AI-ACCELERATED DRUG DISCOVERY

Phosphatidylinositol 3-kinase regulatory subunit alpha

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Phosphatidylinositol 3-kinase regulatory subunit alpha - 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 Phosphatidylinositol 3-kinase regulatory subunit alpha 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 Phosphatidylinositol 3-kinase regulatory subunit alpha 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 Phosphatidylinositol 3-kinase regulatory subunit alpha, 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 Phosphatidylinositol 3-kinase regulatory subunit alpha. 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 Phosphatidylinositol 3-kinase regulatory subunit alpha. 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 Phosphatidylinositol 3-kinase regulatory subunit alpha 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.

Phosphatidylinositol 3-kinase regulatory subunit alpha

partner:

Reaxense

upacc:

P27986

UPID:

P85A_HUMAN

Alternative names:

Phosphatidylinositol 3-kinase 85 kDa regulatory subunit alpha

Alternative UPACC:

P27986; B3KT19; D3DWA0; E7EX19; Q15747; Q4VBZ7; Q53EM6; Q8IXA2; Q8N1C5

Background:

The Phosphatidylinositol 3-kinase regulatory subunit alpha, also known as the 85 kDa regulatory subunit alpha, plays a pivotal role in cellular processes by binding to activated protein-Tyr kinases through its SH2 domain. This interaction is crucial for mediating the association of the p110 catalytic unit to the plasma membrane, facilitating insulin-stimulated glucose uptake and glycogen synthesis in insulin-sensitive tissues.

Therapeutic significance:

Linked to diseases such as Agammaglobulinemia 7, autosomal recessive, SHORT syndrome, and Immunodeficiency 36 with lymphoproliferation, this protein's involvement in primary immunodeficiencies and multisystem diseases underscores its potential as a target for therapeutic intervention. Understanding the role of Phosphatidylinositol 3-kinase regulatory subunit alpha could open doors to potential therapeutic strategies.

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