Focused On-demand Library for Alpha-fetoprotein

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

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

Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast 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

P02771

UPID:

FETA_HUMAN

Alternative names:

Alpha-1-fetoprotein; Alpha-fetoglobulin

Alternative UPACC:

P02771; B2RBU3

Background:

Alpha-fetoprotein (AFP), also known as Alpha-1-fetoprotein or Alpha-fetoglobulin, plays a crucial role in binding substances like copper, nickel, fatty acids, and bilirubin. Its unique ability to bind less to bilirubin than serum albumin, coupled with its estrogen-binding properties in a small fraction of the protein, highlights its multifunctionality in biological systems.

Therapeutic significance:

AFP is linked to conditions such as Alpha-fetoprotein deficiency, a benign state with undetectable AFP levels in amniotic fluid, and hereditary persistence of alpha-fetoprotein, an autosomal dominant condition. Understanding AFP's role could lead to novel therapeutic strategies for these conditions.