Focused On-demand Library for Endogenous retrovirus group K member 6 Pol protein

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

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.

Our library stands out due to several important features:

The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9BXR3

UPID:

POK6_HUMAN

Alternative names:

HERV-K(C7) Pol protein; HERV-K(HML-2.HOM) Pol protein; HERV-K108 Pol protein; HERV-K_7p22.1 provirus ancestral Pol protein

Alternative UPACC:

Q9BXR3; Q6KH04; Q9BXR4; Q9UKH5; Q9UP31; Q9WIK9; Q9WJR4

Background:

The Endogenous retrovirus group K member 6 Pol protein, with alternative names such as HERV-K(C7) Pol protein and HERV-K108 Pol protein, plays a crucial role in the early post-infection stage. It converts viral RNA into double-stranded DNA, with its RNase H domain degrading the RNA template and removing the RNA primer. This protein is also involved in the integration of viral DNA into the host cell chromosome, a process facilitated by the integrase.

Therapeutic significance:

Understanding the role of Endogenous retrovirus group K member 6 Pol protein could open doors to potential therapeutic strategies. Its involvement in the early stages of viral infection and integration into the host genome makes it a compelling target for antiviral research.