AI-ACCELERATED DRUG DISCOVERY

Brain-specific angiogenesis inhibitor 1-associated protein 2

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Brain-specific angiogenesis inhibitor 1-associated protein 2 - Focused Library Design

Available from Reaxense

This protein is integrated into the Receptor.AI ecosystem as a prospective target with high therapeutic potential. We performed a comprehensive characterization of Brain-specific angiogenesis inhibitor 1-associated protein 2 including:

1. LLM-powered literature research

Our custom-tailored LLM extracted and formalized all relevant information about the protein from a large set of structured and unstructured data sources and stored it in the form of a Knowledge Graph. This comprehensive analysis allowed us to gain insight into Brain-specific angiogenesis inhibitor 1-associated protein 2 therapeutic significance, existing small molecule ligands, relevant off-targets, and protein-protein interactions.

 Fig. 1. Preliminary target research workflow

2. AI-Driven Conformational Ensemble Generation

Starting from the initial protein structure, we employed advanced AI algorithms to predict alternative functional states of Brain-specific angiogenesis inhibitor 1-associated protein 2, including large-scale conformational changes along "soft" collective coordinates. Through molecular simulations with AI-enhanced sampling and trajectory clustering, we explored the broad conformational space of the protein and identified its representative structures. Utilizing diffusion-based AI models and active learning AutoML, we generated a statistically robust ensemble of equilibrium protein conformations that capture the receptor's full dynamic behavior, providing a robust foundation for accurate structure-based drug design.

 Fig. 2. AI-powered molecular dynamics simulations workflow

3. Binding pockets identification and characterization

We employed the AI-based pocket prediction module to discover orthosteric, allosteric, hidden, and cryptic binding pockets on the protein’s surface. Our technique integrates the LLM-driven literature search and structure-aware ensemble-based pocket detection algorithm that utilizes previously established protein dynamics. Tentative pockets are then subject to AI scoring and ranking with simultaneous detection of false positives. In the final step, the AI model assesses the druggability of each pocket enabling a comprehensive selection of the most promising pockets for further targeting.

 Fig. 3. AI-based binding pocket detection workflow

4. AI-Powered Virtual Screening

Our ecosystem is equipped to perform AI-driven virtual screening on Brain-specific angiogenesis inhibitor 1-associated protein 2. With access to a vast chemical space and cutting-edge AI docking algorithms, we can rapidly and reliably predict the most promising, novel, diverse, potent, and safe small molecule ligands of Brain-specific angiogenesis inhibitor 1-associated protein 2. This approach allows us to achieve an excellent hit rate and to identify compounds ready for advanced lead discovery and optimization.

 Fig. 4. The screening workflow of Receptor.AI

Receptor.AI, in partnership with Reaxense, developed a next-generation technology for on-demand focused library design to enable extensive target exploration.

The focused library for Brain-specific angiogenesis inhibitor 1-associated protein 2 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.

Brain-specific angiogenesis inhibitor 1-associated protein 2

partner:

Reaxense

upacc:

Q9UQB8

UPID:

BAIP2_HUMAN

Alternative names:

Fas ligand-associated factor 3; Insulin receptor substrate p53/p58; Insulin receptor substrate protein of 53 kDa

Alternative UPACC:

Q9UQB8; O43858; Q53HB1; Q86WC1; Q8N5C0; Q96CR7; Q9UBR3; Q9UQ43

Background:

Brain-specific angiogenesis inhibitor 1-associated protein 2, also known as Fas ligand-associated factor 3, plays a pivotal role in cellular processes by linking membrane-bound small G-proteins to cytoplasmic effector proteins. It is essential for CDC42-mediated actin cytoskeleton reorganization and RAC1-mediated membrane ruffling. This protein also contributes to neurite growth, filopodia formation, and actin cytoskeleton reorganization in response to bacterial infection.

Therapeutic significance:

Understanding the role of Brain-specific angiogenesis inhibitor 1-associated protein 2 could open doors to potential therapeutic strategies.

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