AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Pre-mRNA-splicing regulator WTAP

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 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 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 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

Q15007

UPID:

FL2D_HUMAN

Alternative names:

Female-lethal(2)D homolog; WT1-associated protein; Wilms tumor 1-associating protein

Alternative UPACC:

Q15007; Q5TCL8; Q5TCL9; Q96T28; Q9BYJ7; Q9H4E2

Background:

Pre-mRNA-splicing regulator WTAP, also known as Female-lethal(2)D homolog, WT1-associated protein, and Wilms tumor 1-associating protein, plays a pivotal role in RNA metabolism. It is a key component of the WMM complex, crucial for N6-methyladenosine (m6A) methylation of RNAs, enhancing mRNA splicing and RNA processing efficiency. WTAP facilitates the nuclear speckle accumulation of METTL3 and METTL14, regulates mRNA splicing, and influences G2/M cell-cycle transition by stabilizing CCNA2 mRNA. It also modulates WT1 DNA-binding capacity, affecting WT1 target gene expression.

Therapeutic significance:

Understanding the role of Pre-mRNA-splicing regulator WTAP could open doors to potential therapeutic strategies.

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