Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.


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 use our state-of-the-art dedicated workflow for designing focused 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
Q14974

UPID:
IMB1_HUMAN

ALTERNATIVE NAMES:
Importin-90; Karyopherin subunit beta-1; Nuclear factor p97; Pore targeting complex 97 kDa subunit

ALTERNATIVE UPACC:
Q14974; B7ZAV6; D3DTT3; Q14637; Q53XN2; Q96J27

BACKGROUND:
Importin subunit beta-1, identified by the accession number Q14974, is pivotal in mediating nuclear import, either independently or through interaction with importin-alpha. It facilitates the docking of importin/substrate complexes to the nuclear pore complex, enabling their translocation into the nucleus. This protein is instrumental in the nuclear import of key molecules such as ribosomal proteins and histones, and plays a significant role in the life cycle of HIV-1 by importing the HIV-1 Rev protein.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Importin subunit beta-1 could open doors to potential therapeutic strategies.

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.