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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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.


 

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 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
O95297

UPID:
MPZL1_HUMAN

ALTERNATIVE NAMES:
Protein zero-related

ALTERNATIVE UPACC:
O95297; B2REB9; B2REC0; Q5R332; Q8IX11; Q9BWZ3; Q9NYK4; Q9UL20

BACKGROUND:
The Myelin protein zero-like protein 1, known as Protein zero-related, is integral to signal transduction processes at the cell surface. It is instrumental in recruiting PTPN11/SHP-2 to the cell membrane and serves as a potential substrate for PTPN11/SHP-2. As a principal receptor for concanavalin-A (ConA), it is involved in the cellular signaling pathways triggered by ConA, likely including the activation of Src family tyrosine-protein kinases. Isoform 1 of this protein is associated with the regulation of integrin-mediated cell motility, unlike isoforms 2 and 3, with isoform 3 specifically blocking tyrosine phosphorylation of MPZL1 induced by ConA.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Myelin protein zero-like protein 1 could open doors to potential therapeutic strategies.

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