Journal of Computational Chemistry

Lii, Jenn‐Huei; Ma, Buyong; Allinger, Norman L.

doi: 10.1002/(SICI)1096-987X(19991130)20:15<1593::AID-JCC1>3.0.CO;2-Apmid: N/A

An extensive quantum mechanical study of a water dimer suggests that the introduction of a diffuse function into the basis set, which significantly reduces the basis set superposition error (BSSE) in the hydrogen bonding energy calculation, is the key to better calculations of the potential energy surfaces of carbohydrates. This article examines the potential energy surfaces of selected d‐aldo‐ and d‐ketohexoses (a total of 82 conformers) by quantum mechanics (QM) and molecular mechanics (MM) methods. In contrast to the results with a smaller basis set (B3LYP/6‐31G** 5d), we found at the higher level calculation (B3LYP/6‐311++G(2d,2p)//B3LYP/6‐31G** 5d) that, in most cases, the furanose forms are less stable than the pyranose forms. These discrepancies are mainly due to the fact that intramolecular hydrogen bonding energies are overestimated in the lower level calculations. The higher level QM calculations of the potential energy surfaces of d‐aldo‐ and d‐ketohexoses now are more comparable to the MM3 results. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 1593–1603, 1999

Schäfer, Heiko; Van Gunsteren, Wilfred F.; Mark, Alan E.

doi: 10.1002/(SICI)1096-987X(19991130)20:15<1604::AID-JCC2>3.0.CO;2-Apmid: N/A

The ability to determine the free energy of solvation for a number of small organic molecules with varying sizes and properties from the coordinate trajectory of a single simulation of a given reference state was investigated. The relative free energies were estimated from a single step perturbation using the perturbation formula. The reference state consisted of a cavity surrounded by solvent. To enhance sampling a soft‐core interaction was used for the cavity. The effect of the size of the cavity, the effective core height, and the length of simulation on the ability to reproduce results obtained from thermodynamic integration calculations was considered. The results using a single step perturbation from an appropriately chosen initial state were comparable to results from thermodynamic integration calculations for a wide range of compounds. Using a large number of compounds the computational efficiency was potentially increased by 2–3 orders of magnitude over traditional free energy approaches. Factors determining the efficiency of the approach are discussed. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 1604–1617, 1999

Harrison, Robert W.

doi: 10.1002/(SICI)1096-987X(19991130)20:15<1618::AID-JCC3>3.0.CO;2-Vpmid: N/A

A computer algorithm is developed for integrating density functional quantum mechanics into a molecular mechanics program. The computationally infeasible aspects of the standard LCAO‐MO approach (the iterative calculation of eigenvectors and the requirement of orthogonal expansions for the orbitals) are replaced with an efficient use of optimization via the trace theorem of linear algebra. The construction of a basis is also described for expanding the electron density that transforms with the molecular geometry. The combination of the trace method and the basis allow the solution for one configuration of atoms and electrons to be tracked over a wide range of internal conformations. The approach is readily adaptable to being used in the context of an imposed classical field that allows it to be used on part of a macromolecular complex. The initial implementation in the program AMMP is described. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 1618–1633, 1999

Godden, Jeffrey W.; Stahura, Florence L.; Bajorath, Jürgen

doi: 10.1002/(SICI)1096-987X(19991130)20:15<1634::AID-JCC4>3.0.CO;2-1pmid: N/A

The results of 16 docking simulations with rigid receptor sites and flexible ligands (∼60,000 compounds in each case) are statistically analyzed and compared. Different combinations of binding sites, scoring functions, and compound collections are used in these calculations. The docking scores are not randomly distributed over the scoring range; they follow Gaussian distributions (regardless of the binding sites), scoring functions, or screened compounds. If the docking sites are small, the Gaussian distributions are positively skewed. Peaks of the Gaussian distributions are populated with compounds having similar scores but different sizes and binding modes. These findings have implications for compound selection via computational docking. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 1634–1643, 1999

