AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Endogenous retrovirus group K member 11 Pol protein

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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. Our partner Reaxense helps in synthesizing and delivering these compounds.

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

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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

Reaxense

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, alternatively known as HERV-K_3q27.2 provirus ancestral Pol protein, plays a crucial role in the early stages of viral infection. It is responsible for converting viral RNA into double-stranded DNA, a process facilitated by its reverse transcriptase and RNase H domain. This domain not only degrades the RNA template but also removes the RNA primer from the RNA/DNA hybrid, paving the way for the integration of viral DNA into the host cell chromosome.

Therapeutic significance:

Understanding the role of Endogenous retrovirus group K member 11 Pol protein could open doors to potential therapeutic strategies. Its pivotal function in viral DNA integration highlights its significance in viral replication and pathogenesis, offering a promising target for antiviral drug development.

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