BEAR (binding estimation after refinement) is a new virtual screening technology based on the conformational refinement of docking poses through molecular dynamics and prediction of binding free energies using accurate scoring functions. Here, the authors report the results of an extensive benchmark of the BEAR performance in identifying a smaller subset of known inhibitors seeded in a large (1.5 million) database of compounds. BEAR performance proved strikingly better if compared with standard docking screening methods. The validations performed so far showed that BEAR is a reliable tool for drug discovery. It is fast, modular, and automated, and it can be applied to virtual screenings against any biological target with known structure and any database of compounds. (Journal of Biomolecular Screening 2011:129-133)
Intracellular chloride concentration [Cl
–
]
i
is defective in several neurological disorders. In neurons,
[Cl
–
]
i
is mainly regulated by the action
of the Na
+
–K
+
–Cl
–
importer NKCC1 and the K
+
–Cl
–
exporter KCC2. Recently, we have reported the discovery of
ARN23746
as the lead candidate of a novel class of selective
inhibitors of NKCC1. Importantly,
ARN23746
is able to
rescue core symptoms of Down syndrome (DS) and autism in mouse models.
Here, we describe the discovery and extensive characterization of
this chemical class of selective NKCC1 inhibitors, with focus on
ARN23746
and other promising derivatives. In particular, we
present compound
40
(
ARN24092
) as a backup/follow-up
lead with
in vivo
efficacy in a mouse model of DS.
These results further strengthen the potential of this new class of
compounds for the treatment of core symptoms of brain disorders characterized
by the defective NKCC1/KCC2 expression ratio.
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