Structure

Physi-Chem Properties

Molecular Weight:  523.26
Volume:  541.617
LogP:  4.475
LogD:  3.942
LogS:  -4.265
# Rotatable Bonds:  17
TPSA:  62.74
# H-Bond Aceptor:  6
# H-Bond Donor:  0
# Rings:  1
# Heavy Atoms:  8

MedChem Properties

QED Drug-Likeness Score:  0.151
Synthetic Accessibility Score:  4.386
Fsp3:  0.593
Lipinski Rule-of-5:  Accepted
Pfizer Rule:  Rejected
GSK Rule:  Rejected
BMS Rule:  1
Golden Triangle Rule:  Rejected
Chelating Alert:  0
PAINS Alert:  0

ADMET Properties (ADMETlab2.0)

ADMET: Absorption

Caco-2 Permeability:  -4.869
MDCK Permeability:  3.0007220630068332e-05
Pgp-inhibitor:  0.593
Pgp-substrate:  0.012
Human Intestinal Absorption (HIA):  0.489
20% Bioavailability (F20%):  0.201
30% Bioavailability (F30%):  0.948

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.972
Plasma Protein Binding (PPB):  83.60480499267578%
Volume Distribution (VD):  0.818
Pgp-substrate:  9.119297981262207%

ADMET: Metabolism

CYP1A2-inhibitor:  0.317
CYP1A2-substrate:  0.64
CYP2C19-inhibitor:  0.964
CYP2C19-substrate:  0.878
CYP2C9-inhibitor:  0.888
CYP2C9-substrate:  0.225
CYP2D6-inhibitor:  0.89
CYP2D6-substrate:  0.534
CYP3A4-inhibitor:  0.953
CYP3A4-substrate:  0.776

ADMET: Excretion

Clearance (CL):  4.813
Half-life (T1/2):  0.629

ADMET: Toxicity

hERG Blockers:  0.068
Human Hepatotoxicity (H-HT):  0.967
Drug-inuced Liver Injury (DILI):  0.864
AMES Toxicity:  0.014
Rat Oral Acute Toxicity:  0.026
Maximum Recommended Daily Dose:  0.125
Skin Sensitization:  0.685
Carcinogencity:  0.615
Eye Corrosion:  0.003
Eye Irritation:  0.008
Respiratory Toxicity:  0.884

Download Data

Data Type Select
General Info & Identifiers & Properties  
Structure MOL file  
Source Organisms  
Biological Activities  
Similar NPs/Drugs  

  Natural Product: NPC478253

Natural Product ID:  NPC478253
Common Name*:   Biakamide D
IUPAC Name:   (E,4R,6S,9Z)-9-(chloromethylidene)-12-[[(E)-3-methoxybut-2-enoyl]-methylamino]-N,2,4,6-tetramethyl-N-(1,3-thiazol-2-ylmethyl)dodec-2-enamide
Synonyms:  
Standard InCHIKey:  XFUBJKQWCJERLE-HMDSDEAVSA-N
Standard InCHI:  InChI=1S/C27H42ClN3O3S/c1-20(10-11-24(18-28)9-8-13-30(5)26(32)17-23(4)34-7)15-21(2)16-22(3)27(33)31(6)19-25-29-12-14-35-25/h12,14,16-18,20-21H,8-11,13,15,19H2,1-7H3/b22-16+,23-17+,24-18+/t20-,21+/m0/s1
SMILES:  C[C@@H](CC/C(=C/Cl)/CCCN(C)C(=O)/C=C(\C)/OC)C[C@@H](C)/C=C(\C)/C(=O)N(C)CC1=NC=CS1
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   n.a.
PubChem CID:   122377834
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000012] Lipids and lipid-like molecules
      • [CHEMONTID:0000259] Prenol lipids
        • [CHEMONTID:0001549] Monoterpenoids
          • [CHEMONTID:0000051] Aromatic monoterpenoids

*Note: the InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
**Note: the Chemical Classification was calculated by NPClassifier Version 1.5. Reference: PMID:34662515.

  Species Source

Organism ID Organism Name Taxonomy Level Family SuperKingdom Isolation Part Collection Location Collection Time Reference
NPO33692 Petrosaspongia sp. Species Thorectidae Eukaryota n.a. Biak, Indonesia 2005 PMID[28090774]

☑ 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 NP ID 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

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference

☑ Note for Activity Records:
☉ The quantitative biological activities were primarily integrated from ChEMBL (Version-30) database and were also directly collected from PubMed literature. PubMed PMID was provided as the reference link for each activity record.

  Chemically structural similarity: I. Similar Active Natural Products in NPASS

Top-200 similar NPs were calculated against the active-NP-set (includes 4,3285 NPs with experimentally-derived bioactivity available in NPASS)

Similarity level is defined by Tanimoto coefficient (Tc) between two molecules. Tc lies between [0, 1] where '1' indicates the highest similarity. What is Tanimoto coefficient

●  The left chart: Distribution of similarity level between NPC478253 and all remaining natural products in the NPASS database.
●  The right table: Most similar natural products (Tc>=0.56 or Top200).

Similarity Score Similarity Level Natural Product ID
1.0 High Similarity NPC478254
0.9037 High Similarity NPC478252
0.9037 High Similarity NPC478251
0.758 Intermediate Similarity NPC475920
0.695 Remote Similarity NPC145047
0.695 Remote Similarity NPC86490
0.6831 Remote Similarity NPC137705
0.6828 Remote Similarity NPC275393
0.6761 Remote Similarity NPC278902
0.6494 Remote Similarity NPC161143
0.631 Remote Similarity NPC75498
0.6277 Remote Similarity NPC257511
0.623 Remote Similarity NPC239660
0.623 Remote Similarity NPC106235
0.5844 Remote Similarity NPC475604
0.5827 Remote Similarity NPC261708
0.5805 Remote Similarity NPC473886
0.5793 Remote Similarity NPC475390
0.5752 Remote Similarity NPC475568
0.5749 Remote Similarity NPC119481
0.5689 Remote Similarity NPC473398
0.5607 Remote Similarity NPC315252

  Chemically structural similarity: II. Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC478253 and all drugs/candidates.
●  The right table: Most similar clinical/approved drugs (Tc>=0.56 or Top200).

Similarity Score Similarity Level Drug ID Developmental Stage
0.623 Remote Similarity NPD8339 Clinical (unspecified phase)
0.5645 Remote Similarity NPD6632 Clinical (unspecified phase)

  Bioactivity similarity: Similar Natural Products in NPASS

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