Natural Product: NPC195715

Natural Product IDNPC195715
Common Name
?
The InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
3Alpha-O-Acetylolean-12-En-23,27-Dioic Acid
IUPAC Name (3R,4S,4aR,6aR,6bR,8aR,12aR,14aR,14bR)-3-acetyloxy-4,6a,8a,11,11,14b-hexamethyl-1,2,3,4a,5,6,7,8,9,10,12,12a,14,14a-tetradecahydropicene-4,6b-dicarboxylic acid
Synonyms
Synthetic Gene Cluster n.a.
ChEMBL Identifier CHEMBL1079029
PubChem CID 44254603
Chemical Classification
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000012] Lipids and lipid-like molecules
      • [CHEMONTID:0000259] Prenol lipids
        • [CHEMONTID:0001553] Triterpenoids

The Chemical Classification was calculated by Classyfire, a software for chemical taxonomy calculation. Reference: DOI:10.1186/s13321-016-0174-y.

  Chemical Representations

Standard InCHIKey DFNMEZDDQABOQT-DBKYOHCFSA-N
Standard InCHI InChI=1S/C32H48O6/c1-19(33)38-24-11-12-29(5)22-9-8-20-21-18-27(2,3)14-15-28(21,4)16-17-32(20,26(36)37)30(22,6)13-10-23(29)31(24,7)25(34)35/h8,21-24H,9-18H2,1-7H3,(H,34,35)(H,36,37)/t21-,22+,23+,24+,28+,29+,30+,31-,32+/m0/s1
SMILES CC(=O)O[C@@H]1CC[C@]2(C)[C@H]3CC=C4[C@@H]5CC(C)(C)CC[C@]5(C)CC[C@@]4(C(=O)O)[C@]3(C)CC[C@H]2[C@]1(C)C(=O)O

  Calculated Properties

Physi-Chem Properties

MedChem Properties

ADMET Properties (ADMETlab3.0)

ADMET: Absorption

ADMET: Distribution

ADMET: Metabolism

ADMET: Excretion

ADMET: Toxicity

  Species Source

Organism ID Organism Name Taxonomy Level Family SuperKingdom Isolation Part Collection Location Collection Time Reference
NPO24475 Aceriphyllum rossii n.a. n.a. n.a. n.a. n.a. n.a. PMID[19618898]
NPO24475 Aceriphyllum rossii n.a. n.a. n.a. n.a. n.a. n.a. Database[COCONUT]
NPO24475 Aceriphyllum rossii n.a. n.a. n.a. n.a. n.a. n.a. Database[UNPD]

Note for Reference:
In addition to directly collecting NP source organism data from primary literature (where reference will provided as NCBI PMID or DOI links), NPASS also integrated them from below databases:
UNPD: Universal Natural Products Database [PMID: 23638153].
StreptomeDB: a database of streptomycetes natural products [PMID: 33051671].
TM-MC: a database of medicinal materials and chemical compounds in Northeast Asian traditional medicine [PMID: 26156871].
TCM@Taiwan: a Traditional Chinese Medicine database [PMID: 21253603].
TCMID: a Traditional Chinese Medicine database [PMID: 29106634].
TCMSP: The traditional Chinese medicine systems pharmacology database and analysis platform [PMID: 24735618].
HerDing: a herb recommendation system to treat diseases using genes and chemicals [PMID: 26980517].
MetaboLights: a metabolomics database [PMID: 27010336].
FooDB: a database of constituents, chemistry and biology of food species [www.foodb.ca].



  NP Quantity Composition/Concentration

Organism ID Organism Name Organism Material Preparation Organism Part NP Quantity (Standard) NP Quantity (Minimum) NP Quantity (Maximum) Quantity Unit Reference

Note for Reference:
In addition to directly collecting NP quantitative data from primary literature (where reference will provided as NCBI PMID or DOI links), NPASS also integrated NP quantitative records for specific NP domains (e.g., NPS from foods or herbs) from domain-specific databases. These databases include:
DUKE: Dr. Duke's Phytochemical and Ethnobotanical Databases.
PHENOL EXPLORER: is the first comprehensive database on polyphenol content in foods [PMID: 24103452], its homepage can be accessed at here.
FooDB: a database of constituents, chemistry and biology of food species [www.foodb.ca].



