AI-ACCELERATED DRUG DISCOVERY

PAN2-PAN3 deadenylation complex catalytic subunit PAN2

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

PAN2-PAN3 deadenylation complex catalytic subunit PAN2 - 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 PAN2-PAN3 deadenylation complex catalytic subunit PAN2 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 PAN2-PAN3 deadenylation complex catalytic subunit PAN2 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 PAN2-PAN3 deadenylation complex catalytic subunit PAN2, 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 PAN2-PAN3 deadenylation complex catalytic subunit PAN2. 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 PAN2-PAN3 deadenylation complex catalytic subunit PAN2. 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 PAN2-PAN3 deadenylation complex catalytic subunit PAN2 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.

PAN2-PAN3 deadenylation complex catalytic subunit PAN2

partner:

Reaxense

upacc:

Q504Q3

UPID:

PAN2_HUMAN

Alternative names:

Inactive ubiquitin carboxyl-terminal hydrolase 52; PAB1P-dependent poly(A)-specific ribonuclease; Poly(A)-nuclease deadenylation complex subunit 2

Alternative UPACC:

Q504Q3; O75189; Q76E12; Q8IVE1

Background:

The PAN2-PAN3 deadenylation complex catalytic subunit PAN2 plays a pivotal role in mRNA turnover. It is a key component of the poly(A)-nuclease (PAN) deadenylation complex, involved in the shortening of poly(A) tails of RNA, a process stimulated by poly(A)-binding protein (PABP). This action facilitates mRNA degradation via the CCR4-NOT complex and exosome-mediated or deadenylation-dependent mechanisms. Additionally, PAN2 is crucial for HIF1A mRNA stability, influencing the hypoxic response.

Therapeutic significance:

Understanding the role of PAN2-PAN3 deadenylation complex catalytic subunit PAN2 could open doors to potential therapeutic strategies.

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