Abstract

PREDICTION OF NOVEL ANTI-EBOLA VIRUS COMPOUNDS UTILIZING MULTIPLE REGRESSION ANALYSIS OF PROPERTIES

Ronald Bartzatt*

Abstract

Ebola virus disease (EVD), is also referred to as EBOLA haemorrhagic fever, is a rare but quite severe and many times fatal illness in humans. The virus itself is transmitted to humans from various wild animals such as fruit bats or apes and monkeys. However, the disease spreads in the human population through human-to- human transmission, with the mean EVD case fatality rate being around 50%. The molecular properties of 20 known and tested anti-EBOLA compounds have been determined and are presented. These properties include molecular weight, Log P, polar surface area, number of atoms, and molecular volume. These 20 compounds are shown to have favorable drug characteristics. The molecular structures of these 20 compounds are presented and their features discussed. Hierarchical cluster analysis indicates which of these compounds are most similar to each other. Other statistical analysis shows similarities among their molecular properties. The multiple regression algorithm that is produced could be used to predict properties of similar compounds.

Keywords: Ebola, multiple regression, Viral Hemorrhagic Fever.