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 focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

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

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.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

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

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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