AI-ACCELERATED DRUG DISCOVERY

Tricarboxylate transport protein, mitochondrial

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Tricarboxylate transport protein, 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 Tricarboxylate transport protein, 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 Tricarboxylate transport protein, 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 Tricarboxylate transport protein, 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 Tricarboxylate transport protein, 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 Tricarboxylate transport protein, 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 Tricarboxylate transport protein, 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.

Tricarboxylate transport protein, mitochondrial

partner:

Reaxense

upacc:

P53007

UPID:

TXTP_HUMAN

Alternative names:

Citrate transport protein; Mitochondrial citrate carrier; Solute carrier family 25 member 1; Tricarboxylate carrier protein

Alternative UPACC:

P53007; A8K8E8; Q9BSK6

Background:

The Tricarboxylate transport protein, mitochondrial, also known as Citrate transport protein, plays a crucial role in cellular energy metabolism. It facilitates the exchange of citrate from the mitochondria to the cytosol, impacting glycolysis regulation and acetyl-CoA production, essential for fatty acids and sterols synthesis. This protein's activity is vital for neuromuscular junction formation, indicating its importance in muscle function and neurological health.

Therapeutic significance:

Linked to Combined D-2- and L-2-hydroxyglutaric aciduria and congenital Myasthenic syndrome, 23, presynaptic, the Tricarboxylate transport protein's dysfunction underscores its therapeutic potential. Targeting its pathway could offer novel treatments for these neurometabolic and neuromuscular disorders, emphasizing the need for advanced research in its mechanism and therapeutic applications.

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