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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed 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.


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
Q9C093

UPID:
SPEF2_HUMAN

ALTERNATIVE NAMES:
Protein KPL2

ALTERNATIVE UPACC:
Q9C093; Q2TAC9; Q96LL6; Q9H5C7; Q9H5Q7

BACKGROUND:
Protein KPL2, known for its critical function in sperm flagella development, is indispensable for male fertility. It ensures proper sperm head morphology and manchette development. Protein KPL2's role extends to facilitating the localization of IFT20 to the manchette, highlighting its importance in protein transport during spermatogenesis. Its significance is also noted in bone growth, where it aids in osteoblast differentiation.

THERAPEUTIC SIGNIFICANCE:
Linked to the infertility disorder Spermatogenic failure 43, Protein KPL2's dysfunction results in asthenospermia due to flagella defects. Exploring the functions of Protein KPL2 offers promising avenues for developing treatments aimed at overcoming infertility challenges associated with defective sperm motility and structure.

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.