Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We employ our advanced, specialised process to create targeted 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 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
Q9NUN5

UPID:
LMBD1_HUMAN

ALTERNATIVE NAMES:
HDAg-L-interacting protein NESI; LMBR1 domain-containing protein 1; Nuclear export signal-interacting protein

ALTERNATIVE UPACC:
Q9NUN5; A8K204; E1P531; Q5VUN6; Q86Y70; Q96FW4; Q9BY56; Q9NZD6

BACKGROUND:
The Lysosomal cobalamin transport escort protein LMBD1, known for its alternative names such as Nuclear export signal-interacting protein, is pivotal in vitamin B12 trafficking. It ensures the proper export of cobalamin from lysosomes, enabling its transformation into essential cofactors. LMBD1's role extends to mediating the endocytosis of the insulin receptor and is crucial for gastrulation and mesoderm formation during embryogenesis. Its involvement in hepatitis delta virus assembly suggests a broader biological significance.

THERAPEUTIC SIGNIFICANCE:
Given its critical function in cobalamin metabolism and its link to Methylmalonic aciduria and homocystinuria, cblF type, LMBD1 presents a promising target for therapeutic intervention. Exploring the mechanisms of LMBD1 could lead to novel treatments for related metabolic disorders.

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