Natural Product: NPC22469

Natural Product IDNPC22469
Common Name
?
The InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
KMZZTLKNPDAWBH-AJKJBRKTSA-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:0000012] Lipids and lipid-like molecules
      • [CHEMONTID:0000258] Steroids and steroid derivatives
        • [CHEMONTID:0003569] Pregnane steroids
          • [CHEMONTID:0001468] Gluco/mineralocorticoids, progestogins and derivatives

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 KMZZTLKNPDAWBH-AJKJBRKTSA-N
Standard InCHI InChI=1S/C28H48O/c1-18(2)19(3)7-8-20(4)24-11-12-25-23-10-9-21-17-22(29)13-15-27(21,5)26(23)14-16-28(24,25)6/h18-19,21-26,29H,4,7-17H2,1-3,5-6H3/t19-,21+,22+,23+,24-,25+,26+,27+,28-/m1/s1
SMILES CC(C)[C@H](C)CCC(=C)[C@H]1CC[C@H]2[C@@H]3CC[C@H]4C[C@H](CC[C@]4(C)[C@H]3CC[C@]12C)O

  Calculated Properties

Physi-Chem Properties

Molecular Weight:   400.37 Volume:   464.772
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Van der Waals volume.
Dense:   0.861 LogP:   7.355
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The logarithm of the n-octanol/water distribution coefficients.
logD7.4:   5.117
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The logarithm of the n-octanol/water distribution coefficient at pH=7.4.
LogS:   -7.224
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The logarithm of aqueous solubility value.
Rotatable Bonds:   5.0 Rigid Bonds:   21.0
TPSA:   20.23
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Topological Polar Surface Area.
H-Bond Acceptor:   1.0
H-Bond Donor:   1.0 Rings:   4.0
Heavy Atoms:   1.0

MedChem Properties

QED Drug-Likeness Score:   0.47 GASA:   1.0
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GASA represents the probability of being difficult to synthesize, ranging from 0 to 1.
Synthetic Accessibility Score:   4.478 Fsp3:   0.929
MCE-18:   71.0
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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:   Accepted GSK Rule:   Accepted
Golden Triangle Rule:   Accepted BMS Rule:   0
Chelating Alert:   0 PAINS Alert:   0
Colloidal aggregators:   0.749 Fluc inhibitor:   0.006
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The fluc inhibitor value is the probability of being fLuc inhibitors, within the range of 0 to 1.
Blue fluorescence:   0.013
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The blue fluorescence value is the probability of being blue fluorescence, within the range of 0 to 1
Green fluorescence:   0.0
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The green fluorescence value is the probability of being green fluorescence, within the range of 0 to 1
Reactive compounds:   0.757 Promiscuous compounds:   0.195

ADMET Properties (ADMETlab3.0)

ADMET: Absorption

Caco-2 Permeability:   -5.15 MDCK Permeability:   -4.913
Pgp-inhibitor:   0.031 Pgp-substrate:   0.013
PAMPA:   0.035
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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%):   0.004 30% Bioavailability (F30%):   0.018
50% Bioavailability (F50%):   0.937

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):   0.953 MRP1:   0.03
Plasma Protein Binding (PPB):   93.266% Volume Distribution (VD):   -0.015
Fu: 6.624%
?
The fraction unbound in plasms.
OATP1B1 inhibitor:   0.999
OATP1B3 inhibitor:   0.998 BCRP inhibitor:   0.913
BSEP inhibitor:   0.237

ADMET: Metabolism

CYP1A2-inhibitor:   0.0 CYP1A2-substrate:   0.215
CYP2C19-inhibitor:   0.835 CYP2C19-substrate:   0.645
CYP2C9-inhibitor:   0.0 CYP2C9-substrate:   0.99
CYP2D6-inhibitor:   0.317 CYP2D6-substrate:   0.612
CYP3A4-inhibitor:   1.0 CYP3A4-substrate:   1.0
CYP2B6-substrate:   0.0 CYP2C8-inhibitor:   0.996
HLM stability:   0.994
?
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):  15.215 Half-life (T1/2):  1.126

ADMET: Toxicity

hERG Blockers:  0.271 hERG Blockers (10um):  0.362
Human Hepatotoxicity (H-HT):  0.639 Drug-induced Liver Injury (DILI):  0.134
AMES Toxicity:  0.066 Rat Oral Acute Toxicity:  0.031
Maximum Recommended Daily Dose:  0.847 Skin Sensitization:  0.994
Carcinogencity:  0.959 Eye Corrosion:  0.911
Eye Irritation:  0.999 Respiratory Toxicity:  0.965
Drug-induced Neurotoxicity:  0.016 Ototoxicity:  0.397
Hematotoxicity:  0.557 Drug-induced Nephrotoxicity:  0.699
Genotoxicity:  0.001 RPMI-8226 Immunitoxicity:  0.029
A549 Cytotoxicity:  0.16 Hek293 Cytotoxicity:  0.687
BCF:   3.176
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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:   5.048
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48 hour Tetrahymena pyriformis IGC50. The unit of IGC50 is -log10[(mg/L)/(1000*MW)].
LC50DM:   5.55
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48 hour Daphnia magna LC50. The unit of LC50DM is -log10[(mg/L)/(1000*MW)].
LC50FM:   5.839
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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
NPO6414 Eupatorium cannabinum Species Asteraceae Eukaryota n.a. aerial part n.a. PMID[21391659]
NPO6414 Eupatorium cannabinum Species Asteraceae Eukaryota Aerial Parts n.a. n.a. PMID[30653318]
NPO6414 Eupatorium cannabinum Species Asteraceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO6414 Eupatorium cannabinum Species Asteraceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO6414 Eupatorium cannabinum Species Asteraceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO6414 Eupatorium cannabinum Species Asteraceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO6414 Eupatorium cannabinum Species Asteraceae 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 NPC22469 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
0.6471 Remote Similarity NPC148174
0.6275 Remote Similarity NPC71460
0.6275 Remote Similarity NPC218585
0.6122 Remote Similarity NPC114891
0.5893 Remote Similarity NPC167702
0.5893 Remote Similarity NPC280026
0.5769 Remote Similarity NPC320549
0.5769 Remote Similarity NPC156277
0.5769 Remote Similarity NPC58057
0.5769 Remote Similarity NPC151018
0.569 Remote Similarity NPC477819
0.5455 Remote Similarity NPC254340
0.5385 Remote Similarity NPC281540
0.5385 Remote Similarity NPC159654
0.5385 Remote Similarity NPC167995
0.5385 Remote Similarity NPC118937
0.5345 Remote Similarity NPC192456
0.5283 Remote Similarity NPC111234
0.5079 Remote Similarity NPC323180

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC22469 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
0.5893 Remote Similarity NPD6113 Clinical (unspecified phase)
0.5769 Remote Similarity NPD4808 Phase 2
0.5769 Remote Similarity NPD4809 Phase 4

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