NPASS Compound

Structure

NPC249533 OpenBabel06302216132D 32 35 0 0 1 0 0 0 0 0999 V2000 0.8500 -7.3298 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 0.0037 -6.8415 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 0.0035 -5.8645 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 0.8495 -5.3758 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 0.8492 -4.3987 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 1.6952 -3.9100 0.0000 C 0 0 1 0 0 0 0 0 0 0 0 0 2.5414 -4.3983 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 1.6949 -2.9330 0.0000 C 0 0 1 0 0 0 0 0 0 0 0 0 2.5406 -2.4437 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 2.5403 -1.4663 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 0.8474 -1.4668 0.0000 C 0 0 1 0 0 0 0 0 0 0 0 0 0.0003 -0.9780 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 -0.8466 -1.4673 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 -0.8463 -2.4447 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 0.0008 -2.9335 0.0000 C 0 0 2 0 0 0 0 0 0 0 0 0 0.8477 -2.4442 0.0000 C 0 0 2 0 0 0 0 0 0 0 0 0 0.8480 -3.4456 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 0.0011 -3.9348 0.0000 O 0 0 0 0 0 0 0 0 0 0 0 0 -1.6938 -0.9785 0.0000 C 0 0 1 0 0 0 0 0 0 0 0 0 -2.5400 -1.4677 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 -3.3866 -0.9790 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 -3.3869 -0.0010 0.0000 C 0 0 1 0 0 0 0 0 0 0 0 0 -2.5406 0.4883 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 -1.6940 -0.0005 0.0000 C 0 0 2 0 0 0 0 0 0 0 0 0 -0.8472 0.4888 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 -0.0000 -0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 -4.2543 0.4993 0.0000 O 0 0 0 0 0 0 0 0 0 0 0 0 -1.6935 -1.9560 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 -2.4197 -2.6103 0.0000 O 0 0 0 0 0 0 0 0 0 0 0 0 -0.8428 -5.3762 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 -0.8431 -4.3992 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 -1.6888 -5.8650 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 1 2 1 0 0 0 0 2 3 2 0 0 0 0 3 4 1 0 0 0 0 3 30 1 0 0 0 0 4 5 1 0 0 0 0 5 6 1 0 0 0 0 6 7 1 6 0 0 0 8 6 1 6 0 0 0 8 9 1 0 0 0 0 8 16 1 0 0 0 0 9 10 1 0 0 0 0 11 10 1 6 0 0 0 11 12 1 0 0 0 0 11 16 1 0 0 0 0 12 26 1 0 0 0 0 12 13 2 0 0 0 0 13 14 1 0 0 0 0 13 19 1 0 0 0 0 14 15 1 0 0 0 0 15 16 1 0 0 0 0 15 18 1 6 0 0 0 16 17 1 6 0 0 0 19 24 1 0 0 0 0 19 20 1 0 0 0 0 19 28 1 6 0 0 0 20 21 1 0 0 0 0 21 22 1 0 0 0 0 22 23 1 0 0 0 0 22 27 1 6 0 0 0 24 23 1 6 0 0 0 24 25 1 0 0 0 0 25 26 1 0 0 0 0 28 29 1 0 0 0 0 30 31 1 0 0 0 0 30 32 1 0 0 0 0 M END $$$$

Physi-Chem Properties

Molecular Weight:	444.36
Volume:	497.012
LogP:	4.947
LogD:	4.822
LogS:	-5.073
# Rotatable Bonds:	6
TPSA:	60.69
# H-Bond Aceptor:	3
# H-Bond Donor:	3
# Rings:	4
# Heavy Atoms:	3

MedChem Properties

QED Drug-Likeness Score:	0.438
Synthetic Accessibility Score:	5.112
Fsp3:	0.862
Lipinski Rule-of-5:	Accepted
Pfizer Rule:	Rejected
GSK Rule:	Rejected
BMS Rule:	0
Golden Triangle Rule:	Accepted
Chelating Alert:	0
PAINS Alert:	0

ADMET Properties (ADMETlab2.0)

ADMET: Absorption

Caco-2 Permeability:	-4.718
MDCK Permeability:	2.32647689699661e-05
Pgp-inhibitor:	0.891
Pgp-substrate:	0.992
Human Intestinal Absorption (HIA):	0.006
20% Bioavailability (F20%):	0.924
30% Bioavailability (F30%):	0.382

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):	0.321
Plasma Protein Binding (PPB):	92.63982391357422%
Volume Distribution (VD):	1.104
Pgp-substrate:	1.4181610345840454%

