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Data Science in Lead Optimization and Drug Design Data science accelerates the lead optimization and drug design process, transforming how molecules are engineered for therapeutic applications. These complex molecules require precise engineering to ensure optimal efficacy and safety.
The premise at the time was that putting computationalchemistry in the primary position for new molecule ideation would upend the drug discovery paradigm. set up a “virtual project team,” leverage Schrödinger scientists to lead computationalchemistry, and do all the wet work at CROs. It did just that.
The initial discussions that would lead to the PEARL-seq platform involved scanning the literature for the wings, propellers, and engines that we thought we could use. Finally, if we found an rSM that had biological activity, could we correlate that activity with the ability of the rSM to bind RNA?
Fragment-based lead discovery (FBLD) actually has origins in both crystallography [ V1992 | A1996 ] and computationalchemistry [ M1991 | B1992 | E1994 ]. I should also stress that the modern isothermal calorimeter is an engineering marvel and I'd always want this option for label-free, affinity measurement in any project.
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