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.


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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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
P13497

UPID:
BMP1_HUMAN

ALTERNATIVE NAMES:
Mammalian tolloid protein; Procollagen C-proteinase

ALTERNATIVE UPACC:
P13497; A8K6F5; B2RN46; D3DSR0; Q13292; Q13872; Q14874; Q99421; Q99422; Q99423; Q9UL38

BACKGROUND:
The protein BMP1, with alternative names Mammalian tolloid protein and Procollagen C-proteinase, plays a significant role in the formation of the extracellular matrix, impacting developmental and physiological processes such as bone and cartilage formation, and wound healing. It activates key enzymes and structural proteins for tissue integrity.

THERAPEUTIC SIGNIFICANCE:
Given BMP1's critical function in diseases like Osteogenesis imperfecta 13, which leads to severe bone deformity and fractures, exploring its mechanisms offers a promising avenue for developing targeted therapies that could revolutionize treatment paradigms for skeletal diseases.

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