Molecular robots with sensors and intelligence.
Hagiya, Masami; Konagaya, Akihiko; Kobayashi, Satoshi; Saito, Hirohide; Murata, Satoshi
2014-06-17
CONSPECTUS: What we can call a molecular robot is a set of molecular devices such as sensors, logic gates, and actuators integrated into a consistent system. The molecular robot is supposed to react autonomously to its environment by receiving molecular signals and making decisions by molecular computation. Building such a system has long been a dream of scientists; however, despite extensive efforts, systems having all three functions (sensing, computation, and actuation) have not been realized yet. This Account introduces an ongoing research project that focuses on the development of molecular robotics funded by MEXT (Ministry of Education, Culture, Sports, Science and Technology, Japan). This 5 year project started in July 2012 and is titled "Development of Molecular Robots Equipped with Sensors and Intelligence". The major issues in the field of molecular robotics all correspond to a feedback (i.e., plan-do-see) cycle of a robotic system. More specifically, these issues are (1) developing molecular sensors capable of handling a wide array of signals, (2) developing amplification methods of signals to drive molecular computing devices, (3) accelerating molecular computing, (4) developing actuators that are controllable by molecular computers, and (5) providing bodies of molecular robots encapsulating the above molecular devices, which implement the conformational changes and locomotion of the robots. In this Account, the latest contributions to the project are reported. There are four research teams in the project that specialize on sensing, intelligence, amoeba-like actuation, and slime-like actuation, respectively. The molecular sensor team is focusing on the development of molecular sensors that can handle a variety of signals. This team is also investigating methods to amplify signals from the molecular sensors. The molecular intelligence team is developing molecular computers and is currently focusing on a new photochemical technology for accelerating DNA-based computations. They also introduce novel computational models behind various kinds of molecular computers necessary for designing such computers. The amoeba robot team aims at constructing amoeba-like robots. The team is trying to incorporate motor proteins, including kinesin and microtubules (MTs), for use as actuators implemented in a liposomal compartment as a robot body. They are also developing a methodology to link DNA-based computation and molecular motor control. The slime robot team focuses on the development of slime-like robots. The team is evaluating various gels, including DNA gel and BZ gel, for use as actuators, as well as the body material to disperse various molecular devices in it. They also try to control the gel actuators by DNA signals coming from molecular computers.
NASA Technical Reports Server (NTRS)
Srivastava, Deepak; Menon, Madhu; Cho, Kyeongjae; Biegel, Bryan (Technical Monitor)
2001-01-01
The role of computational nanotechnology in developing next generation of multifunctional materials, molecular scale electronic and computing devices, sensors, actuators, and machines is described through a brief review of enabling computational techniques and few recent examples derived from computer simulations of carbon nanotube based molecular nanotechnology.
Federal Register 2010, 2011, 2012, 2013, 2014
2013-09-30
... Generation Risk Assessment: Incorporation of Recent Advances in Molecular, Computational, and Systems Biology..., Computational, and Systems Biology [External Review Draft]'' (EPA/600/R-13/214A). EPA is also announcing that... Advances in Molecular, Computational, and Systems Biology [External Review Draft]'' is available primarily...
Federal Register 2010, 2011, 2012, 2013, 2014
2013-11-13
... Generation Risk Assessment: Incorporation of Recent Advances in Molecular, Computational, and Systems Biology... Generation Risk Assessment: Incorporation of Recent Advances in Molecular, Computational, and Systems Biology..., computational, and systems biology data can better inform risk assessment. This draft document is available for...
In vitro molecular machine learning algorithm via symmetric internal loops of DNA.
Lee, Ji-Hoon; Lee, Seung Hwan; Baek, Christina; Chun, Hyosun; Ryu, Je-Hwan; Kim, Jin-Woo; Deaton, Russell; Zhang, Byoung-Tak
2017-08-01
Programmable biomolecules, such as DNA strands, deoxyribozymes, and restriction enzymes, have been used to solve computational problems, construct large-scale logic circuits, and program simple molecular games. Although studies have shown the potential of molecular computing, the capability of computational learning with DNA molecules, i.e., molecular machine learning, has yet to be experimentally verified. Here, we present a novel molecular learning in vitro model in which symmetric internal loops of double-stranded DNA are exploited to measure the differences between training instances, thus enabling the molecules to learn from small errors. The model was evaluated on a data set of twenty dialogue sentences obtained from the television shows Friends and Prison Break. The wet DNA-computing experiments confirmed that the molecular learning machine was able to generalize the dialogue patterns of each show and successfully identify the show from which the sentences originated. The molecular machine learning model described here opens the way for solving machine learning problems in computer science and biology using in vitro molecular computing with the data encoded in DNA molecules. Copyright © 2017. Published by Elsevier B.V.
Magnetic polyoxometalates: from molecular magnetism to molecular spintronics and quantum computing.
Clemente-Juan, Juan M; Coronado, Eugenio; Gaita-Ariño, Alejandro
2012-11-21
In this review we discuss the relevance of polyoxometalate (POM) chemistry to provide model objects in molecular magnetism. We present several potential applications in nanomagnetism, in particular, in molecular spintronics and quantum computing.
Computational Design of Molecularly Imprinted Polymers
NASA Astrophysics Data System (ADS)
Subrahmanyam, Sreenath; Piletsky, Sergey A.
Artificial receptors have been in use for several decades as sensor elements, in affinity separation, and as models for investigation of molecular recognition. Although there have been numerous publications on the use of molecular modeling in characterization of their affinity and selectivity, very few attempts have been made on the application of molecular modeling in computational design of synthetic receptors. This chapter discusses recent successes in the use of computational design for the development of one particular branch of synthetic receptors - molecularly imprinted polymers.
Computer-Based Molecular Modelling: Finnish School Teachers' Experiences and Views
ERIC Educational Resources Information Center
Aksela, Maija; Lundell, Jan
2008-01-01
Modern computer-based molecular modelling opens up new possibilities for chemistry teaching at different levels. This article presents a case study seeking insight into Finnish school teachers' use of computer-based molecular modelling in teaching chemistry, into the different working and teaching methods used, and their opinions about necessary…
The emerging role of cloud computing in molecular modelling.
Ebejer, Jean-Paul; Fulle, Simone; Morris, Garrett M; Finn, Paul W
2013-07-01
There is a growing recognition of the importance of cloud computing for large-scale and data-intensive applications. The distinguishing features of cloud computing and their relationship to other distributed computing paradigms are described, as are the strengths and weaknesses of the approach. We review the use made to date of cloud computing for molecular modelling projects and the availability of front ends for molecular modelling applications. Although the use of cloud computing technologies for molecular modelling is still in its infancy, we demonstrate its potential by presenting several case studies. Rapid growth can be expected as more applications become available and costs continue to fall; cloud computing can make a major contribution not just in terms of the availability of on-demand computing power, but could also spur innovation in the development of novel approaches that utilize that capacity in more effective ways. Copyright © 2013 Elsevier Inc. All rights reserved.
ERIC Educational Resources Information Center
Elmore, Donald E.; Guayasamin, Ryann C.; Kieffer, Madeleine E.
2010-01-01
As computational modeling plays an increasingly central role in biochemical research, it is important to provide students with exposure to common modeling methods in their undergraduate curriculum. This article describes a series of computer labs designed to introduce undergraduate students to energy minimization, molecular dynamics simulations,…
Using a Computer Animation to Teach High School Molecular Biology
ERIC Educational Resources Information Center
Rotbain, Yosi; Marbach-Ad, Gili; Stavy, Ruth
2008-01-01
We present an active way to use a computer animation in secondary molecular genetics class. For this purpose we developed an activity booklet that helps students to work interactively with a computer animation which deals with abstract concepts and processes in molecular biology. The achievements of the experimental group were compared with those…
Molecular computational elements encode large populations of small objects
NASA Astrophysics Data System (ADS)
Prasanna de Silva, A.; James, Mark R.; McKinney, Bernadine O. F.; Pears, David A.; Weir, Sheenagh M.
2006-10-01
Since the introduction of molecular computation, experimental molecular computational elements have grown to encompass small-scale integration, arithmetic and games, among others. However, the need for a practical application has been pressing. Here we present molecular computational identification (MCID), a demonstration that molecular logic and computation can be applied to a widely relevant issue. Examples of populations that need encoding in the microscopic world are cells in diagnostics or beads in combinatorial chemistry (tags). Taking advantage of the small size (about 1nm) and large `on/off' output ratios of molecular logic gates and using the great variety of logic types, input chemical combinations, switching thresholds and even gate arrays in addition to colours, we produce unique identifiers for members of populations of small polymer beads (about 100μm) used for synthesis of combinatorial libraries. Many millions of distinguishable tags become available. This method should be extensible to far smaller objects, with the only requirement being a `wash and watch' protocol. Our focus on converting molecular science into technology concerning analog sensors, turns to digital logic devices in the present work.
Molecular computational elements encode large populations of small objects.
de Silva, A Prasanna; James, Mark R; McKinney, Bernadine O F; Pears, David A; Weir, Sheenagh M
2006-10-01
Since the introduction of molecular computation, experimental molecular computational elements have grown to encompass small-scale integration, arithmetic and games, among others. However, the need for a practical application has been pressing. Here we present molecular computational identification (MCID), a demonstration that molecular logic and computation can be applied to a widely relevant issue. Examples of populations that need encoding in the microscopic world are cells in diagnostics or beads in combinatorial chemistry (tags). Taking advantage of the small size (about 1 nm) and large 'on/off' output ratios of molecular logic gates and using the great variety of logic types, input chemical combinations, switching thresholds and even gate arrays in addition to colours, we produce unique identifiers for members of populations of small polymer beads (about 100 microm) used for synthesis of combinatorial libraries. Many millions of distinguishable tags become available. This method should be extensible to far smaller objects, with the only requirement being a 'wash and watch' protocol. Our focus on converting molecular science into technology concerning analog sensors, turns to digital logic devices in the present work.
Introducing Molecular Life Science Students to Model Building Using Computer Simulations
ERIC Educational Resources Information Center
Aegerter-Wilmsen, Tinri; Kettenis, Dik; Sessink, Olivier; Hartog, Rob; Bisseling, Ton; Janssen, Fred
2006-01-01
Computer simulations can facilitate the building of models of natural phenomena in research, such as in the molecular life sciences. In order to introduce molecular life science students to the use of computer simulations for model building, a digital case was developed in which students build a model of a pattern formation process in…
Stochastic computing with biomolecular automata
Adar, Rivka; Benenson, Yaakov; Linshiz, Gregory; Rosner, Amit; Tishby, Naftali; Shapiro, Ehud
2004-01-01
Stochastic computing has a broad range of applications, yet electronic computers realize its basic step, stochastic choice between alternative computation paths, in a cumbersome way. Biomolecular computers use a different computational paradigm and hence afford novel designs. We constructed a stochastic molecular automaton in which stochastic choice is realized by means of competition between alternative biochemical pathways, and choice probabilities are programmed by the relative molar concentrations of the software molecules coding for the alternatives. Programmable and autonomous stochastic molecular automata have been shown to perform direct analysis of disease-related molecular indicators in vitro and may have the potential to provide in situ medical diagnosis and cure. PMID:15215499
Huang, Wei Tao; Luo, Hong Qun; Li, Nian Bing
2014-05-06
The most serious, and yet unsolved, problem of constructing molecular computing devices consists in connecting all of these molecular events into a usable device. This report demonstrates the use of Boolean logic tree for analyzing the chemical event network based on graphene, organic dye, thrombin aptamer, and Fenton reaction, organizing and connecting these basic chemical events. And this chemical event network can be utilized to implement fluorescent combinatorial logic (including basic logic gates and complex integrated logic circuits) and fuzzy logic computing. On the basis of the Boolean logic tree analysis and logic computing, these basic chemical events can be considered as programmable "words" and chemical interactions as "syntax" logic rules to construct molecular search engine for performing intelligent molecular search query. Our approach is helpful in developing the advanced logic program based on molecules for application in biosensing, nanotechnology, and drug delivery.
GPU-Accelerated Molecular Modeling Coming Of Age
Stone, John E.; Hardy, David J.; Ufimtsev, Ivan S.
2010-01-01
Graphics processing units (GPUs) have traditionally been used in molecular modeling solely for visualization of molecular structures and animation of trajectories resulting from molecular dynamics simulations. Modern GPUs have evolved into fully programmable, massively parallel co-processors that can now be exploited to accelerate many scientific computations, typically providing about one order of magnitude speedup over CPU code and in special cases providing speedups of two orders of magnitude. This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks. PMID:20675161
GPU-accelerated molecular modeling coming of age.
Stone, John E; Hardy, David J; Ufimtsev, Ivan S; Schulten, Klaus
2010-09-01
Graphics processing units (GPUs) have traditionally been used in molecular modeling solely for visualization of molecular structures and animation of trajectories resulting from molecular dynamics simulations. Modern GPUs have evolved into fully programmable, massively parallel co-processors that can now be exploited to accelerate many scientific computations, typically providing about one order of magnitude speedup over CPU code and in special cases providing speedups of two orders of magnitude. This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks. (c) 2010 Elsevier Inc. All rights reserved.
Teaching 1H NMR Spectrometry Using Computer Modeling.
ERIC Educational Resources Information Center
Habata, Yoichi; Akabori, Sadatoshi
2001-01-01
Molecular modeling by computer is used to display stereochemistry, molecular orbitals, structure of transition states, and progress of reactions. Describes new ideas for teaching 1H NMR spectroscopy using computer modeling. (Contains 12 references.) (ASK)
Symbolic programming language in molecular multicenter integral problem
NASA Astrophysics Data System (ADS)
Safouhi, Hassan; Bouferguene, Ahmed
It is well known that in any ab initio molecular orbital (MO) calculation, the major task involves the computation of molecular integrals, among which the computation of three-center nuclear attraction and Coulomb integrals is the most frequently encountered. As the molecular system becomes larger, computation of these integrals becomes one of the most laborious and time-consuming steps in molecular systems calculation. Improvement of the computational methods of molecular integrals would be indispensable to further development in computational studies of large molecular systems. To develop fast and accurate algorithms for the numerical evaluation of these integrals over B functions, we used nonlinear transformations for improving convergence of highly oscillatory integrals. These methods form the basis of new methods for solving various problems that were unsolvable otherwise and have many applications as well. To apply these nonlinear transformations, the integrands should satisfy linear differential equations with coefficients having asymptotic power series in the sense of Poincaré, which in their turn should satisfy some limit conditions. These differential equations are very difficult to obtain explicitly. In the case of molecular integrals, we used a symbolic programming language (MAPLE) to demonstrate that all the conditions required to apply these nonlinear transformation methods are satisfied. Differential equations are obtained explicitly, allowing us to demonstrate that the limit conditions are also satisfied.
Informing Mechanistic Toxicology with Computational Molecular Models
Computational molecular models of chemicals interacting with biomolecular targets provides toxicologists a valuable, affordable, and sustainable source of in silico molecular level information that augments, enriches, and complements in vitro and in vivo effo...
Logic integration of mRNA signals by an RNAi-based molecular computer.
Xie, Zhen; Liu, Siyuan John; Bleris, Leonidas; Benenson, Yaakov
2010-05-01
Synthetic in vivo molecular 'computers' could rewire biological processes by establishing programmable, non-native pathways between molecular signals and biological responses. Multiple molecular computer prototypes have been shown to work in simple buffered solutions. Many of those prototypes were made of DNA strands and performed computations using cycles of annealing-digestion or strand displacement. We have previously introduced RNA interference (RNAi)-based computing as a way of implementing complex molecular logic in vivo. Because it also relies on nucleic acids for its operation, RNAi computing could benefit from the tools developed for DNA systems. However, these tools must be harnessed to produce bioactive components and be adapted for harsh operating environments that reflect in vivo conditions. In a step toward this goal, we report the construction and implementation of biosensors that 'transduce' mRNA levels into bioactive, small interfering RNA molecules via RNA strand exchange in a cell-free Drosophila embryo lysate, a step beyond simple buffered environments. We further integrate the sensors with our RNAi 'computational' module to evaluate two-input logic functions on mRNA concentrations. Our results show how RNA strand exchange can expand the utility of RNAi computing and point toward the possibility of using strand exchange in a native biological setting.
Science | Argonne National Laboratory
Publications Researchers Postdocs Exascale Computing Institute for Molecular Engineering at Argonne Work with Scientific Publications Researchers Postdocs Exascale Computing Institute for Molecular Engineering at understand, predict, and ultimately control matter and energy at the electronic, atomic, and molecular levels
Argonne Research Library | Argonne National Laboratory
Publications Researchers Postdocs Exascale Computing Institute for Molecular Engineering at Argonne Work with Scientific Publications Researchers Postdocs Exascale Computing Institute for Molecular Engineering at IMEInstitute for Molecular Engineering JCESRJoint Center for Energy Storage Research MCSGMidwest Center for
Parallel, stochastic measurement of molecular surface area.
Juba, Derek; Varshney, Amitabh
2008-08-01
Biochemists often wish to compute surface areas of proteins. A variety of algorithms have been developed for this task, but they are designed for traditional single-processor architectures. The current trend in computer hardware is towards increasingly parallel architectures for which these algorithms are not well suited. We describe a parallel, stochastic algorithm for molecular surface area computation that maps well to the emerging multi-core architectures. Our algorithm is also progressive, providing a rough estimate of surface area immediately and refining this estimate as time goes on. Furthermore, the algorithm generates points on the molecular surface which can be used for point-based rendering. We demonstrate a GPU implementation of our algorithm and show that it compares favorably with several existing molecular surface computation programs, giving fast estimates of the molecular surface area with good accuracy.
Workshop in computational molecular biology, April 15, 1991--April 14, 1994
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tavare, S.
Funds from this award were used to the Workshop in Computational Molecular Biology, `91 Symposium entitled Interface: Computing Science and Statistics, Seattle, Washington, April 21, 1991; the Workshop in Statistical Issues in Molecular Biology held at Stanford, California, August 8, 1993; and the Session on Population Genetics a part of the 56th Annual Meeting, Institute of Mathematical Statistics, San Francisco, California, August 9, 1993.
An autonomous molecular computer for logical control of gene expression.
Benenson, Yaakov; Gil, Binyamin; Ben-Dor, Uri; Adar, Rivka; Shapiro, Ehud
2004-05-27
Early biomolecular computer research focused on laboratory-scale, human-operated computers for complex computational problems. Recently, simple molecular-scale autonomous programmable computers were demonstrated allowing both input and output information to be in molecular form. Such computers, using biological molecules as input data and biologically active molecules as outputs, could produce a system for 'logical' control of biological processes. Here we describe an autonomous biomolecular computer that, at least in vitro, logically analyses the levels of messenger RNA species, and in response produces a molecule capable of affecting levels of gene expression. The computer operates at a concentration of close to a trillion computers per microlitre and consists of three programmable modules: a computation module, that is, a stochastic molecular automaton; an input module, by which specific mRNA levels or point mutations regulate software molecule concentrations, and hence automaton transition probabilities; and an output module, capable of controlled release of a short single-stranded DNA molecule. This approach might be applied in vivo to biochemical sensing, genetic engineering and even medical diagnosis and treatment. As a proof of principle we programmed the computer to identify and analyse mRNA of disease-related genes associated with models of small-cell lung cancer and prostate cancer, and to produce a single-stranded DNA molecule modelled after an anticancer drug.
Assessment of Molecular Modeling & Simulation
DOE Office of Scientific and Technical Information (OSTI.GOV)
None
2002-01-03
This report reviews the development and applications of molecular and materials modeling in Europe and Japan in comparison to those in the United States. Topics covered include computational quantum chemistry, molecular simulations by molecular dynamics and Monte Carlo methods, mesoscale modeling of material domains, molecular-structure/macroscale property correlations like QSARs and QSPRs, and related information technologies like informatics and special-purpose molecular-modeling computers. The panel's findings include the following: The United States leads this field in many scientific areas. However, Canada has particular strengths in DFT methods and homogeneous catalysis; Europe in heterogeneous catalysis, mesoscale, and materials modeling; and Japan in materialsmore » modeling and special-purpose computing. Major government-industry initiatives are underway in Europe and Japan, notably in multi-scale materials modeling and in development of chemistry-capable ab-initio molecular dynamics codes.« less
High Performance Parallel Computational Nanotechnology
NASA Technical Reports Server (NTRS)
Saini, Subhash; Craw, James M. (Technical Monitor)
1995-01-01
At a recent press conference, NASA Administrator Dan Goldin encouraged NASA Ames Research Center to take a lead role in promoting research and development of advanced, high-performance computer technology, including nanotechnology. Manufacturers of leading-edge microprocessors currently perform large-scale simulations in the design and verification of semiconductor devices and microprocessors. Recently, the need for this intensive simulation and modeling analysis has greatly increased, due in part to the ever-increasing complexity of these devices, as well as the lessons of experiences such as the Pentium fiasco. Simulation, modeling, testing, and validation will be even more important for designing molecular computers because of the complex specification of millions of atoms, thousands of assembly steps, as well as the simulation and modeling needed to ensure reliable, robust and efficient fabrication of the molecular devices. The software for this capacity does not exist today, but it can be extrapolated from the software currently used in molecular modeling for other applications: semi-empirical methods, ab initio methods, self-consistent field methods, Hartree-Fock methods, molecular mechanics; and simulation methods for diamondoid structures. In as much as it seems clear that the application of such methods in nanotechnology will require powerful, highly powerful systems, this talk will discuss techniques and issues for performing these types of computations on parallel systems. We will describe system design issues (memory, I/O, mass storage, operating system requirements, special user interface issues, interconnects, bandwidths, and programming languages) involved in parallel methods for scalable classical, semiclassical, quantum, molecular mechanics, and continuum models; molecular nanotechnology computer-aided designs (NanoCAD) techniques; visualization using virtual reality techniques of structural models and assembly sequences; software required to control mini robotic manipulators for positional control; scalable numerical algorithms for reliability, verifications and testability. There appears no fundamental obstacle to simulating molecular compilers and molecular computers on high performance parallel computers, just as the Boeing 777 was simulated on a computer before manufacturing it.
Symplectic molecular dynamics simulations on specially designed parallel computers.
Borstnik, Urban; Janezic, Dusanka
2005-01-01
We have developed a computer program for molecular dynamics (MD) simulation that implements the Split Integration Symplectic Method (SISM) and is designed to run on specialized parallel computers. The MD integration is performed by the SISM, which analytically treats high-frequency vibrational motion and thus enables the use of longer simulation time steps. The low-frequency motion is treated numerically on specially designed parallel computers, which decreases the computational time of each simulation time step. The combination of these approaches means that less time is required and fewer steps are needed and so enables fast MD simulations. We study the computational performance of MD simulation of molecular systems on specialized computers and provide a comparison to standard personal computers. The combination of the SISM with two specialized parallel computers is an effective way to increase the speed of MD simulations up to 16-fold over a single PC processor.
NASA Astrophysics Data System (ADS)
Puzyrkov, Dmitry; Polyakov, Sergey; Podryga, Viktoriia; Markizov, Sergey
2018-02-01
At the present stage of computer technology development it is possible to study the properties and processes in complex systems at molecular and even atomic levels, for example, by means of molecular dynamics methods. The most interesting are problems related with the study of complex processes under real physical conditions. Solving such problems requires the use of high performance computing systems of various types, for example, GRID systems and HPC clusters. Considering the time consuming computational tasks, the need arises of software for automatic and unified monitoring of such computations. A complex computational task can be performed over different HPC systems. It requires output data synchronization between the storage chosen by a scientist and the HPC system used for computations. The design of the computational domain is also quite a problem. It requires complex software tools and algorithms for proper atomistic data generation on HPC systems. The paper describes the prototype of a cloud service, intended for design of atomistic systems of large volume for further detailed molecular dynamic calculations and computational management for this calculations, and presents the part of its concept aimed at initial data generation on the HPC systems.
On the computation of molecular surface correlations for protein docking using fourier techniques.
Sakk, Eric
2007-08-01
The computation of surface correlations using a variety of molecular models has been applied to the unbound protein docking problem. Because of the computational complexity involved in examining all possible molecular orientations, the fast Fourier transform (FFT) (a fast numerical implementation of the discrete Fourier transform (DFT)) is generally applied to minimize the number of calculations. This approach is rooted in the convolution theorem which allows one to inverse transform the product of two DFTs in order to perform the correlation calculation. However, such a DFT calculation results in a cyclic or "circular" correlation which, in general, does not lead to the same result as the linear correlation desired for the docking problem. In this work, we provide computational bounds for constructing molecular models used in the molecular surface correlation problem. The derived bounds are then shown to be consistent with various intuitive guidelines previously reported in the protein docking literature. Finally, these bounds are applied to different molecular models in order to investigate their effect on the correlation calculation.
ERIC Educational Resources Information Center
Hakerem, Gita; And Others
The Water and Molecular Networks (WAMNet) Project uses graduate student written Reduced Instruction Set Computing (RISC) computer simulations of the molecular structure of water to assist high school students learn about the nature of water. This study examined: (1) preconceptions concerning the molecular structure of water common among high…
Bajaj, Chandrajit; Chen, Shun-Chuan; Rand, Alexander
2011-01-01
In order to compute polarization energy of biomolecules, we describe a boundary element approach to solving the linearized Poisson-Boltzmann equation. Our approach combines several important features including the derivative boundary formulation of the problem and a smooth approximation of the molecular surface based on the algebraic spline molecular surface. State of the art software for numerical linear algebra and the kernel independent fast multipole method is used for both simplicity and efficiency of our implementation. We perform a variety of computational experiments, testing our method on a number of actual proteins involved in molecular docking and demonstrating the effectiveness of our solver for computing molecular polarization energy. PMID:21660123
Logic circuits based on molecular spider systems.
Mo, Dandan; Lakin, Matthew R; Stefanovic, Darko
2016-08-01
Spatial locality brings the advantages of computation speed-up and sequence reuse to molecular computing. In particular, molecular walkers that undergo localized reactions are of interest for implementing logic computations at the nanoscale. We use molecular spider walkers to implement logic circuits. We develop an extended multi-spider model with a dynamic environment wherein signal transmission is triggered via localized reactions, and use this model to implement three basic gates (AND, OR, NOT) and a cascading mechanism. We develop an algorithm to automatically generate the layout of the circuit. We use a kinetic Monte Carlo algorithm to simulate circuit computations, and we analyze circuit complexity: our design scales linearly with formula size and has a logarithmic time complexity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
ChemEngine: harvesting 3D chemical structures of supplementary data from PDF files.
Karthikeyan, Muthukumarasamy; Vyas, Renu
2016-01-01
Digital access to chemical journals resulted in a vast array of molecular information that is now available in the supplementary material files in PDF format. However, extracting this molecular information, generally from a PDF document format is a daunting task. Here we present an approach to harvest 3D molecular data from the supporting information of scientific research articles that are normally available from publisher's resources. In order to demonstrate the feasibility of extracting truly computable molecules from PDF file formats in a fast and efficient manner, we have developed a Java based application, namely ChemEngine. This program recognizes textual patterns from the supplementary data and generates standard molecular structure data (bond matrix, atomic coordinates) that can be subjected to a multitude of computational processes automatically. The methodology has been demonstrated via several case studies on different formats of coordinates data stored in supplementary information files, wherein ChemEngine selectively harvested the atomic coordinates and interpreted them as molecules with high accuracy. The reusability of extracted molecular coordinate data was demonstrated by computing Single Point Energies that were in close agreement with the original computed data provided with the articles. It is envisaged that the methodology will enable large scale conversion of molecular information from supplementary files available in the PDF format into a collection of ready- to- compute molecular data to create an automated workflow for advanced computational processes. Software along with source codes and instructions available at https://sourceforge.net/projects/chemengine/files/?source=navbar.Graphical abstract.
Visualizing functional motions of membrane transporters with molecular dynamics simulations.
Shaikh, Saher A; Li, Jing; Enkavi, Giray; Wen, Po-Chao; Huang, Zhijian; Tajkhorshid, Emad
2013-01-29
Computational modeling and molecular simulation techniques have become an integral part of modern molecular research. Various areas of molecular sciences continue to benefit from, indeed rely on, the unparalleled spatial and temporal resolutions offered by these technologies, to provide a more complete picture of the molecular problems at hand. Because of the continuous development of more efficient algorithms harvesting ever-expanding computational resources, and the emergence of more advanced and novel theories and methodologies, the scope of computational studies has expanded significantly over the past decade, now including much larger molecular systems and far more complex molecular phenomena. Among the various computer modeling techniques, the application of molecular dynamics (MD) simulation and related techniques has particularly drawn attention in biomolecular research, because of the ability of the method to describe the dynamical nature of the molecular systems and thereby to provide a more realistic representation, which is often needed for understanding fundamental molecular properties. The method has proven to be remarkably successful in capturing molecular events and structural transitions highly relevant to the function and/or physicochemical properties of biomolecular systems. Herein, after a brief introduction to the method of MD, we use a number of membrane transport proteins studied in our laboratory as examples to showcase the scope and applicability of the method and its power in characterizing molecular motions of various magnitudes and time scales that are involved in the function of this important class of membrane proteins.
Visualizing Functional Motions of Membrane Transporters with Molecular Dynamics Simulations
2013-01-01
Computational modeling and molecular simulation techniques have become an integral part of modern molecular research. Various areas of molecular sciences continue to benefit from, indeed rely on, the unparalleled spatial and temporal resolutions offered by these technologies, to provide a more complete picture of the molecular problems at hand. Because of the continuous development of more efficient algorithms harvesting ever-expanding computational resources, and the emergence of more advanced and novel theories and methodologies, the scope of computational studies has expanded significantly over the past decade, now including much larger molecular systems and far more complex molecular phenomena. Among the various computer modeling techniques, the application of molecular dynamics (MD) simulation and related techniques has particularly drawn attention in biomolecular research, because of the ability of the method to describe the dynamical nature of the molecular systems and thereby to provide a more realistic representation, which is often needed for understanding fundamental molecular properties. The method has proven to be remarkably successful in capturing molecular events and structural transitions highly relevant to the function and/or physicochemical properties of biomolecular systems. Herein, after a brief introduction to the method of MD, we use a number of membrane transport proteins studied in our laboratory as examples to showcase the scope and applicability of the method and its power in characterizing molecular motions of various magnitudes and time scales that are involved in the function of this important class of membrane proteins. PMID:23298176
Teaching Molecular Biology with Microcomputers.
ERIC Educational Resources Information Center
Reiss, Rebecca; Jameson, David
1984-01-01
Describes a series of computer programs that use simulation and gaming techniques to present the basic principles of the central dogma of molecular genetics, mutation, and the genetic code. A history of discoveries in molecular biology is presented and the evolution of these computer assisted instructional programs is described. (MBR)
BetaCavityWeb: a webserver for molecular voids and channels
Kim, Jae-Kwan; Cho, Youngsong; Lee, Mokwon; Laskowski, Roman A.; Ryu, Seong Eon; Sugihara, Kokichi; Kim, Deok-Soo
2015-01-01
Molecular cavities, which include voids and channels, are critical for molecular function. We present a webserver, BetaCavityWeb, which computes these cavities for a given molecular structure and a given spherical probe, and reports their geometrical properties: volume, boundary area, buried area, etc. The server's algorithms are based on the Voronoi diagram of atoms and its derivative construct: the beta-complex. The correctness of the computed result and computational efficiency are both mathematically guaranteed. BetaCavityWeb is freely accessible at the Voronoi Diagram Research Center (VDRC) (http://voronoi.hanyang.ac.kr/betacavityweb). PMID:25904629
Computational Nanotechnology Molecular Electronics, Materials and Machines
NASA Technical Reports Server (NTRS)
Srivastava, Deepak; Biegel, Bryan A. (Technical Monitor)
2002-01-01
This presentation covers research being performed on computational nanotechnology, carbon nanotubes and fullerenes at the NASA Ames Research Center. Topics cover include: nanomechanics of nanomaterials, nanotubes and composite materials, molecular electronics with nanotube junctions, kinky chemistry, and nanotechnology for solid-state quantum computers using fullerenes.
Molecular Modeling and Computational Chemistry at Humboldt State University.
ERIC Educational Resources Information Center
Paselk, Richard A.; Zoellner, Robert W.
2002-01-01
Describes a molecular modeling and computational chemistry (MM&CC) facility for undergraduate instruction and research at Humboldt State University. This facility complex allows the introduction of MM&CC throughout the chemistry curriculum with tailored experiments in general, organic, and inorganic courses as well as a new molecular modeling…
An autonomous molecular computer for logical control of gene expression
Benenson, Yaakov; Gil, Binyamin; Ben-Dor, Uri; Adar, Rivka; Shapiro, Ehud
2013-01-01
Early biomolecular computer research focused on laboratory-scale, human-operated computers for complex computational problems1–7. Recently, simple molecular-scale autonomous programmable computers were demonstrated8–15 allowing both input and output information to be in molecular form. Such computers, using biological molecules as input data and biologically active molecules as outputs, could produce a system for ‘logical’ control of biological processes. Here we describe an autonomous biomolecular computer that, at least in vitro, logically analyses the levels of messenger RNA species, and in response produces a molecule capable of affecting levels of gene expression. The computer operates at a concentration of close to a trillion computers per microlitre and consists of three programmable modules: a computation module, that is, a stochastic molecular automaton12–17; an input module, by which specific mRNA levels or point mutations regulate software molecule concentrations, and hence automaton transition probabilities; and an output module, capable of controlled release of a short single-stranded DNA molecule. This approach might be applied in vivo to biochemical sensing, genetic engineering and even medical diagnosis and treatment. As a proof of principle we programmed the computer to identify and analyse mRNA of disease-related genes18–22 associated with models of small-cell lung cancer and prostate cancer, and to produce a single-stranded DNA molecule modelled after an anticancer drug. PMID:15116117
Agent-Based Modeling in Molecular Systems Biology.
Soheilypour, Mohammad; Mofrad, Mohammad R K
2018-07-01
Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. While several different mathematical and computational methods are developed to study molecular systems at different spatiotemporal scales, there is still a need for methods that bridge the gap between spatially-detailed and computationally-efficient approaches. In this review, we summarize the capabilities of agent-based modeling (ABM) as an emerging molecular systems biology technique that provides researchers with a new tool in exploring the dynamics of molecular systems/pathways in health and disease. © 2018 WILEY Periodicals, Inc.
Phase computations and phase models for discrete molecular oscillators.
Suvak, Onder; Demir, Alper
2012-06-11
Biochemical oscillators perform crucial functions in cells, e.g., they set up circadian clocks. The dynamical behavior of oscillators is best described and analyzed in terms of the scalar quantity, phase. A rigorous and useful definition for phase is based on the so-called isochrons of oscillators. Phase computation techniques for continuous oscillators that are based on isochrons have been used for characterizing the behavior of various types of oscillators under the influence of perturbations such as noise. In this article, we extend the applicability of these phase computation methods to biochemical oscillators as discrete molecular systems, upon the information obtained from a continuous-state approximation of such oscillators. In particular, we describe techniques for computing the instantaneous phase of discrete, molecular oscillators for stochastic simulation algorithm generated sample paths. We comment on the accuracies and derive certain measures for assessing the feasibilities of the proposed phase computation methods. Phase computation experiments on the sample paths of well-known biological oscillators validate our analyses. The impact of noise that arises from the discrete and random nature of the mechanisms that make up molecular oscillators can be characterized based on the phase computation techniques proposed in this article. The concept of isochrons is the natural choice upon which the phase notion of oscillators can be founded. The isochron-theoretic phase computation methods that we propose can be applied to discrete molecular oscillators of any dimension, provided that the oscillatory behavior observed in discrete-state does not vanish in a continuous-state approximation. Analysis of the full versatility of phase noise phenomena in molecular oscillators will be possible if a proper phase model theory is developed, without resorting to such approximations.
Phase computations and phase models for discrete molecular oscillators
2012-01-01
Background Biochemical oscillators perform crucial functions in cells, e.g., they set up circadian clocks. The dynamical behavior of oscillators is best described and analyzed in terms of the scalar quantity, phase. A rigorous and useful definition for phase is based on the so-called isochrons of oscillators. Phase computation techniques for continuous oscillators that are based on isochrons have been used for characterizing the behavior of various types of oscillators under the influence of perturbations such as noise. Results In this article, we extend the applicability of these phase computation methods to biochemical oscillators as discrete molecular systems, upon the information obtained from a continuous-state approximation of such oscillators. In particular, we describe techniques for computing the instantaneous phase of discrete, molecular oscillators for stochastic simulation algorithm generated sample paths. We comment on the accuracies and derive certain measures for assessing the feasibilities of the proposed phase computation methods. Phase computation experiments on the sample paths of well-known biological oscillators validate our analyses. Conclusions The impact of noise that arises from the discrete and random nature of the mechanisms that make up molecular oscillators can be characterized based on the phase computation techniques proposed in this article. The concept of isochrons is the natural choice upon which the phase notion of oscillators can be founded. The isochron-theoretic phase computation methods that we propose can be applied to discrete molecular oscillators of any dimension, provided that the oscillatory behavior observed in discrete-state does not vanish in a continuous-state approximation. Analysis of the full versatility of phase noise phenomena in molecular oscillators will be possible if a proper phase model theory is developed, without resorting to such approximations. PMID:22687330
Exploring Biomolecular Recognition by Modeling and Simulation
NASA Astrophysics Data System (ADS)
Wade, Rebecca
2007-12-01
Biomolecular recognition is complex. The balance between the different molecular properties that contribute to molecular recognition, such as shape, electrostatics, dynamics and entropy, varies from case to case. This, along with the extent of experimental characterization, influences the choice of appropriate computational approaches to study biomolecular interactions. I will present computational studies in which we aim to make concerted use of bioinformatics, biochemical network modeling and molecular simulation techniques to study protein-protein and protein-small molecule interactions and to facilitate computer-aided drug design.
Avoiding Defect Nucleation during Equilibration in Molecular Dynamics Simulations with ReaxFF
2015-04-01
respectively. All simulations are performed using the LAMMPS computer code.12 2 Fig. 1 a) Initial and b) final configurations of the molecular centers...Plimpton S. Fast parallel algorithms for short-range molecular dynamics. Comput J Phys. 1995;117:1–19. (Software available at http:// lammps .sandia.gov
The Distributed Diagonal Force Decomposition Method for Parallelizing Molecular Dynamics Simulations
Boršnik, Urban; Miller, Benjamin T.; Brooks, Bernard R.; Janežič, Dušanka
2011-01-01
Parallelization is an effective way to reduce the computational time needed for molecular dynamics simulations. We describe a new parallelization method, the distributed-diagonal force decomposition method, with which we extend and improve the existing force decomposition methods. Our new method requires less data communication during molecular dynamics simulations than replicated data and current force decomposition methods, increasing the parallel efficiency. It also dynamically load-balances the processors' computational load throughout the simulation. The method is readily implemented in existing molecular dynamics codes and it has been incorporated into the CHARMM program, allowing its immediate use in conjunction with the many molecular dynamics simulation techniques that are already present in the program. We also present the design of the Force Decomposition Machine, a cluster of personal computers and networks that is tailored to running molecular dynamics simulations using the distributed diagonal force decomposition method. The design is expandable and provides various degrees of fault resilience. This approach is easily adaptable to computers with Graphics Processing Units because it is independent of the processor type being used. PMID:21793007
Computational Nanotechnology at NASA Ames Research Center, 1996
NASA Technical Reports Server (NTRS)
Globus, Al; Bailey, David; Langhoff, Steve; Pohorille, Andrew; Levit, Creon; Chancellor, Marisa K. (Technical Monitor)
1996-01-01
Some forms of nanotechnology appear to have enormous potential to improve aerospace and computer systems; computational nanotechnology, the design and simulation of programmable molecular machines, is crucial to progress. NASA Ames Research Center has begun a computational nanotechnology program including in-house work, external research grants, and grants of supercomputer time. Four goals have been established: (1) Simulate a hypothetical programmable molecular machine replicating itself and building other products. (2) Develop molecular manufacturing CAD (computer aided design) software and use it to design molecular manufacturing systems and products of aerospace interest, including computer components. (3) Characterize nanotechnologically accessible materials of aerospace interest. Such materials may have excellent strength and thermal properties. (4) Collaborate with experimentalists. Current in-house activities include: (1) Development of NanoDesign, software to design and simulate a nanotechnology based on functionalized fullerenes. Early work focuses on gears. (2) A design for high density atomically precise memory. (3) Design of nanotechnology systems based on biology. (4) Characterization of diamonoid mechanosynthetic pathways. (5) Studies of the laplacian of the electronic charge density to understand molecular structure and reactivity. (6) Studies of entropic effects during self-assembly. Characterization of properties of matter for clusters up to sizes exhibiting bulk properties. In addition, the NAS (NASA Advanced Supercomputing) supercomputer division sponsored a workshop on computational molecular nanotechnology on March 4-5, 1996 held at NASA Ames Research Center. Finally, collaborations with Bill Goddard at CalTech, Ralph Merkle at Xerox Parc, Don Brenner at NCSU (North Carolina State University), Tom McKendree at Hughes, and Todd Wipke at UCSC are underway.
Logic integration of mRNA signals by an RNAi-based molecular computer
Xie, Zhen; Liu, Siyuan John; Bleris, Leonidas; Benenson, Yaakov
2010-01-01
Synthetic in vivo molecular ‘computers’ could rewire biological processes by establishing programmable, non-native pathways between molecular signals and biological responses. Multiple molecular computer prototypes have been shown to work in simple buffered solutions. Many of those prototypes were made of DNA strands and performed computations using cycles of annealing-digestion or strand displacement. We have previously introduced RNA interference (RNAi)-based computing as a way of implementing complex molecular logic in vivo. Because it also relies on nucleic acids for its operation, RNAi computing could benefit from the tools developed for DNA systems. However, these tools must be harnessed to produce bioactive components and be adapted for harsh operating environments that reflect in vivo conditions. In a step toward this goal, we report the construction and implementation of biosensors that ‘transduce’ mRNA levels into bioactive, small interfering RNA molecules via RNA strand exchange in a cell-free Drosophila embryo lysate, a step beyond simple buffered environments. We further integrate the sensors with our RNAi ‘computational’ module to evaluate two-input logic functions on mRNA concentrations. Our results show how RNA strand exchange can expand the utility of RNAi computing and point toward the possibility of using strand exchange in a native biological setting. PMID:20194121
NASA Astrophysics Data System (ADS)
John, Christopher; Spura, Thomas; Habershon, Scott; Kühne, Thomas D.
2016-04-01
We present a simple and accurate computational method which facilitates ab initio path-integral molecular dynamics simulations, where the quantum-mechanical nature of the nuclei is explicitly taken into account, at essentially no additional computational cost in comparison to the corresponding calculation using classical nuclei. The predictive power of the proposed quantum ring-polymer contraction method is demonstrated by computing various static and dynamic properties of liquid water at ambient conditions using density functional theory. This development will enable routine inclusion of nuclear quantum effects in ab initio molecular dynamics simulations of condensed-phase systems.
Molecular electronics: The technology of sixth generation computers
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jarvis, M.T.; Miller, R.K.
1987-01-01
In February 1986, Japan began the 6th Generation project. At the 1987 Economic Summit in Venice, Prime Minister Yashuhiro Makasone opened the project to world collaboration. A project director suggests that the 6th Generation ''may just be a turning point for human society.'' The major rationale for building molecular electronic devices is to achieve advances in computational densities and speeds. Proposed chromophore chains for molecular-scale chips, for example, could be spaced closer than today's silicone elements by a factor of almost 100. This book describes the research and proposed designs for molecular electronic devices and computers. It examines specific potentialmore » applications and the relationship to molecular electronics to silicon technology and presents the first published survey of experts on research issues, applications, and forecast of future developments and also includes market forecast. An interesting suggestion of the survey is that the chemical industry may become a significant factor in the computer industry as the sixth generation unfolds.« less
Structural biology computing: Lessons for the biomedical research sciences.
Morin, Andrew; Sliz, Piotr
2013-11-01
The field of structural biology, whose aim is to elucidate the molecular and atomic structures of biological macromolecules, has long been at the forefront of biomedical sciences in adopting and developing computational research methods. Operating at the intersection between biophysics, biochemistry, and molecular biology, structural biology's growth into a foundational framework on which many concepts and findings of molecular biology are interpreted1 has depended largely on parallel advancements in computational tools and techniques. Without these computing advances, modern structural biology would likely have remained an exclusive pursuit practiced by few, and not become the widely practiced, foundational field it is today. As other areas of biomedical research increasingly embrace research computing techniques, the successes, failures and lessons of structural biology computing can serve as a useful guide to progress in other biomedically related research fields. Copyright © 2013 Wiley Periodicals, Inc.
Using Computer Technology to Create a Revolutionary New Style of Biology.
ERIC Educational Resources Information Center
Monaghan, Peter
1993-01-01
A $13-million gift of William Gates III to the University of Washington has enabled establishment of the country's first department in molecular biotechnology, a combination of medicine and molecular biology to be practiced by researchers versed in a variety of fields, including computer science, computation, applied physics, and engineering. (MSE)
ERIC Educational Resources Information Center
Orenha, Renato P.; Galembeck, Sérgio E.
2014-01-01
This computational experiment presents qualitative molecular orbital (QMO) and computational quantum chemistry exercises of NO, NO[superscript+], and NO[superscript-]. Initially students explore several properties of the target molecules by Lewis diagrams and the QMO theory. Then, they compare qualitative conclusions with EHT and DFT calculations…
Computer-Based Semantic Network in Molecular Biology: A Demonstration.
ERIC Educational Resources Information Center
Callman, Joshua L.; And Others
This paper analyzes the hardware and software features that would be desirable in a computer-based semantic network system for representing biology knowledge. It then describes in detail a prototype network of molecular biology knowledge that has been developed using Filevision software and a Macintosh computer. The prototype contains about 100…
DNA-programmed dynamic assembly of quantum dots for molecular computation.
He, Xuewen; Li, Zhi; Chen, Muzi; Ma, Nan
2014-12-22
Despite the widespread use of quantum dots (QDs) for biosensing and bioimaging, QD-based bio-interfaceable and reconfigurable molecular computing systems have not yet been realized. DNA-programmed dynamic assembly of multi-color QDs is presented for the construction of a new class of fluorescence resonance energy transfer (FRET)-based QD computing systems. A complete set of seven elementary logic gates (OR, AND, NOR, NAND, INH, XOR, XNOR) are realized using a series of binary and ternary QD complexes operated by strand displacement reactions. The integration of different logic gates into a half-adder circuit for molecular computation is also demonstrated. This strategy is quite versatile and straightforward for logical operations and would pave the way for QD-biocomputing-based intelligent molecular diagnostics. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Adiabatic quantum computing with spin qubits hosted by molecules.
Yamamoto, Satoru; Nakazawa, Shigeaki; Sugisaki, Kenji; Sato, Kazunobu; Toyota, Kazuo; Shiomi, Daisuke; Takui, Takeji
2015-01-28
A molecular spin quantum computer (MSQC) requires electron spin qubits, which pulse-based electron spin/magnetic resonance (ESR/MR) techniques can afford to manipulate for implementing quantum gate operations in open shell molecular entities. Importantly, nuclear spins, which are topologically connected, particularly in organic molecular spin systems, are client qubits, while electron spins play a role of bus qubits. Here, we introduce the implementation for an adiabatic quantum algorithm, suggesting the possible utilization of molecular spins with optimized spin structures for MSQCs. We exemplify the utilization of an adiabatic factorization problem of 21, compared with the corresponding nuclear magnetic resonance (NMR) case. Two molecular spins are selected: one is a molecular spin composed of three exchange-coupled electrons as electron-only qubits and the other an electron-bus qubit with two client nuclear spin qubits. Their electronic spin structures are well characterized in terms of the quantum mechanical behaviour in the spin Hamiltonian. The implementation of adiabatic quantum computing/computation (AQC) has, for the first time, been achieved by establishing ESR/MR pulse sequences for effective spin Hamiltonians in a fully controlled manner of spin manipulation. The conquered pulse sequences have been compared with the NMR experiments and shown much faster CPU times corresponding to the interaction strength between the spins. Significant differences are shown in rotational operations and pulse intervals for ESR/MR operations. As a result, we suggest the advantages and possible utilization of the time-evolution based AQC approach for molecular spin quantum computers and molecular spin quantum simulators underlain by sophisticated ESR/MR pulsed spin technology.
ERIC Educational Resources Information Center
Ruddick, Kristie R.; Parrill, Abby L.; Petersen, Richard L.
2012-01-01
In this study, a computational molecular orbital theory experiment was implemented in a first-semester honors general chemistry course. Students used the GAMESS (General Atomic and Molecular Electronic Structure System) quantum mechanical software (as implemented in ChemBio3D) to optimize the geometry for various small molecules. Extended Huckel…
Spinello, Angelo; Magistrato, Alessandra
2017-08-01
Metallo-drugs have attracted enormous interest for cancer treatment. The achievements of this drug-type are summarized by the success story of cisplatin. That being said, there have been many drawbacks with its clinical use, which prompted decades worth of research efforts to move towards safer and more effective agents, either containing platinum or different metals. Areas covered: In this review, the authors provide an atomistic picture of the molecular mechanisms involving selected metallo-drugs from structural and molecular simulation studies. They also provide an omics perspective, pointing out many unsettled aspects of the most relevant families of metallo-drugs at an epigenetic level. Expert opinion: Molecular simulations are able to provide detailed information at atomistic and temporal (ps) resolutions that are rarely accessible to experiments. The increasing accuracy of computational methods and the growing performance of computational platforms, allow us to mirror wet lab experiments in silico. Consequently, the molecular mechanisms of drugs action/failure can be directly viewed on a computer screen, like a 'computational microscope', allowing us to harness this knowledge for the design of the next-generation of metallo-drugs.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bowers, Geoffrey
United States Department of Energy grant DE-FG02-10ER16128, “Computational and Spectroscopic Investigations of the Molecular Scale Structure and Dynamics of Geologically Important Fluids and Mineral-Fluid Interfaces” (Geoffrey M. Bowers, P.I.) focused on developing a molecular-scale understanding of processes that occur in fluids and at solid-fluid interfaces using the combination of spectroscopic, microscopic, and diffraction studies with molecular dynamics computer modeling. The work is intimately tied to the twin proposal at Michigan State University (DOE DE-FG02-08ER15929; same title: R. James Kirkpatrick, P.I. and A. Ozgur Yazaydin, co-P.I.).
2009-11-01
dynamics of the complex predicted by multiple molecular dynamics simulations , and discuss further structural optimization to achieve better in vivo efficacy...complex with BoNTAe and the dynamics of the complex predicted by multiple molecular dynamics simulations (MMDSs). On the basis of the 3D model, we discuss...is unlimited whereas AHP exhibited 54% inhibition under the same conditions (Table 1). Computer Simulation Twenty different molecular dynamics
NASA Astrophysics Data System (ADS)
Jain, A.
2017-08-01
Computer based method can help in discovery of leads and can potentially eliminate chemical synthesis and screening of many irrelevant compounds, and in this way, it save time as well as cost. Molecular modeling systems are powerful tools for building, visualizing, analyzing and storing models of complex molecular structure that can help to interpretate structure activity relationship. The use of various techniques of molecular mechanics and dynamics and software in Computer aided drug design along with statistics analysis is powerful tool for the medicinal chemistry to synthesis therapeutic and effective drugs with minimum side effect.
Spintronics: The molecular way
NASA Astrophysics Data System (ADS)
Cornia, Andrea; Seneor, Pierre
2017-05-01
Molecular spintronics is an interdisciplinary field at the interface between organic spintronics, molecular magnetism, molecular electronics and quantum computing, which is advancing fast and promises large technological payoffs.
Open Source Molecular Modeling
Pirhadi, Somayeh; Sunseri, Jocelyn; Koes, David Ryan
2016-01-01
The success of molecular modeling and computational chemistry efforts are, by definition, dependent on quality software applications. Open source software development provides many advantages to users of modeling applications, not the least of which is that the software is free and completely extendable. In this review we categorize, enumerate, and describe available open source software packages for molecular modeling and computational chemistry. PMID:27631126
Accessible high-throughput virtual screening molecular docking software for students and educators.
Jacob, Reed B; Andersen, Tim; McDougal, Owen M
2012-05-01
We survey low cost high-throughput virtual screening (HTVS) computer programs for instructors who wish to demonstrate molecular docking in their courses. Since HTVS programs are a useful adjunct to the time consuming and expensive wet bench experiments necessary to discover new drug therapies, the topic of molecular docking is core to the instruction of biochemistry and molecular biology. The availability of HTVS programs coupled with decreasing costs and advances in computer hardware have made computational approaches to drug discovery possible at institutional and non-profit budgets. This paper focuses on HTVS programs with graphical user interfaces (GUIs) that use either DOCK or AutoDock for the prediction of DockoMatic, PyRx, DockingServer, and MOLA since their utility has been proven by the research community, they are free or affordable, and the programs operate on a range of computer platforms.
NASA Astrophysics Data System (ADS)
Lahti, Paul M.; Motyka, Eric J.; Lancashire, Robert J.
2000-05-01
A straightforward procedure is described to combine computation of molecular vibrational modes using commonly available molecular modeling programs with visualization of the modes using advanced features of the MDL Information Systems Inc. Chime World Wide Web browser plug-in. Minor editing of experimental spectra that are stored in the JCAMP-DX format allows linkage of IR spectral frequency ranges to Chime molecular display windows. The spectra and animation files can be combined by Hypertext Markup Language programming to allow interactive linkage between experimental spectra and computationally generated vibrational displays. Both the spectra and the molecular displays can be interactively manipulated to allow the user maximum control of the objects being viewed. This procedure should be very valuable not only for aiding students through visual linkage of spectra and various vibrational animations, but also by assisting them in learning the advantages and limitations of computational chemistry by comparison to experiment.
Nanotube Heterojunctions and Endo-Fullerenes for Nanoelectronics
NASA Technical Reports Server (NTRS)
Srivastava, Deepak; Menon, M.; Andriotis, Antonis; Cho, K.; Park, Jun; Biegel, Bryan A. (Technical Monitor)
2002-01-01
Topics discussed include: (1) Light-Weight Multi-Functional Materials: Nanomechanics; Nanotubes and Composites; Thermal/Chemical/Electrical Characterization; (2) Biomimetic/Revolutionary Concepts: Evolutionary Computing and Sensing; Self-Heating Materials; (3) Central Computing System: Molecular Electronics; Materials for Quantum Bits; and (4) Molecular Machines.
Computational studies of Ras and PI3K
NASA Technical Reports Server (NTRS)
Ren, Lei; Cucinotta, Francis A.
2004-01-01
Until recently, experimental techniques in molecular cell biology have been the primary means to investigate biological risk upon space radiation. However, computational modeling provides an alternative theoretical approach, which utilizes various computational tools to simulate proteins, nucleotides, and their interactions. In this study, we are focused on using molecular mechanics (MM) and molecular dynamics (MD) to study the mechanism of protein-protein binding and to estimate the binding free energy between proteins. Ras is a key element in a variety of cell processes, and its activation of phosphoinositide 3-kinase (PI3K) is important for survival of transformed cells. Different computational approaches for this particular study are presented to calculate the solvation energies and binding free energies of H-Ras and PI3K. The goal of this study is to establish computational methods to investigate the roles of different proteins played in the cellular responses to space radiation, including modification of protein function through gene mutation, and to support the studies in molecular cell biology and theoretical kinetics models for our risk assessment project.
Grid computing in large pharmaceutical molecular modeling.
