Natural Product: NPC195131

Natural Product IDNPC195131
Common Name
?
The InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
Cipatrijugin D
IUPAC Name n.a.
Synonyms Cipatrijugin D
Synthetic Gene Cluster n.a.
ChEMBL Identifier CHEMBL253139
PubChem CID 23626013
Chemical Classification
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000264] Organic acids and derivatives
      • [CHEMONTID:0000265] Carboxylic acids and derivatives
        • [CHEMONTID:0002966] Tetracarboxylic acids and derivatives

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

  Chemical Representations

Standard InCHIKey QBSRTZKWHMBTEU-PIFFJMDHSA-N
Standard InCHI InChI=1S/C31H38O11/c1-15-24-25(36)29(6)19(11-22(34)37-8)28(4,5)20(39-16(2)32)12-21(29)42-31(15)13-23(35)41-26(18-9-10-38-14-18)30(31,7)27(24)40-17(3)33/h9-10,14,19-21,24,26-27H,1,11-13H2,2-8H3/t19-,20+,21-,24-,26-,27-,29+,30+,31-/m0/s1
SMILES C=C1[C@H]2C(=O)[C@]3(C)[C@@H](CC(=O)OC)C(C)(C)[C@@H](C[C@@H]3O[C@]31CC(=O)O[C@@H](c1ccoc1)[C@]3(C)[C@H]2OC(=O)C)OC(=O)C

  Calculated Properties

Physi-Chem Properties

Molecular Weight:   586.24 Volume:   577.551
?
Van der Waals volume.
Dense:   1.015 LogP:   1.439
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The logarithm of the n-octanol/water distribution coefficients.
logD7.4:   1.8
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The logarithm of the n-octanol/water distribution coefficient at pH=7.4.
LogS:   -3.481
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The logarithm of aqueous solubility value.
Rotatable Bonds:   8.0 Rigid Bonds:   31.0
TPSA:   144.64
?
Topological Polar Surface Area.
H-Bond Acceptor:   11.0
H-Bond Donor:   0.0 Rings:   5.0
Heavy Atoms:   11.0

MedChem Properties

QED Drug-Likeness Score:   0.283 GASA:   1.0
?
GASA represents the probability of being difficult to synthesize, ranging from 0 to 1.
Synthetic Accessibility Score:   6.574 Fsp3:   0.645
MCE-18:   178.824
?
MCE-18 stands for medicinal chemistry evolution.MCE-18≥45 is considered a suitable value.
Lipinski Rule-of-5:   Accepted
Pfizer Rule:   Rejected GSK Rule:   Accepted
Golden Triangle Rule:   Accepted BMS Rule:   0
Chelating Alert:   0 PAINS Alert:   0
Colloidal aggregators:   0.474 Fluc inhibitor:   0.001
?
The fluc inhibitor value is the probability of being fLuc inhibitors, within the range of 0 to 1.
Blue fluorescence:   0.019
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The blue fluorescence value is the probability of being blue fluorescence, within the range of 0 to 1
Green fluorescence:   0.018
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The green fluorescence value is the probability of being green fluorescence, within the range of 0 to 1
Reactive compounds:   0.142 Promiscuous compounds:   0.539

ADMET Properties (ADMETlab3.0)

ADMET: Absorption

Caco-2 Permeability:   -5.212 MDCK Permeability:   -4.953
Pgp-inhibitor:   0.993 Pgp-substrate:   0.066
PAMPA:   0.644
?
The experimental data for Peff was logarithmically transformed (logPeff). Molecules with log Peff values below 2.0 were classified as low-permeability (Category 0), while those with log Peff values exceeding 2.5 were classified as high-permeability (Category 1).
Human Intestinal Absorption (HIA):   0.006
20% Bioavailability (F20%):   0.117 30% Bioavailability (F30%):   0.879
50% Bioavailability (F50%):   0.919

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):   0.0 MRP1:   0.915
Plasma Protein Binding (PPB):   59.609% Volume Distribution (VD):   -0.439
Fu: 40.685%
?
The fraction unbound in plasms.
OATP1B1 inhibitor:   0.999
OATP1B3 inhibitor:   0.99 BCRP inhibitor:   0.243
BSEP inhibitor:   0.938

