Genome-Scale Metabolic Reconstruction, Non-Targeted LC-QTOF-MS Based Metabolomics Data, and Evaluation of Anticancer Activity of Cannabis sativa Leaf Extracts
1Group of Product and Process Design, Department of Chemical and Food Engineering, Universidad de los Andes, Bogotá 111711, Colombia; fd.gonzalez@uniandes.edu.co (F.D.G.C.); ad.sanchez@uniandes.edu.co (A.S.-C.)
2Applied Genomics Research Group Vice-Presidency for Research and Creation, Universidad de los Andes, Bogotá 111711, Colombia; mi.guevara34@uniandes.edu.co
3Metabolomics Core Facility—MetCore Vice-Presidency for Research and Creation, Universidad de los Andes, Bogotá 111711, Colombia; m.santamariatorres@uniandes.edu.co (M.S.-T.); mp.cala10@uniandes.edu.co (M.P.C.)
4Laboratory of Mycology and Phytopathology (LAMFU), Department of Biological Sciences and Department of Chemical and Food Engineering, Universidad de los Andes, Bogotá 111711, Colombia; srestrep@uniandes.edu.co
5Leibniz-Institute of Plant Biochemistry, Department of Bioorganic Chemistry, Weinberg 3, 06110 Halle, Germany; miguelangel.fernandeznino@ipb-halle.de
6Ecomedics S.A.S., Commercially Known as Clever Leaves, Calle 95 # 11A-94, Bogota 110221, Colombia; mariacorujobesga@gmail.com
7Chemical and Biochemical Processes Group, Department of Chemical and Environmental Engineering, National University of Colombia, Bogotá 11001, Colombia; acgallom@unal.edu.co
8Research Group on Nanobiomaterials, Cell Engineering and Bioprinting (GINIB), Department of Biomedical Engineering, Universidad de los Andes, Bogotá 111711, Colombia; jf.cifuentes10@uniandes.edu.co (J.C.); ja.serna10@uniandes.edu.co (J.A.S.); jc.cruz@uniandes.edu.co (J.C.C.); c.munoz2016@uniandes.edu.co (C.M.-C.)
*Correspondence: andgonza@uniandes.edu.coAbstract
Over the past decades, Colombia has suffered complex social problems related to illicit crops, including forced displacement, violence, and environmental damage, among other consequences for vulnerable populations. Considerable effort has been made in the regulation of illicit crops, predominantly Cannabis sativa, leading to advances such as the legalization of medical cannabis and its derivatives, the improvement of crops, and leaving an open window to the development of scientific knowledge to explore alternative uses. It is estimated that C. sativa can produce approximately 750 specialized secondary metabolites. Some of the most relevant due to their anticancer properties, besides cannabinoids, are monoterpenes, sesquiterpenoids, triterpenoids, essential oils, flavonoids, and phenolic compounds. However, despite the increase in scientific research on the subject, it is necessary to study the primary and secondary metabolism of the plant and to identify key pathways that explore its great metabolic potential. For this purpose, a genome-scale metabolic reconstruction of C. sativa is described and contextualized using LC-QTOF-MS metabolic data obtained from the leaf extract from plants grown in the region of Pesca-Boyaca, Colombia under greenhouse conditions at the Clever Leaves facility. A compartmentalized model with 2101 reactions and 1314 metabolites highlights pathways associated with fatty acid biosynthesis, steroids, and amino acids, along with the metabolism of purine, pyrimidine, glucose, starch, and sucrose. Key metabolites were identified through metabolomic data, such as neurine, cannabisativine, cannflavin A, palmitoleic acid, cannabinoids, geranylhydroquinone, and steroids. They were analyzed and integrated into the reconstruction, and their potential applications are discussed. Cytotoxicity assays revealed high anticancer activity against gastric adenocarcinoma (AGS), melanoma cells (A375), and lung carcinoma cells (A549), combined with negligible impact against healthy human skin cells.
1. Introduction
Over the past decades, Colombia has suffered from complex social problems related to illicit crops, including forced displacement, violence, and environmental damage, among other consequences for vulnerable populations [1]. Considerable effort has been made in Colombia to address this issue by creating a regulatory framework for import, export, cultivation, extraction, and research activities, especially of Cannabis sativa [2,3]. When the contingency caused by the coronavirus began, the former Minister of Health authorized Resolution 315 of 2020, which updates the lists of precursor drugs subject to state control and gives free access to the sale of master formulations (preparations made for medical indications) in order to eliminate some access barriers for research, medical, and scientific use [4]. In addition, two years later, Resolution 227 of 2022 was approved, regulating the use of medicinal C. sativa (non-psychoactive components) in food, beverages, and dietary supplements. Furthermore, since the beginning of this year, the national government, through Resolution 2808 of 2022, decided to include magistral preparations of C. sativa medicines within the health benefits plan for patients with pathologies such as refractory epilepsy, fibromyalgia, sleep and appetite disorder, cachexia due to cancer, insomnia, chronic pain, neuropathic pain, and pain associated with cancer, in order to address those public health concerns [5]. These laws laid the groundwork for the cultivation of C. sativa plants, the emergence of the medical cannabis industry, and safe access to medical and scientific use, among other developments. Hence, the current regulatory framework promotes scientific knowledge of C. sativa and allows for the exploration of potential markets for its alternative uses [6].
The field of research related to C. sativa has been expanding at an accelerated rate [7] thanks to the biotechnological capacity hidden in the plant. It is estimated that C. sativa can produce approximately 750 specialized secondary metabolites [8,9,10]. Some of the most relevant are monoterpenes, sesquiterpenoids, triterpenoids, essential oils, flavonoids, phenolic compounds (known as polyphenols [7]), lignans, stilbenoid derivatives, alkaloids, amino acids, spiro-indans, steroids, and glycoproteins, mainly due to their anticancer properties [8,11,12,13,14]. Previous studies have shown a synergy among the metabolic compounds of the plant that, as a whole, show different behavior compared to the individual performance of each metabolite due to the “entourage effect” [15,16]. It is established that C. sativa chemotypes’ rich cannabinoid and terpenoid content offer better pharmacological activities that are able to broaden clinical applications and improve therapeutic issues [17,18,19]. In the same way, remarkable anticancerogenic activity has been demonstrated for C. sativa extracts against different carcinoma cell lines such as melanoma [20], ovarian [21], prostate [22], breast [23], and pancreatic cancer [16]. These studies have revealed a reduction in tumor growth and promotion of apoptosis and autophagy in carcinoma cells [15,23,24,25]. At the taxonomic level, chemotypes are grouped in terms of the relative amounts of their main compounds, the cannabinoids. Drug-type plants (chemotype I) contain high concentrations of the most prevalent cannabinoid known for its psychotropic capacity, (-)-trans-∆9-tetrahydrocannabinol, or D9-THC. When the cannabinoid content corresponds mostly to the second most abundant cannabinoid in the C. sativa plant, cannabidiol, CBD, it corresponds to chemotype III [26]. Finally, chemotype II, which is very scarce, is defined as a balanced content of the two main cannabinoids [27].
