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.


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.


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.


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


 

Fig. 1. The screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.


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
A4D2B0

UPID:
MBLC1_HUMAN

ALTERNATIVE NAMES:
Endoribonuclease MBLAC1

ALTERNATIVE UPACC:
A4D2B0; Q8N5X8

BACKGROUND:
The Metallo-beta-lactamase domain-containing protein 1, known alternatively as Endoribonuclease MBLAC1, is integral to histone pre-mRNA processing during the S-phase of the cell cycle. By catalyzing the hydrolysis of histone-coding pre-mRNA 3'-end, MBLAC1 ensures the proper progression through the S-phase. It achieves specificity by cleaving at sequences downstream of the stem-loop, a mechanism vital for the cell's genetic material's proper packaging and function.

THERAPEUTIC SIGNIFICANCE:
The exploration of Metallo-beta-lactamase domain-containing protein 1's function offers a promising avenue for developing novel therapeutic approaches. Given its crucial role in cell cycle regulation and histone pre-mRNA processing, targeting MBLAC1 could provide insights into treatments for conditions characterized by abnormal cell cycle activity.

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