Efficient computational algorithms for docking and for generating and matching a library of functional epitopes I. Rigid and flexible hinge-bending docking algorithms.
In this, and the next review article (1), we present highly efficient, computer-vision and robotics based algorithms for docking and for the generation and matching of epitopes on molecular surfaces. We start with descriptions of molecular surfaces, and proceed to utilize these in both rigid-body and flexible matching routines. These algorithms originate in the computer vision and robotics disciplines. Frequently used approaches, both in searches for molecular similarity and for docking, i.e., molecular complementarity, strive to obtain highly accurate correspondence of respective molecular surfaces. However, owing to molecular surface variability in solution, to mutational events, and to the need to use modeled structures in addition to high resolution ones, utilization of epitopes might prove to be a judicious approach to follow. Furthermore, through the deployment of libraries of epitopes which represent recurring features, or motifs in a given family of receptors or of enzymes, in principle we a priori focus on the more critical groups of atoms, or amino acids, essential for the binding of the two molecules. Utilization of recurring motifs may prove more robust than single molecule matchings. In addition, via utilization of epitopes one can make use of information derived from evolutionary related molecules. All of the above combine to represent an approach which may be highly advantageous. Combinatorial approaches have proven their immense utility in the wet laboratory. The combination of efficient computational approaches and the utilization of such libraries may well be particularly profitable. Our highly efficient techniques are amenable to such a task. In this review we focus on rigid and flexible docking algorithms. In the second review (1) we address the generation of epitopes in families of molecules. These may be used by the docking algorithms to identify the more likely bound interfaces.
Nussinov
R
R
Intramural Research Support Program - SAIC, National Cancer Institute, Frederick Cancer Research and Development Center, Frederick, MD 21702, USA. ruthn@ncicrf.gov
Wolfson
H J
HJ
D000465:Algorithms; D001665:Binding Sites; D020650:Combinatorial Chemistry Techniques; D003198:Computer Simulation; D000939:Epitopes; D008024:Ligands; D008968:Molecular Conformation; D004364:Pharmaceutical Preparations; D011485:Protein Binding; D012371:Robotics
D000939:Epitopes; D008024:Ligands; D004364:Pharmaceutical Preparations