Efficient simulation of ligand-receptor binding processes using the conformation dynamics approach.
The understanding of biological ligand-receptor binding processes is relevant for a variety of research topics and assists the rational design of novel drug molecules. Computer simulation can help to advance this understanding, but, due to the high dimensionality of according systems, suffers from the severe computational cost. Based on the framework provided by conformation dynamics and transition state theory, a novel heuristic approach of simulating ligand-receptor binding processes is introduced, which is not dependent on calculating lengthy molecular dynamics trajectories. First, the relevant portion of conformational space is partitioned with meshless methods. Then, each region is sampled separately, using hybrid Monte Carlo. Finally, the dynamical binding process is reconstructed from the static overlaps between the partial densities obtained in the sampling step. The method characterizes the metastable steps of the binding process and can yield the corresponding transition probabilities.
Bujotzek
Alexander
A
Computational Drug Design Group, Zuse Institute Berlin, Takustrasse 7, D-14195 Berlin, Germany. bujotzek@zib.de
Weber
Marcus
M
D000465:Algorithms; D018826:CD13 Antigens / Q000737:chemistry / Q000378:metabolism; D019295:Computational Biology; D003198:Computer Simulation; D018819:Dipeptidyl Peptidase 4 / Q000737:chemistry / Q000378:metabolism; D029968:Escherichia coli Proteins / Q000737:chemistry / Q000378:metabolism; D006801:Humans; D008024:Ligands; D008958:Models, Molecular; D009010:Monte Carlo Method; D011485:Protein Binding; D011487:Protein Conformation; D011956:Receptors, Cell Surface / Q000737:chemistry* / Q000378:metabolism*; D013816:Thermodynamics
D029968:Escherichia coli Proteins; D008024:Ligands; D011956:Receptors, Cell Surface; D018826:CD13 Antigens; C042807:DPP4 protein, human; D018819:Dipeptidyl Peptidase 4