Simulation of Biomolecular Nanomechanical Systems

DTIC Science & Technology

2006-10-01

optimization of doping concentration and minimizing the interface traps. Surface Immobilization of Receptors For biomolecular binding experiments...Biosensors,” Langmuir, Vol. 21, pp. 1956-1961 (2005). 13. M. Yue, Multiplexed Label-Free Bioassays Using Nanomechanics and Nanofluidics , PhD Thesis

Update of KDBI: Kinetic Data of Bio-molecular Interaction database

PubMed Central

Kumar, Pankaj; Han, B. C.; Shi, Z.; Jia, J.; Wang, Y. P.; Zhang, Y. T.; Liang, L.; Liu, Q. F.; Ji, Z. L.; Chen, Y. Z.

2009-01-01

Knowledge of the kinetics of biomolecular interactions is important for facilitating the study of cellular processes and underlying molecular events, and is essential for quantitative study and simulation of biological systems. Kinetic Data of Bio-molecular Interaction database (KDBI) has been developed to provide information about experimentally determined kinetic data of protein–protein, protein–nucleic acid, protein–ligand, nucleic acid–ligand binding or reaction events described in the literature. To accommodate increasing demand for studying and simulating biological systems, numerous improvements and updates have been made to KDBI, including new ways to access data by pathway and molecule names, data file in System Biology Markup Language format, more efficient search engine, access to published parameter sets of simulation models of 63 pathways, and 2.3-fold increase of data (19 263 entries of 10 532 distinctive biomolecular binding and 11 954 interaction events, involving 2635 proteins/protein complexes, 847 nucleic acids, 1603 small molecules and 45 multi-step processes). KDBI is publically available at http://bidd.nus.edu.sg/group/kdbi/kdbi.asp. PMID:18971255

Quantum-assisted biomolecular modelling.

PubMed

Harris, Sarah A; Kendon, Vivien M

2010-08-13

Our understanding of the physics of biological molecules, such as proteins and DNA, is limited because the approximations we usually apply to model inert materials are not, in general, applicable to soft, chemically inhomogeneous systems. The configurational complexity of biomolecules means the entropic contribution to the free energy is a significant factor in their behaviour, requiring detailed dynamical calculations to fully evaluate. Computer simulations capable of taking all interatomic interactions into account are therefore vital. However, even with the best current supercomputing facilities, we are unable to capture enough of the most interesting aspects of their behaviour to properly understand how they work. This limits our ability to design new molecules, to treat diseases, for example. Progress in biomolecular simulation depends crucially on increasing the computing power available. Faster classical computers are in the pipeline, but these provide only incremental improvements. Quantum computing offers the possibility of performing huge numbers of calculations in parallel, when it becomes available. We discuss the current open questions in biomolecular simulation, how these might be addressed using quantum computation and speculate on the future importance of quantum-assisted biomolecular modelling.

Computer Programming and Biomolecular Structure Studies: A Step beyond Internet Bioinformatics

ERIC Educational Resources Information Center

Likic, Vladimir A.

2006-01-01

This article describes the experience of teaching structural bioinformatics to third year undergraduate students in a subject titled "Biomolecular Structure and Bioinformatics." Students were introduced to computer programming and used this knowledge in a practical application as an alternative to the well established Internet bioinformatics…

ORAC: a molecular dynamics simulation program to explore free energy surfaces in biomolecular systems at the atomistic level.

PubMed

Marsili, Simone; Signorini, Giorgio Federico; Chelli, Riccardo; Marchi, Massimo; Procacci, Piero

2010-04-15

We present the new release of the ORAC engine (Procacci et al., Comput Chem 1997, 18, 1834), a FORTRAN suite to simulate complex biosystems at the atomistic level. The previous release of the ORAC code included multiple time steps integration, smooth particle mesh Ewald method, constant pressure and constant temperature simulations. The present release has been supplemented with the most advanced techniques for enhanced sampling in atomistic systems including replica exchange with solute tempering, metadynamics and steered molecular dynamics. All these computational technologies have been implemented for parallel architectures using the standard MPI communication protocol. ORAC is an open-source program distributed free of charge under the GNU general public license (GPL) at http://www.chim.unifi.it/orac. 2009 Wiley Periodicals, Inc.

Biomolecular characterization of glass surfaces

NASA Astrophysics Data System (ADS)

Clare, Alexis G.; Hall, Matthew M.; Korwin-Edson, Michelle L.; Goldstein, Alan H.

2003-08-01

This paper introduces the concept of biomolecular characterization of inorganic surfaces. The choice of biomolecule is discussed followed by techniques that can be used to analyse the quantity of bound species, strength of binding, the nature of binding sites, conformational changes and the layer morphology. The prospects of modelling this data using a combination of molecular dynamics simulation and protein structural modelling and the correlation to measured data are outlined. The studies described in this paper are directed toward assessing the feasibility of biomolecular characterization, however, the data collected in the process are designed to also help elucidate our understanding of the interaction between biomolecular species and inorganic materials interfaces.

Potential energy functions for atomic-level simulations of water and organic and biomolecular systems.

PubMed

Jorgensen, William L; Tirado-Rives, Julian

2005-05-10

An overview is provided on the development and status of potential energy functions that are used in atomic-level statistical mechanics and molecular dynamics simulations of water and of organic and biomolecular systems. Some topics that are considered are the form of force fields, their parameterization and performance, simulations of organic liquids, computation of free energies of hydration, universal extension for organic molecules, and choice of atomic charges. The discussion of water models covers some history, performance issues, and special topics such as nuclear quantum effects.

Application-Level Interoperability Across Grids and Clouds

NASA Astrophysics Data System (ADS)

Jha, Shantenu; Luckow, Andre; Merzky, Andre; Erdely, Miklos; Sehgal, Saurabh

Application-level interoperability is defined as the ability of an application to utilize multiple distributed heterogeneous resources. Such interoperability is becoming increasingly important with increasing volumes of data, multiple sources of data as well as resource types. The primary aim of this chapter is to understand different ways in which application-level interoperability can be provided across distributed infrastructure. We achieve this by (i) using the canonical wordcount application, based on an enhanced version of MapReduce that scales-out across clusters, clouds, and HPC resources, (ii) establishing how SAGA enables the execution of wordcount application using MapReduce and other programming models such as Sphere concurrently, and (iii) demonstrating the scale-out of ensemble-based biomolecular simulations across multiple resources. We show user-level control of the relative placement of compute and data and also provide simple performance measures and analysis of SAGA-MapReduce when using multiple, different, heterogeneous infrastructures concurrently for the same problem instance. Finally, we discuss Azure and some of the system-level abstractions that it provides and show how it is used to support ensemble-based biomolecular simulations.

Studying chemical reactions in biological systems with MBN Explorer: implementation of molecular mechanics with dynamical topology

NASA Astrophysics Data System (ADS)

Sushko, Gennady B.; Solov'yov, Ilia A.; Verkhovtsev, Alexey V.; Volkov, Sergey N.; Solov'yov, Andrey V.

2016-01-01

The concept of molecular mechanics force field has been widely accepted nowadays for studying various processes in biomolecular systems. In this paper, we suggest a modification for the standard CHARMM force field that permits simulations of systems with dynamically changing molecular topologies. The implementation of the modified force field was carried out in the popular program MBN Explorer, and, to support the development, we provide several illustrative case studies where dynamical topology is necessary. In particular, it is shown that the modified molecular mechanics force field can be applied for studying processes where rupture of chemical bonds plays an essential role, e.g., in irradiation- or collision-induced damage, and also in transformation and fragmentation processes involving biomolecular systems. Contribution to the Topical Issue "COST Action Nano-IBCT: Nano-scale Processes Behind Ion-Beam Cancer Therapy", edited by Andrey V. Solov'yov, Nigel Mason, Gustavo Garcia and Eugene Surdutovich.

iBIOMES Lite: Summarizing Biomolecular Simulation Data in Limited Settings

PubMed Central

2015-01-01

As the amount of data generated by biomolecular simulations dramatically increases, new tools need to be developed to help manage this data at the individual investigator or small research group level. In this paper, we introduce iBIOMES Lite, a lightweight tool for biomolecular simulation data indexing and summarization. The main goal of iBIOMES Lite is to provide a simple interface to summarize computational experiments in a setting where the user might have limited privileges and limited access to IT resources. A command-line interface allows the user to summarize, publish, and search local simulation data sets. Published data sets are accessible via static hypertext markup language (HTML) pages that summarize the simulation protocols and also display data analysis graphically. The publication process is customized via extensible markup language (XML) descriptors while the HTML summary template is customized through extensible stylesheet language (XSL). iBIOMES Lite was tested on different platforms and at several national computing centers using various data sets generated through classical and quantum molecular dynamics, quantum chemistry, and QM/MM. The associated parsers currently support AMBER, GROMACS, Gaussian, and NWChem data set publication. The code is available at https://github.com/jcvthibault/ibiomes. PMID:24830957

21st International Conference on DNA Computing and Molecular Programming: 8.1 Biochemistry

DTIC Science & Technology

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fogarty, Aoife C., E-mail: fogarty@mpip-mainz.mpg.de; Potestio, Raffaello, E-mail: potestio@mpip-mainz.mpg.de; Kremer, Kurt, E-mail: kremer@mpip-mainz.mpg.de

A fully atomistic modelling of many biophysical and biochemical processes at biologically relevant length- and time scales is beyond our reach with current computational resources, and one approach to overcome this difficulty is the use of multiscale simulation techniques. In such simulations, when system properties necessitate a boundary between resolutions that falls within the solvent region, one can use an approach such as the Adaptive Resolution Scheme (AdResS), in which solvent particles change their resolution on the fly during the simulation. Here, we apply the existing AdResS methodology to biomolecular systems, simulating a fully atomistic protein with an atomistic hydrationmore » shell, solvated in a coarse-grained particle reservoir and heat bath. Using as a test case an aqueous solution of the regulatory protein ubiquitin, we first confirm the validity of the AdResS approach for such systems, via an examination of protein and solvent structural and dynamical properties. We then demonstrate how, in addition to providing a computational speedup, such a multiscale AdResS approach can yield otherwise inaccessible physical insights into biomolecular function. We use our methodology to show that protein structure and dynamics can still be correctly modelled using only a few shells of atomistic water molecules. We also discuss aspects of the AdResS methodology peculiar to biomolecular simulations.« less

Agent-based models of cellular systems.

PubMed

Cannata, Nicola; Corradini, Flavio; Merelli, Emanuela; Tesei, Luca

2013-01-01

Software agents are particularly suitable for engineering models and simulations of cellular systems. In a very natural and intuitive manner, individual software components are therein delegated to reproduce "in silico" the behavior of individual components of alive systems at a given level of resolution. Individuals' actions and interactions among individuals allow complex collective behavior to emerge. In this chapter we first introduce the readers to software agents and multi-agent systems, reviewing the evolution of agent-based modeling of biomolecular systems in the last decade. We then describe the main tools, platforms, and methodologies available for programming societies of agents, possibly profiting also of toolkits that do not require advanced programming skills.

Adaptive resolution simulation of a biomolecule and its hydration shell: Structural and dynamical properties

NASA Astrophysics Data System (ADS)

Fogarty, Aoife C.; Potestio, Raffaello; Kremer, Kurt

2015-05-01

A fully atomistic modelling of many biophysical and biochemical processes at biologically relevant length- and time scales is beyond our reach with current computational resources, and one approach to overcome this difficulty is the use of multiscale simulation techniques. In such simulations, when system properties necessitate a boundary between resolutions that falls within the solvent region, one can use an approach such as the Adaptive Resolution Scheme (AdResS), in which solvent particles change their resolution on the fly during the simulation. Here, we apply the existing AdResS methodology to biomolecular systems, simulating a fully atomistic protein with an atomistic hydration shell, solvated in a coarse-grained particle reservoir and heat bath. Using as a test case an aqueous solution of the regulatory protein ubiquitin, we first confirm the validity of the AdResS approach for such systems, via an examination of protein and solvent structural and dynamical properties. We then demonstrate how, in addition to providing a computational speedup, such a multiscale AdResS approach can yield otherwise inaccessible physical insights into biomolecular function. We use our methodology to show that protein structure and dynamics can still be correctly modelled using only a few shells of atomistic water molecules. We also discuss aspects of the AdResS methodology peculiar to biomolecular simulations.

Scalable Molecular Dynamics with NAMD

PubMed Central

Phillips, James C.; Braun, Rosemary; Wang, Wei; Gumbart, James; Tajkhorshid, Emad; Villa, Elizabeth; Chipot, Christophe; Skeel, Robert D.; Kalé, Laxmikant; Schulten, Klaus

2008-01-01

NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD scales to hundreds of processors on high-end parallel platforms, as well as tens of processors on low-cost commodity clusters, and also runs on individual desktop and laptop computers. NAMD works with AMBER and CHARMM potential functions, parameters, and file formats. This paper, directed to novices as well as experts, first introduces concepts and methods used in the NAMD program, describing the classical molecular dynamics force field, equations of motion, and integration methods along with the efficient electrostatics evaluation algorithms employed and temperature and pressure controls used. Features for steering the simulation across barriers and for calculating both alchemical and conformational free energy differences are presented. The motivations for and a roadmap to the internal design of NAMD, implemented in C++ and based on Charm++ parallel objects, are outlined. The factors affecting the serial and parallel performance of a simulation are discussed. Next, typical NAMD use is illustrated with representative applications to a small, a medium, and a large biomolecular system, highlighting particular features of NAMD, e.g., the Tcl scripting language. Finally, the paper provides a list of the key features of NAMD and discusses the benefits of combining NAMD with the molecular graphics/sequence analysis software VMD and the grid computing/collaboratory software BioCoRE. NAMD is distributed free of charge with source code at www.ks.uiuc.edu. PMID:16222654

Enhanced sampling techniques in biomolecular simulations.

PubMed

Spiwok, Vojtech; Sucur, Zoran; Hosek, Petr

2015-11-01

Biomolecular simulations are routinely used in biochemistry and molecular biology research; however, they often fail to match expectations of their impact on pharmaceutical and biotech industry. This is caused by the fact that a vast amount of computer time is required to simulate short episodes from the life of biomolecules. Several approaches have been developed to overcome this obstacle, including application of massively parallel and special purpose computers or non-conventional hardware. Methodological approaches are represented by coarse-grained models and enhanced sampling techniques. These techniques can show how the studied system behaves in long time-scales on the basis of relatively short simulations. This review presents an overview of new simulation approaches, the theory behind enhanced sampling methods and success stories of their applications with a direct impact on biotechnology or drug design. Copyright © 2014 Elsevier Inc. All rights reserved.

Perspective: Markov models for long-timescale biomolecular dynamics.

PubMed

Schwantes, C R; McGibbon, R T; Pande, V S

2014-09-07

Molecular dynamics simulations have the potential to provide atomic-level detail and insight to important questions in chemical physics that cannot be observed in typical experiments. However, simply generating a long trajectory is insufficient, as researchers must be able to transform the data in a simulation trajectory into specific scientific insights. Although this analysis step has often been taken for granted, it deserves further attention as large-scale simulations become increasingly routine. In this perspective, we discuss the application of Markov models to the analysis of large-scale biomolecular simulations. We draw attention to recent improvements in the construction of these models as well as several important open issues. In addition, we highlight recent theoretical advances that pave the way for a new generation of models of molecular kinetics.

CHARMM: The Biomolecular Simulation Program

PubMed Central

Brooks, B.R.; Brooks, C.L.; MacKerell, A.D.; Nilsson, L.; Petrella, R.J.; Roux, B.; Won, Y.; Archontis, G.; Bartels, C.; Boresch, S.; Caflisch, A.; Caves, L.; Cui, Q.; Dinner, A.R.; Feig, M.; Fischer, S.; Gao, J.; Hodoscek, M.; Im, W.; Kuczera, K.; Lazaridis, T.; Ma, J.; Ovchinnikov, V.; Paci, E.; Pastor, R.W.; Post, C.B.; Pu, J.Z.; Schaefer, M.; Tidor, B.; Venable, R. M.; Woodcock, H. L.; Wu, X.; Yang, W.; York, D.M.; Karplus, M.

2009-01-01

CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecular simulation program. It has been developed over the last three decades with a primary focus on molecules of biological interest, including proteins, peptides, lipids, nucleic acids, carbohydrates and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estimators, molecular minimization, dynamics, and analysis techniques, and model-building capabilities. In addition, the CHARMM program is applicable to problems involving a much broader class of many-particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numerous platforms in both serial and parallel architectures. This paper provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM paper in 1983. PMID:19444816

Theoretical approaches for dynamical ordering of biomolecular systems.

PubMed

Okumura, Hisashi; Higashi, Masahiro; Yoshida, Yuichiro; Sato, Hirofumi; Akiyama, Ryo

2018-02-01

Living systems are characterized by the dynamic assembly and disassembly of biomolecules. The dynamical ordering mechanism of these biomolecules has been investigated both experimentally and theoretically. The main theoretical approaches include quantum mechanical (QM) calculation, all-atom (AA) modeling, and coarse-grained (CG) modeling. The selected approach depends on the size of the target system (which differs among electrons, atoms, molecules, and molecular assemblies). These hierarchal approaches can be combined with molecular dynamics (MD) simulation and/or integral equation theories for liquids, which cover all size hierarchies. We review the framework of quantum mechanical/molecular mechanical (QM/MM) calculations, AA MD simulations, CG modeling, and integral equation theories. Applications of these methods to the dynamical ordering of biomolecular systems are also exemplified. The QM/MM calculation enables the study of chemical reactions. The AA MD simulation, which omits the QM calculation, can follow longer time-scale phenomena. By reducing the number of degrees of freedom and the computational cost, CG modeling can follow much longer time-scale phenomena than AA modeling. Integral equation theories for liquids elucidate the liquid structure, for example, whether the liquid follows a radial distribution function. These theoretical approaches can analyze the dynamic behaviors of biomolecular systems. They also provide useful tools for exploring the dynamic ordering systems of biomolecules, such as self-assembly. This article is part of a Special Issue entitled "Biophysical Exploration of Dynamical Ordering of Biomolecular Systems" edited by Dr. Koichi Kato. Copyright © 2017 Elsevier B.V. All rights reserved.

Thermodynamic properties of water solvating biomolecular surfaces

NASA Astrophysics Data System (ADS)

Heyden, Matthias

Changes in the potential energy and entropy of water molecules hydrating biomolecular interfaces play a significant role for biomolecular solubility and association. Free energy perturbation and thermodynamic integration methods allow calculations of free energy differences between two states from simulations. However, these methods are computationally demanding and do not provide insights into individual thermodynamic contributions, i.e. changes in the solvent energy or entropy. Here, we employ methods to spatially resolve distributions of hydration water thermodynamic properties in the vicinity of biomolecular surfaces. This allows direct insights into thermodynamic signatures of the hydration of hydrophobic and hydrophilic solvent accessible sites of proteins and small molecules and comparisons to ideal model surfaces. We correlate dynamic properties of hydration water molecules, i.e. translational and rotational mobility, to their thermodynamics. The latter can be used as a guide to extract thermodynamic information from experimental measurements of site-resolved water dynamics. Further, we study energy-entropy compensations of water at different hydration sites of biomolecular surfaces. This work is supported by the Cluster of Excellence RESOLV (EXC 1069) funded by the Deutsche Forschungsgemeinschaft.

Virtual interface substructure synthesis method for normal mode analysis of super-large molecular complexes at atomic resolution.

PubMed

Chen, Xuehui; Sun, Yunxiang; An, Xiongbo; Ming, Dengming

2011-10-14

Normal mode analysis of large biomolecular complexes at atomic resolution remains challenging in computational structure biology due to the requirement of large amount of memory space and central processing unit time. In this paper, we present a method called virtual interface substructure synthesis method or VISSM to calculate approximate normal modes of large biomolecular complexes at atomic resolution. VISSM introduces the subunit interfaces as independent substructures that join contacting molecules so as to keep the integrity of the system. Compared with other approximate methods, VISSM delivers atomic modes with no need of a coarse-graining-then-projection procedure. The method was examined for 54 protein-complexes with the conventional all-atom normal mode analysis using CHARMM simulation program and the overlap of the first 100 low-frequency modes is greater than 0.7 for 49 complexes, indicating its accuracy and reliability. We then applied VISSM to the satellite panicum mosaic virus (SPMV, 78,300 atoms) and to F-actin filament structures of up to 39-mer, 228,813 atoms and found that VISSM calculations capture functionally important conformational changes accessible to these structures at atomic resolution. Our results support the idea that the dynamics of a large biomolecular complex might be understood based on the motions of its component subunits and the way in which subunits bind one another. © 2011 American Institute of Physics

Relaxation mode analysis of a peptide system: comparison with principal component analysis.

PubMed

Mitsutake, Ayori; Iijima, Hiromitsu; Takano, Hiroshi

2011-10-28

This article reports the first attempt to apply the relaxation mode analysis method to a simulation of a biomolecular system. In biomolecular systems, the principal component analysis is a well-known method for analyzing the static properties of fluctuations of structures obtained by a simulation and classifying the structures into some groups. On the other hand, the relaxation mode analysis has been used to analyze the dynamic properties of homopolymer systems. In this article, a long Monte Carlo simulation of Met-enkephalin in gas phase has been performed. The results are analyzed by the principal component analysis and relaxation mode analysis methods. We compare the results of both methods and show the effectiveness of the relaxation mode analysis.

H++ 3.0: automating pK prediction and the preparation of biomolecular structures for atomistic molecular modeling and simulations.

PubMed

Anandakrishnan, Ramu; Aguilar, Boris; Onufriev, Alexey V

2012-07-01

The accuracy of atomistic biomolecular modeling and simulation studies depend on the accuracy of the input structures. Preparing these structures for an atomistic modeling task, such as molecular dynamics (MD) simulation, can involve the use of a variety of different tools for: correcting errors, adding missing atoms, filling valences with hydrogens, predicting pK values for titratable amino acids, assigning predefined partial charges and radii to all atoms, and generating force field parameter/topology files for MD. Identifying, installing and effectively using the appropriate tools for each of these tasks can be difficult for novice and time-consuming for experienced users. H++ (http://biophysics.cs.vt.edu/) is a free open-source web server that automates the above key steps in the preparation of biomolecular structures for molecular modeling and simulations. H++ also performs extensive error and consistency checking, providing error/warning messages together with the suggested corrections. In addition to numerous minor improvements, the latest version of H++ includes several new capabilities and options: fix erroneous (flipped) side chain conformations for HIS, GLN and ASN, include a ligand in the input structure, process nucleic acid structures and generate a solvent box with specified number of common ions for explicit solvent MD.

Resolution-Adapted All-Atomic and Coarse-Grained Model for Biomolecular Simulations.

PubMed

Shen, Lin; Hu, Hao

2014-06-10

We develop here an adaptive multiresolution method for the simulation of complex heterogeneous systems such as the protein molecules. The target molecular system is described with the atomistic structure while maintaining concurrently a mapping to the coarse-grained models. The theoretical model, or force field, used to describe the interactions between two sites is automatically adjusted in the simulation processes according to the interaction distance/strength. Therefore, all-atomic, coarse-grained, or mixed all-atomic and coarse-grained models would be used together to describe the interactions between a group of atoms and its surroundings. Because the choice of theory is made on the force field level while the sampling is always carried out in the atomic space, the new adaptive method preserves naturally the atomic structure and thermodynamic properties of the entire system throughout the simulation processes. The new method will be very useful in many biomolecular simulations where atomistic details are critically needed.

Dynamics Govern Specificity of a Protein-Protein Interface: Substrate Recognition by Thrombin.

PubMed

Fuchs, Julian E; Huber, Roland G; Waldner, Birgit J; Kahler, Ursula; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R

2015-01-01

Biomolecular recognition is crucial in cellular signal transduction. Signaling is mediated through molecular interactions at protein-protein interfaces. Still, specificity and promiscuity of protein-protein interfaces cannot be explained using simplistic static binding models. Our study rationalizes specificity of the prototypic protein-protein interface between thrombin and its peptide substrates relying solely on binding site dynamics derived from molecular dynamics simulations. We find conformational selection and thus dynamic contributions to be a key player in biomolecular recognition. Arising entropic contributions complement chemical intuition primarily reflecting enthalpic interaction patterns. The paradigm "dynamics govern specificity" might provide direct guidance for the identification of specific anchor points in biomolecular recognition processes and structure-based drug design.

ANCA: Anharmonic Conformational Analysis of Biomolecular Simulations.

PubMed

Parvatikar, Akash; Vacaliuc, Gabriel S; Ramanathan, Arvind; Chennubhotla, S Chakra

2018-05-08

Anharmonicity in time-dependent conformational fluctuations is noted to be a key feature of functional dynamics of biomolecules. Although anharmonic events are rare, long-timescale (μs-ms and beyond) simulations facilitate probing of such events. We have previously developed quasi-anharmonic analysis to resolve higher-order spatial correlations and characterize anharmonicity in biomolecular simulations. In this article, we have extended this toolbox to resolve higher-order temporal correlations and built a scalable Python package called anharmonic conformational analysis (ANCA). ANCA has modules to: 1) measure anharmonicity in the form of higher-order statistics and its variation as a function of time, 2) output a storyboard representation of the simulations to identify key anharmonic conformational events, and 3) identify putative anharmonic conformational substates and visualization of transitions between these substates. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Simulation of FRET dyes allows quantitative comparison against experimental data

NASA Astrophysics Data System (ADS)

Reinartz, Ines; Sinner, Claude; Nettels, Daniel; Stucki-Buchli, Brigitte; Stockmar, Florian; Panek, Pawel T.; Jacob, Christoph R.; Nienhaus, Gerd Ulrich; Schuler, Benjamin; Schug, Alexander

2018-03-01

Fully understanding biomolecular function requires detailed insight into the systems' structural dynamics. Powerful experimental techniques such as single molecule Förster Resonance Energy Transfer (FRET) provide access to such dynamic information yet have to be carefully interpreted. Molecular simulations can complement these experiments but typically face limits in accessing slow time scales and large or unstructured systems. Here, we introduce a coarse-grained simulation technique that tackles these challenges. While requiring only few parameters, we maintain full protein flexibility and include all heavy atoms of proteins, linkers, and dyes. We are able to sufficiently reduce computational demands to simulate large or heterogeneous structural dynamics and ensembles on slow time scales found in, e.g., protein folding. The simulations allow for calculating FRET efficiencies which quantitatively agree with experimentally determined values. By providing atomically resolved trajectories, this work supports the planning and microscopic interpretation of experiments. Overall, these results highlight how simulations and experiments can complement each other leading to new insights into biomolecular dynamics and function.

New Funding Opportunity from the Human Biomolecular Atlas Program (HuBMAP)! | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

The NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) aims to develop a framework for functional mapping the human body with cellular resolution to enhance our understanding of cellular organization-function. HuBMAP will accelerate the development of the next generation of tools and techniques to generate 3D tissue maps using validated high-content, high-throughput imaging and omics assays, and establish an open data platform for integrating, visualizing data to build multi-dimensional maps.

