AI-ACCELERATED DRUG DISCOVERY

Sp110 nuclear body protein

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Sp110 nuclear body protein - 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 Sp110 nuclear body protein 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 Sp110 nuclear body protein 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 Sp110 nuclear body protein, 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 Sp110 nuclear body protein. 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 Sp110 nuclear body protein. 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 Sp110 nuclear body protein 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.

Sp110 nuclear body protein

partner:

Reaxense

upacc:

Q9HB58

UPID:

SP110_HUMAN

Alternative names:

Interferon-induced protein 41/75; Speckled 110 kDa; Transcriptional coactivator Sp110

Alternative UPACC:

Q9HB58; B4DVI4; F5H1M1; Q14976; Q14977; Q53TG2; Q8WUZ6; Q9HCT8

Background:

The Sp110 nuclear body protein, also known as Interferon-induced protein 41/75, Speckled 110 kDa, and Transcriptional coactivator Sp110, plays a pivotal role in the immune system. It functions as a transcription factor and may act as a nuclear hormone receptor coactivator, enhancing the transcription of genes with retinoic acid response elements (RARE).

Therapeutic significance:

Sp110 is directly linked to Hepatic venoocclusive disease with immunodeficiency, a severe condition characterized by hypogammaglobulinemia, combined T and B-cell immunodeficiency, and absence of lymph node germinal centers. Understanding the role of Sp110 could open doors to potential therapeutic strategies for this immunodeficiency.

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