Claus, Brian L; Johnson, Stephen R
2008-07-01
Most major pharmaceutical companies have employed grid computing to expand their compute resources with the intention of minimizing additional financial expenditure. Historically, one of the issues restricting widespread utilization of the grid resources in molecular modeling is the limited set of suitable applications amenable to coarse-grained parallelization. Recent advances in grid infrastructure technology coupled with advances in application research and redesign will enable fine-grained parallel problems, such as quantum mechanics and molecular dynamics, which were previously inaccessible to the grid environment. This will enable new science as well as increase resource flexibility to load balance and schedule existing workloads.
ERIC Educational Resources Information Center
Harris, Michelle A.; Peck, Ronald F.; Colton, Shannon; Morris, Jennifer; Neto, Elias Chaibub; Kallio, Julie
2009-01-01
We conducted a controlled investigation to examine whether a combination of computer imagery and tactile tools helps introductory cell biology laboratory undergraduate students better learn about protein structure/function relationships as compared with computer imagery alone. In all five laboratory sections, students used the molecular imaging…
The impact of computer science in molecular medicine: enabling high-throughput research.
de la Iglesia, Diana; García-Remesal, Miguel; de la Calle, Guillermo; Kulikowski, Casimir; Sanz, Ferran; Maojo, Víctor
2013-01-01
The Human Genome Project and the explosion of high-throughput data have transformed the areas of molecular and personalized medicine, which are producing a wide range of studies and experimental results and providing new insights for developing medical applications. Research in many interdisciplinary fields is resulting in data repositories and computational tools that support a wide diversity of tasks: genome sequencing, genome-wide association studies, analysis of genotype-phenotype interactions, drug toxicity and side effects assessment, prediction of protein interactions and diseases, development of computational models, biomarker discovery, and many others. The authors of the present paper have developed several inventories covering tools, initiatives and studies in different computational fields related to molecular medicine: medical informatics, bioinformatics, clinical informatics and nanoinformatics. With these inventories, created by mining the scientific literature, we have carried out several reviews of these fields, providing researchers with a useful framework to locate, discover, search and integrate resources. In this paper we present an analysis of the state-of-the-art as it relates to computational resources for molecular medicine, based on results compiled in our inventories, as well as results extracted from a systematic review of the literature and other scientific media. The present review is based on the impact of their related publications and the available data and software resources for molecular medicine. It aims to provide information that can be useful to support ongoing research and work to improve diagnostics and therapeutics based on molecular-level insights.
Liang, Yuzhen; Xiong, Ruichang; Sandler, Stanley I; Di Toro, Dominic M
2017-09-05
Polyparameter Linear Free Energy Relationships (pp-LFERs), also called Linear Solvation Energy Relationships (LSERs), are used to predict many environmentally significant properties of chemicals. A method is presented for computing the necessary chemical parameters, the Abraham parameters (AP), used by many pp-LFERs. It employs quantum chemical calculations and uses only the chemical's molecular structure. The method computes the Abraham E parameter using density functional theory computed molecular polarizability and the Clausius-Mossotti equation relating the index refraction to the molecular polarizability, estimates the Abraham V as the COSMO calculated molecular volume, and computes the remaining AP S, A, and B jointly with a multiple linear regression using sixty-five solvent-water partition coefficients computed using the quantum mechanical COSMO-SAC solvation model. These solute parameters, referred to as Quantum Chemically estimated Abraham Parameters (QCAP), are further adjusted by fitting to experimentally based APs using QCAP parameters as the independent variables so that they are compatible with existing Abraham pp-LFERs. QCAP and adjusted QCAP for 1827 neutral chemicals are included. For 24 solvent-water systems including octanol-water, predicted log solvent-water partition coefficients using adjusted QCAP have the smallest root-mean-square errors (RMSEs, 0.314-0.602) compared to predictions made using APs estimated using the molecular fragment based method ABSOLV (0.45-0.716). For munition and munition-like compounds, adjusted QCAP has much lower RMSE (0.860) than does ABSOLV (4.45) which essentially fails for these compounds.
Designing Ionic Liquids for CO2 Capture: What’s the role for computation?
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brennecke, Joan F.
Presentation on the computational aspects of ionic liquid selection for carbon dioxide capture to the conference attendees at the New Vistas in Molecular Thermodynamics: Experimentation, Molecular Modeling, and Inverse Design, Berkeley, CA, January 7 through 9, 2018
2007-11-05
limits of what is considered practical when applying all-atom molecular - dynamics simulation methods. Lattice models provide computationally robust...of expectation values from the density of states. All-atom molecular - dynamics simulations provide the most rigorous sampling method to generate con... molecular - dynamics simulations of protein folding,6–9 reported studies of computing a heat capacity or other calorimetric observables have been limited to
Computational Materials Research
NASA Technical Reports Server (NTRS)
Hinkley, Jeffrey A. (Editor); Gates, Thomas S. (Editor)
1996-01-01
Computational Materials aims to model and predict thermodynamic, mechanical, and transport properties of polymer matrix composites. This workshop, the second coordinated by NASA Langley, reports progress in measurements and modeling at a number of length scales: atomic, molecular, nano, and continuum. Assembled here are presentations on quantum calculations for force field development, molecular mechanics of interfaces, molecular weight effects on mechanical properties, molecular dynamics applied to poling of polymers for electrets, Monte Carlo simulation of aromatic thermoplastics, thermal pressure coefficients of liquids, ultrasonic elastic constants, group additivity predictions, bulk constitutive models, and viscoplasticity characterization.
Computer-aided design of polymers and composites
NASA Technical Reports Server (NTRS)
Kaelble, D. H.
1985-01-01
This book on computer-aided design of polymers and composites introduces and discusses the subject from the viewpoint of atomic and molecular models. Thus, the origins of stiffness, strength, extensibility, and fracture toughness in composite materials can be analyzed directly in terms of chemical composition and molecular structure. Aspects of polymer composite reliability are considered along with characterization techniques for composite reliability, relations between atomic and molecular properties, computer aided design and manufacture, polymer CAD/CAM models, and composite CAD/CAM models. Attention is given to multiphase structural adhesives, fibrous composite reliability, metal joint reliability, polymer physical states and transitions, chemical quality assurance, processability testing, cure monitoring and management, nondestructive evaluation (NDE), surface NDE, elementary properties, ionic-covalent bonding, molecular analysis, acid-base interactions, the manufacturing science, and peel mechanics.
Non-linear molecular pattern classification using molecular beacons with multiple targets.
Lee, In-Hee; Lee, Seung Hwan; Park, Tai Hyun; Zhang, Byoung-Tak
2013-12-01
In vitro pattern classification has been highlighted as an important future application of DNA computing. Previous work has demonstrated the feasibility of linear classifiers using DNA-based molecular computing. However, complex tasks require non-linear classification capability. Here we design a molecular beacon that can interact with multiple targets and experimentally shows that its fluorescent signals form a complex radial-basis function, enabling it to be used as a building block for non-linear molecular classification in vitro. The proposed method was successfully applied to solving artificial and real-world classification problems: XOR and microRNA expression patterns. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Molecular and nanoscale materials and devices in electronics.
Fu, Lei; Cao, Lingchao; Liu, Yunqi; Zhu, Daoben
2004-12-13
Over the past several years, there have been many significant advances toward the realization of electronic computers integrated on the molecular scale and a much greater understanding of the types of materials that will be useful in molecular devices and their properties. It was demonstrated that individual molecules could serve as incomprehensibly tiny switch and wire one million times smaller than those on conventional silicon microchip. This has resulted very recently in the assembly and demonstration of tiny computer logic circuits built from such molecular scale devices. The purpose of this review is to provide a general introduction to molecular and nanoscale materials and devices in electronics.
The Computer Simulation of Liquids by Molecular Dynamics.
ERIC Educational Resources Information Center
Smith, W.
1987-01-01
Proposes a mathematical computer model for the behavior of liquids using the classical dynamic principles of Sir Isaac Newton and the molecular dynamics method invented by other scientists. Concludes that other applications will be successful using supercomputers to go beyond simple Newtonian physics. (CW)
The computer program SPARC (SPARC Performs Automated Reasoning in Chemistry) has been under development for several years to estimate physical properties and chemical reactivity parameters of organic compounds strictly from molecular structure. SPARC uses computational algorithms...
2008-02-09
Campbell, S. Ogata, and F. Shimojo, “ Multimillion atom simulations of nanosystems on parallel computers,” in Proceedings of the International...nanomesas: multimillion -atom molecular dynamics simulations on parallel computers,” J. Appl. Phys. 94, 6762 (2003). 21. P. Vashishta, R. K. Kalia...and A. Nakano, “ Multimillion atom molecular dynamics simulations of nanoparticles on parallel computers,” Journal of Nanoparticle Research 5, 119-135
Computing the Ediz eccentric connectivity index of discrete dynamic structures
NASA Astrophysics Data System (ADS)
Wu, Hualong; Kamran Siddiqui, Muhammad; Zhao, Bo; Gan, Jianhou; Gao, Wei
2017-06-01
From the earlier studies in physical and chemical sciences, it is found that the physico-chemical characteristics of chemical compounds are internally connected with their molecular structures. As a theoretical basis, it provides a new way of thinking by analyzing the molecular structure of the compounds to understand their physical and chemical properties. In our article, we study the physico-chemical properties of certain molecular structures via computing the Ediz eccentric connectivity index from mathematical standpoint. The results we yielded mainly apply to the techniques of distance and degree computation of mathematical derivation, and the conclusions have guiding significance in physical engineering.
TopoMS: Comprehensive topological exploration for molecular and condensed-matter systems.
Bhatia, Harsh; Gyulassy, Attila G; Lordi, Vincenzo; Pask, John E; Pascucci, Valerio; Bremer, Peer-Timo
2018-06-15
We introduce TopoMS, a computational tool enabling detailed topological analysis of molecular and condensed-matter systems, including the computation of atomic volumes and charges through the quantum theory of atoms in molecules, as well as the complete molecular graph. With roots in techniques from computational topology, and using a shared-memory parallel approach, TopoMS provides scalable, numerically robust, and topologically consistent analysis. TopoMS can be used as a command-line tool or with a GUI (graphical user interface), where the latter also enables an interactive exploration of the molecular graph. This paper presents algorithmic details of TopoMS and compares it with state-of-the-art tools: Bader charge analysis v1.0 (Arnaldsson et al., 01/11/17) and molecular graph extraction using Critic2 (Otero-de-la-Roza et al., Comput. Phys. Commun. 2014, 185, 1007). TopoMS not only combines the functionality of these individual codes but also demonstrates up to 4× performance gain on a standard laptop, faster convergence to fine-grid solution, robustness against lattice bias, and topological consistency. TopoMS is released publicly under BSD License. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.
Ivanciuc, Ovidiu
2013-06-01
Chemical and molecular graphs have fundamental applications in chemoinformatics, quantitative structureproperty relationships (QSPR), quantitative structure-activity relationships (QSAR), virtual screening of chemical libraries, and computational drug design. Chemoinformatics applications of graphs include chemical structure representation and coding, database search and retrieval, and physicochemical property prediction. QSPR, QSAR and virtual screening are based on the structure-property principle, which states that the physicochemical and biological properties of chemical compounds can be predicted from their chemical structure. Such structure-property correlations are usually developed from topological indices and fingerprints computed from the molecular graph and from molecular descriptors computed from the three-dimensional chemical structure. We present here a selection of the most important graph descriptors and topological indices, including molecular matrices, graph spectra, spectral moments, graph polynomials, and vertex topological indices. These graph descriptors are used to define several topological indices based on molecular connectivity, graph distance, reciprocal distance, distance-degree, distance-valency, spectra, polynomials, and information theory concepts. The molecular descriptors and topological indices can be developed with a more general approach, based on molecular graph operators, which define a family of graph indices related by a common formula. Graph descriptors and topological indices for molecules containing heteroatoms and multiple bonds are computed with weighting schemes based on atomic properties, such as the atomic number, covalent radius, or electronegativity. The correlation in QSPR and QSAR models can be improved by optimizing some parameters in the formula of topological indices, as demonstrated for structural descriptors based on atomic connectivity and graph distance.
Sarpeshkar, R
2014-03-28
We analyse the pros and cons of analog versus digital computation in living cells. Our analysis is based on fundamental laws of noise in gene and protein expression, which set limits on the energy, time, space, molecular count and part-count resources needed to compute at a given level of precision. We conclude that analog computation is significantly more efficient in its use of resources than deterministic digital computation even at relatively high levels of precision in the cell. Based on this analysis, we conclude that synthetic biology must use analog, collective analog, probabilistic and hybrid analog-digital computational approaches; otherwise, even relatively simple synthetic computations in cells such as addition will exceed energy and molecular-count budgets. We present schematics for efficiently representing analog DNA-protein computation in cells. Analog electronic flow in subthreshold transistors and analog molecular flux in chemical reactions obey Boltzmann exponential laws of thermodynamics and are described by astoundingly similar logarithmic electrochemical potentials. Therefore, cytomorphic circuits can help to map circuit designs between electronic and biochemical domains. We review recent work that uses positive-feedback linearization circuits to architect wide-dynamic-range logarithmic analog computation in Escherichia coli using three transcription factors, nearly two orders of magnitude more efficient in parts than prior digital implementations.
Sarpeshkar, R.
2014-01-01
We analyse the pros and cons of analog versus digital computation in living cells. Our analysis is based on fundamental laws of noise in gene and protein expression, which set limits on the energy, time, space, molecular count and part-count resources needed to compute at a given level of precision. We conclude that analog computation is significantly more efficient in its use of resources than deterministic digital computation even at relatively high levels of precision in the cell. Based on this analysis, we conclude that synthetic biology must use analog, collective analog, probabilistic and hybrid analog–digital computational approaches; otherwise, even relatively simple synthetic computations in cells such as addition will exceed energy and molecular-count budgets. We present schematics for efficiently representing analog DNA–protein computation in cells. Analog electronic flow in subthreshold transistors and analog molecular flux in chemical reactions obey Boltzmann exponential laws of thermodynamics and are described by astoundingly similar logarithmic electrochemical potentials. Therefore, cytomorphic circuits can help to map circuit designs between electronic and biochemical domains. We review recent work that uses positive-feedback linearization circuits to architect wide-dynamic-range logarithmic analog computation in Escherichia coli using three transcription factors, nearly two orders of magnitude more efficient in parts than prior digital implementations. PMID:24567476
Computationally Efficient Multiconfigurational Reactive Molecular Dynamics
Yamashita, Takefumi; Peng, Yuxing; Knight, Chris; Voth, Gregory A.
2012-01-01
It is a computationally demanding task to explicitly simulate the electronic degrees of freedom in a system to observe the chemical transformations of interest, while at the same time sampling the time and length scales required to converge statistical properties and thus reduce artifacts due to initial conditions, finite-size effects, and limited sampling. One solution that significantly reduces the computational expense consists of molecular models in which effective interactions between particles govern the dynamics of the system. If the interaction potentials in these models are developed to reproduce calculated properties from electronic structure calculations and/or ab initio molecular dynamics simulations, then one can calculate accurate properties at a fraction of the computational cost. Multiconfigurational algorithms model the system as a linear combination of several chemical bonding topologies to simulate chemical reactions, also sometimes referred to as “multistate”. These algorithms typically utilize energy and force calculations already found in popular molecular dynamics software packages, thus facilitating their implementation without significant changes to the structure of the code. However, the evaluation of energies and forces for several bonding topologies per simulation step can lead to poor computational efficiency if redundancy is not efficiently removed, particularly with respect to the calculation of long-ranged Coulombic interactions. This paper presents accurate approximations (effective long-range interaction and resulting hybrid methods) and multiple-program parallelization strategies for the efficient calculation of electrostatic interactions in reactive molecular simulations. PMID:25100924
Computational Modeling and Treatment Identification in the Myelodysplastic Syndromes.
Drusbosky, Leylah M; Cogle, Christopher R
2017-10-01
This review discusses the need for computational modeling in myelodysplastic syndromes (MDS) and early test results. As our evolving understanding of MDS reveals a molecularly complicated disease, the need for sophisticated computer analytics is required to keep track of the number and complex interplay among the molecular abnormalities. Computational modeling and digital drug simulations using whole exome sequencing data input have produced early results showing high accuracy in predicting treatment response to standard of care drugs. Furthermore, the computational MDS models serve as clinically relevant MDS cell lines for pre-clinical assays of investigational agents. MDS is an ideal disease for computational modeling and digital drug simulations. Current research is focused on establishing the prediction value of computational modeling. Future research will test the clinical advantage of computer-informed therapy in MDS.
Advances in visual representation of molecular potentials.
Du, Qi-Shi; Huang, Ri-Bo; Chou, Kuo-Chen
2010-06-01
The recent advances in visual representations of molecular properties in 3D space are summarized, and their applications in molecular modeling study and rational drug design are introduced. The visual representation methods provide us with detailed insights into protein-ligand interactions, and hence can play a major role in elucidating the structure or reactivity of a biomolecular system. Three newly developed computation and visualization methods for studying the physical and chemical properties of molecules are introduced, including their electrostatic potential, lipophilicity potential and excess chemical potential. The newest application examples of visual representations in structure-based rational drug are presented. The 3D electrostatic potentials, calculated using the empirical method (EM-ESP), in which the classical Coulomb equation and traditional atomic partial changes are discarded, are highly consistent with the results by the higher level quantum chemical method. The 3D lipophilicity potentials, computed by the heuristic molecular lipophilicity potential method based on the principles of quantum mechanics and statistical mechanics, are more accurate and reliable than those by using the traditional empirical methods. The 3D excess chemical potentials, derived by the reference interaction site model-hypernetted chain theory, provide a new tool for computational chemistry and molecular modeling. For structure-based drug design, the visual representations of molecular properties will play a significant role in practical applications. It is anticipated that the new advances in computational chemistry will stimulate the development of molecular modeling methods, further enriching the visual representation techniques for rational drug design, as well as other relevant fields in life science.
Enantiomerically enriched, polycrystalline molecular sieves
Brand, Stephen K.; Schmidt, Joel E.; Deem, Michael W.; ...
2017-05-01
Zeolite and zeolite-like molecular sieves are being used in a large number of applications such as adsorption and catalysis. Achievement of the long-standing goal of creating a chiral, polycrystalline molecular sieve with bulk enantioenrichment would enable these materials to perform enantioselective functions. Here, we report the synthesis of enantiomerically enriched samples of a molecular sieve. For this study, enantiopure organic structure directing agents are designed with the assistance of computational methods and used to synthesize enantioenriched, polycrystalline molecular sieve samples of either enantiomer. Computational results correctly predicted which enantiomer is obtained, and enantiomeric enrichment is proven by high-resolution transmission electronmore » microscopy. The enantioenriched and racemic samples of the molecular sieves are tested as adsorbents and heterogeneous catalysts. The enantioenriched molecular sieves show enantioselectivity for the ring opening reaction of epoxides and enantioselective adsorption of 2-butanol (the R enantiomer of the molecular sieve shows opposite and approximately equal enantioselectivity compared with the S enantiomer of the molecular sieve, whereas the racemic sample of the molecular sieve shows no enantioselectivity).« less
Enantiomerically enriched, polycrystalline molecular sieves
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brand, Stephen K.; Schmidt, Joel E.; Deem, Michael W.
Zeolite and zeolite-like molecular sieves are being used in a large number of applications such as adsorption and catalysis. Achievement of the long-standing goal of creating a chiral, polycrystalline molecular sieve with bulk enantioenrichment would enable these materials to perform enantioselective functions. Here, we report the synthesis of enantiomerically enriched samples of a molecular sieve. For this study, enantiopure organic structure directing agents are designed with the assistance of computational methods and used to synthesize enantioenriched, polycrystalline molecular sieve samples of either enantiomer. Computational results correctly predicted which enantiomer is obtained, and enantiomeric enrichment is proven by high-resolution transmission electronmore » microscopy. The enantioenriched and racemic samples of the molecular sieves are tested as adsorbents and heterogeneous catalysts. The enantioenriched molecular sieves show enantioselectivity for the ring opening reaction of epoxides and enantioselective adsorption of 2-butanol (the R enantiomer of the molecular sieve shows opposite and approximately equal enantioselectivity compared with the S enantiomer of the molecular sieve, whereas the racemic sample of the molecular sieve shows no enantioselectivity).« less
ten Kate, Gerrit L.; Sijbrands, Eric J. G.; Valkema, Roelf; ten Cate, Folkert J.; Feinstein, Steven B.; van der Steen, Antonius F. W.; Daemen, Mat J. A. P.
2010-01-01
Current developments in cardiovascular biology and imaging enable the noninvasive molecular evaluation of atherosclerotic vascular disease. Intraplaque neovascularization sprouting from the adventitial vasa vasorum has been identified as an independent predictor of intraplaque hemorrhage and plaque rupture. These intraplaque vasa vasorum result from angiogenesis, most likely under influence of hypoxic and inflammatory stimuli. Several molecular imaging techniques are currently available. Most experience has been obtained with molecular imaging using positron emission tomography and single photon emission computed tomography. Recently, the development of targeted contrast agents has allowed molecular imaging with magnetic resonance imaging, ultrasound and computed tomography. The present review discusses the use of these molecular imaging techniques to identify inflammation and intraplaque vasa vasorum to identify vulnerable atherosclerotic plaques at risk of rupture and thrombosis. The available literature on molecular imaging techniques and molecular targets associated with inflammation and angiogenesis is discussed, and the clinical applications of molecular cardiovascular imaging and the use of molecular techniques for local drug delivery are addressed. PMID:20552308
Morgnanesi, Dante; Heinrichs, Eric J; Mele, Anthony R; Wilkinson, Sean; Zhou, Suzanne; Kulp, John L
2015-11-01
Computational chemical biology, applied to research on hepatitis B virus (HBV), has two major branches: bioinformatics (statistical models) and first-principle methods (molecular physics). While bioinformatics focuses on statistical tools and biological databases, molecular physics uses mathematics and chemical theory to study the interactions of biomolecules. Three computational techniques most commonly used in HBV research are homology modeling, molecular docking, and molecular dynamics. Homology modeling is a computational simulation to predict protein structure and has been used to construct conformers of the viral polymerase (reverse transcriptase domain and RNase H domain) and the HBV X protein. Molecular docking is used to predict the most likely orientation of a ligand when it is bound to a protein, as well as determining an energy score of the docked conformation. Molecular dynamics is a simulation that analyzes biomolecule motions and determines conformation and stability patterns. All of these modeling techniques have aided in the understanding of resistance mutations on HBV non-nucleos(t)ide reverse-transcriptase inhibitor binding. Finally, bioinformatics can be used to study the DNA and RNA protein sequences of viruses to both analyze drug resistance and to genotype the viral genomes. Overall, with these techniques, and others, computational chemical biology is becoming more and more necessary in hepatitis B research. This article forms part of a symposium in Antiviral Research on "An unfinished story: from the discovery of the Australia antigen to the development of new curative therapies for hepatitis B." Copyright © 2015 Elsevier B.V. All rights reserved.
Fast parallel molecular algorithms for DNA-based computation: factoring integers.
Chang, Weng-Long; Guo, Minyi; Ho, Michael Shan-Hui
2005-06-01
The RSA public-key cryptosystem is an algorithm that converts input data to an unrecognizable encryption and converts the unrecognizable data back into its original decryption form. The security of the RSA public-key cryptosystem is based on the difficulty of factoring the product of two large prime numbers. This paper demonstrates to factor the product of two large prime numbers, and is a breakthrough in basic biological operations using a molecular computer. In order to achieve this, we propose three DNA-based algorithms for parallel subtractor, parallel comparator, and parallel modular arithmetic that formally verify our designed molecular solutions for factoring the product of two large prime numbers. Furthermore, this work indicates that the cryptosystems using public-key are perhaps insecure and also presents clear evidence of the ability of molecular computing to perform complicated mathematical operations.
Benson, W.H., R.T. Di Giulio, J.C. Cook, J. Freedman, R.L. Malek, C. Thompson and D. Versteeg. In press. Emerging Molecular and Computational Approaches for Cross-Species Extrapolations: A Workshop Summary Report (Abstract). To be presented at the SETAC Fourth World Congress, 14-...
EPA announced the release of the final report, Next Generation Risk Assessment: Incorporation of Recent Advances in Molecular, Computational, and Systems Biology. This report describes new approaches that are faster, less resource intensive, and more robust that can help ...
Enhanced Molecular Dynamics Methods Applied to Drug Design Projects.
Ziada, Sonia; Braka, Abdennour; Diharce, Julien; Aci-Sèche, Samia; Bonnet, Pascal
2018-01-01
Nobel Laureate Richard P. Feynman stated: "[…] everything that living things do can be understood in terms of jiggling and wiggling of atoms […]." The importance of computer simulations of macromolecules, which use classical mechanics principles to describe atom behavior, is widely acknowledged and nowadays, they are applied in many fields such as material sciences and drug discovery. With the increase of computing power, molecular dynamics simulations can be applied to understand biological mechanisms at realistic timescales. In this chapter, we share our computational experience providing a global view of two of the widely used enhanced molecular dynamics methods to study protein structure and dynamics through the description of their characteristics, limits and we provide some examples of their applications in drug design. We also discuss the appropriate choice of software and hardware. In a detailed practical procedure, we describe how to set up, run, and analyze two main molecular dynamics methods, the umbrella sampling (US) and the accelerated molecular dynamics (aMD) methods.
Extended Lagrangian Density Functional Tight-Binding Molecular Dynamics for Molecules and Solids.
Aradi, Bálint; Niklasson, Anders M N; Frauenheim, Thomas
2015-07-14
A computationally fast quantum mechanical molecular dynamics scheme using an extended Lagrangian density functional tight-binding formulation has been developed and implemented in the DFTB+ electronic structure program package for simulations of solids and molecular systems. The scheme combines the computational speed of self-consistent density functional tight-binding theory with the efficiency and long-term accuracy of extended Lagrangian Born-Oppenheimer molecular dynamics. For systems without self-consistent charge instabilities, only a single diagonalization or construction of the single-particle density matrix is required in each time step. The molecular dynamics simulation scheme can be applied to a broad range of problems in materials science, chemistry, and biology.
Jahn-Teller effect in molecular electronics: quantum cellular automata
NASA Astrophysics Data System (ADS)
Tsukerblat, B.; Palii, A.; Clemente-Juan, J. M.; Coronado, E.
2017-05-01
The article summarizes the main results of application of the theory of the Jahn-Teller (JT) and pseudo JT effects to the description of molecular quantum dot cellular automata (QCA), a new paradigm of quantum computing. The following issues are discussed: 1) QCA as a new paradigm of quantum computing, principles and advantages; 2) molecular implementation of QCA; 3) role of the JT effect in charge trapping, encoding of binary information in the quantum cell and non-linear cell-cell response; 4) spin-switching in molecular QCA based on mixed-valence cell; 5) intervalence optical absorption in tetrameric molecular mixed-valence cell through the symmetry assisted approach to the multimode/multilevel JT and pseudo JT problems.
2014-01-01
Study Material properties and performance are governed by material molecular chemistry structures and molecular level interactions. Methods to...understand relationships between the material properties and performance and their correlation to the molecular level chemistry and morphology, and thus...find ways of manipulating and adjusting matters at the atomistic level in order to improve material performance are required. A computational material
Hirano, Toshiyuki; Sato, Fumitoshi
2014-07-28
We used grid-free modified Cholesky decomposition (CD) to develop a density-functional-theory (DFT)-based method for calculating the canonical molecular orbitals (CMOs) of large molecules. Our method can be used to calculate standard CMOs, analytically compute exchange-correlation terms, and maximise the capacity of next-generation supercomputers. Cholesky vectors were first analytically downscaled using low-rank pivoted CD and CD with adaptive metric (CDAM). The obtained Cholesky vectors were distributed and stored on each computer node in a parallel computer, and the Coulomb, Fock exchange, and pure exchange-correlation terms were calculated by multiplying the Cholesky vectors without evaluating molecular integrals in self-consistent field iterations. Our method enables DFT and massively distributed memory parallel computers to be used in order to very efficiently calculate the CMOs of large molecules.
Computing by physical interaction in neurons.
Aur, Dorian; Jog, Mandar; Poznanski, Roman R
2011-12-01
The electrodynamics of action potentials represents the fundamental level where information is integrated and processed in neurons. The Hodgkin-Huxley model cannot explain the non-stereotyped spatial charge density dynamics that occur during action potential propagation. Revealed in experiments as spike directivity, the non-uniform charge density dynamics within neurons carry meaningful information and suggest that fragments of information regarding our memories are endogenously stored in structural patterns at a molecular level and are revealed only during spiking activity. The main conceptual idea is that under the influence of electric fields, efficient computation by interaction occurs between charge densities embedded within molecular structures and the transient developed flow of electrical charges. This process of computation underlying electrical interactions and molecular mechanisms at the subcellular level is dissimilar from spiking neuron models that are completely devoid of physical interactions. Computation by interaction describes a more powerful continuous model of computation than the one that consists of discrete steps as represented in Turing machines.
Toward integration of in vivo molecular computing devices: successes and challenges
Hayat, Sikander; Hinze, Thomas
2008-01-01
The computing power unleashed by biomolecule based massively parallel computational units has been the focus of many interdisciplinary studies that couple state of the art ideas from mathematical logic, theoretical computer science, bioengineering, and nanotechnology to fulfill some computational task. The output can influence, for instance, release of a drug at a specific target, gene expression, cell population, or be a purely mathematical entity. Analysis of the results of several studies has led to the emergence of a general set of rules concerning the implementation and optimization of in vivo computational units. Taking two recent studies on in vivo computing as examples, we discuss the impact of mathematical modeling and simulation in the field of synthetic biology and on in vivo computing. The impact of the emergence of gene regulatory networks and the potential of proteins acting as “circuit wires” on the problem of interconnecting molecular computing device subunits is also highlighted. PMID:19404433
ERIC Educational Resources Information Center
Stokes-Huby, Heather; Vitale, Dale E.
2007-01-01
This exercise integrates the infrared unknown identification ("IR-ID") experiment common to most organic laboratory syllabi with computer molecular modeling. In this modification students are still required to identify unknown compounds from their IR spectra, but must additionally match some of the absorptions with computed frequencies they…
High performance computing in biology: multimillion atom simulations of nanoscale systems
Sanbonmatsu, K. Y.; Tung, C.-S.
2007-01-01
Computational methods have been used in biology for sequence analysis (bioinformatics), all-atom simulation (molecular dynamics and quantum calculations), and more recently for modeling biological networks (systems biology). Of these three techniques, all-atom simulation is currently the most computationally demanding, in terms of compute load, communication speed, and memory load. Breakthroughs in electrostatic force calculation and dynamic load balancing have enabled molecular dynamics simulations of large biomolecular complexes. Here, we report simulation results for the ribosome, using approximately 2.64 million atoms, the largest all-atom biomolecular simulation published to date. Several other nanoscale systems with different numbers of atoms were studied to measure the performance of the NAMD molecular dynamics simulation program on the Los Alamos National Laboratory Q Machine. We demonstrate that multimillion atom systems represent a 'sweet spot' for the NAMD code on large supercomputers. NAMD displays an unprecedented 85% parallel scaling efficiency for the ribosome system on 1024 CPUs. We also review recent targeted molecular dynamics simulations of the ribosome that prove useful for studying conformational changes of this large biomolecular complex in atomic detail. PMID:17187988
Open source molecular modeling.
Pirhadi, Somayeh; Sunseri, Jocelyn; Koes, David Ryan
2016-09-01
The success of molecular modeling and computational chemistry efforts are, by definition, dependent on quality software applications. Open source software development provides many advantages to users of modeling applications, not the least of which is that the software is free and completely extendable. In this review we categorize, enumerate, and describe available open source software packages for molecular modeling and computational chemistry. An updated online version of this catalog can be found at https://opensourcemolecularmodeling.github.io. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.
Biosensors with Built-In Biomolecular Logic Gates for Practical Applications
Lai, Yu-Hsuan; Sun, Sin-Cih; Chuang, Min-Chieh
2014-01-01
Molecular logic gates, designs constructed with biological and chemical molecules, have emerged as an alternative computing approach to silicon-based logic operations. These molecular computers are capable of receiving and integrating multiple stimuli of biochemical significance to generate a definitive output, opening a new research avenue to advanced diagnostics and therapeutics which demand handling of complex factors and precise control. In molecularly gated devices, Boolean logic computations can be activated by specific inputs and accurately processed via bio-recognition, bio-catalysis, and selective chemical reactions. In this review, we survey recent advances of the molecular logic approaches to practical applications of biosensors, including designs constructed with proteins, enzymes, nucleic acids, nanomaterials, and organic compounds, as well as the research avenues for future development of digitally operating “sense and act” schemes that logically process biochemical signals through networked circuits to implement intelligent control systems. PMID:25587423
Sergiievskyi, Volodymyr P; Jeanmairet, Guillaume; Levesque, Maximilien; Borgis, Daniel
2014-06-05
Molecular density functional theory (MDFT) offers an efficient implicit-solvent method to estimate molecule solvation free-energies, whereas conserving a fully molecular representation of the solvent. Even within a second-order approximation for the free-energy functional, the so-called homogeneous reference fluid approximation, we show that the hydration free-energies computed for a data set of 500 organic compounds are of similar quality as those obtained from molecular dynamics free-energy perturbation simulations, with a computer cost reduced by 2-3 orders of magnitude. This requires to introduce the proper partial volume correction to transform the results from the grand canonical to the isobaric-isotherm ensemble that is pertinent to experiments. We show that this correction can be extended to 3D-RISM calculations, giving a sound theoretical justification to empirical partial molar volume corrections that have been proposed recently.
Evaluation of a grid based molecular dynamics approach for polypeptide simulations.
Merelli, Ivan; Morra, Giulia; Milanesi, Luciano
2007-09-01
Molecular dynamics is very important for biomedical research because it makes possible simulation of the behavior of a biological macromolecule in silico. However, molecular dynamics is computationally rather expensive: the simulation of some nanoseconds of dynamics for a large macromolecule such as a protein takes very long time, due to the high number of operations that are needed for solving the Newton's equations in the case of a system of thousands of atoms. In order to obtain biologically significant data, it is desirable to use high-performance computation resources to perform these simulations. Recently, a distributed computing approach based on replacing a single long simulation with many independent short trajectories has been introduced, which in many cases provides valuable results. This study concerns the development of an infrastructure to run molecular dynamics simulations on a grid platform in a distributed way. The implemented software allows the parallel submission of different simulations that are singularly short but together bring important biological information. Moreover, each simulation is divided into a chain of jobs to avoid data loss in case of system failure and to contain the dimension of each data transfer from the grid. The results confirm that the distributed approach on grid computing is particularly suitable for molecular dynamics simulations thanks to the elevated scalability.
Extended Lagrangian Density Functional Tight-Binding Molecular Dynamics for Molecules and Solids
DOE Office of Scientific and Technical Information (OSTI.GOV)
Aradi, Bálint; Niklasson, Anders M. N.; Frauenheim, Thomas
A computationally fast quantum mechanical molecular dynamics scheme using an extended Lagrangian density functional tight-binding formulation has been developed and implemented in the DFTB+ electronic structure program package for simulations of solids and molecular systems. The scheme combines the computational speed of self-consistent density functional tight-binding theory with the efficiency and long-term accuracy of extended Lagrangian Born–Oppenheimer molecular dynamics. Furthermore, for systems without self-consistent charge instabilities, only a single diagonalization or construction of the single-particle density matrix is required in each time step. The molecular dynamics simulation scheme can also be applied to a broad range of problems in materialsmore » science, chemistry, and biology.« less
Extended Lagrangian Density Functional Tight-Binding Molecular Dynamics for Molecules and Solids
Aradi, Bálint; Niklasson, Anders M. N.; Frauenheim, Thomas
2015-06-26
A computationally fast quantum mechanical molecular dynamics scheme using an extended Lagrangian density functional tight-binding formulation has been developed and implemented in the DFTB+ electronic structure program package for simulations of solids and molecular systems. The scheme combines the computational speed of self-consistent density functional tight-binding theory with the efficiency and long-term accuracy of extended Lagrangian Born–Oppenheimer molecular dynamics. Furthermore, for systems without self-consistent charge instabilities, only a single diagonalization or construction of the single-particle density matrix is required in each time step. The molecular dynamics simulation scheme can also be applied to a broad range of problems in materialsmore » science, chemistry, and biology.« less
ISMB Conference Funding to Support Attendance of Early Researchers and Students
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gaasterland, Terry
ISMB Conference Funding for Students and Young Scientists Historical Description The Intelligent Systems for Molecular Biology (ISMB) conference has provided a general forum for disseminating the latest developments in bioinformatics on an annual basis for the past 22 years. ISMB is a multidisciplinary conference that brings together scientists from computer science, molecular biology, mathematics and statistics. The goal of the ISMB meeting is to bring together biologists and computational scientists in a focus on actual biological problems, i.e., not simply theoretical calculations. The combined focus on “intelligent systems” and actual biological data makes ISMB a unique and highly important meeting.more » 21 years of experience in holding the conference has resulted in a consistently well-organized, well attended, and highly respected annual conference. "Intelligent systems" include any software which goes beyond straightforward, closed-form algorithms or standard database technologies, and encompasses those that view data in a symbolic fashion, learn from examples, consolidate multiple levels of abstraction, or synthesize results to be cognitively tractable to a human, including the development and application of advanced computational methods for biological problems. Relevant computational techniques include, but are not limited to: machine learning, pattern recognition, knowledge representation, databases, combinatorics, stochastic modeling, string and graph algorithms, linguistic methods, robotics, constraint satisfaction, and parallel computation. Biological areas of interest include molecular structure, genomics, molecular sequence analysis, evolution and phylogenetics, molecular interactions, metabolic pathways, regulatory networks, developmental control, and molecular biology generally. Emphasis is placed on the validation of methods using real data sets, on practical applications in the biological sciences, and on development of novel computational techniques. The ISMB conferences are distinguished from many other conferences in computational biology or artificial intelligence by an insistence that the researchers work with real molecular biology data, not theoretical or toy examples; and from many other biological conferences by providing a forum for technical advances as they occur, which otherwise may be shunned until a firm experimental result is published. The resulting intellectual richness and cross-disciplinary diversity provides an important opportunity for both students and senior researchers. ISMB has become the premier conference series in this field with refereed, published proceedings, establishing an infrastructure to promote the growing body of research.« less
Ou-Yang, Si-sheng; Lu, Jun-yan; Kong, Xiang-qian; Liang, Zhong-jie; Luo, Cheng; Jiang, Hualiang
2012-01-01
Computational drug discovery is an effective strategy for accelerating and economizing drug discovery and development process. Because of the dramatic increase in the availability of biological macromolecule and small molecule information, the applicability of computational drug discovery has been extended and broadly applied to nearly every stage in the drug discovery and development workflow, including target identification and validation, lead discovery and optimization and preclinical tests. Over the past decades, computational drug discovery methods such as molecular docking, pharmacophore modeling and mapping, de novo design, molecular similarity calculation and sequence-based virtual screening have been greatly improved. In this review, we present an overview of these important computational methods, platforms and successful applications in this field. PMID:22922346
Sumner, Isaiah; Iyengar, Srinivasan S
2007-10-18
We have introduced a computational methodology to study vibrational spectroscopy in clusters inclusive of critical nuclear quantum effects. This approach is based on the recently developed quantum wavepacket ab initio molecular dynamics method that combines quantum wavepacket dynamics with ab initio molecular dynamics. The computational efficiency of the dynamical procedure is drastically improved (by several orders of magnitude) through the utilization of wavelet-based techniques combined with the previously introduced time-dependent deterministic sampling procedure measure to achieve stable, picosecond length, quantum-classical dynamics of electrons and nuclei in clusters. The dynamical information is employed to construct a novel cumulative flux/velocity correlation function, where the wavepacket flux from the quantized particle is combined with classical nuclear velocities to obtain the vibrational density of states. The approach is demonstrated by computing the vibrational density of states of [Cl-H-Cl]-, inclusive of critical quantum nuclear effects, and our results are in good agreement with experiment. A general hierarchical procedure is also provided, based on electronic structure harmonic frequencies, classical ab initio molecular dynamics, computation of nuclear quantum-mechanical eigenstates, and employing quantum wavepacket ab initio dynamics to understand vibrational spectroscopy in hydrogen-bonded clusters that display large degrees of anharmonicities.
Computational approaches in the design of synthetic receptors - A review.
Cowen, Todd; Karim, Kal; Piletsky, Sergey
2016-09-14
The rational design of molecularly imprinted polymers (MIPs) has been a major contributor to their reputation as "plastic antibodies" - high affinity robust synthetic receptors which can be optimally designed, and produced for a much reduced cost than their biological equivalents. Computational design has become a routine procedure in the production of MIPs, and has led to major advances in functional monomer screening, selection of cross-linker and solvent, optimisation of monomer(s)-template ratio and selectivity analysis. In this review the various computational methods will be discussed with reference to all the published relevant literature since the end of 2013, with each article described by the target molecule, the computational approach applied (whether molecular mechanics/molecular dynamics, semi-empirical quantum mechanics, ab initio quantum mechanics (Hartree-Fock, Møller-Plesset, etc.) or DFT) and the purpose for which they were used. Detailed analysis is given to novel techniques including analysis of polymer binding sites, the use of novel screening programs and simulations of MIP polymerisation reaction. The further advances in molecular modelling and computational design of synthetic receptors in particular will have serious impact on the future of nanotechnology and biotechnology, permitting the further translation of MIPs into the realms of analytics and medical technology. Copyright © 2016 Elsevier B.V. All rights reserved.
ERIC Educational Resources Information Center
Marbach-Ad, Gili; Rotbain, Yosi; Stavy, Ruth
2008-01-01
Our main goal in this study was to determine whether the use of computer animation and illustration activities in high school can contribute to student achievement in molecular genetics. Three comparable groups of eleventh- and twelfth-grade students participated: the control group (116 students) was taught in the traditional lecture format,…
Computer display and manipulation of biological molecules
NASA Technical Reports Server (NTRS)
Coeckelenbergh, Y.; Macelroy, R. D.; Hart, J.; Rein, R.
1978-01-01
This paper describes a computer model that was designed to investigate the conformation of molecules, macromolecules and subsequent complexes. Utilizing an advanced 3-D dynamic computer display system, the model is sufficiently versatile to accommodate a large variety of molecular input and to generate data for multiple purposes such as visual representation of conformational changes, and calculation of conformation and interaction energy. Molecules can be built on the basis of several levels of information. These include the specification of atomic coordinates and connectivities and the grouping of building blocks and duplicated substructures using symmetry rules found in crystals and polymers such as proteins and nucleic acids. Called AIMS (Ames Interactive Molecular modeling System), the model is now being used to study pre-biotic molecular evolution toward life.
Emerging Themes in Image Informatics and Molecular Analysis for Digital Pathology.
Bhargava, Rohit; Madabhushi, Anant
2016-07-11
Pathology is essential for research in disease and development, as well as for clinical decision making. For more than 100 years, pathology practice has involved analyzing images of stained, thin tissue sections by a trained human using an optical microscope. Technological advances are now driving major changes in this paradigm toward digital pathology (DP). The digital transformation of pathology goes beyond recording, archiving, and retrieving images, providing new computational tools to inform better decision making for precision medicine. First, we discuss some emerging innovations in both computational image analytics and imaging instrumentation in DP. Second, we discuss molecular contrast in pathology. Molecular DP has traditionally been an extension of pathology with molecularly specific dyes. Label-free, spectroscopic images are rapidly emerging as another important information source, and we describe the benefits and potential of this evolution. Third, we describe multimodal DP, which is enabled by computational algorithms and combines the best characteristics of structural and molecular pathology. Finally, we provide examples of application areas in telepathology, education, and precision medicine. We conclude by discussing challenges and emerging opportunities in this area.
Emerging Themes in Image Informatics and Molecular Analysis for Digital Pathology
Bhargava, Rohit; Madabhushi, Anant
2017-01-01
Pathology is essential for research in disease and development, as well as for clinical decision making. For more than 100 years, pathology practice has involved analyzing images of stained, thin tissue sections by a trained human using an optical microscope. Technological advances are now driving major changes in this paradigm toward digital pathology (DP). The digital transformation of pathology goes beyond recording, archiving, and retrieving images, providing new computational tools to inform better decision making for precision medicine. First, we discuss some emerging innovations in both computational image analytics and imaging instrumentation in DP. Second, we discuss molecular contrast in pathology. Molecular DP has traditionally been an extension of pathology with molecularly specific dyes. Label-free, spectroscopic images are rapidly emerging as another important information source, and we describe the benefits and potential of this evolution. Third, we describe multimodal DP, which is enabled by computational algorithms and combines the best characteristics of structural and molecular pathology. Finally, we provide examples of application areas in telepathology, education, and precision medicine. We conclude by discussing challenges and emerging opportunities in this area. PMID:27420575
Anticipatory dynamics of biological systems: from molecular quantum states to evolution
NASA Astrophysics Data System (ADS)
Igamberdiev, Abir U.
2015-08-01
Living systems possess anticipatory behaviour that is based on the flexibility of internal models generated by the system's embedded description. The idea was suggested by Aristotle and is explicitly introduced to theoretical biology by Rosen. The possibility of holding the embedded internal model is grounded in the principle of stable non-equilibrium (Bauer). From the quantum mechanical view, this principle aims to minimize energy dissipation in expense of long relaxation times. The ideas of stable non-equilibrium were developed by Liberman who viewed living systems as subdivided into the quantum regulator and the molecular computer supporting coherence of the regulator's internal quantum state. The computational power of the cell molecular computer is based on the possibility of molecular rearrangements according to molecular addresses. In evolution, the anticipatory strategies are realized both as a precession of phylogenesis by ontogenesis (Berg) and as the anticipatory search of genetic fixation of adaptive changes that incorporates them into the internal model of genetic system. We discuss how the fundamental ideas of anticipation can be introduced into the basic foundations of theoretical biology.
Clustering molecular dynamics trajectories for optimizing docking experiments.
De Paris, Renata; Quevedo, Christian V; Ruiz, Duncan D; Norberto de Souza, Osmar; Barros, Rodrigo C
2015-01-01
Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand.
Motta, Mario; Zhang, Shiwei
2017-11-14
We address the computation of ground-state properties of chemical systems and realistic materials within the auxiliary-field quantum Monte Carlo method. The phase constraint to control the Fermion phase problem requires the random walks in Slater determinant space to be open-ended with branching. This in turn makes it necessary to use back-propagation (BP) to compute averages and correlation functions of operators that do not commute with the Hamiltonian. Several BP schemes are investigated, and their optimization with respect to the phaseless constraint is considered. We propose a modified BP method for the computation of observables in electronic systems, discuss its numerical stability and computational complexity, and assess its performance by computing ground-state properties in several molecular systems, including small organic molecules.
RNA nanotechnology for computer design and in vivo computation
Qiu, Meikang; Khisamutdinov, Emil; Zhao, Zhengyi; Pan, Cheryl; Choi, Jeong-Woo; Leontis, Neocles B.; Guo, Peixuan
2013-01-01
Molecular-scale computing has been explored since 1989 owing to the foreseeable limitation of Moore's law for silicon-based computation devices. With the potential of massive parallelism, low energy consumption and capability of working in vivo, molecular-scale computing promises a new computational paradigm. Inspired by the concepts from the electronic computer, DNA computing has realized basic Boolean functions and has progressed into multi-layered circuits. Recently, RNA nanotechnology has emerged as an alternative approach. Owing to the newly discovered thermodynamic stability of a special RNA motif (Shu et al. 2011 Nat. Nanotechnol. 6, 658–667 (doi:10.1038/nnano.2011.105)), RNA nanoparticles are emerging as another promising medium for nanodevice and nanomedicine as well as molecular-scale computing. Like DNA, RNA sequences can be designed to form desired secondary structures in a straightforward manner, but RNA is structurally more versatile and more thermodynamically stable owing to its non-canonical base-pairing, tertiary interactions and base-stacking property. A 90-nucleotide RNA can exhibit 490 nanostructures, and its loops and tertiary architecture can serve as a mounting dovetail that eliminates the need for external linking dowels. Its enzymatic and fluorogenic activity creates diversity in computational design. Varieties of small RNA can work cooperatively, synergistically or antagonistically to carry out computational logic circuits. The riboswitch and enzymatic ribozyme activities and its special in vivo attributes offer a great potential for in vivo computation. Unique features in transcription, termination, self-assembly, self-processing and acid resistance enable in vivo production of RNA nanoparticles that harbour various regulators for intracellular manipulation. With all these advantages, RNA computation is promising, but it is still in its infancy. Many challenges still exist. Collaborations between RNA nanotechnologists and computer scientists are necessary to advance this nascent technology. PMID:24000362
RNA nanotechnology for computer design and in vivo computation.
Qiu, Meikang; Khisamutdinov, Emil; Zhao, Zhengyi; Pan, Cheryl; Choi, Jeong-Woo; Leontis, Neocles B; Guo, Peixuan
2013-10-13
Molecular-scale computing has been explored since 1989 owing to the foreseeable limitation of Moore's law for silicon-based computation devices. With the potential of massive parallelism, low energy consumption and capability of working in vivo, molecular-scale computing promises a new computational paradigm. Inspired by the concepts from the electronic computer, DNA computing has realized basic Boolean functions and has progressed into multi-layered circuits. Recently, RNA nanotechnology has emerged as an alternative approach. Owing to the newly discovered thermodynamic stability of a special RNA motif (Shu et al. 2011 Nat. Nanotechnol. 6, 658-667 (doi:10.1038/nnano.2011.105)), RNA nanoparticles are emerging as another promising medium for nanodevice and nanomedicine as well as molecular-scale computing. Like DNA, RNA sequences can be designed to form desired secondary structures in a straightforward manner, but RNA is structurally more versatile and more thermodynamically stable owing to its non-canonical base-pairing, tertiary interactions and base-stacking property. A 90-nucleotide RNA can exhibit 4⁹⁰ nanostructures, and its loops and tertiary architecture can serve as a mounting dovetail that eliminates the need for external linking dowels. Its enzymatic and fluorogenic activity creates diversity in computational design. Varieties of small RNA can work cooperatively, synergistically or antagonistically to carry out computational logic circuits. The riboswitch and enzymatic ribozyme activities and its special in vivo attributes offer a great potential for in vivo computation. Unique features in transcription, termination, self-assembly, self-processing and acid resistance enable in vivo production of RNA nanoparticles that harbour various regulators for intracellular manipulation. With all these advantages, RNA computation is promising, but it is still in its infancy. Many challenges still exist. Collaborations between RNA nanotechnologists and computer scientists are necessary to advance this nascent technology.
Photochromic molecular implementations of universal computation.
Chaplin, Jack C; Krasnogor, Natalio; Russell, Noah A
2014-12-01
Unconventional computing is an area of research in which novel materials and paradigms are utilised to implement computation. Previously we have demonstrated how registers, logic gates and logic circuits can be implemented, unconventionally, with a biocompatible molecular switch, NitroBIPS, embedded in a polymer matrix. NitroBIPS and related molecules have been shown elsewhere to be capable of modifying many biological processes in a manner that is dependent on its molecular form. Thus, one possible application of this type of unconventional computing is to embed computational processes into biological systems. Here we expand on our earlier proof-of-principle work and demonstrate that universal computation can be implemented using NitroBIPS. We have previously shown that spatially localised computational elements, including registers and logic gates, can be produced. We explain how parallel registers can be implemented, then demonstrate an application of parallel registers in the form of Turing machine tapes, and demonstrate both parallel registers and logic circuits in the form of elementary cellular automata. The Turing machines and elementary cellular automata utilise the same samples and same hardware to implement their registers, logic gates and logic circuits; and both represent examples of universal computing paradigms. This shows that homogenous photochromic computational devices can be dynamically repurposed without invasive reconfiguration. The result represents an important, necessary step towards demonstrating the general feasibility of interfacial computation embedded in biological systems or other unconventional materials and environments. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.
Computer Analogies: Teaching Molecular Biology and Ecology.
ERIC Educational Resources Information Center
Rice, Stanley; McArthur, John
2002-01-01
Suggests that computer science analogies can aid the understanding of gene expression, including the storage of genetic information on chromosomes. Presents a matrix of biology and computer science concepts. (DDR)
Greco, Cristina; Marini, Alberto; Frezza, Elisa; Ferrarini, Alberta
2014-05-19
We present a computational investigation of the nematic phase of the bent-core liquid crystal A131. We use an integrated approach that bridges density functional theory calculations of molecular geometry and torsional potentials to elastic properties through the molecular conformational and orientational distribution function. This unique capability to simultaneously access different length scales enables us to consistently describe molecular and material properties. We can reassign (13)C NMR chemical shifts and analyze the dependence of phase properties on molecular shape. Focusing on the elastic constants we can draw some general conclusions on the unconventional behavior of bent-core nematics and highlight the crucial role of a properly-bent shape. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.
Kumar, Sudhir; Stecher, Glen; Li, Michael; Knyaz, Christina; Tamura, Koichiro
2018-06-01
The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
AceCloud: Molecular Dynamics Simulations in the Cloud.
Harvey, M J; De Fabritiis, G
2015-05-26
We present AceCloud, an on-demand service for molecular dynamics simulations. AceCloud is designed to facilitate the secure execution of large ensembles of simulations on an external cloud computing service (currently Amazon Web Services). The AceCloud client, integrated into the ACEMD molecular dynamics package, provides an easy-to-use interface that abstracts all aspects of interaction with the cloud services. This gives the user the experience that all simulations are running on their local machine, minimizing the learning curve typically associated with the transition to using high performance computing services.
Characterizing the heterogeneity of tumor tissues from spatially resolved molecular measures
Zavodszky, Maria I.
2017-01-01
Background Tumor heterogeneity can manifest itself by sub-populations of cells having distinct phenotypic profiles expressed as diverse molecular, morphological and spatial distributions. This inherent heterogeneity poses challenges in terms of diagnosis, prognosis and efficient treatment. Consequently, tools and techniques are being developed to properly characterize and quantify tumor heterogeneity. Multiplexed immunofluorescence (MxIF) is one such technology that offers molecular insight into both inter-individual and intratumor heterogeneity. It enables the quantification of both the concentration and spatial distribution of 60+ proteins across a tissue section. Upon bioimage processing, protein expression data can be generated for each cell from a tissue field of view. Results The Multi-Omics Heterogeneity Analysis (MOHA) tool was developed to compute tissue heterogeneity metrics from MxIF spatially resolved tissue imaging data. This technique computes the molecular state of each cell in a sample based on a pathway or gene set. Spatial states are then computed based on the spatial arrangements of the cells as distinguished by their respective molecular states. MOHA computes tissue heterogeneity metrics from the distributions of these molecular and spatially defined states. A colorectal cancer cohort of approximately 700 subjects with MxIF data is presented to demonstrate the MOHA methodology. Within this dataset, statistically significant correlations were found between the intratumor AKT pathway state diversity and cancer stage and histological tumor grade. Furthermore, intratumor spatial diversity metrics were found to correlate with cancer recurrence. Conclusions MOHA provides a simple and robust approach to characterize molecular and spatial heterogeneity of tissues. Research projects that generate spatially resolved tissue imaging data can take full advantage of this useful technique. The MOHA algorithm is implemented as a freely available R script (see supplementary information). PMID:29190747
Bubble nucleation in simple and molecular liquids via the largest spherical cavity method
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gonzalez, Miguel A., E-mail: m.gonzalez12@imperial.ac.uk; Department of Chemistry, Imperial College London, London SW7 2AZ; Abascal, José L. F.
