SAMS is a program used for both Structure Elucidation and New Chemical Entities (NCEs) Generation. SAMS algorithm is designed for optimized structure generation based on known molecular formula and bond constraints derived from small molecule fragments. SAMS is a powerful tool for new lead generation. Combining the power of SAMS with ADME/TOX profiling accelerates de novo drug discovery, and SAMS is also used for designing combinatorial libraries.
SAMS is an excellent tool for structure elucidation of unknown or partially known structures when extensive NMR data is not available due to sample limitation. SAMS uses high-resolution molecular formula information, along with additional structure information from the known starting materials involved in reaction and functional group analysis from IR spectroscopy and UV to generate all possible structures that satisfy the molecular formula. The structures generated are then used for proton and carbon prediction to eliminate all but one final structure for an unknown. SAMS can also be used for LC-NMR based structure elucidation.
SAMS is an excellent tool for de novo chemical structure generation. SAMS uses high-resolution molecular formula information along with bond constraints derived from partial structural fragments to generate chemical libraries of new lead compounds. SAMS can be used for generating analogs of known drug molecules. SAMS generated new leads can be further filtered with in silico ADME/Tox profiles for identifying potential lead compounds.
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