Natural Product: NPC611870

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 NPC611870 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 NPC482747
1.0 High Similarity NPC202666
1.0 High Similarity NPC471961
1.0 High Similarity NPC242015
0.9 High Similarity NPC482741
0.9 High Similarity NPC482745
0.9 High Similarity NPC482743
0.9 High Similarity NPC146753
0.8901 High Similarity NPC471965
0.8901 High Similarity NPC482749
0.8837 High Similarity NPC482752
0.8526 High Similarity NPC262199
0.8404 Intermediate Similarity NPC14617
0.8152 Intermediate Similarity NPC482750
0.8085 Intermediate Similarity NPC482746
0.8041 Intermediate Similarity NPC482734
0.8041 Intermediate Similarity NPC182342
0.8041 Intermediate Similarity NPC482727
0.8041 Intermediate Similarity NPC471964
0.7957 Intermediate Similarity NPC309780
0.7526 Intermediate Similarity NPC482717
0.7374 Intermediate Similarity NPC285091
0.7353 Intermediate Similarity NPC247315
0.7353 Intermediate Similarity NPC482728
0.7255 Intermediate Similarity NPC482755
0.7228 Intermediate Similarity NPC482722
0.7228 Intermediate Similarity NPC471963
0.7228 Intermediate Similarity NPC482729
0.7228 Intermediate Similarity NPC482742
0.7228 Intermediate Similarity NPC482744
0.7204 Intermediate Similarity NPC471967
0.7143 Intermediate Similarity NPC482748
0.7115 Intermediate Similarity NPC482737
0.7115 Intermediate Similarity NPC482735
0.701 Intermediate Similarity NPC482726
0.7009 Intermediate Similarity NPC471962
0.6667 Remote Similarity NPC482739
0.6607 Remote Similarity NPC482736
0.6607 Remote Similarity NPC482738
0.6569 Remote Similarity NPC482751
0.6389 Remote Similarity NPC482740
0.6222 Remote Similarity NPC482712
0.6222 Remote Similarity NPC74751
0.6154 Remote Similarity NPC275343
0.6 Remote Similarity NPC4036
0.6 Remote Similarity NPC65120
0.6 Remote Similarity NPC145067
0.6 Remote Similarity NPC233455
0.6 Remote Similarity NPC158030
0.5364 Remote Similarity NPC472949
0.5326 Remote Similarity NPC96095
0.5192 Remote Similarity NPC286347
0.5175 Remote Similarity NPC251768
0.5093 Remote Similarity NPC480938
0.5085 Remote Similarity NPC301449
0.5085 Remote Similarity NPC601290

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC611870 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
1.0 High Similarity NPD8328 Phase 2
0.6222 Remote Similarity NPD7748 Pre-clinical
0.6 Remote Similarity NPD7515 Phase 2
0.5895 Remote Similarity NPD7902 Phase 4

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