The efficient evaluation of electrostatic energies of macromolecules in aqueous solutions is useful for many problems in theoretical structural biology. A continuum method based on the generalized Born (GB) approximation is implemented here. It is shown that the choice of the dielectric discontinuity surface is critical for obtaining correct electrostatic energies of molecules in solution. In addition, it is demonstrated that an electrostatic model validated on solvation energies (vacuum to water transfer) might not be appropriate for energies in solution and might not yield correct energy ranking of ligand/protein complexes. The agreement between the GB approach and the finite difference solution of the Poisson equation is shown to be very good for both the molecular and the solvent accessible surface. The discrepancies between the GB and the finite difference approach are much lower than the ones due to the use of different surfaces.

A new method is presented for docking molecular fragments to a rigid protein with evaluation of the binding energy. Polar fragments are docked with at least one hydrogen bond with the protein while apolar fragments are positioned in the hydrophobic pockets. The electrostatic contribution to the binding energy, which consists of screened intermolecular energy and protein and fragment desolvation terms, is evaluated efficiently by a numerical approach based on the continuum dielectric approximation. The latter is also used to predetermine the hydrophobic pockets of the protein by rolling a low dielectric sphere over the protein surface and calculating the electrostatic desolvation of the protein and van der Waals interaction energy. The method was implemented in the program SEED (solvation energy for exhaustive docking). The SEED continuum electrostatic approach has been successfully validated by a comparison with finite difference solutions of the Poisson equation for more than 2,500 complexes of small molecules with thrombin and the monomer of HIV-1 aspartic proteinase. The fragments docked by SEED in the active site of thrombin reproduce the structural features of the interaction patterns between known inhibitors and thrombin. Moreover, the combinatorial connection of these fragments yields a number of compounds that are very similar to potent inhibitors of thrombin. Proteins 1999;37:88-105.

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The potential of mean force in aqueous solution for rotation around the two backbone dihedrals φ and ψ of the alanine dipeptide is computed in explicit water and in the continuum approximation by numerical integration of the self-energies and the generalized Born (GB) equation. The two models show good agreement. The experimentally observed increase in the gauche/trans population ratio for dichloroethane in going from the gas phase to the pure liquid is reproduced by the GB solvation model with a solvent dielectric constant of 10.5. This test case shows that the GB model gives accurate predictions also for solvents with much lower polarizability than water. For both test systems additional calculations with a finite difference Poisson equation solver yield somewhat more accurate results at a much higher computational cost than the GB solvation model.

Dengue fever is a viral disease that affects 50-100 million people annually and is one of the most important emerging infectious diseases in many areas of the world. Currently, neither specific drugs nor vaccines are available. Here, we report on the discovery of new inhibitors of the viral NS5 RNA methyltransferase, a promising flavivirus drug target. We have used a multistage molecular docking approach to screen a library of more than 5 million commercially available compounds against the two binding sites of this enzyme. In 263 compounds chosen for experimental verification, we found 10 inhibitors with IC(50) values of <100 microM, of which four exhibited IC(50) values of <10 microM in in vitro assays. The initial hit list also contained 25 nonspecific aggregators. We discuss why this likely occurred for this particular target. We also describe our attempts to use aggregation prediction to further guide the study, following this finding.