2015-04-21
In this work, we propose a methodology to compute bubble nucleation free energy barriers using trajectories generated via molecular dynamics simulations. We follow the bubble nucleation process by means of a local order parameter, defined by the volume of the largest spherical cavity (LSC) formed in the nucleating trajectories. This order parameter simplifies considerably the monitoring of the nucleation events, as compared with the previous approaches which require ad hoc criteria to classify the atoms and molecules as liquid or vapor. The combination of the LSC and the mean first passage time technique can then be used to obtain themore » free energy curves. Upon computation of the cavity distribution function the nucleation rate and free-energy barrier can then be computed. We test our method against recent computations of bubble nucleation in simple liquids and water at negative pressures. We obtain free-energy barriers in good agreement with the previous works. The LSC method provides a versatile and computationally efficient route to estimate the volume of critical bubbles the nucleation rate and to compute bubble nucleation free-energies in both simple and molecular liquids.« less
Molecular implementation of simple logic programs.
Ran, Tom; Kaplan, Shai; Shapiro, Ehud
2009-10-01
Autonomous programmable computing devices made of biomolecules could interact with a biological environment and be used in future biological and medical applications. Biomolecular implementations of finite automata and logic gates have already been developed. Here, we report an autonomous programmable molecular system based on the manipulation of DNA strands that is capable of performing simple logical deductions. Using molecular representations of facts such as Man(Socrates) and rules such as Mortal(X) <-- Man(X) (Every Man is Mortal), the system can answer molecular queries such as Mortal(Socrates)? (Is Socrates Mortal?) and Mortal(X)? (Who is Mortal?). This biomolecular computing system compares favourably with previous approaches in terms of expressive power, performance and precision. A compiler translates facts, rules and queries into their molecular representations and subsequently operates a robotic system that assembles the logical deductions and delivers the result. This prototype is the first simple programming language with a molecular-scale implementation.
The emerging field of computational toxicology applies mathematical and computer models and molecular biological and chemical approaches to explore both qualitative and quantitative relationships between sources of environmental pollutant exposure and adverse health outcomes. Th...
jAMVLE, a New Integrated Molecular Visualization Learning Environment
ERIC Educational Resources Information Center
Bottomley, Steven; Chandler, David; Morgan, Eleanor; Helmerhorst, Erik
2006-01-01
A new computer-based molecular visualization tool has been developed for teaching, and learning, molecular structure. This java-based jmol Amalgamated Molecular Visualization Learning Environment (jAMVLE) is platform-independent, integrated, and interactive. It has an overall graphical user interface that is intuitive and easy to use. The…
ERIC Educational Resources Information Center
Litofsky, Joshua; Viswanathan, Rama
2015-01-01
Matrix diagonalization, the key technique at the heart of modern computational chemistry for the numerical solution of the Schrödinger equation, can be easily introduced in the physical chemistry curriculum in a pedagogical context using simple Hückel molecular orbital theory for p bonding in molecules. We present details and results of…
Molecular Isotopic Distribution Analysis (MIDAs) with Adjustable Mass Accuracy
NASA Astrophysics Data System (ADS)
Alves, Gelio; Ogurtsov, Aleksey Y.; Yu, Yi-Kuo
2014-01-01
In this paper, we present Molecular Isotopic Distribution Analysis (MIDAs), a new software tool designed to compute molecular isotopic distributions with adjustable accuracies. MIDAs offers two algorithms, one polynomial-based and one Fourier-transform-based, both of which compute molecular isotopic distributions accurately and efficiently. The polynomial-based algorithm contains few novel aspects, whereas the Fourier-transform-based algorithm consists mainly of improvements to other existing Fourier-transform-based algorithms. We have benchmarked the performance of the two algorithms implemented in MIDAs with that of eight software packages (BRAIN, Emass, Mercury, Mercury5, NeutronCluster, Qmass, JFC, IC) using a consensus set of benchmark molecules. Under the proposed evaluation criteria, MIDAs's algorithms, JFC, and Emass compute with comparable accuracy the coarse-grained (low-resolution) isotopic distributions and are more accurate than the other software packages. For fine-grained isotopic distributions, we compared IC, MIDAs's polynomial algorithm, and MIDAs's Fourier transform algorithm. Among the three, IC and MIDAs's polynomial algorithm compute isotopic distributions that better resemble their corresponding exact fine-grained (high-resolution) isotopic distributions. MIDAs can be accessed freely through a user-friendly web-interface at http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/midas/index.html.
Vermorel, Romain; Oulebsir, Fouad; Galliero, Guillaume
2017-09-14
The computation of diffusion coefficients in molecular systems ranks among the most useful applications of equilibrium molecular dynamics simulations. However, when dealing with the problem of fluid diffusion through vanishingly thin interfaces, classical techniques are not applicable. This is because the volume of space in which molecules diffuse is ill-defined. In such conditions, non-equilibrium techniques allow for the computation of transport coefficients per unit interface width, but their weak point lies in their inability to isolate the contribution of the different physical mechanisms prone to impact the flux of permeating molecules. In this work, we propose a simple and accurate method to compute the diffusional transport coefficient of a pure fluid through a planar interface from equilibrium molecular dynamics simulations, in the form of a diffusion coefficient per unit interface width. In order to demonstrate its validity and accuracy, we apply our method to the case study of a dilute gas diffusing through a smoothly repulsive single-layer porous solid. We believe this complementary technique can benefit to the interpretation of the results obtained on single-layer membranes by means of complex non-equilibrium methods.
Molecular Isotopic Distribution Analysis (MIDAs) with adjustable mass accuracy.
Alves, Gelio; Ogurtsov, Aleksey Y; Yu, Yi-Kuo
2014-01-01
In this paper, we present Molecular Isotopic Distribution Analysis (MIDAs), a new software tool designed to compute molecular isotopic distributions with adjustable accuracies. MIDAs offers two algorithms, one polynomial-based and one Fourier-transform-based, both of which compute molecular isotopic distributions accurately and efficiently. The polynomial-based algorithm contains few novel aspects, whereas the Fourier-transform-based algorithm consists mainly of improvements to other existing Fourier-transform-based algorithms. We have benchmarked the performance of the two algorithms implemented in MIDAs with that of eight software packages (BRAIN, Emass, Mercury, Mercury5, NeutronCluster, Qmass, JFC, IC) using a consensus set of benchmark molecules. Under the proposed evaluation criteria, MIDAs's algorithms, JFC, and Emass compute with comparable accuracy the coarse-grained (low-resolution) isotopic distributions and are more accurate than the other software packages. For fine-grained isotopic distributions, we compared IC, MIDAs's polynomial algorithm, and MIDAs's Fourier transform algorithm. Among the three, IC and MIDAs's polynomial algorithm compute isotopic distributions that better resemble their corresponding exact fine-grained (high-resolution) isotopic distributions. MIDAs can be accessed freely through a user-friendly web-interface at http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/midas/index.html.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tamrin, Mohd Izzuddin Mohd; Turaev, Sherzod; Sembok, Tengku Mohd Tengku
There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes andmore » fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy processes. We define weighted Watson-Crick automata adapting weight restriction mechanisms associated with formal grammars and automata. We also study the generative capacities of weighted Watson-Crick automata, including probabilistic and fuzzy variants. We show that weighted variants of Watson-Crick automata increase their generative power.« less
Li, Kenli; Zou, Shuting; Xv, Jin
2008-01-01
Elliptic curve cryptographic algorithms convert input data to unrecognizable encryption and the unrecognizable data back again into its original decrypted form. The security of this form of encryption hinges on the enormous difficulty that is required to solve the elliptic curve discrete logarithm problem (ECDLP), especially over GF(2(n)), n in Z+. This paper describes an effective method to find solutions to the ECDLP by means of a molecular computer. We propose that this research accomplishment would represent a breakthrough for applied biological computation and this paper demonstrates that in principle this is possible. Three DNA-based algorithms: a parallel adder, a parallel multiplier, and a parallel inverse over GF(2(n)) are described. The biological operation time of all of these algorithms is polynomial with respect to n. Considering this analysis, cryptography using a public key might be less secure. In this respect, a principal contribution of this paper is to provide enhanced evidence of the potential of molecular computing to tackle such ambitious computations.
Li, Kenli; Zou, Shuting; Xv, Jin
2008-01-01
Elliptic curve cryptographic algorithms convert input data to unrecognizable encryption and the unrecognizable data back again into its original decrypted form. The security of this form of encryption hinges on the enormous difficulty that is required to solve the elliptic curve discrete logarithm problem (ECDLP), especially over GF(2n), n ∈ Z+. This paper describes an effective method to find solutions to the ECDLP by means of a molecular computer. We propose that this research accomplishment would represent a breakthrough for applied biological computation and this paper demonstrates that in principle this is possible. Three DNA-based algorithms: a parallel adder, a parallel multiplier, and a parallel inverse over GF(2n) are described. The biological operation time of all of these algorithms is polynomial with respect to n. Considering this analysis, cryptography using a public key might be less secure. In this respect, a principal contribution of this paper is to provide enhanced evidence of the potential of molecular computing to tackle such ambitious computations. PMID:18431451
Weighted Watson-Crick automata
NASA Astrophysics Data System (ADS)
Tamrin, Mohd Izzuddin Mohd; Turaev, Sherzod; Sembok, Tengku Mohd Tengku
2014-07-01
There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes and fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy processes. We define weighted Watson-Crick automata adapting weight restriction mechanisms associated with formal grammars and automata. We also study the generative capacities of weighted Watson-Crick automata, including probabilistic and fuzzy variants. We show that weighted variants of Watson-Crick automata increase their generative power.
Computational modeling in melanoma for novel drug discovery.
Pennisi, Marzio; Russo, Giulia; Di Salvatore, Valentina; Candido, Saverio; Libra, Massimo; Pappalardo, Francesco
2016-06-01
There is a growing body of evidence highlighting the applications of computational modeling in the field of biomedicine. It has recently been applied to the in silico analysis of cancer dynamics. In the era of precision medicine, this analysis may allow the discovery of new molecular targets useful for the design of novel therapies and for overcoming resistance to anticancer drugs. According to its molecular behavior, melanoma represents an interesting tumor model in which computational modeling can be applied. Melanoma is an aggressive tumor of the skin with a poor prognosis for patients with advanced disease as it is resistant to current therapeutic approaches. This review discusses the basics of computational modeling in melanoma drug discovery and development. Discussion includes the in silico discovery of novel molecular drug targets, the optimization of immunotherapies and personalized medicine trials. Mathematical and computational models are gradually being used to help understand biomedical data produced by high-throughput analysis. The use of advanced computer models allowing the simulation of complex biological processes provides hypotheses and supports experimental design. The research in fighting aggressive cancers, such as melanoma, is making great strides. Computational models represent the key component to complement these efforts. Due to the combinatorial complexity of new drug discovery, a systematic approach based only on experimentation is not possible. Computational and mathematical models are necessary for bringing cancer drug discovery into the era of omics, big data and personalized medicine.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schröder, Florian A. Y. N.; Cole, Jacqueline M.; Waddell, Paul G.
2015-02-03
The re-functionalization of a series of four well-known industrial laser dyes, based on benzophenoxazine, is explored with the prospect of molecularly engineering new chromophores for dye-sensitized solar cell (DSC) applications. Such engineering is important since a lack of suitable dyes is stifling the progress of DSC technology. The conceptual idea involves making laser dyes DSC-active by chemical modification, while maintaining their key property attributes that are attractive to DSC applications. This molecular engineering follows a step-wise approach. Firstly, molecular structures and optical absorption properties are determined for the parent laser dyes: Cresyl Violet (1); Oxazine 170 (2); Nile Blue Amore » (3), Oxazine 750 (4). These reveal structure-property relationships which define the prerequisites for computational molecular design of DSC dyes; the nature of their molecular architecture (D-π-A) and intramolecular charge transfer. Secondly, new DSC dyes are computationally designed by the in silico addition of a carboxylic acid anchor at various chemical substitution points in the parent laser dyes. A comparison of the resulting frontier molecular orbital energy levels with the conduction band edge of a TiO2 DSC photoanode and the redox potential of two electrolyte options I-/I3- and Co(II/III)tris(bipyridyl) suggests promise for these computationally designed dyes as co-sensitizers for DSC applications.« less
A Simple Method for Automated Equilibration Detection in Molecular Simulations.
Chodera, John D
2016-04-12
Molecular simulations intended to compute equilibrium properties are often initiated from configurations that are highly atypical of equilibrium samples, a practice which can generate a distinct initial transient in mechanical observables computed from the simulation trajectory. Traditional practice in simulation data analysis recommends this initial portion be discarded to equilibration, but no simple, general, and automated procedure for this process exists. Here, we suggest a conceptually simple automated procedure that does not make strict assumptions about the distribution of the observable of interest in which the equilibration time is chosen to maximize the number of effectively uncorrelated samples in the production timespan used to compute equilibrium averages. We present a simple Python reference implementation of this procedure and demonstrate its utility on typical molecular simulation data.
NASA Astrophysics Data System (ADS)
Sagdinc, Seda; Kandemirli, Fatma; Bayari, Sevgi Haman
2007-02-01
Sertraline hydrochloride is a highly potent and selective inhibitor of serotonin (5HT). It is a basic compound of pharmaceutical application for antidepressant treatment (brand name: Zoloft). Ab initio and density functional computations of the vibrational (IR) spectrum, the molecular geometry, the atomic charges and polarizabilities were carried out. The infrared spectrum of sertraline is recorded in the solid state. The observed IR wave numbers were analysed in light of the computed vibrational spectrum. On the basis of the comparison between calculated and experimental results and the comparison with related molecules, assignments of fundamental vibrational modes are examined. The X-ray geometry and experimental frequencies are compared with the results of our theoretical calculations.
A simple method for automated equilibration detection in molecular simulations
Chodera, John D.
2016-01-01
Molecular simulations intended to compute equilibrium properties are often initiated from configurations that are highly atypical of equilibrium samples, a practice which can generate a distinct initial transient in mechanical observables computed from the simulation trajectory. Traditional practice in simulation data analysis recommends this initial portion be discarded to equilibration, but no simple, general, and automated procedure for this process exists. Here, we suggest a conceptually simple automated procedure that does not make strict assumptions about the distribution of the observable of interest, in which the equilibration time is chosen to maximize the number of effectively uncorrelated samples in the production timespan used to compute equilibrium averages. We present a simple Python reference implementation of this procedure, and demonstrate its utility on typical molecular simulation data. PMID:26771390
Surface similarity-based molecular query-retrieval
Singh, Rahul
2007-01-01
Background Discerning the similarity between molecules is a challenging problem in drug discovery as well as in molecular biology. The importance of this problem is due to the fact that the biochemical characteristics of a molecule are closely related to its structure. Therefore molecular similarity is a key notion in investigations targeting exploration of molecular structural space, query-retrieval in molecular databases, and structure-activity modelling. Determining molecular similarity is related to the choice of molecular representation. Currently, representations with high descriptive power and physical relevance like 3D surface-based descriptors are available. Information from such representations is both surface-based and volumetric. However, most techniques for determining molecular similarity tend to focus on idealized 2D graph-based descriptors due to the complexity that accompanies reasoning with more elaborate representations. Results This paper addresses the problem of determining similarity when molecules are described using complex surface-based representations. It proposes an intrinsic, spherical representation that systematically maps points on a molecular surface to points on a standard coordinate system (a sphere). Molecular surface properties such as shape, field strengths, and effects due to field super-positioningcan then be captured as distributions on the surface of the sphere. Surface-based molecular similarity is subsequently determined by computing the similarity of the surface-property distributions using a novel formulation of histogram-intersection. The similarity formulation is not only sensitive to the 3D distribution of the surface properties, but is also highly efficient to compute. Conclusion The proposed method obviates the computationally expensive step of molecular pose-optimisation, can incorporate conformational variations, and facilitates highly efficient determination of similarity by directly comparing molecular surfaces and surface-based properties. Retrieval performance, applications in structure-activity modeling of complex biological properties, and comparisons with existing research and commercial methods demonstrate the validity and effectiveness of the approach. PMID:17634096
NASA Astrophysics Data System (ADS)
Schwörer, Magnus; Lorenzen, Konstantin; Mathias, Gerald; Tavan, Paul
2015-03-01
Recently, a novel approach to hybrid quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations has been suggested [Schwörer et al., J. Chem. Phys. 138, 244103 (2013)]. Here, the forces acting on the atoms are calculated by grid-based density functional theory (DFT) for a solute molecule and by a polarizable molecular mechanics (PMM) force field for a large solvent environment composed of several 103-105 molecules as negative gradients of a DFT/PMM hybrid Hamiltonian. The electrostatic interactions are efficiently described by a hierarchical fast multipole method (FMM). Adopting recent progress of this FMM technique [Lorenzen et al., J. Chem. Theory Comput. 10, 3244 (2014)], which particularly entails a strictly linear scaling of the computational effort with the system size, and adapting this revised FMM approach to the computation of the interactions between the DFT and PMM fragments of a simulation system, here, we show how one can further enhance the efficiency and accuracy of such DFT/PMM-MD simulations. The resulting gain of total performance, as measured for alanine dipeptide (DFT) embedded in water (PMM) by the product of the gains in efficiency and accuracy, amounts to about one order of magnitude. We also demonstrate that the jointly parallelized implementation of the DFT and PMM-MD parts of the computation enables the efficient use of high-performance computing systems. The associated software is available online.
Protocols for Molecular Dynamics Simulations of RNA Nanostructures.
Kim, Taejin; Kasprzak, Wojciech K; Shapiro, Bruce A
2017-01-01
Molecular dynamics (MD) simulations have been used as one of the main research tools to study a wide range of biological systems and bridge the gap between X-ray crystallography or NMR structures and biological mechanism. In the field of RNA nanostructures, MD simulations have been used to fix steric clashes in computationally designed RNA nanostructures, characterize the dynamics, and investigate the interaction between RNA and other biomolecules such as delivery agents and membranes.In this chapter we present examples of computational protocols for molecular dynamics simulations in explicit and implicit solvent using the Amber Molecular Dynamics Package. We also show examples of post-simulation analysis steps and briefly mention selected tools beyond the Amber package. Limitations of the methods, tools, and protocols are also discussed. Most of the examples are illustrated for a small RNA duplex (helix), but the protocols are applicable to any nucleic acid structure, subject only to the computational speed and memory limitations of the hardware available to the user.
Over the last several years, there has been increased pressure to utilize novel technologies derived from computational chemistry, molecular biology and systems biology in toxicological risk assessment. This new area has been referred to as "Computational Toxicology". Our resear...
Caetano-Anollés, Gustavo; Caetano-Anollés, Derek
2015-01-01
Accretion occurs pervasively in nature at widely different timeframes. The process also manifests in the evolution of macromolecules. Here we review recent computational and structural biology studies of evolutionary accretion that make use of the ideographic (historical, retrodictive) and nomothetic (universal, predictive) scientific frameworks. Computational studies uncover explicit timelines of accretion of structural parts in molecular repertoires and molecules. Phylogenetic trees of protein structural domains and proteomes and their molecular functions were built from a genomic census of millions of encoded proteins and associated terminal Gene Ontology terms. Trees reveal a ‘metabolic-first’ origin of proteins, the late development of translation, and a patchwork distribution of proteins in biological networks mediated by molecular recruitment. Similarly, the natural history of ancient RNA molecules inferred from trees of molecular substructures built from a census of molecular features shows patchwork-like accretion patterns. Ideographic analyses of ribosomal history uncover the early appearance of structures supporting mRNA decoding and tRNA translocation, the coevolution of ribosomal proteins and RNA, and a first evolutionary transition that brings ribosomal subunits together into a processive protein biosynthetic complex. Nomothetic structural biology studies of tertiary interactions and ancient insertions in rRNA complement these findings, once concentric layering assumptions are removed. Patterns of coaxial helical stacking reveal a frustrated dynamics of outward and inward ribosomal growth possibly mediated by structural grafting. The early rise of the ribosomal ‘turnstile’ suggests an evolutionary transition in natural biological computation. Results make explicit the need to understand processes of molecular growth and information transfer of macromolecules. PMID:27096056
Molecular Sticker Model Stimulation on Silicon for a Maximum Clique Problem
Ning, Jianguo; Li, Yanmei; Yu, Wen
2015-01-01
Molecular computers (also called DNA computers), as an alternative to traditional electronic computers, are smaller in size but more energy efficient, and have massive parallel processing capacity. However, DNA computers may not outperform electronic computers owing to their higher error rates and some limitations of the biological laboratory. The stickers model, as a typical DNA-based computer, is computationally complete and universal, and can be viewed as a bit-vertically operating machine. This makes it attractive for silicon implementation. Inspired by the information processing method on the stickers computer, we propose a novel parallel computing model called DEM (DNA Electronic Computing Model) on System-on-a-Programmable-Chip (SOPC) architecture. Except for the significant difference in the computing medium—transistor chips rather than bio-molecules—the DEM works similarly to DNA computers in immense parallel information processing. Additionally, a plasma display panel (PDP) is used to show the change of solutions, and helps us directly see the distribution of assignments. The feasibility of the DEM is tested by applying it to compute a maximum clique problem (MCP) with eight vertices. Owing to the limited computing sources on SOPC architecture, the DEM could solve moderate-size problems in polynomial time. PMID:26075867
Ding, Wendu; Koepf, Matthieu; Koenigsmann, Christopher; ...
2015-11-03
Here, we report a systematic computational search of molecular frameworks for intrinsic rectification of electron transport. The screening of molecular rectifiers includes 52 molecules and conformers spanning over 9 series of structural motifs. N-Phenylbenzamide is found to be a promising framework with both suitable conductance and rectification properties. A targeted screening performed on 30 additional derivatives and conformers of N-phenylbenzamide yielded enhanced rectification based on asymmetric functionalization. We demonstrate that electron-donating substituent groups that maintain an asymmetric distribution of charge in the dominant transport channel (e.g., HOMO) enhance rectification by raising the channel closer to the Fermi level. These findingsmore » are particularly valuable for the design of molecular assemblies that could ensure directionality of electron transport in a wide range of applications, from molecular electronics to catalytic reactions.« less
Nishizawa, Hiroaki; Nishimura, Yoshifumi; Kobayashi, Masato; Irle, Stephan; Nakai, Hiromi
2016-08-05
The linear-scaling divide-and-conquer (DC) quantum chemical methodology is applied to the density-functional tight-binding (DFTB) theory to develop a massively parallel program that achieves on-the-fly molecular reaction dynamics simulations of huge systems from scratch. The functions to perform large scale geometry optimization and molecular dynamics with DC-DFTB potential energy surface are implemented to the program called DC-DFTB-K. A novel interpolation-based algorithm is developed for parallelizing the determination of the Fermi level in the DC method. The performance of the DC-DFTB-K program is assessed using a laboratory computer and the K computer. Numerical tests show the high efficiency of the DC-DFTB-K program, a single-point energy gradient calculation of a one-million-atom system is completed within 60 s using 7290 nodes of the K computer. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Saglam, Ali S; Chong, Lillian T
2016-01-14
An essential baseline for determining the extent to which electrostatic interactions enhance the kinetics of protein-protein association is the "basal" kon, which is the rate constant for association in the absence of electrostatic interactions. However, since such association events are beyond the milliseconds time scale, it has not been practical to compute the basal kon by directly simulating the association with flexible models. Here, we computed the basal kon for barnase and barstar, two of the most rapidly associating proteins, using highly efficient, flexible molecular simulations. These simulations involved (a) pseudoatomic protein models that reproduce the molecular shapes, electrostatic, and diffusion properties of all-atom models, and (b) application of the weighted ensemble path sampling strategy, which enhanced the efficiency of generating association events by >130-fold. We also examined the extent to which the computed basal kon is affected by inclusion of intermolecular hydrodynamic interactions in the simulations.
Marc Snir | Argonne National Laboratory
Molecular biology Proteomics Environmental science & technology Air quality Atmospheric & climate , H.S., Jr., Demonstrating the scalability of a molecular dynamics application on a Petaflop computer Transformations IGSBInstitute for Genomics and Systems Biology IMEInstitute for Molecular Engineering JCESRJoint
Teaching Ionic Solvation Structure with a Monte Carlo Liquid Simulation Program
ERIC Educational Resources Information Center
Serrano, Agostinho; Santos, Flavia M. T.; Greca, Ileana M.
2004-01-01
The use of molecular dynamics and Monte Carlo methods has provided efficient means to stimulate the behavior of molecular liquids and solutions. A Monte Carlo simulation program is used to compute the structure of liquid water and of water as a solvent to Na(super +), Cl(super -), and Ar on a personal computer to show that it is easily feasible to…
Fukunishi, Yoshifumi; Mashimo, Tadaaki; Misoo, Kiyotaka; Wakabayashi, Yoshinori; Miyaki, Toshiaki; Ohta, Seiji; Nakamura, Mayu; Ikeda, Kazuyoshi
2016-01-01
Computer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design.
Fukunishi, Yoshifumi; Mashimo, Tadaaki; Misoo, Kiyotaka; Wakabayashi, Yoshinori; Miyaki, Toshiaki; Ohta, Seiji; Nakamura, Mayu; Ikeda, Kazuyoshi
2016-01-01
Abstract: Background Computer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design. PMID:27075578
Towards quantum chemistry on a quantum computer.
Lanyon, B P; Whitfield, J D; Gillett, G G; Goggin, M E; Almeida, M P; Kassal, I; Biamonte, J D; Mohseni, M; Powell, B J; Barbieri, M; Aspuru-Guzik, A; White, A G
2010-02-01
Exact first-principles calculations of molecular properties are currently intractable because their computational cost grows exponentially with both the number of atoms and basis set size. A solution is to move to a radically different model of computing by building a quantum computer, which is a device that uses quantum systems themselves to store and process data. Here we report the application of the latest photonic quantum computer technology to calculate properties of the smallest molecular system: the hydrogen molecule in a minimal basis. We calculate the complete energy spectrum to 20 bits of precision and discuss how the technique can be expanded to solve large-scale chemical problems that lie beyond the reach of modern supercomputers. These results represent an early practical step toward a powerful tool with a broad range of quantum-chemical applications.
Efficient and Flexible Computation of Many-Electron Wave Function Overlaps.
Plasser, Felix; Ruckenbauer, Matthias; Mai, Sebastian; Oppel, Markus; Marquetand, Philipp; González, Leticia
2016-03-08
A new algorithm for the computation of the overlap between many-electron wave functions is described. This algorithm allows for the extensive use of recurring intermediates and thus provides high computational efficiency. Because of the general formalism employed, overlaps can be computed for varying wave function types, molecular orbitals, basis sets, and molecular geometries. This paves the way for efficiently computing nonadiabatic interaction terms for dynamics simulations. In addition, other application areas can be envisaged, such as the comparison of wave functions constructed at different levels of theory. Aside from explaining the algorithm and evaluating the performance, a detailed analysis of the numerical stability of wave function overlaps is carried out, and strategies for overcoming potential severe pitfalls due to displaced atoms and truncated wave functions are presented.
Radke, Wolfgang
2004-03-05
Simulations of the distribution coefficients of linear polymers and regular combs with various spacings between the arms have been performed. The distribution coefficients were plotted as a function of the number of segments in order to compare the size exclusion chromatography (SEC)-elution behavior of combs relative to linear molecules. By comparing the simulated SEC-calibration curves it is possible to predict the elution behavior of comb-shaped polymers relative to linear ones. In order to compare the results obtained by computer simulations with experimental data, a variety of comb-shaped polymers varying in side chain length, spacing between the side chains and molecular weights of the backbone were analyzed by SEC with light-scattering detection. It was found that the computer simulations could predict the molecular weights of linear molecules having the same retention volume with an accuracy of about 10%, i.e. the error in the molecular weight obtained by calculating the molecular weight of the comb-polymer based on a calibration curve constructed using linear standards and the results of the computer simulations are of the same magnitude as the experimental error of absolute molecular weight determination.
Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments
De Paris, Renata; Quevedo, Christian V.; Ruiz, Duncan D.; Norberto de Souza, Osmar; Barros, Rodrigo C.
2015-01-01
Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand. PMID:25873944
NASA Technical Reports Server (NTRS)
Johnson, H. R.; Krupp, B. M.
1975-01-01
An opacity sampling (OS) technique for treating the radiative opacity of large numbers of atomic and molecular lines in cool stellar atmospheres is presented. Tests were conducted and results show that the structure of atmospheric models is accurately fixed by the use of 1000 frequency points, and 500 frequency points is often adequate. The effects of atomic and molecular lines are separately studied. A test model computed by using the OS method agrees very well with a model having identical atmospheric parameters computed by the giant line (opacity distribution function) method.
Energy conserving, linear scaling Born-Oppenheimer molecular dynamics.
Cawkwell, M J; Niklasson, Anders M N
2012-10-07
Born-Oppenheimer molecular dynamics simulations with long-term conservation of the total energy and a computational cost that scales linearly with system size have been obtained simultaneously. Linear scaling with a low pre-factor is achieved using density matrix purification with sparse matrix algebra and a numerical threshold on matrix elements. The extended Lagrangian Born-Oppenheimer molecular dynamics formalism [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] yields microcanonical trajectories with the approximate forces obtained from the linear scaling method that exhibit no systematic drift over hundreds of picoseconds and which are indistinguishable from trajectories computed using exact forces.
Searching molecular structure databases with tandem mass spectra using CSI:FingerID
Dührkop, Kai; Shen, Huibin; Meusel, Marvin; Rousu, Juho; Böcker, Sebastian
2015-01-01
Metabolites provide a direct functional signature of cellular state. Untargeted metabolomics experiments usually rely on tandem MS to identify the thousands of compounds in a biological sample. Today, the vast majority of metabolites remain unknown. We present a method for searching molecular structure databases using tandem MS data of small molecules. Our method computes a fragmentation tree that best explains the fragmentation spectrum of an unknown molecule. We use the fragmentation tree to predict the molecular structure fingerprint of the unknown compound using machine learning. This fingerprint is then used to search a molecular structure database such as PubChem. Our method is shown to improve on the competing methods for computational metabolite identification by a considerable margin. PMID:26392543
Molecular dynamics simulations through GPU video games technologies
Loukatou, Styliani; Papageorgiou, Louis; Fakourelis, Paraskevas; Filntisi, Arianna; Polychronidou, Eleftheria; Bassis, Ioannis; Megalooikonomou, Vasileios; Makałowski, Wojciech; Vlachakis, Dimitrios; Kossida, Sophia
2016-01-01
Bioinformatics is the scientific field that focuses on the application of computer technology to the management of biological information. Over the years, bioinformatics applications have been used to store, process and integrate biological and genetic information, using a wide range of methodologies. One of the most de novo techniques used to understand the physical movements of atoms and molecules is molecular dynamics (MD). MD is an in silico method to simulate the physical motions of atoms and molecules under certain conditions. This has become a state strategic technique and now plays a key role in many areas of exact sciences, such as chemistry, biology, physics and medicine. Due to their complexity, MD calculations could require enormous amounts of computer memory and time and therefore their execution has been a big problem. Despite the huge computational cost, molecular dynamics have been implemented using traditional computers with a central memory unit (CPU). A graphics processing unit (GPU) computing technology was first designed with the goal to improve video games, by rapidly creating and displaying images in a frame buffer such as screens. The hybrid GPU-CPU implementation, combined with parallel computing is a novel technology to perform a wide range of calculations. GPUs have been proposed and used to accelerate many scientific computations including MD simulations. Herein, we describe the new methodologies developed initially as video games and how they are now applied in MD simulations. PMID:27525251
A Computational and Theoretical Study of Conductance in Hydrogen-bonded Molecular Junctions
NASA Astrophysics Data System (ADS)
Wimmer, Michael
This thesis is devoted to the theoretical and computational study of electron transport in molecular junctions where one or more hydrogen bonds are involved in the process. While electron transport through covalent bonds has been extensively studied, in recent work the focus has been shifted towards hydrogen-bonded systems due to their ubiquitous presence in biological systems and their potential in forming nano-junctions between molecular electronic devices and biological systems. This analysis allows us to significantly expand our comprehension of the experimentally observed result that the inclusion of hydrogen bonding in a molecular junction significantly impacts its transport properties, a fact that has important implications for our understanding of transport through DNA, and nano-biological interfaces in general. In part of this work I have explored the implications of quasiresonant transport in short chains of weakly-bonded molecular junctions involving hydrogen bonds. I used theoretical and computational analysis to interpret recent experiments and explain the role of Fano resonances in the transmission properties of the junction. In a different direction, I have undertaken the study of the transversal conduction through nucleotide chains that involve a variable number of different hydrogen bonds, e.g. NH˙˙˙O, OH˙˙˙O, and NH˙˙˙N, which are the three most prevalent hydrogen bonds in biological systems and organic electronics. My effort here has focused on the analysis of electronic descriptors that allow a simplified conceptual and computational understanding of transport properties. Specifically, I have expanded our previous work where the molecular polarizability was used as a conductance descriptor to include the possibility of atomic and bond partitions of the molecular polarizability. This is important because it affords an alternative molecular description of conductance that is not based on the conventional view of molecular orbitals as transport channels. My findings suggest that the hydrogen-bond networks are crucial in understanding the conductance of these junctions. A broader impact of this work pertains the fact that characterizing transport through hydrogen bonding networks may help in developing faster and cost-effective approaches to personalized medicine, to advance DNA sequencing and implantable electronics, and to progress in the design and application of new drugs.
Takeshima, T; Takahashi, T; Yamashita, J; Okada, Y; Watanabe, S
2018-05-25
Multi-emitter fitting algorithms have been developed to improve the temporal resolution of single-molecule switching nanoscopy, but the molecular density range they can analyse is narrow and the computation required is intensive, significantly limiting their practical application. Here, we propose a computationally fast method, wedged template matching (WTM), an algorithm that uses a template matching technique to localise molecules at any overlapping molecular density from sparse to ultrahigh density with subdiffraction resolution. WTM achieves the localization of overlapping molecules at densities up to 600 molecules μm -2 with a high detection sensitivity and fast computational speed. WTM also shows localization precision comparable with that of DAOSTORM (an algorithm for high-density super-resolution microscopy), at densities up to 20 molecules μm -2 , and better than DAOSTORM at higher molecular densities. The application of WTM to a high-density biological sample image demonstrated that it resolved protein dynamics from live cell images with subdiffraction resolution and a temporal resolution of several hundred milliseconds or less through a significant reduction in the number of camera images required for a high-density reconstruction. WTM algorithm is a computationally fast, multi-emitter fitting algorithm that can analyse over a wide range of molecular densities. The algorithm is available through the website. https://doi.org/10.17632/bf3z6xpn5j.1. © 2018 The Authors. Journal of Microscopy published by JohnWiley & Sons Ltd on behalf of Royal Microscopical Society.
ERIC Educational Resources Information Center
Halpern, Arthur M.; Glendening, Eric D.
2013-01-01
A project for students in an upper-level course in quantum or computational chemistry is described in which they are introduced to the concepts and applications of a high quality, ab initio treatment of the ground-state potential energy curve (PEC) for H[subscript 2] and D[subscript 2]. Using a commercial computational chemistry application and a…
2013-01-01
fabricated today are based on polymer matrix composites containing Kevlarw KM2 reinforcements , the present work will deal with generic PPTA fibers . In...Multi-length scale enriched continuum-level material model for Kevlarw- fiber reinforced polymer-matrix composites”, Journal of Materials...mechanical transverse behavior of p-phenylene terephthalamide (PPTA) fibers Purpose – A series of all-atom molecular-level computational analyses is
Asynchronous Replica Exchange Software for Grid and Heterogeneous Computing.
Gallicchio, Emilio; Xia, Junchao; Flynn, William F; Zhang, Baofeng; Samlalsingh, Sade; Mentes, Ahmet; Levy, Ronald M
2015-11-01
Parallel replica exchange sampling is an extended ensemble technique often used to accelerate the exploration of the conformational ensemble of atomistic molecular simulations of chemical systems. Inter-process communication and coordination requirements have historically discouraged the deployment of replica exchange on distributed and heterogeneous resources. Here we describe the architecture of a software (named ASyncRE) for performing asynchronous replica exchange molecular simulations on volunteered computing grids and heterogeneous high performance clusters. The asynchronous replica exchange algorithm on which the software is based avoids centralized synchronization steps and the need for direct communication between remote processes. It allows molecular dynamics threads to progress at different rates and enables parameter exchanges among arbitrary sets of replicas independently from other replicas. ASyncRE is written in Python following a modular design conducive to extensions to various replica exchange schemes and molecular dynamics engines. Applications of the software for the modeling of association equilibria of supramolecular and macromolecular complexes on BOINC campus computational grids and on the CPU/MIC heterogeneous hardware of the XSEDE Stampede supercomputer are illustrated. They show the ability of ASyncRE to utilize large grids of desktop computers running the Windows, MacOS, and/or Linux operating systems as well as collections of high performance heterogeneous hardware devices.
Feedback quantum control of molecular electronic population transfer
NASA Astrophysics Data System (ADS)
Bardeen, Christopher J.; Yakovlev, Vladislav V.; Wilson, Kent R.; Carpenter, Scott D.; Weber, Peter M.; Warren, Warren S.
1997-11-01
Feedback quantum control, where the sample `teaches' a computer-controlled arbitrary lightform generator to find the optimal light field, is experimentally demonstrated for a molecular system. Femtosecond pulses tailored by a computer-controlled acousto-optic pulse shaper excite fluorescence from laser dye molecules in solution. Fluorescence and laser power are monitored, and the computer uses the experimental data and a genetic algorithm to optimize population transfer from ground to first excited state. Both efficiency (the ratio of excited state population to laser energy) and effectiveness (total excited state population) are optimized. Potential use as an `automated theory tester' is discussed.
Rotational relaxation of molecular hydrogen at moderate temperatures
NASA Technical Reports Server (NTRS)
Sharma, S. P.
1994-01-01
Using a coupled rotation-vibration-dissociation model the rotational relaxation times for molecular hydrogen as a function of final temperature (500-5000 K), in a hypothetical scenario of sudden compression, are computed. The theoretical model is based on a master equation solver. The bound-bound and bound-free transition rates have been computed using a quasiclassical trajectory method. A review of the available experimental data on the rotational relaxation of hydrogen is presented, with a critical overview of the method of measurements and data reduction, including the sources of errors. These experimental data are then compared with the computed results.
EMERGING MOLECULAR COMPUTATIONAL APPROACHES FOR CROSS-SPECIES EXTRAPOLATIONS: A WORKSHOP SUMMARY
Advances in molecular technology have led to the elucidation of full genomic sequences of several multicellular organisms, ranging from nematodes to man. The related molecular field of proteomics and metabolomics are now beginning to advance rapidly as well. In addition, advances...
Software Applications on the Peregrine System | High-Performance Computing
programming and optimization. Gaussian Chemistry Program for calculating molecular electronic structure and Materials Science Open-source classical molecular dynamics program designed for massively parallel systems framework Q-Chem Chemistry ab initio quantum chemistry package for predictin molecular structures
Ghoufi, Aziz; Dražević, Emil; Szymczyk, Anthony
2017-03-07
In this work we have examined a computational approach in predicting the interactions between uncharged organic solutes and polyamide membranes. We used three model organic molecules with identical molecular weights (100.1 g/mol), 4-aminopiperidine, 3,3-dimethyl-2-butanone (pinacolone) and methylisobutyl ketone for which we obtained experimental data on partitioning, diffusion and separation on a typical seawater reverse osmosis (RO) membrane. The interaction energy between the solutes and the membrane phase (fully aromatic polyamide) was computed from molecular dynamics (MD) simulations and the resulting sequence was found to correlate well with the experimental rejections and sorption data. Sorption of the different organic solutes within the membrane skin layer determined from attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) nicely agreed with interaction energies computed from molecular simulations. Qualitative information about solute diffusivity inside the membrane was also extracted from MD simulations while ATR-FTIR experiments indicated strongly hindered diffusion with diffusion coefficients in the membrane about 10 -15 m 2 /s. The computational approach presented here could be a first step toward predicting rejections trends of, for example, hormones and pharmaceuticals by RO dense membranes.
Use of Computer-Based Case Studies in a Problem-Solving Curriculum.
ERIC Educational Resources Information Center
Haworth, Ian S.; And Others
1997-01-01
Describes the use of three case studies, on computer, to enhance problem solving and critical thinking among doctoral pharmacy students in a physical chemistry course. Students are expected to use specific computer programs, spreadsheets, electronic mail, molecular graphics, word processing, online literature searching, and other computer-based…
Computer Series, 29: Bits and Pieces, 10.
ERIC Educational Resources Information Center
Moore, John W., Ed.
1982-01-01
Describes computer programs (available from authors) including molecular input to computer, programs for quantum chemistry, library orientation to technical literature, plotting potentiometric titration data, simulating oscilloscope curves, organic qualitative analysis with dynamic graphics, extended Huckel calculations, and calculator programs…
COMPUTATIONAL TOXICOLOGY: FRAMEWORK, PARTNERSHIPS, AND PROGRAM DEVELOPMENT
Computational toxicology is a new research initiative being developed within the Office of Research and Development (ORD) of the US Environmental Protection Agency (EPA). Operationally, it is defined as the application of mathematical and computer models together with molecular c...
Exposure Science and the US EPA National Center for Computational Toxicology
The emerging field of computational toxicology applies mathematical and computer models and molecular biological and chemical approaches to explore both qualitative and quantitative relationships between sources of environmental pollutant exposure and adverse health outcomes. The...
Valdés-Martiní, José R; Marrero-Ponce, Yovani; García-Jacas, César R; Martinez-Mayorga, Karina; Barigye, Stephen J; Vaz d'Almeida, Yasser Silveira; Pham-The, Hai; Pérez-Giménez, Facundo; Morell, Carlos A
2017-06-07
In previous reports, Marrero-Ponce et al. proposed algebraic formalisms for characterizing topological (2D) and chiral (2.5D) molecular features through atom- and bond-based ToMoCoMD-CARDD (acronym for Topological Molecular Computational Design-Computer Aided Rational Drug Design) molecular descriptors. These MDs codify molecular information based on the bilinear, quadratic and linear algebraic forms and the graph-theoretical electronic-density and edge-adjacency matrices in order to consider atom- and bond-based relations, respectively. These MDs have been successfully applied in the screening of chemical compounds of different therapeutic applications ranging from antimalarials, antibacterials, tyrosinase inhibitors and so on. To compute these MDs, a computational program with the same name was initially developed. However, this in house software barely offered the functionalities required in contemporary molecular modeling tasks, in addition to the inherent limitations that made its usability impractical. Therefore, the present manuscript introduces the QuBiLS-MAS (acronym for Quadratic, Bilinear and N-Linear mapS based on graph-theoretic electronic-density Matrices and Atomic weightingS) software designed to compute topological (0-2.5D) molecular descriptors based on bilinear, quadratic and linear algebraic forms for atom- and bond-based relations. The QuBiLS-MAS module was designed as standalone software, in which extensions and generalizations of the former ToMoCoMD-CARDD 2D-algebraic indices are implemented, considering the following aspects: (a) two new matrix normalization approaches based on double-stochastic and mutual probability formalisms; (b) topological constraints (cut-offs) to take into account particular inter-atomic relations; (c) six additional atomic properties to be used as weighting schemes in the calculation of the molecular vectors; (d) four new local-fragments to consider molecular regions of interest; (e) number of lone-pair electrons in chemical structure defined by diagonal coefficients in matrix representations; and (f) several aggregation operators (invariants) applied over atom/bond-level descriptors in order to compute global indices. This software permits the parallel computation of the indices, contains a batch processing module and data curation functionalities. This program was developed in Java v1.7 using the Chemistry Development Kit library (version 1.4.19). The QuBiLS-MAS software consists of two components: a desktop interface (GUI) and an API library allowing for the easy integration of the latter in chemoinformatics applications. The relevance of the novel extensions and generalizations implemented in this software is demonstrated through three studies. Firstly, a comparative Shannon's entropy based variability study for the proposed QuBiLS-MAS and the DRAGON indices demonstrates superior performance for the former. A principal component analysis reveals that the QuBiLS-MAS approach captures chemical information orthogonal to that codified by the DRAGON descriptors. Lastly, a QSAR study for the binding affinity to the corticosteroid-binding globulin using Cramer's steroid dataset is carried out. From these analyses, it is revealed that the QuBiLS-MAS approach for atom-pair relations yields similar-to-superior performance with regard to other QSAR methodologies reported in the literature. Therefore, the QuBiLS-MAS approach constitutes a useful tool for the diversity analysis of chemical compound datasets and high-throughput screening of structure-activity data.
The Development and Comparison of Molecular Dynamics Simulation and Monte Carlo Simulation
NASA Astrophysics Data System (ADS)
Chen, Jundong
2018-03-01
Molecular dynamics is an integrated technology that combines physics, mathematics and chemistry. Molecular dynamics method is a computer simulation experimental method, which is a powerful tool for studying condensed matter system. This technique not only can get the trajectory of the atom, but can also observe the microscopic details of the atomic motion. By studying the numerical integration algorithm in molecular dynamics simulation, we can not only analyze the microstructure, the motion of particles and the image of macroscopic relationship between them and the material, but can also study the relationship between the interaction and the macroscopic properties more conveniently. The Monte Carlo Simulation, similar to the molecular dynamics, is a tool for studying the micro-molecular and particle nature. In this paper, the theoretical background of computer numerical simulation is introduced, and the specific methods of numerical integration are summarized, including Verlet method, Leap-frog method and Velocity Verlet method. At the same time, the method and principle of Monte Carlo Simulation are introduced. Finally, similarities and differences of Monte Carlo Simulation and the molecular dynamics simulation are discussed.
Wang, Zhaocai; Ji, Zuwen; Wang, Xiaoming; Wu, Tunhua; Huang, Wei
2017-12-01
As a promising approach to solve the computationally intractable problem, the method based on DNA computing is an emerging research area including mathematics, computer science and molecular biology. The task scheduling problem, as a well-known NP-complete problem, arranges n jobs to m individuals and finds the minimum execution time of last finished individual. In this paper, we use a biologically inspired computational model and describe a new parallel algorithm to solve the task scheduling problem by basic DNA molecular operations. In turn, we skillfully design flexible length DNA strands to represent elements of the allocation matrix, take appropriate biological experiment operations and get solutions of the task scheduling problem in proper length range with less than O(n 2 ) time complexity. Copyright © 2017. Published by Elsevier B.V.
birgHPC: creating instant computing clusters for bioinformatics and molecular dynamics.
Chew, Teong Han; Joyce-Tan, Kwee Hong; Akma, Farizuwana; Shamsir, Mohd Shahir
2011-05-01
birgHPC, a bootable Linux Live CD has been developed to create high-performance clusters for bioinformatics and molecular dynamics studies using any Local Area Network (LAN)-networked computers. birgHPC features automated hardware and slots detection as well as provides a simple job submission interface. The latest versions of GROMACS, NAMD, mpiBLAST and ClustalW-MPI can be run in parallel by simply booting the birgHPC CD or flash drive from the head node, which immediately positions the rest of the PCs on the network as computing nodes. Thus, a temporary, affordable, scalable and high-performance computing environment can be built by non-computing-based researchers using low-cost commodity hardware. The birgHPC Live CD and relevant user guide are available for free at http://birg1.fbb.utm.my/birghpc.
Molecular dynamics simulations and applications in computational toxicology and nanotoxicology.
Selvaraj, Chandrabose; Sakkiah, Sugunadevi; Tong, Weida; Hong, Huixiao
2018-02-01
Nanotoxicology studies toxicity of nanomaterials and has been widely applied in biomedical researches to explore toxicity of various biological systems. Investigating biological systems through in vivo and in vitro methods is expensive and time taking. Therefore, computational toxicology, a multi-discipline field that utilizes computational power and algorithms to examine toxicology of biological systems, has gained attractions to scientists. Molecular dynamics (MD) simulations of biomolecules such as proteins and DNA are popular for understanding of interactions between biological systems and chemicals in computational toxicology. In this paper, we review MD simulation methods, protocol for running MD simulations and their applications in studies of toxicity and nanotechnology. We also briefly summarize some popular software tools for execution of MD simulations. Published by Elsevier Ltd.
Multiscale Computation. Needs and Opportunities for BER Science
DOE Office of Scientific and Technical Information (OSTI.GOV)
Scheibe, Timothy D.; Smith, Jeremy C.
2015-01-01
The Environmental Molecular Sciences Laboratory (EMSL), a scientific user facility managed by Pacific Northwest National Laboratory for the U.S. Department of Energy, Office of Biological and Environmental Research (BER), conducted a one-day workshop on August 26, 2014 on the topic of “Multiscale Computation: Needs and Opportunities for BER Science.” Twenty invited participants, from various computational disciplines within the BER program research areas, were charged with the following objectives; Identify BER-relevant models and their potential cross-scale linkages that could be exploited to better connect molecular-scale research to BER research at larger scales and; Identify critical science directions that will motivate EMSLmore » decisions regarding future computational (hardware and software) architectures.« less
The electrostatic interaction is a critical component of intermolecular interactions in biological processes. Rapid methods for the computation and characterization of the molecular electrostatic potential (MEP) that segment the molecular charge distribution and replace this cont...
NREL Receives Editors' Choice Awards for Supercomputer Research | News |
function," Beckham said. "We followed up these molecular simulations with experimental work to Award. The awards recognize outstanding research in computational molecular science and engineering Mechanisms of Cellulose-Active Enzymes Using Molecular Simulation" at the AIChE 2014 Annual Meeting
Gao, Jinting; Liu, Yaqing; Lin, Xiaodong; Deng, Jiankang; Yin, Jinjin; Wang, Shuo
2017-10-25
Wiring a series of simple logic gates to process complex data is significantly important and a large challenge for untraditional molecular computing systems. The programmable property of DNA endows its powerful application in molecular computing. In our investigation, it was found that DNA exhibits excellent peroxidase-like activity in a colorimetric system of TMB/H 2 O 2 /Hemin (TMB, 3,3', 5,5'-Tetramethylbenzidine) in the presence of K + and Cu 2+ , which is significantly inhibited by the addition of an antioxidant. According to the modulated catalytic activity of this DNA-based catalyst, three cascade logic gates including AND-OR-INH (INHIBIT), AND-INH and OR-INH were successfully constructed. Interestingly, by only modulating the concentration of Cu 2+ , a majority logic gate with a single-vote veto function was realized following the same threshold value as that of the cascade logic gates. The strategy is quite straightforward and versatile and provides an instructive method for constructing multiple logic gates on a simple platform to implement complex molecular computing.
Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes
NASA Astrophysics Data System (ADS)
Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt; Stuehn, Torsten
2017-11-01
Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach, the theoretical modeling and scaling laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. These two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.
NASA Astrophysics Data System (ADS)
Lee, Nien-En; Zhou, Jin-Jian; Agapito, Luis A.; Bernardi, Marco
2018-03-01
Predicting charge transport in organic molecular crystals is notoriously challenging. Carrier mobility calculations in organic semiconductors are dominated by quantum chemistry methods based on charge hopping, which are laborious and only moderately accurate. We compute from first principles the electron-phonon scattering and the phonon-limited hole mobility of naphthalene crystal in the framework of ab initio band theory. Our calculations combine GW electronic bandstructures, ab initio electron-phonon scattering, and the Boltzmann transport equation. The calculated hole mobility is in very good agreement with experiment between 100 -300 K , and we can predict its temperature dependence with high accuracy. We show that scattering between intermolecular phonons and holes regulates the mobility, though intramolecular phonons possess the strongest coupling with holes. We revisit the common belief that only rigid molecular motions affect carrier dynamics in organic molecular crystals. Our paper provides a quantitative and rigorous framework to compute charge transport in organic crystals and is a first step toward reconciling band theory and carrier hopping computational methods.
Computer-Aided Molecular Design of Bis-phosphine Oxide Lanthanide Extractants
McCann, Billy W.; Silva, Nuwan De; Windus, Theresa L.; ...