For all these reasons, it is critical to understand plant metabolism on a system-wide level to identify metabolic pathways involved in the production of key metabolites, characterize specific phenotypes influenced by environmental factors, and explore alternative uses of the leaf, such as nutraceuticals.
In the last two decades, Genome-Scale Metabolic (GEM) reconstructions have become a fundamental tool taking advantage of the development of high throughput data of omics technologies to study and understand the complex interactions of organisms [28]. Regarding the development of omics technologies in C. sativa, the first sequenced and assembled genome was produced in 2011 by Grassa et al. [29] and since then, publications based on whole-genome sequencing and population studies [30,31,32], transcriptomics [33], proteomics [34], and metabolomics have resolved compelling questions about the chemotype of the plant and its relationship with geography or characteristic markers [9]. Additionally, studies of C. sativa on the metabolic response of the plant under different degrees of stress [35], its potential uses in different industries [14,16], and particularly nutraceuticals [36,37], such as evaluation of anti-malarial activity [38], observation of in vivo antioxidant effects [39], and pathogen resistance [30], among others, stand out.
Meanwhile, in plant systems biology, genome-scale modeling has advanced considerably thanks to the reconstruction of Arabidopsis thaliana, Zea mays, Oryza sativa, and Saccharum officinarum, among others [40], which have proven accurate predictions focused on specific aspects of central carbon metabolism. For Arabidopsis thaliana, GEM modeling has evolved from the production of biomass components observed in experimental data to the inclusion of compartments (cytosol, plastid, mitochondrion, peroxisome, and vacuole), calculation of cell maintenance energy costs, description of photosynthetic processes, integration of secondary metabolism pathways, gene expression, proteomic data, and multi-tissue models [41]; as an example, Scheunemann et al. used the Plant SEED scheme to obtain reconstructions and subsequently integrate transcriptomics data extracted from different plant tissues [42].
Here we present a Genome-Scale Metabolic (GEM) reconstruction of C. sativa with an analysis of non-targeted LC-QTOF-MS (Liquid Chromatography-Quadrupole Time-of-Flight Mass Spectrometry)-based metabolomics data and evaluation of cytotoxicity and anticancer activity of leaf extracts, which could help to pave the way for the development of alternative uses of the leaf with potential applications in the food, cosmetic, textile, and agrochemical industries and also to enhance exploration of anticancer, analgesic, and anti-inflammatory compounds [11]. To our knowledge, this is the first attempt to comprehensively describe the metabolic capacities of C. sativa leaf (including both primary and secondary metabolism) based on a Genome-Scale Metabolic reconstruction; the contextualization of the reconstruction was carried out via LC-QTOF-MS to favor the identification of metabolites with known (anticancer, due to cannabinoids) and alternative properties (nutraceuticals, due to flavonoids and amino acids) [43].
2. Materials and Methods
2.2. Chromatographic Analysis of C. sativa Leaf: LC-PDA and RP-LC-QTOF-MS
2.2.1. Plant Material and Extraction
The sample material was obtained from plants grown in the region of Pesca-Boyaca, Colombia, under greenhouse conditions at the Clever Leaves facility, in a legal operation and under controlled growing conditions, following the guidelines for good agricultural and collection practices (GACP) for starting materials of herbal origin.
The drying process of the plant material was carried out in rooms with controlled conditions for this purpose. The extraction process was carried out from fresh leaf tissue that was ground to a particle size of 1.4 mm, at a 5:1 ratio of ethanol to dry leaves by weight. Constant agitation was performed in a Heidolph shaker at 2000 rpm for 4 h. The supernatant was transferred to a new vial.
Subsequently, the extract obtained was used for LC-PDA and LC-QTOF-MS analysis under the conditions described below.
2.2.2. LC-PDA
The chromatographic analysis was carried out using a methodology validated by Clever Leaves, a company dedicated to pharmaceutical grade cannabis-based products.
The liquid chromatography method with PDA (photodiode array) detection was employed, using the following conditions. Mobile phase A involved a solution of 0.1% trifluoroacetic acid in water, while mobile phase B involved a solution of acetonitrile. A total injection volume of 2 μL was used for the analysis. UV detection was set at a wavelength of 220 nm. Chromatographic separation was carried out on a CORTECS® UPLC® Shield RP18 column (Milford, USA) with dimensions of 2.1 × 100 mm and a particle size of 1.6 μm. The autosampler and column temperatures were maintained at 8 °C and 35 °C, respectively. The total run time for the analysis was 11 min. Acetonitrile HPLC was used as the solvent for dilutions, while a mixture of acetonitrile and water (70:30) was employed as solvent. The purge solvent consisted of a water–acetonitrile mixture (90:10). The flow rate was set at 0.7 mL/min, and the mobile phase composition was kept isocratic at 41% mobile phase A and 59% mobile phase B. The system suitability test required a resolution between peaks to be greater than 1.5 for proper analysis.
2.2.3. Analysis by RP-LC-QTOF-MS
For metabolic analysis, 5 mg of the crude extract of C. sativa, which contains a high cannabidiol (CBD) content (>85% of the total phytocannabinoids extracted) [18], was dissolved in methanol to a final concentration of 250 mg/L for subsequent analysis via reverse-phase liquid chromatography coupled with mass spectrometry (RP-LC-QTOF-MS).
Samples were analyzed in a liquid chromatography system (Agilent Technologies 1260) coupled with a quadrupole time-of-flight (Q-TOF) mass analyzer (Agilent Technologies 6545B) with an electrospray ionization source (ESI). Separation was conducted in a C18 column (InfinityLab Poroshell 120 EC-C18 (100 × 3.0 mm, 2.7 µm) at 30 °C with a gradient elution consisting of 0.1% (v/v) formic acid in Milli-Q water (Phase A) and 0.1% (v/v) formic acid in acetonitrile (Phase B) at a constant flow rate of 0.4 mL/min. Mass spectrometric detection was performed initially in positive mode, followed by a subsequent analysis in negative mode using the same set of acquired data at full scan from 70 to 1100 m/z. The QTOF instrument was operated in 4 GHz (high resolution) mode. The data acquisition parameters were configured as follows: ion source temperature of 325 °C, gas flow of 8 L/min, nebulizer gas pressure at 50 psi, and capillary voltage of 2800 V. MS/MS acquisition mode was performed in data-dependent acquisition (DDA) mode in the range of m/z 50 to 1100 with a scan sweep rate of 3 spectra/s and under chromatographic and spectrometric conditions identical to those employed in the initial analysis. For each sample, analysis was performed at different collision energies 20 eV, 40 eV, and equation mode was used (CE = 3.6 × (m/z)/100 + 4.8) [59,60], using 3 precursors per cycle. During the analysis, several reference masses were used for mass correction: m/z 121.0509 (C5H4N4), m/z 922.0098 (C18H18O6N3P3F24) in positive mode and m/z 112.9856 [C2O2F3 (NH4)], and m/z 1033.9881 (C18H18O6N3P3F24) in negative mode.