Dynamics Govern Specificity of a Protein-Protein Interface: Substrate Recognition by Thrombin

PubMed Central

Fuchs, Julian E.; Huber, Roland G.; Waldner, Birgit J.; Kahler, Ursula; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R.

2015-01-01

Biomolecular recognition is crucial in cellular signal transduction. Signaling is mediated through molecular interactions at protein-protein interfaces. Still, specificity and promiscuity of protein-protein interfaces cannot be explained using simplistic static binding models. Our study rationalizes specificity of the prototypic protein-protein interface between thrombin and its peptide substrates relying solely on binding site dynamics derived from molecular dynamics simulations. We find conformational selection and thus dynamic contributions to be a key player in biomolecular recognition. Arising entropic contributions complement chemical intuition primarily reflecting enthalpic interaction patterns. The paradigm “dynamics govern specificity” might provide direct guidance for the identification of specific anchor points in biomolecular recognition processes and structure-based drug design. PMID:26496636

GROMACS 4:  Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation.

PubMed

Hess, Berk; Kutzner, Carsten; van der Spoel, David; Lindahl, Erik

2008-03-01

Molecular simulation is an extremely useful, but computationally very expensive tool for studies of chemical and biomolecular systems. Here, we present a new implementation of our molecular simulation toolkit GROMACS which now both achieves extremely high performance on single processors from algorithmic optimizations and hand-coded routines and simultaneously scales very well on parallel machines. The code encompasses a minimal-communication domain decomposition algorithm, full dynamic load balancing, a state-of-the-art parallel constraint solver, and efficient virtual site algorithms that allow removal of hydrogen atom degrees of freedom to enable integration time steps up to 5 fs for atomistic simulations also in parallel. To improve the scaling properties of the common particle mesh Ewald electrostatics algorithms, we have in addition used a Multiple-Program, Multiple-Data approach, with separate node domains responsible for direct and reciprocal space interactions. Not only does this combination of algorithms enable extremely long simulations of large systems but also it provides that simulation performance on quite modest numbers of standard cluster nodes.

g_contacts: Fast contact search in bio-molecular ensemble data

NASA Astrophysics Data System (ADS)

Blau, Christian; Grubmuller, Helmut

2013-12-01

Short-range interatomic interactions govern many bio-molecular processes. Therefore, identifying close interaction partners in ensemble data is an essential task in structural biology and computational biophysics. A contact search can be cast as a typical range search problem for which efficient algorithms have been developed. However, none of those has yet been adapted to the context of macromolecular ensembles, particularly in a molecular dynamics (MD) framework. Here a set-decomposition algorithm is implemented which detects all contacting atoms or residues in maximum O(Nlog(N)) run-time, in contrast to the O(N2) complexity of a brute-force approach. Catalogue identifier: AEQA_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEQA_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 8945 No. of bytes in distributed program, including test data, etc.: 981604 Distribution format: tar.gz Programming language: C99. Computer: PC. Operating system: Linux. RAM: ≈Size of input frame Classification: 3, 4.14. External routines: Gromacs 4.6[1] Nature of problem: Finding atoms or residues that are closer to one another than a given cut-off. Solution method: Excluding distant atoms from distance calculations by decomposing the given set of atoms into disjoint subsets. Running time:≤O(Nlog(N)) References: [1] S. Pronk, S. Pall, R. Schulz, P. Larsson, P. Bjelkmar, R. Apostolov, M. R. Shirts, J.C. Smith, P. M. Kasson, D. van der Spoel, B. Hess and Erik Lindahl, Gromacs 4.5: a high-throughput and highly parallel open source molecular simulation toolkit, Bioinformatics 29 (7) (2013).

A mechanical Turing machine: blueprint for a biomolecular computer

PubMed Central

Shapiro, Ehud

2012-01-01

We describe a working mechanical device that embodies the theoretical computing machine of Alan Turing, and as such is a universal programmable computer. The device operates on three-dimensional building blocks by applying mechanical analogues of polymer elongation, cleavage and ligation, movement along a polymer, and control by molecular recognition unleashing allosteric conformational changes. Logically, the device is not more complicated than biomolecular machines of the living cell, and all its operations are part of the standard repertoire of these machines; hence, a biomolecular embodiment of the device is not infeasible. If implemented, such a biomolecular device may operate in vivo, interacting with its biochemical environment in a program-controlled manner. In particular, it may ‘compute’ synthetic biopolymers and release them into its environment in response to input from the environment, a capability that may have broad pharmaceutical and biological applications. PMID:22649583

A DNA network as an information processing system.

PubMed

Santini, Cristina Costa; Bath, Jonathan; Turberfield, Andrew J; Tyrrell, Andy M

2012-01-01

Biomolecular systems that can process information are sought for computational applications, because of their potential for parallelism and miniaturization and because their biocompatibility also makes them suitable for future biomedical applications. DNA has been used to design machines, motors, finite automata, logic gates, reaction networks and logic programs, amongst many other structures and dynamic behaviours. Here we design and program a synthetic DNA network to implement computational paradigms abstracted from cellular regulatory networks. These show information processing properties that are desirable in artificial, engineered molecular systems, including robustness of the output in relation to different sources of variation. We show the results of numerical simulations of the dynamic behaviour of the network and preliminary experimental analysis of its main components.

Electron-correlated fragment-molecular-orbital calculations for biomolecular and nano systems.

PubMed

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.

CG2AA: backmapping protein coarse-grained structures.

PubMed

Lombardi, Leandro E; Martí, Marcelo A; Capece, Luciana

2016-04-15

Coarse grain (CG) models allow long-scale simulations with a much lower computational cost than that of all-atom simulations. However, the absence of atomistic detail impedes the analysis of specific atomic interactions that are determinant in most interesting biomolecular processes. In order to study these phenomena, it is necessary to reconstruct the atomistic structure from the CG representation. This structure can be analyzed by itself or be used as an onset for atomistic molecular dynamics simulations. In this work, we present a computer program that accurately reconstructs the atomistic structure from a CG model for proteins, using a simple geometrical algorithm. The software is free and available online at http://www.ic.fcen.uba.ar/cg2aa/cg2aa.py Supplementary data are available at Bioinformatics online. lula@qi.fcen.uba.ar. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Mapping to Irregular Torus Topologies and Other Techniques for Petascale Biomolecular Simulation

PubMed Central

Phillips, James C.; Sun, Yanhua; Jain, Nikhil; Bohm, Eric J.; Kalé, Laxmikant V.

2014-01-01

Currently deployed petascale supercomputers typically use toroidal network topologies in three or more dimensions. While these networks perform well for topology-agnostic codes on a few thousand nodes, leadership machines with 20,000 nodes require topology awareness to avoid network contention for communication-intensive codes. Topology adaptation is complicated by irregular node allocation shapes and holes due to dedicated input/output nodes or hardware failure. In the context of the popular molecular dynamics program NAMD, we present methods for mapping a periodic 3-D grid of fixed-size spatial decomposition domains to 3-D Cray Gemini and 5-D IBM Blue Gene/Q toroidal networks to enable hundred-million atom full machine simulations, and to similarly partition node allocations into compact domains for smaller simulations using multiple-copy algorithms. Additional enabling techniques are discussed and performance is reported for NCSA Blue Waters, ORNL Titan, ANL Mira, TACC Stampede, and NERSC Edison. PMID:25594075

Multiple-basin energy landscapes for large-amplitude conformational motions of proteins: Structure-based molecular dynamics simulations

PubMed Central

Okazaki, Kei-ichi; Koga, Nobuyasu; Takada, Shoji; Onuchic, Jose N.; Wolynes, Peter G.

2006-01-01

Biomolecules often undergo large-amplitude motions when they bind or release other molecules. Unlike macroscopic machines, these biomolecular machines can partially disassemble (unfold) and then reassemble (fold) during such transitions. Here we put forward a minimal structure-based model, the “multiple-basin model,” that can directly be used for molecular dynamics simulation of even very large biomolecular systems so long as the endpoints of the conformational change are known. We investigate the model by simulating large-scale motions of four proteins: glutamine-binding protein, S100A6, dihydrofolate reductase, and HIV-1 protease. The mechanisms of conformational transition depend on the protein basin topologies and change with temperature near the folding transition. The conformational transition rate varies linearly with driving force over a fairly large range. This linearity appears to be a consequence of partial unfolding during the conformational transition. PMID:16877541

In pursuit of an accurate spatial and temporal model of biomolecules at the atomistic level: a perspective on computer simulation.

PubMed

Gray, Alan; Harlen, Oliver G; Harris, Sarah A; Khalid, Syma; Leung, Yuk Ming; Lonsdale, Richard; Mulholland, Adrian J; Pearson, Arwen R; Read, Daniel J; Richardson, Robin A

2015-01-01

Despite huge advances in the computational techniques available for simulating biomolecules at the quantum-mechanical, atomistic and coarse-grained levels, there is still a widespread perception amongst the experimental community that these calculations are highly specialist and are not generally applicable by researchers outside the theoretical community. In this article, the successes and limitations of biomolecular simulation and the further developments that are likely in the near future are discussed. A brief overview is also provided of the experimental biophysical methods that are commonly used to probe biomolecular structure and dynamics, and the accuracy of the information that can be obtained from each is compared with that from modelling. It is concluded that progress towards an accurate spatial and temporal model of biomacromolecules requires a combination of all of these biophysical techniques, both experimental and computational.

DspaceOgre 3D Graphics Visualization Tool

NASA Technical Reports Server (NTRS)

Jain, Abhinandan; Myin, Steven; Pomerantz, Marc I.

2011-01-01

This general-purpose 3D graphics visualization C++ tool is designed for visualization of simulation and analysis data for articulated mechanisms. Examples of such systems are vehicles, robotic arms, biomechanics models, and biomolecular structures. DspaceOgre builds upon the open-source Ogre3D graphics visualization library. It provides additional classes to support the management of complex scenes involving multiple viewpoints and different scene groups, and can be used as a remote graphics server. This software provides improved support for adding programs at the graphics processing unit (GPU) level for improved performance. It also improves upon the messaging interface it exposes for use as a visualization server.

Perspective: Watching low-frequency vibrations of water in biomolecular recognition by THz spectroscopy.

PubMed

Xu, Yao; Havenith, Martina

2015-11-07

Terahertz (THz) spectroscopy has turned out to be a powerful tool which is able to shed new light on the role of water in biomolecular processes. The low frequency spectrum of the solvated biomolecule in combination with MD simulations provides deep insights into the collective hydrogen bond dynamics on the sub-ps time scale. The absorption spectrum between 1 THz and 10 THz of solvated biomolecules is sensitive to changes in the fast fluctuations of the water network. Systematic studies on mutants of antifreeze proteins indicate a direct correlation between biological activity and a retardation of the (sub)-ps hydration dynamics at the protein binding site, i.e., a "hydration funnel." Kinetic THz absorption studies probe the temporal changes of THz absorption during a biological process, and give access to the kinetics of the coupled protein-hydration dynamics. When combined with simulations, the observed results can be explained in terms of a two-tier model involving a local binding and a long range influence on the hydration bond dynamics of the water around the binding site that highlights the significance of the changes in the hydration dynamics at recognition site for biomolecular recognition. Water is shown to assist molecular recognition processes.

Perspective: Watching low-frequency vibrations of water in biomolecular recognition by THz spectroscopy

NASA Astrophysics Data System (ADS)

Xu, Yao; Havenith, Martina

2015-11-01

Terahertz (THz) spectroscopy has turned out to be a powerful tool which is able to shed new light on the role of water in biomolecular processes. The low frequency spectrum of the solvated biomolecule in combination with MD simulations provides deep insights into the collective hydrogen bond dynamics on the sub-ps time scale. The absorption spectrum between 1 THz and 10 THz of solvated biomolecules is sensitive to changes in the fast fluctuations of the water network. Systematic studies on mutants of antifreeze proteins indicate a direct correlation between biological activity and a retardation of the (sub)-ps hydration dynamics at the protein binding site, i.e., a "hydration funnel." Kinetic THz absorption studies probe the temporal changes of THz absorption during a biological process, and give access to the kinetics of the coupled protein-hydration dynamics. When combined with simulations, the observed results can be explained in terms of a two-tier model involving a local binding and a long range influence on the hydration bond dynamics of the water around the binding site that highlights the significance of the changes in the hydration dynamics at recognition site for biomolecular recognition. Water is shown to assist molecular recognition processes.

Stochastic Simulation of Biomolecular Networks in Dynamic Environments

PubMed Central

Voliotis, Margaritis; Thomas, Philipp; Grima, Ramon; Bowsher, Clive G.

2016-01-01

Simulation of biomolecular networks is now indispensable for studying biological systems, from small reaction networks to large ensembles of cells. Here we present a novel approach for stochastic simulation of networks embedded in the dynamic environment of the cell and its surroundings. We thus sample trajectories of the stochastic process described by the chemical master equation with time-varying propensities. A comparative analysis shows that existing approaches can either fail dramatically, or else can impose impractical computational burdens due to numerical integration of reaction propensities, especially when cell ensembles are studied. Here we introduce the Extrande method which, given a simulated time course of dynamic network inputs, provides a conditionally exact and several orders-of-magnitude faster simulation solution. The new approach makes it feasible to demonstrate—using decision-making by a large population of quorum sensing bacteria—that robustness to fluctuations from upstream signaling places strong constraints on the design of networks determining cell fate. Our approach has the potential to significantly advance both understanding of molecular systems biology and design of synthetic circuits. PMID:27248512

Massively parallel implementation of 3D-RISM calculation with volumetric 3D-FFT.

PubMed

Maruyama, Yutaka; Yoshida, Norio; Tadano, Hiroto; Takahashi, Daisuke; Sato, Mitsuhisa; Hirata, Fumio

2014-07-05

A new three-dimensional reference interaction site model (3D-RISM) program for massively parallel machines combined with the volumetric 3D fast Fourier transform (3D-FFT) was developed, and tested on the RIKEN K supercomputer. The ordinary parallel 3D-RISM program has a limitation on the number of parallelizations because of the limitations of the slab-type 3D-FFT. The volumetric 3D-FFT relieves this limitation drastically. We tested the 3D-RISM calculation on the large and fine calculation cell (2048(3) grid points) on 16,384 nodes, each having eight CPU cores. The new 3D-RISM program achieved excellent scalability to the parallelization, running on the RIKEN K supercomputer. As a benchmark application, we employed the program, combined with molecular dynamics simulation, to analyze the oligomerization process of chymotrypsin Inhibitor 2 mutant. The results demonstrate that the massive parallel 3D-RISM program is effective to analyze the hydration properties of the large biomolecular systems. Copyright © 2014 Wiley Periodicals, Inc.

GROMOS polarizable charge-on-spring models for liquid urea: COS/U and COS/U2

NASA Astrophysics Data System (ADS)

Lin, Zhixiong; Bachmann, Stephan J.; van Gunsteren, Wilfred F.

2015-03-01

Two one-site polarizable urea models, COS/U and COS/U2, based on the charge-on-spring model are proposed. The models are parametrized against thermodynamic properties of urea-water mixtures in combination with the polarizable COS/G2 and COS/D2 models for liquid water, respectively, and have the same functional form of the inter-atomic interaction function and are based on the same parameter calibration procedure and type of experimental data as used to develop the GROMOS biomolecular force field. Thermodynamic, dielectric, and dynamic properties of urea-water mixtures simulated using the polarizable models are closer to experimental data than using the non-polarizable models. The COS/U and COS/U2 models may be used in biomolecular simulations of protein denaturation.

Probing biomolecular interaction forces using an anharmonic acoustic technique for selective detection of bacterial spores.

PubMed

Ghosh, Sourav K; Ostanin, Victor P; Johnson, Christian L; Lowe, Christopher R; Seshia, Ashwin A

2011-11-15

Receptor-based detection of pathogens often suffers from non-specific interactions, and as most detection techniques cannot distinguish between affinities of interactions, false positive responses remain a plaguing reality. Here, we report an anharmonic acoustic based method of detection that addresses the inherent weakness of current ligand dependant assays. Spores of Bacillus subtilis (Bacillus anthracis simulant) were immobilized on a thickness-shear mode AT-cut quartz crystal functionalized with anti-spore antibody and the sensor was driven by a pure sinusoidal oscillation at increasing amplitude. Biomolecular interaction forces between the coupled spores and the accelerating surface caused a nonlinear modulation of the acoustic response of the crystal. In particular, the deviation in the third harmonic of the transduced electrical response versus oscillation amplitude of the sensor (signal) was found to be significant. Signals from the specifically-bound spores were clearly distinguishable in shape from those of the physisorbed streptavidin-coated polystyrene microbeads. The analytical model presented here enables estimation of the biomolecular interaction forces from the measured response. Thus, probing biomolecular interaction forces using the described technique can quantitatively detect pathogens and distinguish specific from non-specific interactions, with potential applicability to rapid point-of-care detection. This also serves as a potential tool for rapid force-spectroscopy, affinity-based biomolecular screening and mapping of molecular interaction networks. Copyright © 2011 Elsevier B.V. All rights reserved.

Comparison of structural, thermodynamic, kinetic and mass transport properties of Mg(2+) ion models commonly used in biomolecular simulations.

PubMed

Panteva, Maria T; Giambaşu, George M; York, Darrin M

2015-05-15

The prevalence of Mg(2+) ions in biology and their essential role in nucleic acid structure and function has motivated the development of various Mg(2+) ion models for use in molecular simulations. Currently, the most widely used models in biomolecular simulations represent a nonbonded metal ion as an ion-centered point charge surrounded by a nonelectrostatic pairwise potential that takes into account dispersion interactions and exchange effects that give rise to the ion's excluded volume. One strategy toward developing improved models for biomolecular simulations is to first identify a Mg(2+) model that is consistent with the simulation force fields that closely reproduces a range of properties in aqueous solution, and then, in a second step, balance the ion-water and ion-solute interactions by tuning parameters in a pairwise fashion where necessary. The present work addresses the first step in which we compare 17 different nonbonded single-site Mg(2+) ion models with respect to their ability to simultaneously reproduce structural, thermodynamic, kinetic and mass transport properties in aqueous solution. None of the models based on a 12-6 nonelectrostatic nonbonded potential was able to reproduce the experimental radial distribution function, solvation free energy, exchange barrier and diffusion constant. The models based on a 12-6-4 potential offered improvement, and one model in particular, in conjunction with the SPC/E water model, performed exceptionally well for all properties. The results reported here establish useful benchmark calculations for Mg(2+) ion models that provide insight into the origin of the behavior in aqueous solution, and may aid in the development of next-generation models that target specific binding sites in biomolecules. © 2015 Wiley Periodicals, Inc.

NRL Fact Book

DTIC Science & Technology

1991-05-01

Bio/Molecular Science & Engineering High Resolution Patterning Program Manager Archaebacteria Research Program Manager ONT Receptor Based Biosensor...CMC) in discharging their responsibilities on matters of general scientific and technical interest to the United States in the United Kingdom , Europe

An Assembly Funnel Makes Biomolecular Complex Assembly Efficient

PubMed Central

Zenk, John; Schulman, Rebecca

2014-01-01

Like protein folding and crystallization, the self-assembly of complexes is a fundamental form of biomolecular organization. While the number of methods for creating synthetic complexes is growing rapidly, most require empirical tuning of assembly conditions and/or produce low yields. We use coarse-grained simulations of the assembly kinetics of complexes to identify generic limitations on yields that arise because of the many simultaneous interactions allowed between the components and intermediates of a complex. Efficient assembly occurs when nucleation is fast and growth pathways are few, i.e. when there is an assembly “funnel”. For typical complexes, an assembly funnel occurs in a narrow window of conditions whose location is highly complex specific. However, by redesigning the components this window can be drastically broadened, so that complexes can form quickly across many conditions. The generality of this approach suggests assembly funnel design as a foundational strategy for robust biomolecular complex synthesis. PMID:25360818

Snoopy--a unifying Petri net framework to investigate biomolecular networks.

PubMed

Rohr, Christian; Marwan, Wolfgang; Heiner, Monika

2010-04-01

To investigate biomolecular networks, Snoopy provides a unifying Petri net framework comprising a family of related Petri net classes. Models can be hierarchically structured, allowing for the mastering of larger networks. To move easily between the qualitative, stochastic and continuous modelling paradigms, models can be converted into each other. We get models sharing structure, but specialized by their kinetic information. The analysis and iterative reverse engineering of biomolecular networks is supported by the simultaneous use of several Petri net classes, while the graphical user interface adapts dynamically to the active one. Built-in animation and simulation are complemented by exports to various analysis tools. Snoopy facilitates the addition of new Petri net classes thanks to its generic design. Our tool with Petri net samples is available free of charge for non-commercial use at http://www-dssz.informatik.tu-cottbus.de/snoopy.html; supported operating systems: Mac OS X, Windows and Linux (selected distributions).

Design and application of implicit solvent models in biomolecular simulations.

PubMed

Kleinjung, Jens; Fraternali, Franca

2014-04-01

We review implicit solvent models and their parametrisation by introducing the concepts and recent devlopments of the most popular models with a focus on parametrisation via force matching. An overview of recent applications of the solvation energy term in protein dynamics, modelling, design and prediction is given to illustrate the usability and versatility of implicit solvation in reproducing the physical behaviour of biomolecular systems. Limitations of implicit modes are discussed through the example of more challenging systems like nucleic acids and membranes. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Unique temporal and spatial biomolecular emission profile on individual zinc oxide nanorods

NASA Astrophysics Data System (ADS)

Singh, Manpreet; Song, Sheng; Hahm, Jong-In

2013-12-01

Zinc oxide nanorods (ZnO NRs) have emerged in recent years as extremely useful, optical signal-enhancing platforms in DNA and protein detection. Although the use of ZnO NRs in biodetection has been demonstrated so far in systems involving many ZnO NRs per detection element, their future applications will likely take place in a miniaturized setting while exploiting single ZnO NRs in a low-volume, high-throughput bioanalysis. In this paper, we investigate temporal and spatial characteristics of the biomolecular fluorescence on individual ZnO NR systems. Quantitative and qualitative examinations of the biomolecular intensity and photostability are carried out as a function of two important criteria, the time and position along the long axis (length) of NRs. Photostability profiles are also measured with respect to the position on NRs and compared to those characteristics of biomolecules on polymeric control platforms. Unlike the uniformly distributed signal observed on the control platforms, both the fluorescence intensity and photostability are position-dependent on individual ZnO NRs. We have identified a unique phenomenon of highly localized, fluorescence intensification on the nanorod ends (FINE) of well-characterized, individual ZnO nanostructures. When compared to the polymeric controls, the biomolecular fluorescence intensity and photostability are determined to be higher on individual ZnO NRs regardless of the position on NRs. We have also carried out finite-difference time-domain simulations the results of which are in good agreement with the observed FINE. The outcomes of our investigation will offer a much needed basis for signal interpretation for biodetection devices and platforms consisting of single ZnO NRs and, at the same time, contribute significantly to provide insight in understanding the biomolecular fluorescence observed from ZnO NR ensemble-based systems.Zinc oxide nanorods (ZnO NRs) have emerged in recent years as extremely useful, optical signal-enhancing platforms in DNA and protein detection. Although the use of ZnO NRs in biodetection has been demonstrated so far in systems involving many ZnO NRs per detection element, their future applications will likely take place in a miniaturized setting while exploiting single ZnO NRs in a low-volume, high-throughput bioanalysis. In this paper, we investigate temporal and spatial characteristics of the biomolecular fluorescence on individual ZnO NR systems. Quantitative and qualitative examinations of the biomolecular intensity and photostability are carried out as a function of two important criteria, the time and position along the long axis (length) of NRs. Photostability profiles are also measured with respect to the position on NRs and compared to those characteristics of biomolecules on polymeric control platforms. Unlike the uniformly distributed signal observed on the control platforms, both the fluorescence intensity and photostability are position-dependent on individual ZnO NRs. We have identified a unique phenomenon of highly localized, fluorescence intensification on the nanorod ends (FINE) of well-characterized, individual ZnO nanostructures. When compared to the polymeric controls, the biomolecular fluorescence intensity and photostability are determined to be higher on individual ZnO NRs regardless of the position on NRs. We have also carried out finite-difference time-domain simulations the results of which are in good agreement with the observed FINE. The outcomes of our investigation will offer a much needed basis for signal interpretation for biodetection devices and platforms consisting of single ZnO NRs and, at the same time, contribute significantly to provide insight in understanding the biomolecular fluorescence observed from ZnO NR ensemble-based systems. Electronic supplementary information (ESI) available: ZnO NR size distributions, a FINE image from fluorophores on ZnO NR without protein coupling, and FDTD simulation movies. See DOI: 10.1039/c3nr05031a

RPYFMM: Parallel adaptive fast multipole method for Rotne-Prager-Yamakawa tensor in biomolecular hydrodynamics simulations

NASA Astrophysics Data System (ADS)

Guan, W.; Cheng, X.; Huang, J.; Huber, G.; Li, W.; McCammon, J. A.; Zhang, B.

2018-06-01

RPYFMM is a software package for the efficient evaluation of the potential field governed by the Rotne-Prager-Yamakawa (RPY) tensor interactions in biomolecular hydrodynamics simulations. In our algorithm, the RPY tensor is decomposed as a linear combination of four Laplace interactions, each of which is evaluated using the adaptive fast multipole method (FMM) (Greengard and Rokhlin, 1997) where the exponential expansions are applied to diagonalize the multipole-to-local translation operators. RPYFMM offers a unified execution on both shared and distributed memory computers by leveraging the DASHMM library (DeBuhr et al., 2016, 2018). Preliminary numerical results show that the interactions for a molecular system of 15 million particles (beads) can be computed within one second on a Cray XC30 cluster using 12,288 cores, while achieving approximately 54% strong-scaling efficiency.

GROMOS polarizable charge-on-spring models for liquid urea: COS/U and COS/U2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Zhixiong; Bachmann, Stephan J.; Gunsteren, Wilfred F. van, E-mail: wfvgn@igc.phys.chem.ethz.ch

2015-03-07

Two one-site polarizable urea models, COS/U and COS/U2, based on the charge-on-spring model are proposed. The models are parametrized against thermodynamic properties of urea-water mixtures in combination with the polarizable COS/G2 and COS/D2 models for liquid water, respectively, and have the same functional form of the inter-atomic interaction function and are based on the same parameter calibration procedure and type of experimental data as used to develop the GROMOS biomolecular force field. Thermodynamic, dielectric, and dynamic properties of urea-water mixtures simulated using the polarizable models are closer to experimental data than using the non-polarizable models. The COS/U and COS/U2 modelsmore » may be used in biomolecular simulations of protein denaturation.« less

NASA Tech Briefs, February 2006

NASA Technical Reports Server (NTRS)

2006-01-01

Topics discussed include: Nearly Direct Measurement of Relative Permittivity; DCS-Neural-Network Program for Aircraft Control and Testing; Dielectric Heaters for Testing Spacecraft Nuclear Reactors; Using Doppler Shifts of GPS Signals To Measure Angular Speed; Monitoring Temperatures of Tires Using Luminescent Materials; Highly Efficient Multilayer Thermoelectric Devices; Very High-Speed Digital Video Capability for In-Flight Use; MMIC DHBT Common-Base Amplifier for 172 GHz; Modular, Microprocessor-Controlled Flash Lighting System; Generic Environment for Simulating Launch Operations; Modular Aero-Propulsion System Simulation; X-Windows Socket Widget Class; Infrastructure for Rapid Development of Java GUI Programs; Processing Raman Spectra of High-Pressure Hydrogen Flames; X-Windows Information Sharing Protocol Widget Class; Simulating Humans as Integral Parts of Spacecraft Missions; Analyzing Power Supply and Demand on the ISS; Polyimides From a-BPDA and Aromatic Diamines; Making Plant-Support Structures From Waste Plant Fiber; Large Deployable Reflectarray Antenna; Periodically Discharging, Gas-Coalescing Filter; Ion Milling On Steps for Fabrication of Nanowires; Neuro-Prosthetic Implants With Adjustable Electrode Arrays; Microfluidic Devices for Studying Biomolecular Interactions; Studying Functions of All Yeast Genes Simultaneously; Polarization Phase-Compensating Coats for Metallic Mirrors; Tunable-Bandwidth Filter System; Methodology for Designing Fault-Protection Software; and Ground-Based Localization of Mars Rovers.

