BETABiohacksAI is a research tool for informational purposes only. All outputs are computational hypothesis candidates — not confirmed mechanisms, not medical advice, and not a substitute for professional medical judgment. Independent experimental validation is always required.
BiohacksAI is an evolving scientific literature platform. New compounds and evidence are indexed continuously.
B
MOLECULAR TARGETUniProt: Q9HAT2

SIAE

sialic acid acetylesterase

29 compounds · BiohacksAI corpus v20260307-01

29
compounds
Compounds
29
Gene Symbol
SIAE
NCBI Gene
54414

Looking for compounds that interact with SIAE?

View all 29 compounds →
About SIAE

SIAE (sialic acid acetylesterase) is a biological target studied in biomedical research. The BiohacksAI corpus identifies 29 compounds with documented interactions with this target, based on BindingDB assay data and PubMed literature.

View SIAE on UniProt →
Compounds Targeting SIAE (29)
300
studies
1.10
confidence
300
studies
0.69
confidence
3
Myricetinflavonoids
0
studies
0.69
confidence
300
studies
0.69
confidence
208
studies
0.69
confidence
297
studies
0.69
confidence
7
Aconitum Carmichaelii
0.50
confidence
8
Alisma Plantago
0.50
confidence
9
Aloe Vera
0.50
confidence
10
Apis Mellifera
0.50
confidence
11
Artemisia Annua
0.50
confidence
12
Atractylodes Macrocephala
0.50
confidence
13
Carthamus Tinctorius
0.50
confidence
14
Citrus Reticulata
0.50
confidence
15
Coix Lacryma
0.50
confidence
16
Commiphora Myrrha
0.50
confidence
17
Ephedra Sinica
0.50
confidence
18
Glycine Max
0.50
confidence
500
studies
0.50
confidence
20
Lonicera Japonica
0.50
confidence
21
Morus Alba
0.50
confidence
0
studies
0.50
confidence
300
studies
0.50
confidence
24
Perilla Frutescens
0.50
confidence
25
Prunella Vulgaris
0.50
confidence
500
studies
0.50
confidence
27
Tussilago Farfara
0.50
confidence
28
Vigna Radiata
0.50
confidence
29
Ziziphus Jujuba
0.50
confidence
Top 29 compounds by confidence score. Derived from BindingDB assay data.
Data Source
Corpusv20260307-01
SourceBindingDB · ChEMBL · PubMed

All data is computationally derived from published research. Not medical advice. Independent validation required.