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This approach allows us to design drug molecules with optimal passive transport properties.
This paper presents a computer-aided technology for the synthesis of molecules with optimal properties.
CAMD technique is a reverse engineering approach which predicts the molecules with optimal properties using property prediction models.
A key challenge in biomass conversion is how to achieve valuable molecules with optimal reactivity in the presence of immiscible reactants.
A challenge for drug design is to create molecules with optimal functions that also partition efficiently into the appropriate in vivo compartment(s).
Because of the limitations of existing compound collections, this diversity can only fully be exploited using in silico design techniques to guide the selection of molecules with optimal binding properties.
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The drug discovery phase is really the solution of a combinatorial optimization problem, namely to find a molecule with optimal efficacy and other physiochemical properties across a given molecular space.
We synthesized mucic acid-derivatized sugar-based amphiphilic molecules (AM) with optimal stereochemistry, rigidity, and charge for enhanced dual binding affinity to SRs and fabricated serum-stable nanoparticles via flash nanoprecipitation comprising hydrophobe cores and amphiphile shells.
Endothelial cell proliferation inhibition increases as the size of the molecule decreases, with optimal effects between 4.5 and 6.5 kDa [ 35], whilst TFPI release increases with an increase in molecule size [ 37].
Evaluation of the biophysical properties of a selection of humanised Fab fragments in a number of assays allowed us to select the molecule with the optimal stability profile.
However, our genotyping data may suggest that BSSL forms dimers and that the combination of a low with a high repeat molecule provides the combination with optimal DC-SIGN binding properties.
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