Natural Product: NPC601275

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 NPC601275 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
0.8448 Intermediate Similarity NPC192744
0.7812 Intermediate Similarity NPC608379
0.7742 Intermediate Similarity NPC201655
0.7576 Intermediate Similarity NPC603461
0.7077 Intermediate Similarity NPC16377
0.6716 Remote Similarity NPC474719
0.6618 Remote Similarity NPC611139
0.6486 Remote Similarity NPC605397
0.6269 Remote Similarity NPC488164
0.6269 Remote Similarity NPC264005
0.6154 Remote Similarity NPC103754
0.6143 Remote Similarity NPC488165
0.6119 Remote Similarity NPC264317
0.6119 Remote Similarity NPC294438
0.6061 Remote Similarity NPC474484
0.6056 Remote Similarity NPC600004
0.6053 Remote Similarity NPC611262
0.6 Remote Similarity NPC68828
0.5972 Remote Similarity NPC600907
0.5833 Remote Similarity NPC602147
0.5797 Remote Similarity NPC488506
0.5797 Remote Similarity NPC220498
0.5753 Remote Similarity NPC606727
0.5694 Remote Similarity NPC603784
0.5652 Remote Similarity NPC80590
0.5634 Remote Similarity NPC4309
0.5634 Remote Similarity NPC151191
0.5634 Remote Similarity NPC606726
0.5571 Remote Similarity NPC24772
0.5571 Remote Similarity NPC292553
0.5571 Remote Similarity NPC213832
0.5522 Remote Similarity NPC246445
0.5522 Remote Similarity NPC201459
0.5513 Remote Similarity NPC606354
0.5493 Remote Similarity NPC271974
0.5493 Remote Similarity NPC195395
0.5493 Remote Similarity NPC247312
0.5479 Remote Similarity NPC160506
0.5429 Remote Similarity NPC30583
0.5385 Remote Similarity NPC602512
0.5362 Remote Similarity NPC472740
0.5362 Remote Similarity NPC69101
0.5352 Remote Similarity NPC211162
0.5352 Remote Similarity NPC183374
0.5342 Remote Similarity NPC488213
0.5333 Remote Similarity NPC487492
0.5286 Remote Similarity NPC175410
0.5286 Remote Similarity NPC119743
0.5278 Remote Similarity NPC277399
0.527 Remote Similarity NPC486704
0.52 Remote Similarity NPC478841
0.52 Remote Similarity NPC488166
0.52 Remote Similarity NPC606728
0.52 Remote Similarity NPC608881
0.5152 Remote Similarity NPC43300
0.5139 Remote Similarity NPC291373
0.5135 Remote Similarity NPC474511
0.5135 Remote Similarity NPC475061
0.5063 Remote Similarity NPC607678
0.5063 Remote Similarity NPC607679

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC601275 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
0.6119 Remote Similarity NPD7520 Phase 1
0.5479 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