AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Progesterone-induced-blocking factor 1

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.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q8WXW3

UPID:

PIBF1_HUMAN

Alternative names:

Centrosomal protein of 90 kDa

Alternative UPACC:

Q8WXW3; O95664; Q6U9V2; Q6UG50; Q86V07; Q96SF4

Background:

Progesterone-induced-blocking factor 1, also known as Centrosomal protein of 90 kDa, is pivotal in ciliogenesis and maintaining mitotic spindle pole integrity. It facilitates the centrosomal accumulation of PCM1, aiding in primary cilia formation and centriole duplication. Its secreted form acts as a mediator of progesterone, influencing arachidonic acid metabolism and promoting a Th2 biased immune response.

Therapeutic significance:

Linked to Joubert syndrome 33, a disorder characterized by cerebellar ataxia and psychomotor delay, understanding the role of Progesterone-induced-blocking factor 1 could open doors to potential therapeutic strategies.

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