Randomized algorithms for three dimensional protein structures alignment

The explosive growth of genetic sequence information has offered us comprehensive collections of the protein sequences found in many living organisms. The challenge of understanding these gene products has led to the development of functional proteomics methods, which collectively aim to imbue the raw sequence with biological understanding. Protein structure provides the opportunity to recognize homology that is undetectable by sequence comparison, and it represents a powerful means of discovering functions, yielding direct insight into the molecular mechanisms. Currently, there are several techniques available in attempting to find the optimal alignment of shared structural motifs between two proteins. In this paper, we propose novel algorithms for pairwise alignment of protein structures. Methods of locating suitable isometric transformations of one structure and aligning it to the other structure are addressed. Our methods allow sequence gaps of any length, reversal of chain direction, and free topological connectivity of atom sequences. Sequential connectivity can be imposed as an option. The method is fully automatic to identify structural resemblances and common structural cores accurately and sensitively, even in the presence of geometrical distortions.