| Autor: |
Sullivan DJ; W. Harry Feinstone Department of Molecular Micorbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America., Liu Y; W. Harry Feinstone Department of Molecular Micorbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America., Mott BT; Division of Preclinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, United States of America., Kaludov N; Gradient Biomodeling LLC, Park City, Utah, United States of America., Martinov MN; Gradient Biomodeling LLC, Park City, Utah, United States of America. |
| Jazyk: |
angličtina |
| Zdroj: |
PloS one [PLoS One] 2015 May 07; Vol. 10 (5), pp. e0125593. Date of Electronic Publication: 2015 May 07 (Print Publication: 2015). |
| DOI: |
10.1371/journal.pone.0125593 |
| Abstrakt: |
Without quantum theory any understanding of molecular interactions is incomplete. In principal, chemistry, and even biology, can be fully derived from non-relativistic quantum mechanics. In practice, conventional quantum chemical calculations are computationally too intensive and time consuming to be useful for drug discovery on more than a limited basis. A previously described, original, quantum-based computational process for drug discovery and design bridges this gap between theory and practice, and allows the application of quantum methods to large-scale in silico identification of active compounds. Here, we show the results of this quantum-similarity approach applied to the discovery of novel liver-stage antimalarials. Testing of only five of the model-predicted compounds in vitro and in vivo hepatic stage drug inhibition assays with P. berghei identified four novel chemical structures representing three separate quantum classes of liver-stage antimalarials. All four compounds inhibited liver-stage Plasmodium as a single oral dose in the quantitative PCR mouse liver-stage sporozoites-challenge model. One of the newly identified compounds, cethromycin [ABT-773], a macrolide-quinoline hybrid, is a drug with an extensive (over 5,000 people) safety profile warranting its exploitation as a new weapon for the current effort of malaria eradication. The results of our molecular modeling exceed current state-of-the-art computational methods. Drug discovery through quantum similarity is data-driven, agnostic to any particular target or disease process that can evaluate multiple phenotypic, target-specific, or co-crystal structural data. This allows the incorporation of additional pharmacological requirements, as well as rapid exploration of novel chemical spaces for therapeutic applications. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
|
