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.


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.


Our high-tech, dedicated method is applied to construct targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive 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
P49281

UPID:
NRAM2_HUMAN

ALTERNATIVE NAMES:
Divalent cation transporter 1; Divalent metal transporter 1; Solute carrier family 11 member 2

ALTERNATIVE UPACC:
P49281; B3KT08; B4DK84; F5H741; O43288; O60932; O94801; Q498Z5; Q8IUD7; Q96J35

BACKGROUND:
The protein Natural resistance-associated macrophage protein 2, known alternatively as Divalent cation transporter 1 and Solute carrier family 11 member 2, is essential for iron and manganese transport. Its ability to selectively transport divalent metal cations underlines its critical function in maintaining iron homeostasis, influencing mitochondrial function, heme synthesis, and cellular antioxidant mechanisms.

THERAPEUTIC SIGNIFICANCE:
Given its crucial role in iron metabolism and association with Anemia, hypochromic microcytic, with iron overload 1, targeting NRAMP2 could offer innovative therapeutic avenues. Exploring NRAMP2's function further could lead to groundbreaking treatments for iron-related disorders, enhancing patient outcomes.

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