Structure

Physi-Chem Properties

Molecular Weight:  297.14
Volume:  313.127
LogP:  2.406
LogD:  3.312
LogS:  -3.996
# Rotatable Bonds:  5
TPSA:  38.77
# H-Bond Aceptor:  4
# H-Bond Donor:  0
# Rings:  3
# Heavy Atoms:  4

MedChem Properties

QED Drug-Likeness Score:  0.633
Synthetic Accessibility Score:  2.539
Fsp3:  0.278
Lipinski Rule-of-5:  Accepted
Pfizer Rule:  Accepted
GSK Rule:  Accepted
BMS Rule:  1
Golden Triangle Rule:  Accepted
Chelating Alert:  0
PAINS Alert:  0

ADMET Properties (ADMETlab2.0)

ADMET: Absorption

Caco-2 Permeability:  -4.905
MDCK Permeability:  2.4850640329532325e-05
Pgp-inhibitor:  0.997
Pgp-substrate:  0.001
Human Intestinal Absorption (HIA):  0.006
20% Bioavailability (F20%):  0.673
30% Bioavailability (F30%):  0.01

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.411
Plasma Protein Binding (PPB):  94.8022689819336%
Volume Distribution (VD):  0.41
Pgp-substrate:  4.39337158203125%

ADMET: Metabolism

CYP1A2-inhibitor:  0.98
CYP1A2-substrate:  0.176
CYP2C19-inhibitor:  0.942
CYP2C19-substrate:  0.124
CYP2C9-inhibitor:  0.527
CYP2C9-substrate:  0.974
CYP2D6-inhibitor:  0.942
CYP2D6-substrate:  0.936
CYP3A4-inhibitor:  0.942
CYP3A4-substrate:  0.138

ADMET: Excretion

Clearance (CL):  8.936
Half-life (T1/2):  0.217

ADMET: Toxicity

hERG Blockers:  0.965
Human Hepatotoxicity (H-HT):  0.23
Drug-inuced Liver Injury (DILI):  0.658
AMES Toxicity:  0.015
Rat Oral Acute Toxicity:  0.015
Maximum Recommended Daily Dose:  0.225
Skin Sensitization:  0.891
Carcinogencity:  0.872
Eye Corrosion:  0.08
Eye Irritation:  0.523
Respiratory Toxicity:  0.941

Download Data

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

  Natural Product: NPC95889

Natural Product ID:  NPC95889
Common Name*:   CUTSGEORQNCXRC-SQSUNLSESA-N
IUPAC Name:   n.a.
Synonyms:  
Standard InCHIKey:  CUTSGEORQNCXRC-SQSUNLSESA-N
Standard InCHI:  InChI=1S/C18H19NO3/c20-18(19-11-5-6-12-19)8-4-2-1-3-7-15-9-10-16-17(13-15)22-14-21-16/h1-4,7-10,13H,5-6,11-12,14H2/b2-1+,7-3+,8-4+
SMILES:  C(=CC=CC(=O)N1CCCC1)/C=C/c1ccc2c(c1)OCO2
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   n.a.
PubChem CID:   11781469
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000002] Organoheterocyclic compounds
      • [CHEMONTID:0000296] Benzodioxoles

*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
NPO16915 Callyspongia aerizusa Species Callyspongiidae Eukaryota n.a. n.a. n.a. PMID[26213786]
NPO14795 Vitis coignetiae Species Vitaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO14795 Vitis coignetiae Species Vitaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO16447 Potato virus n.a. n.a. n.a. n.a. n.a. n.a. Database[UNPD]
NPO2913 Tabebuia pentaphylla Species Bignoniaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO18069 Streptomyces coelicoflavus Species Streptomycetaceae Bacteria n.a. n.a. n.a. Database[UNPD]
NPO16048 Euphorbia serrata Species Euphorbiaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO21786 Culcitium serratifolium Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO15734 Euchresta horsfeldii Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO17297 Caragana pygmaea Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO15893 Solandra guttata Species Solanaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO17517 Artemisia arborescens Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO15369 Tabernaemontana rupicola Species Apocynaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO16915 Callyspongia aerizusa Species Callyspongiidae 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 NPC95889 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 NPC95889 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