Flat-Bottom Strategy for Improved Accuracy in Protein Side-Chain Placements.

We present a new strategy for protein side-chain placement that uses flat-bottom potentials for rotamer scoring. The extent of the flat bottom depends on the coarseness of the rotamer library and is optimized for libraries ranging from diversities of 0.2 Å to 5.

Fidelity of seryl-tRNA synthetase to binding of natural amino acids from HierDock first principles computations.

Seryl-tRNA synthetase (SerRS) charges serine to tRNA(Ser) following the formation of a seryl adenylate intermediate, but the extent to which other non-cognate amino acids compete with serine to bind to SerRS or for the formation of the activated seryl adenylate intermediate is not known. To examine the mechanism of discrimination against non-cognate amino acids, we calculated the relative binding energies of the 20 natural amino acids to SerRS. Starting with the crystal structure of SerRS from Thermus thermophilus with seryl adenylate bound, we used the HierDock and SCREAM (Side-Chain Rotamer Energy Analysis Method) computational methods to predict the binding conformation and binding energy of each of the 20 natural amino acids in the binding site in the best-binding mode and the activating mode.

The predicted 3D structure of the human D2 dopamine receptor and the binding site and binding affinities for agonists and antagonists.

Dopamine neurotransmitter and its receptors play a critical role in the cell signaling process responsible for information transfer in neurons functioning in the nervous system. Development of improved therapeutics for such disorders as Parkinson's disease and schizophrenia would be significantly enhanced with the availability of the 3D structure for the dopamine receptors and of the binding site for dopamine and other agonists and antagonists. We report here the 3D structure of the long isoform of the human D2 dopamine receptor, predicted from primary sequence using first-principles theoretical and computational techniques (i.

Predicted 3D structure for the human beta 2 adrenergic receptor and its binding site for agonists and antagonists.

We report the 3D structure of human beta2 adrenergic receptor (AR) predicted by using the MembStruk first principles method. To validate this structure, we use the HierDock first principles method to predict the ligand-binding sites for epinephrine and norepinephrine and for eight other ligands, including agonists and antagonists to beta 2 AR and ligands not observed to bind to beta 2 AR. The binding sites agree well with available mutagenesis data, and the calculated relative binding energies correlate reasonably with measured binding affinities.