AI-ACCELERATED DRUG DISCOVERY

Proton-coupled folate transporter

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Proton-coupled folate transporter - 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 Proton-coupled folate transporter 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 Proton-coupled folate transporter 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 Proton-coupled folate transporter, 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 Proton-coupled folate transporter. 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 Proton-coupled folate transporter. 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 Proton-coupled folate transporter 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.

Proton-coupled folate transporter

partner:

Reaxense

upacc:

Q96NT5

UPID:

PCFT_HUMAN

Alternative names:

Heme carrier protein 1; PCFT/HCP1; Solute carrier family 46 member 1

Alternative UPACC:

Q96NT5; Q1HE20; Q86T92; Q8TEG3; Q96FL0

Background:

The Proton-coupled Folate Transporter (PCFT/HCP1), encoded by the gene with accession number Q96NT5, is pivotal in mediating folate absorption in the intestine and its transport across the blood-brain barrier. This protein operates using a proton gradient, facilitating the intake of folates at acidic pH levels. It also transports antifolate drugs like methotrexate, crucial for treating cancer and autoimmune diseases, and serves as a heme carrier in various tissues.

Therapeutic significance:

Hereditary folate malabsorption, a rare autosomal recessive disorder, is directly linked to mutations affecting PCFT/HCP1. This condition leads to severe folate deficiency, resulting in anemia, immune deficiencies, and neurological issues. Early diagnosis and folate administration can mitigate, if not prevent, fatal outcomes and irreversible neurological damage, highlighting the critical therapeutic importance of understanding and targeting PCFT/HCP1.

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