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T.P. Straatsma

Bio: T.P. Straatsma is an academic researcher from Pacific Northwest National Laboratory. The author has contributed to research in topics: Active site & Massively parallel. The author has an hindex of 17, co-authored 25 publications receiving 5586 citations. Previous affiliations of T.P. Straatsma include Environmental Molecular Sciences Laboratory & United States Department of Energy.

Papers
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Journal ArticleDOI
TL;DR: An overview of NWChem is provided focusing primarily on the core theoretical modules provided by the code and their parallel performance, as well as Scalable parallel implementations and modular software design enable efficient utilization of current computational architectures.

4,666 citations

Journal ArticleDOI
TL;DR: The design and some implementation details of the overall NWChem architecture facilitates rapid development and portability of fully distributed application modules and shows performance of a few of the modules within NWChem.

726 citations

Journal ArticleDOI
TL;DR: A molecular model for the rough LPS of Pseudomonas aeruginosa has been designed based on experimentally determined structural information and an electrostatic model was developed based on Hartree-Fock SCF calculations of the complete LPS molecule to obtain partial atomic charges.

110 citations

Journal ArticleDOI
TL;DR: Two 1-ns molecular dynamics simulations have been carried out on completely hydrated models of the HIV-1 integrase catalytic domain, and predict that the region of the active site that is missing in the published crystal structures has (at the time of this work) more secondary structure than previously thought.

76 citations

Journal ArticleDOI
01 Dec 2005-Proteins
TL;DR: An ensemble of receptor conformations generated from a molecular dynamics simulation for molecular docking is examined, finding that a useful way to identify the correctly docked structure was to locate the structure that appeared most frequently as the lowest energy structure in the docking experiments to different snapshots.
Abstract: Even if the structure of a receptor has been determined experimentally, it may not be a conformation to which a ligand would bind when induced fit effects are significant. Molecular docking using such a receptor structure may thus fail to recognize a ligand to which the receptor can bind with reasonable affinity. Here, we examine one way to alleviate this problem by using an ensemble of receptor conformations generated from a molecular dynamics simulation for molecular docking. Two molecular dynamics simulations were conducted to generate snapshots for protein kinase A: one with the ligand bound, the other without. The ligand, balanol, was then docked to conformations of the receptors presented by these trajectories. The Lamarckian genetic algorithm in Autodock [Goodsell et al. J Mol Recognit 1996;9(1):1-5; Morris et al. J Comput Chem 1998;19(14):1639-1662] was used in the docking. Three ligand models were used: rigid, flexible, and flexible with torsional potentials. When the snapshots were taken from the molecular dynamics simulation of the protein-ligand complex, the correct docking structure could be recovered easily by the docking algorithm in all cases. This was an easier case for challenging the docking algorithm because, by using the structure of the protein in a protein-ligand complex, one essentially assumed that the protein already had a pocket to which the ligand can fit well. However, when the snapshots were taken from the ligand-free protein simulation, which is more useful for a practical application when the structure of the protein-ligand complex is not known, several clusters of structures were found. Of the 10 docking runs for each snapshot, at least one structure was close to the correctly docked structure when the flexible-ligand models were used. We found that a useful way to identify the correctly docked structure was to locate the structure that appeared most frequently as the lowest energy structure in the docking experiments to different snapshots.

70 citations


Cited by
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Journal ArticleDOI
TL;DR: The M06-2X meta-exchange correlation function is proposed in this paper, which is parametrized including both transition metals and nonmetals, and is a high-non-locality functional with double the amount of nonlocal exchange.
Abstract: We present two new hybrid meta exchange- correlation functionals, called M06 and M06-2X. The M06 functional is parametrized including both transition metals and nonmetals, whereas the M06-2X functional is a high-nonlocality functional with double the amount of nonlocal exchange (2X), and it is parametrized only for nonmetals.The functionals, along with the previously published M06-L local functional and the M06-HF full-Hartree–Fock functionals, constitute the M06 suite of complementary functionals. We assess these four functionals by comparing their performance to that of 12 other functionals and Hartree–Fock theory for 403 energetic data in 29 diverse databases, including ten databases for thermochemistry, four databases for kinetics, eight databases for noncovalent interactions, three databases for transition metal bonding, one database for metal atom excitation energies, and three databases for molecular excitation energies. We also illustrate the performance of these 17 methods for three databases containing 40 bond lengths and for databases containing 38 vibrational frequencies and 15 vibrational zero point energies. We recommend the M06-2X functional for applications involving main-group thermochemistry, kinetics, noncovalent interactions, and electronic excitation energies to valence and Rydberg states. We recommend the M06 functional for application in organometallic and inorganometallic chemistry and for noncovalent interactions.

