Computational methods for the structural alignment of molecules

In drug design, often enough, no structural information on a particular rec eptor protein is available. However, frequently a considerable number of di fferent ligands is known together with their measured binding affinities to wards a receptor under consideration. In such a situation, a set of plausib le relative superpositions of different ligands, hopefully approximating th eir putative binding geometry, is usually the method of choice for preparin g data for the subsequent application of 3D methods that analyze the simila rity or diversity of the ligands. Examples are 3D-QSAR studies, pharmacopho re elucidation, and receptor modeling. An aggravating fact is that ligands are usually quite flexible and a rigorous analysis has to incorporate molec ular flexibility. We review the past six years of scientific publishing on molecular superposition. Our focus lies on automatic procedures to be perfo rmed on arbitrary molecular structures. Methodical aspects are our main con cern here. Accordingly, plain application studies with few methodical eleme nts are omitted in this presentation. While this review cannot mention ever y contribution to this actively developing field, we intend to provide poin ters to the recent literature providing important contributions to computat ional methods for the structural alignment of molecules. Finally we provide a perspective on how superposition methods can effectively be used for the purpose of virtual database screening. In our opinion it is the ultimate g oal to detect analogues in structure databases of nontrivial size in order to narrow down the search space for subsequent experiments.