Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


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


 

Fig. 1. The screening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.


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
Receptor.AI
 
UPACC
Q13822

UPID:
ENPP2_HUMAN

ALTERNATIVE NAMES:
Autotaxin; Extracellular lysophospholipase D

ALTERNATIVE UPACC:
Q13822; A8UHA1; E9PHP7; Q13827; Q14555; Q15117; Q9UCQ8; Q9UCR0; Q9UCR1; Q9UCR2; Q9UCR3; Q9UCR4

BACKGROUND:
The protein known as Ectonucleotide pyrophosphatase/phosphodiesterase family member 2, with alternative names Autotaxin and Extracellular lysophospholipase D, is crucial for producing lysophosphatidic acid (LPA) from lysophospholipids. It acts on various substrates, including lysophosphatidylcholine and sphingosylphosphorylcholine, influencing cell motility, angiogenesis, and neurite outgrowth. Its role extends to stimulating smooth muscle cell migration, influencing melanoma cell motility, and possibly playing a part in parturition and adipose tissue development. The enzyme's involvement in tumor cell motility and LPA production highlights its importance in physiological and pathological processes.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Ectonucleotide pyrophosphatase/phosphodiesterase family member 2 offers promising avenues for developing novel therapeutic approaches, especially in addressing challenges in oncology, regenerative medicine, and wound healing processes.

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.