Natural Product: NPC284586

Natural Product IDNPC284586
Common Name
?
The InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
WAGHSYJXJAHWPX-LLUYJYKPSA-N
IUPAC Name n.a.
Synonyms
Synthetic Gene Cluster n.a.
ChEMBL Identifier n.a.
PubChem CID 70698213
Chemical Classification
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000012] Lipids and lipid-like molecules
      • [CHEMONTID:0000259] Prenol lipids
        • [CHEMONTID:0001553] Triterpenoids

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 WAGHSYJXJAHWPX-LLUYJYKPSA-N
Standard InCHI InChI=1S/C30H46O2/c1-19(2)16-21-17-20(18-32-21)22-10-14-30(7)24-8-9-25-27(3,4)26(31)12-13-28(25,5)23(24)11-15-29(22,30)6/h8,16,20-23,25H,9-15,17-18H2,1-7H3/t20-,21+,22+,23+,25+,28-,29+,30-/m1/s1
SMILES CC(=C[C@H]1C[C@H](CO1)[C@@H]1CC[C@]2(C)C3=CC[C@H]4C(C)(C)C(=O)CC[C@]4(C)[C@H]3CC[C@@]12C)C

  Calculated Properties

Physi-Chem Properties

Molecular Weight:   438.35 Volume:   494.325
?
Van der Waals volume.
Dense:   0.887 LogP:   6.599
?
The logarithm of the n-octanol/water distribution coefficients.
logD7.4:   4.496
?
The logarithm of the n-octanol/water distribution coefficient at pH=7.4.
LogS:   -7.213
?
The logarithm of aqueous solubility value.
Rotatable Bonds:   2.0 Rigid Bonds:   27.0
TPSA:   26.3
?
Topological Polar Surface Area.
H-Bond Acceptor:   2.0
H-Bond Donor:   0.0 Rings:   5.0
Heavy Atoms:   2.0

MedChem Properties

QED Drug-Likeness Score:   0.416 GASA:   1.0
?
GASA represents the probability of being difficult to synthesize, ranging from 0 to 1.
Synthetic Accessibility Score:   4.944 Fsp3:   0.833
MCE-18:   92.909
?
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:   Rejected BMS Rule:   0
Chelating Alert:   0 PAINS Alert:   0
Colloidal aggregators:   0.874 Fluc inhibitor:   0.0
?
The fluc inhibitor value is the probability of being fLuc inhibitors, within the range of 0 to 1.
Blue fluorescence:   0.004
?
The blue fluorescence value is the probability of being blue fluorescence, within the range of 0 to 1
Green fluorescence:   0.0
?
The green fluorescence value is the probability of being green fluorescence, within the range of 0 to 1
Reactive compounds:   0.544 Promiscuous compounds:   0.288

ADMET Properties (ADMETlab3.0)

ADMET: Absorption

Caco-2 Permeability:   -4.523 MDCK Permeability:   -4.672
Pgp-inhibitor:   0.984 Pgp-substrate:   0.009
PAMPA:   0.054
?
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%):   0.033 30% Bioavailability (F30%):   0.058
50% Bioavailability (F50%):   0.899

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):   0.079 MRP1:   0.891
Plasma Protein Binding (PPB):   94.159% Volume Distribution (VD):   0.594
Fu: 6.182%
?
The fraction unbound in plasms.
OATP1B1 inhibitor:   1.0
OATP1B3 inhibitor:   1.0 BCRP inhibitor:   0.878
BSEP inhibitor:   1.0

ADMET: Metabolism

CYP1A2-inhibitor:   0.041 CYP1A2-substrate:   0.625
CYP2C19-inhibitor:   1.0 CYP2C19-substrate:   0.02
CYP2C9-inhibitor:   0.0 CYP2C9-substrate:   0.001
CYP2D6-inhibitor:   0.0 CYP2D6-substrate:   0.999
CYP3A4-inhibitor:   1.0 CYP3A4-substrate:   1.0
CYP2B6-substrate:   0.0 CYP2C8-inhibitor:   1.0
HLM stability:   0.996
?
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):  11.084 Half-life (T1/2):  0.25

