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
○
BiohacksAI/Targets/AMFR/Compounds

Compounds That Target AMFR

AMFR · 60 compounds in BiohacksAI corpus

AMFR (AMFR) is a biological target with 60 documented compound interactions in the BiohacksAI corpus. The compounds listed below have been identified through computational analysis of BindingDB binding assay data and PubMed literature. Each interaction is ranked by confidence score reflecting the breadth and strength of experimental evidence. This resource supports research into AMFR modulation for therapeutic and biohacking applications.

View AMFR target page →
Most Studied Compounds for AMFR
1
Allium Sativum
500+
studies
2
Juglans Regia
500+
studies
3
Portulaca Oleracea
500+
studies
4
Centella Asiatica
499+
studies
5
Foeniculum Vulgare
499+
studies
6
Panax Ginseng
300+
studies
7
Smilax China
142+
studies
All 50 Compounds — Ranked by Evidence
1
Centella Asiatica
499+
studies
1.00
confidence
2
Foeniculum Vulgare
499+
studies
1.00
confidence
3
Glycine Max
1.00
confidence
4
Lithospermum Erythrorhizon
1.00
confidence
5
Panax Notoginseng
1.00
confidence
6
Perilla Frutescens
1.00
confidence
7
Prunella Vulgaris
1.00
confidence
8
Smilax China
142+
studies
1.00
confidence
9
Smilax Glabra
1.00
confidence
10
Achyranthes Bidentata
0.50
confidence
11
Aconitum Carmichaelii
0.50
confidence
12
Allium Fistulosum
0.50
confidence
13
Allium Sativum
500+
studies
0.50
confidence
14
Aloe Vera
0.50
confidence
15
Apis Mellifera
0.50
confidence
16
Arctium Lappa
0.50
confidence
17
Artemisia Capillaris
0.50
confidence
18
Atractylodes Macrocephala
0.50
confidence
19
Bombyx Mori
0.50
confidence
20
Bupleurum Chinense
0.50
confidence
21
Carthamus Tinctorius
0.50
confidence
22
Chaenomeles Speciosa
0.50
confidence
23
Cnidium Monnieri
0.50
confidence
24
Coix Lacryma
0.50
confidence
25
Commiphora Myrrha
0.50
confidence
26
Corydalis Yanhusuo
0.50
confidence
27
Crataegus Pinnatifida
0.50
confidence
28
Ephedra Sinica
0.50
confidence
29
Eriobotrya Japonica
0.50
confidence
30
Euryale Ferox
0.50
confidence
31
Forsythia Suspensa
0.50
confidence
32
Gentiana Macrophylla
0.50
confidence
33
Hirudo Nipponia
0.50
confidence
34
Juglans Regia
500+
studies
0.50
confidence
35
Leonurus Japonicus
0.50
confidence
36
Lilium Lancifolium
0.50
confidence
37
Litchi Chinensis
0.50
confidence
38
Lycopus Lucidus
0.50
confidence
39
Mentha Haplocalyx
0.50
confidence
40
Morus Alba
0.50
confidence
41
Mosla Chinensis
0.50
confidence
42
Nelumbo Nucifera
0.50
confidence
43
Paeonia Lactiflora
0.50
confidence
44
Panax Ginseng
300+
studies
0.50
confidence
45
Pinellia Ternata
0.50
confidence
46
Piper Nigrum
0.50
confidence
47
Polygala Tenuifolia
0.50
confidence
48
Polygonum Cuspidatum
0.50
confidence
49
Poria Cocos
0.50
confidence
50
Portulaca Oleracea
500+
studies
0.50
confidence

The compounds above were identified through computational analysis of BindingDB binding assay data and PubMed literature for AMFR (AMFR). Confidence scores reflect the strength and breadth of experimental evidence.

Explore related resources: AMFR target overview · All biological targets · Biological pathways

Data from BindingDB and PubMed. For research purposes only. Not medical advice.