Jörg Weiser

Bio: Jörg Weiser is an academic researcher from Columbia University. The author has contributed to research in topics: Van der Waals surface & Gaussian. The author has an hindex of 4, co-authored 4 publications receiving 926 citations.

Approximate atomic surfaces from linear combinations of pairwise overlaps (lcpo)

Abstract: A fast analytical formula was derived for the calculation of approximate atomic and molecular van der Waals (vdWSA), and solvent-accessible surface areas (SASAs), as well as the first and second derivatives of these quantities with respect to atomic coordinates. This method makes use of linear combinations of terms composed from pairwise overlaps of hard spheres; therefore, we term this the LCPO method for linear combination of pairwise overlaps. For higher performance, neighbor-list reduction (NLR) was applied as a preprocessing step. Eighteen compounds of different sizes (8–2366 atoms) and classes (organic, proteins, DNA, and various complexes) were chosen as representative test cases. LCPO/NLR computed the SASA and first derivatives of penicillopepsin, a protein with 2366 atoms, in 0.87 s (0.22 s for the creation of the neighbor list, 0.35 s for NLR, and 0.30 s for SASA and first derivatives) on an SGI R10000/194 Mhz processor. This appears comparable to or better than timings reported previously for other algorithms. The vdWSAs were in good agreement with the numerical results: relative errors for total molecular surface areas ranged from 0.1 to 2.0% and average absolute atomic surface area deviations from 0.3 to 0.7 A2. For SASAs without NLR, the LCPO method exhibited relative errors in the range of 0.4–9.2% for total molecular surface areas and average absolute atomic surface area deviations of 2.0–2.7 A2; with NLR the relative molecular errors ranged from 0.1 to 7.8% and the average absolute atomic surface area deviation from 1.6 to 3.0 A2. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 217–230, 1999

Optimization of Gaussian surface calculations and extension to solvent-accessible surface areas.

Abstract: We explored the use of several breadth-first and depth-first algorithms for the computation of Gaussian atomic and molecular surface areas. Our results for whole-molecule van der Waals surface areas (vdWSAs) were 10 times more accurate in relative error, relative to actual hard-sphere areas, than those reported by earlier workers. We were also able to extend the method to the computation of solvent-accessible surface areas (SASAs). This was made possible by an appropriate combination of algorithms, parameters, and preprocessing steps. For united-atom 3app, a 2366-atom protein, we obtained an average absolute atomic error of 1.16 A2 with respect to the hard-sphere atomic SASA results in 7 s of CPU time on an R10000/194 MHz processor. Speed and accuracy were both optimized for SASA by the use of neighbor-list reduction (NLR), buried-atom elimination (BAE), and a depth-first search of the tree of atomic intersections. Accuracy was further optimized by the application of atom type specific parameters to the raw Gaussian results. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 688–703, 1999

Neighbor-list reduction: Optimization for computation of molecular van der Waals and solvent-accessible surface areas

Abstract: A general, fast, and exact optimization, called neighbor-list reduction (NLR), is presented, which can be used to accelerate the computation of hard-sphere molecular surface areas. NLR allows selected neighbors of a central atom to be removed from the computation in a preprocessing step, thus allowing the calculation of the atom's surface area to proceed with a shorter list of neighbors. The atoms removed are those having intersections with the central atom falling entirely within unions of other atoms' intersections with the central atom. We describe explicit methods for two levels of neighbor-list reduction: 3NLR considers three hard spheres at a time—the central atom, the candidate for removal, and one other neighbor; whereas 4NLR considers two other neighbors. We demonstrate the correctness and efficiency of this optimization by means of a modified version of the NACCESS program, which computes atomic and molecular surface areas numerically. As test cases we used compounds of different size and class, with and without explicit hydrogens. When van der Waals surface (vdWSA) is computed, the NLR methods reduce the length of the neighbor list by as much as 41%; when solvent-accessible surface area (SASA) is computed, the reduction is as great as 74%. The overall speed improvement due to these reductions is a factor of only about 1.2 for vdWSA, but is about 2.0 for the computation of SASA, in the context of this particular program. All 39,554 calculated atomic surface areas (vdWSA and SASA) were found to be identical to within 0.001 A2 to those obtained without NLR. © 1998 John Wiley & Sons, Inc. J Comput Chem 19: 797–808, 1998

