In silico screening services. We count with a library of 500,000 fragment compounds to test on protein target structures. Our in silico screening protocol, which has a 10% to 20% hit rate, employs proprietary machine learning algorithms, together with protein conformational assessment, to perform the candidate compound selection.
Our strategies for the de novo hit identification and optimization, which combine structural information, chemoinformatic and machine learning approaches, allow us to spot the most promising molecules in the hit-to-lead process.
A de novo hit identification strategy is applied in situations where the establishment of a new lead molecules is required. Virtual Screening campaigns are implemented by employing all receptor structural information available together with a library of 500,000 fragment molecules. Virtual Screening results are analyzed, with chemoinformatics and machine learning protocols, to identify molecules with the highest probability of succeed in experimental assays. After experimental validation of molecule candidates, the decision is taken on whether the goals have been reached or further search are needed. In the latter case, interdisciplinary team decisions are taken to establish pharmacophoric hypothesis and identify potential grow compound directions. From these ideas, enriched and/or ad hoc chemical libraries a designed to start a new search cycle.
A lead optimization strategy is applied in situations where previous information from inhibiting molecules is known. Similarly, as in the de novo hit identification strategy, Virtual Screening campaigns are implemented by employing all receptor structural information available. The chemical libraries are ad hoc designed to guide the molecule grow. Virtual screening results are analyzed, with pharmacophoric and machine learning protocols, to identify molecules with the highest probability of succeed in experimental assays. After experimental validation of molecule candidates, the decision is taken on whether the goals have been reached or further search are needed. In the latter case, interdisciplinary team decisions are taken to refine the pharmacophoric hypothesis, design new chemical libraries and start a new search cycle.