The objective of our study is to explore the potential active ingredients and activity of Ginseng and Astragalus decoction (GAD) in the treatment of malignant pleural effusion (MPE) by using network pharmacology and molecular docking technologies.  The active ingredients and corresponding targets of Ginseng and Astragalus were extracted from the Traditional Chinese Medicine System Pharmacology Database and Analysis Platform. The relevant targets of malignant pleural effusion (MPE) were searched in the disease databases. Overlapping targets of Ginseng and Astragalus and the corresponding targets of MPE were obtained to define the effective target of GAD for the treatment of MPE. The STRING database was applied to construct a predicted protein-protein interaction network for intersected targets. The Cytoscape software was used to screen key targets with a therapeutic potential. Using the Metascape database, we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis on the targets identified in the study. PyMOL and AutoDock Vina were used to molecularly dock the selected key components to their respective key targets for MPE treatment.  The core target network revealed 22 main active ingredients, 26 main targets, and 16 signaling pathways in GAD. Molecular docking revealed 6 targets  that could partially dock with kaempferol, frutinone A, ginsenoside RH2, formononetin, and quercetin.  Several components, targets, and signaling pathways of GAD contribute to the treatment of MPE, which suggests a rationale for further investigation on GAD's active molecule and mechanism of action in the clinical application of MPE. Malignant pleural effusion (MPE) is one of the most common adverse consequences of lung cancer in the advanced stages of the disease . It was In clinical practice, traditional Chinese medicine (TCM) has been considered to be effective in the clinical treatment of MPE , 7, but Network pharmacology is a new network model of multitarget, multipathway, and multiple associations that combines biological and pharmacological knowledge with a modern data analysis technology to reveal the mechanisms of GAD through multimolecule synergistic effects on diseases. This study aimed to explore potential active ingredients of the GAD, its targets, and mechanisms of action on MPE to understand the clinical application of MPE with GAD.https://tcmspw.com/tcmsp.php) [https://www.uniprot.org/) [https://www.genecards.org/); Online Mendelian Inheritance in Man  [https://go.drugbank.com/) [https://www.string-db.org); Network analysis and mapping software, Cytoscape 3.8.2 ; the Gene function analysis database, Metascape (https://metascape.org) [http://www1.rcsb.org/) [https://pubchem.ncbi.nlm.nih.gov/); 3D structure display software, PyMOL  [http://vina.scripps.edu/)[http://www.bioinformatics.com.cn/) were used as bioinformatics tools.The Systematic Pharmacology database of Traditional Chinese medicine  ; Proteinot.org/) ; Human Gim.org/) ; and Drunk.com/)  were useape.org) ; Proteinsb.org/) ; CompounOR, USA) ; moleculpps.edu/) and bioiThe main active components of Ginseng and Astragalus were retrieved from the systematic pharmacology analysis platform TCMSP. Oral bioavailability (OB) ≥ 30% and drug-like (DL) ≥ 0.18 were selected as the screening conditions for active likeness. The targets of active ingredient were retrieved from the TCMSP database, and the information of target proteins were standardized and converted through UniProt  network was raised for the intersecting targets using STRING database.P  <  0.05, were screened out. The sequence of the enriched genes was carried out, and the pathway information was imported into the bioinformatics tool to draw the bubble map and bar chart.Cytoscape was applied to analyze the PPI network, to analyze closeness, betweenness, and degree of nodes in the network and to screen according to the median of the three parameters. Metascape was applied to conduct Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis for the screened core network proteins, and the biological processes and pathways with Core network proteins were carefully chosen, and the corresponding active components were determined according to the relationship between the active components and the corresponding targets. The three-dimensional structure (3D) was downloaded and established using the “.PDB” file of the core protein in the PDB database, and the corresponding 3D “.SDF” file of the structure of the active ingredient in the PubChem database. With the PyMOL software, the 3D structure files were processed by water removal, hydrogenation, and charge distribution. Molecular docking was executed out using the software AutoDock Vina 1.1.2 . BindingIn total, 190 compounds were identified in Ginseng and 87 compounds were identified in Astragalus from the TCMSP platform. Based on the selection criteria (OB ≥ 30% and DL ≥ 0.18), the core active ingredients were further filtered to 22 in Ginseng and 20 in Astragalus, among which kaempferol (KPL) was a compound shared by both drugs . Next, 2By searching GeneCards, OMIM, and DrugBank databases, 1499, 315, and 124 target genes related to MPE were collected, respectively. We derived a list of 1602 genes that may have been responsible for the MPE, considering only the genes that were not repeated. It was determined through Venn analysis that 114 intersection genes  might be regulated by the active ingredient of GAD treatment on MPE . A netwoTo analyze interaction between proteins, 114 potential targets were added to the STRING database . There wG protein coupled receptor binding, and endopeptidase activities.GO functional analysis and signaling pathway analysis were performed with the 26 targets in Metascape and KEGG, respectively. GO function enrichment analysis identified the following processes: biological processes mainly concentrated in the lipopolysaccharide response, oxidative stress response, regulation of cell migration, response to growth factors, angiogenesis, leukocyte differentiation, response to inorganic substances, epithelial cell proliferation, DNA metabolism, and DNA-binding transcription factor activity regulation . CellulaThe enrichment analysis of the KEGG signaling pathway is shown in Molecular docking was used to predict the binding pattern and affinity of drugs and proteins through the characteristics of the receptor, as defined by the interaction between the receptor and the drug molecule. The conformational stability of the ligand binding to the receptor is defined as by its binding energy : lower binding energy means the higher stabilization of the ligand. We performed a molecular docking simulation between the top 6 targets AKT serine/threonine kinase 1 (AKT1), intercellular adhesion molecule 1 (ICAM1), Jun proto-oncogene (JUN), peroxisome proliferator-activated receptor gamma (PPARG), prostaglandin-endoperoxide synthase 2 (PTGS2), and tumor necrosis factor (TNF) in the core target network with kaempferol (KPL), frutinone A (FNA), ginsenoside RH2 (GRH2), formononetin (FNN), and quercetin (QCN), respectively . The resMost MPE patients present with systemic symptoms such as inappetence, weight loss, and discomfort because the condition is usually diagnosed at an advanced stage. There is no clear understanding of how large pleural effusions cause breathing difficulties. However, various factors could include reduced chest wall compliance, contralateral mediastinal displacement, ipsilateral lung volume reduction, and pain from lung and chest wall stimulation . The preThe relationships between drug-compound-target-disease resulting from the treatment of GAD were explored using a network pharmacology approach and 41 compounds and 114 targets were identified from the study. Among these, KPL, FNA, GRH2, FNN, and QCN were identified as the main potential active ingredients. The most common flavonoid in vegetables and fruit is KPL, a natural ingredient commonly found in many foods. It has been described to have a variety of anticancer activities, against tumors of the breast, prostate, bladder, cervical, colon, liver, lung, ovarian, and leukemia . Studiesβ-catenin, and MAPK/ERK signaling pathways [FNN is an isoflavone derived from numerous therapeutic herbs and plants, such as Astragalus and red clover. FNN has been studied extensively in the past decade because of strong evidence that it promotes apoptosis and inhibits proliferation, suggesting that it can be used as an anticancer drug against various cancer types. Breast, prostatic carcinoma, and colorectal tumors are among the tumor models in which the anticancer properties have been observed. The ability of FNN to inhibit tumor growth and metastasis has also been demonstrated in various in vivo studies , 24. Thepathways .β-catenin, leading to breast cancer cell infiltration. AKT1 inhibition induces nuclear accumulation of β-catenin and depends on extended stimulation of the EGFR signaling pathway in mammary gland tumor cells. Downregulation of AKT1 in mechanistic experiments dephosphorylate PIKfyve on Ser and inactivate the PIKfyve site, resulting in mammary cancer metastasis through EGFR signaling pathways [According to the core target network, GAD activity is exerted mainly via activation of AKT1, ICAM1, JUN, PPARG, PTGS2, and TNF and other targets in MPE. Among these, AKT1 is an important signaling molecule that plays a necessary effect in cell cycle, growth, survival, metabolism, and immune response. AKT1 is highly activated in a variety of human cancers. AKT1 is phosphorylated at Thr308 and Ser473, two important modified sites. Active AKT1 could activate numerous downstream proteins in cytoplasm and/or nucleus . In the As a member of the immunoglobulin superfamily of adhesion molecules, ICAM1 is an important adhesion molecule that mediates adhesion reactions. ICAM1 significantly encourages the adhesion of inflammatory sites, regulates cancer development and metastasis, and modifies the immune response. ICAM1, ICAM4, and ICAM5 are associated with breast cancer susceptibility loci as indicators of disease severity . The expC-Jun is an element of transcription factor activator protein 1, which associates to and stimulates transcription on the TRE/AP-1 element. C-Jun-dependent transcription is activated when phosphorylation of C-Jun at serene 63/73 is stimulated by various growth factor, cellular signaling, oncoproteins, and ultraviolet radiations. So, phosphorylated C-Jun may significantly affect tumorigenesis and cancer development . C-Jun iFew publications have demonstrated that peroxisome proliferator-activated receptors impact the progression of a variety of tumors. Zhao et al.  reportedα signaling in mammary gland cancer cells, including clinical observations related to TNF-α. Møller et al. [α expression. Further, TNF-α paracrine and autocrine activity induced cell death in colorectal cancer. Thus, as can be seen from the above, the core targets of GAD defined in this study mainly involve biological processes, for example, cell migration, proliferation, cell survival, inflammatory response, and cell death. Moreover, it shows that the GAD plays an important part in the treatment of MPE through multiple targets.PTGS2 is the important enzyme in prostaglandin biosynthesis, which differs in regulating expression and tissue distribution. It is controlled by precise stimuli, suggesting that it is involved in prostaglandin biosynthesis-related with inflammation and mitosis. It has been suggested that tumor recurrence and prognosis of colon tumor is related to PTGS2 expression . Furtherr et al.  found thIn our study, network pharmacology and molecular docking techniques were applied to preliminary explore the key compounds, action targets, biological functions, signaling pathways, and potential mechanisms of the GAD in the treatment of MPE. The results showed that KPL, FNA, and GRH2, FNN, QCN, and other major active ingredients might play an important part in inhibiting apoptosis and regulating cell metabolism through multiple signaling pathways. The treatment effect on MPE by the GAD is not mediated by a single component but involves a collaborative effect of numerous components and targets. The results indicate the potential effect of the GAD on MPE and provide a direction and rationale for further studies involving the GAD on MPE.


