Povzetek

The KV10.1 voltage-gated potassium channel is highly expressed in 70% of tumors, and thus represents a promising target for anticancer drug discovery. However, only a few ligands are known to inhibit KV10.1, and almost all also inhibit the very similar cardiac hERG channel, which can lead to undesirable side-effects. In the absence of the structure of the KV10.1%inhibitor complex, there remains the need for new strategies to identify selective KV10.1 inhibitors and to understand the binding modes of the known KV10.1 inhibitors. To investigate these binding modes in the central cavity of KV10.1, a unique approach was used that allows derivation and analysis of ligand-protein interactions from molecular dynamics trajectories through pharmacophore modeling. The final molecular dynamics-derived structure-based pharmacophore model for the simulated KV10.1-ligand complexes describes the necessary pharmacophore features for KV10.1 inhibition and is highly similar to the previously reported ligand-based hERG pharmacophore model used to explain the nonselectivity of KV10.1 pore blockers. Moreover, analysis of the molecular dynamics trajectories revealed disruption of the Pi Pi network of aromatic residues F359, Y464, and F468 of KV10.1, which has been reported to be important for binding of various ligands for both KV10.1 and hERG channels. These data indicate that targeting the KV10.1 channel pore is also likely to result in undesired hERG inhibition, and other potential binding sites should be explored to develop true KV10.1-selective inhibitors as new anticancer agents.

Ključne besede

zaviralci kalijevih kanalčkov;molekularna dinamika;farmakofor;cancer;Eag1;hERG;KV10.1 inhibitors;molecular dynamics;pharmacophore;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UL FFA - Fakulteta za farmacijo
UDK: 615.4:54:616-006
COBISS: 73744899 Povezava se bo odprla v novem oknu
ISSN: 1422-0067
Št. ogledov: 132
Št. prenosov: 50
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Slovenski jezik
Sekundarne ključne besede: Rak (medicina);Farmacevtska kemija;
Vrsta dela (COBISS): Članek v reviji
Strani: str. 1-24
Letnik: ǂVol. ǂ22
Zvezek: ǂno. ǂ16
Čas izdaje: 2021
DOI: 10.3390/ijms22168999
ID: 14976275