Natural Product: NPC601313

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 NPC601313 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 NPC76565
0.8876 High Similarity NPC326930
0.8791 High Similarity NPC476110
0.8778 High Similarity NPC475301
0.8681 High Similarity NPC87152
0.8681 High Similarity NPC475600
0.8681 High Similarity NPC475631
0.8571 High Similarity NPC475303
0.8387 Intermediate Similarity NPC475596
0.809 Intermediate Similarity NPC35208
0.8061 Intermediate Similarity NPC483853
0.8061 Intermediate Similarity NPC608314
0.8022 Intermediate Similarity NPC475498
0.79 Intermediate Similarity NPC475426
0.7889 Intermediate Similarity NPC250807
0.7889 Intermediate Similarity NPC57797
0.7778 Intermediate Similarity NPC328928
0.77 Intermediate Similarity NPC327769
0.7609 Intermediate Similarity NPC475137
0.7551 Intermediate Similarity NPC475644
0.7524 Intermediate Similarity NPC483856
0.7368 Intermediate Similarity NPC146824
0.7358 Intermediate Similarity NPC483854
0.729 Intermediate Similarity NPC482915
0.72 Intermediate Similarity NPC30456
0.72 Intermediate Similarity NPC488904
0.7188 Intermediate Similarity NPC473833
0.7041 Intermediate Similarity NPC53255
0.7041 Intermediate Similarity NPC85879
0.7021 Intermediate Similarity NPC470306
0.699 Remote Similarity NPC477787
0.69 Remote Similarity NPC122968
0.69 Remote Similarity NPC328186
0.69 Remote Similarity NPC228377
0.6893 Remote Similarity NPC244839
0.6893 Remote Similarity NPC600583
0.6832 Remote Similarity NPC470486
0.6667 Remote Similarity NPC319880
0.6667 Remote Similarity NPC316841
0.6667 Remote Similarity NPC320324
0.6667 Remote Similarity NPC471977
0.6602 Remote Similarity NPC13603
0.6569 Remote Similarity NPC475533
0.6476 Remote Similarity NPC473689
0.6476 Remote Similarity NPC292416
0.6449 Remote Similarity NPC327904
0.6449 Remote Similarity NPC38959
0.6389 Remote Similarity NPC471979
0.6364 Remote Similarity NPC471016
0.6262 Remote Similarity NPC475406
0.6132 Remote Similarity NPC471190
0.6058 Remote Similarity NPC475362
0.5981 Remote Similarity NPC324619
0.5941 Remote Similarity NPC473850
0.5888 Remote Similarity NPC475315
0.5856 Remote Similarity NPC170751
0.5833 Remote Similarity NPC600224
0.5763 Remote Similarity NPC483855
0.5727 Remote Similarity NPC611166
0.5688 Remote Similarity NPC604935
0.566 Remote Similarity NPC473506
0.5596 Remote Similarity NPC328154
0.5586 Remote Similarity NPC600607
0.5577 Remote Similarity NPC471014
0.5536 Remote Similarity NPC601643
0.5455 Remote Similarity NPC477788
0.5398 Remote Similarity NPC253482
0.5333 Remote Similarity NPC475408
0.5263 Remote Similarity NPC237702
0.5225 Remote Similarity NPC607403
0.521 Remote Similarity NPC469748
0.5138 Remote Similarity NPC483892
0.513 Remote Similarity NPC475648
0.5091 Remote Similarity NPC475601

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC601313 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