frames and a smaller extent of central visual field defects in patients with dry AMD compared to vitamin C and vitamin E alone , 7. Thisnt years –12. Therhttp://lsp.nwu.edu.cn/tcmsp.php) [http://119.3.41.228:8000/tcmid/) [http://www.uniprot.org) for specification. The drug-component-target intersection was mapped by Cytoscape 3.7.1 software [The websites of TCMSP  (msp.php)  and TCMI/tcmid/)  were use/tcmid/) –17 were software .http://www.genecards.org) and DisGeNET database [https://www.disgenet.org) for potential targets related to dry AMD. Although higher scores in the GeneCards database indicate a strong association between the target and the disease, there were too few relevant targets for dry AMD in several databases (1056 relevant targets in the GeneCards database and only 12 relevant targets in the DisGeNET database) and therefore no targets greater than the median were set as potential targets here. After merging the targets in the two databases, the potential targets for dry AMD can be obtained by deleting the duplicate targets.Using “dry age-related macular degeneration” and “nonexecutive age-related macular degeneration” as keywords, we explored the GeneCards database  (http://database  (https:/https://bioinfogp.cnb.csic.es/tools/venny/) to get intersection targets. The acquired targets are then used to construct a protein-polymer interaction (PPI) network model from the STRING 11.0 database [http://string-db.org). The biological genus is set to “Homo sapiens” and the minimum required interaction score is set to “highest confidence” (>0.900); the rest are default settings to generate the PPI network diagram. Using Cytoscape 3.7.1, the network is analyzed by CytoNCA to calculate the betweeness centrality (BC), closeness centrality (CC), degree centrality (DC), and the eigenvector centrality (EC); the mean value is calculated and then filtered. The PPI network was further analyzed using the MCODE [To clarify the interactions between SDSZT-associated targets and dry AMD-related targets, we first used the Venny 2.1.0 , the P value < 0.01 was set, and enrichment analysis was performed. Using the Metascape database and the Microbiology Letter Platform (http://www.bioinformatics.com.cn/), we have conducted a number of studies on molecular function (MF), biological process (BP), and cellular component (CC). The top 20 functionally annotated catalogs and signaling pathways are selected for analysis, and the results are presented as bar and bubble plots.The combination of functional enrichment, interactomic analysis, gene annotation, and search in Metascape is an effective tool for comprehensive analysis and interpretation of OMICs-based research in the era of big data . TherefoCytoscape 3.7.1 was used to construct a network diagram of the constituents of SDSZT-dry AMD target-pathway network, and Cytoscape 3.7.1 built-in tools were used to analyze the network topology parameters of the active ingredients and targets, including Degree, BetweennessCentrality, and ClosenessCentrality. The network topology parameters were then used to determine the core targets and the main active ingredients that exerted drug effects.Rehmanniae Radix Praeparata, 1042 kinds of Ligustrum lucidum, 2190 kinds of Mori Fructus, 1007 kinds of Paeonia albiflora, 871 kinds of Rhizoma Dioscoreae, 179 kinds of Alisma orientale, 39 kinds of Schisandra chinensis, 22 kinds of Radix Polygoni Multiflori Preparata, 60 kinds of Ophiopogon japonicus, and 49 kinds of Radix Rehmanniae. After ADME screening, there were 2 kinds of chemical composition in Rehmanniae Radix Praeparata, 10 kinds of Ligustrum lucidum, 6 kinds of Mori Fructus, 6 kinds of Paeonia albiflora, 15 kinds of Rhizoma Dioscoreae, 7 kinds of Alisma orientale, 5 kinds of Schisandra chinensi, 4 kinds of Radix Polygoni Multiflori Preparat, 2 kinds of Ophiopogon japonicus, and 2 kinds of Radix Rehmannia  [β-sitosterol, β-carotene, stigmasterol, etc., based on the preliminary screening by network pharmacology method. Studies on the therapeutic mechanisms of dry AMD have shown that polyphenols such as quercetin can directly scavenge reactive oxygen species (ROS) [β-induced increase in interleukin 6 (IL-6), interleukin 8 (IL-8), soluble intercellular adhesion molecule 1 (sICAM-1), and monocyte chemotactic protein 1 (MCP-1) production by inhibiting nuclear transcription factor-kB (NFκ-B) and MAPK signaling pathways to further protect ARPE19 cells [Shuang Di Shou Zhen Tablets (formerly known as Ziyin Bushen Tablets) have been used in the treatment of dry AMD for 20 years. In previous clinical studies, patients with dry AMD were found to have improved visual acuity after receiving a combination of SDSZT and supplements such as vitamin E and vitamin C compared