Natural Product: NPC117691

Natural Product IDNPC117691
Common Name
?
The InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
PRAUVHZJPXOEIF-VGKQSNDQSA-N
IUPAC Name n.a.
Synonyms
Synthetic Gene Cluster n.a.
ChEMBL Identifier n.a.
PubChem CID 6710742
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 PRAUVHZJPXOEIF-VGKQSNDQSA-N
Standard InCHI InChI=1S/C30H48O6/c1-16-9-10-30(25(35)36)12-11-28(5)18(22(30)17(16)2)7-8-21-26(3)13-20(33)24(34)27(4,15-31)23(26)19(32)14-29(21,28)6/h7,16-17,19-24,31-34H,8-15H2,1-6H3,(H,35,36)/t16-,17+,19-,20-,21?,22+,23?,24+,26-,27+,28-,29-,30+/m1/s1
SMILES C[C@@H]1CC[C@@]2(CC[C@]3(C)C(=CCC4[C@@]5(C)C[C@H]([C@@H]([C@@](C)(CO)C5[C@@H](C[C@@]34C)O)O)O)[C@@H]2[C@H]1C)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
NPO11144 Centella asiatica Species Apiaceae Eukaryota n.a. n.a. n.a. PMID[ 17560738]
NPO11144 Centella asiatica Species Apiaceae Eukaryota n.a. n.a. n.a. DOI[10.1007/s11816-015-0350-y]
NPO11144 Centella asiatica Species Apiaceae Eukaryota n.a. aerial part n.a. PMID[17520525]
NPO11144 Centella asiatica Species Apiaceae Eukaryota n.a. n.a. n.a. PMID[22966846]
NPO11144 Centella asiatica Species Apiaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO11144 Centella asiatica Species Apiaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO11144 Centella asiatica Species Apiaceae Eukaryota n.a. n.a. n.a. Database[MetaboLights]
NPO11144 Centella asiatica Species Apiaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO11144 Centella asiatica Species Apiaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO11144 Centella asiatica Species Apiaceae Eukaryota n.a. n.a. n.a. Database[TM-MC]
NPO11144 Centella asiatica Species Apiaceae Eukaryota 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

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 NPC117691 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
1.0 High Similarity NPC305464
1.0 High Similarity NPC19376
1.0 High Similarity NPC25848
0.8125 Intermediate Similarity NPC32407
0.8125 Intermediate Similarity NPC263548
0.8125 Intermediate Similarity NPC606320
0.7424 Intermediate Similarity NPC71074
0.7424 Intermediate Similarity NPC605937
0.7273 Intermediate Similarity NPC307282
0.6812 Remote Similarity NPC40092
0.6812 Remote Similarity NPC87095
0.6667 Remote Similarity NPC61543
0.6667 Remote Similarity NPC293048
0.6667 Remote Similarity NPC225585
0.6429 Remote Similarity NPC37221
0.6301 Remote Similarity NPC20235
0.6301 Remote Similarity NPC299996
0.6301 Remote Similarity NPC117663
0.6286 Remote Similarity NPC51700
0.6286 Remote Similarity NPC88716
0.6286 Remote Similarity NPC68160
0.6232 Remote Similarity NPC43686
0.6197 Remote Similarity NPC88116
0.6111 Remote Similarity NPC173089
0.6027 Remote Similarity NPC247139
0.5972 Remote Similarity NPC231063
0.5972 Remote Similarity NPC282395
0.5972 Remote Similarity NPC173744
0.5972 Remote Similarity NPC204961
0.5972 Remote Similarity NPC73004
0.5972 Remote Similarity NPC609452
0.5946 Remote Similarity NPC137072
0.5915 Remote Similarity NPC477289
0.589 Remote Similarity NPC477288
0.5844 Remote Similarity NPC230151
0.5789 Remote Similarity NPC479743
0.5775 Remote Similarity NPC274050
0.5775 Remote Similarity NPC162632
0.5753 Remote Similarity NPC73489
0.5753 Remote Similarity NPC130278
0.5753 Remote Similarity NPC110308
0.5733 Remote Similarity NPC25299
0.5733 Remote Similarity NPC481322
0.5694 Remote Similarity NPC274330
0.5541 Remote Similarity NPC472149
0.5541 Remote Similarity NPC300351
0.5526 Remote Similarity NPC477290
0.5467 Remote Similarity NPC259733
0.5467 Remote Similarity NPC158371
0.5467 Remote Similarity NPC207922
0.5405 Remote Similarity NPC84319
0.5405 Remote Similarity NPC52021
0.5405 Remote Similarity NPC599947
0.5395 Remote Similarity NPC118519
0.5395 Remote Similarity NPC485589
0.5357 Remote Similarity NPC57362
0.5342 Remote Similarity NPC277399
0.5326 Remote Similarity NPC479747
0.5326 Remote Similarity NPC479746
0.5294 Remote Similarity NPC177246
0.5256 Remote Similarity NPC481318
0.52 Remote Similarity NPC64872
0.52 Remote Similarity NPC25906
0.5195 Remote Similarity NPC201657
0.5132 Remote Similarity NPC481314
0.5128 Remote Similarity NPC127689
0.5125 Remote Similarity NPC485586
0.5125 Remote Similarity NPC485588
0.5065 Remote Similarity NPC291028
0.5065 Remote Similarity NPC145667

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC117691 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