Focused On-demand Library for Fermitin family homolog 1

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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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 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.

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

Q9BQL6

UPID:

FERM1_HUMAN

Alternative names:

Kindlerin; Kindlin syndrome protein; Kindlin-1; Unc-112-related protein 1

Alternative UPACC:

Q9BQL6; D3DW10; Q8IX34; Q8IYH2; Q9NWM2; Q9NXQ3

Background:

Fermitin family homolog 1, known by alternative names such as Kindlerin, Kindlin syndrome protein, and Kindlin-1, plays a crucial role in cell adhesion and integrin activation. It is essential for keratinocyte proliferation, polarization, and migration, facilitating normal wound healing processes. This protein's interaction with talin enhances ITGA2B activation, contributing to cell shape and adhesion to extracellular matrices like fibronectin and laminin.

Therapeutic significance:

Kindler syndrome, a skin disorder characterized by blistering, photosensitivity, and increased cancer risk, is linked to mutations in the FERMT1 gene encoding Fermitin family homolog 1. Understanding the role of Fermitin family homolog 1 could open doors to potential therapeutic strategies, offering hope for targeted treatments for Kindler syndrome and related conditions.