to before treatment. As the number of deformation grid in Amsler table was reduced, the range of central vision defect was reduced, and there were also statistical differences on these respects between treatment group and control group (only treated with vitamin E and vitamin C) ( < 0.05) , 7, but es (ROS)  and it pes (ROS) . Quercetes (ROS)  and acties (ROS) . In vivoes (ROS) . Luteoli19 cells . TherefoPTGS2, also known as cyclooxygenase (COX2), has been reported to be involved in the AMD process as a key enzyme in the inflammatory response, and is highly expressed in retinal pigment epithelial cells [JUN, also known as transcription factor ap-1, can be activated by 4-hydroxyhexenal- (HHE-) under the control of cyanidin-3-glucoside (C3G) and is associated with AMD inflammation [PIK3CG) was upregulated when bevacizumab treated RPE cells in an AMD model [PIK3CG may be a target for the treatment of AMD. Current information on the modes of RPE death in AMD disease includes apoptosis, necrosis, autophagy, and ferroptosis [Bcl-2 and the upregulation of the proapoptosis gene Bax have been shown to be the main causes of apoptosis in RPE cells in the AMD model [Based on the results of this study, the highest degree value target of SDSZT for dry age-related macular degeneration is PTSG2, while AKT1, PTGS1, TNF, JUN, BCL2, CASP3, PIK3CG, AR, and BAX are also likely to be key therapeutic targets for SDSZT. Gene Ontology analysis and KEGG pathway enrichment analysis showed that these key targets involve multiple pathways, including prostate cancer , TNF sigal cells . JUN, alammation . The expMD model , suggestroptosis . The dowMD model .The results of this study indicate that a single monomer compound of SDSZT can regulate different targets, and a single target can interfere with different biological processes and signaling pathways. This embodies the function characteristics of the multipathway, multitarget function of SDSZT. At the same time, it is clear that the whole network can be modulated by modulating a single monomer or an important target or multiple targets in the pharmacological network. This provides a scientific basis for the clinical use of SDSZT for dry age-related macular degeneration and a new direction for exploring the potential mechanisms of SDSZT for dry age-related macular degeneration. However, network pharmacology methods have certain limitations, and validation of the predicted targets and monomer compounds is necessary as well to further demonstrate the clinical therapeutic potential of SDSZT and then clarify the exact regulation target of SDSZT.


RASopathies represent a family of mostly autosomal dominant diseases that are caused by missense variants in the rat sarcoma viral oncogene/mitogen activated protein kinase (RAS/MAPK) pathway including KRAS, NRAS, BRAF, RAF1, and SHP2. These variants are associated with overlapping but distinct phenotypes that affect the heart, craniofacial, skeletal, lymphatic, and nervous systems. Here, we report an analysis of 13 Drosophila transgenic lines, each expressing a different human RASopathy isoform. Similar to their human counterparts, each Drosophila line displayed common aspects but also important differences including distinct signaling pathways such as the Hippo and SAPK/JNK signaling networks. We identified multiple classes of clinically relevant drugs—including statins and histone deacetylase inhibitors—that improved viability across most RASopathy lines; in contrast, several canonical RAS pathway inhibitors proved less broadly effective. Overall, our study compares and contrasts a large number of RASopathy-associated variants including their therapeutic responses.  •Patients with RASopathy present with variable symptoms and have poor therapeutic options•We established 13 Drosophila models, each expressing a human RASopathy variant•Models displayed variability in deregulated pathways, mirroring human heterogeneity•Screening identified drug classes broadly active across RASopathy subtypes Biological Sciences; Physiology; Molecular Biology; Cell Biology PTPN11, is a cytosolic protein that belongs to the protein tyrosine phosphatase superfamily. Following growth factor stimulation, SHP2 is recruited to the intracellular domain of receptor tyrosine kinases (RTKs) to activate the rat sarcoma viral oncogene (RAS)/RAF/mitogen activated protein kinase (MAPK) signal transduction pathway (RIT1-associated Noonan syndrome (NS) with severe hypertrophic cardiomyopathy  pathway. Overall, these results emphasize differences between disease isoforms that may impact disease progression as well as therapeutics. Nevertheless, we demonstrate at least two classes of drugs that provide broad therapeutic benefits across different RASopathy