Focused On-demand Library for Ras-related protein Rab-14

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

We use our state-of-the-art dedicated workflow for designing focused libraries.

Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

Our library stands out due to several important features:

The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

P61106

UPID:

RAB14_HUMAN

Alternative names:

Alternative UPACC:

P61106; B3KR31; P35287; Q5JVD4; Q6Q7K5; Q969L0; Q9UI11

Background:

Ras-related protein Rab-14 plays a pivotal role in membrane trafficking between the Golgi complex and endosomes during early embryonic development. It is crucial for the transport of FGFR-containing vesicles, influencing the development of the basement membrane, epiblast, and primitive endoderm lineages. Rab-14, in collaboration with DENND6A, modulates the endocytic transport of ADAM10 and N-cadherin/CDH2 shedding, impacting cell-cell adhesion.

Therapeutic significance:

Understanding the role of Ras-related protein Rab-14 could open doors to potential therapeutic strategies. Its involvement in key developmental processes and cell adhesion mechanisms presents it as a target for research in developmental disorders and diseases related to cell adhesion.