2016-02-17
Computer-aided molecular design and high-throughput screening of viable host architectures can significantly reduce the efforts in the design of novel ligands for efficient extraction of rare earth elements. This paper presents a computational approach to the deliberate design of bis-phosphine oxide host architectures that are structurally organized for complexation of trivalent lanthanides. Molecule building software, HostDesigner, was interfaced with molecular mechanics software, PCModel, providing a tool for generating and screening millions of potential R 2(O)P-link-P(O)R 2 ligand geometries. The molecular mechanics ranking of ligand structures is consistent with both the solution-phase free energies of complexation obtained with density functional theorymore » and the performance of known bis-phosphine oxide extractants. For the case where link is -CH 2-, evaluation of the ligand geometry provides the first characterization of a steric origin for the ‘anomalous aryl strengthening’ effect. The design approach has identified a number of novel bis-phosphine oxide ligands that are better organized for lanthanide complexation than previously studied examples.« less
Physics Computing '92: Proceedings of the 4th International Conference
NASA Astrophysics Data System (ADS)
de Groot, Robert A.; Nadrchal, Jaroslav
1993-04-01
The Table of Contents for the book is as follows: * Preface * INVITED PAPERS * Ab Initio Theoretical Approaches to the Structural, Electronic and Vibrational Properties of Small Clusters and Fullerenes: The State of the Art * Neural Multigrid Methods for Gauge Theories and Other Disordered Systems * Multicanonical Monte Carlo Simulations * On the Use of the Symbolic Language Maple in Physics and Chemistry: Several Examples * Nonequilibrium Phase Transitions in Catalysis and Population Models * Computer Algebra, Symmetry Analysis and Integrability of Nonlinear Evolution Equations * The Path-Integral Quantum Simulation of Hydrogen in Metals * Digital Optical Computing: A New Approach of Systolic Arrays Based on Coherence Modulation of Light and Integrated Optics Technology * Molecular Dynamics Simulations of Granular Materials * Numerical Implementation of a K.A.M. Algorithm * Quasi-Monte Carlo, Quasi-Random Numbers and Quasi-Error Estimates * What Can We Learn from QMC Simulations * Physics of Fluctuating Membranes * Plato, Apollonius, and Klein: Playing with Spheres * Steady States in Nonequilibrium Lattice Systems * CONVODE: A REDUCE Package for Differential Equations * Chaos in Coupled Rotators * Symplectic Numerical Methods for Hamiltonian Problems * Computer Simulations of Surfactant Self Assembly * High-dimensional and Very Large Cellular Automata for Immunological Shape Space * A Review of the Lattice Boltzmann Method * Electronic Structure of Solids in the Self-interaction Corrected Local-spin-density Approximation * Dedicated Computers for Lattice Gauge Theory Simulations * Physics Education: A Survey of Problems and Possible Solutions * Parallel Computing and Electronic-Structure Theory * High Precision Simulation Techniques for Lattice Field Theory * CONTRIBUTED PAPERS * Case Study of Microscale Hydrodynamics Using Molecular Dynamics and Lattice Gas Methods * Computer Modelling of the Structural and Electronic Properties of the Supported Metal Catalysis * Ordered Particle Simulations for Serial and MIMD Parallel Computers * "NOLP" -- Program Package for Laser Plasma Nonlinear Optics * Algorithms to Solve Nonlinear Least Square Problems * Distribution of Hydrogen Atoms in Pd-H Computed by Molecular Dynamics * A Ray Tracing of Optical System for Protein Crystallography Beamline at Storage Ring-SIBERIA-2 * Vibrational Properties of a Pseudobinary Linear Chain with Correlated Substitutional Disorder * Application of the Software Package Mathematica in Generalized Master Equation Method * Linelist: An Interactive Program for Analysing Beam-foil Spectra * GROMACS: A Parallel Computer for Molecular Dynamics Simulations * GROMACS Method of Virial Calculation Using a Single Sum * The Interactive Program for the Solution of the Laplace Equation with the Elimination of Singularities for Boundary Functions * Random-Number Generators: Testing Procedures and Comparison of RNG Algorithms * Micro-TOPIC: A Tokamak Plasma Impurities Code * Rotational Molecular Scattering Calculations * Orthonormal Polynomial Method for Calibrating of Cryogenic Temperature Sensors * Frame-based System Representing Basis of Physics * The Role of Massively Data-parallel Computers in Large Scale Molecular Dynamics Simulations * Short-range Molecular Dynamics on a Network of Processors and Workstations * An Algorithm for Higher-order Perturbation Theory in Radiative Transfer Computations * Hydrostochastics: The Master Equation Formulation of Fluid Dynamics * HPP Lattice Gas on Transputers and Networked Workstations * Study on the Hysteresis Cycle Simulation Using Modeling with Different Functions on Intervals * Refined Pruning Techniques for Feed-forward Neural Networks * Random Walk Simulation of the Motion of Transient Charges in Photoconductors * The Optical Hysteresis in Hydrogenated Amorphous Silicon * Diffusion Monte Carlo Analysis of Modern Interatomic Potentials for He * A Parallel Strategy for Molecular Dynamics Simulations of Polar Liquids on Transputer Arrays * Distribution of Ions Reflected on Rough Surfaces * The Study of Step Density Distribution During Molecular Beam Epitaxy Growth: Monte Carlo Computer Simulation * Towards a Formal Approach to the Construction of Large-scale Scientific Applications Software * Correlated Random Walk and Discrete Modelling of Propagation through Inhomogeneous Media * Teaching Plasma Physics Simulation * A Theoretical Determination of the Au-Ni Phase Diagram * Boson and Fermion Kinetics in One-dimensional Lattices * Computational Physics Course on the Technical University * Symbolic Computations in Simulation Code Development and Femtosecond-pulse Laser-plasma Interaction Studies * Computer Algebra and Integrated Computing Systems in Education of Physical Sciences * Coordinated System of Programs for Undergraduate Physics Instruction * Program Package MIRIAM and Atomic Physics of Extreme Systems * High Energy Physics Simulation on the T_Node * The Chapman-Kolmogorov Equation as Representation of Huygens' Principle and the Monolithic Self-consistent Numerical Modelling of Lasers * Authoring System for Simulation Developments * Molecular Dynamics Study of Ion Charge Effects in the Structure of Ionic Crystals * A Computational Physics Introductory Course * Computer Calculation of Substrate Temperature Field in MBE System * Multimagnetical Simulation of the Ising Model in Two and Three Dimensions * Failure of the CTRW Treatment of the Quasicoherent Excitation Transfer * Implementation of a Parallel Conjugate Gradient Method for Simulation of Elastic Light Scattering * Algorithms for Study of Thin Film Growth * Algorithms and Programs for Physics Teaching in Romanian Technical Universities * Multicanonical Simulation of 1st order Transitions: Interface Tension of the 2D 7-State Potts Model * Two Numerical Methods for the Calculation of Periodic Orbits in Hamiltonian Systems * Chaotic Behavior in a Probabilistic Cellular Automata? * Wave Optics Computing by a Networked-based Vector Wave Automaton * Tensor Manipulation Package in REDUCE * Propagation of Electromagnetic Pulses in Stratified Media * The Simple Molecular Dynamics Model for the Study of Thermalization of the Hot Nucleon Gas * Electron Spin Polarization in PdCo Alloys Calculated by KKR-CPA-LSD Method * Simulation Studies of Microscopic Droplet Spreading * A Vectorizable Algorithm for the Multicolor Successive Overrelaxation Method * Tetragonality of the CuAu I Lattice and Its Relation to Electronic Specific Heat and Spin Susceptibility * Computer Simulation of the Formation of Metallic Aggregates Produced by Chemical Reactions in Aqueous Solution * Scaling in Growth Models with Diffusion: A Monte Carlo Study * The Nucleus as the Mesoscopic System * Neural Network Computation as Dynamic System Simulation * First-principles Theory of Surface Segregation in Binary Alloys * Data Smooth Approximation Algorithm for Estimating the Temperature Dependence of the Ice Nucleation Rate * Genetic Algorithms in Optical Design * Application of 2D-FFT in the Study of Molecular Exchange Processes by NMR * Advanced Mobility Model for Electron Transport in P-Si Inversion Layers * Computer Simulation for Film Surfaces and its Fractal Dimension * Parallel Computation Techniques and the Structure of Catalyst Surfaces * Educational SW to Teach Digital Electronics and the Corresponding Text Book * Primitive Trinomials (Mod 2) Whose Degree is a Mersenne Exponent * Stochastic Modelisation and Parallel Computing * Remarks on the Hybrid Monte Carlo Algorithm for the ∫4 Model * An Experimental Computer Assisted Workbench for Physics Teaching * A Fully Implicit Code to Model Tokamak Plasma Edge Transport * EXPFIT: An Interactive Program for Automatic Beam-foil Decay Curve Analysis * Mapping Technique for Solving General, 1-D Hamiltonian Systems * Freeway Traffic, Cellular Automata, and Some (Self-Organizing) Criticality * Photonuclear Yield Analysis by Dynamic Programming * Incremental Representation of the Simply Connected Planar Curves * Self-convergence in Monte Carlo Methods * Adaptive Mesh Technique for Shock Wave Propagation * Simulation of Supersonic Coronal Streams and Their Interaction with the Solar Wind * The Nature of Chaos in Two Systems of Ordinary Nonlinear Differential Equations * Considerations of a Window-shopper * Interpretation of Data Obtained by RTP 4-Channel Pulsed Radar Reflectometer Using a Multi Layer Perceptron * Statistics of Lattice Bosons for Finite Systems * Fractal Based Image Compression with Affine Transformations * Algorithmic Studies on Simulation Codes for Heavy-ion Reactions * An Energy-Wise Computer Simulation of DNA-Ion-Water Interactions Explains the Abnormal Structure of Poly[d(A)]:Poly[d(T)] * Computer Simulation Study of Kosterlitz-Thouless-Like Transitions * Problem-oriented Software Package GUN-EBT for Computer Simulation of Beam Formation and Transport in Technological Electron-Optical Systems * Parallelization of a Boundary Value Solver and its Application in Nonlinear Dynamics * The Symbolic Classification of Real Four-dimensional Lie Algebras * Short, Singular Pulses Generation by a Dye Laser at Two Wavelengths Simultaneously * Quantum Monte Carlo Simulations of the Apex-Oxygen-Model * Approximation Procedures for the Axial Symmetric Static Einstein-Maxwell-Higgs Theory * Crystallization on a Sphere: Parallel Simulation on a Transputer Network * FAMULUS: A Software Product (also) for Physics Education * MathCAD vs. FAMULUS -- A Brief Comparison * First-principles Dynamics Used to Study Dissociative Chemisorption * A Computer Controlled System for Crystal Growth from Melt * A Time Resolved Spectroscopic Method for Short Pulsed Particle Emission * Green's Function Computation in Radiative Transfer Theory * Random Search Optimization Technique for One-criteria and Multi-criteria Problems * Hartley Transform Applications to Thermal Drift Elimination in Scanning Tunneling Microscopy * Algorithms of Measuring, Processing and Interpretation of Experimental Data Obtained with Scanning Tunneling Microscope * Time-dependent Atom-surface Interactions * Local and Global Minima on Molecular Potential Energy Surfaces: An Example of N3 Radical * Computation of Bifurcation Surfaces * Symbolic Computations in Quantum Mechanics: Energies in Next-to-solvable Systems * A Tool for RTP Reactor and Lamp Field Design * Modelling of Particle Spectra for the Analysis of Solid State Surface * List of Participants
Komeiji, Y; Yokoyama, H; Uebayasi, M; Taiji, M; Fukushige, T; Sugimoto, D; Takata, R; Shimizu, A; Itsukashi, K
1996-01-01
GRAPE (GRavity PipE) processors are special purpose computers for simulation of classical particles. The performance of MD-GRAPE, one of the GRAPEs developed for molecular dynamics, was investigated. The effective speed of MD-GRAPE was equivalent to approximately 6 Gflops. The precision of MD-GRAPE was good judging from the acceptable fluctuation of the total energy. Then a software named PEACH (Program for Energetic Analysis of bioCHemical molecules) was developed for molecular dynamics of biomolecules in combination with MD-GRAPE. Molecular dynamics simulation was performed for several protein-solvent systems with different sizes. Simulation of the largest system investigated (27,000 atoms) took only 5 sec/step. Thus, the PEACH-GRAPE system is expected to be useful in accurate and reliable simulation of large biomolecules.
NASA Astrophysics Data System (ADS)
Bussert, J.
1982-06-01
The possibility of microchip synthesis from molecular configurations is considered. A bistable memory element concept is described which can be independently written on and read, and which consists of a chain of transition metal atoms, a bulging ligand connecting the transition metal atoms, and two types of ligand attached to the transition metal atoms. The molecular emulation of switches, memory and interfaces is presently being investigated independently, although simultaneous synthesis of entire architectures is the ultimate goal of research. Molecular circuitry, which could incorporate 10,000 more gates into an IC chip than chemical techniques, would be of greatest immediate importance in avionics and other portable military electronics devices for which minimum size and weight are valuable. Attention is given to a computer-controlled method for the synthesis of molecular computers.
Synthetic Ion Channels and DNA Logic Gates as Components of Molecular Robots.
Kawano, Ryuji
2018-02-19
A molecular robot is a next-generation biochemical machine that imitates the actions of microorganisms. It is made of biomaterials such as DNA, proteins, and lipids. Three prerequisites have been proposed for the construction of such a robot: sensors, intelligence, and actuators. This Minireview focuses on recent research on synthetic ion channels and DNA computing technologies, which are viewed as potential candidate components of molecular robots. Synthetic ion channels, which are embedded in artificial cell membranes (lipid bilayers), sense ambient ions or chemicals and import them. These artificial sensors are useful components for molecular robots with bodies consisting of a lipid bilayer because they enable the interface between the inside and outside of the molecular robot to function as gates. After the signal molecules arrive inside the molecular robot, they can operate DNA logic gates, which perform computations. These functions will be integrated into the intelligence and sensor sections of molecular robots. Soon, these molecular machines will be able to be assembled to operate as a mass microrobot and play an active role in environmental monitoring and in vivo diagnosis or therapy. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Sanibel Symposium in the Petascale-Exascale Computational Era
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cheng, Hai-Ping
The 56 th Sanibel Symposium was held February 14-19 2016 at the King and Prince Hotel, St. Simons Island, GA. It successfully brought quantum chemists and chemical and condensed matter physicists together in presentations, posters, and informal discussions bridging those two communities. The Symposium has had a significant role in preparing generations of quantum theorists. As computational potency and algorithmic sophistication have grown, the Symposium has evolved to emphasize more heavily computationally oriented method development in chemistry and materials physics, including nanoscience, complex molecular phenomena, and even bio-molecular methods and problems. Given this context, the 56 th Sanibel meeting systematicallymore » and deliberately had sessions focused on exascale computation. A selection of outstanding theoretical problems that need serious attention was included. Five invited sessions, two contributed sessions (hot topics), and a poster session were organized with the exascale theme. This was a historic milestone in the evolution of the Symposia. Just as years ago linear algebra, perturbation theory, density matrices, and band-structure methods dominated early Sanibel Symposia, the exascale sessions of the 56 thmeeting contributed a transformative influence to add structure and strength to the computational physical science community in an unprecedented way. A copy of the full program of the 56 th Symposium is attached. The exascale sessions were Linear Scaling, Non-Adabatic Dynamics, Interpretive Theory and Models, Computation, Software, and Algorithms, and Quantum Monte Carlo. The Symposium Proceedings will be published in Molecular Physics (2017). Note that the Sanibel proceedings from 2015 and 2014 were published as Molecular Physics vol. 114, issue 3-4 (2016) and vol. 113, issue 3-4 (2015) respectively.« less
Interaction sorting method for molecular dynamics on multi-core SIMD CPU architecture.
Matvienko, Sergey; Alemasov, Nikolay; Fomin, Eduard
2015-02-01
Molecular dynamics (MD) is widely used in computational biology for studying binding mechanisms of molecules, molecular transport, conformational transitions, protein folding, etc. The method is computationally expensive; thus, the demand for the development of novel, much more efficient algorithms is still high. Therefore, the new algorithm designed in 2007 and called interaction sorting (IS) clearly attracted interest, as it outperformed the most efficient MD algorithms. In this work, a new IS modification is proposed which allows the algorithm to utilize SIMD processor instructions. This paper shows that the improvement provides an additional gain in performance, 9% to 45% in comparison to the original IS method.
Quantum Mechanical Study of Atoms and Molecules
NASA Technical Reports Server (NTRS)
Sahni, R. C.
1961-01-01
This paper, following a brief introduction, is divided into five parts. Part I outlines the theory of the molecular orbital method for the ground, ionized and excited states of molecules. Part II gives a brief summary of the interaction integrals and their tabulation. Part III outlines an automatic program designed for the computation of various states of molecules. Part IV gives examples of the study of ground, ionized and excited states of CO, BH and N2 where the program of automatic computation and molecular integrals have been utilized. Part V enlists some special problems of Molecular Quantum Mechanics are being tackled at New York University.
2011-10-14
landscapes. It is motivated by statistical learning arguments and unifies the tasks of biasing the molecular dynamics to escape free energy wells and...statistical learning arguments and unifies the tasks of biasing the molecular dynamics to escape free energy wells and estimating the free energy...experimentally, to characterize global changes as well as investigate relative stabilities. In most applications, a brute- force computation based on
Self-consistent continuum solvation for optical absorption of complex molecular systems in solution
DOE Office of Scientific and Technical Information (OSTI.GOV)
Timrov, Iurii; Biancardi, Alessandro; Andreussi, Oliviero
2015-01-21
We introduce a new method to compute the optical absorption spectra of complex molecular systems in solution, based on the Liouville approach to time-dependent density-functional perturbation theory and the revised self-consistent continuum solvation model. The former allows one to obtain the absorption spectrum over a whole wide frequency range, using a recently proposed Lanczos-based technique, or selected excitation energies, using the Casida equation, without having to ever compute any unoccupied molecular orbitals. The latter is conceptually similar to the polarizable continuum model and offers the further advantages of allowing an easy computation of atomic forces via the Hellmann-Feynman theorem andmore » a ready implementation in periodic-boundary conditions. The new method has been implemented using pseudopotentials and plane-wave basis sets, benchmarked against polarizable continuum model calculations on 4-aminophthalimide, alizarin, and cyanin and made available through the QUANTUM ESPRESSO distribution of open-source codes.« less
Hudson, Phillip S; Woodcock, H Lee; Boresch, Stefan
2015-12-03
Carrying out free energy simulations (FES) using quantum mechanical (QM) Hamiltonians remains an attractive, albeit elusive goal. Renewed efforts in this area have focused on using "indirect" thermodynamic cycles to connect "low level" simulation results to "high level" free energies. The main obstacle to computing converged free energy results between molecular mechanical (MM) and QM (ΔA(MM→QM)), as recently demonstrated by us and others, is differences in the so-called "stiff" degrees of freedom (e.g., bond stretching) between the respective energy surfaces. Herein, we demonstrate that this problem can be efficiently circumvented using nonequilibrium work (NEW) techniques, i.e., Jarzynski's and Crooks' equations. Initial applications of computing ΔA(NEW)(MM→QM), for blocked amino acids alanine and serine as well as to generate butane's potentials of mean force via the indirect QM/MM FES method, showed marked improvement over traditional FES approaches.
Simulated quantum computation of molecular energies.
Aspuru-Guzik, Alán; Dutoi, Anthony D; Love, Peter J; Head-Gordon, Martin
2005-09-09
The calculation time for the energy of atoms and molecules scales exponentially with system size on a classical computer but polynomially using quantum algorithms. We demonstrate that such algorithms can be applied to problems of chemical interest using modest numbers of quantum bits. Calculations of the water and lithium hydride molecular ground-state energies have been carried out on a quantum computer simulator using a recursive phase-estimation algorithm. The recursive algorithm reduces the number of quantum bits required for the readout register from about 20 to 4. Mappings of the molecular wave function to the quantum bits are described. An adiabatic method for the preparation of a good approximate ground-state wave function is described and demonstrated for a stretched hydrogen molecule. The number of quantum bits required scales linearly with the number of basis functions, and the number of gates required grows polynomially with the number of quantum bits.
From Computational Photobiology to the Design of Vibrationally Coherent Molecular Devices and Motors
NASA Astrophysics Data System (ADS)
Olivucci, Massimo
2014-03-01
In the past multi-configurational quantum chemical computations coupled with molecular mechanics force fields have been employed to investigate spectroscopic, thermal and photochemical properties of visual pigments. Here we show how the same computational technology can nowadays be used to design, characterize and ultimately, prepare light-driven molecular switches which mimics the photophysics of the visual pigment bovine rhodopsin (Rh). When embedded in the protein cavity the chromophore of Rh undergoes an ultrafast and coherent photoisomerization. In order to design a synthetic chromophore displaying similar properties in common solvents, we recently focused on indanylidene-pyrroline (NAIP) systems. We found that these systems display light-induced ground state coherent vibrational motion similar to the one detected in Rh. Semi-classical trajectories provide a mechanistic description of the structural changes associated to the observed coherent motion which is shown to be ultimately due to periodic changes in the π-conjugation.
A Review of Enhanced Sampling Approaches for Accelerated Molecular Dynamics
NASA Astrophysics Data System (ADS)
Tiwary, Pratyush; van de Walle, Axel
Molecular dynamics (MD) simulations have become a tool of immense use and popularity for simulating a variety of systems. With the advent of massively parallel computer resources, one now routinely sees applications of MD to systems as large as hundreds of thousands to even several million atoms, which is almost the size of most nanomaterials. However, it is not yet possible to reach laboratory timescales of milliseconds and beyond with MD simulations. Due to the essentially sequential nature of time, parallel computers have been of limited use in solving this so-called timescale problem. Instead, over the years a large range of statistical mechanics based enhanced sampling approaches have been proposed for accelerating molecular dynamics, and accessing timescales that are well beyond the reach of the fastest computers. In this review we provide an overview of these approaches, including the underlying theory, typical applications, and publicly available software resources to implement them.
Molecular Mechanics: The Method and Its Underlying Philosophy.
ERIC Educational Resources Information Center
Boyd, Donald B.; Lipkowitz, Kenny B.
1982-01-01
Molecular mechanics is a nonquantum mechanical method for solving problems concerning molecular geometries and energy. Methodology based on: the principle of combining potential energy functions of all structural features of a particular molecule into a total force field; derivation of basic equations; and use of available computer programs is…
Nagaraja, Sridevi; Reifman, Jaques; Mitrophanov, Alexander Y.
2015-01-01
Timely resolution of inflammation is critical for the restoration of homeostasis in injured or infected tissue. Chronic inflammation is often characterized by a persistent increase in the concentrations of inflammatory cells and molecular mediators, whose distinct amount and timing characteristics offer an opportunity to identify effective therapeutic regulatory targets. Here, we used our recently developed computational model of local inflammation to identify potential targets for molecular interventions and to investigate the effects of individual and combined inhibition of such targets. This was accomplished via the development and application of computational strategies involving the simulation and analysis of thousands of inflammatory scenarios. We found that modulation of macrophage influx and efflux is an effective potential strategy to regulate the amount of inflammatory cells and molecular mediators in both normal and chronic inflammatory scenarios. We identified three molecular mediators − tumor necrosis factor-α (TNF-α), transforming growth factor-β (TGF-β), and the chemokine CXCL8 − as potential molecular targets whose individual or combined inhibition may robustly regulate both the amount and timing properties of the kinetic trajectories for neutrophils and macrophages in chronic inflammation. Modulation of macrophage flux, as well as of the abundance of TNF-α, TGF-β, and CXCL8, may improve the resolution of chronic inflammation. PMID:26633296
Carbó-Dorca, Ramon; Gallegos, Ana; Sánchez, Angel J
2009-05-01
Classical quantitative structure-properties relationship (QSPR) statistical techniques unavoidably present an inherent paradoxical computational context. They rely on the definition of a Gram matrix in descriptor spaces, which is used afterwards to reduce the original dimension via several possible kinds of algebraic manipulations. From there, effective models for the computation of unknown properties of known molecular structures are obtained. However, the reduced descriptor dimension causes linear dependence within the set of discrete vector molecular representations, leading to positive semi-definite Gram matrices in molecular spaces. To resolve this QSPR dimensionality paradox (QSPR DP) here is proposed to adopt as starting point the quantum QSPR (QQSPR) computational framework perspective, where density functions act as infinite dimensional descriptors. The fundamental QQSPR equation, deduced from employing quantum expectation value numerical evaluation, can be approximately solved in order to obtain models exempt of the QSPR DP. The substitution of the quantum similarity matrix by an empirical Gram matrix in molecular spaces, build up with the original non manipulated discrete molecular descriptor vectors, permits to obtain classical QSPR models with the same characteristics as in QQSPR, that is: possessing a certain degree of causality and explicitly independent of the descriptor dimension. 2008 Wiley Periodicals, Inc.
Durant, Fallon; Lobo, Daniel; Hammelman, Jennifer
2016-01-01
Abstract Planaria are complex metazoans that repair damage to their bodies and cease remodeling when a correct anatomy has been achieved. This model system offers a unique opportunity to understand how large‐scale anatomical homeostasis emerges from the activities of individual cells. Much progress has been made on the molecular genetics of stem cell activity in planaria. However, recent data also indicate that the global pattern is regulated by physiological circuits composed of ionic and neurotransmitter signaling. Here, we overview the multi‐scale problem of understanding pattern regulation in planaria, with specific focus on bioelectric signaling via ion channels and gap junctions (electrical synapses), and computational efforts to extract explanatory models from functional and molecular data on regeneration. We present a perspective that interprets results in this fascinating field using concepts from dynamical systems theory and computational neuroscience. Serving as a tractable nexus between genetic, physiological, and computational approaches to pattern regulation, planarian pattern homeostasis harbors many deep insights for regenerative medicine, evolutionary biology, and engineering. PMID:27499881
Zhang, P; Tao, L; Zeng, X; Qin, C; Chen, S Y; Zhu, F; Yang, S Y; Li, Z R; Chen, W P; Chen, Y Z
2017-02-03
The studies of biological, disease, and pharmacological networks are facilitated by the systems-level investigations using computational tools. In particular, the network descriptors developed in other disciplines have found increasing applications in the study of the protein, gene regulatory, metabolic, disease, and drug-targeted networks. Facilities are provided by the public web servers for computing network descriptors, but many descriptors are not covered, including those used or useful for biological studies. We upgraded the PROFEAT web server http://bidd2.nus.edu.sg/cgi-bin/profeat2016/main.cgi for computing up to 329 network descriptors and protein-protein interaction descriptors. PROFEAT network descriptors comprehensively describe the topological and connectivity characteristics of unweighted (uniform binding constants and molecular levels), edge-weighted (varying binding constants), node-weighted (varying molecular levels), edge-node-weighted (varying binding constants and molecular levels), and directed (oriented processes) networks. The usefulness of the network descriptors is illustrated by the literature-reported studies of the biological networks derived from the genome, interactome, transcriptome, metabolome, and diseasome profiles. Copyright © 2016 Elsevier Ltd. All rights reserved.
Glowacki, David R; O'Connor, Michael; Calabró, Gaetano; Price, James; Tew, Philip; Mitchell, Thomas; Hyde, Joseph; Tew, David P; Coughtrie, David J; McIntosh-Smith, Simon
2014-01-01
With advances in computational power, the rapidly growing role of computational/simulation methodologies in the physical sciences, and the development of new human-computer interaction technologies, the field of interactive molecular dynamics seems destined to expand. In this paper, we describe and benchmark the software algorithms and hardware setup for carrying out interactive molecular dynamics utilizing an array of consumer depth sensors. The system works by interpreting the human form as an energy landscape, and superimposing this landscape on a molecular dynamics simulation to chaperone the motion of the simulated atoms, affecting both graphics and sonified simulation data. GPU acceleration has been key to achieving our target of 60 frames per second (FPS), giving an extremely fluid interactive experience. GPU acceleration has also allowed us to scale the system for use in immersive 360° spaces with an array of up to ten depth sensors, allowing several users to simultaneously chaperone the dynamics. The flexibility of our platform for carrying out molecular dynamics simulations has been considerably enhanced by wrappers that facilitate fast communication with a portable selection of GPU-accelerated molecular force evaluation routines. In this paper, we describe a 360° atmospheric molecular dynamics simulation we have run in a chemistry/physics education context. We also describe initial tests in which users have been able to chaperone the dynamics of 10-alanine peptide embedded in an explicit water solvent. Using this system, both expert and novice users have been able to accelerate peptide rare event dynamics by 3-4 orders of magnitude.
Ab initio molecular simulations with numeric atom-centered orbitals
NASA Astrophysics Data System (ADS)
Blum, Volker; Gehrke, Ralf; Hanke, Felix; Havu, Paula; Havu, Ville; Ren, Xinguo; Reuter, Karsten; Scheffler, Matthias
2009-11-01
We describe a complete set of algorithms for ab initio molecular simulations based on numerically tabulated atom-centered orbitals (NAOs) to capture a wide range of molecular and materials properties from quantum-mechanical first principles. The full algorithmic framework described here is embodied in the Fritz Haber Institute "ab initio molecular simulations" (FHI-aims) computer program package. Its comprehensive description should be relevant to any other first-principles implementation based on NAOs. The focus here is on density-functional theory (DFT) in the local and semilocal (generalized gradient) approximations, but an extension to hybrid functionals, Hartree-Fock theory, and MP2/GW electron self-energies for total energies and excited states is possible within the same underlying algorithms. An all-electron/full-potential treatment that is both computationally efficient and accurate is achieved for periodic and cluster geometries on equal footing, including relaxation and ab initio molecular dynamics. We demonstrate the construction of transferable, hierarchical basis sets, allowing the calculation to range from qualitative tight-binding like accuracy to meV-level total energy convergence with the basis set. Since all basis functions are strictly localized, the otherwise computationally dominant grid-based operations scale as O(N) with system size N. Together with a scalar-relativistic treatment, the basis sets provide access to all elements from light to heavy. Both low-communication parallelization of all real-space grid based algorithms and a ScaLapack-based, customized handling of the linear algebra for all matrix operations are possible, guaranteeing efficient scaling (CPU time and memory) up to massively parallel computer systems with thousands of CPUs.
Bio-inspired algorithms applied to molecular docking simulations.
Heberlé, G; de Azevedo, W F
2011-01-01
Nature as a source of inspiration has been shown to have a great beneficial impact on the development of new computational methodologies. In this scenario, analyses of the interactions between a protein target and a ligand can be simulated by biologically inspired algorithms (BIAs). These algorithms mimic biological systems to create new paradigms for computation, such as neural networks, evolutionary computing, and swarm intelligence. This review provides a description of the main concepts behind BIAs applied to molecular docking simulations. Special attention is devoted to evolutionary algorithms, guided-directed evolutionary algorithms, and Lamarckian genetic algorithms. Recent applications of these methodologies to protein targets identified in the Mycobacterium tuberculosis genome are described.
Dudding, Travis; Houk, Kendall N
2004-04-20
The catalytic asymmetric thiazolium- and triazolium-catalyzed benzoin condensations of aldehydes and ketones were studied with computational methods. Transition-state geometries were optimized by using Morokuma's IMOMO [integrated MO (molecular orbital) + MO method] variation of ONIOM (n-layered integrated molecular orbital method) with a combination of B3LYP/6-31G(d) and AM1 levels of theory, and final transition-state energies were computed with single-point B3LYP/6-31G(d) calculations. Correlations between experiment and theory were found, and the origins of stereoselection were identified. Thiazolium catalysts were predicted to be less selective then triazolium catalysts, a trend also found experimentally.
de Jong, Wibe A; Walker, Andrew M; Hanwell, Marcus D
2013-05-24
Multidisciplinary integrated research requires the ability to couple the diverse sets of data obtained from a range of complex experiments and computer simulations. Integrating data requires semantically rich information. In this paper an end-to-end use of semantically rich data in computational chemistry is demonstrated utilizing the Chemical Markup Language (CML) framework. Semantically rich data is generated by the NWChem computational chemistry software with the FoX library and utilized by the Avogadro molecular editor for analysis and visualization. The NWChem computational chemistry software has been modified and coupled to the FoX library to write CML compliant XML data files. The FoX library was expanded to represent the lexical input files and molecular orbitals used by the computational chemistry software. Draft dictionary entries and a format for molecular orbitals within CML CompChem were developed. The Avogadro application was extended to read in CML data, and display molecular geometry and electronic structure in the GUI allowing for an end-to-end solution where Avogadro can create input structures, generate input files, NWChem can run the calculation and Avogadro can then read in and analyse the CML output produced. The developments outlined in this paper will be made available in future releases of NWChem, FoX, and Avogadro. The production of CML compliant XML files for computational chemistry software such as NWChem can be accomplished relatively easily using the FoX library. The CML data can be read in by a newly developed reader in Avogadro and analysed or visualized in various ways. A community-based effort is needed to further develop the CML CompChem convention and dictionary. This will enable the long-term goal of allowing a researcher to run simple "Google-style" searches of chemistry and physics and have the results of computational calculations returned in a comprehensible form alongside articles from the published literature.
2013-01-01
Background Multidisciplinary integrated research requires the ability to couple the diverse sets of data obtained from a range of complex experiments and computer simulations. Integrating data requires semantically rich information. In this paper an end-to-end use of semantically rich data in computational chemistry is demonstrated utilizing the Chemical Markup Language (CML) framework. Semantically rich data is generated by the NWChem computational chemistry software with the FoX library and utilized by the Avogadro molecular editor for analysis and visualization. Results The NWChem computational chemistry software has been modified and coupled to the FoX library to write CML compliant XML data files. The FoX library was expanded to represent the lexical input files and molecular orbitals used by the computational chemistry software. Draft dictionary entries and a format for molecular orbitals within CML CompChem were developed. The Avogadro application was extended to read in CML data, and display molecular geometry and electronic structure in the GUI allowing for an end-to-end solution where Avogadro can create input structures, generate input files, NWChem can run the calculation and Avogadro can then read in and analyse the CML output produced. The developments outlined in this paper will be made available in future releases of NWChem, FoX, and Avogadro. Conclusions The production of CML compliant XML files for computational chemistry software such as NWChem can be accomplished relatively easily using the FoX library. The CML data can be read in by a newly developed reader in Avogadro and analysed or visualized in various ways. A community-based effort is needed to further develop the CML CompChem convention and dictionary. This will enable the long-term goal of allowing a researcher to run simple “Google-style” searches of chemistry and physics and have the results of computational calculations returned in a comprehensible form alongside articles from the published literature. PMID:23705910
DMG-α--a computational geometry library for multimolecular systems.
Szczelina, Robert; Murzyn, Krzysztof
2014-11-24
The DMG-α library grants researchers in the field of computational biology, chemistry, and biophysics access to an open-sourced, easy to use, and intuitive software for performing fine-grained geometric analysis of molecular systems. The library is capable of computing power diagrams (weighted Voronoi diagrams) in three dimensions with 3D periodic boundary conditions, computing approximate projective 2D Voronoi diagrams on arbitrarily defined surfaces, performing shape properties recognition using α-shape theory and can do exact Solvent Accessible Surface Area (SASA) computation. The software is written mainly as a template-based C++ library for greater performance, but a rich Python interface (pydmga) is provided as a convenient way to manipulate the DMG-α routines. To illustrate possible applications of the DMG-α library, we present results of sample analyses which allowed to determine nontrivial geometric properties of two Escherichia coli-specific lipids as emerging from molecular dynamics simulations of relevant model bilayers.
From transistor to trapped-ion computers for quantum chemistry.
Yung, M-H; Casanova, J; Mezzacapo, A; McClean, J; Lamata, L; Aspuru-Guzik, A; Solano, E
2014-01-07
Over the last few decades, quantum chemistry has progressed through the development of computational methods based on modern digital computers. However, these methods can hardly fulfill the exponentially-growing resource requirements when applied to large quantum systems. As pointed out by Feynman, this restriction is intrinsic to all computational models based on classical physics. Recently, the rapid advancement of trapped-ion technologies has opened new possibilities for quantum control and quantum simulations. Here, we present an efficient toolkit that exploits both the internal and motional degrees of freedom of trapped ions for solving problems in quantum chemistry, including molecular electronic structure, molecular dynamics, and vibronic coupling. We focus on applications that go beyond the capacity of classical computers, but may be realizable on state-of-the-art trapped-ion systems. These results allow us to envision a new paradigm of quantum chemistry that shifts from the current transistor to a near-future trapped-ion-based technology.
From transistor to trapped-ion computers for quantum chemistry
Yung, M.-H.; Casanova, J.; Mezzacapo, A.; McClean, J.; Lamata, L.; Aspuru-Guzik, A.; Solano, E.
2014-01-01
Over the last few decades, quantum chemistry has progressed through the development of computational methods based on modern digital computers. However, these methods can hardly fulfill the exponentially-growing resource requirements when applied to large quantum systems. As pointed out by Feynman, this restriction is intrinsic to all computational models based on classical physics. Recently, the rapid advancement of trapped-ion technologies has opened new possibilities for quantum control and quantum simulations. Here, we present an efficient toolkit that exploits both the internal and motional degrees of freedom of trapped ions for solving problems in quantum chemistry, including molecular electronic structure, molecular dynamics, and vibronic coupling. We focus on applications that go beyond the capacity of classical computers, but may be realizable on state-of-the-art trapped-ion systems. These results allow us to envision a new paradigm of quantum chemistry that shifts from the current transistor to a near-future trapped-ion-based technology. PMID:24395054
Accelerating MP2C dispersion corrections for dimers and molecular crystals
NASA Astrophysics Data System (ADS)
Huang, Yuanhang; Shao, Yihan; Beran, Gregory J. O.
2013-06-01
The MP2C dispersion correction of Pitonak and Hesselmann [J. Chem. Theory Comput. 6, 168 (2010)], 10.1021/ct9005882 substantially improves the performance of second-order Møller-Plesset perturbation theory for non-covalent interactions, albeit with non-trivial computational cost. Here, the MP2C correction is computed in a monomer-centered basis instead of a dimer-centered one. When applied to a single dimer MP2 calculation, this change accelerates the MP2C dispersion correction several-fold while introducing only trivial new errors. More significantly, in the context of fragment-based molecular crystal studies, combination of the new monomer basis algorithm and the periodic symmetry of the crystal reduces the cost of computing the dispersion correction by two orders of magnitude. This speed-up reduces the MP2C dispersion correction calculation from a significant computational expense to a negligible one in crystals like aspirin or oxalyl dihydrazide, without compromising accuracy.
Quantitative Characterization of Molecular Similarity Spaces: Tools for Computational Toxicology
2000-01-20
numbers for hydrogen-filled molecular structure, hydrogen-suppressed molecular structure, and van der Waals volume. Van der Waals...relative covalent radii Geometrical Vw van der Waals volume 3DW 3-D Wiener number for the hydrogen-suppressed geometric distance matrix...molecular structure, and van der Waals volume. Van der Waals volume, Vw (Bondi 1964). was calculated using Sybyl 6.1 from Tripos As- sociates. Inc
PSPP: A Protein Structure Prediction Pipeline for Computing Clusters
2009-07-01
Evanseck JD, et al. (1998) All-atom empirical potential for molecular modeling and dynamics studies of proteins. Journal of Physical Chemistry B 102...dimensional (3-D) protein structures are critical for the understanding of molecular mechanisms of living systems. Traditionally, X-ray crystallography...disordered proteins are often responsible for molecular recognition, molecular assembly, protein modifica- tion, and entropic chain activities in organisms [26
2006-08-01
preparing a COBRE Molecular Targets Project with a goal to extend the computational work of Specific Aims of this project to the discovery of novel...million Center of Biomedical Research Excellence ( COBRE ) grant from the National Center for Research Resources at the National Institutes of Health...three year COBRE -funded project in Molecular Targets. My recruitment to the University of Louisville’s Brown Cancer Center and my proposed COBRE
Computer Simulation of Protein-Protein and Protein-Peptide Interactions
1983-12-08
a full molecular dynamic z simulation is performed, with resulting dipolar re - laxation. However, this is prohibitive when a large . number of...1993 Dr. Mike Marron Program Manager Molecular Biology Office of Naval Research 800 N. Quincy Street Arlington, VA 22217 Dear Mike, Here is the...rztnbutior is unLi--ited. , 93-30630 98 12 12/08/93 01/0/92-;03/31/93: Final Report, Computer Simulation of Protein-Protein and Protein-Peptide
Chiang, Harry; Robinson, Lucy C; Brame, Cynthia J; Messina, Troy C
2013-01-01
Over the past 20 years, the biological sciences have increasingly incorporated chemistry, physics, computer science, and mathematics to aid in the development and use of mathematical models. Such combined approaches have been used to address problems from protein structure-function relationships to the workings of complex biological systems. Computer simulations of molecular events can now be accomplished quickly and with standard computer technology. Also, simulation software is freely available for most computing platforms, and online support for the novice user is ample. We have therefore created a molecular dynamics laboratory module to enhance undergraduate student understanding of molecular events underlying organismal phenotype. This module builds on a previously described project in which students use site-directed mutagenesis to investigate functions of conserved sequence features in members of a eukaryotic protein kinase family. In this report, we detail the laboratory activities of a MD module that provide a complement to phenotypic outcomes by providing a hypothesis-driven and quantifiable measure of predicted structural changes caused by targeted mutations. We also present examples of analyses students may perform. These laboratory activities can be integrated with genetics or biochemistry experiments as described, but could also be used independently in any course that would benefit from a quantitative approach to protein structure-function relationships. Copyright © 2013 Wiley Periodicals, Inc.
Atomistic models for free energy evaluation of drug binding to membrane proteins.
Durdagi, S; Zhao, C; Cuervo, J E; Noskov, S Y
2011-01-01
The binding of various molecules to integral membrane proteins with optimal affinity and specificity is central to normal function of cell. While membrane proteins represent about one third of the whole cell proteome, they are a majority of common drug targets. The quest for the development of computational models capable of accurate evaluation of binding affinities, decomposition of the binding into its principal components and thus mapping molecular mechanisms of binding remains one of the main goals of modern computational biophysics and related drug development. The primary scope of this review will be on the recent extension of computational methods for the study of drug binding to membrane proteins. Several examples of such applications will be provided ranging from secondary transporters to voltage gated channels. In this mini-review, we will provide a short summary on the breadth of different methods for binding affinity evaluation. These methods include molecular docking with docking scoring functions, molecular dynamics (MD) simulations combined with post-processing analysis using Molecular Mechanics/Poisson Boltzmann (Generalized Born) Surface Area (MM/PB(GB)SA), as well as direct evaluation of free energies from Free Energy Perturbation (FEP) with constraining schemes, and Potential of Mean Force (PMF) computations. We will compare advantages and shortcomings of popular techniques and provide discussion on the integrative strategies for drug development aimed at targeting membrane proteins.
Computer Aided Drug Design: Success and Limitations.
Baig, Mohammad Hassan; Ahmad, Khurshid; Roy, Sudeep; Ashraf, Jalaluddin Mohammad; Adil, Mohd; Siddiqui, Mohammad Haris; Khan, Saif; Kamal, Mohammad Amjad; Provazník, Ivo; Choi, Inho
2016-01-01
Over the last few decades, computer-aided drug design has emerged as a powerful technique playing a crucial role in the development of new drug molecules. Structure-based drug design and ligand-based drug design are two methods commonly used in computer-aided drug design. In this article, we discuss the theory behind both methods, as well as their successful applications and limitations. To accomplish this, we reviewed structure based and ligand based virtual screening processes. Molecular dynamics simulation, which has become one of the most influential tool for prediction of the conformation of small molecules and changes in their conformation within the biological target, has also been taken into account. Finally, we discuss the principles and concepts of molecular docking, pharmacophores and other methods used in computer-aided drug design.
Solid-liquid phase coexistence of alkali nitrates from molecular dynamics simulations.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jayaraman, Saivenkataraman
2010-03-01
Alkali nitrate eutectic mixtures are finding application as industrial heat transfer fluids in concentrated solar power generation systems. An important property for such applications is the melting point, or phase coexistence temperature. We have computed melting points for lithium, sodium and potassium nitrate from molecular dynamics simulations using a recently developed method, which uses thermodynamic integration to compute the free energy difference between the solid and liquid phases. The computed melting point for NaNO3 was within 15K of its experimental value, while for LiNO3 and KNO3, the computed melting points were within 100K of the experimental values [4]. We aremore » currently extending the approach to calculate melting temperatures for binary mixtures of lithium and sodium nitrate.« less
Integrating Computational Chemistry into a Course in Classical Thermodynamics
ERIC Educational Resources Information Center
Martini, Sheridan R.; Hartzell, Cynthia J.
2015-01-01
Computational chemistry is commonly addressed in the quantum mechanics course of undergraduate physical chemistry curricula. Since quantum mechanics traditionally follows the thermodynamics course, there is a lack of curricula relating computational chemistry to thermodynamics. A method integrating molecular modeling software into a semester long…
Computing Models for FPGA-Based Accelerators
Herbordt, Martin C.; Gu, Yongfeng; VanCourt, Tom; Model, Josh; Sukhwani, Bharat; Chiu, Matt
2011-01-01
Field-programmable gate arrays are widely considered as accelerators for compute-intensive applications. A critical phase of FPGA application development is finding and mapping to the appropriate computing model. FPGA computing enables models with highly flexible fine-grained parallelism and associative operations such as broadcast and collective response. Several case studies demonstrate the effectiveness of using these computing models in developing FPGA applications for molecular modeling. PMID:21603152
Mixed QM/MM molecular electrostatic potentials.
Hernández, B; Luque, F J; Orozco, M
2000-05-01
A new method is presented for the calculation of the Molecular Electrostatic Potential (MEP) in large systems. Based on the mixed Quantum Mechanics/Molecular Mechanics (QM/MM) approach, the method assumes both a quantum and classical description for the molecule, and the calculation of the MEP in the space surrounding the molecule is made using this dual treatment. The MEP at points close to the molecule is computed using a full QM formalism, while a pure classical evaluation of the MEP is used for points located at large distances from the molecule. The algorithm allows the user to select the desired level of accuracy in the MEP, so that the definition of the regions where the MEP is computed at the classical or QM levels is adjusted automatically. The potential use of this QM/MM MEP in molecular modeling studies is discussed.
NASA Technical Reports Server (NTRS)
2000-01-01
The molecule modeling method known as Multibody Order (N) Dynamics, or MBO(N)D, was developed by Moldyn, Inc. at Goddard Space Flight Center through funding provided by the SBIR program. The software can model the dynamics of molecules through technology which stimulates low-frequency molecular motions and properties, such as movements among a molecule's constituent parts. With MBO(N)D, a molecule is substructured into a set of interconnected rigid and flexible bodies. These bodies replace the computation burden of mapping individual atoms. Moldyn's technology cuts computation time while increasing accuracy. The MBO(N)D technology is available as Insight II 97.0 from Molecular Simulations, Inc. Currently the technology is used to account for forces on spacecraft parts and to perform molecular analyses for pharmaceutical purposes. It permits the solution of molecular dynamics problems on a moderate workstation, as opposed to on a supercomputer.
Treatment of atomic and molecular line blanketing by opacity sampling
NASA Technical Reports Server (NTRS)
Johnson, H. R.; Krupp, B. M.
1976-01-01
A sampling technique for treating the radiative opacity of large numbers of atomic and molecular lines in cool stellar atmospheres is subjected to several tests. In this opacity sampling (OS) technique, the global opacity is sampled at only a selected set of frequencies, and at each of these frequencies the total monochromatic opacity is obtained by summing the contribution of every relevant atomic and molecular line. In accord with previous results, we find that the structure of atmospheric models is accurately fixed by the use of 1000 frequency points, and 100 frequency points are adequate for many purposes. The effects of atomic and molecular lines are separately studied. A test model computed using the OS method agrees very well with a model having identical atmospheric parameters, but computed with the giant line (opacity distribution function) method.
Carbohydrate-protein interactions: molecular modeling insights.
Pérez, Serge; Tvaroška, Igor
2014-01-01
The article reviews the significant contributions to, and the present status of, applications of computational methods for the characterization and prediction of protein-carbohydrate interactions. After a presentation of the specific features of carbohydrate modeling, along with a brief description of the experimental data and general features of carbohydrate-protein interactions, the survey provides a thorough coverage of the available computational methods and tools. At the quantum-mechanical level, the use of both molecular orbitals and density-functional theory is critically assessed. These are followed by a presentation and critical evaluation of the applications of semiempirical and empirical methods: QM/MM, molecular dynamics, free-energy calculations, metadynamics, molecular robotics, and others. The usefulness of molecular docking in structural glycobiology is evaluated by considering recent docking- validation studies on a range of protein targets. The range of applications of these theoretical methods provides insights into the structural, energetic, and mechanistic facets that occur in the course of the recognition processes. Selected examples are provided to exemplify the usefulness and the present limitations of these computational methods in their ability to assist in elucidation of the structural basis underlying the diverse function and biological roles of carbohydrates in their dialogue with proteins. These test cases cover the field of both carbohydrate biosynthesis and glycosyltransferases, as well as glycoside hydrolases. The phenomenon of (macro)molecular recognition is illustrated for the interactions of carbohydrates with such proteins as lectins, monoclonal antibodies, GAG-binding proteins, porins, and viruses. © 2014 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Graves, A. Palmer
This study examines the effect of increasing the visual complexity used in computer assisted instruction in general chemistry. Traditional recitation instruction was used as a control for the experiment. One tutorial presented a chemistry topic using 3-D animation showing molecular activity and symbolic representation of the macroscopic view of a chemical phenomenon. A second tutorial presented the same topic but simultaneously presented students with a digital video movie showing the phenomena and 3-D animation showing the molecular view of the phenomena. This experimental set-up was used in two different experiments during the first semester of college level general chemistry course. The topics covered were the molecular effect of heating water through the solid-liquid phase change and the kinetic molecular theory used in explaining pressure changes. The subjects used in the experiment were 236 college students enrolled in a freshman chemistry course at a large university. The data indicated that the simultaneous presentation of digital video, showing the solid to liquid phase change of water, with a molecular animation, showing the molecular behavior during the phase change, had a significant effect on student particulate understanding when compared to traditional recitation. Although the effect of the KMT tutorial was not statistically significant, there was a positive effect on student particulate understanding. The use of computer tutorial also had a significant effect on student attitude toward their comprehension of the lesson.
Grindon, Christina; Harris, Sarah; Evans, Tom; Novik, Keir; Coveney, Peter; Laughton, Charles
2004-07-15
Molecular modelling played a central role in the discovery of the structure of DNA by Watson and Crick. Today, such modelling is done on computers: the more powerful these computers are, the more detailed and extensive can be the study of the dynamics of such biological macromolecules. To fully harness the power of modern massively parallel computers, however, we need to develop and deploy algorithms which can exploit the structure of such hardware. The Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is a scalable molecular dynamics code including long-range Coulomb interactions, which has been specifically designed to function efficiently on parallel platforms. Here we describe the implementation of the AMBER98 force field in LAMMPS and its validation for molecular dynamics investigations of DNA structure and flexibility against the benchmark of results obtained with the long-established code AMBER6 (Assisted Model Building with Energy Refinement, version 6). Extended molecular dynamics simulations on the hydrated DNA dodecamer d(CTTTTGCAAAAG)(2), which has previously been the subject of extensive dynamical analysis using AMBER6, show that it is possible to obtain excellent agreement in terms of static, dynamic and thermodynamic parameters between AMBER6 and LAMMPS. In comparison with AMBER6, LAMMPS shows greatly improved scalability in massively parallel environments, opening up the possibility of efficient simulations of order-of-magnitude larger systems and/or for order-of-magnitude greater simulation times.
NASA Astrophysics Data System (ADS)
Shegog, Ross; Lazarus, Melanie M.; Murray, Nancy G.; Diamond, Pamela M.; Sessions, Nathalie; Zsigmond, Eva
2012-10-01
The transgenic mouse model is useful for studying the causes and potential cures for human genetic diseases. Exposing high school biology students to laboratory experience in developing transgenic animal models is logistically prohibitive. Computer-based simulation, however, offers this potential in addition to advantages of fidelity and reach. This study describes and evaluates a computer-based simulation to train advanced placement high school science students in laboratory protocols, a transgenic mouse model was produced. A simulation module on preparing a gene construct in the molecular biology lab was evaluated using a randomized clinical control design with advanced placement high school biology students in Mercedes, Texas ( n = 44). Pre-post tests assessed procedural and declarative knowledge, time on task, attitudes toward computers for learning and towards science careers. Students who used the simulation increased their procedural and declarative knowledge regarding molecular biology compared to those in the control condition (both p < 0.005). Significant increases continued to occur with additional use of the simulation ( p < 0.001). Students in the treatment group became more positive toward using computers for learning ( p < 0.001). The simulation did not significantly affect attitudes toward science in general. Computer simulation of complex transgenic protocols have potential to provide a "virtual" laboratory experience as an adjunct to conventional educational approaches.
Computer-Assisted Drug Formulation Design: Novel Approach in Drug Delivery.
Metwally, Abdelkader A; Hathout, Rania M
2015-08-03
We hypothesize that, by using several chemo/bio informatics tools and statistical computational methods, we can study and then predict the behavior of several drugs in model nanoparticulate lipid and polymeric systems. Accordingly, two different matrices comprising tripalmitin, a core component of solid lipid nanoparticles (SLN), and PLGA were first modeled using molecular dynamics simulation, and then the interaction of drugs with these systems was studied by means of computing the free energy of binding using the molecular docking technique. These binding energies were hence correlated with the loadings of these drugs in the nanoparticles obtained experimentally from the available literature. The obtained relations were verified experimentally in our laboratory using curcumin as a model drug. Artificial neural networks were then used to establish the effect of the drugs' molecular descriptors on the binding energies and hence on the drug loading. The results showed that the used soft computing methods can provide an accurate method for in silico prediction of drug loading in tripalmitin-based and PLGA nanoparticulate systems. These results have the prospective of being applied to other nano drug-carrier systems, and this integrated statistical and chemo/bio informatics approach offers a new toolbox to the formulation science by proposing what we present as computer-assisted drug formulation design (CADFD).
Computer-Aided Drug Discovery: Molecular Docking of Diminazene Ligands to DNA Minor Groove
ERIC Educational Resources Information Center
Kholod, Yana; Hoag, Erin; Muratore, Katlynn; Kosenkov, Dmytro
2018-01-01
The reported project-based laboratory unit introduces upper-division undergraduate students to the basics of computer-aided drug discovery as a part of a computational chemistry laboratory course. The students learn to perform model binding of organic molecules (ligands) to the DNA minor groove with computer-aided drug discovery (CADD) tools. The…
Calculation of total cross sections for charge exchange in molecular collisions
NASA Technical Reports Server (NTRS)
Ioup, J.
1979-01-01
Areas of investigation summarized include nitrogen ion-nitrogen molecule collisions; molecular collisions with surfaces; molecular identification from analysis of cracking patterns of selected gases; computer modelling of a quadrupole mass spectrometer; study of space charge in a quadrupole; transmission of the 127 deg cylindrical electrostatic analyzer; and mass spectrometer data deconvolution.
USDA-ARS?s Scientific Manuscript database
Immunoassay for low molecular weight food contaminants, such as pesticides, veterinary drugs, and mycotoxins is now a well-established technique which meets the demands for a rapid, reliable, and cost-effective analytical method. However, due to limited understanding of the fundamental aspects of i...
Vidossich, Pietro; Lledós, Agustí; Ujaque, Gregori
2016-06-21
Computational chemistry is a valuable aid to complement experimental studies of organometallic systems and their reactivity. It allows probing mechanistic hypotheses and investigating molecular structures, shedding light on the behavior and properties of molecular assemblies at the atomic scale. When approaching a chemical problem, the computational chemist has to decide on the theoretical approach needed to describe electron/nuclear interactions and the composition of the model used to approximate the actual system. Both factors determine the reliability of the modeling study. The community dedicated much effort to developing and improving the performance and accuracy of theoretical approaches for electronic structure calculations, on which the description of (inter)atomic interactions rely. Here, the importance of the model system used in computational studies is highlighted through examples from our recent research focused on organometallic systems and homogeneous catalytic processes. We show how the inclusion of explicit solvent allows the characterization of molecular events that would otherwise not be accessible in reduced model systems (clusters). These include the stabilization of nascent charged fragments via microscopic solvation (notably, hydrogen bonding), transfer of charge (protons) between distant fragments mediated by solvent molecules, and solvent coordination to unsaturated metal centers. Furthermore, when weak interactions are involved, we show how conformational and solvation properties of organometallic complexes are also affected by the explicit inclusion of solvent molecules. Such extended model systems may be treated under periodic boundary conditions, thus removing the cluster/continuum (or vacuum) boundary, and require a statistical mechanics simulation technique to sample the accessible configurational space. First-principles molecular dynamics, in which atomic forces are computed from electronic structure calculations (namely, density functional theory), is certainly the technique of choice to investigate chemical events in solution. This methodology is well established and thanks to advances in both algorithms and computational resources simulation times required for the modeling of chemical events are nowadays accessible, though the computational requirements use to be high. Specific applications reviewed here include mechanistic studies of the Shilov and Wacker processes, speciation in Pd chemistry, hydrogen bonding to metal centers, and the dynamics of agostic interactions.
Computational prediction of formulation strategies for beyond-rule-of-5 compounds.
Bergström, Christel A S; Charman, William N; Porter, Christopher J H
2016-06-01
The physicochemical properties of some contemporary drug candidates are moving towards higher molecular weight, and coincidentally also higher lipophilicity in the quest for biological selectivity and specificity. These physicochemical properties move the compounds towards beyond rule-of-5 (B-r-o-5) chemical space and often result in lower water solubility. For such B-r-o-5 compounds non-traditional delivery strategies (i.e. those other than conventional tablet and capsule formulations) typically are required to achieve adequate exposure after oral administration. In this review, we present the current status of computational tools for prediction of intestinal drug absorption, models for prediction of the most suitable formulation strategies for B-r-o-5 compounds and models to obtain an enhanced understanding of the interplay between drug, formulation and physiological environment. In silico models are able to identify the likely molecular basis for low solubility in physiologically relevant fluids such as gastric and intestinal fluids. With this baseline information, a formulation scientist can, at an early stage, evaluate different orally administered, enabling formulation strategies. Recent computational models have emerged that predict glass-forming ability and crystallisation tendency and therefore the potential utility of amorphous solid dispersion formulations. Further, computational models of loading capacity in lipids, and therefore the potential for formulation as a lipid-based formulation, are now available. Whilst such tools are useful for rapid identification of suitable formulation strategies, they do not reveal drug localisation and molecular interaction patterns between drug and excipients. For the latter, Molecular Dynamics simulations provide an insight into the interplay between drug, formulation and intestinal fluid. These different computational approaches are reviewed. Additionally, we analyse the molecular requirements of different targets, since these can provide an early signal that enabling formulation strategies will be required. Based on the analysis we conclude that computational biopharmaceutical profiling can be used to identify where non-conventional gateways, such as prediction of 'formulate-ability' during lead optimisation and early development stages, are important and may ultimately increase the number of orally tractable contemporary targets. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Deosarkar, S. D.; Ghatbandhe, A. S.