models, suggesting they have the potential to benefit a large cross section of patient classes in the clinic.Here, we develop and characterize 13 Drosophila RASopathy models, developing a platform that takes a broad, whole animal approach to exploring the signaling differences and therapeutic responses between RASopathy isoforms. Expressing human transgenes in Drosophila epithelia, we demonstrate significant whole animal signaling differences between RASopathy-associated genes and also between models containing variants within the same gene. These differences include tissue-specific phenotypes as well as activation of different signaling networks within the same tissue. Further, we find that both activating and inactivating mutations in Previous work reported Drosophila RASopathy models in which fly genes—altered to model human RASopathy disease isoforms—were expressed in multiple tissue types . The resPTPN11 disease isoforms , three RAF1 disease isoforms , two BRAF isoforms , and single isoforms of KRAS (G12D) and HRAS (G12S). Different isoforms are associated with different RASopathies, perhaps reflecting different signaling properties. Of note, some variants act as inactivating mutations but still give rise to overlapping patient outcomes (tub-GAL4) and targeted expression including ptc-GAL4 , 765-GAL4 (entire developing wing epithelia), and byn-GAL4 . Higher ambient temperatures promote elevated GAL4 driver activity within the fly, a further step of controlling expression.To generate a broad cross section of RASopathy models, we stably expressed inducible transgenes for 13 RASopathy-associated human gene isoforms in flies: six outcomes ; this isoutcomes ). Using outcomes , each trRASopathies can have both broad and more targeted or mosaic impact throughout the patient's body . We ther765-GAL4, ptc-GAL4, and byn-GAL4) at four temperatures  promoter, the transgenes were targeted to a discrete region of the developing wing epithelium (“wing disc”). This discreet stripe within the developing epithelia gives rise to the adult wing tissue between longitudinal veins L3 and L4. Fly lines were examined at increasing temperatures to progressively elevate levels of ptc-GAL4 activity  led to a substantial increase in wing vein material within the ptc expression domain (inter-vein region between L3 and L4). This effect was further enhanced at 25°C. Drosophila wing veins emerge at sites of high RAS pathway activity . All PTPN11 lines except one (PTPN11D61G) altered wing vein material patterns outside of the ptc expression domain .We next explored the consequences of expressing the transgenes more uniformly across the larval wing epithelium using a 4 driver , and S5.765>RAF1D486G, predicted to have loss of kinase activity, exhibited temperature-dependent suppression of wing veins in broad areas of the wing. By contrast, expression of the PTPN11 transgenes with a 765-GAL4 driver led to a very specific effect: an increase in cross-veins between the longitudinal veins (L1-L4), with the penetrance of this phenotype being fairly low. In summary, expression of RAS or RAF disease isoforms led to ectopic wing veins throughout the wing field. Expressing PTPN11 disease isoforms primarily drove ectopic wing cross-veins, suggesting a more cell type-specific effect of this class of RASopathy variants as has been reported in murine RASopathy models -approved drugs as well as polypharmacological tool compounds co-developed in our laboratory.e.g., vemurafenib, axitinib), RTK inhibitors including inhibitors of RET  and epidermal growth factor receptor , SRC inhibitors, etc. We tested inhibitors targeting the proteasome, histone deacetylases (HDACs), and HSP90, which have shown promise as therapies in different RAS-dependent cancer paradigms. We also tested statins, which have been assessed in clinical trials (NCT02713945) on a small number of patients with RASopathy.To screen for therapeutics, we used a quantitative Drosophila survival assay we previously developed to model various human cancer paradigms . We used765-GAL4 at 27°C. The ratio of the number of treated:untreated surviving pupae/adults (“% rescue”) was used to compare results across lines. For the drug screen, we used the driver PTPN11 class of models. At least one statin was active for each RASopathy model. Simvastatin and fluvastatin showed the broadest efficacy, improving viability of RAF1S259A, RAF1D486G, BRAFW531C, PTPN11D61G, PTPN11Y279C flies . Viability of PTPN11D61G flies was improved by vorinostat, entinostat, belinostat, and CUDC-9073 treatment. Viability of RAF1S257L flies was improved by belinostat and CUDC-9073.Histone deacetylase inhibitors belong to a group of inhibitors that target various classes of HDACs . HDAC inPTPN11Q510E but