Glycan Reader: Automated Sugar Identification and Simulation Preparation for Carbohydrates and Glycoproteins

PubMed Central

Jo, Sunhwan; Song, Kevin C.; Desaire, Heather; MacKerell, Alexander D.; Im, Wonpil

2011-01-01

Understanding how glycosylation affects protein structure, dynamics, and function is an emerging and challenging problem in biology. As a first step toward glycan modeling in the context of structural glycobiology, we have developed Glycan Reader and integrated it into the CHARMM-GUI, http://www.charmm-gui.org/input/glycan. Glycan Reader greatly simplifies the reading of PDB structure files containing glycans through (i) detection of carbohydrate molecules, (ii) automatic annotation of carbohydrates based on their three-dimensional structures, (iii) recognition of glycosidic linkages between carbohydrates as well as N-/O-glycosidic linkages to proteins, and (iv) generation of inputs for the biomolecular simulation program CHARMM with the proper glycosidic linkage setup. In addition, Glycan Reader is linked to other functional modules in CHARMM-GUI, allowing users to easily generate carbohydrate or glycoprotein molecular simulation systems in solution or membrane environments and visualize the electrostatic potential on glycoprotein surfaces. These tools are useful for studying the impact of glycosylation on protein structure and dynamics. PMID:21815173

Data Intensive Analysis of Biomolecular Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Straatsma, TP; Soares, Thereza A.

2007-12-01

The advances in biomolecular modeling and simulation made possible by the availability of increasingly powerful high performance computing resources is extending molecular simulations to biological more relevant system size and time scales. At the same time, advances in simulation methodologies are allowing more complex processes to be described more accurately. These developments make a systems approach to computational structural biology feasible, but this will require a focused emphasis on the comparative analysis of the increasing number of molecular simulations that are being carried out for biomolecular systems with more realistic models, multi-component environments, and for longer simulation times. Just asmore » in the case of the analysis of the large data sources created by the new high-throughput experimental technologies, biomolecular computer simulations contribute to the progress in biology through comparative analysis. The continuing increase in available protein structures allows the comparative analysis of the role of structure and conformational flexibility in protein function, and is the foundation of the discipline of structural bioinformatics. This creates the opportunity to derive general findings from the comparative analysis of molecular dynamics simulations of a wide range of proteins, protein-protein complexes and other complex biological systems. Because of the importance of protein conformational dynamics for protein function, it is essential that the analysis of molecular trajectories is carried out using a novel, more integrative and systematic approach. We are developing a much needed rigorous computer science based framework for the efficient analysis of the increasingly large data sets resulting from molecular simulations. Such a suite of capabilities will also provide the required tools for access and analysis of a distributed library of generated trajectories. Our research is focusing on the following areas: (1) the development of an efficient analysis framework for very large scale trajectories on massively parallel architectures, (2) the development of novel methodologies that allow automated detection of events in these very large data sets, and (3) the efficient comparative analysis of multiple trajectories. The goal of the presented work is the development of new algorithms that will allow biomolecular simulation studies to become an integral tool to address the challenges of post-genomic biological research. The strategy to deliver the required data intensive computing applications that can effectively deal with the volume of simulation data that will become available is based on taking advantage of the capabilities offered by the use of large globally addressable memory architectures. The first requirement is the design of a flexible underlying data structure for single large trajectories that will form an adaptable framework for a wide range of analysis capabilities. The typical approach to trajectory analysis is to sequentially process trajectories time frame by time frame. This is the implementation found in molecular simulation codes such as NWChem, and has been designed in this way to be able to run on workstation computers and other architectures with an aggregate amount of memory that would not allow entire trajectories to be held in core. The consequence of this approach is an I/O dominated solution that scales very poorly on parallel machines. We are currently using an approach of developing tools specifically intended for use on large scale machines with sufficient main memory that entire trajectories can be held in core. This greatly reduces the cost of I/O as trajectories are read only once during the analysis. In our current Data Intensive Analysis (DIANA) implementation, each processor determines and skips to the entry within the trajectory that typically will be available in multiple files and independently from all other processors read the appropriate frames.« less

Data Intensive Analysis of Biomolecular Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Straatsma, TP

2008-03-01

The advances in biomolecular modeling and simulation made possible by the availability of increasingly powerful high performance computing resources is extending molecular simulations to biological more relevant system size and time scales. At the same time, advances in simulation methodologies are allowing more complex processes to be described more accurately. These developments make a systems approach to computational structural biology feasible, but this will require a focused emphasis on the comparative analysis of the increasing number of molecular simulations that are being carried out for biomolecular systems with more realistic models, multi-component environments, and for longer simulation times. Just asmore » in the case of the analysis of the large data sources created by the new high-throughput experimental technologies, biomolecular computer simulations contribute to the progress in biology through comparative analysis. The continuing increase in available protein structures allows the comparative analysis of the role of structure and conformational flexibility in protein function, and is the foundation of the discipline of structural bioinformatics. This creates the opportunity to derive general findings from the comparative analysis of molecular dynamics simulations of a wide range of proteins, protein-protein complexes and other complex biological systems. Because of the importance of protein conformational dynamics for protein function, it is essential that the analysis of molecular trajectories is carried out using a novel, more integrative and systematic approach. We are developing a much needed rigorous computer science based framework for the efficient analysis of the increasingly large data sets resulting from molecular simulations. Such a suite of capabilities will also provide the required tools for access and analysis of a distributed library of generated trajectories. Our research is focusing on the following areas: (1) the development of an efficient analysis framework for very large scale trajectories on massively parallel architectures, (2) the development of novel methodologies that allow automated detection of events in these very large data sets, and (3) the efficient comparative analysis of multiple trajectories. The goal of the presented work is the development of new algorithms that will allow biomolecular simulation studies to become an integral tool to address the challenges of post-genomic biological research. The strategy to deliver the required data intensive computing applications that can effectively deal with the volume of simulation data that will become available is based on taking advantage of the capabilities offered by the use of large globally addressable memory architectures. The first requirement is the design of a flexible underlying data structure for single large trajectories that will form an adaptable framework for a wide range of analysis capabilities. The typical approach to trajectory analysis is to sequentially process trajectories time frame by time frame. This is the implementation found in molecular simulation codes such as NWChem, and has been designed in this way to be able to run on workstation computers and other architectures with an aggregate amount of memory that would not allow entire trajectories to be held in core. The consequence of this approach is an I/O dominated solution that scales very poorly on parallel machines. We are currently using an approach of developing tools specifically intended for use on large scale machines with sufficient main memory that entire trajectories can be held in core. This greatly reduces the cost of I/O as trajectories are read only once during the analysis. In our current Data Intensive Analysis (DIANA) implementation, each processor determines and skips to the entry within the trajectory that typically will be available in multiple files and independently from all other processors read the appropriate frames.« less

Phage-based biomolecular filter for the capture of bacterial pathogens in liquid streams

NASA Astrophysics Data System (ADS)

Du, Songtao; Chen, I.-Hsuan; Horikawa, Shin; Lu, Xu; Liu, Yuzhe; Wikle, Howard C.; Suh, Sang Jin; Chin, Bryan A.

2017-05-01

This paper investigates a phage-based biomolecular filter that enables the evaluation of large volumes of liquids for the presence of small quantities of bacterial pathogens. The filter is a planar arrangement of phage-coated, strip-shaped magnetoelastic (ME) biosensors (4 mm × 0.8 mm × 0.03 mm), magnetically coupled to a filter frame structure, through which a liquid of interest flows. This "phage filter" is designed to capture specific bacterial pathogens and allow non-specific debris to pass, eliminating the common clogging issue in conventional bead filters. ANSYS Maxwell was used to simulate the magnetic field pattern required to hold ME biosensors densely and to optimize the frame design. Based on the simulation results, a phage filter structure was constructed, and a proof-in-concept experiment was conducted where a Salmonella solution of known concentration were passed through the filter, and the number of captured Salmonella was quantified by plate counting.

The free energy landscape of small peptides as obtained from metadynamics with umbrella sampling corrections

PubMed Central

Babin, Volodymyr; Roland, Christopher; Darden, Thomas A.; Sagui, Celeste

2007-01-01

There is considerable interest in developing methodologies for the accurate evaluation of free energies, especially in the context of biomolecular simulations. Here, we report on a reexamination of the recently developed metadynamics method, which is explicitly designed to probe “rare events” and areas of phase space that are typically difficult to access with a molecular dynamics simulation. Specifically, we show that the accuracy of the free energy landscape calculated with the metadynamics method may be considerably improved when combined with umbrella sampling techniques. As test cases, we have studied the folding free energy landscape of two prototypical peptides: Ace-(Gly)2-Pro-(Gly)3-Nme in vacuo and trialanine solvated by both implicit and explicit water. The method has been implemented in the classical biomolecular code AMBER and is to be distributed in the next scheduled release of the code. © 2006 American Institute of Physics. PMID:17144742

Reverse engineering biomolecular systems using -omic data: challenges, progress and opportunities.

PubMed

Quo, Chang F; Kaddi, Chanchala; Phan, John H; Zollanvari, Amin; Xu, Mingqing; Wang, May D; Alterovitz, Gil

2012-07-01

Recent advances in high-throughput biotechnologies have led to the rapid growing research interest in reverse engineering of biomolecular systems (REBMS). 'Data-driven' approaches, i.e. data mining, can be used to extract patterns from large volumes of biochemical data at molecular-level resolution while 'design-driven' approaches, i.e. systems modeling, can be used to simulate emergent system properties. Consequently, both data- and design-driven approaches applied to -omic data may lead to novel insights in reverse engineering biological systems that could not be expected before using low-throughput platforms. However, there exist several challenges in this fast growing field of reverse engineering biomolecular systems: (i) to integrate heterogeneous biochemical data for data mining, (ii) to combine top-down and bottom-up approaches for systems modeling and (iii) to validate system models experimentally. In addition to reviewing progress made by the community and opportunities encountered in addressing these challenges, we explore the emerging field of synthetic biology, which is an exciting approach to validate and analyze theoretical system models directly through experimental synthesis, i.e. analysis-by-synthesis. The ultimate goal is to address the present and future challenges in reverse engineering biomolecular systems (REBMS) using integrated workflow of data mining, systems modeling and synthetic biology.

PBEQ-Solver for online visualization of electrostatic potential of biomolecules.

PubMed

Jo, Sunhwan; Vargyas, Miklos; Vasko-Szedlar, Judit; Roux, Benoît; Im, Wonpil

2008-07-01

PBEQ-Solver provides a web-based graphical user interface to read biomolecular structures, solve the Poisson-Boltzmann (PB) equations and interactively visualize the electrostatic potential. PBEQ-Solver calculates (i) electrostatic potential and solvation free energy, (ii) protein-protein (DNA or RNA) electrostatic interaction energy and (iii) pKa of a selected titratable residue. All the calculations can be performed in both aqueous solvent and membrane environments (with a cylindrical pore in the case of membrane). PBEQ-Solver uses the PBEQ module in the biomolecular simulation program CHARMM to solve the finite-difference PB equation of molecules specified by users. Users can interactively inspect the calculated electrostatic potential on the solvent-accessible surface as well as iso-electrostatic potential contours using a novel online visualization tool based on MarvinSpace molecular visualization software, a Java applet integrated within CHARMM-GUI (http://www.charmm-gui.org). To reduce the computational time on the server, and to increase the efficiency in visualization, all the PB calculations are performed with coarse grid spacing (1.5 A before and 1 A after focusing). PBEQ-Solver suggests various physical parameters for PB calculations and users can modify them if necessary. PBEQ-Solver is available at http://www.charmm-gui.org/input/pbeqsolver.

Dynamics of biomolecular processes

NASA Astrophysics Data System (ADS)

Behringer, Hans; Eichhorn, Ralf; Wallin, Stefan

2013-05-01

The last few years have seen enormous progress in the availability of computational resources, so that the size and complexity of physical systems that can be investigated numerically has increased substantially. The physical mechanisms behind the processes creating life, such as those in a living cell, are of foremost interest in biophysical research. A main challenge here is that complexity not only emerges from interactions of many macro-molecular compounds, but is already evident at the level of a single molecule. An exciting recent development in this context is, therefore, that detailed atomistic level characterization of large-scale dynamics of individual bio-macromolecules, such as proteins and DNA, is starting to become feasible in some cases. This has contributed to a better understanding of the molecular mechanisms of, e.g. protein folding and aggregation, as well as DNA dynamics. Nevertheless, simulations of the dynamical behaviour of complex multicomponent cellular processes at an all-atom level will remain beyond reach for the foreseeable future, and may not even be desirable. Ultimate understanding of many biological processes will require the development of methods targeting different time and length scales and, importantly, ways to bridge these in multiscale approaches. At the scientific programme Dynamics of biomolecular processes: from atomistic representations to coarse-grained models held between 27 February and 23 March 2012, and hosted by the Nordic Institute for Theoretical Physics, new modelling approaches and results for particular biological systems were presented and discussed. The programme was attended by around 30 scientists from the Nordic countries and elsewhere. It also included a PhD and postdoc 'winter school', where basic theoretical concepts and techniques of biomolecular modelling and simulations were presented. One to two decades ago, the biomolecular modelling field was dominated by two widely different and largely independent approaches. On the one hand, computationally convenient and highly simplified lattice models were being used to elucidate the fundamental aspects of biomolecular conformational transitions, such as protein folding. On the other hand, these generic coarse-grained approaches were complemented by atomistic representations of the biomolecules. Physico-chemical all-atom models, often with an explicit representation of the surrounding solvent, were applied to specific protein structures to investigate their detailed dynamical behaviour. Today the situation is strikingly different, as was evident during the programme, where several new efforts were presented that try to combine the atomistic and the generic modelling approaches. The aim is to develop coarse-grained models at an intermediate-level resolution that are detailed enough to study specific biomolecular systems, and yet remain computationally efficient. These attempts are accompanied by the emergence of systematic coarse-graining techniques which bridge the physics of different lengths and timescales in a single simulation dynamically by applying appropriate representations of the associated degrees of freedom. Such adaptive resolution schemes represent promising candidates to tackle systems with an intrinsic multiscale nature, such as hierarchical chains and networks of biochemical reactions on a cellular level, calling for a very detailed description on an atomistic particle (or even quantum) level but simultaneously allowing the investigation of large-scale structuring and transport phenomena. The presentations and discussions during the programme also showed that the numerical evidence from (multiscale) simulations needs to be complemented by analytical and theoretical investigations to provide, eventually, a combined and deepened insight into the properties of biomolecular processes. The contributions from this scientific programme published in this issue of Physica Scripta highlight some of these new developments while also addressing related issues, such as the challenge of achieving efficient conformational sampling for chain molecules, and the interaction of nano-particles with biomolecules. The latter topic is especially timely as nano-particles are currently being considered for use as drug delivery devices, and present concerns about the general safety of their use might be resolved (or substantiated) by studies of this kind. This scientific programme and the contributions presented here were made possible by the financial and administrative support of the Nordic Institute for Theoretical Physics.

Event Detection and Sub-state Discovery from Bio-molecular Simulations Using Higher-Order Statistics: Application To Enzyme Adenylate Kinase

PubMed Central

Ramanathan, Arvind; Savol, Andrej J.; Agarwal, Pratul K.; Chennubhotla, Chakra S.

2012-01-01

Biomolecular simulations at milli-second and longer timescales can provide vital insights into functional mechanisms. Since post-simulation analyses of such large trajectory data-sets can be a limiting factor in obtaining biological insights, there is an emerging need to identify key dynamical events and relating these events to the biological function online, that is, as simulations are progressing. Recently, we have introduced a novel computational technique, quasi-anharmonic analysis (QAA) (PLoS One 6(1): e15827), for partitioning the conformational landscape into a hierarchy of functionally relevant sub-states. The unique capabilities of QAA are enabled by exploiting anharmonicity in the form of fourth-order statistics for characterizing atomic fluctuations. In this paper, we extend QAA for analyzing long time-scale simulations online. In particular, we present HOST4MD - a higher-order statistical toolbox for molecular dynamics simulations, which (1) identifies key dynamical events as simulations are in progress, (2) explores potential sub-states and (3) identifies conformational transitions that enable the protein to access those sub-states. We demonstrate HOST4MD on micro-second time-scale simulations of the enzyme adenylate kinase in its apo state. HOST4MD identifies several conformational events in these simulations, revealing how the intrinsic coupling between the three sub-domains (LID, CORE and NMP) changes during the simulations. Further, it also identifies an inherent asymmetry in the opening/closing of the two binding sites. We anticipate HOST4MD will provide a powerful and extensible framework for detecting biophysically relevant conformational coordinates from long time-scale simulations. PMID:22733562

New Distributed Multipole Methods for Accurate Electrostatics for Large-Scale Biomolecular Simultations

NASA Astrophysics Data System (ADS)

Sagui, Celeste

2006-03-01

An accurate and numerically efficient treatment of electrostatics is essential for biomolecular simulations, as this stabilizes much of the delicate 3-d structure associated with biomolecules. Currently, force fields such as AMBER and CHARMM assign ``partial charges'' to every atom in a simulation in order to model the interatomic electrostatic forces, so that the calculation of the electrostatics rapidly becomes the computational bottleneck in large-scale simulations. There are two main issues associated with the current treatment of classical electrostatics: (i) how does one eliminate the artifacts associated with the point-charges (e.g., the underdetermined nature of the current RESP fitting procedure for large, flexible molecules) used in the force fields in a physically meaningful way? (ii) how does one efficiently simulate the very costly long-range electrostatic interactions? Recently, we have dealt with both of these challenges as follows. In order to improve the description of the molecular electrostatic potentials (MEPs), a new distributed multipole analysis based on localized functions -- Wannier, Boys, and Edminston-Ruedenberg -- was introduced, which allows for a first principles calculation of the partial charges and multipoles. Through a suitable generalization of the particle mesh Ewald (PME) and multigrid method, one can treat electrostatic multipoles all the way to hexadecapoles all without prohibitive extra costs. The importance of these methods for large-scale simulations will be discussed, and examplified by simulations from polarizable DNA models.

Global Langevin model of multidimensional biomolecular dynamics.

PubMed

Schaudinnus, Norbert; Lickert, Benjamin; Biswas, Mithun; Stock, Gerhard

2016-11-14

Molecular dynamics simulations of biomolecular processes are often discussed in terms of diffusive motion on a low-dimensional free energy landscape F(). To provide a theoretical basis for this interpretation, one may invoke the system-bath ansatz á la Zwanzig. That is, by assuming a time scale separation between the slow motion along the system coordinate x and the fast fluctuations of the bath, a memory-free Langevin equation can be derived that describes the system's motion on the free energy landscape F(), which is damped by a friction field and driven by a stochastic force that is related to the friction via the fluctuation-dissipation theorem. While the theoretical formulation of Zwanzig typically assumes a highly idealized form of the bath Hamiltonian and the system-bath coupling, one would like to extend the approach to realistic data-based biomolecular systems. Here a practical method is proposed to construct an analytically defined global model of structural dynamics. Given a molecular dynamics simulation and adequate collective coordinates, the approach employs an "empirical valence bond"-type model which is suitable to represent multidimensional free energy landscapes as well as an approximate description of the friction field. Adopting alanine dipeptide and a three-dimensional model of heptaalanine as simple examples, the resulting Langevin model is shown to reproduce the results of the underlying all-atom simulations. Because the Langevin equation can also be shown to satisfy the underlying assumptions of the theory (such as a delta-correlated Gaussian-distributed noise), the global model provides a correct, albeit empirical, realization of Zwanzig's formulation. As an application, the model can be used to investigate the dependence of the system on parameter changes and to predict the effect of site-selective mutations on the dynamics.

Global Langevin model of multidimensional biomolecular dynamics

NASA Astrophysics Data System (ADS)

Schaudinnus, Norbert; Lickert, Benjamin; Biswas, Mithun; Stock, Gerhard

2016-11-01

Molecular dynamics simulations of biomolecular processes are often discussed in terms of diffusive motion on a low-dimensional free energy landscape F ( 𝒙 ) . To provide a theoretical basis for this interpretation, one may invoke the system-bath ansatz á la Zwanzig. That is, by assuming a time scale separation between the slow motion along the system coordinate x and the fast fluctuations of the bath, a memory-free Langevin equation can be derived that describes the system's motion on the free energy landscape F ( 𝒙 ) , which is damped by a friction field and driven by a stochastic force that is related to the friction via the fluctuation-dissipation theorem. While the theoretical formulation of Zwanzig typically assumes a highly idealized form of the bath Hamiltonian and the system-bath coupling, one would like to extend the approach to realistic data-based biomolecular systems. Here a practical method is proposed to construct an analytically defined global model of structural dynamics. Given a molecular dynamics simulation and adequate collective coordinates, the approach employs an "empirical valence bond"-type model which is suitable to represent multidimensional free energy landscapes as well as an approximate description of the friction field. Adopting alanine dipeptide and a three-dimensional model of heptaalanine as simple examples, the resulting Langevin model is shown to reproduce the results of the underlying all-atom simulations. Because the Langevin equation can also be shown to satisfy the underlying assumptions of the theory (such as a delta-correlated Gaussian-distributed noise), the global model provides a correct, albeit empirical, realization of Zwanzig's formulation. As an application, the model can be used to investigate the dependence of the system on parameter changes and to predict the effect of site-selective mutations on the dynamics.

Energy Fluctuations Shape Free Energy of Nonspecific Biomolecular Interactions

NASA Astrophysics Data System (ADS)

Elkin, Michael; Andre, Ingemar; Lukatsky, David B.

2012-01-01

Understanding design principles of biomolecular recognition is a key question of molecular biology. Yet the enormous complexity and diversity of biological molecules hamper the efforts to gain a predictive ability for the free energy of protein-protein, protein-DNA, and protein-RNA binding. Here, using a variant of the Derrida model, we predict that for a large class of biomolecular interactions, it is possible to accurately estimate the relative free energy of binding based on the fluctuation properties of their energy spectra, even if a finite number of the energy levels is known. We show that the free energy of the system possessing a wider binding energy spectrum is almost surely lower compared with the system possessing a narrower energy spectrum. Our predictions imply that low-affinity binding scores, usually wasted in protein-protein and protein-DNA docking algorithms, can be efficiently utilized to compute the free energy. Using the results of Rosetta docking simulations of protein-protein interactions from Andre et al. (Proc. Natl. Acad. Sci. USA 105:16148, 2008), we demonstrate the power of our predictions.

Unconstrained Enhanced Sampling for Free Energy Calculations of Biomolecules: A Review

PubMed Central

Miao, Yinglong; McCammon, J. Andrew

2016-01-01

Free energy calculations are central to understanding the structure, dynamics and function of biomolecules. Yet insufficient sampling of biomolecular configurations is often regarded as one of the main sources of error. Many enhanced sampling techniques have been developed to address this issue. Notably, enhanced sampling methods based on biasing collective variables (CVs), including the widely used umbrella sampling, adaptive biasing force and metadynamics, have been discussed in a recent excellent review (Abrams and Bussi, Entropy, 2014). Here, we aim to review enhanced sampling methods that do not require predefined system-dependent CVs for biomolecular simulations and as such do not suffer from the hidden energy barrier problem as encountered in the CV-biasing methods. These methods include, but are not limited to, replica exchange/parallel tempering, self-guided molecular/Langevin dynamics, essential energy space random walk and accelerated molecular dynamics. While it is overwhelming to describe all details of each method, we provide a summary of the methods along with the applications and offer our perspectives. We conclude with challenges and prospects of the unconstrained enhanced sampling methods for accurate biomolecular free energy calculations. PMID:27453631

Unconstrained Enhanced Sampling for Free Energy Calculations of Biomolecules: A Review.

PubMed

Miao, Yinglong; McCammon, J Andrew

Free energy calculations are central to understanding the structure, dynamics and function of biomolecules. Yet insufficient sampling of biomolecular configurations is often regarded as one of the main sources of error. Many enhanced sampling techniques have been developed to address this issue. Notably, enhanced sampling methods based on biasing collective variables (CVs), including the widely used umbrella sampling, adaptive biasing force and metadynamics, have been discussed in a recent excellent review (Abrams and Bussi, Entropy, 2014). Here, we aim to review enhanced sampling methods that do not require predefined system-dependent CVs for biomolecular simulations and as such do not suffer from the hidden energy barrier problem as encountered in the CV-biasing methods. These methods include, but are not limited to, replica exchange/parallel tempering, self-guided molecular/Langevin dynamics, essential energy space random walk and accelerated molecular dynamics. While it is overwhelming to describe all details of each method, we provide a summary of the methods along with the applications and offer our perspectives. We conclude with challenges and prospects of the unconstrained enhanced sampling methods for accurate biomolecular free energy calculations.

