Natural Product: NPC106920

Natural Product IDNPC106920
Common Name
?
The InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
 (3R,4R)-3-(4-Hydroxy-3-Methoxybenzyl)-4-(3,4,5-Trimethoxybenzyl)Dihydrofuran-2(3H)-One
IUPAC Name (3R,4R)-3-[(4-hydroxy-3-methoxyphenyl)methyl]-4-[(3,4,5-trimethoxyphenyl)methyl]oxolan-2-one
Synonyms
Synthetic Gene Cluster n.a.
ChEMBL Identifier CHEMBL3578258
PubChem CID 10069677
Chemical Classification
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0001392] Lignans, neolignans and related compounds
      • [CHEMONTID:0003686] Furanoid lignans
        • [CHEMONTID:0001604] Tetrahydrofuran lignans
          • [CHEMONTID:0003424] 9,9'-epoxylignans
            • [CHEMONTID:0001613] Dibenzylbutyrolactone lignans

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 DRHBSAJKORZXET-JKSUJKDBSA-N
Standard InCHI InChI=1S/C22H26O7/c1-25-18-9-13(5-6-17(18)23)8-16-15(12-29-22(16)24)7-14-10-19(26-2)21(28-4)20(11-14)27-3/h5-6,9-11,15-16,23H,7-8,12H2,1-4H3/t15-,16+/m0/s1
SMILES COc1cc(ccc1O)C[C@@H]1[C@@H](Cc2cc(c(c(c2)OC)OC)OC)COC1=O

  Calculated Properties

Physi-Chem Properties

Molecular Weight:   402.17 Volume:   406.475
?
Van der Waals volume.
Dense:   0.989 LogP:   1.962
?
The logarithm of the n-octanol/water distribution coefficients.
logD7.4:   2.184
?
The logarithm of the n-octanol/water distribution coefficient at pH=7.4.
 LogS:   -3.204
?
The logarithm of aqueous solubility value.
Rotatable Bonds:   8.0 Rigid Bonds:   18.0
TPSA:   83.45
?
Topological Polar Surface Area.
 H-Bond Acceptor:   7.0
H-Bond Donor:   1.0 Rings:   3.0
Heavy Atoms:   7.0

MedChem Properties

QED Drug-Likeness Score:   0.68 GASA:   0.0
?
GASA represents the probability of being difficult to synthesize, ranging from 0 to 1.
Synthetic Accessibility Score:   3.172 Fsp3:   0.409
MCE-18:   60.677
?
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:   1 PAINS Alert:   0
Colloidal aggregators:   0.117 Fluc inhibitor:   0.196
?
The fluc inhibitor value is the probability of being fLuc inhibitors, within the range of 0 to 1.
Blue fluorescence:   0.026
?
The blue fluorescence value is the probability of being blue fluorescence, within the range of 0 to 1
 Green fluorescence:   0.373
?
The green fluorescence value is the probability of being green fluorescence, within the range of 0 to 1
Reactive compounds:   0.263 Promiscuous compounds:   0.304

ADMET Properties (ADMETlab3.0)

ADMET: Absorption

Caco-2 Permeability:   -5.029 MDCK Permeability:   -4.724
Pgp-inhibitor:   0.351 Pgp-substrate:   0.138
PAMPA:   0.027
?
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):   0.007
20% Bioavailability (F20%):   0.861 30% Bioavailability (F30%):   0.631
50% Bioavailability (F50%):   0.935

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):   0.007 MRP1:   0.975
Plasma Protein Binding (PPB):   94.218% Volume Distribution (VD):   -0.358
Fu: 6.297%
?
The fraction unbound in plasms.
 OATP1B1 inhibitor:   0.997
OATP1B3 inhibitor:   0.974 BCRP inhibitor:   0.078
BSEP inhibitor:   0.992

ADMET: Metabolism

CYP1A2-inhibitor:   0.0 CYP1A2-substrate:   0.443
CYP2C19-inhibitor:   1.0 CYP2C19-substrate:   0.99
CYP2C9-inhibitor:   0.0 CYP2C9-substrate:   0.0
CYP2D6-inhibitor:   0.0 CYP2D6-substrate:   0.99
CYP3A4-inhibitor:   1.0 CYP3A4-substrate:   1.0
CYP2B6-substrate:   0.0 CYP2C8-inhibitor:   1.0
HLM stability:   0.403
?
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):  4.427 Half-life (T1/2):  1.836