ADMET: Metabolism

CYP1A2-inhibitor:   0.182 CYP1A2-substrate:   0.018
CYP2C19-inhibitor:   0.947 CYP2C19-substrate:   0.005
CYP2C9-inhibitor:   0.013 CYP2C9-substrate:   0.0
CYP2D6-inhibitor:   0.006 CYP2D6-substrate:   0.0
CYP3A4-inhibitor:   0.006 CYP3A4-substrate:   0.933
CYP2B6-substrate:   0.071 CYP2C8-inhibitor:   0.998
HLM stability:   0.956
?
Human liver microsomal (HLM) stability. Category 0: stable+ (HLM > 30 min); Category 1: unstable- (HLM ≤ 30 min). The output value is the probability of human liver microsomal instability, where a value closer to 1 indicates a higher likelihood of instability.

ADMET: Excretion

Clearance (CL):  5.024 Half-life (T1/2):  1.291

ADMET: Toxicity

hERG Blockers:  0.01 hERG Blockers (10um):  0.036
Human Hepatotoxicity (H-HT):  0.68 Drug-induced Liver Injury (DILI):  0.988
AMES Toxicity:  0.508 Rat Oral Acute Toxicity:  0.607
Maximum Recommended Daily Dose:  0.766 Skin Sensitization:  0.963
Carcinogencity:  0.941 Eye Corrosion:  0.005
Eye Irritation:  0.713 Respiratory Toxicity:  0.085
Drug-induced Neurotoxicity:  0.114 Ototoxicity:  0.564
Hematotoxicity:  0.554 Drug-induced Nephrotoxicity:  0.966
Genotoxicity:  0.995 RPMI-8226 Immunitoxicity:  0.119
A549 Cytotoxicity:  0.04 Hek293 Cytotoxicity:  0.085
BCF:   0.476
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Bioconcentration factors are used for considering secondary poisoning potential and assessing risks to human health via the food chain. The unit is -log10[(mg/L)/(1000*MW)].
IGC50:   3.293
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48 hour Tetrahymena pyriformis IGC50. The unit of IGC50 is -log10[(mg/L)/(1000*MW)].
LC50DM:   5.663
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48 hour Daphnia magna LC50. The unit of LC50DM is -log10[(mg/L)/(1000*MW)].
LC50FM:   5.071
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96 hour fathead minnow LC50. The unit of LC50FM is -log10[(mg/L)/(1000*MW)].

  Species Source

Organism ID Organism Name Taxonomy Level Family SuperKingdom Isolation Part Collection Location Collection Time Reference
NPO4584 Cipadessa cinerascens Species Meliaceae Eukaryota leaves n.a. n.a. PMID[17655260]
NPO4584 Cipadessa cinerascens Species Meliaceae Eukaryota Leaves n.a. n.a. PMID[19296669]
NPO4584 Cipadessa cinerascens Species Meliaceae Eukaryota leaves Longlin County of Guangxi Province, China 2012-JUL PMID[25970729]
NPO4584 Cipadessa cinerascens Species Meliaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO4584 Cipadessa cinerascens Species Meliaceae Eukaryota n.a. n.a. n.a. Database[UNPD]

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
NPT81 Cell line A549 Homo sapiens ED50 > 5.0 ug ml-1 PMID[15217289]
NPT111 Cell line K562 Homo sapiens ED50 > 5.0 ug ml-1 PMID[17949976]

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 NPC195131 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
0.7436 Intermediate Similarity NPC204663
0.7375 Intermediate Similarity NPC472766
0.6627 Remote Similarity NPC6326
0.6548 Remote Similarity NPC149945
0.6341 Remote Similarity NPC476122
0.5977 Remote Similarity NPC249021
0.593 Remote Similarity NPC282445
0.5632 Remote Similarity NPC472765
0.5568 Remote Similarity NPC472772
0.5506 Remote Similarity NPC472764
0.5455 Remote Similarity NPC472767
0.5169 Remote Similarity NPC167142
0.5165 Remote Similarity NPC476224
0.5114 Remote Similarity NPC196864
0.5111 Remote Similarity NPC476262

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC195131 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