AI-ACCELERATED DRUG DISCOVERY

Potassium voltage-gated channel subfamily A member 5

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Potassium voltage-gated channel subfamily A member 5 - 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 Potassium voltage-gated channel subfamily A member 5 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 Potassium voltage-gated channel subfamily A member 5 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 Potassium voltage-gated channel subfamily A member 5, 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 Potassium voltage-gated channel subfamily A member 5. 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 Potassium voltage-gated channel subfamily A member 5. 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 Potassium voltage-gated channel subfamily A member 5 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.

Potassium voltage-gated channel subfamily A member 5

partner:

Reaxense

upacc:

P22460

UPID:

KCNA5_HUMAN

Alternative names:

HPCN1; Voltage-gated potassium channel HK2; Voltage-gated potassium channel subunit Kv1.5

Alternative UPACC:

P22460; Q4KKT8; Q4VAJ1; Q4VAJ2; Q9UDA4

Background:

Potassium voltage-gated channel subfamily A member 5 (Kv1.5), encoded by the gene with accession number P22460, is a critical component in the regulation of potassium transport across excitable membranes. It forms both homotetrameric and heterotetrameric channels, influencing cellular excitability. The channel's activity is essential for maintaining the resting membrane potential and modulating action potentials in various cell types, including cardiac and pancreatic cells.

Therapeutic significance:

Kv1.5 has been directly linked to Atrial fibrillation, familial, 7, a condition characterized by irregular heart rhythms. This association underscores the protein's potential as a target for therapeutic intervention in cardiac arrhythmias. Understanding the role of Kv1.5 could open doors to potential therapeutic strategies, particularly in the development of selective ion channel modulators to correct heart rhythm disorders.

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