LINC00472/hsa-miR-221-3p/PTPN11, ANP32A-IT1/hsa-miR-182-5p/S100A2, LINC00472/hsa-miR-132-3p/S100A2, and RBM26-AS1/hsa-miR-182-5p/S100A2. According to pathway enrichment analysis, the immune-related DEmRNAs were enriched in the “JAK-STAT signaling pathway” and “Adipocytokine signaling pathway.” An understanding of regulatory mechanisms of ASD-related immune genes would provide novel insights into the molecular mechanisms behind ASD pathogenesis.Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder featuring impairment in verbal and non-verbal interactions, defects in social interactions, stereotypic behaviors as well as restricted interests. In recent times, the incidence of ASD is growing at a rapid pace. In spite of great endeavors devoted to explaining ASD pathophysiology, its precise etiology remains unresolved. ASD pathogenesis is related to different phenomena associated with the immune system; however, the mechanisms behind these immune phenomena as well as the potential contributing genes remain unclear. In the current work, we used a bioinformatics approach to describe the role of long non-coding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) in the peripheral blood (PB) samples to figure out the molecular regulatory procedures involved in ASD better. The Gene Expression Omnibus database was used to obtain the PB microarray dataset (GSE89594) from the subjects suffering from ASD and control subjects, containing the data related to both mRNAs and lncRNAs. The list of immune-related genes was obtained from the ImmPort database. In order to determine the immune-related differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs), the limma package of R software was used. A protein-protein interaction network was developed for the immune-related DEmRNAs. By employing the Human MicroRNA Disease Database, DIANA-LncBase, and DIANA-TarBase databases, the RNA interaction pairs were determined. We used the Pearson correlation coefficient to discover the positive correlations between DElncRNAs and DEmRNAs within the ceRNA network. Finally, the lncRNA-associated ceRNA network was created based on DElncRNA-miRNA-DEmRNA interactions and co-expression interactions. In addition, the KEGG enrichment analysis was conducted for immune-related DEmRNAs found within the constructed network. This work found four potential DElncRNA-miRNA-DEmRNA axes in ASD pathogenesis, including,  Autism spectrum disorder (ASD) is a neurodevelopmental disease that manifests itself early throughout life . ASD incInteracting genes with their synergistic effects cause immune-related pathological events. As a result, a combined study of non-coding RNAs and protein-encoding genes might aid in elucidating the underlying immunological processes . Long noIn the current research, we used a bioinformatics method for the aim of the data mining of the microarray dataset (GSE89594) containing the PB from patients with ASD and their matched controls. We wanted to find immune-related differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs), as well as developing lncRNA-associated ceRNA regulatory network. https://www.ncbi.nlm.nih.gov/geo/). The microarray dataset was based on the GPL16699 platform (Agilent-039494 SurePrint G3 Human GE v2 8 × 60K Microarray 039381). The GSE89594 dataset comprises 32 samples of the PB taken from individuals with ASD and 30 samples of the PB collected from healthy subjects  (https://www.immport.org/home/) (https://www.genenames.org/) was used to collect the entire list of lncRNA genes with HUGO Gene Nomenclature Committee (HGNC) approved symbols  < 0.01, and (Background correction was accomplished using the normexp method  with an or.org/) . Age andg/home/) . Furtherg/home/) . The HGN symbols . Followi symbols : a false.01, and  |log2 foDIANA-LncBase v.3 was utilized to identify experimentally confirmed interactions between DElncRNAs and miRNAs . Human mhttps://string-db.org/) (https://fgrtools.hms.harvard.edu/MIST/)   and Moleu/MIST/) . For PPIu/MIST/) .p < 0.01 were employed. The ceRNA regulatory network were generated using Cytoscape software.The Pearson correlation analysis was used to determine any positive correlations between immune-related DEmRNAs and DElncRNAs in the ceRNA regulatory network. DElncRNAs, targeted DEmRNAs, and interacted miRNAs were deleted from the ceRNA network in the opposite expression pattern between DElncRNAs and the targeted DEmRNAs. Hmisc and corrplot packages were used to compute and visualize the correlations. As inclusion criteria, Pearson correlation coefficients greater than 0.5 and p-value < 0.01 was thought to be statistically significant.The Enrichr tool  was usedp-value < 0.01, and |(log2FC)| > 0.3, a total of 10 DElncRNAs and nine immune-related DEmRNAs were found in GSE89594 PB samples taken from ASD and healthy controls. Prior to conducting DEGA, background adjustments, gene filtering, normalization, and batch adjustment were performed. Box plot for gene expression-related data was presented after normalization to assess data distribution see . In the We used the DIANA-LncBase v3 online platform to predict DElncRNA-miRNA interaction pairings, revealing that nine of the ten DElncRNAs may target potential miRNAs. Following that, DIANA-TarBase was used to identify relationships between miRNAs retrieved using the HMDD and potential mRNAs. We discovered eight overlapping genes after comparing the potential mRNAs to nine immune-related DEmRNAs.Protein interactions amongst immune-related DEmRNAs were identified using the online STRING and MIST tools. LINC00472: long intergenic non-protein coding RNA 472, ANP32A-IT1: ANP32A intronic transcript 1, and RBM26-AS1: RBM26 antisense RNA 1), two immune-related DEmRNAs , and three miRNAs  were included totally.The Pearson correlation analysis was done between immune-related DEmRNAs and DElncRNAs to validate the ceRNA axis hypothesis, which states that lncRNA positively regulates mRNA expression by interaction with miRNA . We deveA KEGG enrichment analysis on immune-related DEmRNAs within the network was carried out. The KEGG pathways that have been enriched were the “JAK-STAT signaling pathway” and “Adipocytokine signaling pathway.”LINC00472/hsa-miR-221-3p/PTPN11, ANP32A-IT1/hsa-miR-182-5p/S100A2, LINC00472/hsa-miR-132-3p/S100A2, and RBM26-AS1/hsa-miR-182-5p/S100A2.This study was concentrated on immune-related genes implicated in the development of ASD. We discovered nine immune-related DEmRNAs and created a ceRNA network in order to investigate the regulatory processes underlying mRNA, miRNA, and lncRNA interactions. Numerous studies have found that ceRNA regulatory axes plus accompanying networks are functional in a range of developmental pathways and pathological situations, including cancer, neurodegenerative diseases , and menLINC00472, ANP32A-IT1, and RBM26-AS1) that function as ceRNAs. Several studies suggest that LINC00472 has an essential function in the inhibition process of tumor development. In acute hepatic damage induced by sepsis and clear cell renal cell carcinoma, LINC00472 controls immune-related genes via functioning as ceRNA for biding to various miRNAs  Tail eXosome Targeting (PAXT) connection promotes the recruiting process of the human ribonucleolytic RNA exosome to nuclear polyadenylated RNA. RBM26, as a new factor, is required for the PAXT function , leading to a regulatory effect on key DEmRNAs. According to the HMDD database, hsa-miR-221-3p is dysregulated in olfactory mucosal stem cells taken from ASD patients in comparison with healthy controls, and hsa-miR-221-3p also exhibits significant neuronal expression in areas crucial for high cognitive skills in the brain of mice (hsa-miR-182-5p may suppress the expression of the immunity‐associated protein family 1 (Gimap1), shown to be reduced in T-helper cell type 17 (Th17) cells and is crucial for Th17 development (MECP2) has an analgesic function in acute and chronic pain development by modulating the CREB/hsa-miR-132-3p pathway. MECP2 is engaged in ASD development and has been connected to neuronal differentiation, synaptic plasticity, and brain development  in a ceRNA manner. PTPN11, also known as SHP2, encodes an unusual protein phosphatase functioning as an activator in different signaling pathways, such as Ras/mitogen-activated protein kinase (Ras/MAPK) signaling pathway, the downstream signaling cascades of other phosphatases are suppressed most of the time. Besides the RAS pathway, it has been demonstrated that SHP2 can also activate the PI3K-AKT pathway, whilst inhibiting the JAK-STAT pathway. In addition, the PTPN11 gene mutations are predominantly related to RASopathies, including Noonan syndrome (NS), and cognitive deficits such as learning disabilities are common in patients with NS  and the peripheral nervous system. In addition to serving as an immunoregulator, a number of cytokines have been considered as neuromodulators as well. Finely tuned cross-talk exists between the immune system and CNS. While the nervous system can modulate the immune response, the immune system is also capable of modulating the nervous system consistently via cytokine activity. More precisely, cytokines that activate the JAK/STAT pathway and their receptors are expressed in various brain cells. In order to maintain CNS homeostasis, both pro- and anti-inflammatory cytokines play significant roles. Different cytokines may result in activation of various sub-pathways associated with the JAK/STAT signaling. Given the significance of this pathway when the immunological responses and homeostasis are regulated in the nervous system, the alterations in JAK/STAT molecules and also the profile of numerous cytokines have implications in ASD . For exaThere are some limitations in our study. Firstly, various parameters, such as sample preparation, the use of different methodologies, data analysis, patient characteristics, and platforms, can affect the gene expression patterns. Secondly, the small size of the sample may result in lower statistical confidence. Finally, the current findings will be validated through confirmative experimental techniques and making a comparison of the findings with modified microarray gene expression obtained from a re-analysis in future studies.LINC00472/hsa-miR-221-3p/PTPN11, ANP32A-IT1/hsa-miR-182-5p/S100A2, LINC00472/hsa-miR-132-3p/S100A2, and RBM26-AS1/hsa-miR-182-5p/S100A2, were identified herein. The observed results are introductory, and additional in vitro and in vivo experiments could profoundly strengthen these findings. While the potential functions of these ceRNA axes demand more in-depth investigation, this research advances the current insights into the immune processes associated with ASD and presents a new perspective into the molecular mechanisms behind ASD pathogenesis.In conclusion, this study is the first to identify lncRNA-associated ceRNA network based on DEmRNAs associated with immune function in ASD. Four possible DElncRNA-miRNA-DEmRNA axes, including


