Natural Product: NPC66384

Natural Product IDNPC66384
Common Name
?
The InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
 4,4',6-Trihydroxy-2-Methoxydihydrochalcone
IUPAC Name 3-(2,4-dihydroxy-6-methoxyphenyl)-1-(4-hydroxyphenyl)propan-1-one
Synonyms
Synthetic Gene Cluster n.a.
ChEMBL Identifier CHEMBL400281
PubChem CID 13939318
Chemical Classification
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000261] Phenylpropanoids and polyketides
      • [CHEMONTID:0003467] Linear 1,3-diarylpropanoids
        • [CHEMONTID:0001630] Chalcones and dihydrochalcones
          • [CHEMONTID:0003475] Retro-dihydrochalcones

The Chemical Classification was calculated by Classyfire, a software for chemical taxonomy calculation. Reference: DOI:10.1186/s13321-016-0174-y.

  Chemical Representations

Standard InCHIKey AQMBVNGTZRFEPF-UHFFFAOYSA-N
Standard InCHI InChI=1S/C16H16O5/c1-21-16-9-12(18)8-15(20)13(16)6-7-14(19)10-2-4-11(17)5-3-10/h2-5,8-9,17-18,20H,6-7H2,1H3
SMILES COc1cc(cc(c1CCC(=O)c1ccc(cc1)O)O)O

  Calculated Properties

Physi-Chem Properties

Molecular Weight:   288.1 Volume:   293.675
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Van der Waals volume.
Dense:   0.981 LogP:   2.086
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The logarithm of the n-octanol/water distribution coefficients.
logD7.4:   2.294
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The logarithm of the n-octanol/water distribution coefficient at pH=7.4.
 LogS:   -2.846
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The logarithm of aqueous solubility value.
Rotatable Bonds:   5.0 Rigid Bonds:   13.0
TPSA:   86.99
?
Topological Polar Surface Area.
 H-Bond Acceptor:   5.0
H-Bond Donor:   3.0 Rings:   2.0
Heavy Atoms:   5.0

MedChem Properties

QED Drug-Likeness Score:   0.736 GASA:   0.0
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GASA represents the probability of being difficult to synthesize, ranging from 0 to 1.
Synthetic Accessibility Score:   2.148 Fsp3:   0.188
MCE-18:   13.0
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MCE-18 stands for medicinal chemistry evolution.MCE-18≥45 is considered a suitable value.
 Lipinski Rule-of-5:   Rejected
Pfizer Rule:   Rejected GSK Rule:   Rejected
Golden Triangle Rule:   Rejected BMS Rule:   0
Chelating Alert:   0 PAINS Alert:   0
Colloidal aggregators:   0.464 Fluc inhibitor:   0.326
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The fluc inhibitor value is the probability of being fLuc inhibitors, within the range of 0 to 1.
Blue fluorescence:   0.08
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The blue fluorescence value is the probability of being blue fluorescence, within the range of 0 to 1
 Green fluorescence:   0.347
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The green fluorescence value is the probability of being green fluorescence, within the range of 0 to 1
Reactive compounds:   0.601 Promiscuous compounds:   0.121

ADMET Properties (ADMETlab3.0)

ADMET: Absorption

Caco-2 Permeability:   -4.818 MDCK Permeability:   -4.805
Pgp-inhibitor:   0.081 Pgp-substrate:   0.029
PAMPA:   0.294
?
The experimental data for Peff was logarithmically transformed (logPeff). Molecules with log Peff values below 2.0 were classified as low-permeability (Category 0), while those with log Peff values exceeding 2.5 were classified as high-permeability (Category 1).
 Human Intestinal Absorption (HIA):   0.0
20% Bioavailability (F20%):   0.019 30% Bioavailability (F30%):   0.106
50% Bioavailability (F50%):   0.892

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):   0.003 MRP1:   0.626
Plasma Protein Binding (PPB):   89.497% Volume Distribution (VD):   -0.015
Fu: 11.948%
?
The fraction unbound in plasms.
 OATP1B1 inhibitor:   0.958
OATP1B3 inhibitor:   0.992 BCRP inhibitor:   0.475
BSEP inhibitor:   0.813

ADMET: Metabolism

CYP1A2-inhibitor:   0.398 CYP1A2-substrate:   0.892
CYP2C19-inhibitor:   0.194 CYP2C19-substrate:   0.8
CYP2C9-inhibitor:   0.942 CYP2C9-substrate:   0.049
CYP2D6-inhibitor:   0.991 CYP2D6-substrate:   0.979
CYP3A4-inhibitor:   0.004 CYP3A4-substrate:   0.013
CYP2B6-substrate:   0.025 CYP2C8-inhibitor:   1.0
HLM stability:   0.983
?
Human liver microsomal (HLM) stability. Category 0: stable+ (HLM > 30 min); Category 1: unstable- (HLM ≤ 30 min). The output value is the probability of human liver microsomal instability, where a value closer to 1 indicates a higher likelihood of instability.