2.2.4. Data Processing
Data processing was performed with the Agilent MassHunter Profinder 10.0 software program for deconvolution, alignment, and integration, using the recursive feature extraction (RFE) algorithm. This algorithm performs a deconvolution of the chromatogram and integration of the molecular characteristics present in the samples according to mass and retention time. The data obtained from the deconvolution and integration were filtered by area by calculating the total area for the sample and then the area of each molecular feature. The annotation of the more abundant molecular features obtained was carried out using the CEU MASS MEDIATOR tool (https://ceumass.eps.uspceu.es/ (accessed on 1 October 2021)) [47], including the Metlin, Kegg, HDMB, and LipidMaps platforms as parameters, and with a tolerance of 10 ppm. Then, MS/MS analyses were performed in order to confirm the identity of the metabolites using MS-DIAL 4.8 (http://prime.psc.riken.jp/compms/msdial/main.html (accessed on 1 October 2021)), in in silico mass spectral fragmentation through CFM-ID 4.0 (https://cfmid.wishartlab.com/ (accessed on October 2021)) and manual MS/MS spectral interpretation using the Agilent MassHunter Qualitative Analysis program (version 10.0, USA).
2.2.5. Cell Cytotoxicity and Anticancer Activity of C. sativa Leaf Extract
Cytotoxicity and anticancer activity were determined by analyzing the impact of C. sativa leaf extract on the metabolic activity of three different human carcinoma cell lines, namely gastric adenocarcinoma (AGS, ATCC® CRL-1739), lung carcinoma (A549, ATCC® CCL-185), and skin melanoma (A375, ATCC® CRL-1619). Additionally, two healthy cell lines were employed, i.e., Vero (ATCC® CCL-81) and human skin fibroblasts (HFF, ATCC® SCRC-1041).
Cell viability was determined via a MTT metabolic activity assay (3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide)) following the manufacturer’s instructions. For this, cells (7000–10,000 cells/well depending on the cell line) were seeded on 96-well microplates with supplemented culture medium (10% FBS) and then incubated at 37 °C, in a 5% CO2, and humidified atmosphere (humidity above 90%) for 24 h. Next, the culture medium was extracted and replaced by a non-supplemented medium containing the C. sativa leaf extract at concentrations ranging from 0.05 to 0.0004 mg/mL (serial dilutions were performed). Cells were incubated at 37 °C, in a 5% CO2 and humidified atmosphere for 24 and 72 h. After the incubation time, 10 µL of the MTT reagent (5 mg/mL) was added to each well, and the microplates were incubated for 2 h under the same conditions. Finally, supernatants were extracted and replaced by 100 µL of DMSO to dissolve formazan crystals. Absorbance was recorded at 595 nm in a microplate reader (Multiskan™ FC Microplate Photometer, ThermoFisher Scientific, Waltham, MA, USA).
Cell viability was calculated using the following equation: where Abs (C) corresponds to the absorbance of the negative control (non-supplemented medium) at 595 nm and Abs (sample) corresponds to the absorbance of the sample at 595 nm. In addition, Cytotoxicity (%) was calculated as 100 Cell viability (%).
3. Results
3.3. Cytotoxicity and Anticancer Activity of C. sativa Leaf Extracts
The cytotoxicity of the C. sativa extract was clearly affected by different factors such as concentration, exposure time, and cell line. Results showed high anticancer activity against gastric adenocarcinoma (AGS) and melanoma cells (A375) (Figure 8).
Cytotoxicity levels ranging from 50 to 90% for concentrations between 0.0125 and 0.05 mg/mL were observed in both cell lines. In contrast, for Vero and lung carcinoma cells (A549), these cytotoxicity levels were observed in concentrations between 0.025 and 0.05 mg/mL. This confirms less activity against A549 and significant toxicity against Vero cells. Surprisingly, results obtained for healthy skin fibroblasts (HFF) showed negligible toxicity in concentrations between 0.0004 and 0.025 mg/mL (below 10%).
4. Discussion
4.3. Cytotoxicity and Anticancer Activity of C. sativa Leaf Extracts
The obtained results confirmed the remarkable anticancer activity of the C. Sativa extracts against different carcinoma cell lines (AGS, A375 and A549). This agreed well with previous works that studied the anticancer activity of C. sativa on different cell lines such as melanoma [20], ovarian cancer [21], prostate cancer [22], and breast and pancreatic cancer [16], among others. The results are also in agreement with the biological activities based on both the chemotype and the extraction taken from the leaves of the plant. Manosroi et al. [86] demonstrated that the ethanolic extract of the leaves and seeds of the C. sativa plant chemotype III, exhibited cytotoxicity activity against B16F10 melanoma cells in a concentration dependent manner (cytotoxicity of 46% at 1 mg/mL and total inhibition at 10 mg/mL). Additionally, both leaf and seed extracts demonstrated negligible toxicity against human skin fibroblast (viability above 80% for concentration below 0.5 mg/mL) confirming high biocompatibility.
The notable activity against melanoma cells combined with the negligible impact on healthy human skin cells confirms the great pharmacological potential that makes them suitable candidates for the development of new-generation topical treatments with reduced side effects, especially for melanoma, the most common and aggressive type of skin cancer. These findings have been confirmed in several works presenting promising results, both in vitro [87] and in vivo [20].
On the other hand, the potential selective toxicity of C. sativa leaf extracts has been widely studied in order to develop novel therapies with reduced negative side effects. Janatová and colleagues [15] evaluated selectivity by comparing the toxicity of six different genotypes of medical cannabis against three cancer cell lines (Ht-29, Caco-2, and Hep-G2) and two healthy cell lines (FHs 74 Int: healthy intestinal cells and MRC-5: healthy lung fibroblast). They demonstrated that the compound content of the different genotypes strongly affects selectivity. Highlighting specific compounds such as myrcene, β-elemene, β-selinene, and α-bisabolol oxid as enhancers of selectivity and β-ocimene and β-caryophyllene oxide as cytotoxicity-associated molecules. Selectivity is therefore determined by the plant genotype (chemical profile and content) and by the specific cell line.
In consequence, these findings can explain the selectivity differences between all the different evaluated cell lines, especially, the significant increase of cytotoxicity observed in Vero cells. Furthermore, the obtained toxicity profiles against Vero cells agree strongly with previously reported articles. For example, Lamdabsri and coworkers [88] showed that the toxicity of cannabis extracts against Vero cells is highly influenced by compound content, reporting high toxicity in the crude and CBN extracts (IC50 of 13.4 and 10.6 μg/mL, respectively) and lower toxicity in the CBG, CBD, and THC (IC50 699.7, 39.77 and 67.2 μg/mL, respectively).
