AI-ACCELERATED DRUG DISCOVERY

Coiled-coil domain-containing protein 62

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Coiled-coil domain-containing protein 62 - 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 Coiled-coil domain-containing protein 62 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 Coiled-coil domain-containing protein 62 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 Coiled-coil domain-containing protein 62, 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 Coiled-coil domain-containing protein 62. 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 Coiled-coil domain-containing protein 62. 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 Coiled-coil domain-containing protein 62 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.

Coiled-coil domain-containing protein 62

partner:

Reaxense

upacc:

Q6P9F0

UPID:

CCD62_HUMAN

Alternative names:

Protein TSP-NY; Protein aaa

Alternative UPACC:

Q6P9F0; A8K8V1; B3KUP3; Q6ZVF2; Q86VJ0; Q9BYZ5

Background:

Coiled-coil domain-containing protein 62, also known as Protein TSP-NY and Protein aaa, plays a pivotal role in spermiogenesis, particularly in acrosome formation. This protein acts as a nuclear receptor coactivator, enhancing the transactivation of estrogen receptors ESR1 and ESR2, and to a lesser extent, modulates progesterone, glucocorticoid, and androgen receptors. Its involvement in hormone receptor signaling underscores its importance in reproductive biology.

Therapeutic significance:

Linked to Spermatogenic failure 67, a disorder leading to male infertility due to globozoospermia, understanding the role of Coiled-coil domain-containing protein 62 could open doors to potential therapeutic strategies. Its critical function in acrosome formation and hormone receptor modulation makes it a promising target for addressing infertility issues.

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