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.


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


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


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across 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
Receptor.AI
 
UPACC
Q86YH6

UPID:
DLP1_HUMAN

ALTERNATIVE NAMES:
All-trans-decaprenyl-diphosphate synthase subunit 2; Candidate tumor suppressor protein; Decaprenyl pyrophosphate synthase subunit 2; Decaprenyl-diphosphate synthase subunit 2; Solanesyl-diphosphate synthase subunit 2

ALTERNATIVE UPACC:
Q86YH6; Q33DR4; Q4G158; Q5VU38; Q5VU39; Q9NR58

BACKGROUND:
The enzyme All trans-polyprenyl-diphosphate synthase PDSS2, with alternative names such as Decaprenyl pyrophosphate synthase subunit 2, is pivotal in the synthesis of ubiquinone-9 (Q9) and ubiquinone-10 (Q10). These molecules are crucial for mitochondrial energy production. PDSS2's activity influences the length of the isoprenoid side chain in CoQ10, directly affecting mitochondrial function and cellular energy levels.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in CoQ10 biosynthesis, PDSS2's dysfunction is associated with Coenzyme Q10 deficiency, primary, 3, leading to severe neurological and renal symptoms. Targeting PDSS2 could offer new avenues for treating mitochondrial disorders, underscoring the enzyme's therapeutic importance.

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