Natural Product: NPC476027

Natural Product IDNPC476027
Common Name
?
The InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
(2S,3R,5R,9R,10R,13R,14S,17S)-17-[(2S,3R)-5-Ethyl-2,3-Dihydroxy-6-(Hydroxymethyl)Hept-6-En-2-Yl]-2,3,14-Trihydroxy-10,13-Dimethyl-2,3,4,5,9,11,12,15,16,17-Decahydro-1H-Cyclopenta[A]Phenanthren-6-One
IUPAC Name (2S,3R,5R,9R,10R,13R,14S,17S)-17-[(2S,3R)-5-ethyl-2,3-dihydroxy-6-(hydroxymethyl)hept-6-en-2-yl]-2,3,14-trihydroxy-10,13-dimethyl-2,3,4,5,9,11,12,15,16,17-decahydro-1H-cyclopenta[a]phenanthren-6-one
Synonyms
Synthetic Gene Cluster n.a.
ChEMBL Identifier CHEMBL522368
PubChem CID 44566371
Chemical Classification
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000012] Lipids and lipid-like molecules
      • [CHEMONTID:0000258] Steroids and steroid derivatives
        • [CHEMONTID:0002031] Stigmastanes 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 ODENAQIZHMFEAO-TYVXGIJNSA-N
Standard InCHI InChI=1S/C29H46O7/c1-6-17(16(2)15-30)11-25(34)28(5,35)24-8-10-29(36)19-12-21(31)20-13-22(32)23(33)14-26(20,3)18(19)7-9-27(24,29)4/h12,17-18,20,22-25,30,32-36H,2,6-11,13-15H2,1,3-5H3/t17?,18-,20-,22+,23-,24-,25+,26+,27+,28-,29+/m0/s1
SMILES CCC(C(=C)CO)C[C@H]([C@]([C@H]1CC[C@@]2([C@]1(C)CC[C@H]1C2=CC(=O)[C@H]2[C@]1(C)C[C@H](O)[C@@H](C2)O)O)(O)C)O

  Calculated Properties

Physi-Chem Properties

Molecular Weight:   506.32 Volume:   529.536
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Van der Waals volume.
Dense:   0.956 LogP:   2.062
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The logarithm of the n-octanol/water distribution coefficients.
logD7.4:   2.531
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The logarithm of the n-octanol/water distribution coefficient at pH=7.4.
LogS:   -3.559
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The logarithm of aqueous solubility value.
Rotatable Bonds:   7.0 Rigid Bonds:   22.0
TPSA:   138.45
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Topological Polar Surface Area.
H-Bond Acceptor:   7.0
H-Bond Donor:   6.0 Rings:   4.0
Heavy Atoms:   7.0

MedChem Properties

QED Drug-Likeness Score:   0.291 GASA:   1.0
?
GASA represents the probability of being difficult to synthesize, ranging from 0 to 1.
Synthetic Accessibility Score:   5.429 Fsp3:   0.828
MCE-18:   85.962
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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:   0.334 Fluc inhibitor:   0.001
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The fluc inhibitor value is the probability of being fLuc inhibitors, within the range of 0 to 1.
Blue fluorescence:   0.008
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The blue fluorescence value is the probability of being blue fluorescence, within the range of 0 to 1
Green fluorescence:   0.003
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The green fluorescence value is the probability of being green fluorescence, within the range of 0 to 1
Reactive compounds:   0.335 Promiscuous compounds:   0.287

ADMET Properties (ADMETlab3.0)

ADMET: Absorption

Caco-2 Permeability:   -4.788 MDCK Permeability:   -4.631
Pgp-inhibitor:   0.0 Pgp-substrate:   0.389
PAMPA:   1.0
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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):   0.003
20% Bioavailability (F20%):   0.446 30% Bioavailability (F30%):   0.292
50% Bioavailability (F50%):   0.998

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):   0.001 MRP1:   0.219
Plasma Protein Binding (PPB):   72.081% Volume Distribution (VD):   -0.005
Fu: 33.767%
?
The fraction unbound in plasms.
OATP1B1 inhibitor:   0.999
OATP1B3 inhibitor:   0.979 BCRP inhibitor:   0.549
BSEP inhibitor:   0.356

ADMET: Metabolism

CYP1A2-inhibitor:   0.0 CYP1A2-substrate:   0.0
CYP2C19-inhibitor:   0.001 CYP2C19-substrate:   0.0
CYP2C9-inhibitor:   0.0 CYP2C9-substrate:   0.0
CYP2D6-inhibitor:   0.0 CYP2D6-substrate:   0.001
CYP3A4-inhibitor:   0.718 CYP3A4-substrate:   0.0
CYP2B6-substrate:   0.0 CYP2C8-inhibitor:   0.108
HLM stability:   0.345
?
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):  5.692 Half-life (T1/2):  2.356

