Natural Product: NPC608314

The Chemical Classification was calculated by Classyfire, a software for chemical taxonomy calculation. Reference: DOI:10.1186/s13321-016-0174-y.

  Chemical Representations

  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

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 NPC608314 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 NPC483853
0.932 High Similarity NPC483856
0.9135 High Similarity NPC483854
0.9048 High Similarity NPC482915
0.8061 Intermediate Similarity NPC76565
0.8061 Intermediate Similarity NPC601313
0.7961 Intermediate Similarity NPC475600
0.7941 Intermediate Similarity NPC326930
0.7524 Intermediate Similarity NPC475301
0.7455 Intermediate Similarity NPC327769
0.7383 Intermediate Similarity NPC476110
0.7328 Intermediate Similarity NPC483855
0.729 Intermediate Similarity NPC87152
0.729 Intermediate Similarity NPC475631
0.7207 Intermediate Similarity NPC170751
0.7196 Intermediate Similarity NPC475303
0.7064 Intermediate Similarity NPC475596
0.7054 Intermediate Similarity NPC328928
0.6729 Remote Similarity NPC475498
0.6604 Remote Similarity NPC35208
0.6581 Remote Similarity NPC475426
0.6549 Remote Similarity NPC475644
0.6449 Remote Similarity NPC250807
0.6449 Remote Similarity NPC57797
0.6429 Remote Similarity NPC122968
0.6429 Remote Similarity NPC228377
0.6396 Remote Similarity NPC53255
0.6396 Remote Similarity NPC85879
0.6271 Remote Similarity NPC471979
0.6261 Remote Similarity NPC30456
0.6261 Remote Similarity NPC488904
0.6239 Remote Similarity NPC475137
0.6228 Remote Similarity NPC471977
0.6071 Remote Similarity NPC146824
0.6068 Remote Similarity NPC473689
0.6068 Remote Similarity NPC292416
0.6034 Remote Similarity NPC13603
0.5966 Remote Similarity NPC477787
0.5929 Remote Similarity NPC473833
0.5882 Remote Similarity NPC475406
0.5862 Remote Similarity NPC328186
0.5812 Remote Similarity NPC470486
0.5766 Remote Similarity NPC470306
0.575 Remote Similarity NPC244839
0.575 Remote Similarity NPC600583
0.5702 Remote Similarity NPC319880
0.5702 Remote Similarity NPC320324
0.5678 Remote Similarity NPC316841
0.5537 Remote Similarity NPC600607
0.5528 Remote Similarity NPC327904
0.5528 Remote Similarity NPC38959
0.55 Remote Similarity NPC324619
0.5462 Remote Similarity NPC475533
0.5372 Remote Similarity NPC471190
0.5289 Remote Similarity NPC328154
0.5259 Remote Similarity NPC471016
0.5242 Remote Similarity NPC601643
0.5167 Remote Similarity NPC475362
0.512 Remote Similarity NPC253482

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC608314 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