Structure

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Physi-Chem Properties

Molecular Weight:  258.09
Volume:  261.669
LogP:  3.119
LogD:  3.187
LogS:  -4.322
# Rotatable Bonds:  1
TPSA:  48.67
# H-Bond Aceptor:  4
# H-Bond Donor:  0
# Rings:  3
# Heavy Atoms:  4

MedChem Properties

QED Drug-Likeness Score:  0.738
Synthetic Accessibility Score:  2.807
Fsp3:  0.267
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:  -4.628
MDCK Permeability:  2.036389196291566e-05
Pgp-inhibitor:  0.984
Pgp-substrate:  0.001
Human Intestinal Absorption (HIA):  0.01
20% Bioavailability (F20%):  0.005
30% Bioavailability (F30%):  0.948

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.068
Plasma Protein Binding (PPB):  88.04528045654297%
Volume Distribution (VD):  0.975
Pgp-substrate:  9.80951976776123%

ADMET: Metabolism

CYP1A2-inhibitor:  0.968
CYP1A2-substrate:  0.897
CYP2C19-inhibitor:  0.716
CYP2C19-substrate:  0.659
CYP2C9-inhibitor:  0.525
CYP2C9-substrate:  0.831
CYP2D6-inhibitor:  0.863
CYP2D6-substrate:  0.853
CYP3A4-inhibitor:  0.708
CYP3A4-substrate:  0.448

ADMET: Excretion

Clearance (CL):  9.022
Half-life (T1/2):  0.389

ADMET: Toxicity

hERG Blockers:  0.022
Human Hepatotoxicity (H-HT):  0.954
Drug-inuced Liver Injury (DILI):  0.953
AMES Toxicity:  0.188
Rat Oral Acute Toxicity:  0.877
Maximum Recommended Daily Dose:  0.235
Skin Sensitization:  0.453
Carcinogencity:  0.913
Eye Corrosion:  0.005
Eye Irritation:  0.096
Respiratory Toxicity:  0.943

Download Data

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

  Natural Product: NPC173350

Natural Product ID:  NPC173350
Common Name*:   5-Methoxyseselin
IUPAC Name:   5-methoxy-8,8-dimethylpyrano[2,3-f]chromen-2-one
Synonyms:   5-Methoxyseselin
Standard InCHIKey:  ZNMRQYJUVCXNGK-UHFFFAOYSA-N
Standard InCHI:  InChI=1S/C15H14O4/c1-15(2)7-6-10-12(19-15)8-11(17-3)9-4-5-13(16)18-14(9)10/h4-8H,1-3H3
SMILES:  CC1(C)C=Cc2c(cc(c3ccc(=O)oc23)OC)O1
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   CHEMBL479894
PubChem CID:   290897
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000261] Phenylpropanoids and polyketides
      • [CHEMONTID:0000145] Coumarins and derivatives
        • [CHEMONTID:0003484] Pyranocoumarins
          • [CHEMONTID:0003485] Angular pyranocoumarins

*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

☑ 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

☑ 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

☑ 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 NPC173350 and all remaining natural products in the NPASS database.
●  The right table: Most similar natural products (Tc>=0.56 or Top200).

  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 NPC173350 and all drugs/candidates.
●  The right table: Most similar clinical/approved drugs (Tc>=0.56 or Top200).

  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