AI-ACCELERATED DRUG DISCOVERY

Growth/differentiation factor 5

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Growth/differentiation factor 5 - 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 Growth/differentiation factor 5 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 Growth/differentiation factor 5 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 Growth/differentiation factor 5, 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 Growth/differentiation factor 5. 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 Growth/differentiation factor 5. 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 Growth/differentiation factor 5 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.

Growth/differentiation factor 5

partner:

Reaxense

upacc:

P43026

UPID:

GDF5_HUMAN

Alternative names:

Bone morphogenetic protein 14; Cartilage-derived morphogenetic protein 1; Lipopolysaccharide-associated protein 4; Radotermin

Alternative UPACC:

P43026; E1P5Q2; Q96SB1

Background:

Growth/differentiation factor 5 (GDF5), also known as Bone morphogenetic protein 14, plays a pivotal role in bone and cartilage formation. It regulates chondrogenic tissue differentiation via two pathways: positively through BMPR1B and BMPR1A interaction, leading to SMAD protein signaling, and negatively through interaction with NOG. Additionally, GDF5 is involved in muscle maintenance upon denervation and mediates LPS-induced inflammatory responses.

Therapeutic significance:

GDF5's involvement in skeletal disorders such as Acromesomelic dysplasia, Brachydactyly, Symphalangism, Multiple synostoses syndrome, and Osteoarthritis highlights its therapeutic potential. Understanding GDF5's role could pave the way for innovative treatments targeting these debilitating conditions, offering hope for affected individuals.

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