Natural Product: NPC49235

Natural Product IDNPC49235
Common Name
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The InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
 Diasesartemin
IUPAC Name 6-[(3R,3aR,6R,6aR)-6-(3,4,5-trimethoxyphenyl)-1,3,3a,4,6,6a-hexahydrofuro[3,4-c]furan-3-yl]-4-methoxy-1,3-benzodioxole
Synonyms Diasesartemin
Synthetic Gene Cluster n.a.
ChEMBL Identifier CHEMBL453301
PubChem CID 73118
Chemical Classification
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0001392] Lignans, neolignans and related compounds
      • [CHEMONTID:0003686] Furanoid 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 DHWUVPPRBIJJKS-PBFVBANWSA-N
Standard InCHI InChI=1S/C23H26O8/c1-24-16-5-12(6-17(25-2)22(16)27-4)20-14-9-29-21(15(14)10-28-20)13-7-18(26-3)23-19(8-13)30-11-31-23/h5-8,14-15,20-21H,9-11H2,1-4H3/t14-,15-,20-,21-/m0/s1
SMILES COc1cc(cc(c1OC)OC)[C@@H]1OC[C@H]2[C@@H]1CO[C@H]2c1cc(OC)c2c(c1)OCO2

  Calculated Properties

Physi-Chem Properties

MedChem Properties

ADMET Properties (ADMETlab3.0)

ADMET: Absorption

ADMET: Distribution

ADMET: Metabolism

ADMET: Excretion

ADMET: Toxicity

  Species Source

Organism ID Organism Name Taxonomy Level Family SuperKingdom Isolation Part Collection Location Collection Time Reference
NPO13567 Streptomyces sahachiroi Species Streptomycetaceae Bacteria n.a. n.a. n.a. PMID[20485749]
NPO13567 Streptomyces sahachiroi Species Streptomycetaceae Bacteria n.a. n.a. n.a. Database[COCONUT]
NPO16527 Baptisia minor Species Fabaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO16197 Eucalyptus microcorys Species Myrtaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO13567 Streptomyces sahachiroi Species Streptomycetaceae Bacteria n.a. n.a. n.a. Database[UNPD]
NPO16197 Eucalyptus microcorys Species Myrtaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO16527 Baptisia minor Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO13402 Eupatorium inulifolium Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO16488 Achromobacter piechaudii Species Alcaligenaceae 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
NPT2 Others Unspecified n.a. IC50 > 4.0 ug.mL-1 PMID[12141878]

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 NPC49235 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 NPC148893
1.0 High Similarity NPC25333
0.8056 Intermediate Similarity NPC281864
0.8056 Intermediate Similarity NPC328682
0.8056 Intermediate Similarity NPC54321
0.7955 Intermediate Similarity NPC185071
0.7907 Intermediate Similarity NPC189474
0.7143 Intermediate Similarity NPC12728
0.7073 Intermediate Similarity NPC473092
0.7073 Intermediate Similarity NPC473093
0.7073 Intermediate Similarity NPC8050
0.6744 Remote Similarity NPC222127
0.6744 Remote Similarity NPC82862
0.6667 Remote Similarity NPC72046
0.6667 Remote Similarity NPC261812
0.6667 Remote Similarity NPC227160
0.6667 Remote Similarity NPC82111
0.6667 Remote Similarity NPC65183
0.6591 Remote Similarity NPC165155
0.6591 Remote Similarity NPC24490
0.6512 Remote Similarity NPC171928
0.6512 Remote Similarity NPC158526
0.6512 Remote Similarity NPC129687
0.6512 Remote Similarity NPC33611
0.6512 Remote Similarity NPC16830
0.6512 Remote Similarity NPC100223
0.6429 Remote Similarity NPC31530
0.6207 Remote Similarity NPC486102
0.6078 Remote Similarity NPC298317
0.6078 Remote Similarity NPC255566
0.5962 Remote Similarity NPC46591
0.5814 Remote Similarity NPC121783
0.5814 Remote Similarity NPC34902
0.5814 Remote Similarity NPC18449
0.5745 Remote Similarity NPC312199
0.5745 Remote Similarity NPC209229
0.5741 Remote Similarity NPC287124
0.5741 Remote Similarity NPC477702
0.566 Remote Similarity NPC474139
0.5556 Remote Similarity NPC166884
0.5556 Remote Similarity NPC141569
0.5556 Remote Similarity NPC88640
0.5556 Remote Similarity NPC101153
0.5556 Remote Similarity NPC193666
0.5556 Remote Similarity NPC123526
0.5556 Remote Similarity NPC477701
0.5556 Remote Similarity NPC608725
0.551 Remote Similarity NPC136750
0.551 Remote Similarity NPC266848
0.5455 Remote Similarity NPC141765
0.5455 Remote Similarity NPC34103
0.5385 Remote Similarity NPC486100
0.5385 Remote Similarity NPC486101
0.5283 Remote Similarity NPC121651
0.5208 Remote Similarity NPC606146
0.5094 Remote Similarity NPC113550
0.5094 Remote Similarity NPC177868
0.5091 Remote Similarity NPC483653

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC49235 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