Structure, Properties, and Drug-likeness of Pharmaceuticals That Inhibit Ebola Virus Disease (EVD) Proliferation | Chapter 01 | Current Trends in Disease and Health Vol. 1
Introduction:
The Ebola virus is one of known viruses within the genus Ebolavirus that are
generally considered to cause Ebola virus disease (EBV) in humans. Some
investigators have determined that Ebola virus outbreaks have an increased
likelihood to occur when temperatures are lower and humidity is higher. The
determination and evaluation of pharmacokinetic and pharmacodynamics properties
of drugs potentially useful for treatment of Ebola virus disease is a very
important consideration for discovery of new pharmaceuticals.
Aims: To present the molecular structures of compounds that has been shown to inhibit the proliferation of Ebola virus. To elucidate the molecular properties of these virus inhibiting compounds.
Study
Design: The molecular properties of virus inhibiting
compounds are elucidated and compiled. Pattern recognition methods and
statistical analysis are applied to determine optimal properties of this group
of compounds.
Place
and Duration of Study: Chemistry Department, Durham Science
Center, University of Nebraska, Omaha NE. between December 2015 and February
2016.
Methodology:
A total of 60 compounds were identified as
inhibiting the virus Ebola. The molecular properties such as Log P, molecular
weight, and 7 other descriptors were elucidated utilizing heuristic methods.
Structures are compared by applying classification methods with statistical
tests to determine trends, underlying relationships, and pattern recognition.
Results:
For 60 compounds identified the averages
determined: for Log P (3.51), polar surface area (89.45 Angstroms2), molecular
weight (432.6), molecular volume (393.96 Angstroms3), and number of rotatable
bonds (7). Molecular weight showed a strong positive correlation to number of
oxygen and nitrogen atoms, number of rotatable bonds, and molecular volume.
K-means clustering indicated seven clusters divided according to highest
similarity of members in the cluster. Ranges found: formula weights (157.1 to
822.94), Log P (-2.24 to 8.93), polar surface area (6.48 to 267.04 A2), and number
of atoms (11 to 58). Multiple regression analysis produced an algorithm to
predict similar compounds.
Conclusion:
The formula weights and Log P values of Ebola virus inhibitors show a broad
range in numerical values. Consistency in properties was identified by
statistical analysis with grouping for similarity by K-means pattern
recognition. Multiple regression analysis enables prediction of similar
compounds as drug candidates. Only 29 compounds showed zero violations of rule
of 5, an indication of favorable drug-likeness. These compounds are highly
varied in structures and properties.
Author(s) Details
Dr. Ronald Bartzatt
University of Nebraska,
Durham Science Center, 6001 Dodge Street, Omaha, Nebraska 68182, USA.
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