Crouzy, Serge; Baudry, Jerôme; Smith, Jeremy C.; Roux, Benoît

doi: 10.1002/(SICI)1096-987X(19991130)20:15<1644::AID-JCC5>3.0.CO;2-Ypmid: N/A

Accurate calculation of potential energy and free‐energy profiles along reaction coordinates of biological processes such as enzymatic reactions or conformational changes is fundamental to the obtention of theoretical insight into protein function. We describe here the practical implementation of the Automatic Map Refinement Procedure (AMRP) and two‐dimensional Weighted Histogram Analysis Method (WHAM) for efficient computation of adiabatic potential energy and free‐energy maps, respectively. Methods for efficiently sampling configuration space with high‐energy barriers and for removing hysteresis in the case of periodic reaction coordinates are presented. The application of these techniques to the isomerization of the C13C14 and C15N16 bonds in the retinal of bacteriorhodopsin is described. In dark‐adapted bacteriorhodopsin (bR), the retinal moiety exists in two conformers, all‐trans and (13,15)cis, with the latter making ≃67% of the population. This experimental free energy difference is reproduced here to within kBT. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 1644–1658, 1999

Baysal, Canan; Meirovitch, Hagai

doi: 10.1002/(SICI)1096-987X(19991130)20:15<1659::AID-JCC6>3.0.CO;2-Fpmid: N/A

Simulated annealing (SA) is a popular global minimizer that can conveniently be applied to complex macromolecular systems. Thus, a molecular dynamics or a Monte Carlo simulation starts at high temperature, which is decreased gradually, and the system is expected to reach the low‐energy region on the potential energy surface of the molecule. However, in many cases this process is not efficient. Alternatively, the low‐energy region can be reached more effectively by minimizing the energy of selected molecular structures generated along the simulation pathway. The efficiency of SA to locate energy‐minimized structures within 5 kcal/mol above the global energy minimum is studied as applied to three peptide models with increasing geometrical restrictions: (1) The linear pentapeptide Leu‐enkephalin described by the ECEPP potential, (2) a cyclic hexapeptide described by the GROMOS force field energy EGRO alone, and (3) the same cyclic peptide with EGRO combined with a restraining potential based on 31 proton–proton restraints obtained from nuclear magnetic resonance (NMR) experiments. The efficiency of SA is compared to that of the Monte Carlo minimization (MCM) method of Li and Scheraga, and to our local torsional deformations (LTD) method for the conformational search of cyclic molecules. The results for the linear peptide show that SA provides a relatively weak guidance towards the most stable energy region; as expected, this guidance increases for the cyclic peptide and the cyclic peptide with NMR restraints. However, in general, MCM and LTD are significantly more efficient than SA as generators of low‐energy minimized structures. This suggests that LTD might provide a better search tool than SA in structure determination of protein regions for which a relatively small number of restraints are provided by NMR. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 1659–1670, 1999

Kolossváry, István; Guida, Wayne C.

doi: 10.1002/(SICI)1096-987X(19991130)20:15<1671::AID-JCC7>3.0.CO;2-Ypmid: N/A

We previously described a new conformational search method, termed low‐mode search (LMOD), and discussed its utility for conformational searches performed on cycloalkanes and a cyclic penta‐peptide.1 In this report, we discuss a rigorous implementation of mode following (c‐LMOD) for conformational searching, and we demonstrate that for a conformational search involving cycloheptadecane, this rigorous implementation is capable of finding all of the previously known structures. To the best of our knowledge, this is the first computational proof that mode following can be used for conformational searches conducted on a complex molecular system. We show, however, that, as expected, it is generally inefficient to perform a conformational search in this manner. Nonetheless, c‐LMOD has been shown to be an excellent method for conducting conformational analyses involving conformational interconversions, where the location of saddle points is important. We also describe refinement to our original LMOD procedure (l‐LMOD) and discuss its utility for a difficult conformational search problem, namely locating the global minimum energy conformation of C39H80. For this search, l‐LMOD combined with limited torsional Monte Carlo movement was able to locate the lowest energy structures yet reported, and significantly outperformed a pure torsional Monte Carlo and a genetic algorithm‐based search. Furthermore, we also demonstrate the utility of l‐LMOD combined with random translation/rotation of a ligand for the extremely difficult problem of docking flexible ligands into flexible protein binding sites on a system that includes 9‐deaza‐guanine‐based inhibitors docked into the flexible biding site of PNP. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 1671–1684, 1999