AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Neurogenic differentiation factor 2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 our associate Reaxense.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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

 Fig. 1. The sreening 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 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

Q15784

UPID:

NDF2_HUMAN

Alternative names:

Class A basic helix-loop-helix protein 1; NeuroD-related factor

Alternative UPACC:

Q15784; Q8TBI7; Q9UQC6

Background:

Neurogenic differentiation factor 2, also known as NeuroD-related factor, plays a pivotal role in neuronal determination and differentiation. It acts as a transcriptional regulator, mediating calcium-dependent transcription activation and is crucial for the repression of neuronal differentiation genetic programs. This protein is involved in the development of various brain regions, including the cerebellum, hippocampus, and the hypothalamic-pituitary axis.

Therapeutic significance:

Given its involvement in Developmental and epileptic encephalopathy 72, a severe early-onset epilepsy with neurodevelopmental impairment, understanding the role of Neurogenic differentiation factor 2 could lead to novel therapeutic strategies targeting this and potentially other neurodevelopmental disorders.

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