Drug discovery and development makes success out of failure—it takes hundreds of experiments to build a hypothesis that leads to a successful drug candidate. But all of these failures generate data that, when organized and applied appropriately, can help scientists not just to identify the right drug candidates to advance through development, but also to fail wrong drug candidates earlier.
In particular, scientists have employed a number of computational techniques in an effort to make critical assessments or predictions about the druggability of target sites and candidate compounds before conducting more costly in vitro or in vivo experiments. These in silico techniques require exhaustive data and sophisticated, well-structured informatics tools to help scientists exploit the data and better understand mechanism of action, ADME performance, and toxicity.
Currently available scientific data facilitates global compound profiling, which provides a broad picture of how a molecule interacts in the pharmacology space and in later-stage ADME studies. These profiles help organizations plan and manage research programs by: alerting scientists to potential off-target interactions or toxicity issues; providing options for repurposing drugs; and enabling more definitive and informed go/no-go decisions.
In silico global compound profiling exploits in vitro and in vivo experimental information to produce a profile of properties for a given compound. It follows the same methodology as experimental profiling, in which a large set of compounds is screened for a particular activity and an active set further pared down (profiled) by specific parameters such as mechanism of action, selectivity, and ADME characteristics.
In silico profiles confer many advantages, including: fewer molecules synthesized, reduced costs; more targeted and less frequent testing and screening, reduced cell and animal use; and predictive, targeted R&D that enables faster experiments and more informed decisions.
The AurSCOPE knowledge databases, the foundation of Aureus’ in silico profiling platform, are organized around ligands, targets, and biological activities. Each element is described and organized into logical hierarchies according to experimental protocols appearing in the literature.
Taken as a whole, the information compiled by Aureus Pharma creates a global pharmacology space encompassing more than 50,000 publications and patents, 650,000 ligands, and 2.3 million biological activities. The AurPROFILER interface enables scientists to navigate this pharmacology space and conduct a variety of searches, including chemical and pharmacophoric similarity searches, to explore and simulate in silico selectivity profiles for targets, cell lines, or drugs/compounds.
AurPROFILER displays results as interactive heat maps to rapidly visualize, navigate, and filter results based on various parameters such as activity, species, bioassay protocols, publication type, and standard target classification hierarchies.
In silico compound profiling allows organizations to gain valuable information in order to organize and prioritize drug discovery and development programs. This tool is frequently used in repurposing drugs and investigating potential off-target effects.