Focused On-demand Library for Immunoglobulin superfamily member 1

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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.

We utilise our cutting-edge, exclusive workflow to develop focused libraries for receptors.

Fig. 1. The sreening workflow of Receptor.AI

The method involves detailed molecular simulations of the receptor in its native membrane environment, with ensemble virtual screening focusing on its conformational mobility. When dealing with dimeric or oligomeric receptors, the whole functional complex is modelled, and the tentative binding pockets on and between the subunits are established to address all possible mechanisms of action.

Our library is unique due to several crucial aspects:

Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q8N6C5

UPID:

IGSF1_HUMAN

Alternative names:

Immunoglobulin-like domain-containing protein 1; Inhibin-binding protein; Pituitary gland-specific factor 2; p120

Alternative UPACC:

Q8N6C5; B5MEG2; H9KV64; O15070; Q9NTC8

Background:

Immunoglobulin superfamily member 1, also known as Immunoglobulin-like domain-containing protein 1, Inhibin-binding protein, Pituitary gland-specific factor 2, or p120, plays a pivotal role in inhibin signaling. It acts as a coreceptor, modulating the effects of inhibin B and antagonizing activin A signaling, thereby influencing various physiological processes.

Therapeutic significance:

The protein's involvement in Hypothyroidism, central, and testicular enlargement, underscores its potential as a target for therapeutic intervention. Understanding the role of Immunoglobulin superfamily member 1 could open doors to potential therapeutic strategies.