In the past years protein-protein interactions have gained a strong interest in
the fields of pharmacy, medicine, biology, and bioinformatics. In this book,
statistical information on protein-protein interactions are computationally
collected and analyzed. Characteristic properties are determined and their
predictability estimated. Therefore, the results from a common docking
approach are re-evaluated with the collected information to discriminate
structures with high yet biologically meaningless geometric complementarity
at the interface region from the near native structures. The results show that
although there is a noticeable improvement in the predictability after
applying statistical information, the overall accuracy is still low. To find other
more specific properties, transient and permanent complexes were compared
to each other. The lack of data led to an extensive search for more suitable
structural data and the development of an extensive database. This database
was ultimately used to retrieve a large number of protein properties that
were automatically analyzed for their separation precision. A high accuracy
was obtained in separating transient and permanent interactions based on
the combination of only four properties. Combining this information with
common docking approaches based on geometrical complementarity may
lead to satisfying sensitivities.