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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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
Q6ZNC8

UPID:
MBOA1_HUMAN

ALTERNATIVE NAMES:
1-acylglycerophosphocholine O-acyltransferase; 1-acylglycerophosphoethanolamine O-acyltransferase; 1-acylglycerophosphoserine O-acyltransferase MBOAT1; Lysophosphatidylserine acyltransferase; Membrane-bound O-acyltransferase domain-containing protein 1

ALTERNATIVE UPACC:
Q6ZNC8; A9EDQ5; B4DL59; B4E3J4; Q86XC2; Q8N9R5

BACKGROUND:
Membrane-bound O-acyltransferase domain-containing protein 1, also recognized as Lysophospholipid acyltransferase 1, is integral to the Lands cycle, facilitating the reacylation step crucial for maintaining phospholipid integrity. It exhibits specificity for substrates like lysophosphatidylserine and lysophosphatidylethanolamine, with a marked preference for oleoyl-CoA. This specificity underlines its critical function in phospholipid biosynthesis and cellular membrane composition.

THERAPEUTIC SIGNIFICANCE:
The exploration of Lysophospholipid acyltransferase 1's function in cellular processes, particularly its potential role in promoting neurite outgrowth, underscores its significance in neurobiology. This understanding could pave the way for innovative therapeutic approaches targeting neural repair and regeneration.

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