not the PTPN11Q510P fly model, indicating a surprising specificity to a single amino acid change. We had previously described a polypharmacological class of drugs that targeted both cellular and lipid kinases . Our panel focused on pathways with known roles in human disease. By comparing activity levels for each signaling pathway, we assessed how each RASopathy isoform activates distinct signaling pathways in situ , to identify conditions in which most isoforms induce MAPK activity. All lines broadly expressing and pMEK . The PTPse pMEK;  and S8, se pMEK; . Two linvs. pMEK .PTPN11Y279C, PTPN11Q510P lines displayed initial activation of pERK followed by suppression of pERK within 24 hr, suggesting negative feedback regulation, a well-described feature of the MAPK pathway  and PTPN11  transgenes.EGFR was moderately activated (pEGFR) by both the RAS/RAF and PTPN11 lines also displayed differences in their regulation of JNK pathway signaling. While 6/7 RAS/RAF lines (exempting HRASG12S) strongly increased pJNK levels above basal levels, 4/6 PTPN11 lines  decreased phosphorylated JNK (pJNK) levels. Previous studies including our own with oncogenic RTK, RAS/MAPK, and SRC components identified increased JNK activity as a key aspect of transformation in Drosophila tissues; this study extends these observations .Using the pathway activity markers pMOB (pMats) and pLATS (pWts), we found that RAS/RAF lines, RAF1D486G and HRASG12S, demonstrated significantly increased levels of pAKT and pGSK3, which were restrained by drugs that improved survival of these variants in our viability assays . Given the heterogeneity of pathway activity across different RASopathy lines, we used our western blot analysis to explore the activity of effective drug candidates for each RASopathy model. Drugs were analyzed at two concentrations for their effects on our panel of protein markers. The vehicle dimethylsulfoxide (DMSO) alone was used as a control. Our analyses identified examples of both expected and unexpected mechanisms by which drugs promote viability of RASopathy variant-expressing Drosophila larvae.Using a targeted screen of clinically relevant drugs and compounds, we identified a small set that improved viability of our RASopathy lines ; reduction of MAPK activation correlated with improved viability  or moderate reduction of pERK and pMEK levels (KRASG12D and RAF1S259A larvae). Vorinostat is an HDAC inhibitor with a broad palette of identified targets including members of the RAS/MAPK pathway , PTPN11Y279C , PTPN11N308D , or PTPN11Q510P  lines, efficacy correlated with upregulation of growth inhibitory markers of the Hippo pathway, pLATS and pMOBS , efficacy correlated with suppression of pJNK levels. These results are consistent with our pathway analyses highlighting a potential role for Hippo and SAPK/JNK activity in RASopathy defects. Linking our observation that pEGFR activity was increased in a subset of PTPN11 models—PTPN11N308D, PTPN11Q510P, PTPN11Q510E—we found that some successful therapeutics in these models restrained pEGFR activation (PTPN11Q510E). In summary, drugs effective in the PTPN11 models represent a wide range of inhibitor classes, suggesting that EGFR, SAPK/JNK, and Hippo pathway markers serve as common surrogate markers of treatment efficacy.For drugs effective at increasing viability of nd pMOBS A and 5B.tivation A and 5B PTPN11 fly lines. Both classes of drugs have a wide range of clinical use in multiple disease paradigms, and the statins in particular are well tolerated over long periods of treatment.In summary, our analyses identify key pathway biomarkers that may prove useful to monitor treatment efficacy in future studies. They emphasize, however, the challenge of identifying a single therapeutic that is effective against most RASopathy-associated variants. Notable exceptions include the HDAC inhibitor vorinostat as well as statins, which were effective at improving viability of both RAS/RAF and G12D and RAF1L613V throughout the developing wing. Expression of the RAF1L613V isoform displayed a temperature-dependent strengthening of the ectopic wing venation phenotype  resulted in an increase of flies eclosing as adults (increase from 5% to 20%), as well as suppression of ectopic wing venation pattern  also improved survival and led to 10% of 765>KRASG12D animals surviving to adulthood Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Ross Cagan (All Drosophila lines generated in this study are available upon request.All data and accession numbers needed to evaluate the conclusions in the paper are present in the paper and/or the Supplemental Materials. Additional data related to this paper may be requested from the authors.All methods can be found in the accompanying