Natural Product: NPC45831

Natural Product IDNPC45831
Common Name
?
The InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
 MRSOKRFVFUXGDC-PXKSBGFPSA-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: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 MRSOKRFVFUXGDC-PXKSBGFPSA-N
Standard InCHI InChI=1S/C32H52O2/c1-19(2)23-18-20(3)22-12-16-31(8)24(28(22)23)10-11-26-30(7)15-14-27(34-21(4)33)29(5,6)25(30)13-17-32(26,31)9/h20,22-28H,1,10-18H2,2-9H3/t20-,22-,23+,24-,25-,26-,27+,28-,30+,31-,32-/m1/s1
SMILES C=C(C)[C@@H]1C[C@@H](C)[C@H]2CC[C@]3(C)[C@H](CC[C@@H]4[C@@]5(C)CC[C@@H](C(C)(C)[C@H]5CC[C@@]34C)OC(=O)C)[C@@H]12

  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
NPO16012 Aconitum altaicum Species Ranunculaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO502 Sophora franchetiana Species Fabaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO5376 Liabum eggersii Species Asteraceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO6293 Ornithogalum umbellatum Species Hyacinthaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO502 Sophora franchetiana Species Fabaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO12269 Astragalus dipelta Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO16012 Aconitum altaicum Species Ranunculaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO6293 Ornithogalum umbellatum Species Hyacinthaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO5376 Liabum eggersii Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO502 Sophora franchetiana Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO14487 Dryopteris remota Species Dryopteridaceae 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 NPC45831 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
0.6552 Remote Similarity NPC305835
0.623 Remote Similarity NPC98270
0.6129 Remote Similarity NPC5280
0.6094 Remote Similarity NPC4309
0.6032 Remote Similarity NPC304194
0.5902 Remote Similarity NPC84868
0.5833 Remote Similarity NPC488509
0.5692 Remote Similarity NPC168231
0.5625 Remote Similarity NPC481227
0.5625 Remote Similarity NPC611062
0.5606 Remote Similarity NPC180204
0.5574 Remote Similarity NPC475509
0.5484 Remote Similarity NPC302280
0.5441 Remote Similarity NPC160506
0.5385 Remote Similarity NPC488508
0.5303 Remote Similarity NPC261616
0.5303 Remote Similarity NPC31031
0.5231 Remote Similarity NPC190940
0.5231 Remote Similarity NPC61107
0.5231 Remote Similarity NPC488510
0.507 Remote Similarity NPC475416

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC45831 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
0.5441 Remote Similarity NPD8035 Phase 2

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