2014-01-01
Molecular interactions and structural fittings in binary ethylene glycol + ethanol (EGE, x EG = 0.4111-0.0418) and ethylene glycol + water (EGW, x EG = 0.1771-0.0133) mixtures were studied through the measurement of densities (ρ), viscosities (η), and refractive indices ( n D ) at 303.15 K. Excess viscosities (η E ), molar volumes ( V m ), excess molar volumes ( V {/m E }), and molar retractions ( R M ) of the both binary systems were computed from measured properties. The measured and computed properties have been used to understand the molecular interactions in unlike solvents and structural fittings in these binary mixtures.
Gutiérrez-Sevillano, Juan José; Caro-Pérez, Alejandro; Dubbeldam, David; Calero, Sofía
2011-12-07
We report a molecular simulation study for Cu-BTC metal-organic frameworks as carbon dioxide-methane separation devices. For this study we have computed adsorption and diffusion of methane and carbon dioxide in the structure, both as pure components and mixtures over the full range of bulk gas compositions. From the single component isotherms, mixture adsorption is predicted using the ideal adsorbed solution theory. These predictions are in very good agreement with our computed mixture isotherms and with previously reported data. Adsorption and diffusion selectivities and preferential sitings are also discussed with the aim to provide new molecular level information for all studied systems.
Pteros: fast and easy to use open-source C++ library for molecular analysis.
Yesylevskyy, Semen O
2012-07-15
An open-source Pteros library for molecular modeling and analysis of molecular dynamics trajectories for C++ programming language is introduced. Pteros provides a number of routine analysis operations ranging from reading and writing trajectory files and geometry transformations to structural alignment and computation of nonbonded interaction energies. The library features asynchronous trajectory reading and parallel execution of several analysis routines, which greatly simplifies development of computationally intensive trajectory analysis algorithms. Pteros programming interface is very simple and intuitive while the source code is well documented and easily extendible. Pteros is available for free under open-source Artistic License from http://sourceforge.net/projects/pteros/. Copyright © 2012 Wiley Periodicals, Inc.
Metabolite identification through multiple kernel learning on fragmentation trees.
Shen, Huibin; Dührkop, Kai; Böcker, Sebastian; Rousu, Juho
2014-06-15
Metabolite identification from tandem mass spectrometric data is a key task in metabolomics. Various computational methods have been proposed for the identification of metabolites from tandem mass spectra. Fragmentation tree methods explore the space of possible ways in which the metabolite can fragment, and base the metabolite identification on scoring of these fragmentation trees. Machine learning methods have been used to map mass spectra to molecular fingerprints; predicted fingerprints, in turn, can be used to score candidate molecular structures. Here, we combine fragmentation tree computations with kernel-based machine learning to predict molecular fingerprints and identify molecular structures. We introduce a family of kernels capturing the similarity of fragmentation trees, and combine these kernels using recently proposed multiple kernel learning approaches. Experiments on two large reference datasets show that the new methods significantly improve molecular fingerprint prediction accuracy. These improvements result in better metabolite identification, doubling the number of metabolites ranked at the top position of the candidates list. © The Author 2014. Published by Oxford University Press.
Structure simulation with calculated NMR parameters - integrating COSMOS into the CCPN framework.
Schneider, Olaf; Fogh, Rasmus H; Sternberg, Ulrich; Klenin, Konstantin; Kondov, Ivan
2012-01-01
The Collaborative Computing Project for NMR (CCPN) has build a software framework consisting of the CCPN data model (with APIs) for NMR related data, the CcpNmr Analysis program and additional tools like CcpNmr FormatConverter. The open architecture allows for the integration of external software to extend the abilities of the CCPN framework with additional calculation methods. Recently, we have carried out the first steps for integrating our software Computer Simulation of Molecular Structures (COSMOS) into the CCPN framework. The COSMOS-NMR force field unites quantum chemical routines for the calculation of molecular properties with a molecular mechanics force field yielding the relative molecular energies. COSMOS-NMR allows introducing NMR parameters as constraints into molecular mechanics calculations. The resulting infrastructure will be made available for the NMR community. As a first application we have tested the evaluation of calculated protein structures using COSMOS-derived 13C Cα and Cβ chemical shifts. In this paper we give an overview of the methodology and a roadmap for future developments and applications.
Web-Based Job Submission Interface for the GAMESS Computational Chemistry Program
ERIC Educational Resources Information Center
Perri, M. J.; Weber, S. H.
2014-01-01
A Web site is described that facilitates use of the free computational chemistry software: General Atomic and Molecular Electronic Structure System (GAMESS). Its goal is to provide an opportunity for undergraduate students to perform computational chemistry experiments without the need to purchase expensive software.
2011-12-01
REMD while reproducing the energy landscape of explicit solvent simulations . ’ INTRODUCTION Molecular dynamics (MD) simulations of proteins can pro...Mongan, J.; McCammon, J. A. Accelerated molecular dynamics : a promising and efficient simulation method for biomolecules. J. Chem. Phys. 2004, 120 (24...Chemical Theory and Computation ARTICLE (8) Abraham,M. J.; Gready, J. E. Ensuringmixing efficiency of replica- exchange molecular dynamics simulations . J
NASA Astrophysics Data System (ADS)
Arefeva, Oksana A.; Kuznetsov, Pavel E.; Tolmachev, Sergey A.; Kupadze, Machammad S.; Khlebtsov, Boris N.; Rogacheva, Svetlana M.
2003-09-01
We have studied the conformational properties and molecular dynamics of polysaccharides by using molecular modeling methods. Theoretical and experimental results of polysaccharide-polysaccharide interactions are described.
General purpose molecular dynamics simulations fully implemented on graphics processing units
NASA Astrophysics Data System (ADS)
Anderson, Joshua A.; Lorenz, Chris D.; Travesset, A.
2008-05-01
Graphics processing units (GPUs), originally developed for rendering real-time effects in computer games, now provide unprecedented computational power for scientific applications. In this paper, we develop a general purpose molecular dynamics code that runs entirely on a single GPU. It is shown that our GPU implementation provides a performance equivalent to that of fast 30 processor core distributed memory cluster. Our results show that GPUs already provide an inexpensive alternative to such clusters and discuss implications for the future.
2010-01-01
This meeting report gives an overview of the keynote lectures and a selection of the student oral and poster presentations at the 6th International Society for Computational Biology Student Council Symposium that was held as a precursor event to the annual international conference on Intelligent Systems for Molecular Biology (ISMB). The symposium was held in Boston, MA, USA on July 9th, 2010.
Computer Simulation of the Elastic Properties of Titanium Alloys for Medical Applications
NASA Astrophysics Data System (ADS)
Estevez, Elsa Paz; Burganova, R. M.; Lysogorskii, Yu. V.
2016-09-01
Results of a computer simulation of the elastic properties of α+β- and β-titanium alloys, used for medical purposes, within the framework of the molecular-dynamics method are presented. It is shown that β-titanium alloys are best suited for the use as bone implants because of their small moduli of elasticity. The advisability of the use of the molecular-dynamics method for the study of the elastic properties of titanium alloys, serving as bone implants, is demonstrated.
1991-01-24
Molecular Graphics, vol. 6, No. 4 (Dec. 1988), p. 223. Turk, Greg, "Interactive Collision Detection for Molecular Graphics," M.S. thesis , UNC-Chapel Hill...Problem," Master’s thesis , UNC Department of Computer Science Technical Report #TR87-013, May 1987. Pique, ME., "Technical Trends in Molecular Graphics...AD-A236 598 Seventeenth Annual Progress Report and 1992-97 Renewal Proposal Interactive Graphics for Molecular Studies TR91-020 January 24, 1991 red
Gartner, Thomas E; Epps, Thomas H; Jayaraman, Arthi
2016-11-08
We describe an extension of the Gibbs ensemble molecular dynamics (GEMD) method for studying phase equilibria. Our modifications to GEMD allow for direct control over particle transfer between phases and improve the method's numerical stability. Additionally, we found that the modified GEMD approach had advantages in computational efficiency in comparison to a hybrid Monte Carlo (MC)/MD Gibbs ensemble scheme in the context of the single component Lennard-Jones fluid. We note that this increase in computational efficiency does not compromise the close agreement of phase equilibrium results between the two methods. However, numerical instabilities in the GEMD scheme hamper GEMD's use near the critical point. We propose that the computationally efficient GEMD simulations can be used to map out the majority of the phase window, with hybrid MC/MD used as a follow up for conditions under which GEMD may be unstable (e.g., near-critical behavior). In this manner, we can capitalize on the contrasting strengths of these two methods to enable the efficient study of phase equilibria for systems that present challenges for a purely stochastic GEMC method, such as dense or low temperature systems, and/or those with complex molecular topologies.
Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt
Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach and paper, the theoretical modeling and scalingmore » laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. Finally, these two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.« less
Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes
Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt; ...
2017-11-27
Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach and paper, the theoretical modeling and scalingmore » laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. Finally, these two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.« less
Demonstrated of the use of a computational systems biology approach to model dose response relationships. Also discussed how the biologically motivated dose response models have only limited reference to the underlying molecular level. Discussed the integration of Computational S...
Computational toxicology is a new research initiative being developed within the Office of Research and Development (ORD) of the US Environmental Protection Agency (EPA). Operationally, it is defined as the application of mathematical and computer models together with molecular c...
Dudding, Travis; Houk, Kendall N.
2004-01-01
The catalytic asymmetric thiazolium- and triazolium-catalyzed benzoin condensations of aldehydes and ketones were studied with computational methods. Transition-state geometries were optimized by using Morokuma's IMOMO [integrated MO (molecular orbital) + MO method] variation of ONIOM (n-layered integrated molecular orbital method) with a combination of B3LYP/6–31G(d) and AM1 levels of theory, and final transition-state energies were computed with single-point B3LYP/6–31G(d) calculations. Correlations between experiment and theory were found, and the origins of stereoselection were identified. Thiazolium catalysts were predicted to be less selective then triazolium catalysts, a trend also found experimentally. PMID:15079058
Extending rule-based methods to model molecular geometry and 3D model resolution.
Hoard, Brittany; Jacobson, Bruna; Manavi, Kasra; Tapia, Lydia
2016-08-01
Computational modeling is an important tool for the study of complex biochemical processes associated with cell signaling networks. However, it is challenging to simulate processes that involve hundreds of large molecules due to the high computational cost of such simulations. Rule-based modeling is a method that can be used to simulate these processes with reasonably low computational cost, but traditional rule-based modeling approaches do not include details of molecular geometry. The incorporation of geometry into biochemical models can more accurately capture details of these processes, and may lead to insights into how geometry affects the products that form. Furthermore, geometric rule-based modeling can be used to complement other computational methods that explicitly represent molecular geometry in order to quantify binding site accessibility and steric effects. We propose a novel implementation of rule-based modeling that encodes details of molecular geometry into the rules and binding rates. We demonstrate how rules are constructed according to the molecular curvature. We then perform a study of antigen-antibody aggregation using our proposed method. We simulate the binding of antibody complexes to binding regions of the shrimp allergen Pen a 1 using a previously developed 3D rigid-body Monte Carlo simulation, and we analyze the aggregate sizes. Then, using our novel approach, we optimize a rule-based model according to the geometry of the Pen a 1 molecule and the data from the Monte Carlo simulation. We use the distances between the binding regions of Pen a 1 to optimize the rules and binding rates. We perform this procedure for multiple conformations of Pen a 1 and analyze the impact of conformation and resolution on the optimal rule-based model. We find that the optimized rule-based models provide information about the average steric hindrance between binding regions and the probability that antibodies will bind to these regions. These optimized models quantify the variation in aggregate size that results from differences in molecular geometry and from model resolution.
Better, Cheaper, Faster Molecular Dynamics
NASA Technical Reports Server (NTRS)
Pohorille, Andrew; DeVincenzi, Donald L. (Technical Monitor)
2001-01-01
Recent, revolutionary progress in genomics and structural, molecular and cellular biology has created new opportunities for molecular-level computer simulations of biological systems by providing vast amounts of data that require interpretation. These opportunities are further enhanced by the increasing availability of massively parallel computers. For many problems, the method of choice is classical molecular dynamics (iterative solving of Newton's equations of motion). It focuses on two main objectives. One is to calculate the relative stability of different states of the system. A typical problem that has' such an objective is computer-aided drug design. Another common objective is to describe evolution of the system towards a low energy (possibly the global minimum energy), "native" state. Perhaps the best example of such a problem is protein folding. Both types of problems share the same difficulty. Often, different states of the system are separated by high energy barriers, which implies that transitions between these states are rare events. This, in turn, can greatly impede exploration of phase space. In some instances this can lead to "quasi non-ergodicity", whereby a part of phase space is inaccessible on time scales of the simulation. To overcome this difficulty and to extend molecular dynamics to "biological" time scales (millisecond or longer) new physical formulations and new algorithmic developments are required. To be efficient they should account for natural limitations of multi-processor computer architecture. I will present work along these lines done in my group. In particular, I will focus on a new approach to calculating the free energies (stability) of different states and to overcoming "the curse of rare events". I will also discuss algorithmic improvements to multiple time step methods and to the treatment of slowly decaying, log-ranged, electrostatic effects.
ISMB 2016 offers outstanding science, networking, and celebration
Fogg, Christiana
2016-01-01
The annual international conference on Intelligent Systems for Molecular Biology (ISMB) is the major meeting of the International Society for Computational Biology (ISCB). Over the past 23 years the ISMB conference has grown to become the world's largest bioinformatics/computational biology conference. ISMB 2016 will be the year's most important computational biology event globally. The conferences provide a multidisciplinary forum for disseminating the latest developments in bioinformatics/computational biology. ISMB brings together scientists from computer science, molecular biology, mathematics, statistics and related fields. Its principal focus is on the development and application of advanced computational methods for biological problems. ISMB 2016 offers the strongest scientific program and the broadest scope of any international bioinformatics/computational biology conference. Building on past successes, the conference is designed to cater to variety of disciplines within the bioinformatics/computational biology community. ISMB 2016 takes place July 8 - 12 at the Swan and Dolphin Hotel in Orlando, Florida, United States. For two days preceding the conference, additional opportunities including Satellite Meetings, Student Council Symposium, and a selection of Special Interest Group Meetings and Applied Knowledge Exchange Sessions (AKES) are all offered to enable registered participants to learn more on the latest methods and tools within specialty research areas. PMID:27347392
ISMB 2016 offers outstanding science, networking, and celebration.
Fogg, Christiana
2016-01-01
The annual international conference on Intelligent Systems for Molecular Biology (ISMB) is the major meeting of the International Society for Computational Biology (ISCB). Over the past 23 years the ISMB conference has grown to become the world's largest bioinformatics/computational biology conference. ISMB 2016 will be the year's most important computational biology event globally. The conferences provide a multidisciplinary forum for disseminating the latest developments in bioinformatics/computational biology. ISMB brings together scientists from computer science, molecular biology, mathematics, statistics and related fields. Its principal focus is on the development and application of advanced computational methods for biological problems. ISMB 2016 offers the strongest scientific program and the broadest scope of any international bioinformatics/computational biology conference. Building on past successes, the conference is designed to cater to variety of disciplines within the bioinformatics/computational biology community. ISMB 2016 takes place July 8 - 12 at the Swan and Dolphin Hotel in Orlando, Florida, United States. For two days preceding the conference, additional opportunities including Satellite Meetings, Student Council Symposium, and a selection of Special Interest Group Meetings and Applied Knowledge Exchange Sessions (AKES) are all offered to enable registered participants to learn more on the latest methods and tools within specialty research areas.
A survey of current trends in computational drug repositioning.
Li, Jiao; Zheng, Si; Chen, Bin; Butte, Atul J; Swamidass, S Joshua; Lu, Zhiyong
2016-01-01
Computational drug repositioning or repurposing is a promising and efficient tool for discovering new uses from existing drugs and holds the great potential for precision medicine in the age of big data. The explosive growth of large-scale genomic and phenotypic data, as well as data of small molecular compounds with granted regulatory approval, is enabling new developments for computational repositioning. To achieve the shortest path toward new drug indications, advanced data processing and analysis strategies are critical for making sense of these heterogeneous molecular measurements. In this review, we show recent advancements in the critical areas of computational drug repositioning from multiple aspects. First, we summarize available data sources and the corresponding computational repositioning strategies. Second, we characterize the commonly used computational techniques. Third, we discuss validation strategies for repositioning studies, including both computational and experimental methods. Finally, we highlight potential opportunities and use-cases, including a few target areas such as cancers. We conclude with a brief discussion of the remaining challenges in computational drug repositioning. Published by Oxford University Press 2015. This work is written by US Government employees and is in the public domain in the US.
Parallel computation with molecular-motor-propelled agents in nanofabricated networks.
Nicolau, Dan V; Lard, Mercy; Korten, Till; van Delft, Falco C M J M; Persson, Malin; Bengtsson, Elina; Månsson, Alf; Diez, Stefan; Linke, Heiner; Nicolau, Dan V
2016-03-08
The combinatorial nature of many important mathematical problems, including nondeterministic-polynomial-time (NP)-complete problems, places a severe limitation on the problem size that can be solved with conventional, sequentially operating electronic computers. There have been significant efforts in conceiving parallel-computation approaches in the past, for example: DNA computation, quantum computation, and microfluidics-based computation. However, these approaches have not proven, so far, to be scalable and practical from a fabrication and operational perspective. Here, we report the foundations of an alternative parallel-computation system in which a given combinatorial problem is encoded into a graphical, modular network that is embedded in a nanofabricated planar device. Exploring the network in a parallel fashion using a large number of independent, molecular-motor-propelled agents then solves the mathematical problem. This approach uses orders of magnitude less energy than conventional computers, thus addressing issues related to power consumption and heat dissipation. We provide a proof-of-concept demonstration of such a device by solving, in a parallel fashion, the small instance {2, 5, 9} of the subset sum problem, which is a benchmark NP-complete problem. Finally, we discuss the technical advances necessary to make our system scalable with presently available technology.
Michael Levitt and Computational Biology
molecular structures, compute structural changes, refine experimental structure, model enzyme catalysis and (May 2004) Top Some links on this page may take you to non-federal websites. Their policies may differ
ERIC Educational Resources Information Center
Carvalho, Ivone; Borges, Aurea D. L.; Bernardes, Lilian S. C.
2005-01-01
The use of computational chemistry and the protein data bank (PDB) to understand and predict the chemical and molecular basis involved in the drug-receptor interactions is discussed. A geometrical and chemical overview of the great structural similarity in the substrate and inhibitor is provided.
A COMPUTER MODELING STUDY OF BINDING PROPERTIES OF CHIRAL NUCLEOPEPTIDE FOR BIOMEDICAL APPLICATIONS.
Pirtskhalava, M; Egoyan, A; Mirtskhulava, M; Roviello, G
2017-12-01
Nucleopeptides often show interesting properties of molecular binding that render them good candidates for development of innovative drugs for anticancer and antiviral therapies. In this work we present results of computer modeling of interactions between the molecules of hexathymine nucleopeptide (T6) and poly rA RNA (A18). The results of geometry optimization calculated using Hyperchem software and our own computer program for molecular docking show that molecules establish stable complexes due to the complementary-nucleobase interaction and the electrostatic interaction between the negative phosphate group of poly rA and the positively-charged residues present in the cationic nucleopeptide structure. Computer modeling makes it possible to find the optimal binding configuration of the molecules of a nucleopeptide and poly rA RNA and to estimate the binding energy between the molecules.
Developing model asphalt systems using molecular simulation : final model.
DOT National Transportation Integrated Search
2009-09-01
Computer based molecular simulations have been used towards developing simple mixture compositions whose : physical properties resemble those of real asphalts. First, Monte Carlo simulations with the OPLS all-atom force : field were used to predict t...
, reaction kinetics, computational modeling, photochemistry, and molecular spectroscopy. Nimlos has served as Chemical reaction energetics and kinetics Biomass pyrolysis and gasification Heterogeneous catalysis in zeolites Quantum modeling and kinetic modeling of reaction Molecular dynamics modeling
of NREL's Computational Science Center, where he uses electronic structure calculations and other introductory chemistry and physical chemistry. Research Interests Electronic structure and dynamics in the quantum/classical molecular dynamics simulation|Coupling of molecular electronic structure to
Molecular vibrational energy flow
NASA Astrophysics Data System (ADS)
Gruebele, M.; Bigwood, R.
This article reviews some recent work in molecular vibrational energy flow (IVR), with emphasis on our own computational and experimental studies. We consider the problem in various representations, and use these to develop a family of simple models which combine specific molecular properties (e.g. size, vibrational frequencies) with statistical properties of the potential energy surface and wavefunctions. This marriage of molecular detail and statistical simplification captures trends of IVR mechanisms and survival probabilities beyond the abilities of purely statistical models or the computational limitations of full ab initio approaches. Of particular interest is IVR in the intermediate time regime, where heavy-atom skeletal modes take over the IVR process from hydrogenic motions even upon X H bond excitation. Experiments and calculations on prototype heavy-atom systems show that intermediate time IVR differs in many aspects from the early stages of hydrogenic mode IVR. As a result, IVR can be coherently frozen, with potential applications to selective chemistry.
ePMV embeds molecular modeling into professional animation software environments.
Johnson, Graham T; Autin, Ludovic; Goodsell, David S; Sanner, Michel F; Olson, Arthur J
2011-03-09
Increasingly complex research has made it more difficult to prepare data for publication, education, and outreach. Many scientists must also wade through black-box code to interface computational algorithms from diverse sources to supplement their bench work. To reduce these barriers we have developed an open-source plug-in, embedded Python Molecular Viewer (ePMV), that runs molecular modeling software directly inside of professional 3D animation applications (hosts) to provide simultaneous access to the capabilities of these newly connected systems. Uniting host and scientific algorithms into a single interface allows users from varied backgrounds to assemble professional quality visuals and to perform computational experiments with relative ease. By enabling easy exchange of algorithms, ePMV can facilitate interdisciplinary research, smooth communication between broadly diverse specialties, and provide a common platform to frame and visualize the increasingly detailed intersection(s) of cellular and molecular biology. Copyright © 2011 Elsevier Ltd. All rights reserved.
Recent Advances in Cardiac Computed Tomography: Dual Energy, Spectral and Molecular CT Imaging
Danad, Ibrahim; Fayad, Zahi A.; Willemink, Martin J.; Min, James K.
2015-01-01
Computed tomography (CT) evolved into a powerful diagnostic tool and it is impossible to imagine current clinical practice without CT imaging. Due to its widespread availability, ease of clinical application, superb sensitivity for detection of CAD, and non-invasive nature, CT has become a valuable tool within the armamentarium of the cardiologist. In the last few years, numerous technological advances in CT have occurred—including dual energy CT (DECT), spectral CT and CT-based molecular imaging. By harnessing the advances in technology, cardiac CT has advanced beyond the mere evaluation of coronary stenosis to an imaging modality tool that permits accurate plaque characterization, assessment of myocardial perfusion and even probing of molecular processes that are involved in coronary atherosclerosis. Novel innovations in CT contrast agents and pre-clinical spectral CT devices have paved the way for CT-based molecular imaging. PMID:26068288
ePMV Embeds Molecular Modeling into Professional Animation Software Environments
Johnson, Graham T.; Autin, Ludovic; Goodsell, David S.; Sanner, Michel F.; Olson, Arthur J.
2011-01-01
SUMMARY Increasingly complex research has made it more difficult to prepare data for publication, education, and outreach. Many scientists must also wade through black-box code to interface computational algorithms from diverse sources to supplement their bench work. To reduce these barriers, we have developed an open-source plug-in, embedded Python Molecular Viewer (ePMV), that runs molecular modeling software directly inside of professional 3D animation applications (hosts) to provide simultaneous access to the capabilities of these newly connected systems. Uniting host and scientific algorithms into a single interface allows users from varied backgrounds to assemble professional quality visuals and to perform computational experiments with relative ease. By enabling easy exchange of algorithms, ePMV can facilitate interdisciplinary research, smooth communication between broadly diverse specialties and provide a common platform to frame and visualize the increasingly detailed intersection(s) of cellular and molecular biology. PMID:21397181
Rodriguez, Alejandro; Canto, Josep; Corcho, Francesc J; Perez, Juan J
2009-01-01
The present report regards a computational study aimed at assessing the conformational profile of the four stereoisomers of the peptide Ace-Pro-c3Phe-NMe, previously reported to exhibit beta-turn structures in dichloromethane with different type I/type II beta-turn profiles. Molecular systems were represented at the molecular mechanics level using the parm96 parameterization of the AMBER force field. Calculations were carried out in dichloromethane using an implicit solvent approach. Characterization of the conformational features of the peptide analogs was carried out using simulated annealing (SA), molecular dynamics (MD) and replica exchange molecular dynamics (REMD). Present results show that MD calculations do not provide a reasonable sampling after 300 ns. In contrast, both SA and REMD provide similar results and agree well with experimental observations. Copyright 2009 Wiley Periodicals, Inc.
Comparative Investigation of Normal Modes and Molecular Dynamics of Hepatitis C NS5B Protein
NASA Astrophysics Data System (ADS)
Asafi, M. S.; Yildirim, A.; Tekpinar, M.
2016-04-01
Understanding dynamics of proteins has many practical implications in terms of finding a cure for many protein related diseases. Normal mode analysis and molecular dynamics methods are widely used physics-based computational methods for investigating dynamics of proteins. In this work, we studied dynamics of Hepatitis C NS5B protein with molecular dynamics and normal mode analysis. Principal components obtained from a 100 nanoseconds molecular dynamics simulation show good overlaps with normal modes calculated with a coarse-grained elastic network model. Coarse-grained normal mode analysis takes at least an order of magnitude shorter time. Encouraged by this good overlaps and short computation times, we analyzed further low frequency normal modes of Hepatitis C NS5B. Motion directions and average spatial fluctuations have been analyzed in detail. Finally, biological implications of these motions in drug design efforts against Hepatitis C infections have been elaborated.
Bardhan, Jaydeep P; Knepley, Matthew G; Anitescu, Mihai
2009-03-14
The importance of electrostatic interactions in molecular biology has driven extensive research toward the development of accurate and efficient theoretical and computational models. Linear continuum electrostatic theory has been surprisingly successful, but the computational costs associated with solving the associated partial differential equations (PDEs) preclude the theory's use in most dynamical simulations. Modern generalized-Born models for electrostatics can reproduce PDE-based calculations to within a few percent and are extremely computationally efficient but do not always faithfully reproduce interactions between chemical groups. Recent work has shown that a boundary-integral-equation formulation of the PDE problem leads naturally to a new approach called boundary-integral-based electrostatics estimation (BIBEE) to approximate electrostatic interactions. In the present paper, we prove that the BIBEE method can be used to rigorously bound the actual continuum-theory electrostatic free energy. The bounds are validated using a set of more than 600 proteins. Detailed numerical results are presented for structures of the peptide met-enkephalin taken from a molecular-dynamics simulation. These bounds, in combination with our demonstration that the BIBEE methods accurately reproduce pairwise interactions, suggest a new approach toward building a highly accurate yet computationally tractable electrostatic model.
Computational Approaches to Phenotyping
Lussier, Yves A.; Liu, Yang
2007-01-01
The recent completion of the Human Genome Project has made possible a high-throughput “systems approach” for accelerating the elucidation of molecular underpinnings of human diseases, and subsequent derivation of molecular-based strategies to more effectively prevent, diagnose, and treat these diseases. Although altered phenotypes are among the most reliable manifestations of altered gene functions, research using systematic analysis of phenotype relationships to study human biology is still in its infancy. This article focuses on the emerging field of high-throughput phenotyping (HTP) phenomics research, which aims to capitalize on novel high-throughput computation and informatics technology developments to derive genomewide molecular networks of genotype–phenotype associations, or “phenomic associations.” The HTP phenomics research field faces the challenge of technological research and development to generate novel tools in computation and informatics that will allow researchers to amass, access, integrate, organize, and manage phenotypic databases across species and enable genomewide analysis to associate phenotypic information with genomic data at different scales of biology. Key state-of-the-art technological advancements critical for HTP phenomics research are covered in this review. In particular, we highlight the power of computational approaches to conduct large-scale phenomics studies. PMID:17202287
Antioxidant behavior of mearnsetin and myricetin flavonoid compounds — A DFT study
NASA Astrophysics Data System (ADS)
Sadasivam, K.; Kumaresan, R.
2011-06-01
The molecular characteristics of two naturally occurring flavonoid compounds mearnsetin and myricetin have been computed using density functional theory (DFT) approach with B3LYP/6-311G(d,p) level of theory. The computation and analysis of bond dissociation enthalpy magnitudes for all the OH sites for both the compounds clearly denotes the contribution of the B-ring for the antioxidant activity. The analysis has also indicated the higher values of BDE on the C5-OH radical species in both the compounds. The computed vibrational frequency analysis indicates the absence of imaginary frequency in the neutral as well as radical species of both the flavonoid compounds. The ionisation potential (IP) analysis was found to be within the range of the IP of synthetic food additives. In addition, various molecular descriptors such as electron affinity, hardness, softness, electronegativity, electrophilic index have also been calculated and the validity of Koopman's theorem is verified. The plot of frontier molecular orbital and spin density distribution analysis for neutral and the corresponding radical species for both the compounds have been computed and interpreted. The polar nature and their polarizing capacity are well established through the analysis of dipole moment and polarisability magnitudes.
NASA Astrophysics Data System (ADS)
Bardhan, Jaydeep P.; Knepley, Matthew G.; Anitescu, Mihai
2009-03-01
The importance of electrostatic interactions in molecular biology has driven extensive research toward the development of accurate and efficient theoretical and computational models. Linear continuum electrostatic theory has been surprisingly successful, but the computational costs associated with solving the associated partial differential equations (PDEs) preclude the theory's use in most dynamical simulations. Modern generalized-Born models for electrostatics can reproduce PDE-based calculations to within a few percent and are extremely computationally efficient but do not always faithfully reproduce interactions between chemical groups. Recent work has shown that a boundary-integral-equation formulation of the PDE problem leads naturally to a new approach called boundary-integral-based electrostatics estimation (BIBEE) to approximate electrostatic interactions. In the present paper, we prove that the BIBEE method can be used to rigorously bound the actual continuum-theory electrostatic free energy. The bounds are validated using a set of more than 600 proteins. Detailed numerical results are presented for structures of the peptide met-enkephalin taken from a molecular-dynamics simulation. These bounds, in combination with our demonstration that the BIBEE methods accurately reproduce pairwise interactions, suggest a new approach toward building a highly accurate yet computationally tractable electrostatic model.
Accurate Evaluation Method of Molecular Binding Affinity from Fluctuation Frequency
NASA Astrophysics Data System (ADS)
Hoshino, Tyuji; Iwamoto, Koji; Ode, Hirotaka; Ohdomari, Iwao
2008-05-01
Exact estimation of the molecular binding affinity is significantly important for drug discovery. The energy calculation is a direct method to compute the strength of the interaction between two molecules. This energetic approach is, however, not accurate enough to evaluate a slight difference in binding affinity when distinguishing a prospective substance from dozens of candidates for medicine. Hence more accurate estimation of drug efficacy in a computer is currently demanded. Previously we proposed a concept of estimating molecular binding affinity, focusing on the fluctuation at an interface between two molecules. The aim of this paper is to demonstrate the compatibility between the proposed computational technique and experimental measurements, through several examples for computer simulations of an association of human immunodeficiency virus type-1 (HIV-1) protease and its inhibitor (an example for a drug-enzyme binding), a complexation of an antigen and its antibody (an example for a protein-protein binding), and a combination of estrogen receptor and its ligand chemicals (an example for a ligand-receptor binding). The proposed affinity estimation has proven to be a promising technique in the advanced stage of the discovery and the design of drugs.
Arooj, Mahreen; Thangapandian, Sundarapandian; John, Shalini; Hwang, Swan; Park, Jong K; Lee, Keun W
2012-12-01
To provide a new idea for drug design, a computational investigation is performed on chymase and its novel 1,4-diazepane-2,5-diones inhibitors that explores the crucial molecular features contributing to binding specificity. Molecular docking studies of inhibitors within the active site of chymase were carried out to rationalize the inhibitory properties of these compounds and understand their inhibition mechanism. The density functional theory method was used to optimize molecular structures with the subsequent analysis of highest occupied molecular orbital, lowest unoccupied molecular orbital, and molecular electrostatic potential maps, which revealed that negative potentials near 1,4-diazepane-2,5-diones ring are essential for effective binding of inhibitors at active site of enzyme. The Bayesian model with receiver operating curve statistic of 0.82 also identified arylsulfonyl and aminocarbonyl as the molecular features favoring and not favoring inhibition of chymase, respectively. Moreover, genetic function approximation was applied to construct 3D quantitative structure-activity relationships models. Two models (genetic function approximation model 1 r(2) = 0.812 and genetic function approximation model 2 r(2) = 0.783) performed better in terms of correlation coefficients and cross-validation analysis. In general, this study is used as example to illustrate how combinational use of 2D/3D quantitative structure-activity relationships modeling techniques, molecular docking, frontier molecular orbital density fields (highest occupied molecular orbital and lowest unoccupied molecular orbital), and molecular electrostatic potential analysis may be useful to gain an insight into the binding mechanism between enzyme and its inhibitors. © 2012 John Wiley & Sons A/S.
Biomolecular electrostatics and solvation: a computational perspective
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ren, Pengyu; Chun, Jaehun; Thomas, Dennis G.
2012-11-01
An understanding of molecular interactions is essential for insight into biological systems at the molecular scale. Among the various components of molecular interactions, electrostatics are of special importance because of their long-range nature and their influence on polar or charged molecules, including water, aqueous ions, proteins, nucleic acids, carbohydrates, and membrane lipids. In particular, robust models of electrostatic interactions are essential for understanding the solvation properties of biomolecules and the effects of solvation upon biomolecular folding, binding, enzyme catalysis and dynamics. Electrostatics, therefore, are of central importance to understanding biomolecular structure and modeling interactions within and among biological molecules. Thismore » review discusses the solvation of biomolecules with a computational biophysics view towards describing the phenomenon. While our main focus lies on the computational aspect of the models, we summarize the common characteristics of biomolecular solvation (e.g., solvent structure, polarization, ion binding, and nonpolar behavior) in order to provide reasonable backgrounds to understand the solvation models.« less
Molecular dynamics simulations in hybrid particle-continuum schemes: Pitfalls and caveats
NASA Astrophysics Data System (ADS)
Stalter, S.; Yelash, L.; Emamy, N.; Statt, A.; Hanke, M.; Lukáčová-Medvid'ová, M.; Virnau, P.
2018-03-01
Heterogeneous multiscale methods (HMM) combine molecular accuracy of particle-based simulations with the computational efficiency of continuum descriptions to model flow in soft matter liquids. In these schemes, molecular simulations typically pose a computational bottleneck, which we investigate in detail in this study. We find that it is preferable to simulate many small systems as opposed to a few large systems, and that a choice of a simple isokinetic thermostat is typically sufficient while thermostats such as Lowe-Andersen allow for simulations at elevated viscosity. We discuss suitable choices for time steps and finite-size effects which arise in the limit of very small simulation boxes. We also argue that if colloidal systems are considered as opposed to atomistic systems, the gap between microscopic and macroscopic simulations regarding time and length scales is significantly smaller. We propose a novel reduced-order technique for the coupling to the macroscopic solver, which allows us to approximate a non-linear stress-strain relation efficiently and thus further reduce computational effort of microscopic simulations.
Thermodynamics of Hydrophobic Amino Acids in Solution: A Combined Experimental–Computational Study
Song, Lingshuang; Yang, Lin; Meng, Jie; ...
2016-12-29
Here, we present a joint experimental-computational study to quantitatively describe the thermodynamics of hydrophobic leucine amino acids in aqueous solution. X-ray scattering data were acquired at a series of solute and salt concentrations to effectively measure inter-leucine interactions, indicating that a major scattering peak is observed consistently at q = 0.83 Å -1. Atomistic molecular dynamics simulations were then performed and compared with the scattering data, achieving high consistency at both small and wider scattering angles (q = 0$-$1.5 Å -1). This experimental-computational consistence enables a first glimpse of the leucineleucine interacting landscape, where two leucine molecules are aligned mostlymore » in a parallel fashion, as opposed to anti-parallel, but also allows us to derive effective leucine-leucine interactions in solution. Collectively, this combined approach of employing experimental scattering and molecular simulation enables a quantitative characterization on effective inter-molecular interactions of hydrophobic amino acids, critical for protein function and dynamics such as protein folding.« less
Dreuw, Andreas
2006-11-13
With the advent of modern computers and advances in the development of efficient quantum chemical computer codes, the meaningful computation of large molecular systems at a quantum mechanical level became feasible. Recent experimental effort to understand photoinitiated processes in biological systems, for instance photosynthesis or vision, at a molecular level also triggered theoretical investigations in this field. In this Minireview, standard quantum chemical methods are presented that are applicable and recently used for the calculation of excited states of photoinitiated processes in biological molecular systems. These methods comprise configuration interaction singles, the complete active space self-consistent field method, and time-dependent density functional theory and its variants. Semiempirical approaches are also covered. Their basic theoretical concepts and mathematical equations are briefly outlined, and their properties and limitations are discussed. Recent successful applications of the methods to photoinitiated processes in biological systems are described and theoretical tools for the analysis of excited states are presented.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Iwasa, Takeshi, E-mail: tiwasa@mail.sci.hokudai.ac.jp; Takenaka, Masato; Taketsugu, Tetsuya
A theoretical method to compute infrared absorption spectra when a molecule is interacting with an arbitrary nonuniform electric field such as near-fields is developed and numerically applied to simple model systems. The method is based on the multipolar Hamiltonian where the light-matter interaction is described by a spatial integral of the inner product of the molecular polarization and applied electric field. The computation scheme is developed under the harmonic approximation for the molecular vibrations and the framework of modern electronic structure calculations such as the density functional theory. Infrared reflection absorption and near-field infrared absorption are considered as model systems.more » The obtained IR spectra successfully reflect the spatial structure of the applied electric field and corresponding vibrational modes, demonstrating applicability of the present method to analyze modern nanovibrational spectroscopy using near-fields. The present method can use arbitral electric fields and thus can integrate two fields such as computational chemistry and electromagnetics.« less
Iwasa, Takeshi; Takenaka, Masato; Taketsugu, Tetsuya
2016-03-28
A theoretical method to compute infrared absorption spectra when a molecule is interacting with an arbitrary nonuniform electric field such as near-fields is developed and numerically applied to simple model systems. The method is based on the multipolar Hamiltonian where the light-matter interaction is described by a spatial integral of the inner product of the molecular polarization and applied electric field. The computation scheme is developed under the harmonic approximation for the molecular vibrations and the framework of modern electronic structure calculations such as the density functional theory. Infrared reflection absorption and near-field infrared absorption are considered as model systems. The obtained IR spectra successfully reflect the spatial structure of the applied electric field and corresponding vibrational modes, demonstrating applicability of the present method to analyze modern nanovibrational spectroscopy using near-fields. The present method can use arbitral electric fields and thus can integrate two fields such as computational chemistry and electromagnetics.
Towards the simulation of molecular collisions with a superconducting quantum computer
NASA Astrophysics Data System (ADS)
Geller, Michael
2013-05-01
I will discuss the prospects for the use of large-scale, error-corrected quantum computers to simulate complex quantum dynamics such as molecular collisions. This will likely require millions qubits. I will also discuss an alternative approach [M. R. Geller et al., arXiv:1210.5260] that is ideally suited for today's superconducting circuits, which uses the single-excitation subspace (SES) of a system of n tunably coupled qubits. The SES method allows many operations in the unitary group SU(n) to be implemented in a single step, bypassing the need for elementary gates, thereby making large computations possible without error correction. The method enables universal quantum simulation, including simulation of the time-dependent Schrodinger equation, and we argue that a 1000-qubit SES processor should be capable of achieving quantum speedup relative to a petaflop supercomputer. We speculate on the utility and practicality of such a simulator for atomic and molecular collision physics. Work supported by the US National Science Foundation CDI program.
Thermodynamics of Hydrophobic Amino Acids in Solution: A Combined Experimental–Computational Study
DOE Office of Scientific and Technical Information (OSTI.GOV)
Song, Lingshuang; Yang, Lin; Meng, Jie
Here, we present a joint experimental-computational study to quantitatively describe the thermodynamics of hydrophobic leucine amino acids in aqueous solution. X-ray scattering data were acquired at a series of solute and salt concentrations to effectively measure inter-leucine interactions, indicating that a major scattering peak is observed consistently at q = 0.83 Å -1. Atomistic molecular dynamics simulations were then performed and compared with the scattering data, achieving high consistency at both small and wider scattering angles (q = 0$-$1.5 Å -1). This experimental-computational consistence enables a first glimpse of the leucineleucine interacting landscape, where two leucine molecules are aligned mostlymore » in a parallel fashion, as opposed to anti-parallel, but also allows us to derive effective leucine-leucine interactions in solution. Collectively, this combined approach of employing experimental scattering and molecular simulation enables a quantitative characterization on effective inter-molecular interactions of hydrophobic amino acids, critical for protein function and dynamics such as protein folding.« less
Tawhai, M. H.; Clark, A. R.; Donovan, G. M.; Burrowes, K. S.
2011-01-01
Computational models of lung structure and function necessarily span multiple spatial and temporal scales, i.e., dynamic molecular interactions give rise to whole organ function, and the link between these scales cannot be fully understood if only molecular or organ-level function is considered. Here, we review progress in constructing multiscale finite element models of lung structure and function that are aimed at providing a computational framework for bridging the spatial scales from molecular to whole organ. These include structural models of the intact lung, embedded models of the pulmonary airways that couple to model lung tissue, and models of the pulmonary vasculature that account for distinct structural differences at the extra- and intra-acinar levels. Biophysically based functional models for tissue deformation, pulmonary blood flow, and airway bronchoconstriction are also described. The development of these advanced multiscale models has led to a better understanding of complex physiological mechanisms that govern regional lung perfusion and emergent heterogeneity during bronchoconstriction. PMID:22011236
Biomolecular electrostatics and solvation: a computational perspective
Ren, Pengyu; Chun, Jaehun; Thomas, Dennis G.; Schnieders, Michael J.; Marucho, Marcelo; Zhang, Jiajing; Baker, Nathan A.
2012-01-01
An understanding of molecular interactions is essential for insight into biological systems at the molecular scale. Among the various components of molecular interactions, electrostatics are of special importance because of their long-range nature and their influence on polar or charged molecules, including water, aqueous ions, proteins, nucleic acids, carbohydrates, and membrane lipids. In particular, robust models of electrostatic interactions are essential for understanding the solvation properties of biomolecules and the effects of solvation upon biomolecular folding, binding, enzyme catalysis, and dynamics. Electrostatics, therefore, are of central importance to understanding biomolecular structure and modeling interactions within and among biological molecules. This review discusses the solvation of biomolecules with a computational biophysics view towards describing the phenomenon. While our main focus lies on the computational aspect of the models, we provide an overview of the basic elements of biomolecular solvation (e.g., solvent structure, polarization, ion binding, and nonpolar behavior) in order to provide a background to understand the different types of solvation models. PMID:23217364
Biomolecular electrostatics and solvation: a computational perspective.
Ren, Pengyu; Chun, Jaehun; Thomas, Dennis G; Schnieders, Michael J; Marucho, Marcelo; Zhang, Jiajing; Baker, Nathan A
2012-11-01
An understanding of molecular interactions is essential for insight into biological systems at the molecular scale. Among the various components of molecular interactions, electrostatics are of special importance because of their long-range nature and their influence on polar or charged molecules, including water, aqueous ions, proteins, nucleic acids, carbohydrates, and membrane lipids. In particular, robust models of electrostatic interactions are essential for understanding the solvation properties of biomolecules and the effects of solvation upon biomolecular folding, binding, enzyme catalysis, and dynamics. Electrostatics, therefore, are of central importance to understanding biomolecular structure and modeling interactions within and among biological molecules. This review discusses the solvation of biomolecules with a computational biophysics view toward describing the phenomenon. While our main focus lies on the computational aspect of the models, we provide an overview of the basic elements of biomolecular solvation (e.g. solvent structure, polarization, ion binding, and non-polar behavior) in order to provide a background to understand the different types of solvation models.
Salvalaglio, Matteo; Tiwary, Pratyush; Maggioni, Giovanni Maria; Mazzotti, Marco; Parrinello, Michele
2016-12-07
Condensation of a liquid droplet from a supersaturated vapour phase is initiated by a prototypical nucleation event. As such it is challenging to compute its rate from atomistic molecular dynamics simulations. In fact at realistic supersaturation conditions condensation occurs on time scales that far exceed what can be reached with conventional molecular dynamics methods. Another known problem in this context is the distortion of the free energy profile associated to nucleation due to the small, finite size of typical simulation boxes. In this work the problem of time scale is addressed with a recently developed enhanced sampling method while contextually correcting for finite size effects. We demonstrate our approach by studying the condensation of argon, and showing that characteristic nucleation times of the order of magnitude of hours can be reliably calculated. Nucleation rates spanning a range of 10 orders of magnitude are computed at moderate supersaturation levels, thus bridging the gap between what standard molecular dynamics simulations can do and real physical systems.
Using computer-aided drug design and medicinal chemistry strategies in the fight against diabetes.
Semighini, Evandro P; Resende, Jonathan A; de Andrade, Peterson; Morais, Pedro A B; Carvalho, Ivone; Taft, Carlton A; Silva, Carlos H T P
2011-04-01
The aim of this work is to present a simple, practical and efficient protocol for drug design, in particular Diabetes, which includes selection of the illness, good choice of a target as well as a bioactive ligand and then usage of various computer aided drug design and medicinal chemistry tools to design novel potential drug candidates in different diseases. We have selected the validated target dipeptidyl peptidase IV (DPP-IV), whose inhibition contributes to reduce glucose levels in type 2 diabetes patients. The most active inhibitor with complex X-ray structure reported was initially extracted from the BindingDB database. By using molecular modification strategies widely used in medicinal chemistry, besides current state-of-the-art tools in drug design (including flexible docking, virtual screening, molecular interaction fields, molecular dynamics, ADME and toxicity predictions), we have proposed 4 novel potential DPP-IV inhibitors with drug properties for Diabetes control, which have been supported and validated by all the computational tools used herewith.
Pouthier, Vincent
2012-11-07
A communication protocol is proposed in which vibron-mediated quantum state transfer takes place in a molecular lattice. We consider two distant molecular groups grafted on each side of the lattice. These groups form two quantum computers where vibrational qubits are implemented and received. The lattice defines the communication channel along which a vibron delocalizes and interacts with a phonon bath. Using quasi-degenerate perturbation theory, vibron-phonon entanglement is taken into account through the effective Hamiltonian concept. A vibron is thus dressed by a virtual phonon cloud whereas a phonon is clothed by virtual vibronic transitions. It is shown that three quasi-degenerate dressed states define the relevant paths followed by a vibron to tunnel between the computers. When the coupling between the computers and the lattice is judiciously chosen, constructive interference takes place between these paths. Phonon-induced decoherence is minimized and a high-fidelity quantum state transfer occurs over a broad temperature range.
NASA Astrophysics Data System (ADS)
Salvalaglio, Matteo; Tiwary, Pratyush; Maggioni, Giovanni Maria; Mazzotti, Marco; Parrinello, Michele
2016-12-01
Condensation of a liquid droplet from a supersaturated vapour phase is initiated by a prototypical nucleation event. As such it is challenging to compute its rate from atomistic molecular dynamics simulations. In fact at realistic supersaturation conditions condensation occurs on time scales that far exceed what can be reached with conventional molecular dynamics methods. Another known problem in this context is the distortion of the free energy profile associated to nucleation due to the small, finite size of typical simulation boxes. In this work the problem of time scale is addressed with a recently developed enhanced sampling method while contextually correcting for finite size effects. We demonstrate our approach by studying the condensation of argon, and showing that characteristic nucleation times of the order of magnitude of hours can be reliably calculated. Nucleation rates spanning a range of 10 orders of magnitude are computed at moderate supersaturation levels, thus bridging the gap between what standard molecular dynamics simulations can do and real physical systems.
Łazarski, Roman; Burow, Asbjörn Manfred; Grajciar, Lukáš; Sierka, Marek
2016-10-30
A full implementation of analytical energy gradients for molecular and periodic systems is reported in the TURBOMOLE program package within the framework of Kohn-Sham density functional theory using Gaussian-type orbitals as basis functions. Its key component is a combination of density fitting (DF) approximation and continuous fast multipole method (CFMM) that allows for an efficient calculation of the Coulomb energy gradient. For exchange-correlation part the hierarchical numerical integration scheme (Burow and Sierka, Journal of Chemical Theory and Computation 2011, 7, 3097) is extended to energy gradients. Computational efficiency and asymptotic O(N) scaling behavior of the implementation is demonstrated for various molecular and periodic model systems, with the largest unit cell of hematite containing 640 atoms and 19,072 basis functions. The overall computational effort of energy gradient is comparable to that of the Kohn-Sham matrix formation. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
ChemoPy: freely available python package for computational biology and chemoinformatics.
Cao, Dong-Sheng; Xu, Qing-Song; Hu, Qian-Nan; Liang, Yi-Zeng
2013-04-15
Molecular representation for small molecules has been routinely used in QSAR/SAR, virtual screening, database search, ranking, drug ADME/T prediction and other drug discovery processes. To facilitate extensive studies of drug molecules, we developed a freely available, open-source python package called chemoinformatics in python (ChemoPy) for calculating the commonly used structural and physicochemical features. It computes 16 drug feature groups composed of 19 descriptors that include 1135 descriptor values. In addition, it provides seven types of molecular fingerprint systems for drug molecules, including topological fingerprints, electro-topological state (E-state) fingerprints, MACCS keys, FP4 keys, atom pairs fingerprints, topological torsion fingerprints and Morgan/circular fingerprints. By applying a semi-empirical quantum chemistry program MOPAC, ChemoPy can also compute a large number of 3D molecular descriptors conveniently. The python package, ChemoPy, is freely available via http://code.google.com/p/pychem/downloads/list, and it runs on Linux and MS-Windows. Supplementary data are available at Bioinformatics online.
Nasrabad, Afshin Eskandari; Laghaei, Rozita; Eu, Byung Chan
2005-04-28
In previous work on the density fluctuation theory of transport coefficients of liquids, it was necessary to use empirical self-diffusion coefficients to calculate the transport coefficients (e.g., shear viscosity of carbon dioxide). In this work, the necessity of empirical input of the self-diffusion coefficients in the calculation of shear viscosity is removed, and the theory is thus made a self-contained molecular theory of transport coefficients of liquids, albeit it contains an empirical parameter in the subcritical regime. The required self-diffusion coefficients of liquid carbon dioxide are calculated by using the modified free volume theory for which the generic van der Waals equation of state and Monte Carlo simulations are combined to accurately compute the mean free volume by means of statistical mechanics. They have been computed as a function of density along four different isotherms and isobars. A Lennard-Jones site-site interaction potential was used to model the molecular carbon dioxide interaction. The density and temperature dependence of the theoretical self-diffusion coefficients are shown to be in excellent agreement with experimental data when the minimum critical free volume is identified with the molecular volume. The self-diffusion coefficients thus computed are then used to compute the density and temperature dependence of the shear viscosity of liquid carbon dioxide by employing the density fluctuation theory formula for shear viscosity as reported in an earlier paper (J. Chem. Phys. 2000, 112, 7118). The theoretical shear viscosity is shown to be robust and yields excellent density and temperature dependence for carbon dioxide. The pair correlation function appearing in the theory has been computed by Monte Carlo simulations.
Algorithms of GPU-enabled reactive force field (ReaxFF) molecular dynamics.
Zheng, Mo; Li, Xiaoxia; Guo, Li
2013-04-01
Reactive force field (ReaxFF), a recent and novel bond order potential, allows for reactive molecular dynamics (ReaxFF MD) simulations for modeling larger and more complex molecular systems involving chemical reactions when compared with computation intensive quantum mechanical methods. However, ReaxFF MD can be approximately 10-50 times slower than classical MD due to its explicit modeling of bond forming and breaking, the dynamic charge equilibration at each time-step, and its one order smaller time-step than the classical MD, all of which pose significant computational challenges in simulation capability to reach spatio-temporal scales of nanometers and nanoseconds. The very recent advances of graphics processing unit (GPU) provide not only highly favorable performance for GPU enabled MD programs compared with CPU implementations but also an opportunity to manage with the computing power and memory demanding nature imposed on computer hardware by ReaxFF MD. In this paper, we present the algorithms of GMD-Reax, the first GPU enabled ReaxFF MD program with significantly improved performance surpassing CPU implementations on desktop workstations. The performance of GMD-Reax has been benchmarked on a PC equipped with a NVIDIA C2050 GPU for coal pyrolysis simulation systems with atoms ranging from 1378 to 27,283. GMD-Reax achieved speedups as high as 12 times faster than Duin et al.'s FORTRAN codes in Lammps on 8 CPU cores and 6 times faster than the Lammps' C codes based on PuReMD in terms of the simulation time per time-step averaged over 100 steps. GMD-Reax could be used as a new and efficient computational tool for exploiting very complex molecular reactions via ReaxFF MD simulation on desktop workstations. Copyright © 2013 Elsevier Inc. All rights reserved.
CARES/LIFE Software Commercialization
NASA Technical Reports Server (NTRS)
1995-01-01
The NASA Lewis Research Center has entered into a letter agreement with BIOSYM Technologies Inc. (now merged with Molecular Simulations Inc. (MSI)). Under this agreement, NASA will provide a developmental copy of the CARES/LIFE computer program to BIOSYM for evaluation. This computer code predicts the time-dependent reliability of a thermomechanically loaded component. BIOSYM will become familiar with CARES/LIFE, provide results of computations useful in validating the code, evaluate it for potential commercialization, and submit suggestions for improvements or extensions to the code or its documentation. If BIOSYM/Molecular Simulations reaches a favorable evaluation of CARES/LIFE, NASA will enter into negotiations for a cooperative agreement with BIOSYM/Molecular Simulations to further develop the code--adding features such as a user-friendly interface and other improvements. This agreement would give BIOSYM intellectual property rights in the modified codes, which they could protect and then commercialize. NASA would provide BIOSYM with the NASA-developed source codes and would agree to cooperate with BIOSYM in further developing the code. In return, NASA would receive certain use rights in the modified CARES/LIFE program. Presently BIOSYM Technologies Inc. has been involved with integration issues concerning its merger with Molecular Simulations Inc., since both companies used to compete in the computational chemistry market, and to some degree, in the materials market. Consequently, evaluation of the CARES/LIFE software is on hold for a month or two while the merger is finalized. Their interest in CARES continues, however, and they expect to get back to the evaluation by early November 1995.
Computation of Dielectric Response in Molecular Solids for High Capacitance Organic Dielectrics.
