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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


Our high-tech, dedicated method is applied to construct targeted libraries for ion channels.


 

Fig. 1. The screening workflow of Receptor.AI

It includes extensive molecular simulations of the channel in its native membrane environment in open, closed and inactivated forms and the ensemble virtual screening accounting for conformational mobility in each of these states. Tentative binding pockets are considered inside the pore, in the gating region and in the allosteric locations to cover the whole spectrum of possible mechanisms of action.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q13936

UPID:
CAC1C_HUMAN

ALTERNATIVE NAMES:
Calcium channel, L type, alpha-1 polypeptide, isoform 1, cardiac muscle; Voltage-gated calcium channel subunit alpha Cav1.2

ALTERNATIVE UPACC:
Q13936; B2RUT3; E9PDJ0; Q13917; Q13918; Q13919; Q13920; Q13921; Q13922; Q13923; Q13924; Q13925; Q13926; Q13927; Q13928; Q13929; Q13930; Q13932; Q13933; Q14743; Q14744; Q15877; Q4VMI7; Q4VMI8; Q4VMI9; Q6PKM7; Q8N6C0; Q99025; Q99241; Q99875

BACKGROUND:
Cav1.2, a key component of L-type calcium channels, is crucial for heart development, blood pressure regulation, and smooth muscle contraction. Its role extends to mediating calcium influx, triggering sarcoplasmic calcium release, and facilitating excitation-contraction coupling.

THERAPEUTIC SIGNIFICANCE:
The association of Cav1.2 with diseases such as Timothy syndrome and various cardiac syndromes underscores its therapeutic potential. Exploring Cav1.2's mechanisms could unveil novel strategies for managing arrhythmias and developmental abnormalities.

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