5. Conclusions
GEM reconstruction of C. sativa contributes to better understanding of cellular phenotypes and metabolic behavior [41,89] in terms of the identification of different biosynthetic pathways by integrating omics data and experimental anticancer results. Using the current model, it is possible to explore different biosynthetic pathways for many valuable compounds, especially those of major interest to the scientific community and which represent a significant opportunity to improve the value chain for C. sativa. The high number of reactions observed in the cytosol, plastids, and mitochondria compartments confirms the significance of primary metabolic pathways such as glycolysis, the Krebs cycle, and the shikimate pathway. These pathways play a crucial role as principal precursors for secondary metabolites, including cannabinoids, flavonoids, fatty acids, and nitrogen-containing compounds. Transport reactions have a crucial role in facilitating the exchange of metabolites between different cellular compartments. This is especially important in compartments such as the chloroplast, cytosol, endoplasmic reticulum, and vacuole, which are related to the synthesis of various metabolites, including alkaloids, terpenes, sterols, and hydrophilic compounds.
On the other hand, the LC-QTOF-MS metabolomics analysis provided insights into the diverse chemical composition and distribution of secondary metabolites in C. sativa. The LC-QTOF-MS data revealed a high abundance of secondary metabolite modules such as cannabinoids, terpenoids, coumarins, phenylpropanoids, and steroids. Specific metabolites identified included delta-9-THC, cannabidiolic acid, cannabichromene, geranylhydroquinone, cannflavin A, pregna-4,9(11)-diene-3,20-dione, and neriantogenin. These metabolites exhibit a range of biological activities and potential therapeutic benefits. Additionally, these metabolites contributed to the integration of the reconstruction, demonstrating that the use of omics contributes to the activation of a greater number of reactions that are required for the synthesis of metabolites in the reconstruction.
Finally, regarding to the cytotoxicity and anticancer activity of C. sativa, it can be concluded that although extracts demonstrated low selectivity in Vero cells, their remarkable selectivity against melanoma cells compared to the healthy skin fibroblast leaves an open window for continuing studies on C. sativa leaf extract as a potential candidate for the development of new-generation treatments for skin cancer with reduced side effects.
Acknowledgments
We thank the “(CESED) Centro de Estudios de Seguridad y Drogas” of the School of Economics of the Universidad de los Andes for funding the metabolomics studies. We also thank Clever Leaves for technical and scientific support for the project. We thank the departments of Biomedical Engineering, Chemical and Food Engineering, and the Vice Rector’s Office for Research and Creation in its core facilities Metcore-Gencore for the human and scientific support. We are grateful to the degree project “Genome-Scale Metabolic Reconstruction of Cannabis sativa and validation with non-targeted LC-MS based leaf metabolomics data” from the master’s degree in computational biology of the Universidad de los Andes, which served as the basis for the present work.
Appendix Group
Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/metabo13070788/s1, Figure S1: Number of reactions per compartment in metabolic reconstruction. Figure S2: Glycolysis in GEM reconstruction of C. sativa; Figure S3: Chromatogram of the main ions extracted from C. sativa. (A) ESI (+) detection mode. (B) ESI (−) detection mode; Figure S4: Fluxer nodes and edge representation of metabolic reconstruction of C. sativa model; Figure S5: Fluxer nodes and edge representation of metabolic reconstruction of AraGEM model; Table S1: Biomass compounds in the objective function; Spreadsheet S1: CannGEM.xls.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Data is contained within the article or Supplementary Material. The data presented in this study are available.
Conflicts of Interest
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
| Strategy—Plant Seed | AraGEM | |
|---|---|---|
| Reactions | 2101 | 1567 |
| Metabolites | 1314 | 1748 |
| GPR | 1462 | 5253 |
| Transport Reactions | 143 | 148 |
| Compartments | c, d, g, v, w, x, m, n, r, e, j | c, m, p, x, plastid, v |
| Strategy II—Plant Seed | |
|---|---|
| allGaps | 228 |
| rootGaps | 100 |
| downstreamGaps | 128 |
| Compound | Formula | Mass | RT (min) | Mass Error (ppm) | Adduct | DET | ID Confidence a | Area (%) b |
|---|---|---|---|---|---|---|---|---|
| Alkaloids and derivatives | ||||||||
| Neurine | C5H13NO | 103.0997 | 1.09 | 7 | [M+H]+ | ESI + | Level 3 | 0.86 |
