Focused On-demand Library for Scavenger receptor class F member 2

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.

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 high-tech, dedicated method is applied to construct 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 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

Q96GP6

UPID:

SREC2_HUMAN

Alternative names:

SRECRP-1; Scavenger receptor expressed by endothelial cells 2 protein

Alternative UPACC:

Q96GP6; E5RFB8; Q58A83; Q8IXF3; Q9BW74

Background:

Scavenger receptor class F member 2 (SRECRP-1, Scavenger receptor expressed by endothelial cells 2 protein) is identified as a probable adhesion protein facilitating both homophilic and heterophilic interactions. Unlike SCARF1, its efficiency in mediating the binding and degradation of acetylated low-density lipoprotein (Ac-LDL) is limited. This protein plays a pivotal role in cellular processes through its receptor functions.

Therapeutic significance:

Van den Ende-Gupta syndrome, a condition marked by distinct craniofacial and skeletal abnormalities, is linked to mutations affecting this protein. Understanding the role of Scavenger receptor class F member 2 could open doors to potential therapeutic strategies for this rare syndrome, highlighting its clinical importance.