Covering: up to 2021Escherichia coli with a focus on alternative metabolic pathways. Alternative pathways can lead to improved titres by providing higher orthogonality to native metabolism that redirects carbon flux, by avoiding toxic intermediates, by bypassing highly-regulated or bottleneck steps, or by being shorter and thus more efficient and easier to manipulate. The canonical 2-C-methyl-d-erythritol 4-phosphate (MEP) and mevalonate (MVA) pathways are engineered to increase titres, sometimes using homologs from different species to address bottlenecks. Further, alternative terpenoid pathways, including additional entry points into the MEP and MVA pathways, archaeal MVA pathways, and new artificial pathways provide new tools to increase titres. Prenyl diphosphate synthases elongate terpenoid chains, and alternative homologs create orthogonal pathways and increase product diversity. Alternative sources of terpenoid synthases and modifying enzymes can also be better suited for E. coli expression. Mining the growing number of bacterial genomes for new bacterial terpenoid synthases and modifying enzymes identifies enzymes that outperform eukaryotic ones and expand microbial terpenoid production diversity. Terpenoid removal from cells is also crucial in production, and so terpenoid recovery and approaches to handle end-product toxicity increase titres. Combined, these strategies are contributing to current efforts to increase microbial terpenoid production towards commercial feasibility.Terpenoids are a diverse group of chemicals used in a wide range of industries. Microbial terpenoid production has the potential to displace traditional manufacturing of these compounds with renewable processes, but further titre improvements are needed to reach cost competitiveness. This review discusses strategies to increase terpenoid titres in  Terpenoids are a diverse group of chemicals used in a wide range of industries. They can be made through alternative metabolic pathways to reach the higher needed for biomanufacturing. As the world economy turns away from fossil fuels and non-food uses for arable land, the need arises to develop microbial cell factories to produce terpenoids sustainably through fermentation of renewable feedstocks.Terpenoids form one of the largest and most diverse classes of chemicals comprising thousands of structures.§etc.We use the correct name “diphosphate”, but the more frequently used abbreviations IPP, DMAPP,  and dimethylallyl diphosphate (DMAPP), produced from central metabolism via the 2-C-methyl-d-erythritol 4-phosphate (MEP) or the mevalonate (MVA) pathways (Most terpenoids are made in nature from the interconvertible C5 precursors isopentenyl diphosphate (IPP)§pathways . IPP/DMAEscherichia coli is one of the main model organisms for terpenoid production, with vast physiological, biochemical and metabolic knowledge available as well as diverse engineering tools. E. coli is advantageous from an industrial perspective because it accepts a wide range of substrates and grows efficiently under low-cost and large-scale conditions.3 In general, engineered E. coli produces higher levels of hemi-, mono- and tetraterpenoids than other organisms, whereas engineered yeast strains produce higher levels of sesqui-, di- and triterpenoid compounds.4–6 Because E. coli is easy to manipulate, insights gained into the benefits of using this host and discussed in this review, can also be applied to more industrially relevant host bacterial organisms.7,8 but have not yet displaced traditional manufacturing routes that remain less expensive. Techno-economic analyses of microbial terpenoid production identify productivity or yield as a main cost driver and conclude titre improvements could enable commercialisation.9,10 Other cost intensive aspects are also a concern .Advances in the last few decades have dramatically improved microbial terpenoid production. Only a few selected processes however are considered as having the potential to be marginally cost competitive. For example, microbial β-farnesene and semi-synthetic artemisinin production were demonstrated at industrial scales,11 Varied production conditions have led to some of the highest reported titres for different terpenoids  whenever available. We review also titres obtained across different publications to gain insight into conditions that lead to the highest titres for a specific terpenoid. Our rationale is that different strategies that produce high titres are of interest from a learning perspective. Combinatorial approaches, for example, could potentially increase these titres further. In those cases where reported titres are low (i.e. lower than the highest reported titres for a specific terpenoid), the interpretation is more challenging but higher titres may become achievable pending further optimisation. In these cases, these lower titres provide an indication of how much optimisation remains to be done to approach the highest reported values in the literature.Titres are the most commonly reported measure in metabolic engineering programs. Titres, however, can vary based on fermentation time and conditions, expression levels of genetic constructs, enzymatic activity of limiting steps, regulation points in the pathway, genetic background, carbon source and other factors. Table S1. ReporteE. coli has enabled terpenoid production at the g L−1 scale  from central metabolism to form 1-deoxy-d-xylulose 5-phosphate (DXP) catalysed by DXP synthase (DXS) in a thiamine diphosphate-dependent reaction  using NADPH,17 and MEP is activated with cytidine 5′-triphosphate (CTP) to produce 4-diphosphocytidyl-2-C-methyl-d-erythritol (CDP-ME) by CPD-ME synthase (CMS).18 CDP-ME is phosphorylated by CDP-ME kinase (CMK), and cyclised to 2-C-methyl-d-erythritol 2,4-cyclodiphosphate (MEcPP) by MEcPP synthase (MCS).19,20 The cyclic diphosphate ring is opened and a reductive dehydration is catalysed by 4-hydroxy-3-methyl-butenyl diphosphate synthase (HDS) to produce 4-hydroxy-3-methyl-butenyl diphosphate (HMBPP).21–23 Finally, a reductive dehydration of HMBPP by HMBPP reductase (HDR) produces both IPP and DMAPP at a ratio of 5 : 1 in E. coli,23–25 and IPP and DMAPP are interconverted by IPP delta-isomerase (IDI). Because both IPP and DMAPP are produced by the MEP pathway, IDI is not essential in organisms containing the MEP pathway, and many bacteria do not have a gene encoding this enzyme.26The MEP pathway starts with the condensation of pyruvate and reaction .15,16 DX27 CTP is consumed at the CDP-ME step and ATP is consumed at the CMK step. Because CTP loses a diphosphate moiety, it needs 2 ATP molecules for regeneration. Therefore, the MEP pathway consumes 3 NADPH and 3 ATP for each IPP/DMAPP from pyruvate and G3P.28NADPH is consumed in the DXR, HDS and HDR steps.2.1.1The MEP pathway has several regulation points. Overexpression of native genes or expression of heterologous variants for these steps is one of the main strategies to increase terpenoid titres through this pathway.Populus trichocarpa DXS is feedback inhibited by IPP and DMAPP, which compete in the thiamine diphosphate binding pocket.29 This regulation is thought to occur in other species as well. Overexpressing dxs stimulates the MEP pathway and it leads to up to 10-fold titre increases;30–33 this has contributed to some of the highest reported terpenoid titres using the MEP pathway  with two equivalents of NADPH yields the 6-carbon intermediate MVA. MVA is phosphorylated twice in the 5-OH position by ATP, first by mevalonate 5-kinase (M5K) producing mevalonate 5-phosphate (M5P), and then by phosphomevalonate kinase (PMK), resulting in mevalonate diphosphate (MVAPP).49–51 This molecule is further decarboxylated in an ATP-mediated reaction catalysed by mevalonate diphosphate decarboxylase (DMD), producing only IPP.50 DMAPP is obtained from IPP by the action of IDI. The MVA pathway is conceptually divided into an upper pathway, from AcCoA to MVA, and a lower pathway, from MVA to IPP/DMAPP.The MVA pathway starts with a Claisen condensation of two acetyl-CoA (AcCoA) molecules catalysed by an acetoacetyl-CoA thiolase (AACT), producing acetoacetyl-CoA . The addHMGR consumes 2 molecules of NADPH and M5K, PMK and DMD each consume ATP. In total, the MVA pathway therefore uses 2 NADPH and 3 ATP molecules to produce one molecule of IPP/DMAPP from AcCoA.2.2.152 Therefore, fine-tuning relative expression of MVA pathway genes is necessary to reduce accumulation of known toxic intermediates such as HMG-CoA and IPP  can be limiting in 57,59–62 In most organisms, downstream diphosphate intermediates such as IPP, DMAPP, GPP, FPP and GGPP inhibit M5K by binding competitively to the ATP-binding site of M5K.60,63–65Streptococcus pneumoniae M5K is inhibited by MVAPP,66 but Staphylococcus aureus M5K is not.60S. aureus and S. cerevisiae M5K are also inhibited by substrate at millimolar MVA concentrations.57,60 This might explain why MVA can be produced at 30 g L−1,67 whereas high level accumulation of metabolites downstream of this step in the MVA pathway is challenging. PMK was also identified as a bottleneck in an amorphadiene producing E. coli strain. Targeted proteomics indicated poor production of this enzyme in the cell. Codon-optimisation and use of stronger promoters to express the gene increased both enzyme and mRNA transcript levels, with concomitant improvements in amorphadiene titres.68M5K is one of the most regulated enzymes of the MVA pathway and its activity can be inhibited by high levels of substrate and product .57,59–62E. coli has basal levels of IDI activity. However, overexpression of idi leads to higher terpenoid production when using the MVA pathway. Basal IDI levels are relatively low and the MVA pathway requires IDI to balance IPP and DMAPP. Overexpression of IDI in a strain harbouring the MVA pathway was found to increase lycopene titres 10-fold to 22.2 mg L−1.54 Similarly, idi overexpression increases DMAPP supply and leads to increases in β-farnesene titres of almost 200-fold (8.74 g L−1).692.2.265,70,71 These homologs can reduce MVA accumulation and are valuable biocatalysts for terpenoid production compared to traditionally used M5K from S. cerevisiae and S. aureus.72–75 The highest isoprene titres achieved so far use the feedback-resistant Methanosarcina mazei M5K;76 (−)-α-bisabolol titres were increased 1.7-fold, reaching almost 600 mg L−1 by replacing S. aureus M5K with the M. mazei homolog.73 Protein engineering can also be used to improve substrate affinity, and thermal and pH stabilities of feedback-inhibited M5K. An E. coli strain harbouring the S. cerevisiae M5KV13D/S148I/V301E variant produced 1.43 g L−1 lycopene, a titre that is 2.4-fold higher compared to the strain containing the wild-type homolog.77Recruiting better performing homologous enzymes from alternative organisms is often a good strategy to minimise bottlenecks in engineered MVA pathways. For example, recently identified feedback-resistant M5K homologs maintain high activity even in the presence of prenyl diphosphates and MVAPP.S. cerevisiae IDI variant (L141H/Y195F/W256C), which improves lycopene production 1.8-fold, reaching 1.2 g L−1.78 Moreover, type II IDIs recently identified in some archaea,79–81 Gram-positive bacteria82,83 and cyanobacteria84 might also be beneficial in terpenoid production using the MVA pathway when compared to type I IDIs. These type II enzymes differ in amino acid sequence, structure, and reaction mechanism compared to the type I IDIs.84 Use of B. licheniformis type II idi in place of E. coli idi increased lycopene production (from 132 mg g−1 DCW to 181 mg g−1 DCW) in E. coli strains containing the MVA pathway.43 Use of S. aureus type II IDI also increased isoprene levels by 1.57-fold relative to E. coli strains containing the S. cerevisiae idi.74Protein engineering has also been used to generate a catalytically superior Enterococcus faecalis HMGS variant (HMGSA110G) increases isoprene production 1.5-fold relative to strains containing the wild-type homolog, achieving production titres for isoprene of 6.3 g L−1.85 Furthermore, use of five different HMGR homologs has been investigated for amorphadiene production in E. coli.57In vitro assays showed that this enzyme can readily catalyse the reverse reaction. HMGR homologs with a high forward and low reverse reaction rate produced higher mevalonate levels in vivo. Nevertheless, when the MVA pathway harbouring these HMGR homologs was coupled to an amorphadiene producing cassette, the strains that accumulated more mevalonate did not produce the highest amorphadiene titres. The