Structure

Physi-Chem Properties

Molecular Weight:  464.13
Volume:  433.08
LogP:  1.208
LogD:  0.838
LogS:  -4.362
# Rotatable Bonds:  5
TPSA:  175.37
# H-Bond Aceptor:  11
# H-Bond Donor:  6
# Rings:  4
# Heavy Atoms:  11

MedChem Properties

QED Drug-Likeness Score:  0.351
Synthetic Accessibility Score:  4.18
Fsp3:  0.409
Lipinski Rule-of-5:  Rejected
Pfizer Rule:  Accepted
GSK Rule:  Rejected
BMS Rule:  1
Golden Triangle Rule:  Accepted
Chelating Alert:  0
PAINS Alert:  0

ADMET Properties (ADMETlab2.0)

ADMET: Absorption

Caco-2 Permeability:  -6.315
MDCK Permeability:  2.560204484325368e-05
Pgp-inhibitor:  0.015
Pgp-substrate:  0.932
Human Intestinal Absorption (HIA):  0.509
20% Bioavailability (F20%):  0.002
30% Bioavailability (F30%):  0.991

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.172
Plasma Protein Binding (PPB):  81.33708190917969%
Volume Distribution (VD):  0.511
Pgp-substrate:  18.016902923583984%

ADMET: Metabolism

CYP1A2-inhibitor:  0.053
CYP1A2-substrate:  0.1
CYP2C19-inhibitor:  0.047
CYP2C19-substrate:  0.369
CYP2C9-inhibitor:  0.1
CYP2C9-substrate:  0.87
CYP2D6-inhibitor:  0.412
CYP2D6-substrate:  0.288
CYP3A4-inhibitor:  0.068
CYP3A4-substrate:  0.097

ADMET: Excretion

Clearance (CL):  9.562
Half-life (T1/2):  0.707

ADMET: Toxicity

hERG Blockers:  0.087
Human Hepatotoxicity (H-HT):  0.374
Drug-inuced Liver Injury (DILI):  0.952
AMES Toxicity:  0.538
Rat Oral Acute Toxicity:  0.576
Maximum Recommended Daily Dose:  0.029
Skin Sensitization:  0.778
Carcinogencity:  0.599
Eye Corrosion:  0.003
Eye Irritation:  0.341
Respiratory Toxicity:  0.846

Download Data

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

  Natural Product: NPC133358

Natural Product ID:  NPC133358
Common Name*:   KOBUGDLTCAJTND-CPCIYWDDSA-N
IUPAC Name:   n.a.
Synonyms:  
Standard InCHIKey:  KOBUGDLTCAJTND-CPCIYWDDSA-N
Standard InCHI:  InChI=1S/C22H24O11/c1-30-9-5-11(25)17-12(26)7-15(31-14(17)6-9)18-10(24)3-2-4-13(18)32-22-21(29)20(28)19(27)16(8-23)33-22/h2-6,15-16,19-25,27-29H,7-8H2,1H3/t15-,16-,19+,20-,21+,22+/m0/s1
SMILES:  COc1cc(c2C(=O)C[C@@H](c3c(cccc3O[C@H]3[C@@H]([C@H]([C@@H]([C@H](CO)O3)O)O)O)O)Oc2c1)O
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   n.a.
PubChem CID:   n.a.
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000261] Phenylpropanoids and polyketides
      • [CHEMONTID:0000334] Flavonoids
        • [CHEMONTID:0002585] O-methylated flavonoids
          • [CHEMONTID:0002592] 7-O-methylated flavonoids

*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
NPO11748 Eunicea knighti Species Plexauridae Eukaryota n.a. Santa Marta Bay, Colombian Caribbean 2007-MAY PMID[19778088]
NPO17543 Stizophyllum riparium Species Bignoniaceae Eukaryota n.a. n.a. n.a. PMID[3598599]
NPO14992 Prunus persica Species Rosaceae Eukaryota n.a. kernel n.a. PMID[7092570]
NPO14992 Prunus persica Species Rosaceae Eukaryota n.a. n.a. Database[FooDB]
NPO14992 Prunus persica Species Rosaceae Eukaryota Fruit n.a. n.a. Database[FooDB]
NPO14992 Prunus persica Species Rosaceae Eukaryota Leaf n.a. n.a. Database[FooDB]
NPO14992 Prunus persica Species Rosaceae Eukaryota Plant n.a. n.a. Database[FooDB]
NPO14992 Prunus persica Species Rosaceae Eukaryota Seed n.a. n.a. Database[FooDB]
NPO14992 Prunus persica Species Rosaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO14992 Prunus persica Species Rosaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO14992 Prunus persica Species Rosaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO14992 Prunus persica Species Rosaceae Eukaryota n.a. n.a. n.a. Database[TM-MC]
NPO17543 Stizophyllum riparium Species Bignoniaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO14691.1 Crambe hispanica subsp. abyssinica Subspecies Brassicaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO14992 Prunus persica Species Rosaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO26084 Vincetoxicum amplexicaule Species Apocynaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO17023 Cusparia macrocarpa n.a. n.a. n.a. n.a. n.a. n.a. Database[UNPD]
NPO16610 Chromodoris hamiltoni Species Chromodorididae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO16730 Helichrysum lindleyi Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO3962 Parinari campestris Species Chrysobalanaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO11748 Eunicea knighti Species Plexauridae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO15658 Utricularia vulgaris Species Lentibulariaceae 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 NPC133358 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 NPC133358 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