AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Nuclear receptor ROR-alpha

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner 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 employ our advanced, specialised process to create targeted libraries for receptors.

 Fig. 1. The sreening workflow of Receptor.AI

It includes extensive molecular simulations of the receptor in its native membrane environment and the ensemble virtual screening accounting for its conformational mobility. In the case of dimeric or oligomeric receptors, the whole functional complex is modelled, and the tentative binding pockets are determined on and between the subunits to cover the whole 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

Reaxense

upacc

P35398

UPID:

RORA_HUMAN

Alternative names:

Nuclear receptor RZR-alpha; Nuclear receptor subfamily 1 group F member 1; RAR-related orphan receptor A; Retinoid-related orphan receptor-alpha

Alternative UPACC:

P35398; P35397; P35399; P45445; Q495X4; Q96H83

Background:

Nuclear receptor ROR-alpha, also known as RAR-related orphan receptor A, plays a pivotal role in various biological processes including embryonic development, cellular differentiation, and metabolism regulation. It binds DNA to modulate the transcription of genes critical for circadian rhythm, lipid metabolism, and immune response.

Therapeutic significance:

The protein's involvement in Intellectual developmental disorder with or without epilepsy or cerebellar ataxia highlights its potential as a target for therapeutic intervention. Understanding the role of Nuclear receptor ROR-alpha could open doors to novel treatments for neurodevelopmental disorders.

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