Structure

Physi-Chem Properties

Molecular Weight:  299.12
Volume:  304.621
LogP:  2.108
LogD:  2.402
LogS:  -3.6
# Rotatable Bonds:  3
TPSA:  67.79
# H-Bond Aceptor:  5
# H-Bond Donor:  2
# Rings:  3
# Heavy Atoms:  5

MedChem Properties

QED Drug-Likeness Score:  0.908
Synthetic Accessibility Score:  3.095
Fsp3:  0.235
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:  -4.789
MDCK Permeability:  2.215498170698993e-05
Pgp-inhibitor:  0.189
Pgp-substrate:  0.226
Human Intestinal Absorption (HIA):  0.005
20% Bioavailability (F20%):  0.187
30% Bioavailability (F30%):  0.978

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.982
Plasma Protein Binding (PPB):  84.28324890136719%
Volume Distribution (VD):  0.644
Pgp-substrate:  17.01970672607422%

ADMET: Metabolism

CYP1A2-inhibitor:  0.046
CYP1A2-substrate:  0.524
CYP2C19-inhibitor:  0.244
CYP2C19-substrate:  0.897
CYP2C9-inhibitor:  0.119
CYP2C9-substrate:  0.491
CYP2D6-inhibitor:  0.05
CYP2D6-substrate:  0.7
CYP3A4-inhibitor:  0.171
CYP3A4-substrate:  0.893

ADMET: Excretion

Clearance (CL):  1.086
Half-life (T1/2):  0.316

ADMET: Toxicity

hERG Blockers:  0.044
Human Hepatotoxicity (H-HT):  0.454
Drug-inuced Liver Injury (DILI):  0.772
AMES Toxicity:  0.76
Rat Oral Acute Toxicity:  0.194
Maximum Recommended Daily Dose:  0.045
Skin Sensitization:  0.547
Carcinogencity:  0.173
Eye Corrosion:  0.003
Eye Irritation:  0.024
Respiratory Toxicity:  0.095

Download Data

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

  Natural Product: NPC264078

Natural Product ID:  NPC264078
Common Name*:   VCKUOSKDXLTBDG-DOTOQJQBSA-N
IUPAC Name:   n.a.
Synonyms:  
Standard InCHIKey:  VCKUOSKDXLTBDG-DOTOQJQBSA-N
Standard InCHI:  InChI=1S/C17H17NO4/c1-21-12-9-7-11(8-10-12)17(20)13-5-3-4-6-14(13)18-16(19)15(17)22-2/h3-10,15,20H,1-2H3,(H,18,19)/t15-,17+/m0/s1
SMILES:  COc1ccc(cc1)[C@]1(c2ccccc2N=C([C@@H]1OC)O)O
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   n.a.
PubChem CID:   25768656
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000002] Organoheterocyclic compounds
      • [CHEMONTID:0001253] Quinolines and derivatives
        • [CHEMONTID:0002348] Phenylquinolines

*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
NPO15811 Sophora pachycarpa Species Fabaceae Eukaryota n.a. root n.a. PMID[17137127]
NPO15994 Dichotella gemmacea Species Ellisellidae Eukaryota n.a. South China Sea n.a. PMID[21721519]
NPO15994 Dichotella gemmacea Species Ellisellidae Eukaryota n.a. n.a. n.a. PMID[21721519]
NPO15994 Dichotella gemmacea Species Ellisellidae Eukaryota n.a. South China Sea n.a. PMID[22647719]
NPO15994 Dichotella gemmacea Species Ellisellidae Eukaryota n.a. n.a. n.a. PMID[23477504]
NPO15811 Sophora pachycarpa Species Fabaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO15811 Sophora pachycarpa Species Fabaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO15811 Sophora pachycarpa Species Fabaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO15811 Sophora pachycarpa Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO22177 Ilybius fenestratus Species Dytiscidae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO28246 Hypomyces rosellus Species Hypocreaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO15994 Dichotella gemmacea Species Ellisellidae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO3191.1 Aspergillus terricola var. indicus Varieties Aspergillaceae 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 NPC264078 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 NPC264078 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