Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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 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.


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
Q9Y238

UPID:
DLEC1_HUMAN

ALTERNATIVE NAMES:
Deleted in lung cancer protein 1

ALTERNATIVE UPACC:
Q9Y238; Q9NSW0; Q9NTG5

BACKGROUND:
The protein Deleted in lung and esophageal cancer protein 1, with its alternative name Deleted in lung cancer protein 1, is essential for male fertility, particularly in spermatogenesis and sperm morphology. Acting as a tumor suppressor by inhibiting cell proliferation, it underscores its critical role in maintaining cellular homeostasis and preventing uncontrolled cell growth.

THERAPEUTIC SIGNIFICANCE:
Given its association with the pathogenesis of lung and esophageal cancers through mechanisms like DLEC1 silencing, Deleted in lung and esophageal cancer protein 1 emerges as a promising target for therapeutic intervention. Exploring its function further could lead to novel strategies for combating these cancers, potentially transforming the landscape of cancer therapy.

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.