Focused On-demand Libraries - Receptor.AI 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.


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.


Our top-notch dedicated system is used to design specialised 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.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
Q9UQG0

UPID:
POK11_HUMAN

ALTERNATIVE NAMES:
HERV-K_3q27.2 provirus ancestral Pol protein

ALTERNATIVE UPACC:
Q9UQG0; Q6KH06; Q86YP3

BACKGROUND:
The Endogenous retrovirus group K member 11 Pol protein, known for its alternative name HERV-K_3q27.2 provirus ancestral Pol protein, is integral to the post-infection phase of viruses. It harbors a reverse transcriptase that transforms viral RNA into double-stranded DNA, with its RNase H domain performing dual functions: degrading the RNA template and removing the RNA primer. This is a critical step before the viral DNA's integration into the host genome, facilitated by the integrase enzyme.

THERAPEUTIC SIGNIFICANCE:
The exploration of Endogenous retrovirus group K member 11 Pol protein's function offers a gateway to innovative therapeutic avenues. Given its essential role in the lifecycle of viruses, targeting this protein could lead to groundbreaking advancements in the treatment of viral infections, underscoring the therapeutic potential of this protein.

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