Adequate bioavailability is one of the essential properties for an orally 
administered drug. Lipinski and others have formulated simplified rules in which 
compounds that satisfy selected physiochemical properties, for example, 
molecular weight (MW) ≤ 500 or the logarithm of the octanol-water partition 
coefficient, log P(o/w) < 5, are anticipated to likely have pharmacokinetic 
properties appropriate for oral administration. However, these schemes do not 
simultaneously consider the combination of the physiochemical properties, 
complicating their application in a more automated fashion. To overcome this, we 
present a novel method to select compounds with a combination of physicochemical 
properties that maximize bioavailability and druglikeness based on compounds in 
the World Drug Index database. In the study four properties, MW, log P(o/w), 
number of hydrogen bond donors, and number of hydrogen acceptors, were combined 
into a 4-dimensional (4D) histogram, from which a scoring function was defined 
on the basis of a 4D dependent multivariate Gaussian model. The resulting 
equation allows for assigning compounds a bioavailability score, termed 4D-BA, 
such that chemicals with higher 4D-BA scores are more likely to have oral 
druglike characteristics. The descriptor is validated by applying the function 
to drugs previously categorized in the Biopharmaceutics Classification System, 
and examples of application of the descriptor are given in the context of 
previously published studies targeting heme oxygenase and SHP2 phosphatase. The 
approach is anticipated to be useful in early lead identification studies in 
combination with clustering methods to maximize chemical and structural 
diversity when selecting compounds for biological assays from large database 
screens. It may also be applied to prioritize synthetically feasible chemical 
modifications during lead compound optimization.