Structure

Physi-Chem Properties

Molecular Weight:  298.12
Volume:  316.841
LogP:  3.719
LogD:  3.672
LogS:  -4.56
# Rotatable Bonds:  4
TPSA:  44.76
# H-Bond Aceptor:  4
# H-Bond Donor:  0
# Rings:  2
# Heavy Atoms:  4

MedChem Properties

QED Drug-Likeness Score:  0.593
Synthetic Accessibility Score:  5.242
Fsp3:  0.389
Lipinski Rule-of-5:  Accepted
Pfizer Rule:  Rejected
GSK Rule:  Accepted
BMS Rule:  0
Golden Triangle Rule:  Accepted
Chelating Alert:  0
PAINS Alert:  0

ADMET Properties (ADMETlab2.0)

ADMET: Absorption

Caco-2 Permeability:  -4.542
MDCK Permeability:  1.7768663383321837e-05
Pgp-inhibitor:  0.179
Pgp-substrate:  0.0
Human Intestinal Absorption (HIA):  0.07
20% Bioavailability (F20%):  0.978
30% Bioavailability (F30%):  1.0

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.055
Plasma Protein Binding (PPB):  99.89457702636719%
Volume Distribution (VD):  2.164
Pgp-substrate:  3.2778494358062744%

ADMET: Metabolism

CYP1A2-inhibitor:  0.853
CYP1A2-substrate:  0.079
CYP2C19-inhibitor:  0.916
CYP2C19-substrate:  0.324
CYP2C9-inhibitor:  0.889
CYP2C9-substrate:  0.138
CYP2D6-inhibitor:  0.807
CYP2D6-substrate:  0.097
CYP3A4-inhibitor:  0.94
CYP3A4-substrate:  0.57

ADMET: Excretion

Clearance (CL):  12.041
Half-life (T1/2):  0.479

ADMET: Toxicity

hERG Blockers:  0.01
Human Hepatotoxicity (H-HT):  0.992
Drug-inuced Liver Injury (DILI):  0.981
AMES Toxicity:  0.974
Rat Oral Acute Toxicity:  0.963
Maximum Recommended Daily Dose:  0.957
Skin Sensitization:  0.941
Carcinogencity:  0.963
Eye Corrosion:  0.012
Eye Irritation:  0.067
Respiratory Toxicity:  0.928

Download Data

Data Type Select
General Info & Identifiers & Properties  
Structure MOL file  
Source Organisms  
Biological Activities  
Similar NPs/Drugs  

  Natural Product: NPC198269

Natural Product ID:  NPC198269
Common Name*:   UDLGECIJZAXBNN-SVCXMFRPSA-N
IUPAC Name:   n.a.
Synonyms:  
Standard InCHIKey:  UDLGECIJZAXBNN-SVCXMFRPSA-N
Standard InCHI:  InChI=1S/C18H18O4/c1-4-5-6-7-8-15-9-11-18(22-15)16(10-12-20-18)21-17(19)13-14(2)3/h8-12,14,16H,13H2,1-3H3/b15-8+/t16-,18+/m0/s1
SMILES:  CC#CC#C/C=C/1C=C[C@]2([C@H](C=CO2)OC(=O)CC(C)C)O1
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   n.a.
PubChem CID:   n.a.
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000012] Lipids and lipid-like molecules
      • [CHEMONTID:0003909] Fatty Acyls
        • [CHEMONTID:0000324] Fatty acid esters

*Note: the InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
**Note: the Chemical Classification was calculated by NPClassifier Version 1.5. Reference: PMID:34662515.

  Species Source

Organism ID Organism Name Taxonomy Level Family SuperKingdom Isolation Part Collection Location Collection Time Reference
NPO11629 Brassica nigra Species Brassicaceae Eukaryota n.a. n.a. n.a. PMID[21861458]
NPO11629 Brassica nigra Species Brassicaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO11629 Brassica nigra Species Brassicaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO15577 Volvariella volvacea Species Pluteaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO18546 Senna longiracemosa Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO19655 Larix sukaczewii Species Pinaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO15940 Pinus gerardiana Species Pinaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO18201 Gonimbrasia belina n.a. n.a. n.a. n.a. n.a. n.a. Database[UNPD]
NPO11629 Brassica nigra Species Brassicaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO18469 Anochetus mayri Species Formicidae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO19200 Rolandra fruticosa Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO19109 Cetraria sanguinea Species Parmeliaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO15577 Volvariella volvacea Species Pluteaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO18798 Parmelia perlata Species Parmeliaceae 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 NP ID 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

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

☑ Note for Activity Records:
☉ The quantitative biological activities were primarily integrated from ChEMBL (Version-30) database and were also directly collected from PubMed literature. PubMed PMID was provided as the reference link for each activity record.

  Chemically structural similarity: I. Similar Active Natural Products in NPASS

Top-200 similar NPs were calculated against the active-NP-set (includes 4,3285 NPs with experimentally-derived bioactivity available in NPASS)

Similarity level is defined by Tanimoto coefficient (Tc) between two molecules. Tc lies between [0, 1] where '1' indicates the highest similarity. What is Tanimoto coefficient

●  The left chart: Distribution of similarity level between NPC198269 and all remaining natural products in the NPASS database.
●  The right table: Most similar natural products (Tc>=0.56 or Top200).

Similarity Score Similarity Level Natural Product ID

  Chemically structural similarity: II. Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC198269 and all drugs/candidates.
●  The right table: Most similar clinical/approved drugs (Tc>=0.56 or Top200).

Similarity Score Similarity Level Drug ID Developmental Stage

  Bioactivity similarity: Similar Natural Products in NPASS

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