Structure

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Physi-Chem Properties

Molecular Weight:  242.09
Volume:  258.799
LogP:  2.935
LogD:  3.395
LogS:  -3.182
# Rotatable Bonds:  3
TPSA:  49.69
# H-Bond Aceptor:  3
# H-Bond Donor:  2
# Rings:  2
# Heavy Atoms:  3

MedChem Properties

QED Drug-Likeness Score:  0.812
Synthetic Accessibility Score:  1.97
Fsp3:  0.067
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:  -4.862
MDCK Permeability:  1.2656038052227814e-05
Pgp-inhibitor:  0.059
Pgp-substrate:  0.004
Human Intestinal Absorption (HIA):  0.019
20% Bioavailability (F20%):  0.96
30% Bioavailability (F30%):  0.962

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.036
Plasma Protein Binding (PPB):  97.64556884765625%
Volume Distribution (VD):  0.8
Pgp-substrate:  1.4343812465667725%

ADMET: Metabolism

CYP1A2-inhibitor:  0.989
CYP1A2-substrate:  0.49
CYP2C19-inhibitor:  0.783
CYP2C19-substrate:  0.06
CYP2C9-inhibitor:  0.41
CYP2C9-substrate:  0.963
CYP2D6-inhibitor:  0.718
CYP2D6-substrate:  0.9
CYP3A4-inhibitor:  0.969
CYP3A4-substrate:  0.198

ADMET: Excretion

Clearance (CL):  11.783
Half-life (T1/2):  0.869

ADMET: Toxicity

hERG Blockers:  0.409
Human Hepatotoxicity (H-HT):  0.049
Drug-inuced Liver Injury (DILI):  0.188
AMES Toxicity:  0.155
Rat Oral Acute Toxicity:  0.03
Maximum Recommended Daily Dose:  0.693
Skin Sensitization:  0.945
Carcinogencity:  0.264
Eye Corrosion:  0.219
Eye Irritation:  0.987
Respiratory Toxicity:  0.709

Download Data

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

  Natural Product: NPC296920

Natural Product ID:  NPC296920
Common Name*:   Resveratrol 4'-Methyl Ether
IUPAC Name:   5-[(E)-2-(4-methoxyphenyl)ethenyl]benzene-1,3-diol
Synonyms:  
Standard InCHIKey:  IHVRWFJGOIWMGC-NSCUHMNNSA-N
Standard InCHI:  InChI=1S/C15H14O3/c1-18-15-6-4-11(5-7-15)2-3-12-8-13(16)10-14(17)9-12/h2-10,16-17H,1H3/b3-2+
SMILES:  COc1ccc(cc1)/C=C/c1cc(O)cc(c1)O
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   CHEMBL291501
PubChem CID:   6255462
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000261] Phenylpropanoids and polyketides
      • [CHEMONTID:0000253] Stilbenes

*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 NPC296920 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 NPC296920 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