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. 2019 Jun 26;5(6):eaav9784.
doi: 10.1126/sciadv.aav9784. eCollection 2019 Jun.

Cheminformatics-driven discovery of polymeric micelle formulations for poorly soluble drugs

Affiliations

Cheminformatics-driven discovery of polymeric micelle formulations for poorly soluble drugs

Vinicius M Alves et al. Sci Adv. .

Abstract

Many drug candidates fail therapeutic development because of poor aqueous solubility. We have conceived a computer-aided strategy to enable polymeric micelle-based delivery of poorly soluble drugs. We built models predicting both drug loading efficiency (LE) and loading capacity (LC) using novel descriptors of drug-polymer complexes. These models were employed for virtual screening of drug libraries, and eight drugs predicted to have either high LE and high LC or low LE and low LC were selected. Three putative positives, as well as three putative negative hits, were confirmed experimentally (implying 75% prediction accuracy). Fortuitously, simvastatin, a putative negative hit, was found to have the desired micelle solubility. Podophyllotoxin and simvastatin (LE of 95% and 87% and LC of 43% and 41%, respectively) were among the top five polymeric micelle-soluble compounds ever studied experimentally. The success of the strategy described herein suggests its broad utility for designing drug delivery systems.

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Figures

Fig. 1
Fig. 1. Study design.
Fig. 2
Fig. 2. Coverage of chemical space by previously tested drugs and compounds rationally selected to increase structural diversity.
Barycentric coordinates are calculated using two-dimensional SiRMS (molecular fragments) descriptors differentiated by atom type.
Fig. 3
Fig. 3. General scheme of descriptor calculation for polymers.
Fig. 4
Fig. 4. Descriptor calculation of drug-polymer complexes.
nA and nB are molar fractions of components A and B (nA < nB).

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