| Cannabisativine | C21H39N3O3 | 381.2991 | 5.66 | 4 | [M+H]+ | ESI + | Level 3 | 0.31 |
| Benzenoids | ||||||||
| Phenylacetaldehyde | C8H8O | 120.0575 | 3.33 | 5 | [M+H-H2O]+ | ESI + | Level 3 | 0.43 |
| Methylstyrene | C9H10 | 118.0783 | 14.59 | 6 | [M+H]+ | ESI + | Level 3 | 2.31 |
| Phenylpropanal | C9H10O | 134.0732 | 14.59 | 5 | [M+H]+ | ESI + | Level 3 | 0.65 |
| Cyclointegrin | C21H20O6 | 368.1260 | 14.87 | 0 | [M-H]− | ESI − | Level 3 | 0.61 |
| Cresol | C7H8O | 108.0575 | 16.46 | 4 | [M-H]− | ESI − | Level 3 | 1.25 |
| Levomethadyl Acetate | C23H31NO2 | 353.2355 | 16.99 | 6 | [M+H]+ | ESI + | Level 3 | 1.17 |
| Hydroxy-(pentadecatrienyl)benzoic acid | C22H30O3 | 342.2195 | 17.33 | 4 | [M-H]− | ESI − | Level 3 | 0.30 |
| Fatty Acyls | ||||||||
| Corchoionol C glucoside | C19H30O8 | 386.1941 | 6.17 | 0 | [M-H]− | ESI − | Level 2 | 0.46 |
| Trihydroxy-octadecadienoic acid | C18H32O5 | 328.2250 | 11.14 | 1 | [M-H]− | ESI − | Level 2 | 0.42 |
| Octadecatetraenoic acid | C18H28O2 | 276.2089 | 15.23 | 1 | [M-H]− | ESI − | Level 3 | 0.37 |
| Hydroxyoctadecatrienic acid | C18H30O3 | 294.2195 | 15.32 | 1 | [M-H-H2O]− | ESI − | Level 3 | 1.40 |
| Palmitoleic acid | C16H30O2 | 254.2246 | 16.89 | 5 | [M+H-H2O]+ | ESI + | Level 3 | 0.79 |
| Glycerolipids | ||||||||
| Gingerglycolipid A | C33H56O14 | 676.3670 | 14.50 | 1 | [M-H]− | ESI −/+ | Level 3 | 0.72 |
| Glycerophospholipids | ||||||||
| LPC 16:0 | C24H50NO7P | 495.3325 | 15.94 | 6 | [M+H]+ | ESI + | Level 2 | 0.43 |
| LPC 8:0 | C16H32NO8P | 397.1866 | 16.21 | 2 | [M+HCOOH-H]− | ESI − | Level 3 | 0.98 |
| PI 41:7 | C50H83O13P | 922.5571 | 16.03 | 7 | [M+HCOOH-H]− | ESI − | Level 3 | 0.39 |
| PS O-37:2 | C43H82NO9P | 787.5727 | 16.51 | 2 | [M+Na]+ | ESI + | Level 3 | 0.39 |
| PE 38:5 | C43H76NO8P | 765.5309 | 16.56 | 3 | [M+H]+ | ESI + | Level 3 | 0.49 |
| PA O-36:4 | C39H71O7P | 682.4937 | 16.59 | 4 | [M+Na]+ | ESI + | Level 3 | 0.72 |
| PA O-36:6 | C39H67O7P | 678.4624 | 16.64 | 6 | [M+H-H2O]+ | ESI + | Level 3 | 0.78 |
| LPG 16:0 | C22H45O9P | 484.2801 | 16.96 | 10 | [M+H]+ | ESI + | Level 3 | 0.62 |
| PG 25:3;O3 | C31H55O13P | 666.3380 | 16.67 | 9 | [M+H]+ | ESI + | Level 3 | 0.37 |
| Organic acids and derivatives | ||||||||
| Alloisoleucine | C6H13NO2 | 131.0946 | 1.89 | 3 | [M-H]− | ESI − | Level 3 | 0.35 |
| Dilauryl 3.3′-thiodipropionate | C30H58O4S2 | 546.3777 | 16.74 | 3 | [M+H-H2O]+ | ESI + | Level 3 | 0.60 |
| Gly-Tyr-Tyr-Pro-Thr | C29H38N5O9 | 600.2670 | 16.99 | 6 | [M+Na]+ | ESI + | Level 3 | 0.61 |
| Organoheterocyclic compounds | ||||||||
| delta-9-THC | C21H30O2 | 314.2246 | 15.76 | 5 | [M+H]+ | ESI + | Level 2 | 3.71 |
| delta-9-THC | C21H30O2 | 314.2246 | 16.47 | 5 | [M+H]+ | ESI + | Level 2 | 5.67 |
| Geranylhydroquinone | C16H22O2 | 246.1620 | 16.46 | 0 | [M-H-H2O]− | ESI − | Level 3 | 13.35 |
| methyl-(4-methylpent-3-en-1-yl)-2H-chromen-ol | C16H20O2 | 244.1463 | 16.46 | 2 | [M-H]- | ESI − | Level 3 | 3.10 |
| Dimethyl-prenylchromene -carboxylic acid | C17H20O3 | 272.1413 | 16.46 | 2 | [M-H]− | ESI − | Level 2 | 2.09 |
| Phaeophorbide b | C35H34N4O6 | 606.2478 | 17.19 | 4 | [M+H]+ | ESI + | Level 3 | 0.55 |
| Organonitrogen compounds | ||||||||
| Tetradecylamine | C14H31N | 213.2457 | 14.11 | 6 | [M+H]+ | ESI + | Level 3 | 0.79 |
| Palmitoleoyl-EA | C18H35NO2 | 297.2668 | 16.31 | 8 | [M+Na]+ | ESI + | Level 3 | 0.34 |
| Organooxygen compounds | ||||||||
| Trehalose | C12H22O11 | 342.1162 | 1.13 | 0 | [M-H]− | ESI − | Level 2 | 0.93 |
| Kobusone | C14H22O2 | 222.1620 | 15.83 | 3 | [M-H]− | ESI − | Level 2 | 0.51 |
| Methyl-pentenone | C6H10O | 98.0732 | 16.46 | 1 | [M-H-H2O]− | ESI − | Level 3 | 0.75 |
| Methylpicraquassioside A | C19H24O10 | 412.1369 | 16.61 | 10 | [M+Cl]− | ESI − | Level 3 | 0.68 |
| (carboxymethoxy)- trihydroxyoxane-carboxylic acid | C8H12O9 | 252.0481 | 16.81 | 1 | [M+HCOOH-H]− | ESI − | Level 3 | 0.61 |
| Epoxyprogesterone | C21H28O3 | 328.2038 | 17.39 | 2 | [M-H]− | ESI − | Level 3 | 0.59 |
| Phenylpropanoids | ||||||||
| Clausarinol | C24H30O6 | 414.2042 | 14.59 | 4 | [M+H]+ | ESI + | Level 3 | 4.45 |
| 6-{[2-(dihydroxyphenyl)-3-(dimethylocta-dien-yl)-hydroxy-(3-methylbut-2-en-yl)-4-oxo-4H-chromen-6-yl]oxy}-trihydroxyoxane-carboxylic acid | C36H42O12 | 666.2676 | 15.58 | 1 | [M-H]− | ESI − | Level 3 | 0.33 |
| Nevskin | C24H32O5 | 400.2250 | 16.27 | 1 | [M+H]+ | ESI + | Level 3 | 0.60 |
| Methoxy-abietatrienolide | C21H28O3 | 328.2038 | 16.48 | 1 | [M-H]− | ESI − | Level 3 | 0.47 |
| Nordihydroguaiaretic acid | C18H22O4 | 302.1518 | 16.65 | 2 | [M-H]− | ESI − | Level 3 | 0.32 |
| Piperidines | ||||||||
| Pipercitine | C23H43NO | 349.3345 | 15.91 | 5 | [M+H-H2O]+ | ESI + | Level 3 | 4.88 |
| Polyketides | ||||||||
| Cannabidiolic acid | C22H30O4 | 358.2144 | 16.26 | 4 | [M+H-H2O]+ | ESI + | Level 3 | 7.15 |
