A new method, called Protonate3D, is presented for the automated prediction of hydrogen coordinates given the 3D coordinates of the heavy atoms of a macromolecular structure. Protonate3D considers side-chain “flip,” rotamer, tautomer, and ionization states of all chemical groups, ligands, and solvent, provided suitable templates are available in a parameter file. The energy model includes van der Waals, Coulomb, solvation, rotamer, tautomer, and titration effects. The results of computational validation experiments suggest that Protonate3D can accurately predict the location of hydrogen atoms in macromolecular structures. Proteins 2009. © 2008 Wiley-Liss, Inc.

A new generalized Born model for estimating the free energy of hydration is presented. The new generalized Born/volume integral (GB/VI) estimates the free energy of hydration as a classical electrostatic energy plus a cavitation energy that is not based upon atomic surface area (SA) used in GB/SA hydration models but on a VI London dispersion energy estimated from quantities already calculated in the classical electrostatic energy. The (relatively few) GB/VI model parameters are fitted to experimental data, and parameterizations for two different atomic partial charge models are presented. Comparison of the calculated and experimental free energies of hydration for 560 small molecules (both neutral and charged) shows good agreement (r(2) = 0.94).

The results of cognate docking with the prepared Astex dataset provided by the organizers of the “Docking and Scoring: A Review of Docking Programs” session at the 241st ACS national meeting are presented. The MOE software with the newly developed GBVI/WSA dG scoring function is used throughout the study. For 80 % of the Astex targets, the MOE docker produces a top-scoring pose within 2 Å of the X-ray structure. For 91 % of the targets a pose within 2 Å of the X-ray structure is produced in the top 30 poses. Docking failures, defined as cases where the top scoring pose is greater than 2 Å from the experimental structure, are shown to be largely due to the absence of bound waters in the source dataset, highlighting the need to include these and other crucial information in future standardized sets. Docking success is shown to depend heavily on data preparation. A “dataset preparation” error of 0.5 kcal/mol is shown to cause fluctuations of over 20 % in docking success rates.

We present a method for conformational search of complex molecular systems such as macrocycles and protein loops. The method is based on perturbing an existing conformation along a molecular dynamics trajectory using initial atomic velocities with kinetic energy concentrated on the low-frequency vibrational modes, followed by energy minimization. A novel Chebyshev polynomial filter is used to heavily dampen the high-frequency components of a randomly generated Maxwell-Boltzmann velocity vector. The method is very efficient, even for large systems; it is straightforward to implement and requires only standard force-field energy and gradient evaluations. The results of several computational experiments suggest that the method is capable of efficiently sampling low-strain energy conformations of complex systems with nontrivial nonbonded interaction networks.

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