low titre obtained with the high MVA producing strains was attributed to substrate inhibition of M5K.57Use of an et al. (2019) built an MVA pathway using E. faecalis AACT and HMGR, M. mazei M5K, and S. pneumoniae PMK, DMD and IDI for isoprene production.53 This pathway initially produced only 55.4 mg L−1 isoprene, but optimising promoter, plasmid copy number and the gene expression cassette, increased isoprene titres to almost 600 mg L−1.53 Replacing S. cerevisiae enzymes of the upper MVA pathway with E. faecalis homologs increased MVA accumulation 50-fold and isoprene production reached 500 mg L−1.85 Comparing the lower MVA pathways from S. aureus, Streptococcus pyogenes, S. pneumoniae, E. faecalis, and S. cerevisiae in a Coenzyme Q10 producing E. coli strain showed that S. pneumoniae genes led to a higher Coenzyme Q10 content under almost all conditions.47 In a similar study, the S. pneumoniae, S. pyogenes, S. aureus, E. faecalis and S. cerevisiae lower MVA pathways were compared to produce β-carotene supplying MVA as substrate. In this case, the S. pneumoniae and S. cerevisiae pathways were shown to be the best performers.86In a more integrated approach, Liu E. coli for the production of most terpenoids – especially the hemi-, mono- and sesquiterpenoids – are obtained through heterologous expression and engineering of the MVA pathway. That said, the highest reported titres for some diterpenoids and lycopene have been obtained using optimised MEP pathways  and that are readily accessed through modified terpenoid biosynthetic pathways.94Canonical terpenoid pathways have been extensively engineered and optimised, but only a small number of terpenoids have been obtained at levels that might be considered as being attractive for commercial production. Variations of existing canonical pathways, or the development of fundamentally new precursor pathways, are alternative engineering approaches of potential benefit. Such strategies can give rise to higher degrees of orthogonality, or by replacing specific steps in existing pathways with metabolite shunts, bypass regulation points and/or avoid the accumulation of potentially toxic intermediates. Inclusion of alternative substrates and biocatalysts in biosynthetic pathways can also increase terpenoid diversity and lead to the production of compounds that are of potential commercial value  in E. coli. Fusing the RibB variant to DXR further increases bisabolene content (to 9 mg g−1 DCW).95Because DXS is one of the most regulated steps in the MEP pathway, alternative pathways to DXP could potentially increase carbon flux towards terpenoid biosynthesis. The structural similarity between DXP and other pentose phosphates has inspired the use of two hosphate .95,96 OvE. coli. In this pathway, a first module of genes degrades exogenous d-arabinose to glycolaldehyde and hydroxyacetone, which are subsequently condensed by a second module consisting of fructose-6-phosphate aldolase to produce 1-deoxyxylulose. This latter compound is then promiscuously phosphorylated by xylulose kinase to DXP  was identified as the missing intermediate between M5P and IPP, and an isopentenyl phosphate kinase (IPK) was found to be responsible for the conversion of IP to IPP   . This st113 DMD and PMD phosphorylate the hydroxyl in the 3-C position of MVAPP and M5P to produce IPP and IP, respectively.113,115,116 PMD loses kinase activity at low pH, but the decarboxylase activity remains intact, becoming a BMD.113 Therefore, there was potentially a need to evolve two separate enzymes that are homologous to PMD (M3K and BMD) to give rise to this alternative pathway.113 Of interest is that the phosphorylation in the 3-OH position and the decarboxylation of M3P are not sequential steps catalysed by the same enzyme  but rather are catalysed by two enzymes. There is also an additional step, a phosphorylation at the 5-OH position that needs a third enzyme from a different family.117The use of two different specialised enzymes (M3K and BMD) to catalyse a decarboxylation step performed by a single enzyme  could have arisen from an adaptation to extremely acid environments that did not favour the canonical pathway.63 Consequently, an alternative pathway that by-passes this enzyme is of potential interest for terpenoid production. M3P accumulates in T. acidophilum and could be used to increase terpenoid production by heterologous expression of this alternative MVA pathway in E. coli.This pathway requires one more catalytic step compared to the canonical pathway, but has the same ATP requirement. As discussed above, the phosphorylation of MVA by M5K in the classical MVA pathway is one of the most heavily regulated enzymatic steps in the pathway.Picrophilus torridus M3K was also used among other homologs to decarboxylate MVA and produce isoprenol in vivo and in vitro without needing to pass through IPP as an intermediate.118 In a different strategy, M3K was converted into a mevalonate 3-phosphate 5-kinase via a single amino acid substitution, and used with the archaeal MVA pathway I to produce approximately 0.347 μg lycopene per mg wet cells. This value is comparable to 0.491 μg lycopene/mg wet cells using the S. cerevisiae classical MVA pathway.119E. coli. This would be of interest as it lacks one of the most regulated steps found in the canonical MVA pathway. Moreover, it would also be of interest to express both the archaeal MVA pathway II and the canonical MVA pathway together to explore any synergistic effects. M3K consumes MVA, and could thus potentially relieve substrate inhibition of M5K.A complete archaeal MVA pathway II has not been tested in 3.2.3Aeropyrum pernix, mevalonate 5-phosphate dehydratase and trans-anhydromevalonate 5-phosphate decarboxylase, responsible for converting M5P to IP through a new intermediate, trans-anhydromevalonate 5-phosphate  and reducing ATP consumption .There are very few examples of heterologous expression of any of the archaeal MVA pathways in 3.346 because it is converted to a toxic prenyl-ATP analog,123 and therefore strategies that bypass IPP can be beneficial by preventing IPP accumulation. Additionally, IPP-bypass pathways can reduce the number of metabolic steps and avoid competition for IPP with native metabolism and negative-feedback regulation. For example, combining the upper MVA pathway with a bacterial Jeotgalicoccus sp. ATCC 8456 fatty acid decarboxylase and a bacterial Elizabethkingia meningoseptica oleate hydratase led to isoprene production in E. coli.124 In this shorter pathway, MVA is decarboxylated directly to isoprenol (−1 isoprene using only two enzymatic steps from MVA (instead of five). This approach led to improved terpenoid levels, exceeding the highest titre achieved using the MEP pathway (314 mg L−1),31 but substantially lower than the highest titre achieved using a canonical MVA pathway (60 g L−1).76 Nonetheless, a shorter pathway could be beneficial when subjected to further titre optimisation .IPP accumulation is undesirablesoprenol , which i125–127 Isoprenol production at up to 10.8 g L−1 has been achieved in fed-batch cultures, the highest titre reported to date for this compound.126,127Similarly, new pathways that utilise decarboxylation of M5P by a variant DMD (to produce IP) and endogenous phosphatases (to dephosphorylate IP into isoprenol) have been reported .125–127 128Although promising for hemiterpenoids, these reduced MVA pathways have not been exploited for longer terpenoid products because they bypass the common building blocks IPP and DMAPP. Because TPSs require IPP/DMAPP and their derivatives, these are the only orthogonal pathways to terpenoids that branch before IPP/DMAPP.3.4129–134 This pathway decouples terpenoid biosynthesis from central metabolism and therefore has the potential to increase metabolic flux towards the production of terpenoids.135 The pathway also reduces any negative impacts on cell growth, since glucose  is reserved for primary metabolism.136 The first of the three steps in this pathway involves phosphorylation of exogenously added isoprenol or prenol to produce IP or DMAP. These are then converted by IPK to IPP or DMAPP, respectively H  to obtain DMAPP from AcCoA, with isoprenol and prenol as intermediates. This new pathway produces 0.6 g L−1 of geranoids.Because the first reaction has not been found in existing metabolic pathways, several enzymes were tested to identify promiscuous kinase activity towards isoprenol and prenol. This new pathway was developed using 37,138 Shorter and orthogonal pathways are less regulated. This makes them easier to optimise compared to the canonical MEP and MVA pathways, which have been iteratively optimised over the past two decades. Consequently, the use of fed-batch processes and relatively simple pathway improvements may lead to competitive production strains after only a few rounds of pathway/strain optimisation.Titres obtained with isoprenol and prenol-derived pathways are generally lower compared to canonical pathways. However, in selected cases titres are promising and higher than those reported using canonical pathways.3.5139 but recently discovered modifications in canonical pathways have allowed the biosynthesis of terpenoids outside this rule (e.g. methyl group addition) can improve biological activity,140 or generate novel organic structures that are otherwise difficult to obtain.The large majority of terpenoids comprise C5 modules and follow the so-called ‘isoprene rule’,his rule . These o141 catalysed by a S-adenosyl-l-methionine-dependent methyl transferase  with IPP. In E. coli. Plant Abies grandis GPP synthase (AgGPPS) is the PPPS that leads to the highest monoterpenoid titres in E. coli  in direct comparisons.182 However, in two instances, S. cerevisiae FPPS outperformed IspA.183,184 ScFPPS is less catalytically efficient than IspA and this might be a reason for why IspA is often selected over ScFPPS.183 Several plant GGPP synthases (GGPPS) have also been used in some of the highest reported diterpenoids titres40,45,89,185–187 , the cis-isomer of GPP, then to Z,Z-FPP, the all-cis-isomer of the more common all-trans E,E-FPP, and then to nerylneryl diphosphate (NNPP), the all-cis-isomer of GGPP  diverts the metabolic flux from IPP/DMAPP to monoterpenoids instead of to FPP .75 This suggests that either the NPP pathway enzymes are more active, which is not the case in yeast,198 or alternatively that NPP bypasses competition with FPP for GPP in E. coli. Further optimisation showed that SlNPPS is efficient enough to sustain limonene production in E. coli to as much as 1.29 g L−1 limonene,75 an amount comparable to the highest reports obtained with other strategies.58,138,160,171 Thus, NPPS can sustain at least as much production as other approaches, and could produce higher titres under different conditions.Competition with FPP in Mycobacterium tuberculosis Z,E-FPPS was used in E. coli to produce Z,E-farnesol from exogenous MVA. Z,E-FPP is likely not incorporated into native E. coli metabolism, therefore creating an orthogonal pathway.205 Also, S. lycopersicum NNPP synthase (NNPPS) and lycosantalonol synthase were used in E. coli to demonstrate biosynthesis of the diterpenoid lycosantalene.188 Beyond these examples, cis-prenyl diphosphates longer than NPP have not yet been explored in E. coli or compared to trans-prenyl diphosphate pathways. However, they could be useful for the production of longer terpenoids if the native PPPSs and TPSs are trans-specific; the cis-prenyl diphosphates can then redirect carbon flux to the terpenoid of interest  is first ionised to form a carbocation and then undergoes a nucleophilic attack by the double bond of IPP followed by proton elimination to form the elongated allylic diphosphate.207,208 Shorter terpenoids formed in a non-head-to-tail