Focused On-demand Library for Cellular tumor antigen p53

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.


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


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.


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
Receptor.AI
 
UPACC
P04637

UPID:
P53_HUMAN

ALTERNATIVE NAMES:
Antigen NY-CO-13; Phosphoprotein p53; Tumor suppressor p53

ALTERNATIVE UPACC:
P04637; Q15086; Q15087; Q15088; Q16535; Q16807; Q16808; Q16809; Q16810; Q16811; Q16848; Q2XN98; Q3LRW1; Q3LRW2; Q3LRW3; Q3LRW4; Q3LRW5; Q86UG1; Q8J016; Q99659; Q9BTM4; Q9HAQ8; Q9NP68; Q9NPJ2; Q9NZD0; Q9UBI2; Q9UQ61

BACKGROUND:
The protein Cellular tumor antigen p53, with alternative names Antigen NY-CO-13 and Tumor suppressor p53, is a cornerstone in the cellular defense against malignancy. It functions as a trans-activator that negatively regulates cell division, and its apoptosis induction is crucial for its tumor suppressive activity. The protein's ability to induce transcription of genes like lincRNA-p21 underscores its significance in cell cycle regulation and apoptosis.

THERAPEUTIC SIGNIFICANCE:
Cellular tumor antigen p53's involvement in a wide array of cancers, including Adrenocortical carcinoma, Basal cell carcinoma 7, and Bone marrow failure syndrome 5, highlights its potential as a target for innovative cancer therapies. The exploration of p53's functions and mechanisms offers promising avenues for the development of novel therapeutic strategies.

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