AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Beta-nerve growth factor

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

Our top-notch dedicated system is used to design specialised libraries for receptors.

 Fig. 1. The sreening workflow of Receptor.AI

The method involves detailed molecular simulations of the receptor in its native membrane environment, with ensemble virtual screening focusing on its conformational mobility. When dealing with dimeric or oligomeric receptors, the whole functional complex is modelled, and the tentative binding pockets on and between the subunits are established to address all possible mechanisms of action.

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

Reaxense

upacc

P01138

UPID:

NGF_HUMAN

Alternative names:

-

Alternative UPACC:

P01138; A1A4E5; Q6FHA0; Q96P60; Q9P2Q8; Q9UKL8

Background:

Beta-nerve growth factor (NGF) plays a pivotal role in the development and maintenance of the sympathetic and sensory nervous systems. It acts as an extracellular ligand for NTRK1 and NGFR receptors, initiating signaling cascades that regulate neuronal proliferation, differentiation, and survival. The precursor form of NGF, proNGF, has contrasting roles, promoting neuronal apoptosis and affecting neuronal growth cone dynamics.

Therapeutic significance:

NGF's involvement in hereditary sensory and autonomic neuropathy type 5 (HSAN5), characterized by loss of pain perception and impaired temperature sensitivity, underscores its therapeutic potential. Understanding NGF's dual roles offers insights into developing treatments for sensory and autonomic nervous system disorders.

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