fashion are very rare, but mono- and sesquiterpenoids with these irregular structures are found for example in plants209 and marine bacteria.210 A plant Lavandula x intermedia PPPS catalyses a head-to-middle condensation of two DMAPP molecules to generate lavandulyl diphosphate, the precursor of (R)-lavandulol and (R)-lavandulyl acetate.209,211 Also, a plant Chrysanthemum cinerariaefolium PPPS catalyses the cyclopropanation of two DMAPP molecules to form the irregular diphosphate chrysanthemyl diphosphate.209,212 Other irregular short diphosphates include cyclolavandulyl, maconellyl, planococcyl and isosesquilavandulyl diphosphates and are converted to short irregular terpenoids.213 To the best of our knowledge, E. coli has not been used as a platform to produce short terpenoids from non-head-to-tail condensations. Expressing and engineering these alternative PPPS could potentially create orthogonal terpenoid biosynthetic pathways similar to the examples listed above with cis-PPPS, and further diversify terpenoid molecules.Some PPPSs catalyse alternative reactions to form non-head-to-tail connected terpenoid skeletons . These r214 Recently, several class I terpenoid cyclases were also found to be bifunctional and able to work as aromatic prenyltransferases. These enzymes catalyse the condensation of DMAPP or GPP and indole to produce prenylated indole compounds in E. coli. This activity might be more widely spread among terpenoid cyclases, opening up a strategy to decrease the accumulation of toxic phosphorylated intermediates such as DMAPP.214 A distant relationship between prenyltransferases and terpenoid cyclases was identified recently that revealed a new family of prenyltransferases, which uses a repurposed terpenoid cyclase structural fold to prenylate glutamic acid.215Terpenoid cyclases promote changes in terpenoid structure by catalysing reactions which generate multiple rings and stereocentres.in vitro studies,216–219 and were reviewed recently.220 Because these irregular and modified prenyl diphosphates differ structurally from their native counterparts, they could be used to create orthogonal pathways to terpenoids in E. coli, or expand the end-product range.Other prenyltransferases generated different diphosphate molecules, including chlorinated analogues, molecules having a hydrophilic moiety in their alkyl chain, or cyclic diphosphate molecules in previous 5E. coli and most of the highest titre reports use genes of plant origin  produces 23.4 mg L−1 1,8-cineole, comparable to 23.6 mg L−1 1,8-cineole produced with plant Salvia fruticosa CinS, and higher than 9.4 mg L−1 1,8-cineole produced with plant A. thaliana CinS and 3.6 mg L−1 1,8-cineole produced with plant Citrus unshiu CinS in a direct comparison.225,226 In this case, the bacterial enzyme also produced almost exclusively 1,8-cineole which is not the case with plant enzymes (96% vs. 42–67%). In an independent study, the same S. clavuligerus CinS produces 228 mg L−1 1,8-cineole, consistently higher but comparable to 200 mg L−1 using the fungal Hypoxylon sp. CinS. Further optimisation allows production of 653 mg L−1 1,8-cineole using this bacterial CinS,165 the highest 1,8-cineole titre in E. coli reported so far. Additionally, bacterial S. clavuligerus linalool synthase (LinS) allowed accumulation to 72.7 mg L−1 linalool, 300 times the 0.26 mg L−1 linalool titre produced by plant Artemisia annua LinS.225,226 When comparing the highest reported titres, bacterial LinS led to more linalool accumulation than plant LinS: 1.03 g L−1 linalool was produced with bacterial S. clavuligerus LinS,159 whereas 601.2 mg L−1 linalool was produced with a fungal LinS,227 505 mg L−1 linalool with plant Mentha citrata LinS165 and approximately 85 mg L−1 linalool with plant Clarkia breweri LinS.228 Thus, whereas several eukaryotic monoterpenoid synthases were screened to find high producers in E. coli, the only two identified bacterial monoterpenoid synthases produced higher or comparable titres to the best eukaryotic synthases.In contrast, bacterial enzymes are more similar to Streptomyces griseus (+)-caryolan-1-ol synthase makes up to 406 mg L−1 sesquiterpenoids in E. coli including 100 mg L−1 caryophyllene and 10 mg L−1 caryolan-1-ol .229 A bacterium such as E. coli might be the preferred chassis for production of these and other terpenoids made by bacterial TPSs. For example, the bacterial S. clavuligerus LinS that produced one of the highest linalool titres in E. coli produces none in S. cerevisiae, even though linalool can be produced in S. cerevisiae with plant M. citrata LinS.230 Also, bacterial Streptomyces coelicor epi-isozizane synthase and Streptomyces UC5319 pentalenene synthase produced 728 mg L−1epi-isozizaene and 780 mg L−1 pentalenene in E. coli, respectively, whereas 344 mg L−1 pentalenene was obtained in S. cerevisiae, although less titre optimisation was applied to the latter.231Most of the TPS diversity comes from plant enzymes, but for a few terpenoids, only bacterial TPSs have been found, which highlights the value of bacterial TPSs despite the difficulty in identifying them. For example, E. coli and obtain high terpenoid titres, the N-terminal domain that contains a signal peptide for membrane insertion is usually modified to direct the protein to the plasma membrane, or truncated to direct to the cytosol.232,233 Thus, eukaryotic CYPs are successfully used for high-titre terpenoid production in E. coli. For example, plant Artemisia annua CYP71AV1 was used to make 105 mg L−1 artemisinic acid, which can be converted to the antimalarial artemisinin,174 and the plant Taxus brevifolia CYP taxadiene 5α-hydroxylase was used to make 58 mg L−1 taxadien-5α-ol.40 However, even following N-terminal domain engineering, eukaryotic CYPs are poorly expressed and have low activity in E. coli as eukaryotic CYPs are usually bound to the ER.174 The recent focus on bacterial terpenoid pathways is also identifying bacterial CYPs that have been used for terpenoid production in E. coli.234 Notable examples include using Bacillus megaterium CYP102A1 (BM3) engineered to change substrate specificity to convert amorphadiene to 250 mg L−1 artemisinic-11S,12-epoxide, which can in turn be converted to artemisinin,173 and Mycobacterium HXN-1500 CYP153A6 to convert limonene to 105 mg L−1 perillyl alcohol.138 To reach high terpenoid titres, CYPs require reducing partners, which work well at a ratio lower than 1 : 1. It is not a trivial exercise to determine which partners will work well with specific CYPs so several are often tested.235,236Subsequent enzymes functionalise the terpenoid backbones made by TPSs and increase terpenoid diversity, creating additional molecules with biological activities of interest. Oxidations are usually catalysed by cytochromes P450 (CYPs) and eukaryotic CYPs are more abundant. CYPs are membrane proteins and so to enhance expression in E. coli  in the thousands of bacterial genomic sequences currently available, mostly in the Streptomyces genus.245 Experimental validation has confirmed the activity of over 70 bacterial TPSs for two monoterpenoids , over 40 sesquiterpenoids and over 30 diterpenoids.240,245–247 Therefore, there are a growing number of bacterial TPS candidates that could be used for terpenoid production.One of the challenges of identifying bacterial TPSs and modifying enzymes is that pathways for natural products biosynthesis are often silent under standard laboratory culture conditions. However, the advent of inexpensive whole-genome sequencing has made thousands of bacterial genomes available for mining of terpenoid pathways and new TPSs. Bacterial TPSs have been elusive because of low whole sequence similarity with eukaryotic TPSs. Recently, Hidden Markov Models, which are trained with known sequences to create profiles that might encode functionality, were used to identify candidate bacterial TPS.248 Genes that encode natural product biosynthetic pathways are often clustered in genomes,249 and this is also true for the terpenoids, where TPS genes are physically close to genes for CYPs and other modifying enzymes. Therefore, identification of biosynthetic gene clusters is useful in genome mining.250 The bacterial genomes database “Antibiotics and Secondary Metabolites Analysis Shell” counts over 5000 putative terpenoid biosynthetic gene clusters.251 So far, over 70 clusters have been characterised and deposited in the Minimum Information about a Biosynthetic Gene cluster database with nucleotide sequences and product descriptions.252With the demonstrated benefits of using bacterial TPSs and modifying enzymes, identification of new bacterial terpenoids and the characterisation of associated terpenoid pathways among the thousands of available genomic sequences is attractive. As pathways are often silent, different culturing conditions might need to be used to induce genes and identify compounds.E. coli, Streptomyces or other bacterial strains to identify products,253 and manipulation of native genomes to activate silent clusters.254 Additionally, omics approaches are also being used. For example, genomics are correlated with metabolomics in groups of closely related species with different terpenoid profiles to match metabolites to conserved gene clusters.255 Many of these approaches can be accelerated using high-throughput automated assembly, screening and MS analysis.256,257 Consequently, new bacterial terpenoid biosynthetic pathways will be identified and utilised in future high-titre production in E. coli or other bacterial hosts.The challenge is to characterise the large and growing number of remaining cryptic clusters. Natural product pathways can be characterised by laboriously expressing single genes or assembling putative pathways, but recent methodologies allow expression of whole gene clusters in 66.1E. coli growth at g L−1 levels .260 Hydrocarbons with log P between 1 and 4 partition easily into membranes and therefore can be toxic;258 above log P 4 water solubility also determines toxicity.260In general, terpenoids are hydrophobic hydrocarbons and therefore can accumulate in biological membranes and increase membrane permeability, thus disrupting vital biological processes  variant alleviates toxicity.264 Another example is that of geraniol; in one report, 75 mg L−1 exogenous geraniol reduces growth rate and 300 mg L−1 inhibits growth entirely,163 whereas similar terpenoids are toxic in the g L−1 range  transporter in the inner membrane, TolC, an outer membrane channel, and AcrA, an accessory protein in the periplasmic space that mediates interaction between AcrB and TolC to export the substrate through the two membranes.269 Overexpressing tolC increases amorphadiene titres from approximately 45 mg L−1 to approximately 160 mg L−1.270 However, overexpressing acrAB has modest, if any, effect on pinene titres, which range from 7.3 to 8.1 mg L−1.271 Also, overexpressing tolC is reported to increase amorphadiene titres from 250 mg L−1 to approximately 350 mg L−1 but kaurene production is perhaps not significantly affected (from approximately 17 mg L−1 to approximately 21 mg L−1). Combining efflux pump components can also further increase titres. Overexpressing acrB and two copies of tolC increases titres to 404.8 mg L−1 amorphadiene and overexpressing acrA, acrB and tolC increases titres to 31.76 mg L−1 kaurene.187 AcrAB-TolC is positively regulated by MarA, a global transcriptional factor that induces efflux pumps.272 Overexpression of marA allows growth on 8.9 g L−1 geraniol, which otherwise completely inhibits growth, and reduces intracellular geraniol levels from 12.9 μg mg−1 to 6.3 μg mg−1, suggesting that efflux pumps might act by reducing intracellular terpenoid concentrations.273The multiprotein AcrAB-TolC is the main E. coli pumps also