Heitzer, Henry M; Marks, Tobin J; Ratner, Mark A
2016-09-20
The dielectric response of a material is central to numerous processes spanning the fields of chemistry, materials science, biology, and physics. Despite this broad importance across these disciplines, describing the dielectric environment of a molecular system at the level of first-principles theory and computation remains a great challenge and is of importance to understand the behavior of existing systems as well as to guide the design and synthetic realization of new ones. Furthermore, with recent advances in molecular electronics, nanotechnology, and molecular biology, it has become necessary to predict the dielectric properties of molecular systems that are often difficult or impossible to measure experimentally. In these scenarios, it is would be highly desirable to be able to determine dielectric response through efficient, accurate, and chemically informative calculations. A good example of where theoretical modeling of dielectric response would be valuable is in the development of high-capacitance organic gate dielectrics for unconventional electronics such as those that could be fabricated by high-throughput printing techniques. Gate dielectrics are fundamental components of all transistor-based logic circuitry, and the combination high dielectric constant and nanoscopic thickness (i.e., high capacitance) is essential to achieving high switching speeds and low power consumption. Molecule-based dielectrics offer the promise of cheap, flexible, and mass producible electronics when used in conjunction with unconventional organic or inorganic semiconducting materials to fabricate organic field effect transistors (OFETs). The molecular dielectrics developed to date typically have limited dielectric response, which results in low capacitances, translating into poor performance of the resulting OFETs. Furthermore, the development of better performing dielectric materials has been hindered by the current highly empirical and labor-intensive pace of synthetic progress. An accurate and efficient theoretical computational approach could drastically decrease this time by screening potential dielectric materials and providing reliable design rules for future molecular dielectrics. Until recently, accurate calculation of dielectric responses in molecular materials was difficult and highly approximate. Most previous modeling efforts relied on classical formalisms to relate molecular polarizability to macroscopic dielectric properties. These efforts often vastly overestimated polarizability in the subject materials and ignored crucial material properties that can affect dielectric response. Recent advances in first-principles calculations via density functional theory (DFT) with periodic boundary conditions have allowed accurate computation of dielectric properties in molecular materials. In this Account, we outline the methodology used to calculate dielectric properties of molecular materials. We demonstrate the validity of this approach on model systems, capturing the frequency dependence of the dielectric response and achieving quantitative accuracy compared with experiment. This method is then used as a guide to new high-capacitance molecular dielectrics by determining what materials and chemical properties are important in maximizing dielectric response in self-assembled monolayers (SAMs). It will be seen that this technique is a powerful tool for understanding and designing new molecular dielectric systems, the properties of which are fundamental to many scientific areas.
Serohijos, Adrian W.R.; Shakhnovich, Eugene I.
2014-01-01
The variation among sequences and structures in nature is both determined by physical laws and by evolutionary history. However, these two factors are traditionally investigated by disciplines with different emphasis and philosophy—molecular biophysics on one hand and evolutionary population genetics in another. Here, we review recent theoretical and computational approaches that address the critical need to integrate these two disciplines. We first articulate the elements of these integrated approaches. Then, we survey their contribution to our mechanistic understanding of molecular evolution, the polymorphisms in coding region, the distribution of fitness effects (DFE) of mutations, the observed folding stability of proteins in nature, and the distribution of protein folds in genomes. PMID:24952216
Serohijos, Adrian W R; Shakhnovich, Eugene I
2014-06-01
The variation among sequences and structures in nature is both determined by physical laws and by evolutionary history. However, these two factors are traditionally investigated by disciplines with different emphasis and philosophy-molecular biophysics on one hand and evolutionary population genetics in another. Here, we review recent theoretical and computational approaches that address the crucial need to integrate these two disciplines. We first articulate the elements of these approaches. Then, we survey their contribution to our mechanistic understanding of molecular evolution, the polymorphisms in coding region, the distribution of fitness effects (DFE) of mutations, the observed folding stability of proteins in nature, and the distribution of protein folds in genomes. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Sokalski, W. A.; Shibata, M.; Ornstein, R. L.; Rein, R.
1993-01-01
Distributed Point Charge Models (PCM) for CO, (H2O)2, and HS-SH molecules have been computed from analytical expressions using multi-center multipole moments. The point charges (set of charges including both atomic and non-atomic positions) exactly reproduce both molecular and segmental multipole moments, thus constituting an accurate representation of the local anisotropy of electrostatic properties. In contrast to other known point charge models, PCM can be used to calculate not only intermolecular, but also intramolecular interactions. Comparison of these results with more accurate calculations demonstrated that PCM can correctly represent both weak and strong (intramolecular) interactions, thus indicating the merit of extending PCM to obtain improved potentials for molecular mechanics and molecular dynamics computational methods.
NASA Technical Reports Server (NTRS)
Romere, P. O.
1982-01-01
A proposed configuration for a Space Operations Center is presented in its eight stages of buildup. The on orbit aerodynamic force and moment characteristics were calculated for each stage based upon free molecular flow theory. Calculation of the aerodynamic characteristics was accomplished through the use of an orbital aerodynamic computer program, and the computation method is described with respect to the free molecular theory used. The aerodynamic characteristics are presented in tabulated form for each buildup stage at angles of attack from 0 to 360 degrees and roll angles from -60 to +60 degrees. The reference altitude is 490 kilometers, however, the data should be applicable for altitudes below 490 kilometers down to approximately 185 kilometers.
NASA Astrophysics Data System (ADS)
Feldt, Jonas; Miranda, Sebastião; Pratas, Frederico; Roma, Nuno; Tomás, Pedro; Mata, Ricardo A.
2017-12-01
In this work, we present an optimized perturbative quantum mechanics/molecular mechanics (QM/MM) method for use in Metropolis Monte Carlo simulations. The model adopted is particularly tailored for the simulation of molecular systems in solution but can be readily extended to other applications, such as catalysis in enzymatic environments. The electrostatic coupling between the QM and MM systems is simplified by applying perturbation theory to estimate the energy changes caused by a movement in the MM system. This approximation, together with the effective use of GPU acceleration, leads to a negligible added computational cost for the sampling of the environment. Benchmark calculations are carried out to evaluate the impact of the approximations applied and the overall computational performance.
Wang, Zhaocai; Pu, Jun; Cao, Liling; Tan, Jian
2015-10-23
The unbalanced assignment problem (UAP) is to optimally resolve the problem of assigning n jobs to m individuals (m < n), such that minimum cost or maximum profit obtained. It is a vitally important Non-deterministic Polynomial (NP) complete problem in operation management and applied mathematics, having numerous real life applications. In this paper, we present a new parallel DNA algorithm for solving the unbalanced assignment problem using DNA molecular operations. We reasonably design flexible-length DNA strands representing different jobs and individuals, take appropriate steps, and get the solutions of the UAP in the proper length range and O(mn) time. We extend the application of DNA molecular operations and simultaneity to simplify the complexity of the computation.
Feldt, Jonas; Miranda, Sebastião; Pratas, Frederico; Roma, Nuno; Tomás, Pedro; Mata, Ricardo A
2017-12-28
In this work, we present an optimized perturbative quantum mechanics/molecular mechanics (QM/MM) method for use in Metropolis Monte Carlo simulations. The model adopted is particularly tailored for the simulation of molecular systems in solution but can be readily extended to other applications, such as catalysis in enzymatic environments. The electrostatic coupling between the QM and MM systems is simplified by applying perturbation theory to estimate the energy changes caused by a movement in the MM system. This approximation, together with the effective use of GPU acceleration, leads to a negligible added computational cost for the sampling of the environment. Benchmark calculations are carried out to evaluate the impact of the approximations applied and the overall computational performance.
Computer Series, 114: MO Theory Made Visible.
ERIC Educational Resources Information Center
Mealli, Carlo; Proserpio, Davide M.
1990-01-01
A collection of Molecular Orbital (MO) programs that have been integrated into routines and programs to illustrate MO theory are presented. Included are discussions of Computer Aided Composition of Atomic Orbitals (CACAO) and Walsh diagrams. (CW)
This commentary provides an overview of the challenges that arise from applying molecular modeling tools developed and commonly used for pharmaceutical discovery to the problem of predicting the potential toxicities of environmental chemicals.
Protocols Utilizing Constant pH Molecular Dynamics to Compute pH-Dependent Binding Free Energies
2015-01-01
In protein–ligand binding, the electrostatic environments of the two binding partners may vary significantly in bound and unbound states, which may lead to protonation changes upon binding. In cases where ligand binding results in a net uptake or release of protons, the free energy of binding is pH-dependent. Nevertheless, conventional free energy calculations and molecular docking protocols typically do not rigorously account for changes in protonation that may occur upon ligand binding. To address these shortcomings, we present a simple methodology based on Wyman’s binding polynomial formalism to account for the pH dependence of binding free energies and demonstrate its use on cucurbit[7]uril (CB[7]) host–guest systems. Using constant pH molecular dynamics and a reference binding free energy that is taken either from experiment or from thermodynamic integration computations, the pH-dependent binding free energy is determined. This computational protocol accurately captures the large pKa shifts observed experimentally upon CB[7]:guest association and reproduces experimental binding free energies at different levels of pH. We show that incorrect assignment of fixed protonation states in free energy computations can give errors of >2 kcal/mol in these host–guest systems. Use of the methods presented here avoids such errors, thus suggesting their utility in computing proton-linked binding free energies for protein–ligand complexes. PMID:25134690
Parsing partial molar volumes of small molecules: a molecular dynamics study.
Patel, Nisha; Dubins, David N; Pomès, Régis; Chalikian, Tigran V
2011-04-28
We used molecular dynamics (MD) simulations in conjunction with the Kirkwood-Buff theory to compute the partial molar volumes for a number of small solutes of various chemical natures. We repeated our computations using modified pair potentials, first, in the absence of the Coulombic term and, second, in the absence of the Coulombic and the attractive Lennard-Jones terms. Comparison of our results with experimental data and the volumetric results of Monte Carlo simulation with hard sphere potentials and scaled particle theory-based computations led us to conclude that, for small solutes, the partial molar volume computed with the Lennard-Jones potential in the absence of the Coulombic term nearly coincides with the cavity volume. On the other hand, MD simulations carried out with the pair interaction potentials containing only the repulsive Lennard-Jones term produce unrealistically large partial molar volumes of solutes that are close to their excluded volumes. Our simulation results are in good agreement with the reported schemes for parsing partial molar volume data on small solutes. In particular, our determined interaction volumes() and the thickness of the thermal volume for individual compounds are in good agreement with empirical estimates. This work is the first computational study that supports and lends credence to the practical algorithms of parsing partial molar volume data that are currently in use for molecular interpretations of volumetric data.
A Scalable O(N) Algorithm for Large-Scale Parallel First-Principles Molecular Dynamics Simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Osei-Kuffuor, Daniel; Fattebert, Jean-Luc
2014-01-01
Traditional algorithms for first-principles molecular dynamics (FPMD) simulations only gain a modest capability increase from current petascale computers, due to their O(N 3) complexity and their heavy use of global communications. To address this issue, we are developing a truly scalable O(N) complexity FPMD algorithm, based on density functional theory (DFT), which avoids global communications. The computational model uses a general nonorthogonal orbital formulation for the DFT energy functional, which requires knowledge of selected elements of the inverse of the associated overlap matrix. We present a scalable algorithm for approximately computing selected entries of the inverse of the overlap matrix,more » based on an approximate inverse technique, by inverting local blocks corresponding to principal submatrices of the global overlap matrix. The new FPMD algorithm exploits sparsity and uses nearest neighbor communication to provide a computational scheme capable of extreme scalability. Accuracy is controlled by the mesh spacing of the finite difference discretization, the size of the localization regions in which the electronic orbitals are confined, and a cutoff beyond which the entries of the overlap matrix can be omitted when computing selected entries of its inverse. We demonstrate the algorithm's excellent parallel scaling for up to O(100K) atoms on O(100K) processors, with a wall-clock time of O(1) minute per molecular dynamics time step.« less
Computational challenges in modeling gene regulatory events.
Pataskar, Abhijeet; Tiwari, Vijay K
2016-10-19
Cellular transcriptional programs driven by genetic and epigenetic mechanisms could be better understood by integrating "omics" data and subsequently modeling the gene-regulatory events. Toward this end, computational biology should keep pace with evolving experimental procedures and data availability. This article gives an exemplified account of the current computational challenges in molecular biology.
Reinforcement learning in depression: A review of computational research.
Chen, Chong; Takahashi, Taiki; Nakagawa, Shin; Inoue, Takeshi; Kusumi, Ichiro
2015-08-01
Despite being considered primarily a mood disorder, major depressive disorder (MDD) is characterized by cognitive and decision making deficits. Recent research has employed computational models of reinforcement learning (RL) to address these deficits. The computational approach has the advantage in making explicit predictions about learning and behavior, specifying the process parameters of RL, differentiating between model-free and model-based RL, and the computational model-based functional magnetic resonance imaging and electroencephalography. With these merits there has been an emerging field of computational psychiatry and here we review specific studies that focused on MDD. Considerable evidence suggests that MDD is associated with impaired brain signals of reward prediction error and expected value ('wanting'), decreased reward sensitivity ('liking') and/or learning (be it model-free or model-based), etc., although the causality remains unclear. These parameters may serve as valuable intermediate phenotypes of MDD, linking general clinical symptoms to underlying molecular dysfunctions. We believe future computational research at clinical, systems, and cellular/molecular/genetic levels will propel us toward a better understanding of the disease. Copyright © 2015 Elsevier Ltd. All rights reserved.
Modeling of diatomic molecule using the Morse potential and the Verlet algorithm
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fidiani, Elok
Performing molecular modeling usually uses special software for Molecular Dynamics (MD) such as: GROMACS, NAMD, JMOL etc. Molecular dynamics is a computational method to calculate the time dependent behavior of a molecular system. In this work, MATLAB was used as numerical method for a simple modeling of some diatomic molecules: HCl, H{sub 2} and O{sub 2}. MATLAB is a matrix based numerical software, in order to do numerical analysis, all the functions and equations describing properties of atoms and molecules must be developed manually in MATLAB. In this work, a Morse potential was generated to describe the bond interaction betweenmore » the two atoms. In order to analyze the simultaneous motion of molecules, the Verlet Algorithm derived from Newton’s Equations of Motion (classical mechanics) was operated. Both the Morse potential and the Verlet algorithm were integrated using MATLAB to derive physical properties and the trajectory of the molecules. The data computed by MATLAB is always in the form of a matrix. To visualize it, Visualized Molecular Dynamics (VMD) was performed. Such method is useful for development and testing some types of interaction on a molecular scale. Besides, this can be very helpful for describing some basic principles of molecular interaction for educational purposes.« less
Nanomicrointerface to read molecular potentials into current-voltage based electronics.
Rangel, Norma L; Seminario, Jorge M
2008-03-21
Molecular potentials are unreadable and unaddressable by any present technology. It is known that the proper assembly of molecules can implement an entire numerical processing system based on digital or even analogical computation. In turn, the outputs of this molecular processing unit need to be amplified in order to be useful. We have developed a nanomicrointerface to read information encoded in molecular level potentials and to amplify this signal to microelectronic levels. The amplification is performed by making the output molecular potential slightly twist the torsional angle between two rings of a pyridazine, 3,6-bis(phenylethynyl) (aza-OPE) molecule, requiring only fractions of kcal/mol energies. In addition, even if the signal from the molecular potentials is not enough to turn the ring or even if the angles are the same for different combinations of outputs, still the current output yields results that resemble the device as a field effect transistor, providing the possibility to reduce channel lengths to the range of just 1 or 2 nm. The slight change in the torsional angle yields readable changes in the current through the aza-OPE biased by an external applied voltage. Using ab initio methods, we computationally demonstrate the amplification of molecular potential signals into currents that can be read by standard circuits.
Lopes, J S; Arenas, M; Posada, D; Beaumont, M A
2014-03-01
The estimation of parameters in molecular evolution may be biased when some processes are not considered. For example, the estimation of selection at the molecular level using codon-substitution models can have an upward bias when recombination is ignored. Here we address the joint estimation of recombination, molecular adaptation and substitution rates from coding sequences using approximate Bayesian computation (ABC). We describe the implementation of a regression-based strategy for choosing subsets of summary statistics for coding data, and show that this approach can accurately infer recombination allowing for intracodon recombination breakpoints, molecular adaptation and codon substitution rates. We demonstrate that our ABC approach can outperform other analytical methods under a variety of evolutionary scenarios. We also show that although the choice of the codon-substitution model is important, our inferences are robust to a moderate degree of model misspecification. In addition, we demonstrate that our approach can accurately choose the evolutionary model that best fits the data, providing an alternative for when the use of full-likelihood methods is impracticable. Finally, we applied our ABC method to co-estimate recombination, substitution and molecular adaptation rates from 24 published human immunodeficiency virus 1 coding data sets.
Molecular Imaging of Experimental Abdominal Aortic Aneurysms
Ramaswamy, Aneesh K.; Hamilton, Mark; Joshi, Rucha V.; Kline, Benjamin P.; Li, Rui; Wang, Pu; Goergen, Craig J.
2013-01-01
Current laboratory research in the field of abdominal aortic aneurysm (AAA) disease often utilizes small animal experimental models induced by genetic manipulation or chemical application. This has led to the use and development of multiple high-resolution molecular imaging modalities capable of tracking disease progression, quantifying the role of inflammation, and evaluating the effects of potential therapeutics. In vivo imaging reduces the number of research animals used, provides molecular and cellular information, and allows for longitudinal studies, a necessity when tracking vessel expansion in a single animal. This review outlines developments of both established and emerging molecular imaging techniques used to study AAA disease. Beyond the typical modalities used for anatomical imaging, which include ultrasound (US) and computed tomography (CT), previous molecular imaging efforts have used magnetic resonance (MR), near-infrared fluorescence (NIRF), bioluminescence, single-photon emission computed tomography (SPECT), and positron emission tomography (PET). Mouse and rat AAA models will hopefully provide insight into potential disease mechanisms, and the development of advanced molecular imaging techniques, if clinically useful, may have translational potential. These efforts could help improve the management of aneurysms and better evaluate the therapeutic potential of new treatments for human AAA disease. PMID:23737735
Training a molecular automaton to play a game
NASA Astrophysics Data System (ADS)
Pei, Renjun; Matamoros, Elizabeth; Liu, Manhong; Stefanovic, Darko; Stojanovic, Milan N.
2010-11-01
Research at the interface between chemistry and cybernetics has led to reports of `programmable molecules', but what does it mean to say `we programmed a set of solution-phase molecules to do X'? A survey of recently implemented solution-phase circuitry indicates that this statement could be replaced with `we pre-mixed a set of molecules to do X and functional subsets of X'. These hard-wired mixtures are then exposed to a set of molecular inputs, which can be interpreted as being keyed to human moves in a game, or as assertions of logical propositions. In nucleic acids-based systems, stemming from DNA computation, these inputs can be seen as generic oligonucleotides. Here, we report using reconfigurable nucleic acid catalyst-based units to build a multipurpose reprogrammable molecular automaton that goes beyond single-purpose `hard-wired' molecular automata. The automaton covers all possible responses to two consecutive sets of four inputs (such as four first and four second moves for a generic set of trivial two-player two-move games). This is a model system for more general molecular field programmable gate array (FPGA)-like devices that can be programmed by example, which means that the operator need not have any knowledge of molecular computing methods.
NASA Astrophysics Data System (ADS)
Thomas, Renjith; Hossain, Mossaraf; Mary, Y. Sheena; Resmi, K. S.; Armaković, Stevan; Armaković, Sanja J.; Nanda, Ashis Kumar; Ranjan, Vivek Kumar; Vijayakumar, G.; Van Alsenoy, C.
2018-04-01
Solvent-free synthesis pathway for obtaining two imidazole derivatives (2-chloro-1-(4-methoxyphenyl)-4,5-dimethyl-1H-imidazole (CLMPDI) and 1-(4-bromophenyl)-2-chloro-4,5-dimethyl-1H-imidazole (BPCLDI) has been reported in this work, followed by detailed experimental and computational spectroscopic characterization and reactivity study. Spectroscopic methods encompassed IR, FT-Raman and NMR techniques, with the mutual comparison of experimentally and computationally obtained results at DFT/B3LYP level of theory. Reactivity study based on DFT calculations encompassed molecular orbitals analysis, followed by calculations of molecular electrostatic potential (MEP) and average local ionization energy (ALIE) values, Fukui functions and bond dissociation energies (BDE). Additionally, the stability of title molecules in water has been investigated via molecular dynamics (MD) simulations, while interactivity with aspulvinonedimethylallyl transferase protein has been evaluated by molecular docking procedure. CLMPDI compound showed antimicrobial activity against all four bacterial strain in both gram positive and gram negative bacteria while, BPCLDI showed only in gram positive bacteria, Staphylococcus Aureus (MTCC1144). The first order hyperpolarizability of CLMPDI and BPCLDI are 20.15 and 6.10 times that of the standard NLO material urea.
Training a molecular automaton to play a game.
Pei, Renjun; Matamoros, Elizabeth; Liu, Manhong; Stefanovic, Darko; Stojanovic, Milan N
2010-11-01
Research at the interface between chemistry and cybernetics has led to reports of 'programmable molecules', but what does it mean to say 'we programmed a set of solution-phase molecules to do X'? A survey of recently implemented solution-phase circuitry indicates that this statement could be replaced with 'we pre-mixed a set of molecules to do X and functional subsets of X'. These hard-wired mixtures are then exposed to a set of molecular inputs, which can be interpreted as being keyed to human moves in a game, or as assertions of logical propositions. In nucleic acids-based systems, stemming from DNA computation, these inputs can be seen as generic oligonucleotides. Here, we report using reconfigurable nucleic acid catalyst-based units to build a multipurpose reprogrammable molecular automaton that goes beyond single-purpose 'hard-wired' molecular automata. The automaton covers all possible responses to two consecutive sets of four inputs (such as four first and four second moves for a generic set of trivial two-player two-move games). This is a model system for more general molecular field programmable gate array (FPGA)-like devices that can be programmed by example, which means that the operator need not have any knowledge of molecular computing methods.
NASA Astrophysics Data System (ADS)
Sachdeva, Ritika; Soni, Abhinav; Singh, V. P.; Saini, G. S. S.
2018-05-01
Etoricoxib is one of the selective cyclooxygenase inhibitor drug which plays a significant role in the pharmacological management of arthritis and pain. The theoretical investigation of its reactivity is done using Density Functional Theory calculations. Molecular Electrostatic Potential Surface of etoricoxib and its Mulliken atomic charge distribution are used for the prediction of its electrophilic and nucleophilic sites. The detailed analysis of its frontier molecular orbitals is also done.
Electronic Spectra from Molecular Dynamics: A Simple Approach.
1983-10-01
82.30.Cr. 33.20K. S2.40.1s The authors provided phototypeset copy for this paper using REFER TlL EON, TOFF On UNIX I ELECTRONIC SPECTRA FROM MOLECULAR...Alamos National Laboratory Los Alamos, NM 87545 I. INTRODUCTION In this paper we show how molecular dynamics can be used in a simple manner to com...could equally use Monte Carlo or explicit integration over coordinates to compute equilibrium electronic absorption bands. How- ever, molecular
Multipole Algorithms for Molecular Dynamics Simulation on High Performance Computers.
NASA Astrophysics Data System (ADS)
Elliott, William Dewey
1995-01-01
A fundamental problem in modeling large molecular systems with molecular dynamics (MD) simulations is the underlying N-body problem of computing the interactions between all pairs of N atoms. The simplest algorithm to compute pair-wise atomic interactions scales in runtime {cal O}(N^2), making it impractical for interesting biomolecular systems, which can contain millions of atoms. Recently, several algorithms have become available that solve the N-body problem by computing the effects of all pair-wise interactions while scaling in runtime less than {cal O}(N^2). One algorithm, which scales {cal O}(N) for a uniform distribution of particles, is called the Greengard-Rokhlin Fast Multipole Algorithm (FMA). This work describes an FMA-like algorithm called the Molecular Dynamics Multipole Algorithm (MDMA). The algorithm contains several features that are new to N-body algorithms. MDMA uses new, efficient series expansion equations to compute general 1/r^{n } potentials to arbitrary accuracy. In particular, the 1/r Coulomb potential and the 1/r^6 portion of the Lennard-Jones potential are implemented. The new equations are based on multivariate Taylor series expansions. In addition, MDMA uses a cell-to-cell interaction region of cells that is closely tied to worst case error bounds. The worst case error bounds for MDMA are derived in this work also. These bounds apply to other multipole algorithms as well. Several implementation enhancements are described which apply to MDMA as well as other N-body algorithms such as FMA and tree codes. The mathematics of the cell -to-cell interactions are converted to the Fourier domain for reduced operation count and faster computation. A relative indexing scheme was devised to locate cells in the interaction region which allows efficient pre-computation of redundant information and prestorage of much of the cell-to-cell interaction. Also, MDMA was integrated into the MD program SIgMA to demonstrate the performance of the program over several simulation timesteps. One MD application described here highlights the utility of including long range contributions to Lennard-Jones potential in constant pressure simulations. Another application shows the time dependence of long range forces in a multiple time step MD simulation.
A Fast Algorithm for Massively Parallel, Long-Term, Simulation of Complex Molecular Dynamics Systems
NASA Technical Reports Server (NTRS)
Jaramillo-Botero, Andres; Goddard, William A, III; Fijany, Amir
1997-01-01
The advances in theory and computing technology over the last decade have led to enormous progress in applying atomistic molecular dynamics (MD) methods to the characterization, prediction, and design of chemical, biological, and material systems,.
77 FR 57571 - Center For Scientific Review; Notice of Closed Meetings
Federal Register 2010, 2011, 2012, 2013, 2014
2012-09-18
...: Genes, Genomes, and Genetics Integrated Review Group; Genomics, Computational Biology and Technology... Reproductive Sciences Integrated Review Group; Cellular, Molecular and Integrative Reproduction Study Section...: Immunology Integrated Review Group; Cellular and Molecular Immunology--B Study Section. [[Page 57572
ESTIMATION OF PHYSIOCHEMICAL PROPERTIES OF ORGANIC COMPOUNDS BY SPARC
The computer program SPARC (SPARC Performs Automated Reasoning in Chemistry) has been under development for several years to estimate physical properties and chemical reactivity parameters of organic compounds strictly from molecular structure. SPARC uses computational algorithms...
Molecular Modeling of Environmentally Important Processes: Reduction Potentials
ERIC Educational Resources Information Center
Lewis, Anne; Bumpus, John A.; Truhlar, Donald G.; Cramer, Christopher J.
2004-01-01
The increasing use of computational quantum chemistry in the modeling of environmentally important processes is described. The employment of computational quantum mechanics for the prediction of oxidation-reduction potential for solutes in an aqueous medium is discussed.
Simultaneous G-Quadruplex DNA Logic.
Bader, Antoine; Cockroft, Scott L
2018-04-03
A fundamental principle of digital computer operation is Boolean logic, where inputs and outputs are described by binary integer voltages. Similarly, inputs and outputs may be processed on the molecular level as exemplified by synthetic circuits that exploit the programmability of DNA base-pairing. Unlike modern computers, which execute large numbers of logic gates in parallel, most implementations of molecular logic have been limited to single computing tasks, or sensing applications. This work reports three G-quadruplex-based logic gates that operate simultaneously in a single reaction vessel. The gates respond to unique Boolean DNA inputs by undergoing topological conversion from duplex to G-quadruplex states that were resolved using a thioflavin T dye and gel electrophoresis. The modular, addressable, and label-free approach could be incorporated into DNA-based sensors, or used for resolving and debugging parallel processes in DNA computing applications. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
NASA Technical Reports Server (NTRS)
Jain, Abhinandan
2011-01-01
Ndarts software provides algorithms for computing quantities associated with the dynamics of articulated, rigid-link, multibody systems. It is designed as a general-purpose dynamics library that can be used for the modeling of robotic platforms, space vehicles, molecular dynamics, and other such applications. The architecture and algorithms in Ndarts are based on the Spatial Operator Algebra (SOA) theory for computational multibody and robot dynamics developed at JPL. It uses minimal, internal coordinate models. The algorithms are low-order, recursive scatter/ gather algorithms. In comparison with the earlier Darts++ software, this version has a more general and cleaner design needed to support a larger class of computational dynamics needs. It includes a frames infrastructure, allows algorithms to operate on subgraphs of the system, and implements lazy and deferred computation for better efficiency. Dynamics modeling modules such as Ndarts are core building blocks of control and simulation software for space, robotic, mechanism, bio-molecular, and material systems modeling.
NASA Astrophysics Data System (ADS)
Motta, Mario; Zhang, Shiwei
2018-05-01
We propose an algorithm for accurate, systematic, and scalable computation of interatomic forces within the auxiliary-field quantum Monte Carlo (AFQMC) method. The algorithm relies on the Hellmann-Feynman theorem and incorporates Pulay corrections in the presence of atomic orbital basis sets. We benchmark the method for small molecules by comparing the computed forces with the derivatives of the AFQMC potential energy surface and by direct comparison with other quantum chemistry methods. We then perform geometry optimizations using the steepest descent algorithm in larger molecules. With realistic basis sets, we obtain equilibrium geometries in agreement, within statistical error bars, with experimental values. The increase in computational cost for computing forces in this approach is only a small prefactor over that of calculating the total energy. This paves the way for a general and efficient approach for geometry optimization and molecular dynamics within AFQMC.
2017 ISCB Overton Prize: Christoph Bock
Fogg, Christiana N.; Kovats, Diane E.; Berger, Bonnie
2017-01-01
The International Society for Computational Biology (ISCB) each year recognizes the achievements of an early to mid-career scientist with the Overton Prize. This prize honors the untimely death of Dr. G. Christian Overton, an admired computational biologist and founding ISCB Board member. Winners of the Overton Prize are independent investigators who are in the early to middle phases of their careers and are selected because of their significant contributions to computational biology through research, teaching, and service. ISCB is pleased to recognize Dr. Christoph Bock, Principal Investigator at the CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences in Vienna, Austria, as the 2017 winner of the Overton Prize. Bock will be presenting a keynote presentation at the 2017 International Conference on Intelligent Systems for Molecular Biology/European Conference on Computational Biology (ISMB/ECCB) in Prague, Czech Republic being held during July 21-25, 2017. PMID:28713546
2017 ISCB Overton Prize: Christoph Bock.
Fogg, Christiana N; Kovats, Diane E; Berger, Bonnie
2017-01-01
The International Society for Computational Biology (ISCB) each year recognizes the achievements of an early to mid-career scientist with the Overton Prize. This prize honors the untimely death of Dr. G. Christian Overton, an admired computational biologist and founding ISCB Board member. Winners of the Overton Prize are independent investigators who are in the early to middle phases of their careers and are selected because of their significant contributions to computational biology through research, teaching, and service. ISCB is pleased to recognize Dr. Christoph Bock, Principal Investigator at the CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences in Vienna, Austria, as the 2017 winner of the Overton Prize. Bock will be presenting a keynote presentation at the 2017 International Conference on Intelligent Systems for Molecular Biology/European Conference on Computational Biology (ISMB/ECCB) in Prague, Czech Republic being held during July 21-25, 2017.
Computational efficiency and Amdahl’s law for the adaptive resolution simulation technique
DOE Office of Scientific and Technical Information (OSTI.GOV)
Junghans, Christoph; Agarwal, Animesh; Delle Site, Luigi
Here, we discuss the computational performance of the adaptive resolution technique in molecular simulation when it is compared with equivalent full coarse-grained and full atomistic simulations. We show that an estimate of its efficiency, within 10%–15% accuracy, is given by the Amdahl’s Law adapted to the specific quantities involved in the problem. The derivation of the predictive formula is general enough that it may be applied to the general case of molecular dynamics approaches where a reduction of degrees of freedom in a multi scale fashion occurs.
Computational efficiency and Amdahl’s law for the adaptive resolution simulation technique
Junghans, Christoph; Agarwal, Animesh; Delle Site, Luigi
2017-06-01
Here, we discuss the computational performance of the adaptive resolution technique in molecular simulation when it is compared with equivalent full coarse-grained and full atomistic simulations. We show that an estimate of its efficiency, within 10%–15% accuracy, is given by the Amdahl’s Law adapted to the specific quantities involved in the problem. The derivation of the predictive formula is general enough that it may be applied to the general case of molecular dynamics approaches where a reduction of degrees of freedom in a multi scale fashion occurs.
Ramalho, Teodorico C.; DeCastro, Alexandre A.; Silva, Daniela R.; ...
2015-08-26
The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and helpmore » in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and help in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ramalho, Teodorico C.; DeCastro, Alexandre A.; Silva, Daniela R.
The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and helpmore » in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and help in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.« less
NASA Astrophysics Data System (ADS)
Perriot, Romain; Kober, Ed; Mniszewski, Sue; Martinez, Enrique; Niklasson, Anders; Yang, Ping; McGrane, Shawn; Cawkwell, Marc
2017-06-01
Characterizing the complex, rapid reactions of energetic materials under conditions of high temperatures and pressures presents strong experimental and computational challenges. The recently developed extended Lagrangian Born-Oppenheimer molecular dynamics formalism enables the long-term conservation of the total energy in microcanonical trajectories, and using a density functional tight binding formulation provides good chemical accuracy. We use this combined approach to study the evolution of temperature, pressure, and chemical species in shock-compressed liquid nitromethane over hundreds of picoseconds. The chemical species seen in nitromethane under shock compression are compared with those seen under static high temperature conditions. A reduced-order representation of the complex sequence of chemical reactions that characterize this system has been developed from the molecular dynamics simulations by focusing on classes of chemical reactions rather than specific molecular species. Time-resolved infra-red vibrational spectra were also computed from the molecular trajectories and compared to the chemical analysis. These spectra provide a time history of the species present in the system that can be compared directly with recent experiments at LANL.
Quantum chemical study of a derivative of 3-substituted dithiocarbamic flavanone
NASA Astrophysics Data System (ADS)
Gosav, Steluta; Paduraru, Nicoleta; Maftei, Dan; Birsa, Mihail Lucian; Praisler, Mirela
2017-02-01
The aim of this work is to characterize a quite novel 3-dithiocarbamic flavonoid by vibrational spectroscopy in conjunction with Density Functional Theory (DFT) calculations. Quantum mechanics calculations of energies, geometries and vibrational wavenumbers in the ground state were carried out by using hybrid functional B3LYP with 6-311G(d,p) as basis set. The results indicate a remarkable agreement between the calculated molecular geometries, as well as vibrational frequencies, and the corresponding experimental data. In addition, a complete assignment of all the absorption bands present in the vibrational spectrum has been performed. In order to assess its chemical potential, quantum molecular descriptors characterizing the interactions between the 3-dithiocarbamic flavonoid and its biological receptors have been computed. The frontier molecular orbitals and the HOMO-LUMO energy gap have been used in order to explain the way in which the new molecule can interact with other species and to characterize its molecular chemical stability/reactivity. The molecular electrostatic potential (MEP) map, computed in order to identify the sites of the studied flavonoid that are most likely to interact with electrophilic and nucleophilic species, is discussed.
Brønsted acidity of protic ionic liquids: a modern ab initio valence bond theory perspective.
Patil, Amol Baliram; Mahadeo Bhanage, Bhalchandra
2016-09-21
Room temperature ionic liquids (ILs), especially protic ionic liquids (PILs), are used in many areas of the chemical sciences. Ionicity, the extent of proton transfer, is a key parameter which determines many physicochemical properties and in turn the suitability of PILs for various applications. The spectrum of computational chemistry techniques applied to investigate ionic liquids includes classical molecular dynamics, Monte Carlo simulations, ab initio molecular dynamics, Density Functional Theory (DFT), CCSD(t) etc. At the other end of the spectrum is another computational approach: modern ab initio Valence Bond Theory (VBT). VBT differs from molecular orbital theory based methods in the expression of the molecular wave function. The molecular wave function in the valence bond ansatz is expressed as a linear combination of valence bond structures. These structures include covalent and ionic structures explicitly. Modern ab initio valence bond theory calculations of representative primary and tertiary ammonium protic ionic liquids indicate that modern ab initio valence bond theory can be employed to assess the acidity and ionicity of protic ionic liquids a priori.
Georgieva, I; Mihaylov, Tz; Trendafilova, N
2014-06-01
The present paper summarizes theoretical and spectroscopic investigations on a series of active coumarins and their lanthanide and transition metal complexes with application in medicine and pharmacy. Molecular modeling as well as IR, Raman, NMR and electronic spectral simulations at different levels of theory were performed to obtain important molecular descriptors: total energy, formation energy, binding energy, stability, conformations, structural parameters, electron density distribution, molecular electrostatic potential, Fukui functions, atomic charges, and reactive indexes. The computations are performed both in gas phase and in solution with consideration of the solvent effect on the molecular structural and energetic parameters. The investigations have shown that the advanced computational methods are reliable for prediction of the metal-coumarin binding mode, electron density distribution, thermodynamic properties as well as the strength and nature of the metal-coumarin interaction (not experimentally accessible) and correctly interpret the experimental spectroscopic data. Known results from biological tests for cytotoxic, antimicrobial, anti-fungal, spasmolytic and anti-HIV activities on the studied metal complexes are reported and discussed. Copyright © 2014 Elsevier Inc. All rights reserved.
Heuristic lipophilicity potential for computer-aided rational drug design
NASA Astrophysics Data System (ADS)
Du, Qishi; Arteca, Gustavo A.; Mezey, Paul G.
1997-09-01
In this contribution we suggest a heuristic molecular lipophilicitypotential (HMLP), which is a structure-based technique requiring noempirical indices of atomic lipophilicity. The input data used in thisapproach are molecular geometries and molecular surfaces. The HMLP is amodified electrostatic potential, combined with the averaged influences fromthe molecular environment. Quantum mechanics is used to calculate theelectron density function ρ(r) and the electrostatic potential V(r), andfrom this information a lipophilicity potential L(r) is generated. The HMLPis a unified lipophilicity and hydrophilicity potential. The interactions ofdipole and multipole moments, hydrogen bonds, and charged atoms in amolecule are included in the hydrophilic interactions in this model. TheHMLP is used to study hydrogen bonds and water-octanol partitioncoefficients in several examples. The calculated results show that the HMLPgives qualitatively and quantitatively correct, as well as chemicallyreasonable, results in cases where comparisons are available. Thesecomparisons indicate that the HMLP has advantages over the empiricallipophilicity potential in many aspects. The HMLP is a three-dimensional andeasily visualizable representation of molecular lipophilicity, suggested asa potential tool in computer-aided three-dimensional drug design.
NASA Astrophysics Data System (ADS)
Mazilu, Irina; Gonzalez, Joshua
2008-03-01
From the point of view of a physicist, a bio-molecular motor represents an interesting non-equilibrium system and it is directly amenable to an analysis using standard methods of non-equilibrium statistical physics. We conduct a rigorous Monte Carlo study of three different driven lattice gas models that retain the basic behavior of three types of cytoskeletal molecular motors. Our models incorporate novel features such as realistic dynamics rules and complex motor-motor interactions. We are interested to have a deeper understanding of how various parameters influence the macroscopic behavior of these systems, what is the density profile and if the system undergoes a phase transition. On the analytical front, we computed the steady-state probability distributions exactly for the one of the models using the matrix method that was established in 1993 by B. Derrida et al. We also explored the possibilities offered by the ``Bethe ansatz'' method by mapping some well studied spin models into asymmetric simple exclusion models (already analyzed using computer simulations), and to use the results obtained for the spin models in finding an exact solution for our problem. We have exhaustive computational studies of the kinesin and dynein molecular motor models that prove to be very useful in checking our analytical work.
Distance-Based Configurational Entropy of Proteins from Molecular Dynamics Simulations
Fogolari, Federico; Corazza, Alessandra; Fortuna, Sara; Soler, Miguel Angel; VanSchouwen, Bryan; Brancolini, Giorgia; Corni, Stefano; Melacini, Giuseppe; Esposito, Gennaro
2015-01-01
Estimation of configurational entropy from molecular dynamics trajectories is a difficult task which is often performed using quasi-harmonic or histogram analysis. An entirely different approach, proposed recently, estimates local density distribution around each conformational sample by measuring the distance from its nearest neighbors. In this work we show this theoretically well grounded the method can be easily applied to estimate the entropy from conformational sampling. We consider a set of systems that are representative of important biomolecular processes. In particular: reference entropies for amino acids in unfolded proteins are obtained from a database of residues not participating in secondary structure elements;the conformational entropy of folding of β2-microglobulin is computed from molecular dynamics simulations using reference entropies for the unfolded state;backbone conformational entropy is computed from molecular dynamics simulations of four different states of the EPAC protein and compared with order parameters (often used as a measure of entropy);the conformational and rototranslational entropy of binding is computed from simulations of 20 tripeptides bound to the peptide binding protein OppA and of β2-microglobulin bound to a citrate coated gold surface. This work shows the potential of the method in the most representative biological processes involving proteins, and provides a valuable alternative, principally in the shown cases, where other approaches are problematic. PMID:26177039
Distance-Based Configurational Entropy of Proteins from Molecular Dynamics Simulations.
Fogolari, Federico; Corazza, Alessandra; Fortuna, Sara; Soler, Miguel Angel; VanSchouwen, Bryan; Brancolini, Giorgia; Corni, Stefano; Melacini, Giuseppe; Esposito, Gennaro
2015-01-01
Estimation of configurational entropy from molecular dynamics trajectories is a difficult task which is often performed using quasi-harmonic or histogram analysis. An entirely different approach, proposed recently, estimates local density distribution around each conformational sample by measuring the distance from its nearest neighbors. In this work we show this theoretically well grounded the method can be easily applied to estimate the entropy from conformational sampling. We consider a set of systems that are representative of important biomolecular processes. In particular: reference entropies for amino acids in unfolded proteins are obtained from a database of residues not participating in secondary structure elements;the conformational entropy of folding of β2-microglobulin is computed from molecular dynamics simulations using reference entropies for the unfolded state;backbone conformational entropy is computed from molecular dynamics simulations of four different states of the EPAC protein and compared with order parameters (often used as a measure of entropy);the conformational and rototranslational entropy of binding is computed from simulations of 20 tripeptides bound to the peptide binding protein OppA and of β2-microglobulin bound to a citrate coated gold surface. This work shows the potential of the method in the most representative biological processes involving proteins, and provides a valuable alternative, principally in the shown cases, where other approaches are problematic.
NASA Astrophysics Data System (ADS)
Aquilanti, Vincenzo; Bitencourt, Ana Carla P.; Ferreira, Cristiane da S.; Marzuoli, Annalisa; Ragni, Mirco
2008-11-01
The mathematical apparatus of quantum-mechanical angular momentum (re)coupling, developed originally to describe spectroscopic phenomena in atomic, molecular, optical and nuclear physics, is embedded in modern algebraic settings which emphasize the underlying combinatorial aspects. SU(2) recoupling theory, involving Wigner's 3nj symbols, as well as the related problems of their calculations, general properties, asymptotic limits for large entries, nowadays plays a prominent role also in quantum gravity and quantum computing applications. We refer to the ingredients of this theory—and of its extension to other Lie and quantum groups—by using the collective term of 'spin networks'. Recent progress is recorded about the already established connections with the mathematical theory of discrete orthogonal polynomials (the so-called Askey scheme), providing powerful tools based on asymptotic expansions, which correspond on the physical side to various levels of semi-classical limits. These results are useful not only in theoretical molecular physics but also in motivating algorithms for the computationally demanding problems of molecular dynamics and chemical reaction theory, where large angular momenta are typically involved. As for quantum chemistry, applications of these techniques include selection and classification of complete orthogonal basis sets in atomic and molecular problems, either in configuration space (Sturmian orbitals) or in momentum space. In this paper, we list and discuss some aspects of these developments—such as for instance the hyperquantization algorithm—as well as a few applications to quantum gravity and topology, thus providing evidence of a unifying background structure.
Fast Particle Methods for Multiscale Phenomena Simulations
NASA Technical Reports Server (NTRS)
Koumoutsakos, P.; Wray, A.; Shariff, K.; Pohorille, Andrew
2000-01-01
We are developing particle methods oriented at improving computational modeling capabilities of multiscale physical phenomena in : (i) high Reynolds number unsteady vortical flows, (ii) particle laden and interfacial flows, (iii)molecular dynamics studies of nanoscale droplets and studies of the structure, functions, and evolution of the earliest living cell. The unifying computational approach involves particle methods implemented in parallel computer architectures. The inherent adaptivity, robustness and efficiency of particle methods makes them a multidisciplinary computational tool capable of bridging the gap of micro-scale and continuum flow simulations. Using efficient tree data structures, multipole expansion algorithms, and improved particle-grid interpolation, particle methods allow for simulations using millions of computational elements, making possible the resolution of a wide range of length and time scales of these important physical phenomena.The current challenges in these simulations are in : [i] the proper formulation of particle methods in the molecular and continuous level for the discretization of the governing equations [ii] the resolution of the wide range of time and length scales governing the phenomena under investigation. [iii] the minimization of numerical artifacts that may interfere with the physics of the systems under consideration. [iv] the parallelization of processes such as tree traversal and grid-particle interpolations We are conducting simulations using vortex methods, molecular dynamics and smooth particle hydrodynamics, exploiting their unifying concepts such as : the solution of the N-body problem in parallel computers, highly accurate particle-particle and grid-particle interpolations, parallel FFT's and the formulation of processes such as diffusion in the context of particle methods. This approach enables us to transcend among seemingly unrelated areas of research.
NASA Astrophysics Data System (ADS)
Sane, Sandeep Bhalchandra
This thesis contains three chapters, which describe different aspects of an investigation of the bulk response of Poly(Methyl Methacrylate) (PMMA). The first chapter describes the physical measurements by means of a Belcher/McKinney-type apparatus. Used earlier for the measurement of the bulk response of Poly(Vinyl Acetate), it was now adapted for making measurements at higher temperatures commensurate with the glass transition temperature of PMMA. The dynamic bulk compliance of PMMA was measured at atmospheric pressure over a wide range of temperatures and frequencies, from which the master curves for the bulk compliance were generated by means of the time-temperature superposition principle. It was found that the extent of the transition ranges for the bulk and shear response were comparable. Comparison of the shift factors for bulk and shear responses supports the idea that different molecular mechanisms contribute to shear and bulk deformations. The second chapter delineates molecular dynamics computations for the bulk response for a range of pressures and temperatures. The model(s) consisted of 2256 atoms formed into three polymer chains with fifty monomer units per chain per unit cell. The time scales accessed were limited to tens of pico seconds. It was found that, in addition to the typical energy minimization and temperature annealing cycles for establishing equilibrium models, it is advantageous to subject the model samples to a cycle of relatively large pressures (GPa-range) for improving the equilibrium state. On comparing the computations with the experimentally determined "glassy" behavior, one finds that, although the computations were limited to small samples in a physical sense, the primary limitation rests in the very short times (pico seconds). The molecular dynamics computations do not model the physically observed temperature sensitivity of PMMA, even if one employs a hypothetical time-temperature shift to account for the large difference in time scales between experiment and computation. The values computed by the molecular dynamics method do agree with the values measured at the coldest temperature and at the highest frequency of one kiloHertz. The third chapter draws on measurements of uniaxial, shear and Poisson response conducted previously in our laboratory. With the availability of four time or frequency-dependent material functions for the same material, the process of interconversion between different material functions was investigated. Computed material functions were evaluated against the direct experimental measurements and the limitations imposed on successful interconversion due to the experimental errors in the underlying physical data were explored. Differences were observed that are larger than the experimental errors would suggest.
A Computational Model for Oocyte Growth Dynamics in Fathead Minnows
Molecular biomarkers have been used in ecotoxicological studies to evaluate the effects of endocrine disrupting chemicals in fish. Changes in these molecular biomarkers must then be linked to the effects upon reproduction in individuals, and subsequently populations. To meet th...
A Computational Model for Oocyte Growth Dynamics in Fathead Minnows (Pimephales promelas)
Molecular biomarkers have been used in ecotoxicological studies to evaluate the effects of endocrine disrupting chemicals in fish. Ideally, changes in these molecular biomarkers should be linked to the effects upon reproduction in individuals, and subsequently populations. To m...
Mobile modeling in the molecular sciences
The art of modeling in the molecular sciences is highly dependent on both the available computational technology, underlying data, and ability to collaborate. With the ever increasing market share of mobile devices, it is assumed by many that tablets will overtake laptops as the...
Developing and evaluating prediactive strategies to elucidate the mode of biological activity of environmental chemicals is a major objective of the concerted efforts of the US-EPA's computational toxicology program.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Haack, Jeffrey; Shohet, Gil
2016-12-02
The software implements a heterogeneous multiscale method (HMM), which involves solving a classical molecular dynamics (MD) problem and then computes the entropy production in order to compute the relaxation times towards equilibrium for use in a Bhatnagar-Gross-Krook (BGK) solver.
Biotechnology Computing: Information Science for the Era of Molecular Medicine.
ERIC Educational Resources Information Center
Masys, Daniel R.
1989-01-01
The evolution from classical genetics to biotechnology, an area of research involving key macromolecules in living cells, is chronicled and the current state of biotechnology is described, noting related advances in computing and clinical medicine. (MSE)
ESTIMATION OF PHYSICAL PROPERTIES AND CHEMICAL REACTIVITY PARAMETERS OF ORGANIC COMPOUNDS
The computer program SPARC (Sparc Performs Automated Reasoning in Chemistry)has been under development for several years to estimate physical properties and chemical reactivity parameters of organic compounds strictly from molecular structure. SPARC uses computational algorithms ...
Computational challenges in modeling gene regulatory events
Pataskar, Abhijeet; Tiwari, Vijay K.
2016-01-01
ABSTRACT Cellular transcriptional programs driven by genetic and epigenetic mechanisms could be better understood by integrating “omics” data and subsequently modeling the gene-regulatory events. Toward this end, computational biology should keep pace with evolving experimental procedures and data availability. This article gives an exemplified account of the current computational challenges in molecular biology. PMID:27390891
ERIC Educational Resources Information Center
Rodrigues, Ricardo P.; Andrade, Saulo F.; Mantoani, Susimaire P.; Eifler-Lima, Vera L.; Silva, Vinicius B.; Kawano, Daniel F.
2015-01-01
Advances in, and dissemination of, computer technologies in the field of drug research now enable the use of molecular modeling tools to teach important concepts of drug design to chemistry and pharmacy students. A series of computer laboratories is described to introduce undergraduate students to commonly adopted "in silico" drug design…
ERIC Educational Resources Information Center
Springer, Michael T.
2014-01-01
Several articles suggest how to incorporate computer models into the organic chemistry laboratory, but relatively few papers discuss how to incorporate these models broadly into the organic chemistry lecture. Previous research has suggested that "manipulating" physical or computer models enhances student understanding; this study…
Electron-correlated fragment-molecular-orbital calculations for biomolecular and nano systems.
Tanaka, Shigenori; Mochizuki, Yuji; Komeiji, Yuto; Okiyama, Yoshio; Fukuzawa, Kaori
2014-06-14
Recent developments in the fragment molecular orbital (FMO) method for theoretical formulation, implementation, and application to nano and biomolecular systems are reviewed. The FMO method has enabled ab initio quantum-mechanical calculations for large molecular systems such as protein-ligand complexes at a reasonable computational cost in a parallelized way. There have been a wealth of application outcomes from the FMO method in the fields of biochemistry, medicinal chemistry and nanotechnology, in which the electron correlation effects play vital roles. With the aid of the advances in high-performance computing, the FMO method promises larger, faster, and more accurate simulations of biomolecular and related systems, including the descriptions of dynamical behaviors in solvent environments. The current status and future prospects of the FMO scheme are addressed in these contexts.
Wang, Zhaocai; Pu, Jun; Cao, Liling; Tan, Jian
2015-01-01
The unbalanced assignment problem (UAP) is to optimally resolve the problem of assigning n jobs to m individuals (m < n), such that minimum cost or maximum profit obtained. It is a vitally important Non-deterministic Polynomial (NP) complete problem in operation management and applied mathematics, having numerous real life applications. In this paper, we present a new parallel DNA algorithm for solving the unbalanced assignment problem using DNA molecular operations. We reasonably design flexible-length DNA strands representing different jobs and individuals, take appropriate steps, and get the solutions of the UAP in the proper length range and O(mn) time. We extend the application of DNA molecular operations and simultaneity to simplify the complexity of the computation. PMID:26512650
Molecular Nanotechnology and Designs of Future
NASA Technical Reports Server (NTRS)
Srivastava, Deepak; Chancellor, Marisa K. (Technical Monitor)
1997-01-01
Reviewing the status of current approaches and future projections, as already published in the scientific journals and books, the talk will summarize the direction in which computational and experimental molecular nanotechnologies are progressing. Examples of nanotechnological approach to the concepts of design and simulation of atomically precise materials in a variety of interdisciplinary areas will be presented. The concepts of hypothetical molecular machines and assemblers as explained in Drexler's and Merckle's already published work and Han et. al's WWW distributed molecular gears will be explained.
DOVIS 2.0: An Efficient and Easy to Use Parallel Virtual Screening Tool Based on AutoDock 4.0
2008-09-08
under the GNU General Public License. Background Molecular docking is a computational method that pre- dicts how a ligand interacts with a receptor...Hence, it is an important tool in studying receptor-ligand interactions and plays an essential role in drug design. Particularly, molecular docking has...libraries from OpenBabel and setup a molecular data structure as a C++ object in our program. This makes handling of molecular structures (e.g., atoms
Building better water models using the shape of the charge distribution of a water molecule
NASA Astrophysics Data System (ADS)
Dharmawardhana, Chamila Chathuranga; Ichiye, Toshiko
2017-11-01
The unique properties of liquid water apparently arise from more than just the tetrahedral bond angle between the nuclei of a water molecule since simple three-site models of water are poor at mimicking these properties in computer simulations. Four- and five-site models add partial charges on dummy sites and are better at modeling these properties, which suggests that the shape of charge distribution is important. Since a multipole expansion of the electrostatic potential describes a charge distribution in an orthogonal basis set that is exact in the limit of infinite order, multipoles may be an even better way to model the charge distribution. In particular, molecular multipoles up to the octupole centered on the oxygen appear to describe the electrostatic potential from electronic structure calculations better than four- and five-site models, and molecular multipole models give better agreement with the temperature and pressure dependence of many liquid state properties of water while retaining the computational efficiency of three-site models. Here, the influence of the shape of the molecular charge distribution on liquid state properties is examined by correlating multipoles of non-polarizable water models with their liquid state properties in computer simulations. This will aid in the development of accurate water models for classical simulations as well as in determining the accuracy needed in quantum mechanical/molecular mechanical studies and ab initio molecular dynamics simulations of water. More fundamentally, this will lead to a greater understanding of how the charge distribution of a water molecule leads to the unique properties of liquid water. In particular, these studies indicate that p-orbital charge out of the molecular plane is important.
Jamal, Salma; Scaria, Vinod
2014-01-01
Background. Traditional Chinese medicine encompasses a well established alternate system of medicine based on a broad range of herbal formulations and is practiced extensively in the region for the treatment of a wide variety of diseases. In recent years, several reports describe in depth studies of the molecular ingredients of traditional Chinese medicines on the biological activities including anti-bacterial activities. The availability of a well-curated dataset of molecular ingredients of traditional Chinese medicines and accurate in-silico cheminformatics models for data mining for antitubercular agents and computational filters to prioritize molecules has prompted us to search for potential hits from these datasets. Results. We used a consensus approach to predict molecules with potential antitubercular activities from a large dataset of molecular ingredients of traditional Chinese medicines available in the public domain. We further prioritized 160 molecules based on five computational filters (SMARTSfilter) so as to avoid potentially undesirable molecules. We further examined the molecules for permeability across Mycobacterial cell wall and for potential activities against non-replicating and drug tolerant Mycobacteria. Additional in-depth literature surveys for the reported antitubercular activities of the molecular ingredients and their sources were considered for drawing support to prioritization. Conclusions. Our analysis suggests that datasets of molecular ingredients of traditional Chinese medicines offer a new opportunity to mine for potential biological activities. In this report, we suggest a proof-of-concept methodology to prioritize molecules for further experimental assays using a variety of computational tools. We also additionally suggest that a subset of prioritized molecules could be used for evaluation for tuberculosis due to their additional effect against non-replicating tuberculosis as well as the additional hepato-protection offered by the source of these ingredients.
