Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


We utilise our cutting-edge, exclusive workflow to develop focused libraries for ion channels.


 

Fig. 1. The screening workflow of Receptor.AI

This process includes comprehensive molecular simulations of the ion channel in its native membrane environment, depicting its open, closed, and inactivated states, and ensemble virtual screening that accounts for conformational mobility in each state. Tentative binding pockets are investigated inside the pore, at the gating region, and in allosteric sites to cover the full spectrum of possible mechanisms of action.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
P22459

UPID:
KCNA4_HUMAN

ALTERNATIVE NAMES:
HPCN2; Voltage-gated K(+) channel HuKII; Voltage-gated potassium channel HBK4; Voltage-gated potassium channel HK1; Voltage-gated potassium channel subunit Kv1.4

ALTERNATIVE UPACC:
P22459

BACKGROUND:
The protein Kv1.4, also known as Potassium voltage-gated channel subfamily A member 4, plays a vital role in the transmembrane transport of potassium ions. It is essential for maintaining the electrochemical gradient across excitable membranes, thereby regulating neuronal excitability and muscle function. Kv1.4 can form channels with varying properties depending on its assembly with other subunits, which allows for a broad range of physiological responses.

THERAPEUTIC SIGNIFICANCE:
Given its critical function in neurological processes, Kv1.4 is implicated in a syndrome involving microcephaly, cognitive impairment, and dystonia. The exploration of Kv1.4's mechanisms offers promising avenues for the development of novel interventions aimed at ameliorating symptoms and potentially reversing the progression of related neurological conditions.

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