increase terpenoid titres. For example, overexpressing mdlB, which encodes a putative ABC transporter, increases isopentenol titres by 12% to 931 mg L−1.274 Also, overexpressing msbA, which encodes an ABC transporter that transports the lipid A-core moiety of lipopolysaccharide from the inner leaflet to the outer leaflet of the inner membrane, increases canthaxantin 4.4-fold from approximately 39 μg L−1 to approximately 170 μg L−1 and β-carotene also 4.4-fold to approximately 250 μg L−1.261Other Alcanivorax borkumensis YP_692684 modestly increases limonene titres from approximately 35 mg L−1 to approximately 55 mg L−1.275 In addition, expressing Salmonella enterica serovar typhimurium msbA with a mutation that results in a I89T change increases zeaxanthin 2.4-fold from approximately 100 μg L−1 to approximately 249 μg L−1 and secreted lycopene 4.3-fold from approximately 48 μg L−1 to approximately 210 μg L−1.261 Expressing Pseudomomas putida ttgB however has very modest (if any) effects on titres (from 8.1 to 9.1 mg L−1 pinene).271Expressing pumps from other organisms also improves tolerance and production. For example, expressing 187 Also, when testing a group of pumps, StMbsA increases zeaxanthin and lycopene titres the most, whereas EcMbsA increases canthaxanthin the most.261 Similarly, several pumps that increase amorphadiene production do not increase lycopene production.270Efflux pumps differ in terpenoid specificity. For example, a combination of efflux pumps that is optimal for increasing amorphadiene titres is different than the optimal combination for increasing kaurene titres.276 Export could be improved through protein engineering to increase specificity and/or activity, particularly with AcrB, which recognises substrates in the cytosol and the inner membrane. Importantly, use of inducing pumps have not yet been reported in most of the higher titre producing systems where they would be expected to be the most beneficial.Therefore, the use of efflux pumps seems to provide some advantage, although the effects in titre can be modest. This suggests that terpenoid production is affected by terpenoid toxicity or intracellular accumulation, but the effects so far are limited, providing about 4-fold titre increase at most. The limitation might be because overexpressing pumps also inhibit bacterial growth.6.4E. coli genes that ‘bend’ membranes when overexpressed, causing invaginations and increasing levels of membrane constituents. For example, overexpressing tsr, which encodes a methyl-accepting chemotaxis protein, promotes the formation of membrane invaginations and extensions, and increases squalene titres 2.3-fold from 272 to 612 mg L−1, the highest squalene titre reported to date.277 Similarly, overexpressing almgs, which encodes monoglucosyldiacylglycerol synthase, causes membrane extension and improves β-carotene titres 1.5-fold from 24.7 mg L−1 to 36.9 mg L−1. Also, overexpressing two genes involved in diglyceride-3-phosphate biosynthesis increases glycerophospholipids (membrane components) and β-carotene titres 1.3-fold (to 31.3 mg L−1). Overexpressing these last three genes together leads to a further synergistic improvement, increasing titres 4.2-fold relative to the parental strain to 103.5 mg L−1 β-carotene. In a separate β-carotene hyperproducing strain, this membrane engineering leads to a 1.4-fold titre increase from 196.3 mg L−1 to 268.1 mg L−1 β-carotene.278 These early results show promise for further rounds of membrane engineering, combining membrane-altering factors to increase storage capacity and terpenoid titres while preserving cell integrity and growth rates.Because terpenoids accumulate in membranes, extending membranes can increase the storage capacity for terpenoids and lead to higher terpenoid production while still allowing cellular functions. There are several 6.5E. coli excretes outer membrane vesicles when deleting tolA or tolR, which encode components of the Tol complex that maintains outer membrane integrity, or nlpI, which encodes an outer membrane-bound protein that might contribute to protein complex formation. Thus, deleting nlpI together with either tolA or tolR increases β-carotene excretion and total production. Additionally, overexpressing genes in the biosynthetic pathway of phosphatidylethanolamine, the main phospholipid in E. coli membranes, to supply additional membrane for the excretion further increases β-carotene production 71-fold relative to the parent strain . Carrying out similar changes in a β-carotene hyperproducing strain leads to a similar 24-fold production increase relative to the parent strain (reaching 44.8 mg g−1 DCW β-carotene279).An alternative way of removing terpenoids from cells is to stimulate excretion. 6.6E. coli grown on media supplemented with pinene increases tolerance from 5 to 20 g L−1, and increases titres by 31% to 7.3 mg L−1 pinene.271 Also, evolving E. coli to grow on increasing sabinene concentrations from 3 g L−1, below the initial point of no growth at 3.5 g L−1, to 12 g L−1 generates a strain with 8-fold increased production (from 22.8 mg L−1 to 191.8 mg L−1). In this strain, a large number of genes have mutations or altered expression levels. Three genes in particular contribute to sabinene tolerance: ycbK, scpA, and ygiZ. ycbK is a gene of unknown function that belongs to the defective Lambda prophage 12 family with roles in biofilm formation, stress response and cell wall maintenance. scpA encodes methylmalonyl-CoA mutase and affects central metabolism. ygiZ encodes an internal membrane protein of unknown function and is induced by the BglJ-RcsB transcriptional activator that regulates motility, biofilm formation and stress responses. Overexpressing ycbK or scpA increases sabinene titres approximately 2-fold, but overexpressing ygiZ decreases sabinene titres.280 This work illustrates the multi-causality of toxicity and how engineering tolerance might require a multi-pronged approach involving several relevant cellular processes simultaneously and mechanisms we still do not fully understand.Because toxicity is multi-causal and can be specific to each terpenoid, adaptive laboratory evolution experiments which address toxicity in a more general fashion are a good strategy to increase terpenoid titres. Adaptive laboratory evolution on E. coli cultivation with isopentenol. Six of these genes involved in oxidative stress response (fpr), general stress response , heat shock-related response (ibpA) and transport (mdlB) increase isopentenol titres when overexpressed. Overexpressing metR, which encodes a DNA-binding transcriptional activator, leads to the highest improvement . Like efflux pumps, genes granting tolerance and titre increases might be terpenoid specific. For example, overexpressing Marinobacter aquaeolei VT8 yceI improves resistance to pinene and terpinolene, but not to limonene or terpinene.281Similarly, other genes increase terpenoid resistance and production titres but by poorly defined mechanisms. For example, several genes are upregulated in response to 6.7282 This approach was partially applied to the particularly toxic geraniol, which reduces growth rate at 75 mg L−1 and fully inhibits growth at 300 mg L−1.163 In contrast, geranyl acetate, an esterified derivative of geraniol, reduces final optical density (OD) by 40% at 4.6 g L−1 but then no further reduces OD up to 45.8 g L−1 . Therefore, expressing the gene encoding Rosa hybrida alcohol acetyltransferase in E. coli to catalyse intracellular esterification of geraniol increases titres from 35 mg L−1 geraniol to 375 mg L−1 geranyl acetate, which represents a more than 8-fold molar increase. By further optimising conditions, 4.8 g L−1 geranyl acetate was produced,163 over 2-fold higher than the previously reported maximum of 2 g L−1 geraniol.162,170 Esterification also prevents spontaneous conversion to toxic geraniol derivatives. Conversion of geranyl acetate back to geraniol however was not discussed in this report. To that end, an endogenous E. coli acetylesterase hydrolyses geranyl acetate to geraniol.162 So far it has been used to increase geraniol levels by preventing spontaneous conversion to geranyl acetate, but has not yet been utilised in a bioderivatisation strategy of the type described above. Expressing this acetylesterase with a secretion tag that allows reconversion outside the cell could potentially enable recovery of geraniol when using bioderivatisation approaches.Bioderivatisation consists of converting the target terpenoid to a less toxic derivative inside the cell to enable accumulation to high titres and subsequently reconverting the derivative to the original target terpenoid.In summary, several approaches have been used separately in attempts to mitigate product toxicity. In many cases, the benefits are modest but a combination of approaches could in principle give rise to synergistic effects. Available evidence suggests that further combinatorial analysis of these types of approaches is warranted.7283,284 The studies described in this review have helped to validate the use of enzymes within a pathway context and provide useful frameworks for further optimisation to reach high-titre terpenoid production. It goes without saying that enzyme engineering, including both rational design and directed evolution, will continue to contribute to this field. This might involve the engineering of enzymes that are more resistant to feedback control, or enzymes with improved catalytic efficiency, or new specificities towards desired target activities/products.77,137,168,173,186,198,257,285,286 The use of alternative and artificial pathways with this ever-expanding enzyme resource and pathway engineering tools should extend current capabilities, thereby allowing high-titre production of a wide range of terpenoids in E. coli and other microbial species.The use of alternative and artificial biosynthetic pathways is now demonstrated for the production of terpenoids in metabolic engineering programs . The eveExtensive studies of the MEP and the MVA pathways have demonstrated that balancing is required to (i) avoid the accumulation of toxic intermediates, (ii) overcome the limiting effects of regulation and (iii) optimise metabolic flux. Complete understanding of canonical pathway regulation and how accumulation of pathway intermediates limits flux remain to be elucidated. This is necessary to inform pathway balancing realised through engineering and modelling, and will likely involve combinatorial approaches that address a range of issues of the type identified in this review.e.g. promoters, ribosome binding sites)287–289 to identify improved pathways and target compound production,41,256,290 with an increased emphasis on the use of data-driven predictive engineering.289,291,292 Establishing high-throughput screening protocols for terpenoids beyond available low sensitivity and non-specific methods will be important.293 Currently, GC-MS is widely used in the field but suffers from low throughput. Amongst others, developments in high-throughput GC-QTOF, which measures terpenoids from the small volumes of multi-well plates, is potentially an attractive approach.257High-throughput methodologies that harness automation and miniaturisation to construct and assess the capabilities of newly engineered strains will become increasingly important to assemble new genetic constructs and test terpenoid production. Automated Design-Build-Test-Learn platforms that are embedded in biofoundry approaches for microbial strain engineering will provide the basis for such work. This will enable rapid exploration of DNA parts . Ultimately, production from renewable feedstocks is required. Limited examples are available, such as the production of pinene from pre-treated switchgrass302 and hydrolysed