AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for RNA-binding protein FUS

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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.

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.

We employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening 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 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

Reaxense

upacc

P35637

UPID:

FUS_HUMAN

Alternative names:

75 kDa DNA-pairing protein; Oncogene FUS; Oncogene TLS; POMp75; Translocated in liposarcoma protein

Alternative UPACC:

P35637; Q9H4A8

Background:

The RNA-binding protein FUS, also known as Translocated in liposarcoma protein and Oncogene FUS, plays a pivotal role in transcription regulation, RNA splicing, transport, and DNA repair. It is essential for cellular processes including dendritic spine formation and synaptic homeostasis, highlighting its importance in neuronal cell function.

Therapeutic significance:

FUS is implicated in diseases such as Angiomatoid fibrous histiocytoma, Amyotrophic lateral sclerosis 6, and Hereditary essential tremor 4. Its involvement in these conditions underscores the potential of targeting FUS for therapeutic strategies, offering hope for treatments.

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