The R.E.D. tools: advances in RESP and ESP charge derivation and force field library building.
Dupradeau, François-Yves; Pigache, Adrien; Zaffran, Thomas; Savineau, Corentin; Lelong, Rodolphe; Grivel, Nicolas; Lelong, Dimitri; Rosanski, Wilfried; Cieplak, Piotr
2010-07-28
Deriving atomic charges and building a force field library for a new molecule are key steps when developing a force field required for conducting structural and energy-based analysis using molecular mechanics. Derivation of popular RESP charges for a set of residues is a complex and error prone procedure because it depends on numerous input parameters. To overcome these problems, the R.E.D. Tools (RESP and ESP charge Derive, ) have been developed to perform charge derivation in an automatic and straightforward way. The R.E.D. program handles chemical elements up to bromine in the periodic table. It interfaces different quantum mechanical programs employed for geometry optimization and computing molecular electrostatic potential(s), and performs charge fitting using the RESP program. By defining tight optimization criteria and by controlling the molecular orientation of each optimized geometry, charge values are reproduced at any computer platform with an accuracy of 0.0001 e. The charges can be fitted using multiple conformations, making them suitable for molecular dynamics simulations. R.E.D. allows also for defining charge constraints during multiple molecule charge fitting, which are used to derive charges for molecular fragments. Finally, R.E.D. incorporates charges into a force field library, readily usable in molecular dynamics computer packages. For complex cases, such as a set of homologous molecules belonging to a common family, an entire force field topology database is generated. Currently, the atomic charges and force field libraries have been developed for more than fifty model systems and stored in the RESP ESP charge DDataBase. Selected results related to non-polarizable charge models are presented and discussed.
San Lucas, F Anthony; Fowler, Jerry; Chang, Kyle; Kopetz, Scott; Vilar, Eduardo; Scheet, Paul
2014-12-01
Large-scale cancer datasets such as The Cancer Genome Atlas (TCGA) allow researchers to profile tumors based on a wide range of clinical and molecular characteristics. Subsequently, TCGA-derived gene expression profiles can be analyzed with the Connectivity Map (CMap) to find candidate drugs to target tumors with specific clinical phenotypes or molecular characteristics. This represents a powerful computational approach for candidate drug identification, but due to the complexity of TCGA and technology differences between CMap and TCGA experiments, such analyses are challenging to conduct and reproduce. We present Cancer in silico Drug Discovery (CiDD; scheet.org/software), a computational drug discovery platform that addresses these challenges. CiDD integrates data from TCGA, CMap, and Cancer Cell Line Encyclopedia (CCLE) to perform computational drug discovery experiments, generating hypotheses for the following three general problems: (i) determining whether specific clinical phenotypes or molecular characteristics are associated with unique gene expression signatures; (ii) finding candidate drugs to repress these expression signatures; and (iii) identifying cell lines that resemble the tumors being studied for subsequent in vitro experiments. The primary input to CiDD is a clinical or molecular characteristic. The output is a biologically annotated list of candidate drugs and a list of cell lines for in vitro experimentation. We applied CiDD to identify candidate drugs to treat colorectal cancers harboring mutations in BRAF. CiDD identified EGFR and proteasome inhibitors, while proposing five cell lines for in vitro testing. CiDD facilitates phenotype-driven, systematic drug discovery based on clinical and molecular data from TCGA. ©2014 American Association for Cancer Research.
Jamal, Salma
2014-01-01
Background. Traditional Chinese medicine encompasses a well established alternate system of medicine based on a broad range of herbal formulations and is practiced extensively in the region for the treatment of a wide variety of diseases. In recent years, several reports describe in depth studies of the molecular ingredients of traditional Chinese medicines on the biological activities including anti-bacterial activities. The availability of a well-curated dataset of molecular ingredients of traditional Chinese medicines and accurate in-silico cheminformatics models for data mining for antitubercular agents and computational filters to prioritize molecules has prompted us to search for potential hits from these datasets. Results. We used a consensus approach to predict molecules with potential antitubercular activities from a large dataset of molecular ingredients of traditional Chinese medicines available in the public domain. We further prioritized 160 molecules based on five computational filters (SMARTSfilter) so as to avoid potentially undesirable molecules. We further examined the molecules for permeability across Mycobacterial cell wall and for potential activities against non-replicating and drug tolerant Mycobacteria. Additional in-depth literature surveys for the reported antitubercular activities of the molecular ingredients and their sources were considered for drawing support to prioritization. Conclusions. Our analysis suggests that datasets of molecular ingredients of traditional Chinese medicines offer a new opportunity to mine for potential biological activities. In this report, we suggest a proof-of-concept methodology to prioritize molecules for further experimental assays using a variety of computational tools. We also additionally suggest that a subset of prioritized molecules could be used for evaluation for tuberculosis due to their additional effect against non-replicating tuberculosis as well as the additional hepato-protection offered by the source of these ingredients. PMID:25081126
NASA Astrophysics Data System (ADS)
Aviat, Félix; Lagardère, Louis; Piquemal, Jean-Philip
2017-10-01
In a recent paper [F. Aviat et al., J. Chem. Theory Comput. 13, 180-190 (2017)], we proposed the Truncated Conjugate Gradient (TCG) approach to compute the polarization energy and forces in polarizable molecular simulations. The method consists in truncating the conjugate gradient algorithm at a fixed predetermined order leading to a fixed computational cost and can thus be considered "non-iterative." This gives the possibility to derive analytical forces avoiding the usual energy conservation (i.e., drifts) issues occurring with iterative approaches. A key point concerns the evaluation of the analytical gradients, which is more complex than that with a usual solver. In this paper, after reviewing the present state of the art of polarization solvers, we detail a viable strategy for the efficient implementation of the TCG calculation. The complete cost of the approach is then measured as it is tested using a multi-time step scheme and compared to timings using usual iterative approaches. We show that the TCG methods are more efficient than traditional techniques, making it a method of choice for future long molecular dynamics simulations using polarizable force fields where energy conservation matters. We detail the various steps required for the implementation of the complete method by software developers.
Aviat, Félix; Lagardère, Louis; Piquemal, Jean-Philip
2017-10-28
In a recent paper [F. Aviat et al., J. Chem. Theory Comput. 13, 180-190 (2017)], we proposed the Truncated Conjugate Gradient (TCG) approach to compute the polarization energy and forces in polarizable molecular simulations. The method consists in truncating the conjugate gradient algorithm at a fixed predetermined order leading to a fixed computational cost and can thus be considered "non-iterative." This gives the possibility to derive analytical forces avoiding the usual energy conservation (i.e., drifts) issues occurring with iterative approaches. A key point concerns the evaluation of the analytical gradients, which is more complex than that with a usual solver. In this paper, after reviewing the present state of the art of polarization solvers, we detail a viable strategy for the efficient implementation of the TCG calculation. The complete cost of the approach is then measured as it is tested using a multi-time step scheme and compared to timings using usual iterative approaches. We show that the TCG methods are more efficient than traditional techniques, making it a method of choice for future long molecular dynamics simulations using polarizable force fields where energy conservation matters. We detail the various steps required for the implementation of the complete method by software developers.
Computational power and generative capacity of genetic systems.
Igamberdiev, Abir U; Shklovskiy-Kordi, Nikita E
2016-01-01
Semiotic characteristics of genetic sequences are based on the general principles of linguistics formulated by Ferdinand de Saussure, such as the arbitrariness of sign and the linear nature of the signifier. Besides these semiotic features that are attributable to the basic structure of the genetic code, the principle of generativity of genetic language is important for understanding biological transformations. The problem of generativity in genetic systems arises to a possibility of different interpretations of genetic texts, and corresponds to what Alexander von Humboldt called "the infinite use of finite means". These interpretations appear in the individual development as the spatiotemporal sequences of realizations of different textual meanings, as well as the emergence of hyper-textual statements about the text itself, which underlies the process of biological evolution. These interpretations are accomplished at the level of the readout of genetic texts by the structures defined by Efim Liberman as "the molecular computer of cell", which includes DNA, RNA and the corresponding enzymes operating with molecular addresses. The molecular computer performs physically manifested mathematical operations and possesses both reading and writing capacities. Generativity paradoxically resides in the biological computational system as a possibility to incorporate meta-statements about the system, and thus establishes the internal capacity for its evolution. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Annapureddy, Harsha Vardhan Reddy; Nune, Satish K.; Motkuri, Radha K.
2015-01-08
Computational studies on nanofluids composed of metal organic frameworks (MOFs) were performed using molecular modeling techniques. Grand Canonical Monte Carlo (GCMC) simulations were used to study adsorption behavior of 1,1,1,3,3-pentafluoropropane (R-245fa) in a MIL-101 MOF at various temperatures. To understand the stability of the nanofluid composed of MIL-101 particles, we performed molecular dynamics simulations to compute potentials of mean force between hypothetical MIL-101 fragments terminated with two different kinds of modulators in R-245fa and water. Our computed potentials of mean force results indicate that the MOF particles tend to disperse better in water than in R-245fa. The reasons for thismore » observation were analyzed and discussed. Our results agree with experimental results indicating that the employed potential models and modeling approaches provide good description of molecular interactions and the reliabilities. Work performed by LXD was supported by the U.S. Department of Energy (DOE), Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences. Work performed by HVRA, SKN, RKM, and PBM was supported by the Office of Energy Efficiency and Renewable Energy, Geothermal Technologies Program. Pacific Northwest National Laboratory is a multiprogram national laboratory operated for DOE by Battelle.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brown, W Michael; Kohlmeyer, Axel; Plimpton, Steven J
The use of accelerators such as graphics processing units (GPUs) has become popular in scientific computing applications due to their low cost, impressive floating-point capabilities, high memory bandwidth, and low electrical power requirements. Hybrid high-performance computers, machines with nodes containing more than one type of floating-point processor (e.g. CPU and GPU), are now becoming more prevalent due to these advantages. In this paper, we present a continuation of previous work implementing algorithms for using accelerators into the LAMMPS molecular dynamics software for distributed memory parallel hybrid machines. In our previous work, we focused on acceleration for short-range models with anmore » approach intended to harness the processing power of both the accelerator and (multi-core) CPUs. To augment the existing implementations, we present an efficient implementation of long-range electrostatic force calculation for molecular dynamics. Specifically, we present an implementation of the particle-particle particle-mesh method based on the work by Harvey and De Fabritiis. We present benchmark results on the Keeneland InfiniBand GPU cluster. We provide a performance comparison of the same kernels compiled with both CUDA and OpenCL. We discuss limitations to parallel efficiency and future directions for improving performance on hybrid or heterogeneous computers.« less
Quantum Molecular Dynamics Simulations of Nanotube Tip Assisted Reactions
NASA Technical Reports Server (NTRS)
Menon, Madhu
1998-01-01
In this report we detail the development and application of an efficient quantum molecular dynamics computational algorithm and its application to the nanotube-tip assisted reactions on silicon and diamond surfaces. The calculations shed interesting insights into the microscopic picture of tip surface interactions.
A conceptually and computationally simple method for the definition, display, quantification, and comparison of the shapes of three-dimensional mathematical molecular models is presented. Molecular or solvent-accessible volume and surface area can also be calculated. Algorithms, ...
Tools and procedures for visualization of proteins and other biomolecules.
Pan, Lurong; Aller, Stephen G
2015-04-01
Protein, peptides, and nucleic acids are biomolecules that drive biological processes in living organisms. An enormous amount of structural data for a large number of these biomolecules has been described with atomic precision in the form of structural "snapshots" that are freely available in public repositories. These snapshots can help explain how the biomolecules function, the nature of interactions between multi-molecular complexes, and even how small-molecule drugs can modulate the biomolecules for clinical benefits. Furthermore, these structural snapshots serve as inputs for sophisticated computer simulations to turn the biomolecules into moving, "breathing" molecular machines for understanding their dynamic properties in real-time computer simulations. In order for the researcher to take advantage of such a wealth of structural data, it is necessary to gain competency in the use of computer molecular visualization tools for exploring the structures and visualizing three-dimensional spatial representations. Here, we present protocols for using two common visualization tools--the Web-based Jmol and the stand-alone PyMOL package--as well as a few examples of other popular tools. Copyright © 2015 John Wiley & Sons, Inc.
Molecular Nanotechnology and Space Settlement
NASA Technical Reports Server (NTRS)
Globus, Al; Saini, Subhash (Technical Monitor)
1998-01-01
Atomically precise manipulation of matter is becoming increasingly common in laboratories around the world. As this control moves into aerospace systems, huge improvements in computers, high-strength materials, and other systems are expected. For example, studies suggest that it may be possible to build: 10(exp 18) MIPS computers, 10(exp 15) bytes/sq cm write once memory, $153-412/kg-of-cargo single- stage-to-orbit launch vehicles and active materials which sense their environment and react intelligently. All of NASA's enterprises should benefit significantly from molecular nanotechnology. Although the time may be measured in decades and the precise path to molecular nanotechnology is unclear, all paths (diamondoid, fullerene, self-assembly, biomolecular, etc.) will require very substantial computation. This talk will discuss fullerene nanotechnology and early work on hypothetical active materials consisting of large numbers of identical machines. The speaker will also discuss aerospace applications, particularly missions leading to widespread space settlement (e.g., small near-Earth - object retrieval). It is interesting to note that control of the tiny - individual atoms and molecules - may lead to colonization of the huge -first the solar system, then the galaxy.
On the origin of the electrostatic potential difference at a liquid-vacuum interface.
Harder, Edward; Roux, Benoît
2008-12-21
The microscopic origin of the interface potential calculated from computer simulations is elucidated by considering a simple model of molecules near an interface. The model posits that molecules are isotropically oriented and their charge density is Gaussian distributed. Molecules that have a charge density that is more negative toward their interior tend to give rise to a negative interface potential relative to the gaseous phase, while charge densities more positive toward their interior give rise to a positive interface potential. The interface potential for the model is compared to the interface potential computed from molecular dynamics simulations of the nonpolar vacuum-methane system and the polar vacuum-water interface system. The computed vacuum-methane interface potential from a molecular dynamics simulation (-220 mV) is captured with quantitative precision by the model. For the vacuum-water interface system, the model predicts a potential of -400 mV compared to -510 mV, calculated from a molecular dynamics simulation. The physical implications of this isotropic contribution to the interface potential is examined using the example of ion solvation in liquid methane.
Penchovsky, Robert
2012-10-19
Here we describe molecular implementations of integrated digital circuits, including a three-input AND logic gate, a two-input multiplexer, and 1-to-2 decoder using allosteric ribozymes. Furthermore, we demonstrate a multiplexer-decoder circuit. The ribozymes are designed to seek-and-destroy specific RNAs with a certain length by a fully computerized procedure. The algorithm can accurately predict one base substitution that alters the ribozyme's logic function. The ability to sense the length of RNA molecules enables single ribozymes to be used as platforms for multiple interactions. These ribozymes can work as integrated circuits with the functionality of up to five logic gates. The ribozyme design is universal since the allosteric and substrate domains can be altered to sense different RNAs. In addition, the ribozymes can specifically cleave RNA molecules with triplet-repeat expansions observed in genetic disorders such as oculopharyngeal muscular dystrophy. Therefore, the designer ribozymes can be employed for scaling up computing and diagnostic networks in the fields of molecular computing and diagnostics and RNA synthetic biology.
Ramalho, Teodorico C; de Castro, Alexandre A; Silva, Daniela R; Silva, Maria Cristina; Franca, Tanos C C; Bennion, Brian J; Kuca, Kamil
2016-01-01
The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and help in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.
Multi-Scale Computational Enzymology: Enhancing Our Understanding of Enzymatic Catalysis
Gherib, Rami; Dokainish, Hisham M.; Gauld, James W.
2014-01-01
Elucidating the origin of enzymatic catalysis stands as one the great challenges of contemporary biochemistry and biophysics. The recent emergence of computational enzymology has enhanced our atomistic-level description of biocatalysis as well the kinetic and thermodynamic properties of their mechanisms. There exists a diversity of computational methods allowing the investigation of specific enzymatic properties. Small or large density functional theory models allow the comparison of a plethora of mechanistic reactive species and divergent catalytic pathways. Molecular docking can model different substrate conformations embedded within enzyme active sites and determine those with optimal binding affinities. Molecular dynamics simulations provide insights into the dynamics and roles of active site components as well as the interactions between substrate and enzymes. Hybrid quantum mechanical/molecular mechanical (QM/MM) can model reactions in active sites while considering steric and electrostatic contributions provided by the surrounding environment. Using previous studies done within our group, on OvoA, EgtB, ThrRS, LuxS and MsrA enzymatic systems, we will review how these methods can be used either independently or cooperatively to get insights into enzymatic catalysis. PMID:24384841
2015-01-01
Web-based user interfaces to scientific applications are important tools that allow researchers to utilize a broad range of software packages with just an Internet connection and a browser.1 One such interface, CHARMMing (CHARMM interface and graphics), facilitates access to the powerful and widely used molecular software package CHARMM. CHARMMing incorporates tasks such as molecular structure analysis, dynamics, multiscale modeling, and other techniques commonly used by computational life scientists. We have extended CHARMMing’s capabilities to include a fragment-based docking protocol that allows users to perform molecular docking and virtual screening calculations either directly via the CHARMMing Web server or on computing resources using the self-contained job scripts generated via the Web interface. The docking protocol was evaluated by performing a series of “re-dockings” with direct comparison to top commercial docking software. Results of this evaluation showed that CHARMMing’s docking implementation is comparable to many widely used software packages and validates the use of the new CHARMM generalized force field for docking and virtual screening. PMID:25151852
Kussmann, Jörg; Ochsenfeld, Christian
2007-08-07
Details of a new density matrix-based formulation for calculating nuclear magnetic resonance chemical shifts at both Hartree-Fock and density functional theory levels are presented. For systems with a nonvanishing highest occupied molecular orbital-lowest unoccupied molecular orbital gap, the method allows us to reduce the asymptotic scaling order of the computational effort from cubic to linear, so that molecular systems with 1000 and more atoms can be tackled with today's computers. The key feature is a reformulation of the coupled-perturbed self-consistent field (CPSCF) theory in terms of the one-particle density matrix (D-CPSCF), which avoids entirely the use of canonical MOs. By means of a direct solution for the required perturbed density matrices and the adaptation of linear-scaling integral contraction schemes, the overall scaling of the computational effort is reduced to linear. A particular focus of our formulation is to ensure numerical stability when sparse-algebra routines are used to obtain an overall linear-scaling behavior.
Pevzner, Yuri; Frugier, Emilie; Schalk, Vinushka; Caflisch, Amedeo; Woodcock, H Lee
2014-09-22
Web-based user interfaces to scientific applications are important tools that allow researchers to utilize a broad range of software packages with just an Internet connection and a browser. One such interface, CHARMMing (CHARMM interface and graphics), facilitates access to the powerful and widely used molecular software package CHARMM. CHARMMing incorporates tasks such as molecular structure analysis, dynamics, multiscale modeling, and other techniques commonly used by computational life scientists. We have extended CHARMMing's capabilities to include a fragment-based docking protocol that allows users to perform molecular docking and virtual screening calculations either directly via the CHARMMing Web server or on computing resources using the self-contained job scripts generated via the Web interface. The docking protocol was evaluated by performing a series of "re-dockings" with direct comparison to top commercial docking software. Results of this evaluation showed that CHARMMing's docking implementation is comparable to many widely used software packages and validates the use of the new CHARMM generalized force field for docking and virtual screening.
Role of Open Source Tools and Resources in Virtual Screening for Drug Discovery.
Karthikeyan, Muthukumarasamy; Vyas, Renu
2015-01-01
Advancement in chemoinformatics research in parallel with availability of high performance computing platform has made handling of large scale multi-dimensional scientific data for high throughput drug discovery easier. In this study we have explored publicly available molecular databases with the help of open-source based integrated in-house molecular informatics tools for virtual screening. The virtual screening literature for past decade has been extensively investigated and thoroughly analyzed to reveal interesting patterns with respect to the drug, target, scaffold and disease space. The review also focuses on the integrated chemoinformatics tools that are capable of harvesting chemical data from textual literature information and transform them into truly computable chemical structures, identification of unique fragments and scaffolds from a class of compounds, automatic generation of focused virtual libraries, computation of molecular descriptors for structure-activity relationship studies, application of conventional filters used in lead discovery along with in-house developed exhaustive PTC (Pharmacophore, Toxicophores and Chemophores) filters and machine learning tools for the design of potential disease specific inhibitors. A case study on kinase inhibitors is provided as an example.
Elucidation of the Chromatographic Enantiomer Elution Order Through Computational Studies.
Sardella, Roccaldo; Ianni, Federica; Macchiarulo, Antonio; Pucciarini, Lucia; Carotti, Andrea; Natalini, Benedetto
2018-01-01
During the last twenty years, the interest towards the development of chiral compound has exponentially been increased. Indeed, the set-up of suitable asymmetric enantioselective synthesis protocols is currently one of the focuses of many pharmaceutical research projects. In this scenario, chiral HPLC separations have gained great importance as well, both for analytical- and preparative-scale applications, the latter devoted to the quantitative isolation of enantiopure compounds. Molecular modelling and quantum chemistry methods can be fruitfully applied to solve chirality related problems especially when enantiomerically pure reference standards are missing. In this framework, with the aim to explain the molecular basis of the enantioselective retention, we performed computational studies to rationalize the enantiomer elution order with both low- and high-molecular weight chiral selectors. Semi-empirical and quantum mechanical computational procedures were successfully applied in the domains of chiral ligand-exchange and chiral ion-exchange chromatography, as well as in studies dealing with the use of polysaccharide-based enantioresolving materials. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
NASA Astrophysics Data System (ADS)
Oberhauser, Nils; Nurisso, Alessandra; Carrupt, Pierre-Alain
2014-05-01
The molecular lipophilicity potential (MLP) is a well-established method to calculate and visualize lipophilicity on molecules. We are here introducing a new computational tool named MLP Tools, written in the programming language Python, and conceived as a free plugin for the popular open source molecular viewer PyMOL. The plugin is divided into several sub-programs which allow the visualization of the MLP on molecular surfaces, as well as in three-dimensional space in order to analyze lipophilic properties of binding pockets. The sub-program Log MLP also implements the virtual log P which allows the prediction of the octanol/water partition coefficients on multiple three-dimensional conformations of the same molecule. An implementation on the recently introduced MLP GOLD procedure, improving the GOLD docking performance in hydrophobic pockets, is also part of the plugin. In this article, all functions of the MLP Tools will be described through a few chosen examples.
NASA Technical Reports Server (NTRS)
Kim, Y.-C.; Demarque, P.; Guenther, D. B.
1991-01-01
Improvements to the Yale Rotating Stellar Evolution Code (YREC) by incorporating the Mihalas-Hummer-Daeppen equation of state, an improved opacity interpolation routine, and the effects of molecular opacities, calculated at Los Alamos, have been made. the effect of each of the improvements on the standard solar model has been tested independently by computing the corresponding solar nonradial oscillation frequencies. According to these tests, the Mihalas-Hummer-Daeppen equation of state has very little effect on the model's low l p-mode oscillation spectrum compared to the model using the existing analytical equation of state implemented in YREC. On the other hand, the molecular opacity does improve the model's oscillation spectrum. The effect of molecular opacity on the computed solar oscillation frequencies is much larger than that of the Mihalas-Hummer-Daeppen equation of state. together, the two improvements to the physics reduce the discrepancy with observations by 10 microHz for the low l modes.
A machine learning approach to computer-aided molecular design
NASA Astrophysics Data System (ADS)
Bolis, Giorgio; Di Pace, Luigi; Fabrocini, Filippo
1991-12-01
Preliminary results of a machine learning application concerning computer-aided molecular design applied to drug discovery are presented. The artificial intelligence techniques of machine learning use a sample of active and inactive compounds, which is viewed as a set of positive and negative examples, to allow the induction of a molecular model characterizing the interaction between the compounds and a target molecule. The algorithm is based on a twofold phase. In the first one — the specialization step — the program identifies a number of active/inactive pairs of compounds which appear to be the most useful in order to make the learning process as effective as possible and generates a dictionary of molecular fragments, deemed to be responsible for the activity of the compounds. In the second phase — the generalization step — the fragments thus generated are combined and generalized in order to select the most plausible hypothesis with respect to the sample of compounds. A knowledge base concerning physical and chemical properties is utilized during the inductive process.
Complex basis functions for molecular resonances: Methodology and applications
NASA Astrophysics Data System (ADS)
White, Alec; McCurdy, C. William; Head-Gordon, Martin
The computation of positions and widths of metastable electronic states is a challenge for molecular electronic structure theory because, in addition to the difficulty of the many-body problem, such states obey scattering boundary conditions. These resonances cannot be addressed with naïve application of traditional bound state electronic structure theory. Non-Hermitian electronic structure methods employing complex basis functions is one way that we may rigorously treat resonances within the framework of traditional electronic structure theory. In this talk, I will discuss our recent work in this area including the methodological extension from single determinant SCF-based approaches to highly correlated levels of wavefunction-based theory such as equation of motion coupled cluster and many-body perturbation theory. These approaches provide a hierarchy of theoretical methods for the computation of positions and widths of molecular resonances. Within this framework, we may also examine properties of resonances including the dependence of these parameters on molecular geometry. Some applications of these methods to temporary anions and dianions will also be discussed.
Investigation for Molecular Attraction Impact Between Contacting Surfaces in Micro-Gears
NASA Astrophysics Data System (ADS)
Yang, Ping; Li, Xialong; Zhao, Yanfang; Yang, Haiying; Wang, Shuting; Yang, Jianming
2013-10-01
The aim of this research work is to provide a systematic method to perform molecular attraction impact between contacting surfaces in micro-gear train. This method is established by integrating involute profile analysis and molecular dynamics simulation. A mathematical computation of micro-gear involute is presented based on geometrical properties, Taylor expression and Hamaker assumption. In the meantime, Morse potential function and the cut-off radius are introduced with a molecular dynamics simulation. So a hybrid computational method for the Van Der Waals force between the contacting faces in micro-gear train is developed. An example is illustrated to show the performance of this method. The results show that the change of Van Der Waals force in micro-gear train has a nonlinear characteristic with parameters change such as the modulus of the gear and the tooth number of gear etc. The procedure implies a potential feasibility that we can control the Van Der Waals force by adjusting the manufacturing parameters for gear train design.
ExpoCast: Exposure Science for Prioritization and Toxicity Testing (T)
The US EPA National Center for Computational Toxicology (NCCT) has a mission to integrate modern computing and information technology with molecular biology to improve Agency prioritization of data requirements and risk assessment of chemicals. Recognizing the critical need for ...
Computer program for calculation of ideal gas thermodynamic data
NASA Technical Reports Server (NTRS)
Gordon, S.; Mc Bride, B. J.
1968-01-01
Computer program calculates ideal gas thermodynamic properties for any species for which molecular constant data is available. Partial functions and derivatives from formulas based on statistical mechanics are provided by the program which is written in FORTRAN 4 and MAP.
Materials-by-design: computation, synthesis, and characterization from atoms to structures
NASA Astrophysics Data System (ADS)
Yeo, Jingjie; Jung, Gang Seob; Martín-Martínez, Francisco J.; Ling, Shengjie; Gu, Grace X.; Qin, Zhao; Buehler, Markus J.
2018-05-01
In the 50 years that succeeded Richard Feynman’s exposition of the idea that there is ‘plenty of room at the bottom’ for manipulating individual atoms for the synthesis and manufacturing processing of materials, the materials-by-design paradigm is being developed gradually through synergistic integration of experimental material synthesis and characterization with predictive computational modeling and optimization. This paper reviews how this paradigm creates the possibility to develop materials according to specific, rational designs from the molecular to the macroscopic scale. We discuss promising techniques in experimental small-scale material synthesis and large-scale fabrication methods to manipulate atomistic or macroscale structures, which can be designed by computational modeling. These include recombinant protein technology to produce peptides and proteins with tailored sequences encoded by recombinant DNA, self-assembly processes induced by conformational transition of proteins, additive manufacturing for designing complex structures, and qualitative and quantitative characterization of materials at different length scales. We describe important material characterization techniques using numerous methods of spectroscopy and microscopy. We detail numerous multi-scale computational modeling techniques that complements these experimental techniques: DFT at the atomistic scale; fully atomistic and coarse-grain molecular dynamics at the molecular to mesoscale; continuum modeling at the macroscale. Additionally, we present case studies that utilize experimental and computational approaches in an integrated manner to broaden our understanding of the properties of two-dimensional materials and materials based on silk and silk-elastin-like proteins.
Venko, Katja; Roy Choudhury, A; Novič, Marjana
2017-01-01
The structural and functional details of transmembrane proteins are vastly underexplored, mostly due to experimental difficulties regarding their solubility and stability. Currently, the majority of transmembrane protein structures are still unknown and this present a huge experimental and computational challenge. Nowadays, thanks to X-ray crystallography or NMR spectroscopy over 3000 structures of membrane proteins have been solved, among them only a few hundred unique ones. Due to the vast biological and pharmaceutical interest in the elucidation of the structure and the functional mechanisms of transmembrane proteins, several computational methods have been developed to overcome the experimental gap. If combined with experimental data the computational information enables rapid, low cost and successful predictions of the molecular structure of unsolved proteins. The reliability of the predictions depends on the availability and accuracy of experimental data associated with structural information. In this review, the following methods are proposed for in silico structure elucidation: sequence-dependent predictions of transmembrane regions, predictions of transmembrane helix-helix interactions, helix arrangements in membrane models, and testing their stability with molecular dynamics simulations. We also demonstrate the usage of the computational methods listed above by proposing a model for the molecular structure of the transmembrane protein bilitranslocase. Bilitranslocase is bilirubin membrane transporter, which shares similar tissue distribution and functional properties with some of the members of the Organic Anion Transporter family and is the only member classified in the Bilirubin Transporter Family. Regarding its unique properties, bilitranslocase is a potentially interesting drug target.
Molecular Imaging and Precision Medicine in Prostate Cancer.
Ceci, Francesco; Fiorentino, Michelangelo; Castellucci, Paolo; Fanti, Stefano
2017-01-01
The aim of the present review is to discuss about the role of new probes for molecular imaging in the evaluation of prostate cancer (PCa). This review focuses particularly on the role of new promising radiotracers for the molecular imaging with PET/computed tomography in the detection of PCa recurrence. The role of these new imaging techniques to guide lesion-target therapies and the potential application of these molecular probes as theranostics agents is discussed. Finally, the molecular mechanisms underlying resistance to castration in PCa and the maintenance of active androgen receptor are discussed. Copyright © 2016 Elsevier Inc. All rights reserved.
Laboratory Sequence in Computational Methods for Introductory Chemistry
NASA Astrophysics Data System (ADS)
Cody, Jason A.; Wiser, Dawn C.
2003-07-01
A four-exercise laboratory sequence for introductory chemistry integrating hands-on, student-centered experience with computer modeling has been designed and implemented. The progression builds from exploration of molecular shapes to intermolecular forces and the impact of those forces on chemical separations made with gas chromatography and distillation. The sequence ends with an exploration of molecular orbitals. The students use the computers as a tool; they build the molecules, submit the calculations, and interpret the results. Because of the construction of the sequence and its placement spanning the semester break, good laboratory notebook practices are reinforced and the continuity of course content and methods between semesters is emphasized. The inclusion of these techniques in the first year of chemistry has had a positive impact on student perceptions and student learning.
Ab Initio Reactive Computer Aided Molecular Design
DOE Office of Scientific and Technical Information (OSTI.GOV)
Martínez, Todd J.
Few would dispute that theoretical chemistry tools can now provide keen insights into chemical phenomena. Yet the holy grail of efficient and reliable prediction of complex reactivity has remained elusive. Fortunately, recent advances in electronic structure theory based on the concepts of both element- and rank-sparsity, coupled with the emergence of new highly parallel computer architectures, have led to a significant increase in the time and length scales which can be simulated using first principles molecular dynamics. This then opens the possibility of new discovery-based approaches to chemical reactivity, such as the recently proposed ab initio nanoreactor. Here, we arguemore » that due to these and other recent advances, the holy grail of computational discovery for complex chemical reactivity is rapidly coming within our reach.« less
Ab Initio Reactive Computer Aided Molecular Design
Martínez, Todd J.
2017-03-21
Few would dispute that theoretical chemistry tools can now provide keen insights into chemical phenomena. Yet the holy grail of efficient and reliable prediction of complex reactivity has remained elusive. Fortunately, recent advances in electronic structure theory based on the concepts of both element- and rank-sparsity, coupled with the emergence of new highly parallel computer architectures, have led to a significant increase in the time and length scales which can be simulated using first principles molecular dynamics. This then opens the possibility of new discovery-based approaches to chemical reactivity, such as the recently proposed ab initio nanoreactor. Here, we arguemore » that due to these and other recent advances, the holy grail of computational discovery for complex chemical reactivity is rapidly coming within our reach.« less
ERIC Educational Resources Information Center
Carlotto, Silvia; Zerbetto, Mirco
2014-01-01
We propose an articulated computational experiment in which both quantum mechanics (QM) and molecular mechanics (MM) methods are employed to investigate environment effects on the free energy surface for the backbone dihedral angles rotation of the small dipeptide N-Acetyl-N'-methyl-L-alanylamide. This computation exercise is appropriate for an…
Computational Enzyme Design: Advances, hurdles and possible ways forward
Linder, Mats
2012-01-01
This mini review addresses recent developments in computational enzyme design. Successful protocols as well as known issues and limitations are discussed from an energetic perspective. It will be argued that improved results can be obtained by including a dynamic treatment in the design protocol. Finally, a molecular dynamics-based approach for evaluating and refining computational designs is presented. PMID:24688650
Supercomputer applications in molecular modeling.
Gund, T M
1988-01-01
An overview of the functions performed by molecular modeling is given. Molecular modeling techniques benefiting from supercomputing are described, namely, conformation, search, deriving bioactive conformations, pharmacophoric pattern searching, receptor mapping, and electrostatic properties. The use of supercomputers for problems that are computationally intensive, such as protein structure prediction, protein dynamics and reactivity, protein conformations, and energetics of binding is also examined. The current status of supercomputing and supercomputer resources are discussed.
Development of a Computational Assay for the Estrogen Receptor
2006-07-01
University Ashley Deline, Senior Thesis in chemistry, " Molecular Dynamic Simulations of a Glycoform and its Constituent Parts Related to Rheumatoid Arthritis...involves running a long molecular dynamics (MD) simulation of the uncoupled receptor in order to sample the protein’s unique conformations. The second...Receptor binding domain. * Performed several long molecular dynamics simulations (800 ps - 3 ns) on the ligand-ER system using ligands with known
DOE Office of Scientific and Technical Information (OSTI.GOV)
Murray, J.S.; Grice, M.E.; Politzer, P.
1990-01-01
The electrostatic potential V(r) that the nuclei and electrons of a molecule create in the surrounding space is well established as a guide in the study of molecular reactivity, and particularly, of biological recognition processes. Its rigorous computation is, however, very demanding of computer time for large molecules, such as those of interest in recognition interactions. The authors have accordingly investigated the use of an approximate finite multicenter multipole expansion technique to determine its applicability for producing reliable electrostatic potentials of dibenzo-p-dioxins and related molecules, with significantly reduced amounts of computer time, at distances of interest in recognition studies. Amore » comparative analysis of the potentials of three dibenzo-q-dioxins and a substituted naphthalene molecule computed using both the multipole expansion technique and GAUSSIAN 82 at the STO-5G level has been carried out. Overall they found that regions of negative and positive V(r) at 1.75 A above the molecular plane are very well reproduced by the multipole expansion technique, with up to a twenty-fold improvement in computer time.« less
Li, Jinhui; Wan, Haitong; Zhang, Hong; Tian, Mei
2011-09-01
Traditional Chinese medicine (TCM), which is fundamentally different from Western medicine, has been widely investigated using various approaches. Cellular- or molecular-based imaging has been used to investigate and illuminate the various challenges identified and progress made using therapeutic methods in TCM. Insight into the processes of TCM at the cellular and molecular changes and the ability to image these processes will enhance our understanding of various diseases of TCM and will provide new tools to diagnose and treat patients. Various TCM therapies including herbs and formulations, acupuncture and moxibustion, massage, Gua Sha, and diet therapy have been analyzed using positron emission tomography, single photon emission computed tomography, functional magnetic resonance imaging and ultrasound and optical imaging. These imaging tools have kept pace with developments in molecular biology, nuclear medicine, and computer technology. We provide an overview of recent developments in demystifying ancient knowledge - like the power of energy flow and blood flow meridians, and serial naturopathies - which are essential to visually and vividly recognize the body using modern technology. In TCM, treatment can be individualized in a holistic or systematic view that is consistent with molecular imaging technologies. Future studies might include using molecular imaging in conjunction with TCM to easily diagnose or monitor patients naturally and noninvasively. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Molecular Docking and Drug Discovery in β-Adrenergic Receptors.
Vilar, Santiago; Sobarzo-Sanchez, Eduardo; Santana, Lourdes; Uriarte, Eugenio
2017-01-01
Evolution in computer engineering, availability of increasing amounts of data and the development of new and fast docking algorithms and software have led to improved molecular simulations with crucial applications in virtual high-throughput screening and drug discovery. Moreover, analysis of protein-ligand recognition through molecular docking has become a valuable tool in drug design. In this review, we focus on the applicability of molecular docking on a particular class of G protein-coupled receptors: the β-adrenergic receptors, which are relevant targets in clinic for the treatment of asthma and cardiovascular diseases. We describe the binding site in β-adrenergic receptors to understand key factors in ligand recognition along with the proteins activation process. Moreover, we focus on the discovery of new lead compounds that bind the receptors, on the evaluation of virtual screening using the active/ inactive binding site states, and on the structural optimization of known families of binders to improve β-adrenergic affinity. We also discussed strengths and challenges related to the applicability of molecular docking in β-adrenergic receptors. Molecular docking is a valuable technique in computational chemistry to deeply analyze ligand recognition and has led to important breakthroughs in drug discovery and design in the field of β-adrenergic receptors. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
NASA Astrophysics Data System (ADS)
Leenaraj, D. R.; Hubert Joe, I.
2017-06-01
Spectral features of non-opioid analgesic drug flupirtine have been explored by the Fourier transform infrared, Raman and Nuclear magnetic resonance spectroscopic techniques combined with density functional theory computations. The bioactive conformer of flupirtine is stabilized by an intramolecular Csbnd H⋯N hydrogen bonding resulting by the steric strain of hydrogen atoms. Natural bond orbital and natural population analysis support this result. The charge redistribution also has been analyzed. Antimicrobial activities of flupirtine have been screened by agar well disc diffusion and molecular docking methods, which exposes the importance of triaminopyridine in flupirtine.
Golas, Ewa I; Czaplewski, Cezary
2014-09-01
This work theoretically investigates the mechanical properties of a novel silk-derived biopolymer as polymerized in silico from sericin and elastin-like monomers. Molecular Dynamics simulations and Steered Molecular Dynamics were the principal computational methods used, the latter of which applies an external force onto the system and thereby enables an observation of its response to stress. The models explored herein are single-molecule approximations, and primarily serve as tools in a rational design process for the preliminary assessment of properties in a new material candidate. © 2014 Wiley Periodicals, Inc.
eScience for molecular-scale simulations and the eMinerals project.
Salje, E K H; Artacho, E; Austen, K F; Bruin, R P; Calleja, M; Chappell, H F; Chiang, G-T; Dove, M T; Frame, I; Goodwin, A L; Kleese van Dam, K; Marmier, A; Parker, S C; Pruneda, J M; Todorov, I T; Trachenko, K; Tyer, R P; Walker, A M; White, T O H
2009-03-13
We review the work carried out within the eMinerals project to develop eScience solutions that facilitate a new generation of molecular-scale simulation work. Technological developments include integration of compute and data systems, developing of collaborative frameworks and new researcher-friendly tools for grid job submission, XML data representation, information delivery, metadata harvesting and metadata management. A number of diverse science applications will illustrate how these tools are being used for large parameter-sweep studies, an emerging type of study for which the integration of computing, data and collaboration is essential.
Direct simulation of high-vorticity gas flows
NASA Technical Reports Server (NTRS)
Bird, G. A.
1987-01-01
The computational limitations associated with the molecular dynamics (MD) method and the direct simulation Monte Carlo (DSMC) method are reviewed in the context of the computation of dilute gas flows with high vorticity. It is concluded that the MD method is generally limited to the dense gas case in which the molecular diameter is one-tenth or more of the mean free path. It is shown that the cell size in DSMC calculations should be small in comparison with the mean free path, and that this may be facilitated by a new subcell procedure for the selection of collision partners.
Brain transcriptome atlases: a computational perspective.
Mahfouz, Ahmed; Huisman, Sjoerd M H; Lelieveldt, Boudewijn P F; Reinders, Marcel J T
2017-05-01
The immense complexity of the mammalian brain is largely reflected in the underlying molecular signatures of its billions of cells. Brain transcriptome atlases provide valuable insights into gene expression patterns across different brain areas throughout the course of development. Such atlases allow researchers to probe the molecular mechanisms which define neuronal identities, neuroanatomy, and patterns of connectivity. Despite the immense effort put into generating such atlases, to answer fundamental questions in neuroscience, an even greater effort is needed to develop methods to probe the resulting high-dimensional multivariate data. We provide a comprehensive overview of the various computational methods used to analyze brain transcriptome atlases.
1990-01-01
expert systems, "intelligent" computer-aided instruction , symbolic learning . These aspects will be discussed, focusing on the specific problems the...VLSI chips) according to preliminary specifications. Finally ES are also used in computer-aided instruction (CAI) due to their ability of... instructions to process controllers), academic teaching (for mathematics , physics, foreign language, etc.). Domains of application The different
Early years of Computational Statistical Mechanics
NASA Astrophysics Data System (ADS)
Mareschal, Michel
2018-05-01
Evidence that a model of hard spheres exhibits a first-order solid-fluid phase transition was provided in the late fifties by two new numerical techniques known as Monte Carlo and Molecular Dynamics. This result can be considered as the starting point of computational statistical mechanics: at the time, it was a confirmation of a counter-intuitive (and controversial) theoretical prediction by J. Kirkwood. It necessitated an intensive collaboration between the Los Alamos team, with Bill Wood developing the Monte Carlo approach, and the Livermore group, where Berni Alder was inventing Molecular Dynamics. This article tells how it happened.
Ji, Jiayuan; Zhao, Lingling; Tao, Lu; Lin, Shangchao
2017-06-29
In CO 2 geological storage, the interfacial tension (IFT) between supercritical CO 2 and brine is critical for the storage capacitance design to prevent CO 2 leakage. IFT relies not only on the interfacial molecule properties but also on the environmental conditions at different storage sites. In this paper, supercritical CO 2 -NaCl solution systems are modeled at 343-373 K and 6-35 MPa under the salinity of 1.89 mol/L using molecular dynamics simulations. After computing and comparing the molecular density profile across the interface, the atomic radial distribution function, the molecular orientation distribution, the molecular Gibbs surface excess (derived from the molecular density profile), and the CO 2 -hydrate number density under the above environmental conditions, we confirm that only the molecular Gibbs surface excess of CO 2 molecules and the CO 2 -hydrate number density correlate strongly with the temperature- and pressure-dependent IFTs. We also compute the populations of two distinct CO 2 -hydrate structures (T-type and H-type) and attribute the observed dependence of IFTs to the dominance of the more stable, surfactant-like T-type CO 2 -hydrates at the interface. On the basis of these new molecular mechanisms behind IFT variations, this study could guide the rational design of suitable injecting environmental pressure and temperature conditions. We believe that the above two molecular-level metrics (Gibbs surface excess and hydrate number density) are of great fundamental importance for understanding the supercritical CO 2 -water interface and engineering applications in geological CO 2 storage.
Jiang, Yuyi; Shao, Zhiqing; Guo, Yi
2014-01-01
A complex computing problem can be solved efficiently on a system with multiple computing nodes by dividing its implementation code into several parallel processing modules or tasks that can be formulated as directed acyclic graph (DAG) problems. The DAG jobs may be mapped to and scheduled on the computing nodes to minimize the total execution time. Searching an optimal DAG scheduling solution is considered to be NP-complete. This paper proposed a tuple molecular structure-based chemical reaction optimization (TMSCRO) method for DAG scheduling on heterogeneous computing systems, based on a very recently proposed metaheuristic method, chemical reaction optimization (CRO). Comparing with other CRO-based algorithms for DAG scheduling, the design of tuple reaction molecular structure and four elementary reaction operators of TMSCRO is more reasonable. TMSCRO also applies the concept of constrained critical paths (CCPs), constrained-critical-path directed acyclic graph (CCPDAG) and super molecule for accelerating convergence. In this paper, we have also conducted simulation experiments to verify the effectiveness and efficiency of TMSCRO upon a large set of randomly generated graphs and the graphs for real world problems. PMID:25143977
Jiang, Yuyi; Shao, Zhiqing; Guo, Yi
2014-01-01
A complex computing problem can be solved efficiently on a system with multiple computing nodes by dividing its implementation code into several parallel processing modules or tasks that can be formulated as directed acyclic graph (DAG) problems. The DAG jobs may be mapped to and scheduled on the computing nodes to minimize the total execution time. Searching an optimal DAG scheduling solution is considered to be NP-complete. This paper proposed a tuple molecular structure-based chemical reaction optimization (TMSCRO) method for DAG scheduling on heterogeneous computing systems, based on a very recently proposed metaheuristic method, chemical reaction optimization (CRO). Comparing with other CRO-based algorithms for DAG scheduling, the design of tuple reaction molecular structure and four elementary reaction operators of TMSCRO is more reasonable. TMSCRO also applies the concept of constrained critical paths (CCPs), constrained-critical-path directed acyclic graph (CCPDAG) and super molecule for accelerating convergence. In this paper, we have also conducted simulation experiments to verify the effectiveness and efficiency of TMSCRO upon a large set of randomly generated graphs and the graphs for real world problems.
Workflow Management Systems for Molecular Dynamics on Leadership Computers
NASA Astrophysics Data System (ADS)
Wells, Jack; Panitkin, Sergey; Oleynik, Danila; Jha, Shantenu
Molecular Dynamics (MD) simulations play an important role in a range of disciplines from Material Science to Biophysical systems and account for a large fraction of cycles consumed on computing resources. Increasingly science problems require the successful execution of ''many'' MD simulations as opposed to a single MD simulation. There is a need to provide scalable and flexible approaches to the execution of the workload. We present preliminary results on the Titan computer at the Oak Ridge Leadership Computing Facility that demonstrate a general capability to manage workload execution agnostic of a specific MD simulation kernel or execution pattern, and in a manner that integrates disparate grid-based and supercomputing resources. Our results build upon our extensive experience of distributed workload management in the high-energy physics ATLAS project using PanDA (Production and Distributed Analysis System), coupled with recent conceptual advances in our understanding of workload management on heterogeneous resources. We will discuss how we will generalize these initial capabilities towards a more production level service on DOE leadership resources. This research is sponsored by US DOE/ASCR and used resources of the OLCF computing facility.
Constructing Smart Protocells with Built-In DNA Computational Core to Eliminate Exogenous Challenge.
Lyu, Yifan; Wu, Cuichen; Heinke, Charles; Han, Da; Cai, Ren; Teng, I-Ting; Liu, Yuan; Liu, Hui; Zhang, Xiaobing; Liu, Qiaoling; Tan, Weihong
2018-06-06
A DNA reaction network is like a biological algorithm that can respond to "molecular input signals", such as biological molecules, while the artificial cell is like a microrobot whose function is powered by the encapsulated DNA reaction network. In this work, we describe the feasibility of using a DNA reaction network as the computational core of a protocell, which will perform an artificial immune response in a concise way to eliminate a mimicked pathogenic challenge. Such a DNA reaction network (RN)-powered protocell can realize the connection of logical computation and biological recognition due to the natural programmability and biological properties of DNA. Thus, the biological input molecules can be easily involved in the molecular computation and the computation process can be spatially isolated and protected by artificial bilayer membrane. We believe the strategy proposed in the current paper, i.e., using DNA RN to power artificial cells, will lay the groundwork for understanding the basic design principles of DNA algorithm-based nanodevices which will, in turn, inspire the construction of artificial cells, or protocells, that will find a place in future biomedical research.
Morrison, Adrian F; Herbert, John M
2017-06-14
Recently, we introduced an ab initio version of the Frenkel-Davydov exciton model for computing excited-state properties of molecular crystals and aggregates. Within this model, supersystem excited states are approximated as linear combinations of excitations localized on molecular sites, and the electronic Hamiltonian is constructed and diagonalized in a direct-product basis of non-orthogonal configuration state functions computed for isolated fragments. Here, we derive and implement analytic derivative couplings for this model, including nuclear derivatives of the natural transition orbital and symmetric orthogonalization transformations that are part of the approximation. Nuclear derivatives of the exciton Hamiltonian's matrix elements, required in order to compute the nonadiabatic couplings, are equivalent to the "Holstein" and "Peierls" exciton/phonon couplings that are widely discussed in the context of model Hamiltonians for energy and charge transport in organic photovoltaics. As an example, we compute the couplings that modulate triplet exciton transport in crystalline tetracene, which is relevant in the context of carrier diffusion following singlet exciton fission.
21st International Conference on DNA Computing and Molecular Programming: 8.1 Biochemistry
include information storage and biological applications of DNA systems, biomolecular chemical reaction networks, applications of self -assembled DNA...nanostructures, tile self -assembly and computation, principles and models of self -assembly, and strand displacement and biomolecular circuits. The fund
DockScreen: A database of in silico biomolecular interactions to support computational toxicology
We have developed DockScreen, a database of in silico biomolecular interactions designed to enable rational molecular toxicological insight within a computational toxicology framework. This database is composed of chemical/target (receptor and enzyme) binding scores calculated by...
SELDI PROTEINCHIP-BASED LIVER BIOMARKERS IN FUNGICIDE EXPOSED ZEBRAFISH
The research presented here is part of a three-phased small fish computational toxicology project using a combination of 1) whole organism endpoints, 2) genomic, proteomic, and metabolomic approaches, and 3) computational modeling to (a) identify new molecular biomarkers of expos...
COMPUTATIONAL ELECTROCHEMISTRY: AQUEOUS ONE-ELECTRON OXIDATION POTENTIALS FOR SUBSTITUTED ANILINES
Semiempirical molecular orbital theory and density functional theory are used to compute one-electron oxidation potentials for aniline and a set of 21 mono- and di-substituted anilines in aqueous solution. Linear relationships between theoretical predictions and experiment are co...
A Review of Computational Methods in Materials Science: Examples from Shock-Wave and Polymer Physics
Steinhauser, Martin O.; Hiermaier, Stefan
2009-01-01
This review discusses several computational methods used on different length and time scales for the simulation of material behavior. First, the importance of physical modeling and its relation to computer simulation on multiscales is discussed. Then, computational methods used on different scales are shortly reviewed, before we focus on the molecular dynamics (MD) method. Here we survey in a tutorial-like fashion some key issues including several MD optimization techniques. Thereafter, computational examples for the capabilities of numerical simulations in materials research are discussed. We focus on recent results of shock wave simulations of a solid which are based on two different modeling approaches and we discuss their respective assets and drawbacks with a view to their application on multiscales. Then, the prospects of computer simulations on the molecular length scale using coarse-grained MD methods are covered by means of examples pertaining to complex topological polymer structures including star-polymers, biomacromolecules such as polyelectrolytes and polymers with intrinsic stiffness. This review ends by highlighting new emerging interdisciplinary applications of computational methods in the field of medical engineering where the application of concepts of polymer physics and of shock waves to biological systems holds a lot of promise for improving medical applications such as extracorporeal shock wave lithotripsy or tumor treatment. PMID:20054467
Computing pKa Values in Different Solvents by Electrostatic Transformation.
Rossini, Emanuele; Netz, Roland R; Knapp, Ernst-Walter
2016-07-12
We introduce a method that requires only moderate computational effort to compute pKa values of small molecules in different solvents with an average accuracy of better than 0.7 pH units. With a known pKa value in one solvent, the electrostatic transform method computes the pKa value in any other solvent if the proton solvation energy is known in both considered solvents. To apply the electrostatic transform method to a molecule, the electrostatic solvation energies of the protonated and deprotonated molecular species are computed in the two considered solvents using a dielectric continuum to describe the solvent. This is demonstrated for 30 molecules belonging to 10 different molecular families by considering 77 measured pKa values in 4 different solvents: water, acetonitrile, dimethyl sulfoxide, and methanol. The electrostatic transform method can be applied to any other solvent if the proton solvation energy is known. It is exclusively based on physicochemical principles, not using any empirical fetch factors or explicit solvent molecules, to obtain agreement with measured pKa values and is therefore ready to be generalized to other solute molecules and solvents. From the computed pKa values, we obtained relative proton solvation energies, which agree very well with the proton solvation energies computed recently by ab initio methods, and used these energies in the present study.
NASA Astrophysics Data System (ADS)
Alphonsa, A. Therasa; Loganathan, C.; Anand, S. Athavan Alias; Kabilan, S.
2016-02-01
We have synthesized (E)-1-(2, 6-bis (4-methoxyphenyl)-3, 3-dimethylpiperidine-4-ylidene)-2-(3-(3, 5-dimethyl-1H-pyrazol-1-yl) pyrazin-2-yl) hydrazine (PM6). It was characterized using FT-IR, FT-Raman, 1H NMR, 13C NMR techniques. To interpret the experimental data, ab initio computations of the vibrational frequencies were carried out using the Gaussian 09 program followed by the full optimizations done using Density Functional Theory (DFT) at B3LYP/6-311 G(d,p) level. The combined use of experiments and computations allowed a firm assignment of the majority of observed bands for the compound. The calculated stretching frequencies have been found to be in good agreement with the experimental frequencies. The electronic and charge transfer properties have been explained on the basis of highest occupied molecular orbitals (HOMOs), lowest unoccupied molecular orbitals (LUMOs) and density of states (DOS). The absorption spectra have been computed by using time dependent density functional theory (TD-DFT). 1H and 13C NMR spectra were recorded and 1H and 13C NMR chemical shifts of the molecule were calculated using the gauge independent atomic orbital (GIAO) method. From the optimized geometry of the molecule, molecular electrostatic potential (MEP) distribution, frontier molecular orbitals (FMOs) of the title compound have been calculated in the ground state theoretically. The theoretical results showed good agreement with the experimental values.
Fan, Feng; Cheng, Jiagao; Li, Zhong; Xu, Xiaoyong; Qian, Xuhong
2010-02-01
Molecular aggregation state of bioactive compounds plays a key role in its bio-interactive procedure. In this article, based on the structure information of dimers, the simplest model of molecular aggregation state, and combined with solvational computation, total four descriptors (DeltaV, MR2, DeltaE(1), and DeltaE(2)) were calculated for QSAR study of a novel insect-growth regulator, N-(5-phenyl-1,3,4-oxadiazol-2-yl)-N'-benzoyl urea. Two QSAR models were constructed with r(2) = 0.671, q(2) = 0.516 and r(2) = 0.816, q(2) = 0.695, respectively. It implicates that the bioactivity may strongly depend on the characters of molecular aggregation state, especially on the dimeric transport ability from oil phase to water phase. Copyright 2009 Wiley Periodicals, Inc.