macroalgae,303 and isopentenol produced from pre-treated and hydrolysed lignocellulose.304 Production may need also to migrate into industrial production hosts to take advantage of agricultural or industrial feedstock waste streams, or carbon dioxide.305,306 There is clearly much to do. This review will hopefully define some of the key challenges and strategies to achieve high level production of terpenoids in E. coli. The hope is that through this expanding knowledge base large-scale production of terpenoids using microbial cell factories will become a reality.Balancing central metabolism precursors, replacing the carbon source, modifying the energy and reducing power balance in the cell, and other approaches will also need to be explored alongside the engineering of new biosynthetic pathways. Redirecting carbon flux and balancing precursor levels are known to increase terpenoid levels,8AACTAcetoacetyl-CoA thiolaseABCATP binding cassetteAcAcCoAAcetoacetyl-CoAAcCoAAcetyl-CoAAgGPPSAbies grandis geranyl diphosphate synthaseAMPDtrans-Anhydromevalonate 5-phosphate decarboxylaseARAldehyde reductaseBMDMevalonate biphosphate decarboxylaseCPD-MEC-methyl-d-erythritol4-Diphophocytidyl-2-CDP-MEPC-methyl-d-erythritol 2-phosphate4-Diphophocytidyl-2-CinS1,8-Cineole synthaseCMKC-methyl-d-erythritol kinase4-Diphophocytidyl-2-CMSC-methyl-d-erythritol synthase4-Diphophocytidyl-2-CTPCytidine 5′-triphosphateCYPCytochrome P450DHAPDihydroxyacetone phosphateDMAPDimethylallyl phosphateDMAPPDimethylallyl diphosphateDMDMevalonate diphosphate decarboxylaseDXd-xylulose1-Deoxy-DXPd-xylulose 5-phosphate1-Deoxy-DXRd-xylulose 5-phosphate reductoisomerase1-Deoxy-DXSd-xylulose 5-phosphate synthase1-deoxy-FPPFarnesyl diphosphateFPPSFarnesyl diphosphate synthaseFSAFructose-6-phosphate aldolaseG3Pd-Glyceraldehyde 3-phosphateGAGlycolaldehydeGGPPGeranylgeranyl diphosphateGGPPSGeranylgeranyl diphosphate synthaseGPPGeranyl diphosphateGPPSGeranyl diphosphate synthaseHAHydroxyacetoneHDR4-Hydroxy-3-methyl-butenyl diphosphate reductaseHDS4-Hydroxy-3-methyl-butenyl diphosphate synthaseHMBPP4-Hydroxy-3-methyl-butenyl diphosphateHMG-CoA3-Hydroxy-3-methylglutaryl-CoAHMGR3-Hydroxy-3-methylglutaryl-CoA reductaseHMGS3-Hydroxy-3-methylglutaryl-CoA synthaseIDIIsopentenyl diphosphate delta-isomeraseIPIsopentenyl phosphateIPKIsopentenyl phosphate kinaseIPPIsopentenyl diphosphateLinSLinalool synthaseM3KMevalonate 3-kinaseM3PMevalonate 3-phosphateM3P5KMevalonate 3-phosphate 5-kinaseM3P5PMevalonate 3,5-biphosphateM5KMevalonate 5-kinaseM5PMevalonate 5-phosphateMB3-Methyl-2-butenalMB-CoA3-Methyl-2-butenoyl-CoAMCSC-Methyl-d-erythritol 2,4-cyclodiphosphate synthase2-MEcPPC-Methyl-d-erythritol 2,4-cyclodiphosphate2-MEPC-Methyl-d-erythritol 4-phosphate2-MGMethylglyoxalMG-CoA3-Methylglutaconyl-CoAMGSMethylglyoxal synthaseMVAMevalonateMVAPPMevalonate diphosphateNNPPNerylneryl diphosphateNNPPSNerylneryl diphosphate synthaseNPPNeryl diphosphateNPPSNeryl diphosphate synthaseODOptical densityPMDMevalonate 5-phosphate decarboxylasePMDhPhosphomevalonate dehydratasePMKPhosphomevalonate kinasePPPSPrenyl diphosphate synthaseSlNPPSSolanum lycopersicum neryl diphosphate synthasetAHMPtrans-Anhydromevalonate 5-phosphateTPSTerpenoid synthaseXKd-Xylulose kinasezFPPSZ,Z-Farnesyl diphosphate synthase9MAR: conceptualisation, visualisation, writing – original draft, writing – review & editing. CAF: conceptualisation, writing – original draft, writing – review & editing. NSS: conceptualisation, supervision, funding acquisition, writing – review & editing.10There are no conflicts to declare.NP-039-D1NP00025J-s001


Salvia miltiorrhiza can alleviate acute pancreatitis. Initially, the active components of Salvia miltiorrhiza and the targets collected from the GeneCards database were screened based on the platform of systematic pharmacology analysis of traditional Chinese medicine. Subsequently, the active components were intersected with the disease targets. Also, interactions among the targets were computed using the STRING database. Biological function and pathway enrichment were analyzed using the Cluster Profiler package in the R software. Protein-protein interaction and component target pathway network were constructed using the Cytoscape software. Ultimately, the key targets and their corresponding components in the network were verified using the AutoDock Vina software. The results showed Salvia miltiorrhiza had 111 targets for acute pancreatitis. The biological process (BP) analysis showed that the active components of Salvia miltiorrhiza induced a drug response, positive regulation of transcription by RNA polymerase II promoter, signal transduction, positive regulation of cell proliferation, and negative regulation of apoptosis. Furthermore, the KEGG enrichment analysis screened 118 (P < 0.05) signaling pathways, such as the pathways related to cancer, neuroactive ligand-receptor interaction, PI3K-Akt signaling pathway, and cAMP signaling pathway, to name a few. Finally, molecular docking showed that the active components of Salvia miltiorrhiza had a good binding affinity with their corresponding target proteins. Through network pharmacology, this study predicted the potential pharmacodynamic material basis and the mechanisms by which Salvia miltiorrhiza can treat acute pancreatitis. Moreover, this study provided a scientific basis for mining the pharmacodynamic components of Salvia miltiorrhiza and expanding the scope of its clinical use.Using network pharmacology and molecular docking, this study investigated the molecular mechanisms by which the active components in  Salvia miltiorrhiza, an inexpensive and easily available traditional medicine, may be used as a routine drug in the comprehensive treatment of AP. It promotes blood circulation, removes blood stasis, dredges channels, relieves pain, dilates microvessels, and improves microcirculation. Clinical studies reported the significant role of [Salvia miltiorrhiza in the treatment of AP. However, the specific mechanism by which Salvia miltiorrhiza can alleviate AP is unclear. Further studies are required to identify the specific disease targets of the components of Salvia miltiorrhiza.Acute pancreatitis (AP) is a common clinical inflammatory disease caused by the abnormal activation of trypsinogen. Approximately 15-25% of the patients with this abnormality might develop severe acute pancreatitis. Also, clinical treatment of AP is difficult for several reasons, including the rapid development of the disease, many complications, and high mortality. Therefore, it is necessary to find a cure for AP. Network pharmacology has recently become popular globally. It provides a holistic perspective of the relationship between drugs and diseases by constructing a “drug-gene target disease” network. Due to its holistic and systematic characteristics, it has been widely used to predict the potentially active components in traditional Chinese medicine and study their mechanism of action on disease targets.Salvia miltiorrhiza for the treatment of acute pancreatitis. It provides a theoretical basis for the screening of the active components of Salvia miltiorrhiza and promotes further research on Salvia miltiorrhiza.Molecular docking, an essential method of virtual drug screening, is important for modern pharmacological research. It predicts the binding affinity between drugs and receptors by computing the interactions and binding energy between small-molecule ligands (drugs) and protein receptors. This study used a combination of network pharmacology and molecular docking methods to investigate the mechanism of action of the active components of The database, analysis platform, and software used in this study are shown in We used the Chinese medicine systems pharmacology analysis platform TCMSP and inserted “Danshen” as the keyword to retrieve all its chemical components. Pharmacokinetics  and drug-like (DL) are often used by researchers to screen for active ingredients. OB values indicate the percentage of drugs that enter the human circulation. High OB values are usually the key indicators for evaluating the effectiveness of drugs. DL values indicate the degree of similarity between the components of traditional Chinese medicine and known chemical drugs. It is important for determining whether the components of Chinese Materia medica can exhibit pharmacological activities in organisms.T = A · B/‖A‖2 + ‖B‖2 − A · B, where A is the molecular descriptor for a given herbal component, and B represents the average value of this property for all molecules in the drug bank database [Drug-likeness (DL) is based on the analysis of the physicochemical properties and/or structural characteristics of existing small organic drugs, especially those with undesirable properties, for example, compounds with poor ADMET  . Based odatabase .DL is related to simple molecular properties such as molecular weight, physicochemical properties, and the number of convertible bonds or aromatic rings. In general, DL is related to the potential success of drug discovery in terms of pharmacokinetics and safety . BecauseSalvia miltiorrhiza were screened under the conditions of OB ≥ 30% and DL ≥ 0.18, and the information of the qualified compounds was recorded and maintained in a tabular form using Microsoft Excel. Additionally, the quality control components of Salvia miltiorrhiza and the reported compounds with definite biological activities in the Chinese Pharmacopoeia were also analyzed as candidates. Then, the chemical structure of the above candidate components was constructed by the ChemBioDraw Ultra software and stored in MOL2 format.In conclusion, the active components of The final list of components was prepared after removing the duplicate active components. This list was used to search the TCMSP analysis platform for targets corresponding to the active components. Furthermore, the gene names of all the targets were obtained using the UniProt database.With “acute pancreatitis” as the keyword and the screening criterion set as median screening, disease-related targets were retrieved using the GeneCards database. “Median screening” ensured the reliability of the candidate targets. Furthermore, the names of AP-related targets were standardized using the UniProt database.Salvia miltiorrhiza and AP as the component target and disease target, respectively. The map provided information about common targets. These common targets were imported into the STRING database after specifying the “species” and “minimum required interaction score” as “Homo sapiens” and “≥0.99,” respectively. The resultant protein interaction (PPI) information was imported into the Cytoscape software for topological analysis and construction of the PPI network diagram.Venny 2.1 was used to build a Wayne map by providing P < 0.05), which were in turn computed using the Cluster Profiler package in the R software.The function of these common targets in signal pathways was further investigated using the GO function and KEGG pathway enrichment  were converted into the pdbqt file format. (iii) The active site in the target protein was prepared for docking by setting the proper Grid Box size and coordinates. Then, the active components of Salvia miltiorrhiza were docked to the active site of the target protein. (iv) Finally, the components that demonstrated the lowest binding energy and highest binding affinity toward the target proteins were selected. The docked complexes of the selected components were visualized using the PyMoL software.From the constructed “Component-Target-Pathway” network, the components and their corresponding targets with moderate to high values were selected for molecular docking studies using AutoDock Vina. A series of steps were performed during molecular docking. (i) The 3D structure of the target protein was