Fast, approximate algorithm for detection of solvent-inaccessible atoms

Abstract: Up to about half of the atoms in biopolymers are inaccessible to solvents. If such atoms can be rapidly identified, time can be saved in the subsequent computation of atomic surface areas. A quick, approximate method, termed buried atom elimination (BAE), was developed for the detection of such atoms. Following the literature, the method makes use of a Gaussian function to calculate the neighbor density in four tetrahedral directions in 3-dimensional space, sometimes twice with different orientations. In macromolecules, our method detects between 63 and 81% of the buried atoms but also incorrectly classifies 2–8% of the exposed atoms as buried. These misidentified atoms all have small solvent-exposed (accessible) surface areas (SASAs): their surfaces sum to a maximum of 0.5% of the molecular SASA, and their maximum atomic SASA is 5.1 A2. Using our recently reported LCPO method for computing atomic surfaces, which is one of the fastest available, the use of BAE increases the overall speed of computing the atomic SASAs by a factor of up to 1.6 for surfaces only and 1.9 when first and second derivatives are computed. BAE decreases the LCPO average absolute atomic error from about 2.3 A2 to about 1.7 A2 (average for larger compounds). BAE was introduced into the MacroModel molecular modeling package and tests show that it increases the efficiency of first- and second-derivative energy minimizations and molecular dynamics simulations without adversely affecting the stability or accuracy of the calculations. BAE parameters were developed for the most important atom types in biopolymers, based on a parameterization set of 18 compounds of different size (33–4346 atoms) and class (organics, proteins, DNA, and various complexes), consisting of a total of 23,186 atoms. ©1999 John Wiley & Sons, Inc. J Comput Chem 20, 586–596, 1999

The Amber biomolecular simulation programs

Abstract: We describe the development, current features, and some directions for future development of the Amber package of computer programs. This package evolved from a program that was constructed in the late 1970s to do Assisted Model Building with Energy Refinement, and now contains a group of programs embodying a number of powerful tools of modern computational chemistry, focused on molecular dynamics and free energy calculations of proteins, nucleic acids, and carbohydrates.

PTRAJ and CPPTRAJ: Software for Processing and Analysis of Molecular Dynamics Trajectory Data

Abstract: We describe PTRAJ and its successor CPPTRAJ, two complementary, portable, and freely available computer programs for the analysis and processing of time series of three-dimensional atomic positions (i.e., coordinate trajectories) and the data therein derived. Common tools include the ability to manipulate the data to convert among trajectory formats, process groups of trajectories generated with ensemble methods (e.g., replica exchange molecular dynamics), image with periodic boundary conditions, create average structures, strip subsets of the system, and perform calculations such as RMS fitting, measuring distances, B-factors, radii of gyration, radial distribution functions, and time correlations, among other actions and analyses. Both the PTRAJ and CPPTRAJ programs and source code are freely available under the GNU General Public License version 3 and are currently distributed within the AmberTools 12 suite of support programs that make up part of the Amber package of computer programs (see http://ambe...

Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations.

Abstract: The Molecular Mechanics/Poisson−Boltzmann Surface Area (MM/PBSA) and the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) methods calculate binding free energies for macromolecules by combining molecular mechanics calculations and continuum solvation models. To systematically evaluate the performance of these methods, we report here an extensive study of 59 ligands interacting with six different proteins. First, we explored the effects of the length of the molecular dynamics (MD) simulation, ranging from 400 to 4800 ps, and the solute dielectric constant (1, 2, or 4) on the binding free energies predicted by MM/PBSA. The following three important conclusions could be observed: (1) MD simulation length has an obvious impact on the predictions, and longer MD simulation is not always necessary to achieve better predictions. (2) The predictions are quite sensitive to the solute dielectric constant, and this parameter should be carefully determined according to the characteristics of the protein/lig...