22,326 citations

Journal ArticleDOI
TL;DR: QUANTUM ESPRESSO as discussed by the authors is an integrated suite of computer codes for electronic-structure calculations and materials modeling, based on density functional theory, plane waves, and pseudopotentials (norm-conserving, ultrasoft, and projector-augmented wave).
Abstract: QUANTUM ESPRESSO is an integrated suite of computer codes for electronic-structure calculations and materials modeling, based on density-functional theory, plane waves, and pseudopotentials (norm-conserving, ultrasoft, and projector-augmented wave). The acronym ESPRESSO stands for opEn Source Package for Research in Electronic Structure, Simulation, and Optimization. It is freely available to researchers around the world under the terms of the GNU General Public License. QUANTUM ESPRESSO builds upon newly-restructured electronic-structure codes that have been developed and tested by some of the original authors of novel electronic-structure algorithms and applied in the last twenty years by some of the leading materials modeling groups worldwide. Innovation and efficiency are still its main focus, with special attention paid to massively parallel architectures, and a great effort being devoted to user friendliness. QUANTUM ESPRESSO is evolving towards a distribution of independent and interoperable codes in the spirit of an open-source project, where researchers active in the field of electronic-structure calculations are encouraged to participate in the project by contributing their own codes or by implementing their own ideas into existing codes.

19,985 citations

Journal ArticleDOI
TL;DR: An overview of the CHARMM program as it exists today is provided with an emphasis on developments since the publication of the original CHARMM article in 1983.
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.

7,035 citations

Journal ArticleDOI
TL;DR: A range of new simulation algorithms and features developed during the past 4 years are presented, leading up to the GROMACS 4.5 software package, which provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations.
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.

6,029 citations

Journal ArticleDOI
TL;DR: The work presented here details the Avogadro library, which is a framework providing a code library and application programming interface (API) with three-dimensional visualization capabilities; and has direct applications to research and education in the fields of chemistry, physics, materials science, and biology.
Abstract: The Avogadro project has developed an advanced molecule editor and visualizer designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas. It offers flexible, high quality rendering, and a powerful plugin architecture. Typical uses include building molecular structures, formatting input files, and analyzing output of a wide variety of computational chemistry packages. By using the CML file format as its native document type, Avogadro seeks to enhance the semantic accessibility of chemical data types. The work presented here details the Avogadro library, which is a framework providing a code library and application programming interface (API) with three-dimensional visualization capabilities; and has direct applications to research and education in the fields of chemistry, physics, materials science, and biology. The Avogadro application provides a rich graphical interface using dynamically loaded plugins through the library itself. The application and library can each be extended by implementing a plugin module in C++ or Python to explore different visualization techniques, build/manipulate molecular structures, and interact with other programs. We describe some example extensions, one which uses a genetic algorithm to find stable crystal structures, and one which interfaces with the PackMol program to create packed, solvated structures for molecular dynamics simulations. The 1.0 release series of Avogadro is the main focus of the results discussed here. Avogadro offers a semantic chemical builder and platform for visualization and analysis. For users, it offers an easy-to-use builder, integrated support for downloading from common databases such as PubChem and the Protein Data Bank, extracting chemical data from a wide variety of formats, including computational chemistry output, and native, semantic support for the CML file format. For developers, it can be easily extended via a powerful plugin mechanism to support new features in organic chemistry, inorganic complexes, drug design, materials, biomolecules, and simulations. Avogadro is freely available under an open-source license from http://avogadro.openmolecules.net .

5,816 citations