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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


We employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening 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 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
P12273

UPID:
PIP_HUMAN

ALTERNATIVE NAMES:
Gross cystic disease fluid protein 15; Prolactin-induced protein; Secretory actin-binding protein; gp17

ALTERNATIVE UPACC:
P12273; A0A963; A0A9C3; A0A9F3; A4D2I1

BACKGROUND:
The Prolactin-inducible protein, with aliases such as Gross cystic disease fluid protein 15 and gp17, is integral to the regulation of several physiological processes. This protein's diverse functions underscore its importance in cellular mechanisms and its potential as a biomarker for various conditions.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Prolactin-inducible protein holds promise for the development of novel therapeutic approaches. The protein's significant role in the body highlights its potential as a key target in the design of new drugs, potentially leading to breakthroughs in treatment modalities.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.