ADMET: Toxicity

hERG Blockers:  0.101 hERG Blockers (10um):  0.35
Human Hepatotoxicity (H-HT):  0.796 Drug-induced Liver Injury (DILI):  0.627
AMES Toxicity:  0.488 Rat Oral Acute Toxicity:  0.644
Maximum Recommended Daily Dose:  0.896 Skin Sensitization:  0.92
Carcinogencity:  0.875 Eye Corrosion:  0.005
Eye Irritation:  0.333 Respiratory Toxicity:  0.692
Drug-induced Neurotoxicity:  0.719 Ototoxicity:  0.464
Hematotoxicity:  0.675 Drug-induced Nephrotoxicity:  0.725
Genotoxicity:  0.923 RPMI-8226 Immunitoxicity:  0.12
A549 Cytotoxicity:  0.318 Hek293 Cytotoxicity:  0.561
BCF:   2.814
?
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:   4.595
?
48 hour Tetrahymena pyriformis IGC50. The unit of IGC50 is -log10[(mg/L)/(1000*MW)].
LC50DM:   5.335
?
48 hour Daphnia magna LC50. The unit of LC50DM is -log10[(mg/L)/(1000*MW)].
LC50FM:   5.35
?
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
NPO19594 Cornus walteri Species Cornaceae Eukaryota n.a. stem n.a. PMID[21182258]
NPO19594 Cornus walteri Species Cornaceae Eukaryota n.a. n.a. n.a. PMID[21182258]
NPO1458 Burkholderia gladioli Species Burkholderiaceae Bacteria n.a. n.a. n.a. Database[COCONUT]
NPO10779 Lychnophora ericoides Species Asteraceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO11004 Cornus capitata Species Cornaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO7268 Ipomoea violacea Species Convolvulaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO26236 Artocarpus incisus Species Moraceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO19594 Cornus walteri Species Cornaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO7268 Ipomoea violacea Species Convolvulaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO7268 Ipomoea violacea Species Convolvulaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO11004 Cornus capitata Species Cornaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO7268 Ipomoea violacea Species Convolvulaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO11004 Cornus capitata Species Cornaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO10779 Lychnophora ericoides Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO6227 Umbilicaria papulosa Species Umbilicariaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO7268 Ipomoea violacea Species Convolvulaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO19594 Cornus walteri Species Cornaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO16022 Streptomyces aureomonopodiales Species Streptomycetaceae Bacteria n.a. n.a. n.a. Database[UNPD]
NPO10411 Bauhinia uruguayensis Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO26236 Artocarpus incisus Species Moraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO1458 Burkholderia gladioli Species Burkholderiaceae Bacteria 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 NPC284586 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 NPC470050
1.0 High Similarity NPC470051
0.7344 Intermediate Similarity NPC470047
0.7344 Intermediate Similarity NPC470046
0.7143 Intermediate Similarity NPC470223
0.6957 Remote Similarity NPC273669
0.6957 Remote Similarity NPC484802
0.6957 Remote Similarity NPC118647
0.6912 Remote Similarity NPC605437
0.6061 Remote Similarity NPC470078
0.6056 Remote Similarity NPC67831
0.6056 Remote Similarity NPC174051
0.5942 Remote Similarity NPC470052
0.5915 Remote Similarity NPC486521
0.5915 Remote Similarity NPC262870
0.5753 Remote Similarity NPC479667
0.5714 Remote Similarity NPC90652
0.5714 Remote Similarity NPC155255
0.5714 Remote Similarity NPC470417
0.5714 Remote Similarity NPC260992
0.5641 Remote Similarity NPC189282
0.5641 Remote Similarity NPC237402
0.5584 Remote Similarity NPC63023
0.5584 Remote Similarity NPC121566
0.5584 Remote Similarity NPC100955
0.5584 Remote Similarity NPC95243
0.5479 Remote Similarity NPC471224
0.5467 Remote Similarity NPC293081
0.5443 Remote Similarity NPC484792
0.5405 Remote Similarity NPC472239
0.5333 Remote Similarity NPC6190
0.5286 Remote Similarity NPC247220
0.527 Remote Similarity NPC28227
0.5139 Remote Similarity NPC470224
0.5135 Remote Similarity NPC147066
0.5132 Remote Similarity NPC478557
0.5128 Remote Similarity NPC73506
0.5068 Remote Similarity NPC470049

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC284586 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