Focused On-demand Library for pre-rRNA 2'-O-ribose RNA methyltransferase FTSJ3

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner 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.

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

Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

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

Reaxense

upacc

Q8IY81

UPID:

SPB1_HUMAN

Alternative names:

Protein ftsJ homolog 3; Putative rRNA methyltransferase 3

Alternative UPACC:

Q8IY81; B2RCA5; D3DU22; Q8N3A3; Q8WXX1; Q9BWM4; Q9NXT6

Background:

Pre-rRNA 2'-O-ribose RNA methyltransferase FTSJ3, also known as Protein ftsJ homolog 3 and Putative rRNA methyltransferase 3, plays a crucial role in the processing of 34S pre-rRNA to 18S rRNA and in the formation of the 40S ribosomal subunit. It is involved in RNA 2'-O-methylation, a critical process for the maturation of ribosomal RNA.

Therapeutic significance:

Understanding the role of pre-rRNA 2'-O-ribose RNA methyltransferase FTSJ3 could open doors to potential therapeutic strategies. Its involvement in RNA processing and ribosomal subunit formation makes it a potential target for interventions in diseases where these processes are dysregulated.