AI-ACCELERATED DRUG DISCOVERY

Centrosomal protein of 120 kDa

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Centrosomal protein of 120 kDa - 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 Centrosomal protein of 120 kDa 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 Centrosomal protein of 120 kDa 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 Centrosomal protein of 120 kDa, 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 Centrosomal protein of 120 kDa. 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 Centrosomal protein of 120 kDa. 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 Centrosomal protein of 120 kDa 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.

Centrosomal protein of 120 kDa

partner:

Reaxense

upacc:

Q8N960

UPID:

CE120_HUMAN

Alternative names:

Coiled-coil domain-containing protein 100

Alternative UPACC:

Q8N960; Q6AI52; Q6AW89; Q8IWB5; Q8N9Y0; Q8NDE8

Background:

Centrosomal protein of 120 kDa, also known as Coiled-coil domain-containing protein 100, is pivotal in microtubule-dependent nucleus-centrosome coupling. It plays a crucial role in centrosome-mediated interkinetic nuclear migration of neural progenitors, neuron positioning during brain development, centriole duplication, maturation during mitosis, and ciliogenesis. Its involvement in neural progenitor migration and self-renewal underscores its significance in cellular dynamics.

Therapeutic significance:

Given its critical role in brain development and association with Short-rib thoracic dysplasia 13 and Joubert syndrome 31, understanding the functions of Centrosomal protein of 120 kDa could unveil novel therapeutic avenues. Targeting the pathways regulated by this protein may offer strategies to mitigate the developmental and skeletal anomalies associated with these conditions.

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