ADMET: Metabolism

CYP1A2-inhibitor:	0.059
CYP1A2-substrate:	0.202
CYP2C19-inhibitor:	0.054
CYP2C19-substrate:	0.861
CYP2C9-inhibitor:	0.188
CYP2C9-substrate:	0.129
CYP2D6-inhibitor:	0.01
CYP2D6-substrate:	0.302
CYP3A4-inhibitor:	0.809
CYP3A4-substrate:	0.516

ADMET: Excretion

Clearance (CL):	8.772
Half-life (T1/2):	0.142

ADMET: Toxicity

hERG Blockers:	0.133
Human Hepatotoxicity (H-HT):	0.12
Drug-inuced Liver Injury (DILI):	0.039
AMES Toxicity:	0.012
Rat Oral Acute Toxicity:	0.144
Maximum Recommended Daily Dose:	0.978
Skin Sensitization:	0.455
Carcinogencity:	0.018
Eye Corrosion:	0.004
Eye Irritation:	0.108
Respiratory Toxicity:	0.943

Download Data

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

Natural Product: NPC249533

Natural Product ID:	NPC249533
*Common Name:**	ZIYYFTNCOZRPFJ-VRYCQNCBSA-N
IUPAC Name:	n.a.
Synonyms:
Standard InCHIKey:	ZIYYFTNCOZRPFJ-VRYCQNCBSA-N
Standard InCHI:	InChI=1S/C29H48O3/c1-6-20(18(2)3)8-7-19(4)24-11-12-25-23-10-9-21-15-22(31)13-14-29(21,17-30)26(23)16-27(32)28(24,25)5/h6,18-19,21-22,24-25,27,30-32H,7-17H2,1-5H3/b20-6+/t19-,21+,22+,24-,25+,27-,28-,29-/m1/s1
SMILES:	C/C=C(CC[C@@H](C)[C@H]1CC[C@H]2C3=C(C[C@H]([C@]12C)O)[C@]1(CC[C@@H](C[C@@H]1CC3)O)CO)/C(C)C
Synthetic Gene Cluster:	n.a.
ChEMBL Identifier:	n.a.
PubChem CID:	101670378
Chemical Classification:**	CHEMONTID:0000000 [Organic compounds] [CHEMONTID:0000012] Lipids and lipid-like molecules [CHEMONTID:0000258] Steroids and steroid derivatives [CHEMONTID:0002031] Stigmastanes and derivatives

*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
NPO14781	Anthocleista vogelii	Species	Gentianaceae	Eukaryota	n.a.	n.a.	n.a.	DOI[10.1016/S0031-9422(00)97499-5]
NPO9675	Aphanoascus fulvescens	Species	Onygenaceae	Eukaryota	n.a.	n.a.	n.a.	PMID[10908107]
NPO6931	Senna multiglandulosa	Species	Fabaceae	Eukaryota	n.a.	n.a.	n.a.	Database[UNPD]
NPO9675	Aphanoascus fulvescens	Species	Onygenaceae	Eukaryota	n.a.	n.a.	n.a.	Database[UNPD]
NPO24165	Litophyton arboreum	Species	Nephtheidae	Eukaryota	n.a.	n.a.	n.a.	Database[UNPD]
NPO6694	Picconia excelsa	Species	Oleaceae	Eukaryota	n.a.	n.a.	n.a.	Database[UNPD]
NPO14781	Anthocleista vogelii	Species	Gentianaceae	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	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 NPC249533 and all remaining natural products in the NPASS database.
● The right table: Most similar natural products (Tc>=0.56 or Top200).

range	Tanimoto Coefficient
0-0.1	146
0.1-0.2	1272
0.2-0.3	6164
0.3-0.4	16206
0.4-0.5	7678
0.5-0.6	6520
0.6-0.7	3567
0.7-0.8	934
0.8-0.85	140
0.85-0.9	58
0.9-0.95	12
0.95-1	0

Similarity Score	Similarity Level	Natural Product ID

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 NPC249533 and all drugs/candidates.
● The right table: Most similar clinical/approved drugs (Tc>=0.56 or Top200).

range	Tanimoto Coefficient
0-0.1	137
0.1-0.2	1663
0.2-0.3	4398
0.3-0.4	2107
0.4-0.5	426
0.5-0.6	204
0.6-0.7	162
0.7-0.8	34
0.8-0.85	17
0.85-0.9	2
0.9-0.95	0
0.95-1	0

Similarity Score	Similarity Level	Drug ID	Developmental Stage

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