Focused On-demand Library for Signal recognition particle 14 kDa protein

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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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.

Several key aspects differentiate our library:

Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

P37108

UPID:

SRP14_HUMAN

Alternative names:

18 kDa Alu RNA-binding protein

Alternative UPACC:

P37108; B5BUF5; Q6B0K5; Q96Q14

Background:

The Signal recognition particle 14 kDa protein (SRP14), also known as the 18 kDa Alu RNA-binding protein, plays a pivotal role in the cotranslational targeting of secretory and membrane proteins to the endoplasmic reticulum. It is a component of the signal recognition particle (SRP) complex, a ribonucleoprotein complex essential for protein synthesis and targeting. SRP14, in conjunction with SRP9 and the Alu portion of the SRP RNA, forms the elongation arrest domain of SRP, crucial for SRP RNA binding.

Therapeutic significance:

Understanding the role of Signal recognition particle 14 kDa protein could open doors to potential therapeutic strategies.