ADMET: Excretion

Clearance (CL):  8.005 Half-life (T1/2):  1.191

ADMET: Toxicity

hERG Blockers:  0.153 hERG Blockers (10um):  0.608
Human Hepatotoxicity (H-HT):  0.346 Drug-induced Liver Injury (DILI):  0.046
AMES Toxicity:  0.303 Rat Oral Acute Toxicity:  0.295
Maximum Recommended Daily Dose:  0.576 Skin Sensitization:  0.495
Carcinogencity:  0.4 Eye Corrosion:  0.133
Eye Irritation:  0.986 Respiratory Toxicity:  0.82
Drug-induced Neurotoxicity:  0.407 Ototoxicity:  0.112
Hematotoxicity:  0.097 Drug-induced Nephrotoxicity:  0.109
Genotoxicity:  0.843 RPMI-8226 Immunitoxicity:  0.037
A549 Cytotoxicity:  0.211 Hek293 Cytotoxicity:  0.761
BCF:   0.979
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Bioconcentration factors are used for considering secondary poisoning potential and assessing risks to human health via the food chain. The unit is -log10[(mg/L)/(1000*MW)].
 IGC50:   3.595
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48 hour Tetrahymena pyriformis IGC50. The unit of IGC50 is -log10[(mg/L)/(1000*MW)].
LC50DM:   4.549
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48 hour Daphnia magna LC50. The unit of LC50DM is -log10[(mg/L)/(1000*MW)].
 LC50FM:   4.018
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96 hour fathead minnow LC50. The unit of LC50FM is -log10[(mg/L)/(1000*MW)].

  Species Source

Organism ID Organism Name Taxonomy Level Family SuperKingdom Isolation Part Collection Location Collection Time Reference
NPO12714 Dracaena cochinchinensis Species Asparagaceae Eukaryota n.a. n.a. n.a. PMID[12016928]
NPO12714 Dracaena cochinchinensis Species Asparagaceae Eukaryota stems Ningming County, Guangxi autonomous region, China 2006-Jan PMID[17883259]
NPO12714 Dracaena cochinchinensis Species Asparagaceae Eukaryota n.a. n.a. n.a. PMID[21661731]
NPO12714 Dracaena cochinchinensis Species Asparagaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO12714 Dracaena cochinchinensis Species Asparagaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO12714 Dracaena cochinchinensis Species Asparagaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO12714 Dracaena cochinchinensis Species Asparagaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO12714 Dracaena cochinchinensis Species Asparagaceae 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 Organism Name 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

Molecular-level activity

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference

In vitro activity

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference
NPT451 Organism Helicobacter pylori Helicobacter pylori MIC = 111100.0 nM PMID[26636180]

In vivo activity

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference





 Experimental ADME

Experiment Model Experiment Tissue ADME Type ADME Relation ADME Value ADME Unit Reference





 Experimental Toxicity

Quantitative toxicity

Experiment Model Experiment Organism Toxicity Type Toxicity Relation Toxicity Value Toxicity Unit Reference

Common Abbreviations:
LC: Lethal Concentration; LD: Lethal Dose; LT:Lethal Time; NOAEL: No-observed-adverse-effect Level; BMDL: Benchmark Dose Lower Confidence Limit; BMD: Benchmark Dose; BMC:Benchmark Concentration; LOAEL: Lowest Observed Adverse Effect Level; RfD:Reference Dose; RfC:Reference Concentration; MRL: Minimal Risk Level; MEG: Maximum Exposure Guideline; PAC: Protective Action Criteria

Categorical toxicity labels

Hepatotoxicity Carcinogenicity Mutagenicity Cardiotoxicity Respiratory Toxicity Eye Irritation Endocrine Disruption
Hepatotoxicity Carcinogenicity Mutagenicity Cardiotoxicity Respiratory Toxicity Eye Irritation Endocrine Disruption

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 toxicity records from domain-specific databases. These databases include:
☉ ToxValDB: a curated database that compiles quantitative toxicity values for chemicals from diverse public sources to support toxicological research and risk assessment.
☉ TOXRIC: a comprehensive, free-to-access, online database providing toxicological/feature data. The toxicity labels are retrieved from this database. [PMID: 36400569]


  Chemically structural similarity

Similar Active Natural Products in NPASS

Top-200 similar NPs were calculated against the active-NP-set (includes approximately 50,000 NPs with experimentally-derived bioactivity available in NPASS)

Similarity is measured using the Tanimoto coefficient (Tc) , which compares the binary fingerprints of two molecules. Tc is calculated as the intersection divided by the union of '1' bits in the fingerprints, ranging from 0 to 1, with 1 indicating highest similarity.

●  The left chart: Distribution of similarity level between NPC66384 and all remaining natural products in the NPASS database.
●  The right table: Most similar natural products (Tc>=0.5 or Top200).

Similarity Score Similarity Level Natural Product ID
0.6957 Remote Similarity NPC128348
0.6809 Remote Similarity NPC309717
0.6327 Remote Similarity NPC189106
0.6087 Remote Similarity NPC159525
0.5882 Remote Similarity NPC112192
0.56 Remote Similarity NPC164236
0.5536 Remote Similarity NPC27139
0.5472 Remote Similarity NPC20560
0.5385 Remote Similarity NPC482472
0.5294 Remote Similarity NPC82225
0.5238 Remote Similarity NPC471473
0.5185 Remote Similarity NPC18877
0.5102 Remote Similarity NPC242895
0.5094 Remote Similarity NPC286336

Similar Clinical/Approved Drugs

Similarity level is defined by Tanimoto coefficient (Tc) between two molecules.

●  The left chart: Distribution of similarity level between NPC66384 and all drugs/candidates.
●  The right table: Most similar clinical/approved drugs (Tc>=0.5 or Top200).

Similarity Score Similarity Level Drug ID Developmental Stage
NPD

Bioactivity similarity

  Bioactivity similarity

Similar Natural Products in NPASS

Similarity level is defined by 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