| Cannflavin A | C26H28O6 | 436.1886 | 16.34 | 4 | [M+H]+ | ESI + | Level 3 | 1.84 |
| Betavulgarin | C17H12O6 | 312.0634 | 16.34 | 3 | [M+H]+ | ESI + | Level 3 | 1.18 |
| Cannflavin A | C26H28O6 | 436.1886 | 16.41 | 4 | [M+H]+ | ESI − | Level 3 | 2.55 |
| Chlorophorin | C24H28O4 | 380.1988 | 16.46 | 8 | [M+HCOOH-H]− | ESI − | Level 3 | 0.53 |
| Quercetol B | C23H28O4 | 368.1988 | 16.51 | 3 | [M-H]− | ESI − | Level 3 | 0.67 |
| Prenol lipids | ||||||||
| Icariside B8 | C19H32O8 | 388.2097 | 6.19 | 2 | [M-H]− | ESI − | Level 3 | 0.34 |
| Capsularone | C27H38O8 | 490.2567 | 11.77 | 1 | [M+HCOOH-H]− | ESI − | Level 3 | 0.66 |
| Diterpenoid EF-D | C27H38O7 | 474.2618 | 13.60 | 1 | [M+HCOOH-H]− | ESI − | Level 3 | 1.13 |
| Persicachrome | C25H36O3 | 384.2664 | 14.33 | 4 | [M+H-H2O]+ | ESI + | Level 3 | 0.72 |
| Nigellic acid | C15H20O5 | 280.1311 | 14.59 | 3 | [M+H]+ | ESI + | Level 3 | 0.37 |
| Yucalexin | C20H26O4 | 330.1831 | 15.67 | 4 | [M-H]− | ESI − | Level 3 | 0.49 |
| 2-(Hydroxy-methylphenyl)-5-methyl-4-hexen-3-one | C14H18O2 | 218.1307 | 15.67 | 7 | [M-H]− | ESI − | Level 3 | 0.38 |
| Tintinnadiol | C21H32O3 | 332.2351 | 15.76 | 1 | [M-H]− | ESI − | Level 3 | 1.21 |
| Hydroxymethylphenyl pentanone | C12H16O2 | 192.1150 | 15.76 | 5 | [M+H]+ | ESI + | Level 2 | 0.32 |
| Dimethylrosmanol | C22H30O5 | 374.2093 | 16.00 | 1 | [M-H]− | ESI − | Level 2 | 0.64 |
| hydroxy-methoxy-(3-methylbut-2-en-1-yl)benzoic acid | C13H16O4 | 236.1049 | 16.26 | 4 | [M+H-H2O]+ | ESI + | Level 2 | 0.77 |
| Lucidone B | C24H32O5 | 400.2250 | 16.28 | 1 | [M-H]− | ESI − | Level 2 | 1.53 |
| Pentylresorcinol | C11H16O2 | 180.1150 | 16.46 | 3 | [M-H]− | ESI − | Level 2 | 2.06 |
| Hyperforin | C35H52O4 | 536.3866 | 16.46 | 1 | [M-H-H2O]− | ESI − | Level 3 | 0.30 |
| Hydroxymethylphenyl)pentanone | C12H16O2 | 192.1150 | 16.47 | 5 | [M+H]+ | ESI +/- | Level 2 | 0.76 |
| Curzerenone | C15H18O2 | 230.1307 | 16.48 | 3 | [M-H]− | ESI − | Level 3 | 0.54 |
| Geranyl benzoate | C17H22O2 | 258.1620 | 16.49 | 6 | [M+H]+ | ESI + | Level 3 | 0.33 |
| Hydroxy- Caroten-3′-one | C40H54O | 550.4175 | 16.71 | 9 | [M+Na]+ | ESI + | Level 3 | 0.73 |
| Trimethyl-pentadecatrien-2-one | C18H30O | 262.2297 | 17.16 | 6 | [M+H]+ | ESI + | Level 2 | 0.82 |
| Grifolin | C22H32O2 | 328.2402 | 17.66 | 3 | [M-H]− | ESI − | Level 3 | 0.32 |
| Pyrazoles | ||||||||
| Glyceryl lactopalmitate | C20H16N6O2S | 404.1055 | 16.23 | 8 | [M+HCOOH-H]− | ESI − | Level 3 | 1.38 |
| Steroids and steroid derivatives | ||||||||
| Pregnadienedione | C21H28O2 | 312.2089 | 16.48 | 0 | [M-H]− | ESI − | Level 3 | 2.24 |
| Neriantogenin | C23H32O4 | 372.2301 | 17.66 | 2 | [M-H]− | ESI − | Level 3 | 2.89 |
| Sterol Lipids | ||||||||
| Rhodexin A | C29H44O9 | 536.2985 | 15.43 | 1 | [M+H]+ | ESI + | Level 3 | 0.45 |
| ST 27:0;O7 | C27H48O7 | 484.3400 | 16.77 | 4 | [M+H]+ | ESI + | Level 3 | 0.35 |
| Dihomocholic acid | C26H44O5 | 436.3189 | 17.30 | 8 | [M+Na]+ | ESI + | Level 3 | 0.53 |
| Precursor | EC Number | Is It Included in CannGEM? | |
|---|---|---|---|
| Anthocyanin biosynthesis | BZ1; anthocyanidin 3-O-glucosyltransferase | 2.4.1.115 | No |
| 3MaT1; anthocyanin 3-O-glucoside-6″-O-malonyltransferase | 2.3.1.171 | No | |
| 3MaT2; anthocyanidin 3-O-glucoside-3″,6″-O-dimalonyltransferase | 2.3.1.- | No | |
| 3GGT; anthocyanidin 3-O-glucoside 2″-O-glucosyltransferase | 2.4.1.297 | No | |
| 5GT; cyanidin 3-O-rutinoside 5-O-glucosyltransferase | 2.4.1.116 | No | |
| AA7GT; cyanidin 3-O-glucoside 7-O-glucosyltransferase (acyl-glucose) | 2.4.1.300 | No | |
| UGT79B1; anthocyanidin 3-O-glucoside 2′″-O-xylosyltransferase | 2.4.2.51 | No | |
| 3AT; anthocyanidin 3-O-glucoside 6″-O-acyltransferase | 2.3.1.215 | No | |
| 5MaT1; anthocyanin 5-O-glucoside-6′″-O-malonyltransferase | 2.3.1.172 | No | |
| 5MaT2; anthocyanin 5-O-glucoside-4′″-O-malonyltransferase | 2.3.1.214 | No | |
| UGT75C1; anthocyanidin 3-O-glucoside 5-O-glucosyltransferase | 2.4.1.298 | No | |
| AA5GT; cyanidin 3-O-glucoside 5-O-glucosyltransferase (acyl-glucose) | 2.4.1.299 | No | |
| 5AT; anthocyanin 5-aromatic acyltransferase | 2.3.1.153 | No | |
| UGAT; cyanidin-3-O-glucoside 2″-O-glucuronosyltransferase | 2.4.1.254 | No | |
| GT1; anthocyanidin 5,3-O-glucosyltransferase | 2.4.1.- | Yes | |
| 3GT; anthocyanin 3′-O-beta-glucosyltransferase | 2.4.1.238 | No | |
| Fatty acid biosynthesis | ACACA; acetyl-CoA carboxylase | 6.4.1.2 | Yes |
| ACSF3; malonyl-CoA/methylmalonyl-CoA synthetase | 6.2.1.- | Yes | |
| FASN; fatty acid synthase, animal type | 2.3.1.85 | Yes | |
| FAS1; fatty acid synthase subunit beta, fungi type | 2.3.1.86 | Yes | |
| fas; fatty acid synthase, bacteria type | 2.3.1.- | No | |
| HT2; 3-hydroxyacyl-thioester dehydratase, animal type | 4.2.1.- | No | |