 Biological Activity

Molecular-level activity

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference

In vitro activity

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference
NPT83 Cell line MCF7 Homo sapiens IC50 = 58440.0 nM PMID[19743809]
NPT20529 Non-molecular NON-PROTEIN TARGET n.a. IC50 > 150000.0 nM PMID[19618898]

In vivo activity

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference





 Experimental ADME

Experiment Model Experiment Tissue ADME Type ADME Relation ADME Value ADME Unit Reference





 Experimental Toxicity

Quantitative toxicity

Experiment Model Experiment Organism Toxicity Type Toxicity Relation Toxicity Value Toxicity Unit Reference

Common Abbreviations:
LC: Lethal Concentration; LD: Lethal Dose; LT:Lethal Time; NOAEL: No-observed-adverse-effect Level; BMDL: Benchmark Dose Lower Confidence Limit; BMD: Benchmark Dose; BMC:Benchmark Concentration; LOAEL: Lowest Observed Adverse Effect Level; RfD:Reference Dose; RfC:Reference Concentration; MRL: Minimal Risk Level; MEG: Maximum Exposure Guideline; PAC: Protective Action Criteria

Categorical toxicity labels

Hepatotoxicity Carcinogenicity Mutagenicity Cardiotoxicity Respiratory Toxicity Eye Irritation Endocrine Disruption
Hepatotoxicity Carcinogenicity Mutagenicity Cardiotoxicity Respiratory Toxicity Eye Irritation Endocrine Disruption

Note for Reference:
In addition to directly collecting NP quantitative data from primary literature (where reference will provided as NCBI PMID or DOI links), NPASS also integrated NP toxicity records from domain-specific databases. These databases include:
ToxValDB: a curated database that compiles quantitative toxicity values for chemicals from diverse public sources to support toxicological research and risk assessment.
TOXRIC: a comprehensive, free-to-access, online database providing toxicological/feature data. The toxicity labels are retrieved from this database. [PMID: 36400569]


  Chemically structural similarity

Similar Active Natural Products in NPASS

Top-200 similar NPs were calculated against the active-NP-set (includes approximately 50,000 NPs with experimentally-derived bioactivity available in NPASS)

Similarity is measured using the Tanimoto coefficient (Tc) , which compares the binary fingerprints of two molecules. Tc is calculated as the intersection divided by the union of '1' bits in the fingerprints, ranging from 0 to 1, with 1 indicating highest similarity.

●  The left chart: Distribution of similarity level between NPC195715 and all remaining natural products in the NPASS database.
●  The right table: Most similar natural products (Tc>=0.5 or Top200).

Similarity Score Similarity Level Natural Product ID
0.7313 Intermediate Similarity NPC470590
0.7313 Intermediate Similarity NPC285184
0.6812 Remote Similarity NPC23621
0.6301 Remote Similarity NPC260149
0.6232 Remote Similarity NPC251779
0.6232 Remote Similarity NPC199595
0.6143 Remote Similarity NPC17733
0.6143 Remote Similarity NPC470629
0.6111 Remote Similarity NPC1753
0.6081 Remote Similarity NPC78580
0.6 Remote Similarity NPC158347
0.5811 Remote Similarity NPC209868
0.5676 Remote Similarity NPC126369
0.5676 Remote Similarity NPC470589
0.5676 Remote Similarity NPC184006
0.5676 Remote Similarity NPC111110
0.5467 Remote Similarity NPC60755
0.5467 Remote Similarity NPC77099
0.5393 Remote Similarity NPC469447
0.52 Remote Similarity NPC473240
0.5135 Remote Similarity NPC71507
0.5132 Remote Similarity NPC189880
0.5067 Remote Similarity NPC471901

Similar Clinical/Approved Drugs

Similarity level is defined by Tanimoto coefficient (Tc) between two molecules.

●  The left chart: Distribution of similarity level between NPC195715 and all drugs/candidates.
●  The right table: Most similar clinical/approved drugs (Tc>=0.5 or Top200).

Similarity Score Similarity Level Drug ID Developmental Stage
NPD

Bioactivity similarity

  Bioactivity similarity

Similar Natural Products in NPASS

Similarity level is defined by Bioactivity similarity was calculated based on bioactivity descriptors of compounds. The bioactivity descriptors were calculated by a recently developed AI algorithm Chemical Checker (CC) [Nature Biotechnology, 38:1087–1096, 2020; Nature Communications, 12:3932, 2021], which evaluated bioactivity similarities at five levels:
A: chemistry similarity;
B: biological targets similarity;
C: networks similarity;
D: cell-based bioactivity similarity;
E: similarity based on clinical data.
Those 5 categories of CC bioactivity descriptors were calculated and then subjected to manifold projection using UMAP algorithm, to project all NPs on a 2-Dimensional space. The current NP was highlighted with a small circle in the 2-D map. Below figures: left-to-right, A-to-E.

A: chemistry similarity
B: biological targets similarity
C: networks similarity
D: cell-based bioactivity similarity
E: similarity based on clinical data