Focused On-demand Library for Sigma non-opioid intracellular receptor 1

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our high-tech, dedicated method is applied to construct targeted libraries for receptors.

Fig. 1. The sreening workflow of Receptor.AI

This process includes extensive molecular simulations of the receptor in its native membrane environment, along with ensemble virtual screening that accounts for its conformational mobility. In the case of dimeric or oligomeric receptors, the entire functional complex is modelled, identifying potential binding pockets on and between the subunits to encompass all possible mechanisms of action.

Our library distinguishes itself through several key aspects:

The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

Q99720

UPID:

SGMR1_HUMAN

Alternative names:

Aging-associated gene 8 protein; SR31747-binding protein; Sigma 1-type opioid receptor

Alternative UPACC:

Q99720; D3DRM7; O00673; O00725; Q0Z9W6; Q153Z1; Q2TSD1; Q53GN2; Q7Z653; Q8N7H3; Q9NYX0

Background:

Sigma non-opioid intracellular receptor 1, also known as Aging-associated gene 8 protein or Sigma 1-type opioid receptor, plays a pivotal role in lipid transport, receptor regulation, and cellular signaling. Its involvement in BDNF and EGF signaling, ion channel modulation, and calcium signaling underscores its multifaceted role in cell functions including proliferation, survival, and death. Additionally, it is crucial for mitochondrial axonal transport in motor neurons and protects against oxidative stress-induced cell death.

Therapeutic significance:

Linked to Amyotrophic lateral sclerosis 16 and Distal spinal muscular atrophy, autosomal recessive, 2, Sigma non-opioid intracellular receptor 1's genetic variants highlight its potential in neurodegenerative disease research. Understanding its role could open doors to novel therapeutic strategies, particularly in targeting motor neuron diseases and enhancing neuroprotective mechanisms.