Simulation Concept - How to Exploit Tools for Computing Hybrids

DTIC Science & Technology

2010-06-01

biomolecular reactions ................................................................ 42  Figure 30: Overview of MATLAB Implementation...Figure 50: Adenine graphed using MATLAB (left) and OpenGL (right) ........................ 70  Figure 51: An overhead view of a thymine and adenine base...93  Figure 68: Response frequency solution from MATLAB

QwikMD — Integrative Molecular Dynamics Toolkit for Novices and Experts

PubMed Central

Ribeiro, João V.; Bernardi, Rafael C.; Rudack, Till; Stone, John E.; Phillips, James C.; Freddolino, Peter L.; Schulten, Klaus

2016-01-01

The proper functioning of biomolecules in living cells requires them to assume particular structures and to undergo conformational changes. Both biomolecular structure and motion can be studied using a wide variety of techniques, but none offers the level of detail as do molecular dynamics (MD) simulations. Integrating two widely used modeling programs, namely NAMD and VMD, we have created a robust, user-friendly software, QwikMD, which enables novices and experts alike to address biomedically relevant questions, where often only molecular dynamics simulations can provide answers. Performing both simple and advanced MD simulations interactively, QwikMD automates as many steps as necessary for preparing, carrying out, and analyzing simulations while checking for common errors and enabling reproducibility. QwikMD meets also the needs of experts in the field, increasing the efficiency and quality of their work by carrying out tedious or repetitive tasks while enabling easy control of every step. Whether carrying out simulations within the live view mode on a small laptop or performing complex and large simulations on supercomputers or Cloud computers, QwikMD uses the same steps and user interface. QwikMD is freely available by download on group and personal computers. It is also available on the cloud at Amazon Web Services. PMID:27216779

QwikMD — Integrative Molecular Dynamics Toolkit for Novices and Experts

NASA Astrophysics Data System (ADS)

Ribeiro, João V.; Bernardi, Rafael C.; Rudack, Till; Stone, John E.; Phillips, James C.; Freddolino, Peter L.; Schulten, Klaus

2016-05-01

The proper functioning of biomolecules in living cells requires them to assume particular structures and to undergo conformational changes. Both biomolecular structure and motion can be studied using a wide variety of techniques, but none offers the level of detail as do molecular dynamics (MD) simulations. Integrating two widely used modeling programs, namely NAMD and VMD, we have created a robust, user-friendly software, QwikMD, which enables novices and experts alike to address biomedically relevant questions, where often only molecular dynamics simulations can provide answers. Performing both simple and advanced MD simulations interactively, QwikMD automates as many steps as necessary for preparing, carrying out, and analyzing simulations while checking for common errors and enabling reproducibility. QwikMD meets also the needs of experts in the field, increasing the efficiency and quality of their work by carrying out tedious or repetitive tasks while enabling easy control of every step. Whether carrying out simulations within the live view mode on a small laptop or performing complex and large simulations on supercomputers or Cloud computers, QwikMD uses the same steps and user interface. QwikMD is freely available by download on group and personal computers. It is also available on the cloud at Amazon Web Services.

An Approach to Help Departments Meet the New ABET Process Safety Requirements

ERIC Educational Resources Information Center

Vaughen, Bruce K.

2012-01-01

The proposed program criteria changes by the Accreditation Board for Engineering and Technology, Inc. (ABET), for chemical, biochemical, biomolecular, and similarly named programs includes a fundamental awareness expectation of the hazards involved in chemical processing for a graduating chemical engineer. As of July 2010, these four new words…

Peptoid Backbone Flexibilility Dictates Its Interaction with Water and Surfaces: A Molecular Dynamics Investigation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prakash, Arushi; Baer, Marcel D.; Mundy, Christopher J.

Peptoids are peptide-mimetic biopolymers that are easy-to-synthesize and adaptable for use in drugs, chemical scaffolds, and coatings. However, there is insufficient information about their structural preferences and interactions with the environment in various applications. We conducted a study to understand the fundamental differences between peptides and peptoids using molecular dynamics simulations with semi-empirical (PM6) and empirical (AMBER) potentials, in conjunction with metadynamics enhanced sampling. From studies of single molecules in water and on surfaces, we found that sarcosine (model peptoid) is much more flexible than alanine (model peptide) in different environments. However, the sarcosine and alanine interact similarly with amore » hydrophobic or a hydrophilic. Finally, this study highlights the conformational landscape of peptoids and the dominant interactions that drive peptoids towards these conformations. ACKNOWLEDGMENT: MD simulations and manuscript preparation were supported by the MS3 (Materials Synthesis and Simulation Across Scales) Initiative at Pacific Northwest National Laboratory (PNNL), a multi-program national laboratory operated by Battelle for the U.S. Department of Energy. CJM was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences Division of Chemical Sciences, Geosciences, and Biosciences. MDB was supported by the US Department of Energy, Office of Basic Energy Sciences, Biomolecular Materials Program at PNNL. Computing resources were generously allocated by University of Washington's IT department and PNNL's Institutional Computing program. The authors greatly acknowledge conversations with Dr. Kayla Sprenger, Josh Smith, and Dr. Yeneneh Yimer.« less

Stochastic computing with biomolecular automata

PubMed Central

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

AFMPB: An adaptive fast multipole Poisson-Boltzmann solver for calculating electrostatics in biomolecular systems

NASA Astrophysics Data System (ADS)

Lu, Benzhuo; Cheng, Xiaolin; Huang, Jingfang; McCammon, J. Andrew

2010-06-01

A Fortran program package is introduced for rapid evaluation of the electrostatic potentials and forces in biomolecular systems modeled by the linearized Poisson-Boltzmann equation. The numerical solver utilizes a well-conditioned boundary integral equation (BIE) formulation, a node-patch discretization scheme, a Krylov subspace iterative solver package with reverse communication protocols, and an adaptive new version of fast multipole method in which the exponential expansions are used to diagonalize the multipole-to-local translations. The program and its full description, as well as several closely related libraries and utility tools are available at http://lsec.cc.ac.cn/~lubz/afmpb.html and a mirror site at http://mccammon.ucsd.edu/. This paper is a brief summary of the program: the algorithms, the implementation and the usage. Program summaryProgram title: AFMPB: Adaptive fast multipole Poisson-Boltzmann solver Catalogue identifier: AEGB_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGB_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GPL 2.0 No. of lines in distributed program, including test data, etc.: 453 649 No. of bytes in distributed program, including test data, etc.: 8 764 754 Distribution format: tar.gz Programming language: Fortran Computer: Any Operating system: Any RAM: Depends on the size of the discretized biomolecular system Classification: 3 External routines: Pre- and post-processing tools are required for generating the boundary elements and for visualization. Users can use MSMS ( http://www.scripps.edu/~sanner/html/msms_home.html) for pre-processing, and VMD ( http://www.ks.uiuc.edu/Research/vmd/) for visualization. Sub-programs included: An iterative Krylov subspace solvers package from SPARSKIT by Yousef Saad ( http://www-users.cs.umn.edu/~saad/software/SPARSKIT/sparskit.html), and the fast multipole methods subroutines from FMMSuite ( http://www.fastmultipole.org/). Nature of problem: Numerical solution of the linearized Poisson-Boltzmann equation that describes electrostatic interactions of molecular systems in ionic solutions. Solution method: A novel node-patch scheme is used to discretize the well-conditioned boundary integral equation formulation of the linearized Poisson-Boltzmann equation. Various Krylov subspace solvers can be subsequently applied to solve the resulting linear system, with a bounded number of iterations independent of the number of discretized unknowns. The matrix-vector multiplication at each iteration is accelerated by the adaptive new versions of fast multipole methods. The AFMPB solver requires other stand-alone pre-processing tools for boundary mesh generation, post-processing tools for data analysis and visualization, and can be conveniently coupled with different time stepping methods for dynamics simulation. Restrictions: Only three or six significant digits options are provided in this version. Unusual features: Most of the codes are in Fortran77 style. Memory allocation functions from Fortran90 and above are used in a few subroutines. Additional comments: The current version of the codes is designed and written for single core/processor desktop machines. Check http://lsec.cc.ac.cn/~lubz/afmpb.html and http://mccammon.ucsd.edu/ for updates and changes. Running time: The running time varies with the number of discretized elements ( N) in the system and their distributions. In most cases, it scales linearly as a function of N.

Achieving Rigorous Accelerated Conformational Sampling in Explicit Solvent.

PubMed

Doshi, Urmi; Hamelberg, Donald

2014-04-03

Molecular dynamics simulations can provide valuable atomistic insights into biomolecular function. However, the accuracy of molecular simulations on general-purpose computers depends on the time scale of the events of interest. Advanced simulation methods, such as accelerated molecular dynamics, have shown tremendous promise in sampling the conformational dynamics of biomolecules, where standard molecular dynamics simulations are nonergodic. Here we present a sampling method based on accelerated molecular dynamics in which rotatable dihedral angles and nonbonded interactions are boosted separately. This method (RaMD-db) is a different implementation of the dual-boost accelerated molecular dynamics, introduced earlier. The advantage is that this method speeds up sampling of the conformational space of biomolecules in explicit solvent, as the degrees of freedom most relevant for conformational transitions are accelerated. We tested RaMD-db on one of the most difficult sampling problems - protein folding. Starting from fully extended polypeptide chains, two fast folding α-helical proteins (Trpcage and the double mutant of C-terminal fragment of Villin headpiece) and a designed β-hairpin (Chignolin) were completely folded to their native structures in very short simulation time. Multiple folding/unfolding transitions could be observed in a single trajectory. Our results show that RaMD-db is a promisingly fast and efficient sampling method for conformational transitions in explicit solvent. RaMD-db thus opens new avenues for understanding biomolecular self-assembly and functional dynamics occurring on long time and length scales.

Long-range interactions and parallel scalability in molecular simulations

NASA Astrophysics Data System (ADS)

Patra, Michael; Hyvönen, Marja T.; Falck, Emma; Sabouri-Ghomi, Mohsen; Vattulainen, Ilpo; Karttunen, Mikko

2007-01-01

Typical biomolecular systems such as cellular membranes, DNA, and protein complexes are highly charged. Thus, efficient and accurate treatment of electrostatic interactions is of great importance in computational modeling of such systems. We have employed the GROMACS simulation package to perform extensive benchmarking of different commonly used electrostatic schemes on a range of computer architectures (Pentium-4, IBM Power 4, and Apple/IBM G5) for single processor and parallel performance up to 8 nodes—we have also tested the scalability on four different networks, namely Infiniband, GigaBit Ethernet, Fast Ethernet, and nearly uniform memory architecture, i.e. communication between CPUs is possible by directly reading from or writing to other CPUs' local memory. It turns out that the particle-mesh Ewald method (PME) performs surprisingly well and offers competitive performance unless parallel runs on PC hardware with older network infrastructure are needed. Lipid bilayers of sizes 128, 512 and 2048 lipid molecules were used as the test systems representing typical cases encountered in biomolecular simulations. Our results enable an accurate prediction of computational speed on most current computing systems, both for serial and parallel runs. These results should be helpful in, for example, choosing the most suitable configuration for a small departmental computer cluster.

ClustENM: ENM-Based Sampling of Essential Conformational Space at Full Atomic Resolution

PubMed Central

Kurkcuoglu, Zeynep; Bahar, Ivet; Doruker, Pemra

2016-01-01

Accurate sampling of conformational space and, in particular, the transitions between functional substates has been a challenge in molecular dynamic (MD) simulations of large biomolecular systems. We developed an Elastic Network Model (ENM)-based computational method, ClustENM, for sampling large conformational changes of biomolecules with various sizes and oligomerization states. ClustENM is an iterative method that combines ENM with energy minimization and clustering steps. It is an unbiased technique, which requires only an initial structure as input, and no information about the target conformation. To test the performance of ClustENM, we applied it to six biomolecular systems: adenylate kinase (AK), calmodulin, p38 MAP kinase, HIV-1 reverse transcriptase (RT), triosephosphate isomerase (TIM), and the 70S ribosomal complex. The generated ensembles of conformers determined at atomic resolution show good agreement with experimental data (979 structures resolved by X-ray and/or NMR) and encompass the subspaces covered in independent MD simulations for TIM, p38, and RT. ClustENM emerges as a computationally efficient tool for characterizing the conformational space of large systems at atomic detail, in addition to generating a representative ensemble of conformers that can be advantageously used in simulating substrate/ligand-binding events. PMID:27494296

Event detection and sub-state discovery from biomolecular simulations using higher-order statistics: application to enzyme adenylate kinase.

PubMed

Ramanathan, Arvind; Savol, Andrej J; Agarwal, Pratul K; Chennubhotla, Chakra S

2012-11-01

Biomolecular simulations at millisecond and longer time-scales can provide vital insights into functional mechanisms. Because post-simulation analyses of such large trajectory datasets can be a limiting factor in obtaining biological insights, there is an emerging need to identify key dynamical events and relating these events to the biological function online, that is, as simulations are progressing. Recently, we have introduced a novel computational technique, quasi-anharmonic analysis (QAA) (Ramanathan et al., PLoS One 2011;6:e15827), for partitioning the conformational landscape into a hierarchy of functionally relevant sub-states. The unique capabilities of QAA are enabled by exploiting anharmonicity in the form of fourth-order statistics for characterizing atomic fluctuations. In this article, we extend QAA for analyzing long time-scale simulations online. In particular, we present HOST4MD--a higher-order statistical toolbox for molecular dynamics simulations, which (1) identifies key dynamical events as simulations are in progress, (2) explores potential sub-states, and (3) identifies conformational transitions that enable the protein to access those sub-states. We demonstrate HOST4MD on microsecond timescale simulations of the enzyme adenylate kinase in its apo state. HOST4MD identifies several conformational events in these simulations, revealing how the intrinsic coupling between the three subdomains (LID, CORE, and NMP) changes during the simulations. Further, it also identifies an inherent asymmetry in the opening/closing of the two binding sites. We anticipate that HOST4MD will provide a powerful and extensible framework for detecting biophysically relevant conformational coordinates from long time-scale simulations. Copyright © 2012 Wiley Periodicals, Inc.

Molecular implementation of simple logic programs.

PubMed

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.

DNA-assisted swarm control in a biomolecular motor system.

PubMed

Keya, Jakia Jannat; Suzuki, Ryuhei; Kabir, Arif Md Rashedul; Inoue, Daisuke; Asanuma, Hiroyuki; Sada, Kazuki; Hess, Henry; Kuzuya, Akinori; Kakugo, Akira

2018-01-31

In nature, swarming behavior has evolved repeatedly among motile organisms because it confers a variety of beneficial emergent properties. These include improved information gathering, protection from predators, and resource utilization. Some organisms, e.g., locusts, switch between solitary and swarm behavior in response to external stimuli. Aspects of swarming behavior have been demonstrated for motile supramolecular systems composed of biomolecular motors and cytoskeletal filaments, where cross-linkers induce large scale organization. The capabilities of such supramolecular systems may be further extended if the swarming behavior can be programmed and controlled. Here, we demonstrate that the swarming of DNA-functionalized microtubules (MTs) propelled by surface-adhered kinesin motors can be programmed and reversibly regulated by DNA signals. Emergent swarm behavior, such as translational and circular motion, can be selected by tuning the MT stiffness. Photoresponsive DNA containing azobenzene groups enables switching between solitary and swarm behavior in response to stimulation with visible or ultraviolet light.

Enhanced sampling by multiple molecular dynamics trajectories: carbonmonoxy myoglobin 10 micros A0-->A(1-3) transition from ten 400 picosecond simulations.

PubMed

Loccisano, Anne E; Acevedo, Orlando; DeChancie, Jason; Schulze, Brita G; Evanseck, Jeffrey D

2004-05-01

The utility of multiple trajectories to extend the time scale of molecular dynamics simulations is reported for the spectroscopic A-states of carbonmonoxy myoglobin (MbCO). Experimentally, the A0-->A(1-3) transition has been observed to be 10 micros at 300 K, which is beyond the time scale of standard molecular dynamics simulations. To simulate this transition, 10 short (400 ps) and two longer time (1.2 ns) molecular dynamics trajectories, starting from five different crystallographic and solution phase structures with random initial velocities centered in a 37 A radius sphere of water, have been used to sample the native-fold of MbCO. Analysis of the ensemble of structures gathered over the cumulative 5.6 ns reveals two biomolecular motions involving the side chains of His64 and Arg45 to explain the spectroscopic states of MbCO. The 10 micros A0-->A(1-3) transition involves the motion of His64, where distance between His64 and CO is found to vary up to 8.8 +/- 1.0 A during the transition of His64 from the ligand (A(1-3)) to bulk solvent (A0). The His64 motion occurs within a single trajectory only once, however the multiple trajectories populate the spectroscopic A-states fully. Consequently, multiple independent molecular dynamics simulations have been found to extend biomolecular motion from 5 ns of total simulation to experimental phenomena on the microsecond time scale.

Understanding and Controlling Living/Inorganic Interfaces to Enable Reconfigurable Switchable Materials

DTIC Science & Technology

2018-03-01

of environmental conditions and surface treatment on binding affinity. 15. SUBJECT TERMS bacterial adhesion, genetically engineered proteins for...mannose binding both experimentally and in molecular dynamics simulation ............................................................ 6 Fig. 3 COMSOL...Research Laboratory (ARL) strengths (e.g., molecular biology/synthetic biology, biomolecular recognition, materials characterization and polymer science

Exploring the Role of Receptor Flexibility in Structure-Based Drug Discovery

PubMed Central

Feixas, Ferran; Lindert, Steffen; Sinko, William; McCammon, J. Andrew

2015-01-01

The proper understanding of biomolecular recognition mechanisms that take place in a drug target is of paramount importance to improve the efficiency of drug discovery and development. The intrinsic dynamic character of proteins has a strong influence on biomolecular recognition mechanisms and models such as conformational selection have been widely used to account for this dynamic association process. However, conformational changes occurring in the receptor prior and upon association with other molecules are diverse and not obvious to predict when only a few structures of the receptor are available. In view of the prominent role of protein flexibility in ligand binding and its implications for drug discovery, it is of great interest to identify receptor conformations that play a major role in biomolecular recognition before starting rational drug design efforts. In this review, we discuss a number of recent advances in computer-aided drug discovery techniques that have been proposed to incorporate receptor flexibility into structure-based drug design. The allowance for receptor flexibility provided by computational techniques such as molecular dynamics simulations or enhanced sampling techniques helps to improve the accuracy of methods used to estimate binding affinities and, thus, such methods can contribute to the discovery of novel drug leads. PMID:24332165

Learning about Biomolecular Solvation from Water in Protein Crystals.

PubMed

Altan, Irem; Fusco, Diana; Afonine, Pavel V; Charbonneau, Patrick

2018-03-08

Water occupies typically 50% of a protein crystal and thus significantly contributes to the diffraction signal in crystallography experiments. Separating its contribution from that of the protein is, however, challenging because most water molecules are not localized and are thus difficult to assign to specific density peaks. The intricateness of the protein-water interface compounds this difficulty. This information has, therefore, not often been used to study biomolecular solvation. Here, we develop a methodology to surmount in part this difficulty. More specifically, we compare the solvent structure obtained from diffraction data for which experimental phasing is available to that obtained from constrained molecular dynamics (MD) simulations. The resulting spatial density maps show that commonly used MD water models are only partially successful at reproducing the structural features of biomolecular solvation. The radial distribution of water is captured with only slightly higher accuracy than its angular distribution, and only a fraction of the water molecules assigned with high reliability to the crystal structure is recovered. These differences are likely due to shortcomings of both the water models and the protein force fields. Despite these limitations, we manage to infer protonation states of some of the side chains utilizing MD-derived densities.

7 CFR 91.5 - Where services are offered.

Code of Federal Regulations, 2010 CFR

2010-01-01

...) Science and Technology Programs National Science Laboratory. A variety of proximate, chemical, microbiological and biomolecular tests and laboratory analyses performed on fruits and vegetables, poultry, meat and meat products, fiber products and processed foods are performed at the Science and Technology...

Evaluation of Emerging Energy-Efficient Heterogeneous Computing Platforms for Biomolecular and Cellular Simulation Workloads.

PubMed

Stone, John E; Hallock, Michael J; Phillips, James C; Peterson, Joseph R; Luthey-Schulten, Zaida; Schulten, Klaus

2016-05-01

Many of the continuing scientific advances achieved through computational biology are predicated on the availability of ongoing increases in computational power required for detailed simulation and analysis of cellular processes on biologically-relevant timescales. A critical challenge facing the development of future exascale supercomputer systems is the development of new computing hardware and associated scientific applications that dramatically improve upon the energy efficiency of existing solutions, while providing increased simulation, analysis, and visualization performance. Mobile computing platforms have recently become powerful enough to support interactive molecular visualization tasks that were previously only possible on laptops and workstations, creating future opportunities for their convenient use for meetings, remote collaboration, and as head mounted displays for immersive stereoscopic viewing. We describe early experiences adapting several biomolecular simulation and analysis applications for emerging heterogeneous computing platforms that combine power-efficient system-on-chip multi-core CPUs with high-performance massively parallel GPUs. We present low-cost power monitoring instrumentation that provides sufficient temporal resolution to evaluate the power consumption of individual CPU algorithms and GPU kernels. We compare the performance and energy efficiency of scientific applications running on emerging platforms with results obtained on traditional platforms, identify hardware and algorithmic performance bottlenecks that affect the usability of these platforms, and describe avenues for improving both the hardware and applications in pursuit of the needs of molecular modeling tasks on mobile devices and future exascale computers.

Enhanced sampling techniques in molecular dynamics simulations of biological systems.

PubMed

Bernardi, Rafael C; Melo, Marcelo C R; Schulten, Klaus

2015-05-01

Molecular dynamics has emerged as an important research methodology covering systems to the level of millions of atoms. However, insufficient sampling often limits its application. The limitation is due to rough energy landscapes, with many local minima separated by high-energy barriers, which govern the biomolecular motion. In the past few decades methods have been developed that address the sampling problem, such as replica-exchange molecular dynamics, metadynamics and simulated annealing. Here we present an overview over theses sampling methods in an attempt to shed light on which should be selected depending on the type of system property studied. Enhanced sampling methods have been employed for a broad range of biological systems and the choice of a suitable method is connected to biological and physical characteristics of the system, in particular system size. While metadynamics and replica-exchange molecular dynamics are the most adopted sampling methods to study biomolecular dynamics, simulated annealing is well suited to characterize very flexible systems. The use of annealing methods for a long time was restricted to simulation of small proteins; however, a variant of the method, generalized simulated annealing, can be employed at a relatively low computational cost to large macromolecular complexes. Molecular dynamics trajectories frequently do not reach all relevant conformational substates, for example those connected with biological function, a problem that can be addressed by employing enhanced sampling algorithms. This article is part of a Special Issue entitled Recent developments of molecular dynamics. Copyright © 2014 Elsevier B.V. All rights reserved.

Bookshelf: a simple curation system for the storage of biomolecular simulation data.

PubMed

Vohra, Shabana; Hall, Benjamin A; Holdbrook, Daniel A; Khalid, Syma; Biggin, Philip C

2010-01-01

Molecular dynamics simulations can now routinely generate data sets of several hundreds of gigabytes in size. The ability to generate this data has become easier over recent years and the rate of data production is likely to increase rapidly in the near future. One major problem associated with this vast amount of data is how to store it in a way that it can be easily retrieved at a later date. The obvious answer to this problem is a database. However, a key issue in the development and maintenance of such a database is its sustainability, which in turn depends on the ease of the deposition and retrieval process. Encouraging users to care about meta-data is difficult and thus the success of any storage system will ultimately depend on how well used by end-users the system is. In this respect we suggest that even a minimal amount of metadata if stored in a sensible fashion is useful, if only at the level of individual research groups. We discuss here, a simple database system which we call 'Bookshelf', that uses python in conjunction with a mysql database to provide an extremely simple system for curating and keeping track of molecular simulation data. It provides a user-friendly, scriptable solution to the common problem amongst biomolecular simulation laboratories; the storage, logging and subsequent retrieval of large numbers of simulations. Download URL: http://sbcb.bioch.ox.ac.uk/bookshelf/

Bookshelf: a simple curation system for the storage of biomolecular simulation data

PubMed Central

Vohra, Shabana; Hall, Benjamin A.; Holdbrook, Daniel A.; Khalid, Syma; Biggin, Philip C.

2010-01-01

Molecular dynamics simulations can now routinely generate data sets of several hundreds of gigabytes in size. The ability to generate this data has become easier over recent years and the rate of data production is likely to increase rapidly in the near future. One major problem associated with this vast amount of data is how to store it in a way that it can be easily retrieved at a later date. The obvious answer to this problem is a database. However, a key issue in the development and maintenance of such a database is its sustainability, which in turn depends on the ease of the deposition and retrieval process. Encouraging users to care about meta-data is difficult and thus the success of any storage system will ultimately depend on how well used by end-users the system is. In this respect we suggest that even a minimal amount of metadata if stored in a sensible fashion is useful, if only at the level of individual research groups. We discuss here, a simple database system which we call ‘Bookshelf’, that uses python in conjunction with a mysql database to provide an extremely simple system for curating and keeping track of molecular simulation data. It provides a user-friendly, scriptable solution to the common problem amongst biomolecular simulation laboratories; the storage, logging and subsequent retrieval of large numbers of simulations. Download URL: http://sbcb.bioch.ox.ac.uk/bookshelf/ PMID:21169341

Applications of MMPBSA to Membrane Proteins I: Efficient Numerical Solutions of Periodic Poisson-Boltzmann Equation

PubMed Central

Botello-Smith, Wesley M.; Luo, Ray

2016-01-01

Continuum solvent models have been widely used in biomolecular modeling applications. Recently much attention has been given to inclusion of implicit membrane into existing continuum Poisson-Boltzmann solvent models to extend their applications to membrane systems. Inclusion of an implicit membrane complicates numerical solutions of the underlining Poisson-Boltzmann equation due to the dielectric inhomogeneity on the boundary surfaces of a computation grid. This can be alleviated by the use of the periodic boundary condition, a common practice in electrostatic computations in particle simulations. The conjugate gradient and successive over-relaxation methods are relatively straightforward to be adapted to periodic calculations, but their convergence rates are quite low, limiting their applications to free energy simulations that require a large number of conformations to be processed. To accelerate convergence, the Incomplete Cholesky preconditioning and the geometric multi-grid methods have been extended to incorporate periodicity for biomolecular applications. Impressive convergence behaviors were found as in the previous applications of these numerical methods to tested biomolecules and MMPBSA calculations. PMID:26389966

Enhanced conformational sampling using enveloping distribution sampling.

PubMed

Lin, Zhixiong; van Gunsteren, Wilfred F

2013-10-14

To lessen the problem of insufficient conformational sampling in biomolecular simulations is still a major challenge in computational biochemistry. In this article, an application of the method of enveloping distribution sampling (EDS) is proposed that addresses this challenge and its sampling efficiency is demonstrated in simulations of a hexa-β-peptide whose conformational equilibrium encompasses two different helical folds, i.e., a right-handed 2.7(10∕12)-helix and a left-handed 3(14)-helix, separated by a high energy barrier. Standard MD simulations of this peptide using the GROMOS 53A6 force field did not reach convergence of the free enthalpy difference between the two helices even after 500 ns of simulation time. The use of soft-core non-bonded interactions in the centre of the peptide did enhance the number of transitions between the helices, but at the same time led to neglect of relevant helical configurations. In the simulations of a two-state EDS reference Hamiltonian that envelops both the physical peptide and the soft-core peptide, sampling of the conformational space of the physical peptide ensures that physically relevant conformations can be visited, and sampling of the conformational space of the soft-core peptide helps to enhance the transitions between the two helices. The EDS simulations sampled many more transitions between the two helices and showed much faster convergence of the relative free enthalpy of the two helices compared with the standard MD simulations with only a slightly larger computational effort to determine optimized EDS parameters. Combined with various methods to smoothen the potential energy surface, the proposed EDS application will be a powerful technique to enhance the sampling efficiency in biomolecular simulations.