ADMET: Toxicity

hERG Blockers:  0.039 hERG Blockers (10um):  0.245
Human Hepatotoxicity (H-HT):  0.651 Drug-induced Liver Injury (DILI):  0.01
AMES Toxicity:  0.093 Rat Oral Acute Toxicity:  0.068
Maximum Recommended Daily Dose:  0.735 Skin Sensitization:  0.621
Carcinogencity:  0.729 Eye Corrosion:  0.0
Eye Irritation:  0.08 Respiratory Toxicity:  0.21
Drug-induced Neurotoxicity:  0.042 Ototoxicity:  0.955
Hematotoxicity:  0.177 Drug-induced Nephrotoxicity:  0.814
Genotoxicity:  0.421 RPMI-8226 Immunitoxicity:  0.088
A549 Cytotoxicity:  0.019 Hek293 Cytotoxicity:  0.275
BCF:   0.506
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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:   3.291
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48 hour Tetrahymena pyriformis IGC50. The unit of IGC50 is -log10[(mg/L)/(1000*MW)].
LC50DM:   5.123
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48 hour Daphnia magna LC50. The unit of LC50DM is -log10[(mg/L)/(1000*MW)].
LC50FM:   4.035
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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
NPO17539 Ajuga decumbens Species Lamiaceae Eukaryota flowering whole plant n.a. n.a. PMID[10425119]
NPO17539 Ajuga decumbens Species Lamiaceae Eukaryota n.a. n.a. n.a. PMID[9748375]
NPO17539 Ajuga decumbens Species Lamiaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO17539 Ajuga decumbens Species Lamiaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO17539 Ajuga decumbens Species Lamiaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO17539 Ajuga decumbens Species Lamiaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO17539 Ajuga decumbens Species Lamiaceae Eukaryota n.a. n.a. n.a. Database[TM-MC]
NPO17539 Ajuga decumbens Species Lamiaceae 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
NPT80 Cell line Raji Homo sapiens Activity = 70.0 % PubChem BioAssay data set
NPT80 Cell line Raji Homo sapiens Activity > 80.0 % PMID[23398362]
NPT2 Others Unspecified n.a. Activity = 49.1 % PMID[10560729]
NPT2 Others Unspecified n.a. Activity = 95.8 % PMID[10560729]
NPT2 Others Unspecified n.a. Activity = 72.6 % PMID[24900585]
NPT2 Others Unspecified n.a. Activity = 4.6 % PMID[17158936]

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 NPC476027 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
0.8226 Intermediate Similarity NPC296945
0.8065 Intermediate Similarity NPC214264
0.8065 Intermediate Similarity NPC475060
0.8065 Intermediate Similarity NPC85829
0.7778 Intermediate Similarity NPC50692
0.7778 Intermediate Similarity NPC260268
0.7778 Intermediate Similarity NPC48733
0.7778 Intermediate Similarity NPC171137
0.7778 Intermediate Similarity NPC152695
0.7778 Intermediate Similarity NPC319077
0.7778 Intermediate Similarity NPC83744
0.7778 Intermediate Similarity NPC97202
0.7778 Intermediate Similarity NPC601752
0.7692 Intermediate Similarity NPC202167
0.7692 Intermediate Similarity NPC49958
0.7656 Intermediate Similarity NPC220229
0.7656 Intermediate Similarity NPC601682
0.7353 Intermediate Similarity NPC49492
0.7353 Intermediate Similarity NPC266728
0.7 Intermediate Similarity NPC600136
0.6818 Remote Similarity NPC302607
0.6714 Remote Similarity NPC207251
0.6571 Remote Similarity NPC317210
0.6351 Remote Similarity NPC109973
0.6232 Remote Similarity NPC76084
0.6176 Remote Similarity NPC150531
0.6087 Remote Similarity NPC204833
0.6087 Remote Similarity NPC209502
0.6087 Remote Similarity NPC477915
0.6087 Remote Similarity NPC600374
0.6053 Remote Similarity NPC475041
0.6 Remote Similarity NPC329417
0.6 Remote Similarity NPC149047
0.5857 Remote Similarity NPC11710
0.5857 Remote Similarity NPC217201
0.5857 Remote Similarity NPC451956
0.5857 Remote Similarity NPC610677
0.5672 Remote Similarity NPC603391
0.5526 Remote Similarity NPC250109
0.5443 Remote Similarity NPC600372
0.5357 Remote Similarity NPC28532
0.5325 Remote Similarity NPC606024
0.5128 Remote Similarity NPC326542
0.5068 Remote Similarity NPC108721
0.5068 Remote Similarity NPC73300

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC476027 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