retrieved from the PDB database, and the ligand and nonprotein molecules (such as water molecules) were removed using the PyMoL software. The target protein files were saved in the PDB format. (ii) The target protein and the components of Salvia miltiorrhiza were retrieved in this study. Using specific screening criteria, such as OB ≥ 30%, DL ≥ 0.18, searching for quality control components in the Chinese Pharmacopoeia, and the removal of nontarget components, 65 active components of Salvia miltiorrhiza were selected. These components are presented in A total of 202 active chemical components of Salvia miltiorrhiza were selected. After removing the inactive components, 58 active components of Salvia miltiorrhiza Bunge were selected, and their corresponding 919 targets were obtained. Finally, the gene names corresponding to the target protein names were obtained from the UniProt database.From the TCPSP database, 65 candidate targets of Salvia miltiorrhiza affected multiple targets.As shown in Salvia miltiorrhiza with the 4,167 targets related to acute pancreatitis was investigated, and 111 common targets were found. These results indicated the active role of the components of Salvia miltiorrhiza in acute pancreatitis through their interaction with multiple targets , screened using KEGG enrichment analysis, mainly involved pathways related to cancer, neuroactive ligand-receptor interaction signaling pathway, PI3K-Akt signaling pathway, and cAMP signaling pathway , 113 molecular functions , and 59 cell components  were obtained. The resultant BP, MF, and CC were sorted according to corrected  pathway .Salvia miltiorrhiza were selected. A “component-target-pathway” was constructed with the selected targets and compounds using the Cytoscape software . It was observed that 83.3% of the components had binding energies ≤–7.5 kcal/mol with their targets. This indicated a strong binding affinity of the components of Salvia miltiorrhiza-Paleonia vulgaris with the target proteins. The binding affinities of the components of Salvia miltiorrhiza including new quinone D and tanshinone IIA to receptor-PTGS2 and the components such as Salviol ketone and quercetin to receptor-OPRM1 were higher than the binding affinity between these receptors and their original ligands. Additionally, the docking results confirmed the reliability of the results of network pharmacological analysis (A previous study reported that the stability of the binding conformation of the target protein with the ligand (active component) depends on the binding energy of the docked complex such that the lower binding energy of the docked complex increases the stability of the binding conformation. Binding energies of ≤-4.25 kcal/mol, ≤-5.0 kcal/mol, and ≤ -7.0 kcal/mol indicated reasonable binding affinity, good binding affinity, and strong binding affinity, respectively. To confirm the results of the network analysis, four targets with high median scores from the “component-target-pathway,” which included PTGS2, RELA, TNF, and AKT1, were selected as receptors for molecular docking studies. Six active components of analysis . FinallyTCM deems that inflammation of internal organs may be due to accumulation of pathogenic qi, dampness, and heat. Qi stagnation causes blood stasis, and dampness leads to distention. When the pathogenic heat flames extremely, carbuncle will form. Acute pancreatitis is classified into “abdominal pain” or “internal carbuncle” in TCM. It can be relieved by the treating principles as follows: promoting qi and blood circulation and removing pathogenic heat by purgation .In this study, the best tanshinones and flavonoid were screened from the high-frequency danshen which was used to treat AP by TCPSP and PubChem database, it is suggested that tanshinones and flavones in Salvia miltiorrhiza may be the main material basis for the treatment of AP. The former includes tanshinone iia, 4-methylenemiltirone, salviolone, neocryptotanshinone ii, and isocryptotanshi-none, and the latter includes luteolin. To further identify the key compounds of Salvia miltiorrhiza in the treatment of AP, we constructed a composite target network, and the compounds in the top 10 degrees were luteolin, tanshinone iia, dihydrotanshinolide, dan-shexinkum d,4-methylenemiltirone salviolone, isocryptotanshi-none, 2-isopropyl-8-methylphenanthrene-3,4-dione, neocryptotanshinone ii, and miltionone I.ΚB pathway, which demonstrated that luteolin could significantly improve the infiltration and necrosis of inflammatory cells in the pancreas. A study by Chen et al. [Salvia miltiorrhiza. Antibacterial, anti-inflammatory, blood stasis promoting, wound healing, and other effects can play a positive therapeutic role in all aspects of the treatment of AP [Salvia miltiorrhiza can not only inhibit the release of inflammatory factors and reduce the inflammatory reaction but also reduce the absorption of intestinal endotoxin and the translocation of pathogenic bacteria. They can also inhibit the growth of cancer cells and play an important role in improving microcirculation and alleviate edema and necrosis of pancreatic tissue. Many studies [Salvia miltiorrhiza, can inhibit LPS-induced inflammation by inhibiting NF-κB and iNOS signals. In a study by Fan et al. [Salvia miltiorrhiza, plays an important role in the regulation of inflammatory cytokines and their signal pathways. TNF, IL-6, and NFKB1 are involved in the inflammation-related pathways, such as the IL-17 signal pathway and the TNF signal pathway, to regulate the inflammatory response in the body.It was found that  luteolinn et al.  confirment of AP . In conc studies , 11 haven et al. , it was Salvia miltiorrhiza reflects its anti-inflammatory and anti-injury characteristics. Based on network analysis, PTGS2, NCOA1, SCN5A, OPRM1, CHRM1, ADRB2, CHRNA7, and ACHE were selected as the key targets of AP.The composition-target network of Radix Salvia miltiorrhiza, can relieve the mechanical and thermal pain induced by Freund's complete adjuvant by inhibiting the expression of p-ERK and NF-κB. The levels of PTGS2 can reduce inflammation by reducing the levels and mRNA expression of IL-1β, IL-6, and tumor necrosis factor in sercytokines IL-1 β, IL-6, and TNF-α, and hence, can reduce pain. OPRM1 is an opioid receptor. The mu-opioid receptor (MOR) encoded by the OPRM1 gene is the main target of most opioid drugs. It is also an important factor that exerts analgesic effects, imparts tolerance, and provides dependence [Salvia miltiorrhiza can dilate blood vessels, promote blood circulation, and remove blood stasis, and thus, inhibit platelet aggregation, anticoagulation, antithrombus, and reduce plasma viscosity. At the onset of AP, the body experiences increased activation of the sympathetic nervous system, which is marked by an increase in the heart rate and blood pressure. The sympathetic nervous system acts on the β1 and β2 receptors in the heart and blood vessels, respectively, regulating blood pressure. The ADRB2 gene regulates blood pressure [β2 adrenergic receptor (β2-AR), expressed by ADRB2, is extensively present in immune cells. In mice and humans, stimulation of β2 AR activates NOD2 signaling, promotes T cell differentiation, and regulates the secretion of related cytokines and inflammation, according to a study [Salvia miltiorrhiza plays an anti-inflammatory role through the cholinergic anti-inflammatory pathway is not clear. By analyzing the KEGG pathway in this study, the authors speculate that CHRNA7 might be expressed in acute pancreatitis and play a key role in regulating inflammation. Salvia miltiorrhiza might play an anti-inflammatory role in the cholinergic anti-inflammatory pathway, which might elucidate the anti-inflammatory mechanisms and suggest clinical applications of Salvia miltiorrhiza. ACHE, a substance released by cholinergic neurons, is a major transmitter of the parasympathetic nervous system that rapidly hydrolyzes the neurotransmitter acetylcholine ACHE and acts as a marker of systemic inflammation. Clinical studies [Studies  have shopendence . Tanshinpendence . There ipendence , 19 frompendence  that Salpressure , and the a study  on dendr a study . The mec studies  have sho studies  found thSalvia miltiorrhiza were extracted from the database. The potential targets of Salvia miltiorrhiza were predicted among these compounds, and the KEGG pathway enrichment analysis was performed. The potential pathway of Salvia miltiorrhiza was obtained based on these targets. According to the KEGG enrichment analysis of the key targets and associated studies, the acute pancreatitis pathway of Salvia miltiorrhiza is mainly involved in the PI3K-Akt signaling pathway, HIF-1 signaling pathway, cAMP signaling pathway, cholinergic synapse, FOXO signaling pathway, insulin resistance, AMPK signaling pathway, pathways associated with cancer, pancreatic cancer, neuroactive ligand-receptor interaction, etc.Acute pancreatitis is a complicated, acute, and severe disease of the abdomen, with many complications and high mortality, involving different metabolic pathways. The compounds in κB in pancreatic tissue were significantly increased [α , Beclin1 gene, and microtubule-associated protein-1 light chain 3-II  are closely related to the pathological development of inflammation [α is very sensitive to the concentration of oxygen in cells and reflects the degree of hypoxia in cells. Inflammatory injury increases the expression of HIF-1α and the release of Beclin1 and LC3-II, which are markers of autophagic activity; it also increases the level of autophagy. In pancreatitis, autophagy is activated but lysosomal degradation is inhibited, and the imbalance between increased autophagy and decreased lysosomal degradation leads to autophagy flux arrest, which can cause severe acinar cell degeneration and trypsinogen activation, leading to the development of AP [κb, which is dependent on estrogen receptor α, inhibits the production of IL-6, and thus, reduces inflammation. Saito et al. [Salvia miltiorrhiza Bunge on the AMPK signal pathway is not clear; however, the authors speculate that Salvia miltiorrhiza Bunge might increase the activity of AMPK, decrease the level of ROS, increase the production of SOD, and enhance the antioxidative ability of an organism. The reduction of oxidative stress in acute pancreatitis might provide important directions for the study of the mechanism of oxidative stress and clinical application of Salvia miltiorrhiza.As an important signal transduction pathway, PI3K/AKT controls a variety of signal transduction pathways, including proliferation, apoptosis, and stress. In the AP model induced by ligation of the pancreatic duct, the expression of p-Akt and the activity of NF-ncreased . The expammation –29. Ischnt of AP . At the nt of AP  have shont of AP  showed to et al.  showed to et al. . The oxio et al. –38. The Salvia miltiorrhiza to be effective against acute pancreatitis by targeting PTGS2, NCOA1, and other key genes. The results of the KEGG enrichment analysis indicated that Salvia miltiorrhiza might alleviate AP by regulating the PI3K-AKT signal pathway and other signal pathways. This study showed that Salvia miltiorrhiza probably affects AP through multiple targets and pathways. In this study, the possible pharmacodynamic basis and the mechanism of action of Salvia miltiorrhiza in treating acute pancreatitis were predicted by network pharmacology. The results of molecular docking also showed that the active molecule of Salvia miltiorrhiza has good binding activity with key target proteins. This study provides a scientific basis for further experimental research and clinical application.In summary, using network pharmacology methods and molecular docking techniques, this study identified quercetin and other active components in