The Universal Statistical Distributions of the Affinity, Equilibrium Constants, Kinetics and Specificity in Biomolecular Recognition

PubMed Central

Zheng, Xiliang; Wang, Jin

2015-01-01

We uncovered the universal statistical laws for the biomolecular recognition/binding process. We quantified the statistical energy landscapes for binding, from which we can characterize the distributions of the binding free energy (affinity), the equilibrium constants, the kinetics and the specificity by exploring the different ligands binding with a particular receptor. The results of the analytical studies are confirmed by the microscopic flexible docking simulations. The distribution of binding affinity is Gaussian around the mean and becomes exponential near the tail. The equilibrium constants of the binding follow a log-normal distribution around the mean and a power law distribution in the tail. The intrinsic specificity for biomolecular recognition measures the degree of discrimination of native versus non-native binding and the optimization of which becomes the maximization of the ratio of the free energy gap between the native state and the average of non-native states versus the roughness measured by the variance of the free energy landscape around its mean. The intrinsic specificity obeys a Gaussian distribution near the mean and an exponential distribution near the tail. Furthermore, the kinetics of binding follows a log-normal distribution near the mean and a power law distribution at the tail. Our study provides new insights into the statistical nature of thermodynamics, kinetics and function from different ligands binding with a specific receptor or equivalently specific ligand binding with different receptors. The elucidation of distributions of the kinetics and free energy has guiding roles in studying biomolecular recognition and function through small-molecule evolution and chemical genetics. PMID:25885453

7 CFR 91.5 - Where services are offered.

Code of Federal Regulations, 2011 CFR

2011-01-01

...) Science and Technology Programs National Science Laboratory. A variety of proximate for composition, chemical, physical, microbiological and biomolecular (DNA-based) tests and laboratory analyses performed on..., honey, meat and meat products, fiber products and processed foods are performed at the Science and...

7 CFR 91.5 - Where services are offered.

Code of Federal Regulations, 2013 CFR

2013-01-01

...) Science and Technology Programs National Science Laboratory. A variety of proximate for composition, chemical, physical, microbiological and biomolecular (DNA-based) tests and laboratory analyses performed on..., honey, meat and meat products, fiber products and processed foods are performed at the Science and...

7 CFR 91.5 - Where services are offered.

Code of Federal Regulations, 2014 CFR

2014-01-01

...) Science and Technology Programs National Science Laboratory. A variety of proximate for composition, chemical, physical, microbiological and biomolecular (DNA-based) tests and laboratory analyses performed on..., honey, meat and meat products, fiber products and processed foods are performed at the Science and...

7 CFR 91.5 - Where services are offered.

Code of Federal Regulations, 2012 CFR

2012-01-01

...) Science and Technology Programs National Science Laboratory. A variety of proximate for composition, chemical, physical, microbiological and biomolecular (DNA-based) tests and laboratory analyses performed on..., honey, meat and meat products, fiber products and processed foods are performed at the Science and...

A cyber-linked undergraduate research experience in computational biomolecular structure prediction and design

PubMed Central

Alford, Rebecca F.; Dolan, Erin L.

2017-01-01

Computational biology is an interdisciplinary field, and many computational biology research projects involve distributed teams of scientists. To accomplish their work, these teams must overcome both disciplinary and geographic barriers. Introducing new training paradigms is one way to facilitate research progress in computational biology. Here, we describe a new undergraduate program in biomolecular structure prediction and design in which students conduct research at labs located at geographically-distributed institutions while remaining connected through an online community. This 10-week summer program begins with one week of training on computational biology methods development, transitions to eight weeks of research, and culminates in one week at the Rosetta annual conference. To date, two cohorts of students have participated, tackling research topics including vaccine design, enzyme design, protein-based materials, glycoprotein modeling, crowd-sourced science, RNA processing, hydrogen bond networks, and amyloid formation. Students in the program report outcomes comparable to students who participate in similar in-person programs. These outcomes include the development of a sense of community and increases in their scientific self-efficacy, scientific identity, and science values, all predictors of continuing in a science research career. Furthermore, the program attracted students from diverse backgrounds, which demonstrates the potential of this approach to broaden the participation of young scientists from backgrounds traditionally underrepresented in computational biology. PMID:29216185

A cyber-linked undergraduate research experience in computational biomolecular structure prediction and design.

PubMed

Alford, Rebecca F; Leaver-Fay, Andrew; Gonzales, Lynda; Dolan, Erin L; Gray, Jeffrey J

2017-12-01

Computational biology is an interdisciplinary field, and many computational biology research projects involve distributed teams of scientists. To accomplish their work, these teams must overcome both disciplinary and geographic barriers. Introducing new training paradigms is one way to facilitate research progress in computational biology. Here, we describe a new undergraduate program in biomolecular structure prediction and design in which students conduct research at labs located at geographically-distributed institutions while remaining connected through an online community. This 10-week summer program begins with one week of training on computational biology methods development, transitions to eight weeks of research, and culminates in one week at the Rosetta annual conference. To date, two cohorts of students have participated, tackling research topics including vaccine design, enzyme design, protein-based materials, glycoprotein modeling, crowd-sourced science, RNA processing, hydrogen bond networks, and amyloid formation. Students in the program report outcomes comparable to students who participate in similar in-person programs. These outcomes include the development of a sense of community and increases in their scientific self-efficacy, scientific identity, and science values, all predictors of continuing in a science research career. Furthermore, the program attracted students from diverse backgrounds, which demonstrates the potential of this approach to broaden the participation of young scientists from backgrounds traditionally underrepresented in computational biology.

A statistical nanomechanism of biomolecular patterning actuated by surface potential

NASA Astrophysics Data System (ADS)

Lin, Chih-Ting; Lin, Chih-Hao

2011-02-01

Biomolecular patterning on a nanoscale/microscale on chip surfaces is one of the most important techniques used in vitro biochip technologies. Here, we report upon a stochastic mechanics model we have developed for biomolecular patterning controlled by surface potential. The probabilistic biomolecular surface adsorption behavior can be modeled by considering the potential difference between the binding and nonbinding states. To verify our model, we experimentally implemented a method of electroactivated biomolecular patterning technology and the resulting fluorescence intensity matched the prediction of the developed model quite well. Based on this result, we also experimentally demonstrated the creation of a bovine serum albumin pattern with a width of 200 nm in 5 min operations. This submicron noncovalent-binding biomolecular pattern can be maintained for hours after removing the applied electrical voltage. These stochastic understandings and experimental results not only prove the feasibility of submicron biomolecular patterns on chips but also pave the way for nanoscale interfacial-bioelectrical engineering.

Unique spatiotemporal biomolecular emission profiles on single zinc oxide nanorods and applications in ultrasensitive biosensing

NASA Astrophysics Data System (ADS)

Singh, Manpreet

There has been longstanding interest in improving the optical detection capabilities of fluorescence spectroscopy to achieve ultrahigh resolution and sensitivity in chemical and biological sensing applications. To promote these efforts, I present my work characterizing and developing zinc oxide nanorods (ZnO NRs) as advanced optical detection platforms that can enable enhanced intensity and stability of adsorbed fluorophore-coupled biomolecules. First, I present my unique findings profiling the temporal and spatial characteristics of biomolecular fluorescence on individual ZnO NRs in which I've identified highly localized, non-linear optical phenomena of fluorescence intensification on nanorod ends (FINE) and enhanced photostability. Using combined experimental and computational strategies, I elucidate the fundamental physicochemical origins of these optical phenomena by systematically decoupling various biomolecular, chemical, and nanomaterial factors. On the biomolecular side, I evaluate the roles of fluorophores with varying spectroscopic properties and concentrations as well as facet-selective biomolecular adsorption on the unique spatiotemporal optical responses on single ZnO NRs. From the chemical/nanomaterial context, I profile the biomolecular emission behaviors on single ZnO NRs as a function of varying NR physical dimensions, NR orientations, and positions along the NR long axis I also present the results of employing finite-difference time domain (FDTD) simulations to corroborate my multifold experimental findings. The FDTD results further clarify the passive waveguiding capacity of the ZnO NRs to couple the radiation of surface-adsorpbed emitters and form evanescent waves that propagate to the NR ends before final emission into the far-field, confirming the experimental manifestation of FINE.. I also present an application exploiting the optical enhancement enabled by ZnO NRs in which I've engineered and validated a novel biosensing assay for the ultrasensitive detection and quantification of two Acute Kidney Injury biomarkers in real patient urine samples. Using micropatterned arrays of ZnO NRs, I've achieved unparalleled sensitivity with detection limits three orders of magnitude lower than conventional enzyme-linked immnosorbent assays allowing for earlier clinical diagnosis and intervention. The combined results of my efforts are hoped to promote the development of highly miniaturized biological/chemical sensing probes, platforms, and devices that utilize the remarkable enhancement of optical intensity and photostability provided by single ZnO NRs.

Multisystem altruistic metadynamics—Well-tempered variant

NASA Astrophysics Data System (ADS)

Hošek, Petr; Kříž, Pavel; Toulcová, Daniela; Spiwok, Vojtěch

2017-03-01

Metadynamics method has been widely used to enhance sampling in molecular simulations. Its original form suffers two major drawbacks, poor convergence in complex (especially biomolecular) systems and its serial nature. The first drawback has been addressed by introduction of a convergent variant known as well-tempered metadynamics. The second was addressed by introduction of a parallel multisystem metadynamics referred to as altruistic metadynamics. Here, we combine both approaches into well-tempered altruistic metadynamics. We provide mathematical arguments and trial simulations to show that it accurately predicts free energy surfaces.

Multisystem altruistic metadynamics-Well-tempered variant.

PubMed

Hošek, Petr; Kříž, Pavel; Toulcová, Daniela; Spiwok, Vojtěch

2017-03-28

Metadynamics method has been widely used to enhance sampling in molecular simulations. Its original form suffers two major drawbacks, poor convergence in complex (especially biomolecular) systems and its serial nature. The first drawback has been addressed by introduction of a convergent variant known as well-tempered metadynamics. The second was addressed by introduction of a parallel multisystem metadynamics referred to as altruistic metadynamics. Here, we combine both approaches into well-tempered altruistic metadynamics. We provide mathematical arguments and trial simulations to show that it accurately predicts free energy surfaces.

pyPcazip: A PCA-based toolkit for compression and analysis of molecular simulation data

NASA Astrophysics Data System (ADS)

Shkurti, Ardita; Goni, Ramon; Andrio, Pau; Breitmoser, Elena; Bethune, Iain; Orozco, Modesto; Laughton, Charles A.

The biomolecular simulation community is currently in need of novel and optimised software tools that can analyse and process, in reasonable timescales, the large generated amounts of molecular simulation data. In light of this, we have developed and present here pyPcazip: a suite of software tools for compression and analysis of molecular dynamics (MD) simulation data. The software is compatible with trajectory file formats generated by most contemporary MD engines such as AMBER, CHARMM, GROMACS and NAMD, and is MPI parallelised to permit the efficient processing of very large datasets. pyPcazip is a Unix based open-source software (BSD licenced) written in Python.

MPBEC, a Matlab Program for Biomolecular Electrostatic Calculations

NASA Astrophysics Data System (ADS)

Vergara-Perez, Sandra; Marucho, Marcelo

2016-01-01

One of the most used and efficient approaches to compute electrostatic properties of biological systems is to numerically solve the Poisson-Boltzmann (PB) equation. There are several software packages available that solve the PB equation for molecules in aqueous electrolyte solutions. Most of these software packages are useful for scientists with specialized training and expertise in computational biophysics. However, the user is usually required to manually take several important choices, depending on the complexity of the biological system, to successfully obtain the numerical solution of the PB equation. This may become an obstacle for researchers, experimentalists, even students with no special training in computational methodologies. Aiming to overcome this limitation, in this article we present MPBEC, a free, cross-platform, open-source software that provides non-experts in the field an easy and efficient way to perform biomolecular electrostatic calculations on single processor computers. MPBEC is a Matlab script based on the Adaptative Poisson-Boltzmann Solver, one of the most popular approaches used to solve the PB equation. MPBEC does not require any user programming, text editing or extensive statistical skills, and comes with detailed user-guide documentation. As a unique feature, MPBEC includes a useful graphical user interface (GUI) application which helps and guides users to configure and setup the optimal parameters and approximations to successfully perform the required biomolecular electrostatic calculations. The GUI also incorporates visualization tools to facilitate users pre- and post-analysis of structural and electrical properties of biomolecules.

MPBEC, a Matlab Program for Biomolecular Electrostatic Calculations

PubMed Central

Vergara-Perez, Sandra; Marucho, Marcelo

2015-01-01

One of the most used and efficient approaches to compute electrostatic properties of biological systems is to numerically solve the Poisson-Boltzmann (PB) equation. There are several software packages available that solve the PB equation for molecules in aqueous electrolyte solutions. Most of these software packages are useful for scientists with specialized training and expertise in computational biophysics. However, the user is usually required to manually take several important choices, depending on the complexity of the biological system, to successfully obtain the numerical solution of the PB equation. This may become an obstacle for researchers, experimentalists, even students with no special training in computational methodologies. Aiming to overcome this limitation, in this article we present MPBEC, a free, cross-platform, open-source software that provides non-experts in the field an easy and efficient way to perform biomolecular electrostatic calculations on single processor computers. MPBEC is a Matlab script based on the Adaptative Poisson Boltzmann Solver, one of the most popular approaches used to solve the PB equation. MPBEC does not require any user programming, text editing or extensive statistical skills, and comes with detailed user-guide documentation. As a unique feature, MPBEC includes a useful graphical user interface (GUI) application which helps and guides users to configure and setup the optimal parameters and approximations to successfully perform the required biomolecular electrostatic calculations. The GUI also incorporates visualization tools to facilitate users pre- and post- analysis of structural and electrical properties of biomolecules. PMID:26924848

MPBEC, a Matlab Program for Biomolecular Electrostatic Calculations.

PubMed

Vergara-Perez, Sandra; Marucho, Marcelo

2016-01-01

One of the most used and efficient approaches to compute electrostatic properties of biological systems is to numerically solve the Poisson-Boltzmann (PB) equation. There are several software packages available that solve the PB equation for molecules in aqueous electrolyte solutions. Most of these software packages are useful for scientists with specialized training and expertise in computational biophysics. However, the user is usually required to manually take several important choices, depending on the complexity of the biological system, to successfully obtain the numerical solution of the PB equation. This may become an obstacle for researchers, experimentalists, even students with no special training in computational methodologies. Aiming to overcome this limitation, in this article we present MPBEC, a free, cross-platform, open-source software that provides non-experts in the field an easy and efficient way to perform biomolecular electrostatic calculations on single processor computers. MPBEC is a Matlab script based on the Adaptative Poisson Boltzmann Solver, one of the most popular approaches used to solve the PB equation. MPBEC does not require any user programming, text editing or extensive statistical skills, and comes with detailed user-guide documentation. As a unique feature, MPBEC includes a useful graphical user interface (GUI) application which helps and guides users to configure and setup the optimal parameters and approximations to successfully perform the required biomolecular electrostatic calculations. The GUI also incorporates visualization tools to facilitate users pre- and post- analysis of structural and electrical properties of biomolecules.

Improved model of hydrated calcium ion for molecular dynamics simulations using classical biomolecular force fields.

PubMed

Yoo, Jejoong; Wilson, James; Aksimentiev, Aleksei

2016-10-01

Calcium ions (Ca(2+) ) play key roles in various fundamental biological processes such as cell signaling and brain function. Molecular dynamics (MD) simulations have been used to study such interactions, however, the accuracy of the Ca(2+) models provided by the standard MD force fields has not been rigorously tested. Here, we assess the performance of the Ca(2+) models from the most popular classical force fields AMBER and CHARMM by computing the osmotic pressure of model compounds and the free energy of DNA-DNA interactions. In the simulations performed using the two standard models, Ca(2+) ions are seen to form artificial clusters with chloride, acetate, and phosphate species; the osmotic pressure of CaAc2 and CaCl2 solutions is a small fraction of the experimental values for both force fields. Using the standard parameterization of Ca(2+) ions in the simulations of Ca(2+) -mediated DNA-DNA interactions leads to qualitatively wrong outcomes: both AMBER and CHARMM simulations suggest strong inter-DNA attraction whereas, in experiment, DNA molecules repel one another. The artificial attraction of Ca(2+) to DNA phosphate is strong enough to affect the direction of the electric field-driven translocation of DNA through a solid-state nanopore. To address these shortcomings of the standard Ca(2+) model, we introduce a custom model of a hydrated Ca(2+) ion and show that using our model brings the results of the above MD simulations in quantitative agreement with experiment. Our improved model of Ca(2+) can be readily applied to MD simulations of various biomolecular systems, including nucleic acids, proteins and lipid bilayer membranes. © 2016 Wiley Periodicals, Inc. Biopolymers 105: 752-763, 2016. © 2016 Wiley Periodicals, Inc.

THE ABRF MARG MICROARRAY SURVEY 2005: TAKING THE PULSE ON THE MICROARRAY FIELD

EPA Science Inventory

Over the past several years microarray technology has evolved into a critical component of any discovery based program. Since 1999, the Association of Biomolecular Resource Facilities (ABRF) Microarray Research Group (MARG) has conducted biennial surveys designed to generate a pr...

Performance of the Cell processor for biomolecular simulations

NASA Astrophysics Data System (ADS)

De Fabritiis, G.

2007-06-01

The new Cell processor represents a turning point for computing intensive applications. Here, I show that for molecular dynamics it is possible to reach an impressive sustained performance in excess of 30 Gflops with a peak of 45 Gflops for the non-bonded force calculations, over one order of magnitude faster than a single core standard processor.

PyContact: Rapid, Customizable, and Visual Analysis of Noncovalent Interactions in MD Simulations.

PubMed

Scheurer, Maximilian; Rodenkirch, Peter; Siggel, Marc; Bernardi, Rafael C; Schulten, Klaus; Tajkhorshid, Emad; Rudack, Till

2018-02-06

Molecular dynamics (MD) simulations have become ubiquitous in all areas of life sciences. The size and model complexity of MD simulations are rapidly growing along with increasing computing power and improved algorithms. This growth has led to the production of a large amount of simulation data that need to be filtered for relevant information to address specific biomedical and biochemical questions. One of the most relevant molecular properties that can be investigated by all-atom MD simulations is the time-dependent evolution of the complex noncovalent interaction networks governing such fundamental aspects as molecular recognition, binding strength, and mechanical and structural stability. Extracting, evaluating, and visualizing noncovalent interactions is a key task in the daily work of structural biologists. We have developed PyContact, an easy-to-use, highly flexible, and intuitive graphical user interface-based application, designed to provide a toolkit to investigate biomolecular interactions in MD trajectories. PyContact is designed to facilitate this task by enabling identification of relevant noncovalent interactions in a comprehensible manner. The implementation of PyContact as a standalone application enables rapid analysis and data visualization without any additional programming requirements, and also preserves full in-program customization and extension capabilities for advanced users. The statistical analysis representation is interactively combined with full mapping of the results on the molecular system through the synergistic connection between PyContact and VMD. We showcase the capabilities and scientific significance of PyContact by analyzing and visualizing in great detail the noncovalent interactions underlying the ion permeation pathway of the human P2X 3 receptor. As a second application, we examine the protein-protein interaction network of the mechanically ultrastable cohesin-dockering complex. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Theoretical restrictions on longest implicit time scales in Markov state models of biomolecular dynamics

NASA Astrophysics Data System (ADS)

Sinitskiy, Anton V.; Pande, Vijay S.

2018-01-01

Markov state models (MSMs) have been widely used to analyze computer simulations of various biomolecular systems. They can capture conformational transitions much slower than an average or maximal length of a single molecular dynamics (MD) trajectory from the set of trajectories used to build the MSM. A rule of thumb claiming that the slowest implicit time scale captured by an MSM should be comparable by the order of magnitude to the aggregate duration of all MD trajectories used to build this MSM has been known in the field. However, this rule has never been formally proved. In this work, we present analytical results for the slowest time scale in several types of MSMs, supporting the above rule. We conclude that the slowest implicit time scale equals the product of the aggregate sampling and four factors that quantify: (1) how much statistics on the conformational transitions corresponding to the longest implicit time scale is available, (2) how good the sampling of the destination Markov state is, (3) the gain in statistics from using a sliding window for counting transitions between Markov states, and (4) a bias in the estimate of the implicit time scale arising from finite sampling of the conformational transitions. We demonstrate that in many practically important cases all these four factors are on the order of unity, and we analyze possible scenarios that could lead to their significant deviation from unity. Overall, we provide for the first time analytical results on the slowest time scales captured by MSMs. These results can guide further practical applications of MSMs to biomolecular dynamics and allow for higher computational efficiency of simulations.

Model Reduction in Biomechanics

NASA Astrophysics Data System (ADS)

Feng, Yan

The mechanical characteristic of the cell is primarily performed by the cytoskeleton. Microtubules, actin, and intermediate filaments are the three main cytoskeletal polymers. Of these, microtubules are the stiffest and have multiple functions within a cell that include: providing tracks for intracellular transport, transmitting the mechanical force necessary for cell division during mitosis, and providing sufficient stiffness for propulsion in flagella and cilia. Microtubule mechanics has been studied by a variety of methods: detailed molecular dynamics (MD), coarse-grained models, engineering type models, and elastic continuum models. In principle, atomistic MD simulations should be able to predict all desired mechanical properties of a single molecule, however, in practice the large computational resources are required to carry out a simulation of larger biomolecular system. Due to the limited accessibility using even the most ambitious all-atom models and the demand for the multiscale molecular modeling and simulation, the emergence of the reduced models is critically important to provide the capability for investigating the biomolecular dynamics that are critical to many biological processes. Then the coarse-grained models, such as elastic network models and anisotropic network models, have been shown to bequite accurate in predicting microtubule mechanical response, but still requires significant computational resources. On the other hand, the microtubule is treated as comprising materials with certain continuum material properties. Such continuum models, especially Euler-Bernoulli beam models, are often used to extract mechanical parameters from experimental results. The microtubule is treated as comprising materials with certain continuum material properties. Such continuum models, especially Euler-Bernoulli beam models in which the biomolecular system is assumed as homogeneous isotropic materials with solid cross-sections, are often used to extract mechanical parameters from experimental results. However, in real biological world, these homogeneous and isotropic assumptions are usually invalidate. Thus, instead of using hypothesized model, a specific continuum model at mesoscopic scale can be introduced based upon data reduction of the results from molecular simulations at atomistic level. Once a continuum model is established, it can provide details on the distribution of stresses and strains induced within the biomolecular system which is useful in determining the distribution and transmission of these forces to the cytoskeletal and sub-cellular components, and help us gain a better understanding in cell mechanics. A data-driven model reduction approach to the problem of microtubule mechanics as an application is present, a beam element is constructed for microtubules based upon data reduction of the results from molecular simulation of the carbon backbone chain of alphabeta-tubulin dimers. The data base of mechanical responses to various types of loads from molecular simulation is reduced to dominant modes. The dominant modes are subsequently used to construct the stiffness matrix of a beam element that captures the anisotropic behavior and deformation mode coupling that arises from a microtubule's spiral structure. In contrast to standard Euler-Bernoulli or Timoshenko beam elements, the link between forces and node displacements results not from hypothesized deformation behavior, but directly from the data obtained by molecular scale simulation. Differences between the resulting microtubule data-driven beam model (MTDDBM) and standard beam elements are presented, with a focus on coupling of bending, stretch, shear deformations. The MTDDBM is just as economical to use as a standard beam element, and allows accurate reconstruction of the mechanical behavior of structures within a cell as exemplified in a simple model of a component element of the mitotic spindle.

Assessment of Linear Finite-Difference Poisson-Boltzmann Solvers

PubMed Central

Wang, Jun; Luo, Ray

2009-01-01

CPU time and memory usage are two vital issues that any numerical solvers for the Poisson-Boltzmann equation have to face in biomolecular applications. In this study we systematically analyzed the CPU time and memory usage of five commonly used finite-difference solvers with a large and diversified set of biomolecular structures. Our comparative analysis shows that modified incomplete Cholesky conjugate gradient and geometric multigrid are the most efficient in the diversified test set. For the two efficient solvers, our test shows that their CPU times increase approximately linearly with the numbers of grids. Their CPU times also increase almost linearly with the negative logarithm of the convergence criterion at very similar rate. Our comparison further shows that geometric multigrid performs better in the large set of tested biomolecules. However, modified incomplete Cholesky conjugate gradient is superior to geometric multigrid in molecular dynamics simulations of tested molecules. We also investigated other significant components in numerical solutions of the Poisson-Boltzmann equation. It turns out that the time-limiting step is the free boundary condition setup for the linear systems for the selected proteins if the electrostatic focusing is not used. Thus, development of future numerical solvers for the Poisson-Boltzmann equation should balance all aspects of the numerical procedures in realistic biomolecular applications. PMID:20063271

Evaluation of Emerging Energy-Efficient Heterogeneous Computing Platforms for Biomolecular and Cellular Simulation Workloads

PubMed Central

Stone, John E.; Hallock, Michael J.; Phillips, James C.; Peterson, Joseph R.; Luthey-Schulten, Zaida; Schulten, Klaus

2016-01-01

Many of the continuing scientific advances achieved through computational biology are predicated on the availability of ongoing increases in computational power required for detailed simulation and analysis of cellular processes on biologically-relevant timescales. A critical challenge facing the development of future exascale supercomputer systems is the development of new computing hardware and associated scientific applications that dramatically improve upon the energy efficiency of existing solutions, while providing increased simulation, analysis, and visualization performance. Mobile computing platforms have recently become powerful enough to support interactive molecular visualization tasks that were previously only possible on laptops and workstations, creating future opportunities for their convenient use for meetings, remote collaboration, and as head mounted displays for immersive stereoscopic viewing. We describe early experiences adapting several biomolecular simulation and analysis applications for emerging heterogeneous computing platforms that combine power-efficient system-on-chip multi-core CPUs with high-performance massively parallel GPUs. We present low-cost power monitoring instrumentation that provides sufficient temporal resolution to evaluate the power consumption of individual CPU algorithms and GPU kernels. We compare the performance and energy efficiency of scientific applications running on emerging platforms with results obtained on traditional platforms, identify hardware and algorithmic performance bottlenecks that affect the usability of these platforms, and describe avenues for improving both the hardware and applications in pursuit of the needs of molecular modeling tasks on mobile devices and future exascale computers. PMID:27516922

A class of exact solutions for biomacromolecule diffusion-reaction in live cells.