Lu, Jiao Yang; Zhang, Xin Xing; Huang, Wei Tao; Zhu, Qiu Yan; Ding, Xue Zhi; Xia, Li Qiu; Luo, Hong Qun; Li, Nian Bing
2017-09-19
The most serious and yet unsolved problems of molecular logic computing consist in how to connect molecular events in complex systems into a usable device with specific functions and how to selectively control branchy logic processes from the cascading logic systems. This report demonstrates that a Boolean logic tree is utilized to organize and connect "plug and play" chemical events DNA, nanomaterials, organic dye, biomolecule, and denaturant for developing the dual-signal electrochemical evolution aptasensor system with good resettability for amplification detection of thrombin, controllable and selectable three-state logic computation, and keypad lock security operation. The aptasensor system combines the merits of DNA-functionalized nanoamplification architecture and simple dual-signal electroactive dye brilliant cresyl blue for sensitive and selective detection of thrombin with a wide linear response range of 0.02-100 nM and a detection limit of 1.92 pM. By using these aforementioned chemical events as inputs and the differential pulse voltammetry current changes at different voltages as dual outputs, a resettable three-input biomolecular keypad lock based on sequential logic is established. Moreover, the first example of controllable and selectable three-state molecular logic computation with active-high and active-low logic functions can be implemented and allows the output ports to assume a high impediment or nothing (Z) state in addition to the 0 and 1 logic levels, effectively controlling subsequent branchy logic computation processes. Our approach is helpful in developing the advanced controllable and selectable logic computing and sensing system in large-scale integration circuits for application in biomedical engineering, intelligent sensing, and control.
An Introduction to Programming for Bioscientists: A Python-Based Primer
Mura, Cameron
2016-01-01
Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in molecular biology, biochemistry, and other biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware, software, and algorithms. These advances have influenced, and even engendered, a phenomenal array of bioscience fields, including molecular evolution and bioinformatics; genome-, proteome-, transcriptome- and metabolome-wide experimental studies; structural genomics; and atomistic simulations of cellular-scale molecular assemblies as large as ribosomes and intact viruses. In short, much of post-genomic biology is increasingly becoming a form of computational biology. The ability to design and write computer programs is among the most indispensable skills that a modern researcher can cultivate. Python has become a popular programming language in the biosciences, largely because (i) its straightforward semantics and clean syntax make it a readily accessible first language; (ii) it is expressive and well-suited to object-oriented programming, as well as other modern paradigms; and (iii) the many available libraries and third-party toolkits extend the functionality of the core language into virtually every biological domain (sequence and structure analyses, phylogenomics, workflow management systems, etc.). This primer offers a basic introduction to coding, via Python, and it includes concrete examples and exercises to illustrate the language’s usage and capabilities; the main text culminates with a final project in structural bioinformatics. A suite of Supplemental Chapters is also provided. Starting with basic concepts, such as that of a “variable,” the Chapters methodically advance the reader to the point of writing a graphical user interface to compute the Hamming distance between two DNA sequences. PMID:27271528
Efficient grid-based techniques for density functional theory
NASA Astrophysics Data System (ADS)
Rodriguez-Hernandez, Juan Ignacio
Understanding the chemical and physical properties of molecules and materials at a fundamental level often requires quantum-mechanical models for these substance's electronic structure. This type of many body quantum mechanics calculation is computationally demanding, hindering its application to substances with more than a few hundreds atoms. The supreme goal of many researches in quantum chemistry---and the topic of this dissertation---is to develop more efficient computational algorithms for electronic structure calculations. In particular, this dissertation develops two new numerical integration techniques for computing molecular and atomic properties within conventional Kohn-Sham-Density Functional Theory (KS-DFT) of molecular electronic structure. The first of these grid-based techniques is based on the transformed sparse grid construction. In this construction, a sparse grid is generated in the unit cube and then mapped to real space according to the pro-molecular density using the conditional distribution transformation. The transformed sparse grid was implemented in program deMon2k, where it is used as the numerical integrator for the exchange-correlation energy and potential in the KS-DFT procedure. We tested our grid by computing ground state energies, equilibrium geometries, and atomization energies. The accuracy on these test calculations shows that our grid is more efficient than some previous integration methods: our grids use fewer points to obtain the same accuracy. The transformed sparse grids were also tested for integrating, interpolating and differentiating in different dimensions (n = 1,2,3,6). The second technique is a grid-based method for computing atomic properties within QTAIM. It was also implemented in deMon2k. The performance of the method was tested by computing QTAIM atomic energies, charges, dipole moments, and quadrupole moments. For medium accuracy, our method is the fastest one we know of.
An Introduction to Programming for Bioscientists: A Python-Based Primer.
Ekmekci, Berk; McAnany, Charles E; Mura, Cameron
2016-06-01
Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in molecular biology, biochemistry, and other biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware, software, and algorithms. These advances have influenced, and even engendered, a phenomenal array of bioscience fields, including molecular evolution and bioinformatics; genome-, proteome-, transcriptome- and metabolome-wide experimental studies; structural genomics; and atomistic simulations of cellular-scale molecular assemblies as large as ribosomes and intact viruses. In short, much of post-genomic biology is increasingly becoming a form of computational biology. The ability to design and write computer programs is among the most indispensable skills that a modern researcher can cultivate. Python has become a popular programming language in the biosciences, largely because (i) its straightforward semantics and clean syntax make it a readily accessible first language; (ii) it is expressive and well-suited to object-oriented programming, as well as other modern paradigms; and (iii) the many available libraries and third-party toolkits extend the functionality of the core language into virtually every biological domain (sequence and structure analyses, phylogenomics, workflow management systems, etc.). This primer offers a basic introduction to coding, via Python, and it includes concrete examples and exercises to illustrate the language's usage and capabilities; the main text culminates with a final project in structural bioinformatics. A suite of Supplemental Chapters is also provided. Starting with basic concepts, such as that of a "variable," the Chapters methodically advance the reader to the point of writing a graphical user interface to compute the Hamming distance between two DNA sequences.
Manak, Martin; Zemek, Michal; Szkandera, Jakub; Kolingerova, Ivana; Papaleo, Elena; Lambrughi, Matteo
2017-06-01
Geometric models of molecular structures are often described as a set of balls, where balls represent individual atoms. The ability to describe and explore the empty space among these balls is important, e.g., in the analysis of the interaction of enzymes with substrates, ligands and solvent molecules. Voronoi diagrams from the field of computational geometry are often used here, because they provide a mathematical description of how the whole space can be divided into regions assigned to individual atoms. This paper introduces a combination of two different types of Voronoi diagrams into a new hybrid Voronoi diagram - one part of this diagram belongs to the additively weighted (aw-Voronoi) diagram and the other to the power diagram. The boundary between them is controlled by a user-defined constant (the probe radius). Both parts are computed by different algorithms, which are already known. The reduced aw-Voronoi diagram is then obtained by removing the power diagram part from the hybrid diagram. Reduced aw-Voronoi diagrams are perfectly tailored for the analysis of dynamic molecular structures, their computation is faster and storage requirements are lower than in the case of complete aw-Voronoi diagrams. Here, we showed their application to key proteins in cancer research such as p53 and ARID proteins as case study. We identified a biologically relevant cavity in p53 structural ensembles generated by molecular dynamics simulations and analyzed its accessibility, attesting the potential of our approach. This method is relevant for cancer research since it permits to depict a dynamical view of cavities and pockets in proteins that could be affected by mutations in the disease. Our approach opens novel prospects for the study of cancer-related proteins by molecular simulations and the identification of novel targets for drug design. Copyright © 2017 Elsevier Inc. All rights reserved.
Detailed mechanism of toluene oxidation and comparison with benzene
NASA Technical Reports Server (NTRS)
Bittker, David A.
1988-01-01
A detailed mechanism for the oxidation of toluene in both argon and nitrogen dilutents is presented. The mechanism was used to compute experimentally ignition delay times for shock-heated toluene-oxygen-argon mixtures with resonably good success over a wide range of initial temperatures and pressures. Attempts to compute experimentally measured concentration profiles for toluene oxidation in a turbulent reactor were partially successful. An extensive sensitivity analysis was performed to determine the reactions which control the ignition process and the rates of formation and destruction of various species. The most important step was found to be the reaction of toluene with molecular oxygen, followed by the reactions of hydroperoxyl and atomic oxygen with benzyl radicals. These findings contrast with the benzene oxidation, where the benzene-molecular oxygen reaction is quite unimportant and the reaction of phenyl with molecular oxygen dominates. In the toluene mechanism the corresponding reaction of benzyl radicals with oxygen is unimportant. Two reactions which are important in the oxidation of benzene also influence the oxidation of toluene for several conditions. These are the oxidations of phenyl and cyclopentadienyl radicals by molecular oxygen. The mechanism presented successfully computes the decrease of toluene concentration with time in the nitrogen diluted turbulent reactor. This fact, in addition to the good prediction of ignition delay times, shows that this mechanism can be used for modeling the ignition and combustion process in practical, well-mixed combustion systems.
NASA Astrophysics Data System (ADS)
Shoemaker, James Richard
Fabrication of silicon carbide (SiC) semiconductor devices are of interest for aerospace applications because of their high-temperature tolerance. Growth of an insulating SiO2 layer on SiC by oxidation is a poorly understood process, and sometimes produces interface defects that degrade device performance. Accurate theoretical models of surface chemistry, using quantum mechanics (QM), do not exist because of the huge computational cost of solving Schrodinger's equation for a molecular cluster large enough to represent a surface. Molecular mechanics (MM), which describes a molecule as a collection of atoms interacting through classical potentials, is a fast computational method, good at predicting molecular structure, but cannot accurately model chemical reactions. A new hybrid QM/MM computational method for surface chemistry was developed and applied to silicon and SiC surfaces. The addition of MM steric constraints was shown to have a large effect on the energetics of O atom adsorption on SiC. Adsorption of O atoms on Si-terminated SiC(111) favors above surface sites, in contrast to Si(111), but favors subsurface adsorption sites on C- terminated SiC(111). This difference, and the energetics of C atom etching via CO2 desorption, can explain the observed poor performance of SiC devices in which insulating layers were grown on C-terminated surfaces.
NASA Astrophysics Data System (ADS)
Kamstra, Rhiannon L.; Dadgar, Saedeh; Wigg, John; Chowdhury, Morshed A.; Phenix, Christopher P.; Floriano, Wely B.
2014-11-01
Our group has recently demonstrated that virtual screening is a useful technique for the identification of target-specific molecular probes. In this paper, we discuss some of our proof-of-concept results involving two biologically relevant target proteins, and report the development of a computational script to generate large databases of fluorescence-labelled compounds for computer-assisted molecular design. The virtual screening of a small library of 1,153 fluorescently-labelled compounds against two targets, and the experimental testing of selected hits reveal that this approach is efficient at identifying molecular probes, and that the screening of a labelled library is preferred over the screening of base compounds followed by conjugation of confirmed hits. The automated script for library generation explores the known reactivity of commercially available dyes, such as NHS-esters, to create large virtual databases of fluorescence-tagged small molecules that can be easily synthesized in a laboratory. A database of 14,862 compounds, each tagged with the ATTO680 fluorophore was generated with the automated script reported here. This library is available for downloading and it is suitable for virtual ligand screening aiming at the identification of target-specific fluorescent molecular probes.
Mei, Ye; Simmonett, Andrew C.; Pickard, Frank C.; DiStasio, Robert A.; Brooks, Bernard R.; Shao, Yihan
2015-01-01
In order to carry out a detailed analysis of the molecular static polarizability, which is the response of the molecule to a uniform external electric field, the molecular polarizability was computed using the finite-difference method for 21 small molecules, using density functional theory. Within nine charge population schemes (Löwdin, Mulliken, Becke, Hirshfeld, CM5, Hirshfeld-I, NPA, CHELPG, MK-ESP) in common use, the charge fluctuation contribution is found to dominate the molecular polarizability, with its ratio ranging from 59.9% with the Hirshfeld or CM5 scheme to 96.2% with the Mulliken scheme. The Hirshfeld-I scheme is also used to compute the other contribution to the molecular polarizability coming from the induced atomic dipoles, and the atomic polarizabilities in 8 small molecules and water pentamer are found to be highly anisotropic for most atoms. Overall, the results suggest that (a) more emphasis probably should be placed on the charge fluctuation terms in future polarizable force field development; (b) an anisotropic polarizability might be more suitable than an isotropic one in polarizable force fields based entirely or partially on the induced atomic dipoles. PMID:25945749
Non-Adiabatic Molecular Dynamics Methods for Materials Discovery
DOE Office of Scientific and Technical Information (OSTI.GOV)
Furche, Filipp; Parker, Shane M.; Muuronen, Mikko J.
2017-04-04
The flow of radiative energy in light-driven materials such as photosensitizer dyes or photocatalysts is governed by non-adiabatic transitions between electronic states and cannot be described within the Born-Oppenheimer approximation commonly used in electronic structure theory. The non-adiabatic molecular dynamics (NAMD) methods based on Tully surface hopping and time-dependent density functional theory developed in this project have greatly extended the range of molecular materials that can be tackled by NAMD simulations. New algorithms to compute molecular excited state and response properties efficiently were developed. Fundamental limitations of common non-linear response methods were discovered and characterized. Methods for accurate computations ofmore » vibronic spectra of materials such as black absorbers were developed and applied. It was shown that open-shell TDDFT methods capture bond breaking in NAMD simulations, a longstanding challenge for single-reference molecular dynamics simulations. The methods developed in this project were applied to study the photodissociation of acetaldehyde and revealed that non-adiabatic effects are experimentally observable in fragment kinetic energy distributions. Finally, the project enabled the first detailed NAMD simulations of photocatalytic water oxidation by titania nanoclusters, uncovering the mechanism of this fundamentally important reaction for fuel generation and storage.« less
Davis, Margaret T.; Holmes, Sophie E.; Pietrzak, Robert H.; Esterlis, Irina
2018-01-01
Chronic stress accounts for billions of dollars of economic loss annually in the United States alone, and is recognized as a major source of disability and mortality worldwide. Robust evidence suggests that chronic stress plays a significant role in the onset of severe and impairing psychiatric conditions, including major depressive disorder, bipolar disorder, and posttraumatic stress disorder. Application of molecular imaging techniques such as positron emission tomography and single photon emission computed tomography in recent years has begun to provide insight into the molecular mechanisms by which chronic stress confers risk for these disorders. The present paper provides a comprehensive review and synthesis of all positron emission tomography and single photon emission computed tomography imaging publications focused on the examination of molecular targets in individuals with major depressive disorder, posttraumatic stress disorder, or bipolar disorder to date. Critical discussion of discrepant findings and broad strengths and weaknesses of the current body of literature is provided. Recommended future directions for the field of molecular imaging to further elucidate the neurobiological substrates of chronic stress-related disorders are also discussed. This article is part of the inaugural issue for the journal focused on various aspects of chronic stress. PMID:29862379
NASA Astrophysics Data System (ADS)
Zahrina, Ida; Mulia, Kamarza; Yanuar, Arry; Nasikin, Mohammad
2018-04-01
DES (deep eutectic solvents) are a new class of ionic liquids that have excellent properties. The strength of interaction between molecules in the DES affects their properties and applications. In this work, the strength of molecular interactions between components in the betaine monohydrate salt and polyol (glycerol or/and propylene glycol) eutectic mixtures was studied by experimental and computational studies. The melting point and fusion enthalpy of the mixtures were measured using STA (Simultaneous Thermal Analyzer). The nature and strength of intermolecular interactions were observed by FT-IR and NMR spectroscopy. The molecular dynamics simulation was used to determine the number of H-bonds, percent occupancy, and radial distribution functions in the eutectic mixtures. The interaction between betaine monohydrate and polyol is following order: betaine monohydrate-glycerol-propylene glycol > betaine monohydrate-glycerol > betaine monohydrate-propylene glycol, where the latter is the eutectic mixture with the lowest stability, strength and extent of the hydrogen bonding interactions between component molecules. The presence of intra-molecular hydrogen bonding interactions, the inter-molecular hydrogen bonding interactions between betaine molecule and polyol, and also interactions between polyol and H2O of betaine monohydrate in the eutectic mixtures.
Heuristic lipophilicity potential for computer-aided rational drug design.
Du, Q; Arteca, G A; Mezey, P G
1997-09-01
In this contribution we suggest a heuristic molecular lipophilicity potential (HMLP), which is a structure-based technique requiring no empirical indices of atomic lipophilicity. The input data used in this approach are molecular geometries and molecular surfaces. The HMLP is a modified electrostatic potential, combined with the averaged influences from the molecular environment. Quantum mechanics is used to calculate the electron density function rho(r) and the electrostatic potential V(r), and from this information a lipophilicity potential L(r) is generated. The HMLP is a unified lipophilicity and hydrophilicity potential. The interactions of dipole and multipole moments, hydrogen bonds, and charged atoms in a molecule are included in the hydrophilic interactions in this model. The HMLP is used to study hydrogen bonds and water-octanol partition coefficients in several examples. The calculated results show that the HMLP gives qualitatively and quantitatively correct, as well as chemically reasonable, results in cases where comparisons are available. These comparisons indicate that the HMLP has advantages over the empirical lipophilicity potential in many aspects. The HMLP is a three-dimensional and easily visualizable representation of molecular lipophilicity, suggested as a potential tool in computer-aided three-dimensional drug design.
ANN expert system screening for illicit amphetamines using molecular descriptors
NASA Astrophysics Data System (ADS)
Gosav, S.; Praisler, M.; Dorohoi, D. O.
2007-05-01
The goal of this study was to develop and an artificial neural network (ANN) based on computed descriptors, which would be able to classify the molecular structures of potential illicit amphetamines and to derive their biological activity according to the similarity of their molecular structure with amphetamines of known toxicity. The system is necessary for testing new molecular structures for epidemiological, clinical, and forensic purposes. It was built using a database formed by 146 compounds representing drugs of abuse (mainly central stimulants, hallucinogens, sympathomimetic amines, narcotics and other potent analgesics), precursors, or derivatized counterparts. Their molecular structures were characterized by computing three types of descriptors: 38 constitutional descriptors (CDs), 69 topological descriptors (TDs) and 160 3D-MoRSE descriptors (3DDs). An ANN system was built for each category of variables. All three networks (CD-NN, TD-NN and 3DD-NN) were trained to distinguish between stimulant amphetamines, hallucinogenic amphetamines, and nonamphetamines. A selection of variables was performed when necessary. The efficiency with which each network identifies the class identity of an unknown sample was evaluated by calculating several figures of merit. The results of the comparative analysis are presented.
In evaluating the risk posed by chemicals introduced into the environment, information
about their molecular mechanism of action provides a basis for extrapolating from the
laboratory to the environment. Polycyclic aromatic hydrocarbons (PAH) are a large class
of...
Beyond [lambda][subscript max] Part 2: Predicting Molecular Color
ERIC Educational Resources Information Center
Williams, Darren L.; Flaherty, Thomas J.; Alnasleh, Bassam K.
2009-01-01
A concise roadmap for using computational chemistry programs (i.e., Gaussian 03W) to predict the color of a molecular species is presented. A color-predicting spreadsheet is available with the online material that uses transition wavelengths and peak-shape parameters to predict the visible absorbance spectrum, transmittance spectrum, chromaticity…
Reasoning with Atomic-Scale Molecular Dynamic Models
ERIC Educational Resources Information Center
Pallant, Amy; Tinker, Robert F.
2004-01-01
The studies reported in this paper are an initial effort to explore the applicability of computational models in introductory science learning. Two instructional interventions are described that use a molecular dynamics model embedded in a set of online learning activities with middle and high school students in 10 classrooms. The studies indicate…
The Use of Molecular Modeling Programs in Medicinal Chemistry Instruction.
ERIC Educational Resources Information Center
Harrold, Marc W.
1992-01-01
This paper describes and evaluates the use of a molecular modeling computer program (Alchemy II) in a pharmaceutical education program. Provided are the hardware requirements and basic program features as well as several examples of how this program and its features have been applied in the classroom. (GLR)
Preliminary Modulus and Breakage Calculations on Cellulose Models
USDA-ARS?s Scientific Manuscript database
The Young’s modulus of polymers can be calculated by stretching molecular models with the computer. The molecule is stretched and the derivative of the changes in stored potential energy for several displacements, divided by the molecular cross-section area, is the stress. The modulus is the slope o...
USDA-ARS?s Scientific Manuscript database
Molecular field topology analysis, scaffold hopping, and molecular docking were used as complementary computational tools for the design of repellents for Aedes aegypti, the insect vector for yellow fever, West Nile fever, and dengue fever. A large number of analogues were evaluated by virtual scree...
Barakat, Assem; Ghabbour, Hazem A; Al-Majid, Abdullah Mohammed; Soliman, Saied M; Ali, M; Mabkhot, Yahia Nasser; Shaik, Mohammed Rafi; Fun, Hoong-Kun
2015-07-21
The synthesis of 2,6-bis(hydroxy(phenyl)methyl)cyclohexanone 1 is described. The molecular structure of the title compound 1 was confirmed by NMR, FT-IR, MS, CHN microanalysis, and X-ray crystallography. The molecular structure was also investigated by a set of computational studies and found to be in good agreement with the experimental data obtained from the various spectrophotometric techniques. The antimicrobial activity and molecular docking of the synthesized compound was investigated.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Afroz, Ziya; Zulkarnain,; Ahmad, Afaq, E-mail: afaqahmad3@gmail.com
2016-05-23
DFT and TD-DFT studies of o-phenylenediamine (PDA), 3,5-dinitrosalicylic acid (DNSA) and their charge transfer complex have been carried out at B3LYP/6-311G(d,p) level of theory. Molecular geometry and various other molecular properties like natural atomic charges, ionization potential, electron affinity, band gap, natural bond orbital (NBO) and frontier molecular analysis have been presented at same level of theory. Frontier molecular orbital and natural bond orbital analysis show the charge delocalization from PDA to DNSA.
Computer Series, 36: Bits and Pieces, 13.
ERIC Educational Resources Information Center
Moore, John W.
1983-01-01
Eleven computer/calculator programs (most are available from authors) are described. Topics include visualizing molecular vibrations, dynamic nuclear magnetic resonance spectra of two-spin systems, programming utilities for Apple II Plus, gas chromatography simulation for TRS-80, infrared spectra analysis on a calculator, naming chemical…
ERIC Educational Resources Information Center
Batt, Russell H., Ed.
1988-01-01
Notes two uses of computer spreadsheets in the chemistry classroom. Discusses the general use of the spreadsheet to easily provide changing parameters of equations and then replotting the results on the screen. Presents a molecular orbital spreadsheet calculation of the LCAO-MO approach. Supplies representative printouts and graphs. (MVL)
Sarkar, Kanchan; Sharma, Rahul; Bhattacharyya, S P
2010-03-09
A density matrix based soft-computing solution to the quantum mechanical problem of computing the molecular electronic structure of fairly long polythiophene (PT) chains is proposed. The soft-computing solution is based on a "random mutation hill climbing" scheme which is modified by blending it with a deterministic method based on a trial single-particle density matrix [P((0))(R)] for the guessed structural parameters (R), which is allowed to evolve under a unitary transformation generated by the Hamiltonian H(R). The Hamiltonian itself changes as the geometrical parameters (R) defining the polythiophene chain undergo mutation. The scale (λ) of the transformation is optimized by making the energy [E(λ)] stationary with respect to λ. The robustness and the performance levels of variants of the algorithm are analyzed and compared with those of other derivative free methods. The method is further tested successfully with optimization of the geometry of bipolaron-doped long PT chains.
Mathematical and Computational Modeling in Complex Biological Systems
Li, Wenyang; Zhu, Xiaoliang
2017-01-01
The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology. PMID:28386558
NASA Technical Reports Server (NTRS)
Borysow, Aleksandra
1998-01-01
Accurate knowledge of certain collision-induced absorption continua of molecular pairs such as H2-H2, H2-He, H2-CH4, CO2-CO2, etc., is a prerequisite for most spectral analyses and modelling attempts of atmospheres of planets and cold stars. We collect and regularly update simple, state of the art computer programs for the calculation of the absorption coefficient of such molecular pairs over a broad range of temperatures and frequencies, for the various rotovibrational bands. The computational results are in agreement with the existing laboratory measurements of such absorption continua, recorded with a spectral resolution of a few wavenumbers, but reliable computational results may be expected even in the far wings, and at temperatures for which laboratory measurements do not exist. Detailed information is given concerning the systems thus studied, the temperature and frequency ranges considered, the rotovibrational bands thus modelled, and how one may obtain copies of the FORTRAN77 computer programs by e-mail.
Pérès, Sabine; Felicori, Liza; Rialle, Stéphanie; Jobard, Elodie; Molina, Franck
2010-01-01
Motivation: In the available databases, biological processes are described from molecular and cellular points of view, but these descriptions are represented with text annotations that make it difficult to handle them for computation. Consequently, there is an obvious need for formal descriptions of biological processes. Results: We present a formalism that uses the BioΨ concepts to model biological processes from molecular details to networks. This computational approach, based on elementary bricks of actions, allows us to calculate on biological functions (e.g. process comparison, mapping structure–function relationships, etc.). We illustrate its application with two examples: the functional comparison of proteases and the functional description of the glycolysis network. This computational approach is compatible with detailed biological knowledge and can be applied to different kinds of systems of simulation. Availability: www.sysdiag.cnrs.fr/publications/supplementary-materials/BioPsi_Manager/ Contact: sabine.peres@sysdiag.cnrs.fr; franck.molina@sysdiag.cnrs.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20448138
Mathematical and Computational Modeling in Complex Biological Systems.
Ji, Zhiwei; Yan, Ke; Li, Wenyang; Hu, Haigen; Zhu, Xiaoliang
2017-01-01
The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology.
Bacterial computing: a form of natural computing and its applications.
Lahoz-Beltra, Rafael; Navarro, Jorge; Marijuán, Pedro C
2014-01-01
The capability to establish adaptive relationships with the environment is an essential characteristic of living cells. Both bacterial computing and bacterial intelligence are two general traits manifested along adaptive behaviors that respond to surrounding environmental conditions. These two traits have generated a variety of theoretical and applied approaches. Since the different systems of bacterial signaling and the different ways of genetic change are better known and more carefully explored, the whole adaptive possibilities of bacteria may be studied under new angles. For instance, there appear instances of molecular "learning" along the mechanisms of evolution. More in concrete, and looking specifically at the time dimension, the bacterial mechanisms of learning and evolution appear as two different and related mechanisms for adaptation to the environment; in somatic time the former and in evolutionary time the latter. In the present chapter it will be reviewed the possible application of both kinds of mechanisms to prokaryotic molecular computing schemes as well as to the solution of real world problems.
Bacterial computing: a form of natural computing and its applications
Lahoz-Beltra, Rafael; Navarro, Jorge; Marijuán, Pedro C.
2014-01-01
The capability to establish adaptive relationships with the environment is an essential characteristic of living cells. Both bacterial computing and bacterial intelligence are two general traits manifested along adaptive behaviors that respond to surrounding environmental conditions. These two traits have generated a variety of theoretical and applied approaches. Since the different systems of bacterial signaling and the different ways of genetic change are better known and more carefully explored, the whole adaptive possibilities of bacteria may be studied under new angles. For instance, there appear instances of molecular “learning” along the mechanisms of evolution. More in concrete, and looking specifically at the time dimension, the bacterial mechanisms of learning and evolution appear as two different and related mechanisms for adaptation to the environment; in somatic time the former and in evolutionary time the latter. In the present chapter it will be reviewed the possible application of both kinds of mechanisms to prokaryotic molecular computing schemes as well as to the solution of real world problems. PMID:24723912
An interactive computer lab of the galvanic cell for students in biochemistry.
Ahlstrand, Emma; Buetti-Dinh, Antoine; Friedman, Ran
2018-01-01
We describe an interactive module that can be used to teach basic concepts in electrochemistry and thermodynamics to first year natural science students. The module is used together with an experimental laboratory and improves the students' understanding of thermodynamic quantities such as Δ r G, Δ r H, and Δ r S that are calculated but not directly measured in the lab. We also discuss how new technologies can substitute some parts of experimental chemistry courses, and improve accessibility to course material. Cloud computing platforms such as CoCalc facilitate the distribution of computer codes and allow students to access and apply interactive course tools beyond the course's scope. Despite some limitations imposed by cloud computing, the students appreciated the approach and the enhanced opportunities to discuss study questions with their classmates and instructor as facilitated by the interactive tools. © 2017 by The International Union of Biochemistry and Molecular Biology, 46(1):58-65, 2018. © 2017 The International Union of Biochemistry and Molecular Biology.
Towards data warehousing and mining of protein unfolding simulation data.
Berrar, Daniel; Stahl, Frederic; Silva, Candida; Rodrigues, J Rui; Brito, Rui M M; Dubitzky, Werner
2005-10-01
The prediction of protein structure and the precise understanding of protein folding and unfolding processes remains one of the greatest challenges in structural biology and bioinformatics. Computer simulations based on molecular dynamics (MD) are at the forefront of the effort to gain a deeper understanding of these complex processes. Currently, these MD simulations are usually on the order of tens of nanoseconds, generate a large amount of conformational data and are computationally expensive. More and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. To adequately organize, manage, and analyze the data generated by unfolding simulation studies, we designed a data warehouse system that is embedded in a grid environment to facilitate the seamless sharing of available computer resources and thus enable many groups to share complex molecular dynamics simulations on a more regular basis. To gain insight into the conformational fluctuations and stability of the monomeric forms of the amyloidogenic protein transthyretin (TTR), molecular dynamics unfolding simulations of the monomer of human TTR have been conducted. Trajectory data and meta-data of the wild-type (WT) protein and the highly amyloidogenic variant L55P-TTR represent the test case for the data warehouse. Web and grid services, especially pre-defined data mining services that can run on or 'near' the data repository of the data warehouse, are likely to play a pivotal role in the analysis of molecular dynamics unfolding data.
Liu, Zhaomin; Pottel, Joshua; Shahamat, Moeed; Tomberg, Anna; Labute, Paul; Moitessier, Nicolas
2016-04-25
Computational chemists use structure-based drug design and molecular dynamics of drug/protein complexes which require an accurate description of the conformational space of drugs. Organic chemists use qualitative chemical principles such as the effect of electronegativity on hyperconjugation, the impact of steric clashes on stereochemical outcome of reactions, and the consequence of resonance on the shape of molecules to rationalize experimental observations. While computational chemists speak about electron densities and molecular orbitals, organic chemists speak about partial charges and localized molecular orbitals. Attempts to reconcile these two parallel approaches such as programs for natural bond orbitals and intrinsic atomic orbitals computing Lewis structures-like orbitals and reaction mechanism have appeared. In the past, we have shown that encoding and quantifying chemistry knowledge and qualitative principles can lead to predictive methods. In the same vein, we thought to understand the conformational behaviors of molecules and to encode this knowledge back into a molecular mechanics tool computing conformational potential energy and to develop an alternative to atom types and training of force fields on large sets of molecules. Herein, we describe a conceptually new approach to model torsion energies based on fundamental chemistry principles. To demonstrate our approach, torsional energy parameters were derived on-the-fly from atomic properties. When the torsional energy terms implemented in GAFF, Parm@Frosst, and MMFF94 were substituted by our method, the accuracy of these force fields to reproduce MP2-derived torsional energy profiles and their transferability to a variety of functional groups and drug fragments were overall improved. In addition, our method did not rely on atom types and consequently did not suffer from poor automated atom type assignments.
McKay, Dennis B; Chang, Cheng; González-Cestari, Tatiana F; McKay, Susan B; El-Hajj, Raed A; Bryant, Darrell L; Zhu, Michael X; Swaan, Peter W; Arason, Kristjan M; Pulipaka, Aravinda B; Orac, Crina M; Bergmeier, Stephen C
2007-05-01
As a novel approach to drug discovery involving neuronal nicotinic acetylcholine receptors (nAChRs), our laboratory targeted nonagonist binding sites (i.e., noncompetitive binding sites, negative allosteric binding sites) located on nAChRs. Cultured bovine adrenal cells were used as neuronal models to investigate interactions of 67 analogs of methyllycaconitine (MLA) on native alpha3beta4* nAChRs. The availability of large numbers of structurally related molecules presents a unique opportunity for the development of pharmacophore models for noncompetitive binding sites. Our MLA analogs inhibited nicotine-mediated functional activation of both native and recombinant alpha3beta4* nAChRs with a wide range of IC(50) values (0.9-115 microM). These analogs had little or no inhibitory effects on agonist binding to native or recombinant nAChRs, supporting noncompetitive inhibitory activity. Based on these data, two highly predictive 3D quantitative structure-activity relationship (comparative molecular field analysis and comparative molecular similarity index analysis) models were generated. These computational models were successfully validated and provided insights into the molecular interactions of MLA analogs with nAChRs. In addition, a pharmacophore model was constructed to analyze and visualize the binding requirements to the analog binding site. The pharmacophore model was subsequently applied to search structurally diverse molecular databases to prospectively identify novel inhibitors. The rapid identification of eight molecules from database mining and our successful demonstration of in vitro inhibitory activity support the utility of these computational models as novel tools for the efficient retrieval of inhibitors. These results demonstrate the effectiveness of computational modeling and pharmacophore development, which may lead to the identification of new therapeutic drugs that target novel sites on nAChRs.
García-Jacas, César R; Marrero-Ponce, Yovani; Acevedo-Martínez, Liesner; Barigye, Stephen J; Valdés-Martiní, José R; Contreras-Torres, Ernesto
2014-07-05
The present report introduces the QuBiLS-MIDAS software belonging to the ToMoCoMD-CARDD suite for the calculation of three-dimensional molecular descriptors (MDs) based on the two-linear (bilinear), three-linear, and four-linear (multilinear or N-linear) algebraic forms. Thus, it is unique software that computes these tensor-based indices. These descriptors, establish relations for two, three, and four atoms by using several (dis-)similarity metrics or multimetrics, matrix transformations, cutoffs, local calculations and aggregation operators. The theoretical background of these N-linear indices is also presented. The QuBiLS-MIDAS software was developed in the Java programming language and employs the Chemical Development Kit library for the manipulation of the chemical structures and the calculation of the atomic properties. This software is composed by a desktop user-friendly interface and an Abstract Programming Interface library. The former was created to simplify the configuration of the different options of the MDs, whereas the library was designed to allow its easy integration to other software for chemoinformatics applications. This program provides functionalities for data cleaning tasks and for batch processing of the molecular indices. In addition, it offers parallel calculation of the MDs through the use of all available processors in current computers. The studies of complexity of the main algorithms demonstrate that these were efficiently implemented with respect to their trivial implementation. Lastly, the performance tests reveal that this software has a suitable behavior when the amount of processors is increased. Therefore, the QuBiLS-MIDAS software constitutes a useful application for the computation of the molecular indices based on N-linear algebraic maps and it can be used freely to perform chemoinformatics studies. Copyright © 2014 Wiley Periodicals, Inc.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Visco, Donald Patrick, Jr.; Faulon, Jean-Loup Michel; Roe, Diana C.
This report is a comprehensive review of the field of molecular enumeration from early isomer counting theories to evolutionary algorithms that design molecules in silico. The core of the review is a detail account on how molecules are counted, enumerated, and sampled. The practical applications of molecular enumeration are also reviewed for chemical information, structure elucidation, molecular design, and combinatorial library design purposes. This review is to appear as a chapter in Reviews in Computational Chemistry volume 21 edited by Kenny B. Lipkowitz.
An Initial Look at Alternative Computing Technologies for the Intelligence Community
2014-01-01
Recommendation (N-1): Guide hardware development with lessons from machine learning and neuroscience . Neuro-inspired computing suffers from a lack...not new to either the government or industry. We have described Google’s approach. The government—most notably The National Security Agency ( NSA ) and...increasing accumulation of knowledge in neuroscience and bio-molecular methods, new computational techniques may become available in the near future
Novel 3-D Computer Model Can Help Predict Pathogens’ Roles in Cancer | Poster
To understand how bacterial and viral infections contribute to human cancers, four NCI at Frederick scientists turned not to the lab bench, but to a computer. The team has created the world’s first—and currently, only—3-D computational approach for studying interactions between pathogen proteins and human proteins based on a molecular adaptation known as interface mimicry.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ibrahim, Khaled Z.; Epifanovsky, Evgeny; Williams, Samuel
Coupled-cluster methods provide highly accurate models of molecular structure through explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix–matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts tomore » extend the Libtensor framework to work in the distributed memory environment in a scalable and energy-efficient manner. We achieve up to 240× speedup compared with the optimized shared memory implementation of Libtensor. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures (Cray XC30 and XC40, and IBM Blue Gene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance, tasking and bulk synchronous models. Nevertheless, we preserve a unified interface to both programming models to maintain the productivity of computational quantum chemists.« less
Ibrahim, Khaled Z.; Epifanovsky, Evgeny; Williams, Samuel; ...
2017-03-08
Coupled-cluster methods provide highly accurate models of molecular structure through explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix–matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts tomore » extend the Libtensor framework to work in the distributed memory environment in a scalable and energy-efficient manner. We achieve up to 240× speedup compared with the optimized shared memory implementation of Libtensor. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures (Cray XC30 and XC40, and IBM Blue Gene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance, tasking and bulk synchronous models. Nevertheless, we preserve a unified interface to both programming models to maintain the productivity of computational quantum chemists.« less
Discovering the intelligence in molecular biology.
Uberbacher, E
1995-12-01
The Third International Conference on Intelligent Systems in Molecular Biology was truly an outstanding event. Computational methods in molecular biology have reached a new level of maturity and utility, resulting in many high-impact applications. The success of this meeting bodes well for the rapid and continuing development of computational methods, intelligent systems and information-based approaches for the biosciences. The basic technology, originally most often applied to 'feasibility' problems, is now dealing effectively with the most difficult real-world problems. Significant progress has been made in understanding protein-structure information, structural classification, and how functional information and the relevant features of active-site geometry can be gleaned from structures by automated computational approaches. The value and limits of homology-based methods, and the ability to classify proteins by structure in the absence of homology, have reached a new level of sophistication. New methods for covariation analysis in the folding of large structures such as RNAs have shown remarkably good results, indicating the long-term potential to understand very complicated molecules and multimolecular complexes using computational means. Novel methods, such as HMMs, context-free grammars and the uses of mutual information theory, have taken center stage as highly valuable tools in our quest to represent and characterize biological information. A focus on creative uses of intelligent systems technologies and the trend toward biological application will undoubtedly continue and grow at the 1996 ISMB meeting in St Louis.
NASA Astrophysics Data System (ADS)
Dimitroulis, Christos; Raptis, Theophanes; Raptis, Vasilios
2015-12-01
We present an application for the calculation of radial distribution functions for molecular centres of mass, based on trajectories generated by molecular simulation methods (Molecular Dynamics, Monte Carlo). When designing this application, the emphasis was placed on ease of use as well as ease of further development. In its current version, the program can read trajectories generated by the well-known DL_POLY package, but it can be easily extended to handle other formats. It is also very easy to 'hack' the program so it can compute intermolecular radial distribution functions for groups of interaction sites rather than whole molecules.
NASA Astrophysics Data System (ADS)
Wyrick, Jonathan; Einstein, T. L.; Bartels, Ludwig
2015-03-01
We present a method of analyzing the results of density functional modeling of molecular adsorption in terms of an analogue of molecular orbitals. This approach permits intuitive chemical insight into the adsorption process. Applied to a set of anthracene derivates (anthracene, 9,10-anthraquinone, 9,10-dithioanthracene, and 9,10-diselenonanthracene), we follow the electronic states of the molecules that are involved in the bonding process and correlate them to both the molecular adsorption geometry and the species' diffusive behavior. We additionally provide computational code to easily repeat this analysis on any system.
Pérez, Alejandro; von Lilienfeld, O Anatole
2011-08-09
Thermodynamic integration, perturbation theory, and λ-dynamics methods were applied to path integral molecular dynamics calculations to investigate free energy differences due to "alchemical" transformations. Several estimators were formulated to compute free energy differences in solvable model systems undergoing changes in mass and/or potential. Linear and nonlinear alchemical interpolations were used for the thermodynamic integration. We find improved convergence for the virial estimators, as well as for the thermodynamic integration over nonlinear interpolation paths. Numerical results for the perturbative treatment of changes in mass and electric field strength in model systems are presented. We used thermodynamic integration in ab initio path integral molecular dynamics to compute the quantum free energy difference of the isotope transformation in the Zundel cation. The performance of different free energy methods is discussed.
Quantum Mechanical Modeling: A Tool for the Understanding of Enzyme Reactions
Náray-Szabó, Gábor; Oláh, Julianna; Krámos, Balázs
2013-01-01
Most enzyme reactions involve formation and cleavage of covalent bonds, while electrostatic effects, as well as dynamics of the active site and surrounding protein regions, may also be crucial. Accordingly, special computational methods are needed to provide an adequate description, which combine quantum mechanics for the reactive region with molecular mechanics and molecular dynamics describing the environment and dynamic effects, respectively. In this review we intend to give an overview to non-specialists on various enzyme models as well as established computational methods and describe applications to some specific cases. For the treatment of various enzyme mechanisms, special approaches are often needed to obtain results, which adequately refer to experimental data. As a result of the spectacular progress in the last two decades, most enzyme reactions can be quite precisely treated by various computational methods. PMID:24970187
Approaching mathematical model of the immune network based DNA Strand Displacement system.
Mardian, Rizki; Sekiyama, Kosuke; Fukuda, Toshio
2013-12-01
One biggest obstacle in molecular programming is that there is still no direct method to compile any existed mathematical model into biochemical reaction in order to solve a computational problem. In this paper, the implementation of DNA Strand Displacement system based on nature-inspired computation is observed. By using the Immune Network Theory and Chemical Reaction Network, the compilation of DNA-based operation is defined and the formulation of its mathematical model is derived. Furthermore, the implementation on this system is compared with the conventional implementation by using silicon-based programming. From the obtained results, we can see a positive correlation between both. One possible application from this DNA-based model is for a decision making scheme of intelligent computer or molecular robot. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Ngwuluka, Ndidi C; Choonara, Yahya E; Kumar, Pradeep; du Toit, Lisa C; Khan, Riaz A; Pillay, Viness
2015-03-01
This study was undertaken to synthesize an interpolyelectrolyte complex (IPEC) of polymethacrylate (E100) and sodium carboxymethylcellulose (NaCMC) to form a polymeric hydrogel material for application in specialized oral drug delivery of sensitive levodopa. Computational modeling was employed to proffer insight into the interactions between the polymers. In addition, the reactional profile of NaCMC and polymethacrylate was elucidated using molecular mechanics energy relationships (MMER) and molecular dynamics simulations (MDS) by exploring the spatial disposition of NaCMC and E100 with respect to each other. Computational modeling revealed that the formation of the IPEC was due to strong ionic associations, hydrogen bonding, and hydrophilic interactions. The computational results corroborated well with the experimental and the analytical data. © 2014 Wiley Periodicals, Inc.
Fully anharmonic IR and Raman spectra of medium-size molecular systems: accuracy and interpretation†
Barone, Vincenzo; Biczysko, Malgorzata; Bloino, Julien
2015-01-01
Computation of full infrared (IR) and Raman spectra (including absolute intensities and transition energies) for medium- and large-sized molecular systems beyond the harmonic approximation is one of the most interesting challenges of contemporary computational chemistry. Contrary to common beliefs, low-order perturbation theory is able to deliver results of high accuracy (actually often better than those issuing from current direct dynamics approaches) provided that anharmonic resonances are properly managed. This perspective sketches the recent developments in our research group toward the development a robust and user-friendly virtual spectrometer rooted into the second-order vibrational perturbation theory (VPT2) and usable also by non-specialists essentially as a black-box procedure. Several examples are explicitly worked out in order to illustrate the features of our computational tool together with the most important ongoing developments. PMID:24346191
Molecular Dynamics Studies of Proton Transport in Hydrogenase and Hydrogenase Mimics.
Ginovska, B; Raugei, S; Shaw, W J
2016-01-01
There is extensive interest in hydrogenases based on their ability to rapidly and efficiently interconvert H2 with protons and electrons, and their (typically) superior function relative to molecular mimics. Understanding the function of enzymes is one approach to implementing design features to make better catalysts and is an approach we have implemented in our work. In this review, we will discuss our efforts to develop design principles from enzymes, with specific focus on proton transport. We will also present computational studies of the mimics we have investigated with similar methodologies. We will discuss the mechanisms used by small scaffolds on molecular mimics which in many cases are surprisingly similar to those used by nature, while in other cases, computational analysis allowed us to reveal an unexpected role. Computational methods provide one of the best ways, and in some cases, the only way, to gain insight into the mechanistic details of enzymes. In this review, we illustrate the general computational strategy we used to study the proton pathway of [FeFe]-hydrogenase, and the similar strategy to investigate small molecules. We present the main results we obtained and how our computational work stimulated or worked in concert with experimental investigations. We also focus on estimation of errors and convergence of properties in the simulations. These studies demonstrate the powerful results that can be obtained by the close pairing of experimental and theoretical approaches. Copyright © 2016 Elsevier Inc. All rights reserved. Battelle, operator of PNNL, under Contract No: DE-AC05-76RL01830 with US DoE.
Integrating Computational Chemistry into the Physical Chemistry Curriculum
ERIC Educational Resources Information Center
Johnson, Lewis E.; Engel, Thomas
2011-01-01
Relatively few undergraduate physical chemistry programs integrate molecular modeling into their quantum mechanics curriculum owing to concerns about limited access to computational facilities, the cost of software, and concerns about increasing the course material. However, modeling exercises can be integrated into an undergraduate course at a…
Computer Series, 60: Bits and Pieces, 23.
ERIC Educational Resources Information Center
Moore, John W., Ed.
1985-01-01
Describes: (1) an interactive computer simulation for a science fair display of chromatography inks; (2) analytical chemistry programs; (3) microcomputer-assisted drills in organic synthesis; (4) programs for conformation analysis of ethane and butane; (5) MOLPIX--a program for generating and displaying molecular structures; and (6) chemical…
ERIC Educational Resources Information Center
Moore, John W., Ed.
1988-01-01
Describes five computer software packages; four for MS-DOS Systems and one for Apple II. Included are SPEC20, an interactive simulation of a Bausch and Lomb Spectronic-20; a database for laboratory chemicals and programs for visualizing Boltzmann-like distributions, orbital plot for the hydrogen atom and molecular orbital theory. (CW)
EPA’s National Center for Computational Toxicology is engaged in high-profile research efforts to improve the ability to more efficiently and effectively prioritize and screen thousands of environmental chemicals for potential toxicity. A central component of these efforts invol...
Applied Computational Chemistry for the Blind and Visually Impaired
ERIC Educational Resources Information Center
Wedler, Henry B.; Cohen, Sarah R.; Davis, Rebecca L.; Harrison, Jason G.; Siebert, Matthew R.; Willenbring, Dan; Hamann, Christian S.; Shaw, Jared T.; Tantillo, Dean J.
2012-01-01
We describe accommodations that we have made to our applied computational-theoretical chemistry laboratory to provide access for blind and visually impaired students interested in independent investigation of structure-function relationships. Our approach utilizes tactile drawings, molecular model kits, existing software, Bash and Perl scripts…
Connecting the virtual world of computers to the real world of medicinal chemistry.
Glen, Robert C
2011-03-01
Drug discovery involves the simultaneous optimization of chemical and biological properties, usually in a single small molecule, which modulates one of nature's most complex systems: the balance between human health and disease. The increased use of computer-aided methods is having a significant impact on all aspects of the drug-discovery and development process and with improved methods and ever faster computers, computer-aided molecular design will be ever more central to the discovery process.
Molecular Imaging of Atherothrombotic Diseases: Seeing Is Believing.
Wang, Xiaowei; Peter, Karlheinz
2017-06-01
Molecular imaging, with major advances in the development of both innovative targeted contrast agents/particles and radiotracers, as well as various imaging technologies, is a fascinating, rapidly growing field with many preclinical and clinical applications, particularly for personalized medicine. Thrombosis in either the venous or the arterial system, the latter typically caused by rupture of unstable atherosclerotic plaques, is a major determinant of mortality and morbidity in patients. However, imaging of the various thrombotic complications and the identification of plaques that are prone to rupture are at best indirect, mostly unreliable, or not available at all. The development of molecular imaging toward diagnosis and prevention of thrombotic disease holds promise for major advance in this clinically important field. Here, we review the medical need and clinical importance of direct molecular imaging of thrombi and unstable atherosclerotic plaques that are prone to rupture, thereby causing thrombotic complications such as myocardial infarction and ischemic stroke. We systematically compare the advantages/disadvantages of the various molecular imaging modalities, including X-ray computed tomography, magnetic resonance imaging, positron emission tomography, single-photon emission computed tomography, fluorescence imaging, and ultrasound. We further systematically discuss molecular targets specific for thrombi and those characterizing unstable, potentially thrombogenic atherosclerotic plaques. Finally, we provide examples for first theranostic approaches in thrombosis, combining diagnosis, targeted therapy, and monitoring of therapeutic success or failure. Overall, molecular imaging is a rapidly advancing field that holds promise of major benefits to many patients with atherothrombotic diseases. © 2017 American Heart Association, Inc.
MEvoLib v1.0: the first molecular evolution library for Python.
Álvarez-Jarreta, Jorge; Ruiz-Pesini, Eduardo
2016-10-28
Molecular evolution studies involve many different hard computational problems solved, in most cases, with heuristic algorithms that provide a nearly optimal solution. Hence, diverse software tools exist for the different stages involved in a molecular evolution workflow. We present MEvoLib, the first molecular evolution library for Python, providing a framework to work with different tools and methods involved in the common tasks of molecular evolution workflows. In contrast with already existing bioinformatics libraries, MEvoLib is focused on the stages involved in molecular evolution studies, enclosing the set of tools with a common purpose in a single high-level interface with fast access to their frequent parameterizations. The gene clustering from partial or complete sequences has been improved with a new method that integrates accessible external information (e.g. GenBank's features data). Moreover, MEvoLib adjusts the fetching process from NCBI databases to optimize the download bandwidth usage. In addition, it has been implemented using parallelization techniques to cope with even large-case scenarios. MEvoLib is the first library for Python designed to facilitate molecular evolution researches both for expert and novel users. Its unique interface for each common task comprises several tools with their most used parameterizations. It has also included a method to take advantage of biological knowledge to improve the gene partition of sequence datasets. Additionally, its implementation incorporates parallelization techniques to enhance computational costs when handling very large input datasets.
Frett, Brendan; McConnell, Nick; Smith, Catherine C.; Wang, Yuanxiang; Shah, Neil P.; Li, Hong-yu
2015-01-01
The FLT3 kinase represents an attractive target to effectively treat AML. Unfortunately, no FLT3 targeted therapeutic is currently approved. In line with our continued interests in treating kinase related disease for anti-FLT3 mutant activity, we utilized pioneering synthetic methodology in combination with computer aided drug discovery and identified low molecular weight, highly ligand efficient, FLT3 kinase inhibitors. Compounds were analyzed for biochemical inhibition, their ability to selectively inhibit cell proliferation, for FLT3 mutant activity, and preliminary aqueous solubility. Validated hits were discovered that can serve as starting platforms for lead candidates. PMID:25765758
The Hartree-Fock calculation of the magnetic properties of molecular solutes
NASA Astrophysics Data System (ADS)
Cammi, R.
1998-08-01
In this paper we set the formal bases for the calculation of the magnetic susceptibility and of the nuclear magnetic shielding tensors for molecular solutes described within the framework of the polarizable continuum model (PCM). The theory has been developed at self-consistent field (SCF) level and adapted to be used within the framework of some of the computational procedures of larger use, i.e., the gauge invariant atomic orbital method (GIAO) and the continuous set gauge transformation method (CSGT). The numerical results relative to the magnetizabilities and chemical shielding of acetonitrile and nitrometane in various solvents computed with the PCM-CSGT method are also presented.
Numerical analysis of the photo-injection time-of-flight curves in molecularly doped polymers
NASA Astrophysics Data System (ADS)
Tyutnev, A. P.; Ikhsanov, R. Sh.; Saenko, V. S.; Nikerov, D. V.
2018-03-01
We have performed numerical analysis of the charge carrier transport in a specific molecularly doped polymer using the multiple trapping model. The computations covered a wide range of applied electric fields, temperatures and most importantly, of the initial energies of photo injected one-sign carriers (in our case, holes). Special attention has been given to comparison of time of flight curves measured by the photo-injection and radiation-induced techniques which has led to a problematic situation concerning an interpretation of the experimental data. Computational results have been compared with both analytical and experimental results available in literature.
Modeling inelastic phonon scattering in atomic- and molecular-wire junctions
NASA Astrophysics Data System (ADS)
Paulsson, Magnus; Frederiksen, Thomas; Brandbyge, Mads
2005-11-01
Computationally inexpensive approximations describing electron-phonon scattering in molecular-scale conductors are derived from the nonequilibrium Green’s function method. The accuracy is demonstrated with a first-principles calculation on an atomic gold wire. Quantitative agreement between the full nonequilibrium Green’s function calculation and the newly derived expressions is obtained while simplifying the computational burden by several orders of magnitude. In addition, analytical models provide intuitive understanding of the conductance including nonequilibrium heating and provide a convenient way of parameterizing the physics. This is exemplified by fitting the expressions to the experimentally observed conductances through both an atomic gold wire and a hydrogen molecule.
Evaluation of synthetic linear motor-molecule actuation energetics
Brough, Branden; Northrop, Brian H.; Schmidt, Jacob J.; Tseng, Hsian-Rong; Houk, Kendall N.; Stoddart, J. Fraser; Ho, Chih-Ming
2006-01-01
By applying atomic force microscope (AFM)-based force spectroscopy together with computational modeling in the form of molecular force-field simulations, we have determined quantitatively the actuation energetics of a synthetic motor-molecule. This multidisciplinary approach was performed on specifically designed, bistable, redox-controllable [2]rotaxanes to probe the steric and electrostatic interactions that dictate their mechanical switching at the single-molecule level. The fusion of experimental force spectroscopy and theoretical computational modeling has revealed that the repulsive electrostatic interaction, which is responsible for the molecular actuation, is as high as 65 kcal·mol−1, a result that is supported by ab initio calculations. PMID:16735470
Computer Simulations of Intrinsically Disordered Proteins
NASA Astrophysics Data System (ADS)
Chong, Song-Ho; Chatterjee, Prathit; Ham, Sihyun
2017-05-01
The investigation of intrinsically disordered proteins (IDPs) is a new frontier in structural and molecular biology that requires a new paradigm to connect structural disorder to function. Molecular dynamics simulations and statistical thermodynamics potentially offer ideal tools for atomic-level characterizations and thermodynamic descriptions of this fascinating class of proteins that will complement experimental studies. However, IDPs display sensitivity to inaccuracies in the underlying molecular mechanics force fields. Thus, achieving an accurate structural characterization of IDPs via simulations is a challenge. It is also daunting to perform a configuration-space integration over heterogeneous structural ensembles sampled by IDPs to extract, in particular, protein configurational entropy. In this review, we summarize recent efforts devoted to the development of force fields and the critical evaluations of their performance when applied to IDPs. We also survey recent advances in computational methods for protein configurational entropy that aim to provide a thermodynamic link between structural disorder and protein activity.