Structure

Physi-Chem Properties

Molecular Weight:  318.22
Volume:  341.348
LogP:  1.954
LogD:  2.522
LogS:  -3.409
# Rotatable Bonds:  2
TPSA:  57.53
# H-Bond Aceptor:  3
# H-Bond Donor:  2
# Rings:  4
# Heavy Atoms:  3

MedChem Properties

QED Drug-Likeness Score:  0.769
Synthetic Accessibility Score:  5.821
Fsp3:  0.85
Lipinski Rule-of-5:  Accepted
Pfizer Rule:  Accepted
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:  -4.847
MDCK Permeability:  9.221575055562425e-06
Pgp-inhibitor:  0.023
Pgp-substrate:  0.004
Human Intestinal Absorption (HIA):  0.004
20% Bioavailability (F20%):  0.642
30% Bioavailability (F30%):  0.006

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.808
Plasma Protein Binding (PPB):  51.92253112792969%
Volume Distribution (VD):  0.816
Pgp-substrate:  44.60491943359375%

ADMET: Metabolism

CYP1A2-inhibitor:  0.032
CYP1A2-substrate:  0.264
CYP2C19-inhibitor:  0.031
CYP2C19-substrate:  0.771
CYP2C9-inhibitor:  0.046
CYP2C9-substrate:  0.101
CYP2D6-inhibitor:  0.014
CYP2D6-substrate:  0.395
CYP3A4-inhibitor:  0.791
CYP3A4-substrate:  0.216

ADMET: Excretion

Clearance (CL):  6.397
Half-life (T1/2):  0.83

ADMET: Toxicity

hERG Blockers:  0.013
Human Hepatotoxicity (H-HT):  0.637
Drug-inuced Liver Injury (DILI):  0.034
AMES Toxicity:  0.186
Rat Oral Acute Toxicity:  0.751
Maximum Recommended Daily Dose:  0.886
Skin Sensitization:  0.053
Carcinogencity:  0.642
Eye Corrosion:  0.004
Eye Irritation:  0.344
Respiratory Toxicity:  0.975

Download Data

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

  Natural Product: NPC303158

Natural Product ID:  NPC303158
Common Name*:   WCGWZJOGQROUFC-SGFSRKTBSA-N
IUPAC Name:   n.a.
Synonyms:  
Standard InCHIKey:  WCGWZJOGQROUFC-SGFSRKTBSA-N
Standard InCHI:  InChI=1S/C20H30O3/c1-13-9-19-8-5-16-18(2,15(19)4-3-14(13)10-19)7-6-17(23)20(16,11-21)12-22/h14-16,21-22H,1,3-12H2,2H3/t14-,15+,16+,18+,19-/m0/s1
SMILES:  C=C1C[C@@]23CC[C@@H]4[C@](C)(CCC(=O)C4(CO)CO)[C@H]3CC[C@H]1C2
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   n.a.
PubChem CID:   72204298
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000012] Lipids and lipid-like molecules
      • [CHEMONTID:0000259] Prenol lipids
        • [CHEMONTID:0001551] Diterpenoids
          • [CHEMONTID:0003782] Kaurane diterpenoids

*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
NPO29103 Spongia matamata Species Spongiidae Eukaryota n.a. n.a. n.a. PMID[10075761]
NPO28939 Piptanthus nepalensis Species Fabaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO28939 Piptanthus nepalensis Species Fabaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO28939 Piptanthus nepalensis Species Fabaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO26540 Echinopsis spachiana Species Cactaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO29402 Launaea arborescens Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO29194 Harziella entomophila n.a. n.a. n.a. n.a. n.a. n.a. Database[UNPD]
NPO29013 Annulohypoxylon cohaerens Species Xylariaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO25969 Aspergillus nomius Species Aspergillaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO28870 Clausena lenis Species Rutaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO11524 Macrotomia ugamensis Species Boraginaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO28808 Piptanthus mongolicus Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO28939 Piptanthus nepalensis Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO29157 Reichardia gaditana Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO28829 Pelvetia wrightii Species Fucaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO28974 Smilax ornata Species Staphylinidae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO29103 Spongia matamata Species Spongiidae 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 NPC303158 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 NPC303158 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