Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of 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
P47992

UPID:
XCL1_HUMAN

ALTERNATIVE NAMES:
ATAC; C motif chemokine 1; Cytokine SCM-1; Lymphotaxin; SCM-1-alpha; Small-inducible cytokine C1; XC chemokine ligand 1

ALTERNATIVE UPACC:
P47992; Q52MA8

BACKGROUND:
The protein Lymphotactin, identified by its unique identifiers such as SCM-1-alpha and Small-inducible cytokine C1, is integral to the immune system's function. It is distinguished by its selective chemotactic activity towards lymphocytes, excluding monocytes and neutrophils. This specificity underlines its role in the targeted movement of lymphocytes within the body. Furthermore, Lymphotactin contributes significantly to the regulatory T cell development within the thymus, a process vital for the maintenance of immune self-tolerance and the prevention of autoimmune diseases.

THERAPEUTIC SIGNIFICANCE:
The exploration of Lymphotactin's functions offers promising avenues for therapeutic intervention. Given its involvement in lymphocyte chemotaxis and the development of regulatory T cells, targeting Lymphotactin could lead to innovative treatments for autoimmune conditions and strategies to modulate the immune response more effectively.

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