Structure

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Physi-Chem Properties

Molecular Weight:  246.09
Volume:  252.929
LogP:  3.389
LogD:  2.599
LogS:  -3.511
# Rotatable Bonds:  2
TPSA:  66.76
# H-Bond Aceptor:  4
# H-Bond Donor:  2
# Rings:  2
# Heavy Atoms:  4

MedChem Properties

QED Drug-Likeness Score:  0.799
Synthetic Accessibility Score:  2.333
Fsp3:  0.214
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:  -4.885
MDCK Permeability:  1.120307842938928e-05
Pgp-inhibitor:  0.005
Pgp-substrate:  0.003
Human Intestinal Absorption (HIA):  0.014
20% Bioavailability (F20%):  0.076
30% Bioavailability (F30%):  0.025

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.027
Plasma Protein Binding (PPB):  97.56539154052734%
Volume Distribution (VD):  0.626
Pgp-substrate:  3.2605197429656982%

ADMET: Metabolism

CYP1A2-inhibitor:  0.98
CYP1A2-substrate:  0.934
CYP2C19-inhibitor:  0.422
CYP2C19-substrate:  0.14
CYP2C9-inhibitor:  0.603
CYP2C9-substrate:  0.861
CYP2D6-inhibitor:  0.66
CYP2D6-substrate:  0.683
CYP3A4-inhibitor:  0.432
CYP3A4-substrate:  0.193

ADMET: Excretion

Clearance (CL):  7.962
Half-life (T1/2):  0.655

ADMET: Toxicity

hERG Blockers:  0.021
Human Hepatotoxicity (H-HT):  0.062
Drug-inuced Liver Injury (DILI):  0.866
AMES Toxicity:  0.574
Rat Oral Acute Toxicity:  0.308
Maximum Recommended Daily Dose:  0.752
Skin Sensitization:  0.883
Carcinogencity:  0.094
Eye Corrosion:  0.058
Eye Irritation:  0.975
Respiratory Toxicity:  0.893

Download Data

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

  Natural Product: NPC94076

Natural Product ID:  NPC94076
Common Name*:   Torachrysone
IUPAC Name:   1-(1,8-dihydroxy-6-methoxy-3-methylnaphthalen-2-yl)ethanone
Synonyms:   Torachrysone
Standard InCHIKey:  BIJOPUWEMBBDEG-UHFFFAOYSA-N
Standard InCHI:  InChI=1S/C14H14O4/c1-7-4-9-5-10(18-3)6-11(16)13(9)14(17)12(7)8(2)15/h4-6,16-17H,1-3H3
SMILES:  Cc1cc2cc(cc(c2c(c1C(=O)C)O)O)OC
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   CHEMBL2204398
PubChem CID:   5321977
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0002448] Benzenoids
      • [CHEMONTID:0000023] Naphthalenes
        • [CHEMONTID:0002441] Naphthols and derivatives

*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 NPC94076 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 NPC94076 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