AI-ACCELERATED DRUG DISCOVERY

Serine/threonine-protein kinase PINK1, mitochondrial

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Serine/threonine-protein kinase PINK1, mitochondrial - 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 Serine/threonine-protein kinase PINK1, mitochondrial 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 Serine/threonine-protein kinase PINK1, mitochondrial 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 Serine/threonine-protein kinase PINK1, mitochondrial, 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 Serine/threonine-protein kinase PINK1, mitochondrial. 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 Serine/threonine-protein kinase PINK1, mitochondrial. 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 Serine/threonine-protein kinase PINK1, mitochondrial 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.

Serine/threonine-protein kinase PINK1, mitochondrial

partner:

Reaxense

upacc:

Q9BXM7

UPID:

PINK1_HUMAN

Alternative names:

BRPK; PTEN-induced putative kinase protein 1

Alternative UPACC:

Q9BXM7; Q8N6T9; Q8NBU3; Q96DE4

Background:

Serine/threonine-protein kinase PINK1, mitochondrial, also known as BRPK or PTEN-induced putative kinase protein 1, plays a pivotal role in protecting against mitochondrial dysfunction during cellular stress. It achieves this by phosphorylating mitochondrial proteins such as PRKN and DNM1L, coordinating mitochondrial quality control mechanisms. These mechanisms include removing and replacing dysfunctional mitochondrial components, preventing apoptosis, stimulating mitochondrial biogenesis, regulating mitochondrial dynamics, and eliminating severely damaged mitochondria via mitophagy.

Therapeutic significance:

PINK1's involvement in Parkinson disease 6, an early-onset form of Parkinson's characterized by parkinsonian signs and mitochondrial dysfunction, underscores its therapeutic significance. Understanding the role of PINK1 could open doors to potential therapeutic strategies targeting mitochondrial quality control mechanisms, offering hope for patients with Parkinson's and possibly other neurodegenerative disorders.

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