Natural Product: NPC607901

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 NPC607901 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 NPC274356
1.0 High Similarity NPC101748
0.84 Intermediate Similarity NPC487677
0.84 Intermediate Similarity NPC487675
0.8 Intermediate Similarity NPC227217
0.8 Intermediate Similarity NPC117780
0.7778 Intermediate Similarity NPC487679
0.7778 Intermediate Similarity NPC487678
0.7692 Intermediate Similarity NPC46880
0.7547 Intermediate Similarity NPC487681
0.7451 Intermediate Similarity NPC284464
0.7447 Intermediate Similarity NPC249788
0.7407 Intermediate Similarity NPC106739
0.7407 Intermediate Similarity NPC161249
0.7273 Intermediate Similarity NPC471505
0.7209 Intermediate Similarity NPC165133
0.7209 Intermediate Similarity NPC242885
0.7209 Intermediate Similarity NPC95614
0.7209 Intermediate Similarity NPC232316
0.7111 Intermediate Similarity NPC344161
0.6977 Remote Similarity NPC80241
0.6977 Remote Similarity NPC301641
0.6977 Remote Similarity NPC485483
0.6724 Remote Similarity NPC282291
0.6724 Remote Similarity NPC166137
0.6724 Remote Similarity NPC169973
0.6471 Remote Similarity NPC485480
0.6327 Remote Similarity NPC56214
0.6275 Remote Similarity NPC607444
0.6078 Remote Similarity NPC127587
0.6 Remote Similarity NPC28398
0.6 Remote Similarity NPC487676
0.5926 Remote Similarity NPC487680
0.5769 Remote Similarity NPC485482
0.5614 Remote Similarity NPC142547
0.5614 Remote Similarity NPC228469
0.5556 Remote Similarity NPC104077
0.5556 Remote Similarity NPC165106
0.5556 Remote Similarity NPC219671
0.5556 Remote Similarity NPC156840
0.5556 Remote Similarity NPC216223
0.5556 Remote Similarity NPC147616
0.551 Remote Similarity NPC40352
0.551 Remote Similarity NPC85488
0.551 Remote Similarity NPC213711
0.55 Remote Similarity NPC291101
0.55 Remote Similarity NPC266197
0.5472 Remote Similarity NPC196937
0.5424 Remote Similarity NPC227002
0.5333 Remote Similarity NPC300776
0.5333 Remote Similarity NPC176814
0.5333 Remote Similarity NPC4982
0.5333 Remote Similarity NPC606629
0.5323 Remote Similarity NPC145569
0.5273 Remote Similarity NPC30951
0.5273 Remote Similarity NPC474288
0.5208 Remote Similarity NPC8547
0.52 Remote Similarity NPC57490
0.5192 Remote Similarity NPC31344
0.5192 Remote Similarity NPC317769
0.5167 Remote Similarity NPC88640
0.5167 Remote Similarity NPC101153
0.5167 Remote Similarity NPC193666
0.5167 Remote Similarity NPC123526
0.5167 Remote Similarity NPC608725
0.5102 Remote Similarity NPC477886
0.5098 Remote Similarity NPC299406
0.5094 Remote Similarity NPC476748
0.5091 Remote Similarity NPC232275
0.5088 Remote Similarity NPC143895
0.5079 Remote Similarity NPC31751
0.5079 Remote Similarity NPC43514
0.5075 Remote Similarity NPC604694

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC607901 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
0.5556 Remote Similarity NPD5283 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