PubMed

Sadegh Zadeh, Kouroush; Montas, Hubert J

2010-06-07

A class of novel explicit analytic solutions for a system of n+1 coupled partial differential equations governing biomolecular mass transfer and reaction in living organisms are proposed, evaluated, and analyzed. The solution process uses Laplace and Hankel transforms and results in a recursive convolution of an exponentially scaled Gaussian with modified Bessel functions. The solution is developed for wide range of biomolecular binding kinetics from pure diffusion to multiple binding reactions. The proposed approach provides solutions for both Dirac and Gaussian laser beam (or fluorescence-labeled biomacromolecule) profiles during the course of a Fluorescence Recovery After Photobleaching (FRAP) experiment. We demonstrate that previous models are simplified forms of our theory for special cases. Model analysis indicates that at the early stages of the transport process, biomolecular dynamics is governed by pure diffusion. At large times, the dominant mass transfer process is effective diffusion. Analysis of the sensitivity equations, derived analytically and verified by finite difference differentiation, indicates that experimental biologists should use full space-time profile (instead of the averaged time series) obtained at the early stages of the fluorescence microscopy experiments to extract meaningful physiological information from the protocol. Such a small time frame requires improved bioinstrumentation relative to that in use today. Our mathematical analysis highlights several limitations of the FRAP protocol and provides strategies to improve it. The proposed model can be used to study biomolecular dynamics in molecular biology, targeted drug delivery in normal and cancerous tissues, motor-driven axonal transport in normal and abnormal nervous systems, kinetics of diffusion-controlled reactions between enzyme and substrate, and to validate numerical simulators of biological mass transport processes in vivo. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Multiscale geometric modeling of macromolecules I: Cartesian representation

NASA Astrophysics Data System (ADS)

Xia, Kelin; Feng, Xin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei

2014-01-01

This paper focuses on the geometric modeling and computational algorithm development of biomolecular structures from two data sources: Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in the Eulerian (or Cartesian) representation. Molecular surface (MS) contains non-smooth geometric singularities, such as cusps, tips and self-intersecting facets, which often lead to computational instabilities in molecular simulations, and violate the physical principle of surface free energy minimization. Variational multiscale surface definitions are proposed based on geometric flows and solvation analysis of biomolecular systems. Our approach leads to geometric and potential driven Laplace-Beltrami flows for biomolecular surface evolution and formation. The resulting surfaces are free of geometric singularities and minimize the total free energy of the biomolecular system. High order partial differential equation (PDE)-based nonlinear filters are employed for EMDB data processing. We show the efficacy of this approach in feature-preserving noise reduction. After the construction of protein multiresolution surfaces, we explore the analysis and characterization of surface morphology by using a variety of curvature definitions. Apart from the classical Gaussian curvature and mean curvature, maximum curvature, minimum curvature, shape index, and curvedness are also applied to macromolecular surface analysis for the first time. Our curvature analysis is uniquely coupled to the analysis of electrostatic surface potential, which is a by-product of our variational multiscale solvation models. As an expository investigation, we particularly emphasize the numerical algorithms and computational protocols for practical applications of the above multiscale geometric models. Such information may otherwise be scattered over the vast literature on this topic. Based on the curvature and electrostatic analysis from our multiresolution surfaces, we introduce a new concept, the polarized curvature, for the prediction of protein binding sites.

Quantitative biological surface science: challenges and recent advances.

PubMed

Höök, Fredrik; Kasemo, Bengt; Grunze, Michael; Zauscher, Stefan

2008-12-23

Biological surface science is a broad, interdisciplinary subfield of surface science, where properties and processes at biological and synthetic surfaces and interfaces are investigated, and where biofunctional surfaces are fabricated. The need to study and to understand biological surfaces and interfaces in liquid environments provides sizable challenges as well as fascinating opportunities. Here, we report on recent progress in biological surface science that was described within the program assembled by the Biomaterial Interface Division of the Science and Technology of Materials, Interfaces and Processes (www.avs.org) during their 55th International Symposium and Exhibition held in Boston, October 19-24, 2008. The selected examples show that the rapid progress in nanoscience and nanotechnology, hand-in-hand with theory and simulation, provides increasingly sophisticated methods and tools to unravel the mechanisms and details of complex processes at biological surfaces and in-depth understanding of biomolecular surface interactions.

Modeling Structural Dynamics of Biomolecular Complexes by Coarse-Grained Molecular Simulations.

PubMed

Takada, Shoji; Kanada, Ryo; Tan, Cheng; Terakawa, Tsuyoshi; Li, Wenfei; Kenzaki, Hiroo

2015-12-15

Due to hierarchic nature of biomolecular systems, their computational modeling calls for multiscale approaches, in which coarse-grained (CG) simulations are used to address long-time dynamics of large systems. Here, we review recent developments and applications of CG modeling methods, focusing on our methods primarily for proteins, DNA, and their complexes. These methods have been implemented in the CG biomolecular simulator, CafeMol. Our CG model has resolution such that ∼10 non-hydrogen atoms are grouped into one CG particle on average. For proteins, each amino acid is represented by one CG particle. For DNA, one nucleotide is simplified by three CG particles, representing sugar, phosphate, and base. The protein modeling is based on the idea that proteins have a globally funnel-like energy landscape, which is encoded in the structure-based potential energy function. We first describe two representative minimal models of proteins, called the elastic network model and the classic Go̅ model. We then present a more elaborate protein model, which extends the minimal model to incorporate sequence and context dependent local flexibility and nonlocal contacts. For DNA, we describe a model developed by de Pablo's group that was tuned to well reproduce sequence-dependent structural and thermodynamic experimental data for single- and double-stranded DNAs. Protein-DNA interactions are modeled either by the structure-based term for specific cases or by electrostatic and excluded volume terms for nonspecific cases. We also discuss the time scale mapping in CG molecular dynamics simulations. While the apparent single time step of our CGMD is about 10 times larger than that in the fully atomistic molecular dynamics for small-scale dynamics, large-scale motions can be further accelerated by two-orders of magnitude with the use of CG model and a low friction constant in Langevin dynamics. Next, we present four examples of applications. First, the classic Go̅ model was used to emulate one ATP cycle of a molecular motor, kinesin. Second, nonspecific protein-DNA binding was studied by a combination of elaborate protein and DNA models. Third, a transcription factor, p53, that contains highly fluctuating regions was simulated on two perpendicularly arranged DNA segments, addressing intersegmental transfer of p53. Fourth, we simulated structural dynamics of dinucleosomes connected by a linker DNA finding distinct types of internucleosome docking and salt-concentration-dependent compaction. Finally, we discuss many of limitations in the current approaches and future directions. Especially, more accurate electrostatic treatment and a phospholipid model that matches our CG resolutions are of immediate importance.

Water-soluble luminescent quantum dots and biomolecular conjugates thereof and related compositions and methods of use

DOEpatents

Nie, Shuming; Chan, Warren C. W.; Emory, Stephen

2007-03-20

The present invention provides a water-soluble luminescent quantum dot, a biomolecular conjugate thereof and a composition comprising such a quantum dot or conjugate. Additionally, the present invention provides a method of obtaining a luminescent quantum dot, a method of making a biomolecular conjugate thereof, and methods of using a biomolecular conjugate for ultrasensitive nonisotopic detection in vitro and in vivo.

Water-soluble luminescent quantum dots and biomolecular conjugates thereof and related compositions and method of use

DOEpatents

Nie, Shuming; Chan, Warren C. W.; Emory, Steven R.

2002-01-01

The present invention provides a water-soluble luminescent quantum dot, a biomolecular conjugate thereof and a composition comprising such a quantum dot or conjugate. Additionally, the present invention provides a method of obtaining a luminescent quantum dot, a method of making a biomolecular conjugate thereof, and methods of using a biomolecular conjugate for ultrasensitive nonisotopic detection in vitro and in vivo.

CAMERRA: An analysis tool for the computation of conformational dynamics by evaluating residue-residue associations.

PubMed

Johnson, Quentin R; Lindsay, Richard J; Shen, Tongye

2018-02-21

A computational method which extracts the dominant motions from an ensemble of biomolecular conformations via a correlation analysis of residue-residue contacts is presented. The algorithm first renders the structural information into contact matrices, then constructs the collective modes based on the correlated dynamics of a selected set of dynamic contacts. Associated programs can bridge the results for further visualization using graphics software. The aim of this method is to provide an analysis of conformations of biopolymers from the contact viewpoint. It may assist a systematical uncovering of conformational switching mechanisms existing in proteins and biopolymer systems in general by statistical analysis of simulation snapshots. In contrast to conventional correlation analyses of Cartesian coordinates (such as distance covariance analysis and Cartesian principal component analysis), this program also provides an alternative way to locate essential collective motions in general. Herein, we detail the algorithm in a stepwise manner and comment on the importance of the method as applied to decoding allosteric mechanisms. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Accounting for receptor flexibility and enhanced sampling methods in computer-aided drug design.

PubMed

Sinko, William; Lindert, Steffen; McCammon, J Andrew

2013-01-01

Protein flexibility plays a major role in biomolecular recognition. In many cases, it is not obvious how molecular structure will change upon association with other molecules. In proteins, these changes can be major, with large deviations in overall backbone structure, or they can be more subtle as in a side-chain rotation. Either way the algorithms that predict the favorability of biomolecular association require relatively accurate predictions of the bound structure to give an accurate assessment of the energy involved in association. Here, we review a number of techniques that have been proposed to accommodate receptor flexibility in the simulation of small molecules binding to protein receptors. We investigate modifications to standard rigid receptor docking algorithms and also explore enhanced sampling techniques, and the combination of free energy calculations and enhanced sampling techniques. The understanding and allowance for receptor flexibility are helping to make computer simulations of ligand protein binding more accurate. These developments may help improve the efficiency of drug discovery and development. Efficiency will be essential as we begin to see personalized medicine tailored to individual patients, which means specific drugs are needed for each patient's genetic makeup. © 2012 John Wiley & Sons A/S.

Knowledge environments representing molecular entities for the virtual physiological human.

PubMed

Hofmann-Apitius, Martin; Fluck, Juliane; Furlong, Laura; Fornes, Oriol; Kolárik, Corinna; Hanser, Susanne; Boeker, Martin; Schulz, Stefan; Sanz, Ferran; Klinger, Roman; Mevissen, Theo; Gattermayer, Tobias; Oliva, Baldo; Friedrich, Christoph M

2008-09-13

In essence, the virtual physiological human (VPH) is a multiscale representation of human physiology spanning from the molecular level via cellular processes and multicellular organization of tissues to complex organ function. The different scales of the VPH deal with different entities, relationships and processes, and in consequence the models used to describe and simulate biological functions vary significantly. Here, we describe methods and strategies to generate knowledge environments representing molecular entities that can be used for modelling the molecular scale of the VPH. Our strategy to generate knowledge environments representing molecular entities is based on the combination of information extraction from scientific text and the integration of information from biomolecular databases. We introduce @neuLink, a first prototype of an automatically generated, disease-specific knowledge environment combining biomolecular, chemical, genetic and medical information. Finally, we provide a perspective for the future implementation and use of knowledge environments representing molecular entities for the VPH.

Let's get honest about sampling.

PubMed

Mobley, David L

2012-01-01

Molecular simulations see widespread and increasing use in computation and molecular design, especially within the area of molecular simulations applied to biomolecular binding and interactions, our focus here. However, force field accuracy remains a concern for many practitioners, and it is often not clear what level of accuracy is really needed for payoffs in a discovery setting. Here, I argue that despite limitations of today's force fields, current simulation tools and force fields now provide the potential for real benefits in a variety of applications. However, these same tools also provide irreproducible results which are often poorly interpreted. Continued progress in the field requires more honesty in assessment and care in evaluation of simulation results, especially with respect to convergence.

Unscrambling micro-solvation of -COOH and -NH groups in neat dimethyl sulfoxide: insights from 1H-NMR spectroscopy and computational studies.

PubMed

Takis, Panteleimon G; Papavasileiou, Konstantinos D; Peristeras, Loukas D; Boulougouris, Georgios C; Melissas, Vasilios S; Troganis, Anastassios N

2017-05-31

Dimethyl sulfoxide (DMSO) has a significant, multi-faceted role in medicine, pharmacy, and biology as well as in biophysical chemistry and catalysis. Its physical properties and impact on biomolecular structures still attract major scientific interest, especially the interactions of DMSO with biomolecular functional groups. In the present study, we shed light on the "isolated" carboxylic (-COOH) and amide (-NH) interactions in neat DMSO via 1 H NMR studies along with extensive theoretical approaches, i.e. molecular dynamics (MD) simulations, density functional theory (DFT), and ab initio calculations, applied on model compounds (i.e. acetic and benzoic acid, ethyl acetamidocyanoacetate). Both experimental and theoretical results show excellent agreement, thereby permitting the calculation of the association constants between the studied compounds and DMSO molecules. Our coupled MD simulations, DFT and ab initio calculations, and NMR spectroscopy results indicated that complex formation is entropically driven and DMSO molecules undergo multiple strong interactions with the studied molecules, particularly with the -COOH groups. The combined experimental and theoretical techniques unraveled the interactions of DMSO with the most abundant functional groups of peptides (i.e. peptide bonds, side chain and terminal carboxyl groups) in high detail, providing significant insights on the underlying thermodynamics driving these interactions. Moreover, the developed methodology for the analysis of the simulation results could serve as a template for future thermodynamic and kinetic studies of similar systems.

Persistent Topology and Metastable State in Conformational Dynamics

PubMed Central

Chang, Huang-Wei; Bacallado, Sergio; Pande, Vijay S.; Carlsson, Gunnar E.

2013-01-01

The large amount of molecular dynamics simulation data produced by modern computational models brings big opportunities and challenges to researchers. Clustering algorithms play an important role in understanding biomolecular kinetics from the simulation data, especially under the Markov state model framework. However, the ruggedness of the free energy landscape in a biomolecular system makes common clustering algorithms very sensitive to perturbations of the data. Here, we introduce a data-exploratory tool which provides an overview of the clustering structure under different parameters. The proposed Multi-Persistent Clustering analysis combines insights from recent studies on the dynamics of systems with dominant metastable states with the concept of multi-dimensional persistence in computational topology. We propose to explore the clustering structure of the data based on its persistence on scale and density. The analysis provides a systematic way to discover clusters that are robust to perturbations of the data. The dominant states of the system can be chosen with confidence. For the clusters on the borderline, the user can choose to do more simulation or make a decision based on their structural characteristics. Furthermore, our multi-resolution analysis gives users information about the relative potential of the clusters and their hierarchical relationship. The effectiveness of the proposed method is illustrated in three biomolecules: alanine dipeptide, Villin headpiece, and the FiP35 WW domain. PMID:23565139

Biomolecular Corona Dictates Aβ Fibrillation Process.

PubMed

Lotfabadi, Alireza; Hajipour, Mohammad Javad; Derakhshankhah, Hossein; Peirovi, Afshin; Saffar, Samaneh; Shams, Elnaz; Fatemi, Elnaz; Barzegari, Ebrahim; Sarvari, Sajad; Moakedi, Faezeh; Ferdousi, Maryam; Atyabi, Fatemeh; Saboury, Ali Akbar; Dinarvand, Rassoul

2018-04-30

Amyloid beta (Aβ), which forms toxic oligomers and fibrils in brain tissues of patients with Alzheimer's disease, is broadly used as a model protein to probe the effect of nanoparticles (NPs) on oligomerization and fibrillation processes. However, the majority of the reports in the field have ignored the effect of the biomolecular corona on the fibrillogenesis of the Aβ proteins. The biomolecular corona, which is a layer composed of various types of biomolecules that covers the surface of NPs upon their interaction with biological fluids, determines the biological fates of NPs. Therefore, during in vivo interaction of NPs with Aβ protein, what the Aβ actually "sees" is the human plasma and/or cerebrospinal fluid (CSF) biomolecular-coated NPs rather than the pristine surface of NPs. Here, to mimic the in vivo effects of therapeutic NPs as antifibrillation agents, we probed the effects of a biomolecular corona derived from human CSF and/or plasma on Aβ fibrillation. The results demonstrated that the type of biomolecular corona can dictate the inhibitory or acceleratory effect of NPs on Aβ 1-42 and Aβ 25-35 fibrillation processes. More specifically, we found that the plasma biomolecular-corona-coated gold NPs, with sphere and rod shapes, has less inhibitory effect on Aβ 1-42 fibrillation kinetics compared with CSF biomolecular-corona-coated and pristine NPs. Opposite results were obtained for Aβ 25-35 peptide, where the pristine NPs accelerated the Aβ 25-35 fibrillation process, whereas corona-coated ones demonstrated an inhibitory effect. In addition, the CSF biomolecular corona had less inhibitory effect than those obtained from plasma.

Recent advances in self-assembled monolayers based biomolecular electronic devices.

PubMed

Arya, Sunil K; Solanki, Pratima R; Datta, Monika; Malhotra, Bansi D

2009-05-15

Self-assembled monolayers (SAMs) have aroused much interest due to their potential applications in biosensors, biomolecular electronics and nanotechnology. This has been largely attributed to their inherent ordered arrangement and controllable properties. SAMs can be formed by chemisorption of organic molecules containing groups like thiols, disulphides, amines, acids or silanes, on desired surfaces and can be used to fabricate biomolecular electronic devices. We focus on recent applications of organosulphur compounds (thiols) based SAMs to biomolecular electronic devices in the last about 3 years.

A Digitally Programmable Cytomorphic Chip for Simulation of Arbitrary Biochemical Reaction Networks.

PubMed

Woo, Sung Sik; Kim, Jaewook; Sarpeshkar, Rahul

2018-04-01

Prior work has shown that compact analog circuits can faithfully represent and model fundamental biomolecular circuits via efficient log-domain cytomorphic transistor equivalents. Such circuits have emphasized basis functions that are dominant in genetic transcription and translation networks and deoxyribonucleic acid (DNA)-protein binding. Here, we report a system featuring digitally programmable 0.35 μm BiCMOS analog cytomorphic chips that enable arbitrary biochemical reaction networks to be exactly represented thus enabling compact and easy composition of protein networks as well. Since all biomolecular networks can be represented as chemical reaction networks, our protein networks also include the former genetic network circuits as a special case. The cytomorphic analog protein circuits use one fundamental association-dissociation-degradation building-block circuit that can be configured digitally to exactly represent any zeroth-, first-, and second-order reaction including loading, dynamics, nonlinearity, and interactions with other building-block circuits. To address a divergence issue caused by random variations in chip fabrication processes, we propose a unique way of performing computation based on total variables and conservation laws, which we instantiate at both the circuit and network levels. Thus, scalable systems that operate with finite error over infinite time can be built. We show how the building-block circuits can be composed to form various network topologies, such as cascade, fan-out, fan-in, loop, dimerization, or arbitrary networks using total variables. We demonstrate results from a system that combines interacting cytomorphic chips to simulate a cancer pathway and a glycolysis pathway. Both simulations are consistent with conventional software simulations. Our highly parallel digitally programmable analog cytomorphic systems can lead to a useful design, analysis, and simulation tool for studying arbitrary large-scale biological networks in systems and synthetic biology.

Scanning number and brightness yields absolute protein concentrations in live cells: a crucial parameter controlling functional bio-molecular interaction networks.

PubMed

Papini, Christina; Royer, Catherine A

2018-02-01

Biological function results from properly timed bio-molecular interactions that transduce external or internal signals, resulting in any number of cellular fates, including triggering of cell-state transitions (division, differentiation, transformation, apoptosis), metabolic homeostasis and adjustment to changing physical or nutritional environments, amongst many more. These bio-molecular interactions can be modulated by chemical modifications of proteins, nucleic acids, lipids and other small molecules. They can result in bio-molecular transport from one cellular compartment to the other and often trigger specific enzyme activities involved in bio-molecular synthesis, modification or degradation. Clearly, a mechanistic understanding of any given high level biological function requires a quantitative characterization of the principal bio-molecular interactions involved and how these may change dynamically. Such information can be obtained using fluctation analysis, in particular scanning number and brightness, and used to build and test mechanistic models of the functional network to define which characteristics are the most important for its regulation.

ff14ipq: A Self-Consistent Force Field for Condensed-Phase Simulations of Proteins

PubMed Central

2015-01-01

We present the ff14ipq force field, implementing the previously published IPolQ charge set for simulations of complete proteins. Minor modifications to the charge derivation scheme and van der Waals interactions between polar atoms are introduced. Torsion parameters are developed through a generational learning approach, based on gas-phase MP2/cc-pVTZ single-point energies computed of structures optimized by the force field itself rather than the quantum benchmark. In this manner, we sacrifice information about the true quantum minima in order to ensure that the force field maintains optimal agreement with the MP2/cc-pVTZ benchmark for the ensembles it will actually produce in simulations. A means of making the gas-phase torsion parameters compatible with solution-phase IPolQ charges is presented. The ff14ipq model is an alternative to ff99SB and other Amber force fields for protein simulations in programs that accommodate pair-specific Lennard–Jones combining rules. The force field gives strong performance on α-helical and β-sheet oligopeptides as well as globular proteins over microsecond time scale simulations, although it has not yet been tested in conjunction with lipid and nucleic acid models. We show how our choices in parameter development influence the resulting force field and how other choices that may have appeared reasonable would actually have led to poorer results. The tools we developed may also aid in the development of future fixed-charge and even polarizable biomolecular force fields. PMID:25328495

Crowding in Cellular Environments at an Atomistic Level from Computer Simulations

PubMed Central

2017-01-01

The effects of crowding in biological environments on biomolecular structure, dynamics, and function remain not well understood. Computer simulations of atomistic models of concentrated peptide and protein systems at different levels of complexity are beginning to provide new insights. Crowding, weak interactions with other macromolecules and metabolites, and altered solvent properties within cellular environments appear to remodel the energy landscape of peptides and proteins in significant ways including the possibility of native state destabilization. Crowding is also seen to affect dynamic properties, both conformational dynamics and diffusional properties of macromolecules. Recent simulations that address these questions are reviewed here and discussed in the context of relevant experiments. PMID:28666087

Visualizing functional motions of membrane transporters with molecular dynamics simulations.

PubMed

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

PubMed Central

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bearinger, J P

This months issue has the following articles: (1) Science Translated for the Greater Good--Commentary by Steven D. Liedle; (2) The New Face of Industrial Partnerships--An entrepreneurial spirit is blossoming at Lawrence Livermore; (3) Monitoring a Nuclear Weapon from the Inside--Livermore researchers are developing tiny sensors to warn of detrimental chemical and physical changes inside nuclear warheads; (4) Simulating the Biomolecular Structure of Nanometer-Size Particles--Grand Challenge simulations reveal the size and structure of nanolipoprotein particles used to study membrane proteins; and (5) Antineutrino Detectors Improve Reactor Safeguards--Antineutrino detectors track the consumption and production of fissile materials inside nuclear reactors.

Equilibrium Sampling in Biomolecular Simulation

PubMed Central

2015-01-01

Equilibrium sampling of biomolecules remains an unmet challenge after more than 30 years of atomistic simulation. Efforts to enhance sampling capability, which are reviewed here, range from the development of new algorithms to parallelization to novel uses of hardware. Special focus is placed on classifying algorithms — most of which are underpinned by a few key ideas — in order to understand their fundamental strengths and limitations. Although algorithms have proliferated, progress resulting from novel hardware use appears to be more clear-cut than from algorithms alone, partly due to the lack of widely used sampling measures. PMID:21370970

Understanding radiation damage on sub-cellular scale using RADAMOL simulation tool

NASA Astrophysics Data System (ADS)

Štěpán, Václav; Davídková, Marie

2016-11-01

We present an overview of the biophysical model RADAMOL developed as a Monte Carlo simulation tool for physical, physico-chemical and chemical stages of ionizing radiation action. Direct and indirect radiation damage by 10 keV electrons, and protons and alpha particles with energies from 1 MeV up to 30 MeV to a free DNA oligomer or DNA in the complex with lac repressor protein is analyzed. The role of radiation type and energy, oxygen concentration and DNA interaction with proteins on yields and distributions of primary biomolecular damage is demonstrated and discussed.

Molecular dynamics simulations of heterogeneous cell membranes in response to uniaxial membrane stretches at high loading rates.

PubMed

Zhang, Lili; Zhang, Zesheng; Jasa, John; Li, Dongli; Cleveland, Robin O; Negahban, Mehrdad; Jérusalem, Antoine

2017-08-16

The chemobiomechanical signatures of diseased cells are often distinctively different from that of healthy cells. This mainly arises from cellular structural/compositional alterations induced by disease development or therapeutic molecules. Therapeutic shock waves have the potential to mechanically destroy diseased cells and/or increase cell membrane permeability for drug delivery. However, the biomolecular mechanisms by which shock waves interact with diseased and healthy cellular components remain largely unknown. By integrating atomistic simulations with a novel multiscale numerical framework, this work provides new biomolecular mechanistic perspectives through which many mechanosensitive cellular processes could be quantitatively characterised. Here we examine the biomechanical responses of the chosen representative membrane complexes under rapid mechanical loadings pertinent to therapeutic shock wave conditions. We find that their rupture characteristics do not exhibit significant sensitivity to the applied strain rates. Furthermore, we show that the embedded rigid inclusions markedly facilitate stretch-induced membrane disruptions while mechanically stiffening the associated complexes under the applied membrane stretches. Our results suggest that the presence of rigid molecules in cellular membranes could serve as "mechanical catalysts" to promote the mechanical destructions of the associated complexes, which, in concert with other biochemical/medical considerations, should provide beneficial information for future biomechanical-mediated therapeutics.

Communication: Multiple atomistic force fields in a single enhanced sampling simulation

NASA Astrophysics Data System (ADS)

Hoang Viet, Man; Derreumaux, Philippe; Nguyen, Phuong H.

2015-07-01

The main concerns of biomolecular dynamics simulations are the convergence of the conformational sampling and the dependence of the results on the force fields. While the first issue can be addressed by employing enhanced sampling techniques such as simulated tempering or replica exchange molecular dynamics, repeating these simulations with different force fields is very time consuming. Here, we propose an automatic method that includes different force fields into a single advanced sampling simulation. Conformational sampling using three all-atom force fields is enhanced by simulated tempering and by formulating the weight parameters of the simulated tempering method in terms of the energy fluctuations, the system is able to perform random walk in both temperature and force field spaces. The method is first demonstrated on a 1D system and then validated by the folding of the 10-residue chignolin peptide in explicit water.