| FATB; fatty acyl-ACP thioesterase B | 3.1.2.14 | Yes | |
| FATA; fatty acyl-ACP thioesterase A | 3.1.2.14 | Yes | |
| ACSL, fad; long-chain acyl-CoA synthetase | 6.2.1.3 | Yes | |
| Fatty acid degradation | ACAT, atoB; acetyl-CoA C-acetyltransferase | 2.3.1.9 | Yes |
| fadA, fadI; acetyl-CoA acyltransferase | 2.3.1.16 | Yes | |
| fadB; 3-hydroxyacyl-CoA dehydrogenase/enoyl-CoA hydratase/3-hydroxybutyryl-CoA epimerase/enoyl-CoA isomerase | 1.1.1.35 | Yes | |
| fadJ; 3-hydroxyacyl-CoA dehydrogenase/enoyl-CoA hydratase/3-hydroxybutyryl-CoA epimerase | 1.1.1.35 | Yes | |
| HAH; 3-hydroxyacyl-CoA dehydrogenase | 1.1.1.35 | Yes | |
| HAHA; enoyl-CoA hydratase/long-chain 3-hydroxyacyl-CoA dehydrogenase | 4.2.1.17 | No | |
| E1.3.3.6, ACOX1, ACOX3; acyl-CoA oxidase | 1.3.3.6 | No | |
| ACAS, bcd; butyryl-CoA dehydrogenase | 1.3.8.1 | No | |
| ACAM, acd; acyl-CoA dehydrogenase | 1.3.8.7 | No | |
| ACAL; long-chain-acyl-CoA dehydrogenase | 1.3.8.8 | No | |
| fadE; acyl-CoA dehydrogenase | 1.3.99.- | No | |
| ACASB; short-chain 2-methylacyl-CoA dehydrogenase | 1.3.8.5 | No | |
| ACAVL; very long chain acyl-CoA dehydrogenase | 1.3.8.9 | No | |
| GCH, gcdH; glutaryl-CoA dehydrogenase | 1.3.8.6 | No | |
| ACSL, fad; long-chain acyl-CoA synthetase | 6.2.1.3 | Yes | |
| CPT1A; carnitine O-palmitoyltransferase 1, liver isoform | 2.3.1.21 | No | |
| ECI1, CI; elta3-elta2-enoyl-CoA isomerase | 5.3.3.8 | No | |
| alkB1_2, alkM; alkane 1-monooxygenase | 1.14.15.3 | No | |
| hca; 3-phenylpropionate/trans-cinnamate dioxygenase ferredoxin reductase component | 1.18.1.3 | No | |
| rubB, alkT; rubredoxin---NA+ reductase | 1.18.1.1 | No | |
| AH1_7; alcohol dehydrogenase 1/7 | 1.1.1.1 | Yes | |
| frmA, AH5, adhC; S-(hydroxymethyl)glutathione dehydrogenase/alcohol dehydrogenase | 1.1.1.284 | No | |
| AH6; alcohol dehydrogenase 6 | 1.1.1.1 | Yes | |
| adhE; acetaldehyde dehydrogenase/alcohol dehydrogenase | 1.2.1.10 | No | |
| ALH; aldehyde dehydrogenase (NA+) | 1.2.1.3 | Yes | |
| ALH7A1; aldehyde dehydrogenase family 7 member A1 | 1.2.1.31 | No | |
| ALH9A1; aldehyde dehydrogenase family 9 member A1 | 1.2.1.47 | No | |
| cyp_E, CYP102A, CYP505; cytochrome P450/NAPH-cytochrome P450 reductase | 1.14.14.1 | No | |
| Fatty acid elongation | HAHB; acetyl-CoA acyltransferase | 2.3.1.16 | Yes |
| HAH; 3-hydroxyacyl-CoA dehydrogenase | 1.1.1.35 | Yes | |
| ECHS1; enoyl-CoA hydratase | 4.2.1.17 | No | |
| PPT; palmitoyl-protein thioesterase | 3.1.2.22 | Yes | |
| ELOVL1; elongation of very long chain fatty acids protein 1 | 2.3.1.199 | No | |
| HS17B12, KAR, IFA38; 17beta-estradiol 17-dehydrogenase/very-long-chain 3-oxoacyl-CoA reductase | 1.1.1.62 | No | |
| HAC, PHS1, PAS2; very-long-chain (3R)-3-hydroxyacyl-CoA dehydratase | 4.2.1.134 | No | |
| TER, TSC13, CER10; very-long-chain enoyl-CoA reductase | 1.3.1.93 | No | |
| ACOT1_2_4; acyl-coenzyme A thioesterase 1/2/4 | 3.1.2.2 | Yes | |
| Phenylalanine, tyrosine and tryptophan biosynthesis | E2.5.1.54, aroF, aroG, aroH; 3-deoxy-7-phosphoheptulonate synthase | 2.5.1.54 | Yes |
| ARO1; pentafunctional AROM polypeptide | 4.2.3.4 | Yes | |
| aroKB; shikimate kinase/3-dehydroquinate synthase | 2.7.1.71 | Yes | |
| K16305; fructose-bisphosphate aldolase/6-deoxy-5-ketofructose 1-phosphate synthase | 4.1.2.13 | Yes | |
| K11646; 3-dehydroquinate synthase II | 1.4.1.24 | No | |
| aro; 3-dehydroquinate dehydratase I | 4.2.1.10 | Yes | |
| QUIB, qa-3; quinate dehydrogenase | 1.1.1.24 | No | |
| aroE; shikimate dehydrogenase | 1.1.1.25 | Yes | |
| quiA; quinate dehydrogenase (quinone) | 1.1.5.8 | No | |
| ydiB; quinate/shikimate dehydrogenase | 1.1.1.282 | Yes | |
| aroK, aroL; shikimate kinase | 2.7.1.71 | Yes | |
| aroA; 3-phosphoshikimate 1-carboxyvinyltransferase | 2.5.1.19 | Yes | |
| K24018; cyclohexadieny/prephenate dehydrogenase/3-phosphoshikimate 1-carboxyvinyltransferase | 1.3.1.43 | No | |
| aroC; chorismate synthase | 4.2.3.5 | Yes | |
| TRP3; anthranilate synthase/indole-3-glycerol phosphate synthase | 4.1.3.27 | Yes | |
| trp; anthranilate phosphoribosyltransferase | 2.4.2.18 | Yes | |
| trpF; phosphoribosylanthranilate isomerase | 5.3.1.24 | Yes | |
| priA; phosphoribosyl isomerase A | 5.3.1.16 | Yes | |
| trpC; indole-3-glycerol phosphate synthase | 4.1.1.48 | Yes | |
| TRP; tryptophan synthase | 4.2.1.20 | Yes | |
| E5.4.99.5; chorismate mutase | 5.4.99.5 | Yes | |
| tyrA1; chorismate mutase | 5.4.99.5 | Yes | |
| tyrA; chorismate mutase/prephenate dehydrogenase | 5.4.99.5 | Yes | |
| pheA1; chorismate mutase | 5.4.99.5 | Yes | |
| pheA; chorismate mutase/prephenate dehydratase | 5.4.99.5 | Yes | |
| AROA1, aroA; chorismate mutase | 5.4.99.5 | Yes | |
| aroH; chorismate mutase | 5.4.99.5 | Yes | |
| pheB; chorismate mutase | 5.4.99.5 | Yes | |
| tyrA2; prephenate dehydrogenase | 1.3.1.12 | No | |
