Peter S. Shenkin

Bio: Peter S. Shenkin is an academic researcher from Columbia University. The author has contributed to research in topics: Solvation & Van der Waals surface. The author has an hindex of 12, co-authored 14 publications receiving 2985 citations. Previous affiliations of Peter S. Shenkin include Baylor College of Medicine.

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

The GB/SA Continuum Model for Solvation. A Fast Analytical Method for the Calculation of Approximate Born Radii

Abstract: Atomic Born radii (α) are used in the generalized Born (GB) equation to calculate approximations to the electrical polarization component (Gpol) of solvation free energy. We present here a simple analytical formula for calculating Born radii rapidly and with useful accuracy. The new function is based on an atomic pairwise rij-4 treatment and contains several empirically determined parameters that were established by optimization against a data set of >10 000 accurate Born radii computed numerically using the Poisson equation on a diverse group of organic molecules, molecular complexes, oligopeptides, and a small protein. Coupling this new Born radius calculation with the previously described GB/SA solvation treatment provides a fully analytical solvation model that is computationally efficient in comparison with traditional molecular solvent models and also affords first and second derivatives. Tests with the GB/SA model and Born radii calculated with our new analytical function and with the accurate but ...

Predicting antibody hypervariable loop conformation. I. Ensembles of random conformations for ringlike structures.

Abstract: One approach to finding the conformation of minimum energy for a complicated molecule is to perform energy minimization, perhaps coupled to more exhaustive search procedures such as dynamics or Monte Carlo sampling, from many starting conformation. Where there are geometric constraints on the conformations, as in a ring molecule, or a variable loop starting and ending in known constant regions of one of a series of homologous proteins, rapidly generating many such starting conformations, all satisfying the constraints, has been a problem in the past. We have devised an algorithm, which we call random tweak, which performs this task in the context of a torsional description of a molecule, and have used it to model the backbones of the six CDRs (complementarity determining regions) of the immunoglobulin MCPC603. These range in size from 5 to 19 residues, and have from 8 to 36 variable dihedral angles. Ensembles of 100 properly closed backbone structures for each CDR were generated under several conditions of van der Waals screening internally and against the rest of the molecule, and ensembles of 1000 were generated for selected CDRs. These structure “libraries” reveal how the geometry at the base of a CDR and the topography of the surrounding protein surface restrict the region of space that a given CDR can occupy. In accord with simple notions of chain molecule statistics, the more highly extended a CDR at its base, the more similar the possible structures and the fewer that are necessary to span the conformational space. Energy minimization and molecular dynamics studies (reported elsewhere) using these libraries to furnish starting conformations show that, as the number of residues in a CDR goes from five to nine, the number of randomly generated structures necessary to ensure that low-lying energetic minima, such as the native conformation, will be found several times goes from a few tens to a few hundred. Some of the spatial features of an ensemble of random conformations are implicit in the histogram of the rms atomic displacements calculated for all the pairs in the ensemble. The random tweak method is carried out by setting each dihederal angle on the main chain of the variable fragment to a random value, then using an iterated linearized Lagrange multiplier technique to enforce the geometric constraints with the minimal conformational perturbation. The time required for the algorithm is linear in fragment length, and the resulting ability of the method to handle large loops makes it especially applicable to the modeling of homologous proteins. In most cases, hundreds of acceptable structures could be generated in a few hours on a VAX 11/780. Where van der Waals screening against fixed atoms need not be performed, as for isolated ring molecules, generation times go down by an order of magnitude or more.

Cluster analysis of molecular conformations

Abstract: We describe a method for locating clusters of geometrically similar conformers in ensembles of chemical conformations. We first calculate the pairwise interconformational distance matrix in either torsional or Cartesian space and then use an agglomerative, single-link clustering method to define a hierarchy of clusterings in the same space. Especially good clusterings are distinguished by high values of the separation ratio: the ratio of the shortest intercluster distance to the characteristic threshold distance defining the clustering. We also discuss other statistics. The method has been embodied in a program called XCluster, which can display the distance matrix, the hierarchy of clusterings, and the clustering statistics in a variety of formats. XCluster can also write out the clustered conformations for subsequent or simultaneous viewing with a molecular visualization program. We demonstrate the sorts of insight that this approach affords with examples obtained from conformational search and molecular dynamics procedures. © 1994 by John Wiley & Sons, Inc.

Solvation Free Energies of Peptides: Comparison of Approximate Continuum Solvation Models with Accurate Solution of the Poisson−Boltzmann Equation

Abstract: We have compared solvation free energies obtained from a number of approximate solvation models with an accurate solution of the Poisson−Boltzmann equation for a large data set of peptide structure...

Quantum mechanical continuum solvation models.

Abstract: 6.2.2. Definition of Effective Properties 3064 6.3. Response Properties to Magnetic Fields 3066 6.3.1. Nuclear Shielding 3066 6.3.2. Indirect Spin−Spin Coupling 3067 6.3.3. EPR Parameters 3068 6.4. Properties of Chiral Systems 3069 6.4.1. Electronic Circular Dichroism (ECD) 3069 6.4.2. Optical Rotation (OR) 3069 6.4.3. VCD and VROA 3070 7. Continuum and Discrete Models 3071 7.1. Continuum Methods within MD and MC Simulations 3072

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.

CHARMM: the biomolecular simulation program.

Abstract: CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecu- lar simulation program. It has been developed over the last three decades with a primary focus on molecules of bio- logical interest, including proteins, peptides, lipids, nucleic acids, carbohydrates, and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estima- tors, molecular minimization, dynamics, and analysis techniques, and model-building capabilities. The CHARMM program is applicable to problems involving a much broader class of many-particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numer- ous platforms in both serial and parallel architectures. This article provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM article in 1983.

Gromacs 4.5

Abstract: Motivation: Molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources. Results: Here, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations. Availability: GROMACS is an open source and free software available from http://www.gromacs.org. Contact: erik.lindahl@scilifelab.se Supplementary information:Supplementary data are available at Bioinformatics online.

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...