Natural Product: NPC63271

Natural Product IDNPC63271
Common Name
?
The InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
 AOPJIQXDBLPZDD-NKWVEPMBSA-N
IUPAC Name n.a.
Synonyms
Synthetic Gene Cluster n.a.
ChEMBL Identifier n.a.
PubChem CID 100956117
Chemical Classification
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000002] Organoheterocyclic compounds
      • [CHEMONTID:0000086] Pyrans
        • [CHEMONTID:0000481] Pyranones and derivatives
          • [CHEMONTID:0001211] Dihydropyranones

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 AOPJIQXDBLPZDD-NKWVEPMBSA-N
Standard InCHI InChI=1S/C8H12O3/c1-6(9)5-7-3-2-4-8(10)11-7/h2,4,6-7,9H,3,5H2,1H3/t6-,7+/m0/s1
SMILES C[C@@H](C[C@H]1CC=CC(=O)O1)O

  Calculated Properties

Physi-Chem Properties

Molecular Weight:   156.08 Volume:   159.466
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Van der Waals volume.
Dense:   0.979 LogP:   0.219
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The logarithm of the n-octanol/water distribution coefficients.
logD7.4:   0.226
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The logarithm of the n-octanol/water distribution coefficient at pH=7.4.
 LogS:   -0.499
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The logarithm of aqueous solubility value.
Rotatable Bonds:   2.0 Rigid Bonds:   7.0
TPSA:   46.53
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Topological Polar Surface Area.
 H-Bond Acceptor:   3.0
H-Bond Donor:   1.0 Rings:   1.0
Heavy Atoms:   3.0

MedChem Properties

QED Drug-Likeness Score:   0.596 GASA:   0.0
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GASA represents the probability of being difficult to synthesize, ranging from 0 to 1.
Synthetic Accessibility Score:   3.773 Fsp3:   0.625
MCE-18:   13.846
?
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:   Accepted BMS Rule:   0
Chelating Alert:   0 PAINS Alert:   0
Colloidal aggregators:   0.147 Fluc inhibitor:   0.044
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The fluc inhibitor value is the probability of being fLuc inhibitors, within the range of 0 to 1.
Blue fluorescence:   0.062
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The blue fluorescence value is the probability of being blue fluorescence, within the range of 0 to 1
 Green fluorescence:   0.001
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The green fluorescence value is the probability of being green fluorescence, within the range of 0 to 1
Reactive compounds:   0.984 Promiscuous compounds:   0.717

ADMET Properties (ADMETlab3.0)

ADMET: Absorption

Caco-2 Permeability:   -4.771 MDCK Permeability:   -4.547
Pgp-inhibitor:   0.022 Pgp-substrate:   0.474
PAMPA:   0.927
?
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):   0.055
20% Bioavailability (F20%):   0.143 30% Bioavailability (F30%):   0.222
50% Bioavailability (F50%):   0.463

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):   0.32 MRP1:   0.597
Plasma Protein Binding (PPB):   21.154% Volume Distribution (VD):   -0.309
Fu: 78.856%
?
The fraction unbound in plasms.
 OATP1B1 inhibitor:   0.392
OATP1B3 inhibitor:   0.545 BCRP inhibitor:   0.053
BSEP inhibitor:   0.433

ADMET: Metabolism

CYP1A2-inhibitor:   0.119 CYP1A2-substrate:   0.688
CYP2C19-inhibitor:   0.692 CYP2C19-substrate:   0.537
CYP2C9-inhibitor:   0.038 CYP2C9-substrate:   0.231
CYP2D6-inhibitor:   0.01 CYP2D6-substrate:   0.154
CYP3A4-inhibitor:   0.001 CYP3A4-substrate:   0.094
CYP2B6-substrate:   0.0 CYP2C8-inhibitor:   0.931
HLM stability:   0.872
?
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):  5.73 Half-life (T1/2):  2.239

ADMET: Toxicity

hERG Blockers:  0.04 hERG Blockers (10um):  0.33
Human Hepatotoxicity (H-HT):  0.328 Drug-induced Liver Injury (DILI):  0.457
AMES Toxicity:  0.857 Rat Oral Acute Toxicity:  0.542
Maximum Recommended Daily Dose:  0.744 Skin Sensitization:  1.0
Carcinogencity:  0.611 Eye Corrosion:  0.995
Eye Irritation:  0.997 Respiratory Toxicity:  0.482
Drug-induced Neurotoxicity:  0.635 Ototoxicity:  0.145
Hematotoxicity:  0.084 Drug-induced Nephrotoxicity:  0.831
Genotoxicity:  0.13 RPMI-8226 Immunitoxicity:  0.088
A549 Cytotoxicity:  0.272 Hek293 Cytotoxicity:  0.127
BCF:   0.335
?
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:   2.839
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48 hour Tetrahymena pyriformis IGC50. The unit of IGC50 is -log10[(mg/L)/(1000*MW)].
LC50DM:   4.151
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48 hour Daphnia magna LC50. The unit of LC50DM is -log10[(mg/L)/(1000*MW)].
 LC50FM:   3.453
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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
NPO3595 Euscaphis japonica Species Staphyleaceae Eukaryota n.a. twig n.a. DOI[10.1021/np1003593]
NPO3595 Euscaphis japonica Species Staphyleaceae Eukaryota Twigs Yangming mountain, Taiwan 2008-APR PMID[20873721]
NPO3595 Euscaphis japonica Species Staphyleaceae Eukaryota n.a. pericarp n.a. PMID[4421158]
NPO3595 Euscaphis japonica Species Staphyleaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO3595 Euscaphis japonica Species Staphyleaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO3595 Euscaphis japonica Species Staphyleaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO3595 Euscaphis japonica Species Staphyleaceae 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 NPC63271 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
0.6667 Remote Similarity NPC481551
0.6452 Remote Similarity NPC159650
0.6316 Remote Similarity NPC481552
0.6154 Remote Similarity NPC327383
0.6154 Remote Similarity NPC185186
0.6 Remote Similarity NPC481554
0.6 Remote Similarity NPC285840
0.6 Remote Similarity NPC327041
0.6 Remote Similarity NPC481553
0.5854 Remote Similarity NPC489162
0.5854 Remote Similarity NPC489161
0.5854 Remote Similarity NPC489164
0.5854 Remote Similarity NPC489163
0.5455 Remote Similarity NPC481555
0.5435 Remote Similarity NPC329890
0.5208 Remote Similarity NPC329914
0.5172 Remote Similarity NPC275316

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC63271 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