ADMET: Toxicity

hERG Blockers:  0.18 hERG Blockers (10um):  0.644
Human Hepatotoxicity (H-HT):  0.943 Drug-induced Liver Injury (DILI):  0.957
AMES Toxicity:  0.712 Rat Oral Acute Toxicity:  0.304
Maximum Recommended Daily Dose:  0.576 Skin Sensitization:  0.895
Carcinogencity:  0.72 Eye Corrosion:  0.003
Eye Irritation:  0.821 Respiratory Toxicity:  0.336
Drug-induced Neurotoxicity:  0.779 Ototoxicity:  0.673
Hematotoxicity:  0.654 Drug-induced Nephrotoxicity:  0.883
Genotoxicity:  0.96 RPMI-8226 Immunitoxicity:  0.273
A549 Cytotoxicity:  0.467 Hek293 Cytotoxicity:  0.588
BCF:   1.181
?
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:   3.903
?
48 hour Tetrahymena pyriformis IGC50. The unit of IGC50 is -log10[(mg/L)/(1000*MW)].
LC50DM:   5.209
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48 hour Daphnia magna LC50. The unit of LC50DM is -log10[(mg/L)/(1000*MW)].
 LC50FM:   4.634
?
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
NPO683 Rosa canina Species Rosaceae Eukaryota n.a. n.a. n.a. PMID[12880322]
NPO7267 Glycosmis chlorosperma Species Rutaceae Eukaryota n.a. n.a. n.a. PMID[24798019]
NPO10398 Myrica gale Species Myricaceae Eukaryota n.a. n.a. n.a. PMID[36903911]
NPO8340 Stachys sylvatica Species Lamiaceae Eukaryota n.a. n.a. n.a. PMID[38769997]
NPO19459 Dictyota kunthii Species Dictyotaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO683 Rosa canina Species Rosaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO7267 Glycosmis chlorosperma Species Rutaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO28466 Torreya nucifera Species Taxaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO12235 Trachelospermum jasminoides Species Apocynaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO10398 Myrica gale Species Myricaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO8340 Stachys sylvatica Species Lamiaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO14834 Trachelospermum asiaticum Species Apocynaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO12235 Trachelospermum jasminoides Species Apocynaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO683 Rosa canina Species Rosaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO14834 Trachelospermum asiaticum Species Apocynaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO683 Rosa canina Species Rosaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO12235 Trachelospermum jasminoides Species Apocynaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO10398 Myrica gale Species Myricaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO7267 Glycosmis chlorosperma Species Rutaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO8340 Stachys sylvatica Species Lamiaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO10398 Myrica gale Species Myricaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO12235 Trachelospermum jasminoides Species Apocynaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO683 Rosa canina Species Rosaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO14834 Trachelospermum asiaticum Species Apocynaceae Eukaryota n.a. n.a. n.a. Database[TM-MC]
NPO12235 Trachelospermum jasminoides Species Apocynaceae Eukaryota n.a. n.a. n.a. Database[TM-MC]
NPO12235 Trachelospermum jasminoides Species Apocynaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO7267 Glycosmis chlorosperma Species Rutaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO28466 Torreya nucifera Species Taxaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO8340 Stachys sylvatica Species Lamiaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO683 Rosa canina Species Rosaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO6760 Saussurea conica Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO14834 Trachelospermum asiaticum Species Apocynaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO19459 Dictyota kunthii Species Dictyotaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO10398 Myrica gale Species Myricaceae 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
NPT839 Cell line L6 Rattus norvegicus Activity = 128.8 % PMID[25941553]
NPT839 Cell line L6 Rattus norvegicus Activity = 233.9 % PMID[25941553]
NPT839 Cell line L6 Rattus norvegicus Ratio = 0.551 n.a. PMID[25941553]

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 NPC106920 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 NPC15811
0.8776 High Similarity NPC68779
0.8776 High Similarity NPC108598
0.8571 High Similarity NPC216223
0.8491 Intermediate Similarity NPC300776
0.8491 Intermediate Similarity NPC176814
0.8491 Intermediate Similarity NPC4982
0.8491 Intermediate Similarity NPC606629
0.8462 Intermediate Similarity NPC273657
0.7759 Intermediate Similarity NPC282291
0.7759 Intermediate Similarity NPC166137
0.7347 Intermediate Similarity NPC72796
0.7258 Intermediate Similarity NPC478703
0.7258 Intermediate Similarity NPC478704
0.717 Intermediate Similarity NPC211386
0.678 Remote Similarity NPC293757
0.678 Remote Similarity NPC668
0.661 Remote Similarity NPC5310
0.6557 Remote Similarity NPC145569
0.6552 Remote Similarity NPC176586
0.6552 Remote Similarity NPC210354
0.6441 Remote Similarity NPC102908
0.6429 Remote Similarity NPC40237
0.6429 Remote Similarity NPC487680
0.6415 Remote Similarity NPC223807
0.625 Remote Similarity NPC92693
0.625 Remote Similarity NPC299706
0.625 Remote Similarity NPC115466
0.625 Remote Similarity NPC174512
0.625 Remote Similarity NPC61604
0.623 Remote Similarity NPC100675
0.623 Remote Similarity NPC601691
0.6167 Remote Similarity NPC191158
0.6167 Remote Similarity NPC177644
0.6061 Remote Similarity NPC478705
0.6038 Remote Similarity NPC31344
0.6038 Remote Similarity NPC317769
0.5938 Remote Similarity NPC487679
0.5938 Remote Similarity NPC487678
0.5806 Remote Similarity NPC110699
0.5806 Remote Similarity NPC106055
0.5714 Remote Similarity NPC606339
0.5667 Remote Similarity NPC205915
0.5625 Remote Similarity NPC485282
0.5625 Remote Similarity NPC485283
0.5625 Remote Similarity NPC485281
0.5625 Remote Similarity NPC610284
0.5606 Remote Similarity NPC608199
0.5517 Remote Similarity NPC110958
0.5517 Remote Similarity NPC19890
0.5472 Remote Similarity NPC57490
0.541 Remote Similarity NPC275950
0.5385 Remote Similarity NPC67247
0.5333 Remote Similarity NPC173308
0.5333 Remote Similarity NPC181079
0.5323 Remote Similarity NPC253481
0.5323 Remote Similarity NPC253722
0.5303 Remote Similarity NPC31751
0.5294 Remote Similarity NPC120852
0.5263 Remote Similarity NPC325295
0.5263 Remote Similarity NPC227217
0.5263 Remote Similarity NPC117780
0.5263 Remote Similarity NPC76308
0.5195 Remote Similarity NPC245615
0.519 Remote Similarity NPC486547
0.5147 Remote Similarity NPC169973
0.5094 Remote Similarity NPC165133
0.5094 Remote Similarity NPC242885
0.5094 Remote Similarity NPC95614
0.5094 Remote Similarity NPC232316
0.5085 Remote Similarity NPC607444
0.5082 Remote Similarity NPC143895
0.5079 Remote Similarity NPC475875
0.5077 Remote Similarity NPC610652
0.5075 Remote Similarity NPC29599

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC106920 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