Structure

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Physi-Chem Properties

Molecular Weight:  742.08
Volume:  673.528
LogP:  5.871
LogD:  2.557
LogS:  -11.227
# Rotatable Bonds:  6
TPSA:  287.14
# H-Bond Aceptor:  18
# H-Bond Donor:  11
# Rings:  8
# Heavy Atoms:  18

MedChem Properties

QED Drug-Likeness Score:  0.078
Synthetic Accessibility Score:  3.775
Fsp3:  0.0
Lipinski Rule-of-5:  Rejected
Pfizer Rule:  Accepted
GSK Rule:  Rejected
BMS Rule:  1
Golden Triangle Rule:  Rejected
Chelating Alert:  0
PAINS Alert:  0

ADMET Properties (ADMETlab2.0)

ADMET: Absorption

Caco-2 Permeability:  -6.841
MDCK Permeability:  1.0289424608345143e-05
Pgp-inhibitor:  0.21
Pgp-substrate:  0.0
Human Intestinal Absorption (HIA):  0.799
20% Bioavailability (F20%):  0.317
30% Bioavailability (F30%):  0.967

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.002
Plasma Protein Binding (PPB):  91.4821548461914%
Volume Distribution (VD):  0.06
Pgp-substrate:  13.420221328735352%

ADMET: Metabolism

CYP1A2-inhibitor:  0.684
CYP1A2-substrate:  0.081
CYP2C19-inhibitor:  0.063
CYP2C19-substrate:  0.026
CYP2C9-inhibitor:  0.291
CYP2C9-substrate:  0.433
CYP2D6-inhibitor:  0.0
CYP2D6-substrate:  0.217
CYP3A4-inhibitor:  0.038
CYP3A4-substrate:  0.072

ADMET: Excretion

Clearance (CL):  7.761
Half-life (T1/2):  0.698

ADMET: Toxicity

hERG Blockers:  0.042
Human Hepatotoxicity (H-HT):  0.005
Drug-inuced Liver Injury (DILI):  0.729
AMES Toxicity:  0.084
Rat Oral Acute Toxicity:  1.0
Maximum Recommended Daily Dose:  0.998
Skin Sensitization:  0.994
Carcinogencity:  0.074
Eye Corrosion:  0.003
Eye Irritation:  0.964
Respiratory Toxicity:  0.073

Download Data

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

  Natural Product: NPC110677

Natural Product ID:  NPC110677
Common Name*:   Dieckol
IUPAC Name:   4-[4-[6-(3,5-dihydroxyphenoxy)-4,7,9-trihydroxydibenzo-p-dioxin-2-yl]oxy-3,5-dihydroxyphenoxy]dibenzo-p-dioxin-1,3,6,8-tetrol
Synonyms:   Dieckol
Standard InCHIKey:  DRZQFGYIIYNNEC-UHFFFAOYSA-N
Standard InCHI:  InChI=1S/C36H22O18/c37-12-1-13(38)3-15(2-12)49-31-22(44)10-25(47)34-35(31)54-30-21(43)8-17(9-27(30)52-34)48-28-19(41)6-16(7-20(28)42)50-32-23(45)11-24(46)33-36(32)53-29-18(40)4-14(39)5-26(29)51-33/h1-11,37-47H
SMILES:  Oc1cc(O)cc(c1)Oc1c(O)cc(c2c1Oc1c(O)cc(cc1O2)Oc1c(O)cc(cc1O)Oc1c(O)cc(c2c1Oc1c(O)cc(cc1O2)O)O)O
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   CHEMBL508791
PubChem CID:   3008868
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000261] Phenylpropanoids and polyketides
      • [CHEMONTID:0000238] Tannins

*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 NPC110677 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 NPC110677 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