Natural Product: NPC241602

Natural Product IDNPC241602
Common Name
?
The InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
 KIZBWUUJNJEYCM-POLDBNSMSA-N
IUPAC Name n.a.
Synonyms
Synthetic Gene Cluster n.a.
ChEMBL Identifier n.a.
PubChem CID n.a.
Chemical Classification
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0002448] Benzenoids
      • [CHEMONTID:0000018] Anthracenes
        • [CHEMONTID:0000151] Anthraquinones

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 KIZBWUUJNJEYCM-POLDBNSMSA-N
Standard InCHI InChI=1S/C21H20O10/c22-6-8-4-10-14(11(24)5-8)18(27)15-9(16(10)25)2-1-3-12(15)30-21-20(29)19(28)17(26)13(7-23)31-21/h1-5,13,17,19-24,26,28-29H,6-7H2/t13-,17+,19-,20+,21-/m0/s1
SMILES c1cc2c(c(c1)O[C@@H]1[C@@H]([C@H]([C@@H]([C@H](CO)O1)O)O)O)C(=O)c1c(cc(cc1O)CO)C2=O

  Calculated Properties

Physi-Chem Properties

Molecular Weight:   432.11 Volume:   404.357
?
Van der Waals volume.
Dense:   1.069 LogP:   1.054
?
The logarithm of the n-octanol/water distribution coefficients.
logD7.4:   1.421
?
The logarithm of the n-octanol/water distribution coefficient at pH=7.4.
 LogS:   -3.212
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The logarithm of aqueous solubility value.
Rotatable Bonds:   4.0 Rigid Bonds:   24.0
TPSA:   173.98
?
Topological Polar Surface Area.
 H-Bond Acceptor:   10.0
H-Bond Donor:   6.0 Rings:   4.0
Heavy Atoms:   10.0

MedChem Properties

QED Drug-Likeness Score:   0.295 GASA:   0.0
?
GASA represents the probability of being difficult to synthesize, ranging from 0 to 1.
Synthetic Accessibility Score:   3.851 Fsp3:   0.333
MCE-18:   87.286
?
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:   Accepted
Golden Triangle Rule:   Rejected BMS Rule:   0
Chelating Alert:   0 PAINS Alert:   1
Colloidal aggregators:   0.459 Fluc inhibitor:   0.163
?
The fluc inhibitor value is the probability of being fLuc inhibitors, within the range of 0 to 1.
Blue fluorescence:   0.371
?
The blue fluorescence value is the probability of being blue fluorescence, within the range of 0 to 1
 Green fluorescence:   0.77
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The green fluorescence value is the probability of being green fluorescence, within the range of 0 to 1
Reactive compounds:   0.289 Promiscuous compounds:   0.363

ADMET Properties (ADMETlab3.0)

ADMET: Absorption

Caco-2 Permeability:   -6.505 MDCK Permeability:   -5.131
Pgp-inhibitor:   0.0 Pgp-substrate:   0.172
PAMPA:   1.0
?
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):   0.846
20% Bioavailability (F20%):   0.361 30% Bioavailability (F30%):   0.996
50% Bioavailability (F50%):   0.996

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):   0.0 MRP1:   0.258
Plasma Protein Binding (PPB):   87.233% Volume Distribution (VD):   0.389
Fu: 15.697%
?
The fraction unbound in plasms.
 OATP1B1 inhibitor:   0.913
OATP1B3 inhibitor:   0.997 BCRP inhibitor:   0.088
BSEP inhibitor:   0.033

ADMET: Metabolism

CYP1A2-inhibitor:   0.06 CYP1A2-substrate:   0.0
CYP2C19-inhibitor:   0.295 CYP2C19-substrate:   0.0
CYP2C9-inhibitor:   0.002 CYP2C9-substrate:   0.0
CYP2D6-inhibitor:   0.0 CYP2D6-substrate:   0.0
CYP3A4-inhibitor:   0.017 CYP3A4-substrate:   0.009
CYP2B6-substrate:   0.0 CYP2C8-inhibitor:   1.0
HLM stability:   0.045
?
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):  2.499 Half-life (T1/2):  3.007