Stochastic level-set variational implicit-solvent approach to solute-solvent interfacial fluctuations

PubMed Central

Zhou, Shenggao; Sun, Hui; Cheng, Li-Tien; Dzubiella, Joachim; McCammon, J. Andrew

2016-01-01

Recent years have seen the initial success of a variational implicit-solvent model (VISM), implemented with a robust level-set method, in capturing efficiently different hydration states and providing quantitatively good estimation of solvation free energies of biomolecules. The level-set minimization of the VISM solvation free-energy functional of all possible solute-solvent interfaces or dielectric boundaries predicts an equilibrium biomolecular conformation that is often close to an initial guess. In this work, we develop a theory in the form of Langevin geometrical flow to incorporate solute-solvent interfacial fluctuations into the VISM. Such fluctuations are crucial to biomolecular conformational changes and binding process. We also develop a stochastic level-set method to numerically implement such a theory. We describe the interfacial fluctuation through the “normal velocity” that is the solute-solvent interfacial force, derive the corresponding stochastic level-set equation in the sense of Stratonovich so that the surface representation is independent of the choice of implicit function, and develop numerical techniques for solving such an equation and processing the numerical data. We apply our computational method to study the dewetting transition in the system of two hydrophobic plates and a hydrophobic cavity of a synthetic host molecule cucurbit[7]uril. Numerical simulations demonstrate that our approach can describe an underlying system jumping out of a local minimum of the free-energy functional and can capture dewetting transitions of hydrophobic systems. In the case of two hydrophobic plates, we find that the wavelength of interfacial fluctuations has a strong influence to the dewetting transition. In addition, we find that the estimated energy barrier of the dewetting transition scales quadratically with the inter-plate distance, agreeing well with existing studies of molecular dynamics simulations. Our work is a first step toward the inclusion of fluctuations into the VISM and understanding the impact of interfacial fluctuations on biomolecular solvation with an implicit-solvent approach. PMID:27497546

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Shenggao, E-mail: sgzhou@suda.edu.cn, E-mail: bli@math.ucsd.edu; Sun, Hui; Cheng, Li-Tien

Recent years have seen the initial success of a variational implicit-solvent model (VISM), implemented with a robust level-set method, in capturing efficiently different hydration states and providing quantitatively good estimation of solvation free energies of biomolecules. The level-set minimization of the VISM solvation free-energy functional of all possible solute-solvent interfaces or dielectric boundaries predicts an equilibrium biomolecular conformation that is often close to an initial guess. In this work, we develop a theory in the form of Langevin geometrical flow to incorporate solute-solvent interfacial fluctuations into the VISM. Such fluctuations are crucial to biomolecular conformational changes and binding process. Wemore » also develop a stochastic level-set method to numerically implement such a theory. We describe the interfacial fluctuation through the “normal velocity” that is the solute-solvent interfacial force, derive the corresponding stochastic level-set equation in the sense of Stratonovich so that the surface representation is independent of the choice of implicit function, and develop numerical techniques for solving such an equation and processing the numerical data. We apply our computational method to study the dewetting transition in the system of two hydrophobic plates and a hydrophobic cavity of a synthetic host molecule cucurbit[7]uril. Numerical simulations demonstrate that our approach can describe an underlying system jumping out of a local minimum of the free-energy functional and can capture dewetting transitions of hydrophobic systems. In the case of two hydrophobic plates, we find that the wavelength of interfacial fluctuations has a strong influence to the dewetting transition. In addition, we find that the estimated energy barrier of the dewetting transition scales quadratically with the inter-plate distance, agreeing well with existing studies of molecular dynamics simulations. Our work is a first step toward the inclusion of fluctuations into the VISM and understanding the impact of interfacial fluctuations on biomolecular solvation with an implicit-solvent approach.« less

Towards an accurate representation of electrostatics in classical force fields: Efficient implementation of multipolar interactions in biomolecular simulations

NASA Astrophysics Data System (ADS)

Sagui, Celeste; Pedersen, Lee G.; Darden, Thomas A.

2004-01-01

The accurate simulation of biologically active macromolecules faces serious limitations that originate in the treatment of electrostatics in the empirical force fields. The current use of "partial charges" is a significant source of errors, since these vary widely with different conformations. By contrast, the molecular electrostatic potential (MEP) obtained through the use of a distributed multipole moment description, has been shown to converge to the quantum MEP outside the van der Waals surface, when higher order multipoles are used. However, in spite of the considerable improvement to the representation of the electronic cloud, higher order multipoles are not part of current classical biomolecular force fields due to the excessive computational cost. In this paper we present an efficient formalism for the treatment of higher order multipoles in Cartesian tensor formalism. The Ewald "direct sum" is evaluated through a McMurchie-Davidson formalism [L. McMurchie and E. Davidson, J. Comput. Phys. 26, 218 (1978)]. The "reciprocal sum" has been implemented in three different ways: using an Ewald scheme, a particle mesh Ewald (PME) method, and a multigrid-based approach. We find that even though the use of the McMurchie-Davidson formalism considerably reduces the cost of the calculation with respect to the standard matrix implementation of multipole interactions, the calculation in direct space remains expensive. When most of the calculation is moved to reciprocal space via the PME method, the cost of a calculation where all multipolar interactions (up to hexadecapole-hexadecapole) are included is only about 8.5 times more expensive than a regular AMBER 7 [D. A. Pearlman et al., Comput. Phys. Commun. 91, 1 (1995)] implementation with only charge-charge interactions. The multigrid implementation is slower but shows very promising results for parallelization. It provides a natural way to interface with continuous, Gaussian-based electrostatics in the future. It is hoped that this new formalism will facilitate the systematic implementation of higher order multipoles in classical biomolecular force fields.

Classical investigation of long-range coherence in biological systems

NASA Astrophysics Data System (ADS)

Preto, Jordane

2016-12-01

Almost five decades ago, H. Fröhlich [H. Fröhlich, "Long-range coherence and energy storage in biological systems," Int. J. Quantum Chem. 2(5), 641-649 (1968)] reported, on a theoretical basis, that the excitation of quantum modes of vibration in contact with a thermal reservoir may lead to steady states, where under high enough rate of energy supply, only specific low-frequency modes of vibration are strongly excited. This nonlinear phenomenon was predicted to occur in biomolecular systems, which are known to exhibit complex vibrational spectral properties, especially in the terahertz frequency domain. However, since the effects of terahertz or lower-frequency modes are mainly classical at physiological temperatures, there are serious doubts that Fröhlich's quantum description can be applied to predict such a coherent behavior in a biological environment, as suggested by the author. In addition, a quantum formalism makes the phenomenon hard to investigate using realistic molecular dynamics simulations (MD) as they are usually based on the classical principles. In the current paper, we provide a general classical Hamiltonian description of a nonlinear open system composed of many degrees of freedom (biomolecular structure) excited by an external energy source. It is shown that a coherent behaviour similar to Fröhlich's effect is to be expected in the classical case for a given range of parameter values. Thus, the supplied energy is not completely thermalized but stored in a highly ordered fashion. The connection between our Hamiltonian description, carried out in the space of normal modes, and a more standard treatment in the physical space is emphasized in order to facilitate the prediction of the effect from MD simulations. It is shown how such a coherent phenomenon may induce long-range resonance effects that could be of critical importance at the biomolecular level. The present work is motivated by recent experimental evidences of long-lived excited low-frequency modes in protein structures, which were reported as a consequence of the Fröhlich's effect.

Optical biosensors: a revolution towards quantum nanoscale electronics device fabrication.

PubMed

Dey, D; Goswami, T

2011-01-01

The dimension of biomolecules is of few nanometers, so the biomolecular devices ought to be of that range so a better understanding about the performance of the electronic biomolecular devices can be obtained at nanoscale. Development of optical biomolecular device is a new move towards revolution of nano-bioelectronics. Optical biosensor is one of such nano-biomolecular devices that has a potential to pave a new dimension of research and device fabrication in the field of optical and biomedical fields. This paper is a very small report about optical biosensor and its development and importance in various fields.

Design of a biochemical circuit motif for learning linear functions

PubMed Central

Lakin, Matthew R.; Minnich, Amanda; Lane, Terran; Stefanovic, Darko

2014-01-01

Learning and adaptive behaviour are fundamental biological processes. A key goal in the field of bioengineering is to develop biochemical circuit architectures with the ability to adapt to dynamic chemical environments. Here, we present a novel design for a biomolecular circuit capable of supervised learning of linear functions, using a model based on chemical reactions catalysed by DNAzymes. To achieve this, we propose a novel mechanism of maintaining and modifying internal state in biochemical systems, thereby advancing the state of the art in biomolecular circuit architecture. We use simulations to demonstrate that the circuit is capable of learning behaviour and assess its asymptotic learning performance, scalability and robustness to noise. Such circuits show great potential for building autonomous in vivo nanomedical devices. While such a biochemical system can tell us a great deal about the fundamentals of learning in living systems and may have broad applications in biomedicine (e.g. autonomous and adaptive drugs), it also offers some intriguing challenges and surprising behaviours from a machine learning perspective. PMID:25401175

Design of a biochemical circuit motif for learning linear functions.

PubMed

Lakin, Matthew R; Minnich, Amanda; Lane, Terran; Stefanovic, Darko

2014-12-06

Learning and adaptive behaviour are fundamental biological processes. A key goal in the field of bioengineering is to develop biochemical circuit architectures with the ability to adapt to dynamic chemical environments. Here, we present a novel design for a biomolecular circuit capable of supervised learning of linear functions, using a model based on chemical reactions catalysed by DNAzymes. To achieve this, we propose a novel mechanism of maintaining and modifying internal state in biochemical systems, thereby advancing the state of the art in biomolecular circuit architecture. We use simulations to demonstrate that the circuit is capable of learning behaviour and assess its asymptotic learning performance, scalability and robustness to noise. Such circuits show great potential for building autonomous in vivo nanomedical devices. While such a biochemical system can tell us a great deal about the fundamentals of learning in living systems and may have broad applications in biomedicine (e.g. autonomous and adaptive drugs), it also offers some intriguing challenges and surprising behaviours from a machine learning perspective.

Relativistic frequency upshift to the extreme ultraviolet regime using self-induced oscillatory flying mirrors

PubMed Central

Kim, I Jong; Pae, Ki Hong; Kim, Chul Min; Kim, Hyung Taek; Yun, Hyeok; Yun, Sang Jae; Sung, Jae Hee; Lee, Seong Ku; Yoon, Jin Woo; Yu, Tae Jun; Jeong, Tae Moon; Nam, Chang Hee; Lee, Jongmin

2012-01-01

Coherent short-wavelength radiation from laser–plasma interactions is of increasing interest in disciplines including ultrafast biomolecular imaging and attosecond physics. Using solid targets instead of atomic gases could enable the generation of coherent extreme ultraviolet radiation with higher energy and more energetic photons. Here we present the generation of extreme ultraviolet radiation through coherent high-harmonic generation from self-induced oscillatory flying mirrors—a new-generation mechanism established in a long underdense plasma on a solid target. Using a 30-fs, 100-TW Ti:sapphire laser, we obtain wavelengths as short as 4.9 nm for an optimized level of amplified spontaneous emission. Particle-in-cell simulations show that oscillatory flying electron nanosheets form in a long underdense plasma, and suggest that the high-harmonic generation is caused by reflection of the laser pulse from electron nanosheets. We expect this extreme ultraviolet radiation to be valuable in realizing a compact X-ray instrument for research in biomolecular imaging and attosecond physics. PMID:23187631

CHARMM-GUI PDB manipulator for advanced modeling and simulations of proteins containing nonstandard residues.

PubMed

Jo, Sunhwan; Cheng, Xi; Islam, Shahidul M; Huang, Lei; Rui, Huan; Zhu, Allen; Lee, Hui Sun; Qi, Yifei; Han, Wei; Vanommeslaeghe, Kenno; MacKerell, Alexander D; Roux, Benoît; Im, Wonpil

2014-01-01

CHARMM-GUI, http://www.charmm-gui.org, is a web-based graphical user interface to prepare molecular simulation systems and input files to facilitate the usage of common and advanced simulation techniques. Since it is originally developed in 2006, CHARMM-GUI has been widely adopted for various purposes and now contains a number of different modules designed to setup a broad range of simulations including free energy calculation and large-scale coarse-grained representation. Here, we describe functionalities that have recently been integrated into CHARMM-GUI PDB Manipulator, such as ligand force field generation, incorporation of methanethiosulfonate spin labels and chemical modifiers, and substitution of amino acids with unnatural amino acids. These new features are expected to be useful in advanced biomolecular modeling and simulation of proteins. © 2014 Elsevier Inc. All rights reserved.

The interplay of intrinsic and extrinsic bounded noises in biomolecular networks.

PubMed

Caravagna, Giulio; Mauri, Giancarlo; d'Onofrio, Alberto

2013-01-01

After being considered as a nuisance to be filtered out, it became recently clear that biochemical noise plays a complex role, often fully functional, for a biomolecular network. The influence of intrinsic and extrinsic noises on biomolecular networks has intensively been investigated in last ten years, though contributions on the co-presence of both are sparse. Extrinsic noise is usually modeled as an unbounded white or colored gaussian stochastic process, even though realistic stochastic perturbations are clearly bounded. In this paper we consider Gillespie-like stochastic models of nonlinear networks, i.e. the intrinsic noise, where the model jump rates are affected by colored bounded extrinsic noises synthesized by a suitable biochemical state-dependent Langevin system. These systems are described by a master equation, and a simulation algorithm to analyze them is derived. This new modeling paradigm should enlarge the class of systems amenable at modeling. We investigated the influence of both amplitude and autocorrelation time of a extrinsic Sine-Wiener noise on: (i) the Michaelis-Menten approximation of noisy enzymatic reactions, which we show to be applicable also in co-presence of both intrinsic and extrinsic noise, (ii) a model of enzymatic futile cycle and (iii) a genetic toggle switch. In (ii) and (iii) we show that the presence of a bounded extrinsic noise induces qualitative modifications in the probability densities of the involved chemicals, where new modes emerge, thus suggesting the possible functional role of bounded noises.

An Advanced Platform for Biomolecular Detection and Analysis Systems

DTIC Science & Technology

2005-02-01

AFRL-IF-RS-TR-2005-54 Final Technical Report February 2005 AN ADVANCED PLATFORM FOR BIOMOLECULAR DETECTION AND ANALYSIS SYSTEMS...SUBTITLE AN ADVANCED PLATFORM FOR BIOMOLECULAR DETECTION AND ANALYSIS SYSTEMS 6. AUTHOR(S) David J. Beebe 5. FUNDING NUMBERS G...detection, analysis and response as well as many non BC warfare applications such as environmental toxicology, clinical detection and diagnosis

Best bang for your buck: GPU nodes for GROMACS biomolecular simulations

PubMed Central

Páll, Szilárd; Fechner, Martin; Esztermann, Ansgar; de Groot, Bert L.; Grubmüller, Helmut

2015-01-01

The molecular dynamics simulation package GROMACS runs efficiently on a wide variety of hardware from commodity workstations to high performance computing clusters. Hardware features are well‐exploited with a combination of single instruction multiple data, multithreading, and message passing interface (MPI)‐based single program multiple data/multiple program multiple data parallelism while graphics processing units (GPUs) can be used as accelerators to compute interactions off‐loaded from the CPU. Here, we evaluate which hardware produces trajectories with GROMACS 4.6 or 5.0 in the most economical way. We have assembled and benchmarked compute nodes with various CPU/GPU combinations to identify optimal compositions in terms of raw trajectory production rate, performance‐to‐price ratio, energy efficiency, and several other criteria. Although hardware prices are naturally subject to trends and fluctuations, general tendencies are clearly visible. Adding any type of GPU significantly boosts a node's simulation performance. For inexpensive consumer‐class GPUs this improvement equally reflects in the performance‐to‐price ratio. Although memory issues in consumer‐class GPUs could pass unnoticed as these cards do not support error checking and correction memory, unreliable GPUs can be sorted out with memory checking tools. Apart from the obvious determinants for cost‐efficiency like hardware expenses and raw performance, the energy consumption of a node is a major cost factor. Over the typical hardware lifetime until replacement of a few years, the costs for electrical power and cooling can become larger than the costs of the hardware itself. Taking that into account, nodes with a well‐balanced ratio of CPU and consumer‐class GPU resources produce the maximum amount of GROMACS trajectory over their lifetime. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. PMID:26238484

Best bang for your buck: GPU nodes for GROMACS biomolecular simulations.

PubMed

Kutzner, Carsten; Páll, Szilárd; Fechner, Martin; Esztermann, Ansgar; de Groot, Bert L; Grubmüller, Helmut

2015-10-05

The molecular dynamics simulation package GROMACS runs efficiently on a wide variety of hardware from commodity workstations to high performance computing clusters. Hardware features are well-exploited with a combination of single instruction multiple data, multithreading, and message passing interface (MPI)-based single program multiple data/multiple program multiple data parallelism while graphics processing units (GPUs) can be used as accelerators to compute interactions off-loaded from the CPU. Here, we evaluate which hardware produces trajectories with GROMACS 4.6 or 5.0 in the most economical way. We have assembled and benchmarked compute nodes with various CPU/GPU combinations to identify optimal compositions in terms of raw trajectory production rate, performance-to-price ratio, energy efficiency, and several other criteria. Although hardware prices are naturally subject to trends and fluctuations, general tendencies are clearly visible. Adding any type of GPU significantly boosts a node's simulation performance. For inexpensive consumer-class GPUs this improvement equally reflects in the performance-to-price ratio. Although memory issues in consumer-class GPUs could pass unnoticed as these cards do not support error checking and correction memory, unreliable GPUs can be sorted out with memory checking tools. Apart from the obvious determinants for cost-efficiency like hardware expenses and raw performance, the energy consumption of a node is a major cost factor. Over the typical hardware lifetime until replacement of a few years, the costs for electrical power and cooling can become larger than the costs of the hardware itself. Taking that into account, nodes with a well-balanced ratio of CPU and consumer-class GPU resources produce the maximum amount of GROMACS trajectory over their lifetime. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

A synergic simulation-optimization approach for analyzing biomolecular dynamics in living organisms.

PubMed

Sadegh Zadeh, Kouroush

2011-01-01

A synergic duo simulation-optimization approach was developed and implemented to study protein-substrate dynamics and binding kinetics in living organisms. The forward problem is a system of several coupled nonlinear partial differential equations which, with a given set of kinetics and diffusion parameters, can provide not only the commonly used bleached area-averaged time series in fluorescence microscopy experiments but more informative full biomolecular/drug space-time series and can be successfully used to study dynamics of both Dirac and Gaussian fluorescence-labeled biomacromolecules in vivo. The incomplete Cholesky preconditioner was coupled with the finite difference discretization scheme and an adaptive time-stepping strategy to solve the forward problem. The proposed approach was validated with analytical as well as reference solutions and used to simulate dynamics of GFP-tagged glucocorticoid receptor (GFP-GR) in mouse cancer cell during a fluorescence recovery after photobleaching experiment. Model analysis indicates that the commonly practiced bleach spot-averaged time series is not an efficient approach to extract physiological information from the fluorescence microscopy protocols. It was recommended that experimental biophysicists should use full space-time series, resulting from experimental protocols, to study dynamics of biomacromolecules and drugs in living organisms. It was also concluded that in parameterization of biological mass transfer processes, setting the norm of the gradient of the penalty function at the solution to zero is not an efficient stopping rule to end the inverse algorithm. Theoreticians should use multi-criteria stopping rules to quantify model parameters by optimization. Copyright © 2010 Elsevier Ltd. All rights reserved.

Characterizing rare-event property distributions via replicate molecular dynamics simulations of proteins.

PubMed

Krishnan, Ranjani; Walton, Emily B; Van Vliet, Krystyn J

2009-11-01

As computational resources increase, molecular dynamics simulations of biomolecules are becoming an increasingly informative complement to experimental studies. In particular, it has now become feasible to use multiple initial molecular configurations to generate an ensemble of replicate production-run simulations that allows for more complete characterization of rare events such as ligand-receptor unbinding. However, there are currently no explicit guidelines for selecting an ensemble of initial configurations for replicate simulations. Here, we use clustering analysis and steered molecular dynamics simulations to demonstrate that the configurational changes accessible in molecular dynamics simulations of biomolecules do not necessarily correlate with observed rare-event properties. This informs selection of a representative set of initial configurations. We also employ statistical analysis to identify the minimum number of replicate simulations required to sufficiently sample a given biomolecular property distribution. Together, these results suggest a general procedure for generating an ensemble of replicate simulations that will maximize accurate characterization of rare-event property distributions in biomolecules.

Biomolecular Dynamics: Order-Disorder Transitions and Energy Landscapes

PubMed Central

Whitford, Paul C.; Sanbonmatsu, Karissa Y.; Onuchic, José N.

2013-01-01

While the energy landscape theory of protein folding is now a widely accepted view for understanding how relatively-weak molecular interactions lead to rapid and cooperative protein folding, such a framework must be extended to describe the large-scale functional motions observed in molecular machines. In this review, we discuss 1) the development of the energy landscape theory of biomolecular folding, 2) recent advances towards establishing a consistent understanding of folding and function, and 3) emerging themes in the functional motions of enzymes, biomolecular motors, and other biomolecular machines. Recent theoretical, computational, and experimental lines of investigation are providing a very dynamic picture of biomolecular motion. In contrast to earlier ideas, where molecular machines were thought to function similarly to macroscopic machines, with rigid components that move along a few degrees of freedom in a deterministic fashion, biomolecular complexes are only marginally stable. Since the stabilizing contribution of each atomic interaction is on the order of the thermal fluctuations in solution, the rigid body description of molecular function must be revisited. An emerging theme is that functional motions encompass order-disorder transitions and structural flexibility provide significant contributions to the free-energy. In this review, we describe the biological importance of order-disorder transitions and discuss the statistical-mechanical foundation of theoretical approaches that can characterize such transitions. PMID:22790780

Poisson-Nernst-Planck equations for simulating biomolecular diffusion-reaction processes I: Finite element solutions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu Benzhuo; Holst, Michael J.; Center for Theoretical Biological Physics, University of California San Diego, La Jolla, CA 92093

2010-09-20

In this paper we developed accurate finite element methods for solving 3-D Poisson-Nernst-Planck (PNP) equations with singular permanent charges for simulating electrodiffusion in solvated biomolecular systems. The electrostatic Poisson equation was defined in the biomolecules and in the solvent, while the Nernst-Planck equation was defined only in the solvent. We applied a stable regularization scheme to remove the singular component of the electrostatic potential induced by the permanent charges inside biomolecules, and formulated regular, well-posed PNP equations. An inexact-Newton method was used to solve the coupled nonlinear elliptic equations for the steady problems; while an Adams-Bashforth-Crank-Nicolson method was devised formore » time integration for the unsteady electrodiffusion. We numerically investigated the conditioning of the stiffness matrices for the finite element approximations of the two formulations of the Nernst-Planck equation, and theoretically proved that the transformed formulation is always associated with an ill-conditioned stiffness matrix. We also studied the electroneutrality of the solution and its relation with the boundary conditions on the molecular surface, and concluded that a large net charge concentration is always present near the molecular surface due to the presence of multiple species of charged particles in the solution. The numerical methods are shown to be accurate and stable by various test problems, and are applicable to real large-scale biophysical electrodiffusion problems.« less

Lipid Interaction Sites on Channels, Transporters and Receptors: Recent Insights from Molecular Dynamics Simulations

PubMed Central

Hedger, George; Sansom, Mark S. P.

2017-01-01

Lipid molecules are able to selectively interact with specific sites on integral membrane proteins, and modulate their structure and function. Identification and characterisation of these sites is of importance for our understanding of the molecular basis of membrane protein function and stability, and may facilitate the design of lipid-like drug molecules. Molecular dynamics simulations provide a powerful tool for the identification of these sites, complementing advances in membrane protein structural biology and biophysics. We describe recent notable biomolecular simulation studies which have identified lipid interaction sites on a range of different membrane proteins. The sites identified in these simulation studies agree well with those identified by complementary experimental techniques. This demonstrates the power of the molecular dynamics approach in the prediction and characterization of lipid interaction sites on integral membrane proteins. PMID:26946244

MDANSE: An Interactive Analysis Environment for Molecular Dynamics Simulations.

PubMed

Goret, G; Aoun, B; Pellegrini, E

2017-01-23

The MDANSE software-Molecular Dynamics Analysis of Neutron Scattering Experiments-is presented. It is an interactive application for postprocessing molecular dynamics (MD) simulations. Given the widespread use of MD simulations in material and biomolecular sciences to get a better insight for experimental techniques such as thermal neutron scattering (TNS), the development of MDANSE has focused on providing a user-friendly, interactive, graphical user interface for analyzing many trajectories in the same session and running several analyses simultaneously independently of the interface. This first version of MDANSE already proposes a broad range of analyses, and the application has been designed to facilitate the introduction of new analyses in the framework. All this makes MDANSE a valuable tool for extracting useful information from trajectories resulting from a wide range of MD codes.

Coarse-grained molecular dynamics simulations for giant protein-DNA complexes

NASA Astrophysics Data System (ADS)

Takada, Shoji

Biomolecules are highly hierarchic and intrinsically flexible. Thus, computational modeling calls for multi-scale methodologies. We have been developing a coarse-grained biomolecular model where on-average 10-20 atoms are grouped into one coarse-grained (CG) particle. Interactions among CG particles are tuned based on atomistic interactions and the fluctuation matching algorithm. CG molecular dynamics methods enable us to simulate much longer time scale motions of much larger molecular systems than fully atomistic models. After broad sampling of structures with CG models, we can easily reconstruct atomistic models, from which one can continue conventional molecular dynamics simulations if desired. Here, we describe our CG modeling methodology for protein-DNA complexes, together with various biological applications, such as the DNA duplication initiation complex, model chromatins, and transcription factor dynamics on chromatin-like environment.

Computational design and multiscale modeling of a nanoactuator using DNA actuation.

PubMed

Hamdi, Mustapha

2009-12-02

Developments in the field of nanobiodevices coupling nanostructures and biological components are of great interest in medical nanorobotics. As the fundamentals of bio/non-bio interaction processes are still poorly understood in the design of these devices, design tools and multiscale dynamics modeling approaches are necessary at the fabrication pre-project stage. This paper proposes a new concept of optimized carbon nanotube based servomotor design for drug delivery and biomolecular transport applications. The design of an encapsulated DNA-multi-walled carbon nanotube actuator is prototyped using multiscale modeling. The system is parametrized by using a quantum level approach and characterized by using a molecular dynamics simulation. Based on the analysis of the simulation results, a servo nanoactuator using ionic current feedback is simulated and analyzed for application as a drug delivery carrier.

An Atomic Force Microscope with Dual Actuation Capability for Biomolecular Experiments

NASA Astrophysics Data System (ADS)

Sevim, Semih; Shamsudhin, Naveen; Ozer, Sevil; Feng, Luying; Fakhraee, Arielle; Ergeneman, Olgaç; Pané, Salvador; Nelson, Bradley J.; Torun, Hamdi

2016-06-01

We report a modular atomic force microscope (AFM) design for biomolecular experiments. The AFM head uses readily available components and incorporates deflection-based optics and a piezotube-based cantilever actuator. Jetted-polymers have been used in the mechanical assembly, which allows rapid manufacturing. In addition, a FeCo-tipped electromagnet provides high-force cantilever actuation with vertical magnetic fields up to 0.55 T. Magnetic field calibration has been performed with a micro-hall sensor, which corresponds well with results from finite element magnetostatics simulations. An integrated force resolution of 1.82 and 2.98 pN, in air and in DI water, respectively was achieved in 1 kHz bandwidth with commercially available cantilevers made of Silicon Nitride. The controller and user interface are implemented on modular hardware to ensure scalability. The AFM can be operated in different modes, such as molecular pulling or force-clamp, by actuating the cantilever with the available actuators. The electromagnetic and piezoelectric actuation capabilities have been demonstrated in unbinding experiments of the biotin-streptavidin complex.

Evaluating Parametrization Protocols for Hydration Free Energy Calculations with the AMOEBA Polarizable Force Field.

PubMed

Bradshaw, Richard T; Essex, Jonathan W

2016-08-09

Hydration free energy (HFE) calculations are often used to assess the performance of biomolecular force fields and the quality of assigned parameters. The AMOEBA polarizable force field moves beyond traditional pairwise additive models of electrostatics and may be expected to improve upon predictions of thermodynamic quantities such as HFEs over and above fixed-point-charge models. The recent SAMPL4 challenge evaluated the AMOEBA polarizable force field in this regard but showed substantially worse results than those using the fixed-point-charge GAFF model. Starting with a set of automatically generated AMOEBA parameters for the SAMPL4 data set, we evaluate the cumulative effects of a series of incremental improvements in parametrization protocol, including both solute and solvent model changes. Ultimately, the optimized AMOEBA parameters give a set of results that are not statistically significantly different from those of GAFF in terms of signed and unsigned error metrics. This allows us to propose a number of guidelines for new molecule parameter derivation with AMOEBA, which we expect to have benefits for a range of biomolecular simulation applications such as protein-ligand binding studies.

