ABSTRACT
Lamarckian Genetic Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . .162 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .166
A prominent tool in the computational drug discovery toolbox are the various methods and algorithms developed for virtual screening, that is, the selection of molecules likely to show a desired bioactivity from a large database. While the preceding Chapter 4 focused on methods to describe molecules (molecular descriptors), the present chapter will firstly deal with methods of how molecules of the desired type
can actually be selected from the database. Hence, Section 5.1 will describe similarity searching methods, among which similarity and distance coefficients are prominent examples.