ADMET: Toxicity

hERG Blockers:  0.017 hERG Blockers (10um):  0.26
Human Hepatotoxicity (H-HT):  0.686 Drug-induced Liver Injury (DILI):  0.884
AMES Toxicity:  0.907 Rat Oral Acute Toxicity:  0.043
Maximum Recommended Daily Dose:  0.021 Skin Sensitization:  0.884
Carcinogencity:  0.383 Eye Corrosion:  0.0
Eye Irritation:  0.32 Respiratory Toxicity:  0.037
Drug-induced Neurotoxicity:  0.029 Ototoxicity:  0.975
Hematotoxicity:  0.602 Drug-induced Nephrotoxicity:  0.877
Genotoxicity:  0.719 RPMI-8226 Immunitoxicity:  0.262
A549 Cytotoxicity:  0.439 Hek293 Cytotoxicity:  0.144
BCF:   0.75
?
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:   3.304
?
48 hour Tetrahymena pyriformis IGC50. The unit of IGC50 is -log10[(mg/L)/(1000*MW)].
LC50DM:   4.986
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48 hour Daphnia magna LC50. The unit of LC50DM is -log10[(mg/L)/(1000*MW)].
 LC50FM:   4.089
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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
NPO27239 Maclura tinctoria Species Moraceae Eukaryota n.a. n.a. n.a. PMID[11087602]
NPO27239 Maclura tinctoria Species Moraceae Eukaryota n.a. n.a. n.a. PMID[12932124]
NPO27239 Maclura tinctoria Species Moraceae Eukaryota n.a. stem n.a. PMID[12932124]
NPO27164 Aspergillus alliaceus Species Aspergillaceae Eukaryota n.a. n.a. n.a. PMID[29517220]
NPO27164 Aspergillus alliaceus Species Aspergillaceae Eukaryota n.a. n.a. n.a. PMID[3417561]
NPO27873 Ravenia spectabilis Species Rutaceae Eukaryota n.a. n.a. n.a. PMID[34570617]
NPO26972 Baccharis potosina Species Asteraceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO19050 Garcinia polyantha Species Clusiaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO27873 Ravenia spectabilis Species Rutaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO27239 Maclura tinctoria Species Moraceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO27164 Aspergillus alliaceus Species Aspergillaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO27140 Amanita phalloides Species Amanitaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO27140 Amanita phalloides Species Amanitaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO19050 Garcinia polyantha Species Clusiaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO3980 Frangula purshiana Species Rhamnaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO19050 Garcinia polyantha Species Clusiaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO4132 Cranfillia fluviatilis Species Blechnaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO27454 Turbo cornutus Species Turbinidae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO27790 Delia arenicola Species Anthomyiidae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO3980 Frangula purshiana Species Rhamnaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO24629 Achromobacter denitrificans Species Alcaligenaceae Bacteria n.a. n.a. n.a. Database[UNPD]
NPO27140 Amanita phalloides Species Amanitaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO10239 Magnolia figo Species Magnoliaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO27564 Stevia berlandieri Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO17822 Fridericia triplinervia Species Bignoniaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO27873 Ravenia spectabilis Species Rutaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO26972 Baccharis potosina Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO27164 Aspergillus alliaceus Species Aspergillaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO27239 Maclura tinctoria Species Moraceae 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

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 NPC241602 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
1.0 High Similarity NPC101116
0.8281 Intermediate Similarity NPC278329
0.7246 Intermediate Similarity NPC212099
0.6479 Remote Similarity NPC271385
0.6479 Remote Similarity NPC146837
0.6377 Remote Similarity NPC610808
0.6351 Remote Similarity NPC178281
0.6301 Remote Similarity NPC76128
0.6027 Remote Similarity NPC5029
0.5811 Remote Similarity NPC30432
0.5797 Remote Similarity NPC222455
0.5694 Remote Similarity NPC111536
0.5663 Remote Similarity NPC105591
0.5658 Remote Similarity NPC199357
0.56 Remote Similarity NPC605700
0.5538 Remote Similarity NPC226712
0.55 Remote Similarity NPC76112
0.55 Remote Similarity NPC170018
0.55 Remote Similarity NPC92403
0.55 Remote Similarity NPC66820
0.5455 Remote Similarity NPC606202
0.5294 Remote Similarity NPC46958
0.5294 Remote Similarity NPC40377
0.52 Remote Similarity NPC600107
0.5156 Remote Similarity NPC269242
0.5075 Remote Similarity NPC608788

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC241602 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
0.5538 Remote Similarity NPD1091 Pre-clinical
0.55 Remote Similarity NPD8312 Approved
0.55 Remote Similarity NPD8313 Approved

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