| TYR1; prephenate dehydrogenase (NAP+) | 1.3.1.13 | No | |
| tyrC; cyclohexadieny/prephenate dehydrogenase | 1.3.1.43 | No | |
| tyrAa; arogenate dehydrogenase (NAP+) | 1.3.1.78 | Yes | |
| pheC; cyclohexadienyl dehydratase | 4.2.1.51 | Yes | |
| AT, PT; arogenate/prephenate dehydratase | 4.2.1.91 | Yes | |
| GOT1; aspartate aminotransferase, cytoplasmic | 2.6.1.1 | Yes | |
| TAT; tyrosine aminotransferase | 2.6.1.5 | Yes | |
| hisC; histidinol-phosphate aminotransferase | 2.6.1.9 | Yes | |
| tyrB; aromatic-amino-acid transaminase | 2.6.1.57 | Yes | |
| ARO8; aromatic amino acid aminotransferase I/2-aminoadipate transaminase | 2.6.1.57 | Yes | |
| ARO9; aromatic amino acid aminotransferase II | 2.6.1.58 | Yes | |
| pdh; phenylalanine dehydrogenase | 1.4.1.20 | No | |
| IL4I1; L-amino-acid oxidase | 1.4.3.2 | No | |
| phhA, PAH; phenylalanine-4-hydroxylase | 1.14.16.1 | No | |
| hphA; benzylmalate synthase | 2.3.3.- | No | |
| hphC; 3-benzylmalate isomerase | 4.2.1.- | No | |
| hphB; 3-benzylmalate dehydrogenase | 1.1.1.- | Yes | |
| xanB2; chorismate lyase/3-hydroxybenzoate synthase | 4.1.3.40 | No | |
| fkbO, rapK; chorismatase | 3.3.2.13 | No | |
| Terpenoid backbone biosynthesis | dxs; 1-deoxy--xylulose-5-phosphate synthase | 2.2.1.7 | Yes |
| dxr; 1-deoxy--xylulose-5-phosphate reductoisomerase | 1.1.1.267 | Yes | |
| isp; 2-C-methyl--erythritol 4-phosphate cytidylyltransferase | 2.7.7.60 | Yes | |
| ispE; 4-diphosphocytidyl-2-C-methyl--erythritol kinase | 2.7.1.148 | Yes | |
| ispF; 2-C-methyl--erythritol 2,4-cyclodiphosphate synthase | 4.6.1.12 | Yes | |
| gcpE, ispG; (E)-4-hydroxy-3-methylbut-2-enyl-diphosphate synthase | 1.17.7.1 | Yes | |
| ispH, lytB; 4-hydroxy-3-methylbut-2-en-1-yl diphosphate reductase | 1.17.7.4 | No | |
| ACAT, atoB; acetyl-CoA C-acetyltransferase | 2.3.1.9 | Yes | |
| HMGCS; hydroxymethylglutaryl-CoA synthase | 2.3.3.10 | Yes | |
| HMGCR; hydroxymethylglutaryl-CoA reductase (NAPH) | 1.1.1.34 | Yes | |
| mvaA; hydroxymethylglutaryl-CoA reductase | 1.1.1.88 | No | |
| MVK, mvaK1; mevalonate kinase | 2.7.1.36 | Yes | |
| E2.7.4.2, mvaK2; phosphomevalonate kinase | 2.7.4.2 | Yes | |
| PMVK; phosphomevalonate kinase | 2.7.4.2 | Yes | |
| MV, mva; diphosphomevalonate decarboxylase | 4.1.1.33 | Yes | |
| pmd; phosphomevalonate decarboxylase | 4.1.1.99 | No | |
| ipk; isopentenyl phosphate kinase | 2.7.4.26 | No | |
| acnX1; mevalonate 5-phosphate dehydratase large subunit | 4.2.1.- | No | |
| K25518; trans-anhydromevalonate 5-phosphate decarboxylase | 4.1.1.- | Yes | |
| ubiX, bsdB, PA1; flavin prenyltransferase | 2.5.1.129 | No | |
| E2.7.1.185; mevalonate-3-kinase | 2.7.1.185 | No | |
| E2.7.1.186; mevalonate-3-phosphate-5-kinase | 2.7.1.186 | No | |
| E4.1.1.110; bisphosphomevalonate decarboxylase | 4.1.1.110 | No | |
| idi, II; isopentenyl-diphosphate elta-isomerase | 5.3.3.2 | Yes | |
| FPS; farnesyl diphosphate synthase | 2.5.1.1 | Yes | |
| E2.5.1.68; short-chain Z-isoprenyl diphosphate synthase | 2.5.1.68 | No | |
| ZFPS; (2Z,6Z)-farnesyl diphosphate synthase | 2.5.1.92 | No | |
| E2.5.1.86; trans, polycis-decaprenyl diphosphate synthase | 2.5.1.86 | No | |
| E2.5.1.88; trans, polycis-polyprenyl diphosphate synthase | 2.5.1.88 | No | |
| hexPS, COQ1; hexaprenyl-diphosphate synthase | 2.5.1.82 | No | |
| hexs-a; hexaprenyl-diphosphate synthase small subunit | 2.5.1.83 | No | |
| hepS; heptaprenyl diphosphate synthase component 1 | 2.5.1.30 | Yes | |
| ispB; octaprenyl-diphosphate synthase | 2.5.1.90 | No | |
| SPS, sds; all-trans-nonaprenyl-diphosphate synthase | 2.5.1.84 | Yes | |
| PSS1; decaprenyl-diphosphate synthase subunit 1 | 2.5.1.91 | No | |
| uppS; undecaprenyl diphosphate synthase | 2.5.1.31 | No | |
| NUS1; dehydrodolichyl diphosphate syntase complex subunit NUS1 | 2.5.1.87 | No | |
| uppS, cpdS; tritrans, polycis-undecaprenyl-diphosphate synthase [geranylgeranyl-diphosphate specific | Yes | ||
| chlP, bchP; geranylgeranyl diphosphate/geranylgeranyl-bacteriochlorophyllide a reductase | 1.3.1.83 | No | |
| ispS; isoprene synthase | 4.2.3.27 | No | |
| FNTA; protein farnesyltransferase/geranylgeranyltransferase type-1 subunit alpha | 2.5.1.58 | No | |
| RCE1, FACE2; prenyl protein peptidase | 3.4.22.- | No | |
| STE24; STE24 endopeptidase | 3.4.24.84 | No | |
| ICMT, STE14; protein-S-isoprenylcysteine O-methyltransferase | 2.1.1.100 | No | |
| PCME; prenylcysteine alpha-carboxyl methylesterase | 3.1.1.- | No | |
| PCYOX1, FCLY; prenylcysteine oxidase/farnesylcysteine lyase | 1.8.3.5 | No | |
| FOHSR; NAP+-dependent farnesol dehydrogenase | 1.1.1.216 | No | |
| FLH; NA+-dependent farnesol dehydrogenase | 1.1.1.354 | No | |
| FOLK; farnesol kinase | 2.7.1.216 | No | |
| K15793; acyclic sesquiterpene synthase | 4.2.3.49 | No | |