Rapid microfluidic mixing and liquid jets for studying biomolecular chemical dynamics

NASA Astrophysics Data System (ADS)

Langley, Daniel; Abbey, Brian

2018-01-01

X-ray Free-Electron Lasers (XFELs) offer a unique opportunity to study the structural dynamics of proteins on a femtosecond time-scale. To realize the full potential of XFEL sources for studying time-resolved biomolecular processes however, requires the optimization and development of devices that can both act as a trigger and a delivery mechanism for the system of interest. Here we present numerical simulations and actual devices exploring the conditions required for the development of successful mixing and injection devices for tracking the molecular dynamics of proteins in solution on micro to nanosecond timescales using XFELs. The mechanism for combining reagents employs a threefold combination of pico-liter volumes, lamination and serpentine mixing. Focusing and delivering the sample in solution is achieved using the Gas Dynamic Virtual Nozzle (GDVN), which was specifically developed to produce a micrometer diameter, in-vacuum liquid jet. We explore the influence of parameters such as flow rate and gas pressure on the mixing time and jet stability, and explore the formation of rapid homogeneously mixed jets for `mix-and-inject' liquid scattering experiments at Synchrotron and XFEL facilities.

An Atomic Force Microscope with Dual Actuation Capability for Biomolecular Experiments

PubMed Central

Sevim, Semih; Shamsudhin, Naveen; Ozer, Sevil; Feng, Luying; Fakhraee, Arielle; Ergeneman, Olgaç; Pané, Salvador; Nelson, Bradley J.; Torun, Hamdi

2016-01-01

We report a modular atomic force microscope (AFM) design for biomolecular experiments. The AFM head uses readily available components and incorporates deflection-based optics and a piezotube-based cantilever actuator. Jetted-polymers have been used in the mechanical assembly, which allows rapid manufacturing. In addition, a FeCo-tipped electromagnet provides high-force cantilever actuation with vertical magnetic fields up to 0.55 T. Magnetic field calibration has been performed with a micro-hall sensor, which corresponds well with results from finite element magnetostatics simulations. An integrated force resolution of 1.82 and 2.98 pN, in air and in DI water, respectively was achieved in 1 kHz bandwidth with commercially available cantilevers made of Silicon Nitride. The controller and user interface are implemented on modular hardware to ensure scalability. The AFM can be operated in different modes, such as molecular pulling or force-clamp, by actuating the cantilever with the available actuators. The electromagnetic and piezoelectric actuation capabilities have been demonstrated in unbinding experiments of the biotin-streptavidin complex. PMID:27273214

Developing the Biomolecular Screening Facility at the EPFL into the Chemical Biology Screening Platform for Switzerland.

PubMed

Turcatti, Gerardo

2014-05-01

The Biomolecular Screening Facility (BSF) is a multidisciplinary laboratory created in 2006 at the Ecole Polytechnique Federale de Lausanne (EPFL) to perform medium and high throughput screening in life sciences-related projects. The BSF was conceived and developed to meet the needs of a wide range of researchers, without privileging a particular biological discipline or therapeutic area. The facility has the necessary infrastructure, multidisciplinary expertise and flexibility to perform large screening programs using small interfering RNAs (siRNAs) and chemical collections in the areas of chemical biology, systems biology and drug discovery. In the framework of the National Centres of Competence in Research (NCCR) Chemical Biology, the BSF is hosting 'ACCESS', the Academic Chemical Screening Platform of Switzerland that provides the scientific community with chemical diversity, screening facilities and know-how in chemical genetics. In addition, the BSF started its own applied research axes that are driven by innovation in thematic areas related to preclinical drug discovery and discovery of bioactive probes.

On Macroscopic Quantum Phenomena in Biomolecules and Cells: From Levinthal to Hopfield

PubMed Central

Raković, Dejan; Dugić, Miroljub; Jeknić-Dugić, Jasmina; Plavšić, Milenko; Jaćimovski, Stevo; Šetrajčić, Jovan

2014-01-01

In the context of the macroscopic quantum phenomena of the second kind, we hereby seek for a solution-in-principle of the long standing problem of the polymer folding, which was considered by Levinthal as (semi)classically intractable. To illuminate it, we applied quantum-chemical and quantum decoherence approaches to conformational transitions. Our analyses imply the existence of novel macroscopic quantum biomolecular phenomena, with biomolecular chain folding in an open environment considered as a subtle interplay between energy and conformation eigenstates of this biomolecule, governed by quantum-chemical and quantum decoherence laws. On the other hand, within an open biological cell, a system of all identical (noninteracting and dynamically noncoupled) biomolecular proteins might be considered as corresponding spatial quantum ensemble of these identical biomolecular processors, providing spatially distributed quantum solution to a single corresponding biomolecular chain folding, whose density of conformational states might be represented as Hopfield-like quantum-holographic associative neural network too (providing an equivalent global quantum-informational alternative to standard molecular-biology local biochemical approach in biomolecules and cells and higher hierarchical levels of organism, as well). PMID:25028662

Molecular Dynamics Visualization (MDV): Stereoscopic 3D Display of Biomolecular Structure and Interactions Using the Unity Game Engine.

PubMed

Wiebrands, Michael; Malajczuk, Chris J; Woods, Andrew J; Rohl, Andrew L; Mancera, Ricardo L

2018-06-21

Molecular graphics systems are visualization tools which, upon integration into a 3D immersive environment, provide a unique virtual reality experience for research and teaching of biomolecular structure, function and interactions. We have developed a molecular structure and dynamics application, the Molecular Dynamics Visualization tool, that uses the Unity game engine combined with large scale, multi-user, stereoscopic visualization systems to deliver an immersive display experience, particularly with a large cylindrical projection display. The application is structured to separate the biomolecular modeling and visualization systems. The biomolecular model loading and analysis system was developed as a stand-alone C# library and provides the foundation for the custom visualization system built in Unity. All visual models displayed within the tool are generated using Unity-based procedural mesh building routines. A 3D user interface was built to allow seamless dynamic interaction with the model while being viewed in 3D space. Biomolecular structure analysis and display capabilities are exemplified with a range of complex systems involving cell membranes, protein folding and lipid droplets.

Improvements to the APBS biomolecular solvation software suite: Improvements to the APBS Software Suite

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jurrus, Elizabeth; Engel, Dave; Star, Keith

The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that has provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suitemore » of accompanying software since its release in 2001. In this manuscript, we discuss the models and capabilities that have recently been implemented within the APBS software package including: a Poisson-Boltzmann analytical and a semi-analytical solver, an optimized boundary element solver, a geometry-based geometric flow solvation model, a graph theory based algorithm for determining pKa values, and an improved web-based visualization tool for viewing electrostatics.« less

Improvements to the APBS biomolecular solvation software suite.

PubMed

Jurrus, Elizabeth; Engel, Dave; Star, Keith; Monson, Kyle; Brandi, Juan; Felberg, Lisa E; Brookes, David H; Wilson, Leighton; Chen, Jiahui; Liles, Karina; Chun, Minju; Li, Peter; Gohara, David W; Dolinsky, Todd; Konecny, Robert; Koes, David R; Nielsen, Jens Erik; Head-Gordon, Teresa; Geng, Weihua; Krasny, Robert; Wei, Guo-Wei; Holst, Michael J; McCammon, J Andrew; Baker, Nathan A

2018-01-01

The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that have provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses the three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suite of accompanying software since its release in 2001. In this article, we discuss the models and capabilities that have recently been implemented within the APBS software package including a Poisson-Boltzmann analytical and a semi-analytical solver, an optimized boundary element solver, a geometry-based geometric flow solvation model, a graph theory-based algorithm for determining pK a values, and an improved web-based visualization tool for viewing electrostatics. © 2017 The Protein Society.

Biomolecular computers with multiple restriction enzymes.

PubMed

Sakowski, Sebastian; Krasinski, Tadeusz; Waldmajer, Jacek; Sarnik, Joanna; Blasiak, Janusz; Poplawski, Tomasz

2017-01-01

The development of conventional, silicon-based computers has several limitations, including some related to the Heisenberg uncertainty principle and the von Neumann "bottleneck". Biomolecular computers based on DNA and proteins are largely free of these disadvantages and, along with quantum computers, are reasonable alternatives to their conventional counterparts in some applications. The idea of a DNA computer proposed by Ehud Shapiro's group at the Weizmann Institute of Science was developed using one restriction enzyme as hardware and DNA fragments (the transition molecules) as software and input/output signals. This computer represented a two-state two-symbol finite automaton that was subsequently extended by using two restriction enzymes. In this paper, we propose the idea of a multistate biomolecular computer with multiple commercially available restriction enzymes as hardware. Additionally, an algorithmic method for the construction of transition molecules in the DNA computer based on the use of multiple restriction enzymes is presented. We use this method to construct multistate, biomolecular, nondeterministic finite automata with four commercially available restriction enzymes as hardware. We also describe an experimental applicaton of this theoretical model to a biomolecular finite automaton made of four endonucleases.

Mapping mechanical force propagation through biomolecular complexes

DOE PAGES

Schoeler, Constantin; Bernardi, Rafael C.; Malinowska, Klara H.; ...

2015-08-11

In this paper, we employ single-molecule force spectroscopy with an atomic force microscope (AFM) and steered molecular dynamics (SMD) simulations to reveal force propagation pathways through a mechanically ultrastable multidomain cellulosome protein complex. We demonstrate a new combination of network-based correlation analysis supported by AFM directional pulling experiments, which allowed us to visualize stiff paths through the protein complex along which force is transmitted. Finally, the results implicate specific force-propagation routes nonparallel to the pulling axis that are advantageous for achieving high dissociation forces.

Validation of nuclear magnetic resonance structures of proteins and nucleic acids: hydrogen geometry and nomenclature.

PubMed

Doreleijers, J F; Vriend, G; Raves, M L; Kaptein, R

1999-11-15

A statistical analysis is reported of 1,200 of the 1,404 nuclear magnetic resonance (NMR)-derived protein and nucleic acid structures deposited in the Protein Data Bank (PDB) before 1999. Excluded from this analysis were the entries not yet fully validated by the PDB and the more than 100 entries that contained < 95% of the expected hydrogens. The aim was to assess the geometry of the hydrogens in the remaining structures and to provide a check on their nomenclature. Deviations in bond lengths, bond angles, improper dihedral angles, and planarity with respect to estimated values were checked. More than 100 entries showed anomalous protonation states for some of their amino acids. Approximately 250,000 (1.7%) atom names differed from the consensus PDB nomenclature. Most of the inconsistencies are due to swapped prochiral labeling. Large deviations from the expected geometry exist for a considerable number of entries, many of which are average structures. The most common causes for these deviations seem to be poor minimization of average structures and an improper balance between force-field constraints for experimental and holonomic data. Some specific geometric outliers are related to the refinement programs used. A number of recommendations for biomolecular databases, modeling programs, and authors submitting biomolecular structures are given.

Calculation of relative free energies for ligand-protein binding, solvation, and conformational transitions using the GROMOS software.

PubMed

Riniker, Sereina; Christ, Clara D; Hansen, Halvor S; Hünenberger, Philippe H; Oostenbrink, Chris; Steiner, Denise; van Gunsteren, Wilfred F

2011-11-24

The calculation of the relative free energies of ligand-protein binding, of solvation for different compounds, and of different conformational states of a polypeptide is of considerable interest in the design or selection of potential enzyme inhibitors. Since such processes in aqueous solution generally comprise energetic and entropic contributions from many molecular configurations, adequate sampling of the relevant parts of configurational space is required and can be achieved through molecular dynamics simulations. Various techniques to obtain converged ensemble averages and their implementation in the GROMOS software for biomolecular simulation are discussed, and examples of their application to biomolecules in aqueous solution are given. © 2011 American Chemical Society

A Simple and Accurate Method To Calculate Free Energy Profiles and Reaction Rates from Restrained Molecular Simulations of Diffusive Processes.

PubMed

Ovchinnikov, Victor; Nam, Kwangho; Karplus, Martin

2016-08-25

A method is developed to obtain simultaneously free energy profiles and diffusion constants from restrained molecular simulations in diffusive systems. The method is based on low-order expansions of the free energy and diffusivity as functions of the reaction coordinate. These expansions lead to simple analytical relationships between simulation statistics and model parameters. The method is tested on 1D and 2D model systems; its accuracy is found to be comparable to or better than that of the existing alternatives, which are briefly discussed. An important aspect of the method is that the free energy is constructed by integrating its derivatives, which can be computed without need for overlapping sampling windows. The implementation of the method in any molecular simulation program that supports external umbrella potentials (e.g., CHARMM) requires modification of only a few lines of code. As a demonstration of its applicability to realistic biomolecular systems, the method is applied to model the α-helix ↔ β-sheet transition in a 16-residue peptide in implicit solvent, with the reaction coordinate provided by the string method. Possible modifications of the method are briefly discussed; they include generalization to multidimensional reaction coordinates [in the spirit of the model of Ermak and McCammon (Ermak, D. L.; McCammon, J. A. J. Chem. Phys. 1978, 69, 1352-1360)], a higher-order expansion of the free energy surface, applicability in nonequilibrium systems, and a simple test for Markovianity. In view of the small overhead of the method relative to standard umbrella sampling, we suggest its routine application in the cases where umbrella potential simulations are appropriate.

Lightweight Object Oriented Structure analysis: Tools for building Tools to Analyze Molecular Dynamics Simulations

PubMed Central

Romo, Tod D.; Leioatts, Nicholas; Grossfield, Alan

2014-01-01

LOOS (Lightweight Object-Oriented Structure-analysis) is a C++ library designed to facilitate making novel tools for analyzing molecular dynamics simulations by abstracting out the repetitive tasks, allowing developers to focus on the scientifically relevant part of the problem. LOOS supports input using the native file formats of most common biomolecular simulation packages, including CHARMM, NAMD, Amber, Tinker, and Gromacs. A dynamic atom selection language based on the C expression syntax is included and is easily accessible to the tool-writer. In addition, LOOS is bundled with over 120 pre-built tools, including suites of tools for analyzing simulation convergence, 3D histograms, and elastic network models. Through modern C++ design, LOOS is both simple to develop with (requiring knowledge of only 4 core classes and a few utility functions) and is easily extensible. A python interface to the core classes is also provided, further facilitating tool development. PMID:25327784

Lightweight object oriented structure analysis: tools for building tools to analyze molecular dynamics simulations.

PubMed

Romo, Tod D; Leioatts, Nicholas; Grossfield, Alan

2014-12-15

LOOS (Lightweight Object Oriented Structure-analysis) is a C++ library designed to facilitate making novel tools for analyzing molecular dynamics simulations by abstracting out the repetitive tasks, allowing developers to focus on the scientifically relevant part of the problem. LOOS supports input using the native file formats of most common biomolecular simulation packages, including CHARMM, NAMD, Amber, Tinker, and Gromacs. A dynamic atom selection language based on the C expression syntax is included and is easily accessible to the tool-writer. In addition, LOOS is bundled with over 140 prebuilt tools, including suites of tools for analyzing simulation convergence, three-dimensional histograms, and elastic network models. Through modern C++ design, LOOS is both simple to develop with (requiring knowledge of only four core classes and a few utility functions) and is easily extensible. A python interface to the core classes is also provided, further facilitating tool development. © 2014 Wiley Periodicals, Inc.

The ligand binding mechanism to purine nucleoside phosphorylase elucidated via molecular dynamics and machine learning.

PubMed

Decherchi, Sergio; Berteotti, Anna; Bottegoni, Giovanni; Rocchia, Walter; Cavalli, Andrea

2015-01-27

The study of biomolecular interactions between a drug and its biological target is of paramount importance for the design of novel bioactive compounds. In this paper, we report on the use of molecular dynamics (MD) simulations and machine learning to study the binding mechanism of a transition state analogue (DADMe-immucillin-H) to the purine nucleoside phosphorylase (PNP) enzyme. Microsecond-long MD simulations allow us to observe several binding events, following different dynamical routes and reaching diverse binding configurations. These simulations are used to estimate kinetic and thermodynamic quantities, such as kon and binding free energy, obtaining a good agreement with available experimental data. In addition, we advance a hypothesis for the slow-onset inhibition mechanism of DADMe-immucillin-H against PNP. Combining extensive MD simulations with machine learning algorithms could therefore be a fruitful approach for capturing key aspects of drug-target recognition and binding.

Proton storage site in bacteriorhodopsin: new insights from QM/MM simulations of microscopic pKa and infrared spectra

PubMed Central

Goyal, Puja; Ghosh, Nilanjan; Phatak, Prasad; Clemens, Maike; Gaus, Michael; Elstner, Marcus; Cui, Qiang

2011-01-01

Identifying the group that acts as the proton storage/loading site is a challenging but important problem for understanding the mechanism of proton pumping in biomolecular proton pumps, such as bacteriorhodopsin (bR) and cytochrome c oxidase. Recent experimental studies of bR propelled the idea that the proton storage/release group (PRG) in bR is not an amino acid but a water cluster embedded in the protein. We argue that this idea is at odds with our knowledge of protein electrostatics, since invoking the water cluster as PRG would require the protein to raise the pKa of a hydronium by almost 11 pKa units, which is difficult considering known cases of pKa shifts in proteins. Our recent QM/MM simulations suggested an alternative “intermolecular proton bond” model in which the stored proton is shared between two conserved Glu residues (194 and 204). Here we show that this model leads to microscopic pKa values consistent with available experimental data and the functional requirement of a PRG. Extensive QM/MM simulations also show that, independent of a number of technical issues, such as the influence of QM region size, starting x-ray structure and nuclear quantum effects, the “intermolecular proton bond” model is qualitatively consistent with available spectroscopic data. Potential of mean force calculations show explicitly that the stored proton strongly prefers the pair of Glu residues over the water cluster. The results and analyses help highlight the importance of considering protein electrostatics and provide arguments for why the “intermolecular proton bond” model is likely applicable to PRG in biomolecular proton pumps in general. PMID:21761868

The Molecular Origin of Enthalpy/Entropy Compensation in Biomolecular Recognition.

PubMed

Fox, Jerome M; Zhao, Mengxia; Fink, Michael J; Kang, Kyungtae; Whitesides, George M

2018-05-20

Biomolecular recognition can be stubborn; changes in the structures of associating molecules, or the environments in which they associate, often yield compensating changes in enthalpies and entropies of binding and no net change in affinities. This phenomenon-termed enthalpy/entropy (H/S) compensation-hinders efforts in biomolecular design, and its incidence-often a surprise to experimentalists-makes interactions between biomolecules difficult to predict. Although characterizing H/S compensation requires experimental care, it is unquestionably a real phenomenon that has, from an engineering perspective, useful physical origins. Studying H/S compensation can help illuminate the still-murky roles of water and dynamics in biomolecular recognition and self-assembly. This review summarizes known sources of H/ S compensation (real and perceived) and lays out a conceptual framework for understanding and dissecting-and, perhaps, avoiding or exploiting-this phenomenon in biophysical systems.

Electrochemical sensor for multiplex screening of genetically modified DNA: identification of biotech crops by logic-based biomolecular analysis.

PubMed

Liao, Wei-Ching; Chuang, Min-Chieh; Ho, Ja-An Annie

2013-12-15

Genetically modified (GM) technique, one of the modern biomolecular engineering technologies, has been deemed as profitable strategy to fight against global starvation. Yet rapid and reliable analytical method is deficient to evaluate the quality and potential risk of such resulting GM products. We herein present a biomolecular analytical system constructed with distinct biochemical activities to expedite the computational detection of genetically modified organisms (GMOs). The computational mechanism provides an alternative to the complex procedures commonly involved in the screening of GMOs. Given that the bioanalytical system is capable of processing promoter, coding and species genes, affirmative interpretations succeed to identify specified GM event in terms of both electrochemical and optical fashions. The biomolecular computational assay exhibits detection capability of genetically modified DNA below sub-nanomolar level and is found interference-free by abundant coexistence of non-GM DNA. This bioanalytical system, furthermore, sophisticates in array fashion operating multiplex screening against variable GM events. Such a biomolecular computational assay and biosensor holds great promise for rapid, cost-effective, and high-fidelity screening of GMO. Copyright © 2013 Elsevier B.V. All rights reserved.

Biomolecular computers with multiple restriction enzymes

PubMed Central

Sakowski, Sebastian; Krasinski, Tadeusz; Waldmajer, Jacek; Sarnik, Joanna; Blasiak, Janusz; Poplawski, Tomasz

2017-01-01

Abstract The development of conventional, silicon-based computers has several limitations, including some related to the Heisenberg uncertainty principle and the von Neumann “bottleneck”. Biomolecular computers based on DNA and proteins are largely free of these disadvantages and, along with quantum computers, are reasonable alternatives to their conventional counterparts in some applications. The idea of a DNA computer proposed by Ehud Shapiro’s group at the Weizmann Institute of Science was developed using one restriction enzyme as hardware and DNA fragments (the transition molecules) as software and input/output signals. This computer represented a two-state two-symbol finite automaton that was subsequently extended by using two restriction enzymes. In this paper, we propose the idea of a multistate biomolecular computer with multiple commercially available restriction enzymes as hardware. Additionally, an algorithmic method for the construction of transition molecules in the DNA computer based on the use of multiple restriction enzymes is presented. We use this method to construct multistate, biomolecular, nondeterministic finite automata with four commercially available restriction enzymes as hardware. We also describe an experimental applicaton of this theoretical model to a biomolecular finite automaton made of four endonucleases. PMID:29064510

DNA algorithms of implementing biomolecular databases on a biological computer.

PubMed

Chang, Weng-Long; Vasilakos, Athanasios V

2015-01-01

In this paper, DNA algorithms are proposed to perform eight operations of relational algebra (calculus), which include Cartesian product, union, set difference, selection, projection, intersection, join, and division, on biomolecular relational databases.

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.

Photochemical Concepts on the Origin of Biomolecular Asymmetry

NASA Astrophysics Data System (ADS)

Meierhenrich, Uwe J.; Thiemann, Wolfram H.-P.

2004-02-01

Biopolymers like DNA and proteins are strongly selective towards the chirality of their monomer units. The use of homochiral monomers is regarded as essential for the construction and function of biopolymers; the emergence of the molecular asymmetry is therefore considered as a fundamental step in Chemical Evolution. This work focuses on physicochemical mechanisms for the origin of biomolecular asymmetry. Very recently two groups, one from Allamandola at NASA Ames and the other from our Inter-European team, demonstrated simultaneously the spontaneous photoformation of a variety of chiral amino acid structures under simulated interstellar conditions. Since both groups used unpolarized light for the photoreaction the obtained amino acids turned out racemic as expected. The obtained experimental data support the assumption that tiny ice grains can furthermore play host to important asymmetric reactions when irradiated by interstellar circularly polarized ultraviolet light. It is possible that such ice grains could have become incorporated into the early cloud that formed our Solar System and ended up on Earth, assisting life to start. Several lines of evidence suggest that some of the building blocks of life were delivered to the primitive Earth via (micro-) meteoroids and/or comets. These results suggest that asymmetric interstellar photochemistry may have played a significant part in supplying Earth with some of the enantioenriched organic materials needed to trigger life. The search for the origin of biomolecular homochirality leads to a strong interest in the fields of asymmetric photochemistry with special emphasis on absolute asymmetric synthesis. We outline here the theoretical background on asymmetric interstellar ice photochemistry, summarize recent concepts and advances in the field, and discuss briefly its implications. The obtained data are crucial for the design of the enantioselective COSAC GC-MS experiment onboard the ROSETTA spacecraft to a comet to be launched in the very near future.

Molecular dynamics simulations of a DMSO/water mixture using the AMBER force field.

PubMed

Stachura, Slawomir S; Malajczuk, Chris J; Mancera, Ricardo L

2018-06-25

Due to its protective properties of biological samples at low temperatures and under desiccation, dimethyl sulfoxide (DMSO) in aqueous solutions has been studied widely by many experimental approaches and molecular dynamics (MD) simulations. In the case of the latter, AMBER is among the most commonly used force fields for simulations of biomolecular systems; however, the parameters for DMSO published by Fox and Kollman in 1998 have only been tested for pure liquid DMSO. We have conducted an MD simulation study of DMSO in a water mixture and computed several structural and dynamical properties such as of the mean density, self-diffusion coefficient, hydrogen bonding and DMSO and water ordering. The AMBER force field of DMSO is seen to reproduce well most of the experimental properties of DMSO in water, with the mixture displaying strong and specific water ordering, as observed in experiments and multiple other MD simulations with other non-polarizable force fields. Graphical abstract Hydration structure within hydrogen-bonding distance around a DMSOmolecule.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noe, F; Diadone, Isabella; Lollmann, Marc

There is a gap between kinetic experiment and simulation in their views of the dynamics of complex biomolecular systems. Whereas experiments typically reveal only a few readily discernible exponential relaxations, simulations often indicate complex multistate behavior. Here, a theoretical framework is presented that reconciles these two approaches. The central concept is dynamical fingerprints which contain peaks at the time scales of the dynamical processes involved with amplitudes determined by the experimental observable. Fingerprints can be generated from both experimental and simulation data, and their comparison by matching peaks permits assignment of structural changes present in the simulation to experimentally observedmore » relaxation processes. The approach is applied here to a test case interpreting single molecule fluorescence correlation spectroscopy experiments on a set of fluorescent peptides with molecular dynamics simulations. The peptides exhibit complex kinetics shown to be consistent with the apparent simplicity of the experimental data. Moreover, the fingerprint approach can be used to design new experiments with site-specific labels that optimally probe specific dynamical processes in the molecule under investigation.« less

An optics-based variable-temperature assay system for characterizing thermodynamics of biomolecular reactions on solid support

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fei, Yiyan; Landry, James P.; Zhu, X. D., E-mail: xdzhu@physics.ucdavis.edu

A biological state is equilibrium of multiple concurrent biomolecular reactions. The relative importance of these reactions depends on physiological temperature typically between 10 °C and 50 °C. Experimentally the temperature dependence of binding reaction constants reveals thermodynamics and thus details of these biomolecular processes. We developed a variable-temperature opto-fluidic system for real-time measurement of multiple (400–10 000) biomolecular binding reactions on solid supports from 10 °C to 60 °C within ±0.1 °C. We illustrate the performance of this system with investigation of binding reactions of plant lectins (carbohydrate-binding proteins) with 24 synthetic glycans (i.e., carbohydrates). We found that the lectin-glycan reactions in general can be enthalpy-driven,more » entropy-driven, or both, and water molecules play critical roles in the thermodynamics of these reactions.« less

An optics-based variable-temperature assay system for characterizing thermodynamics of biomolecular reactions on solid support

NASA Astrophysics Data System (ADS)

Fei, Yiyan; Landry, James P.; Li, Yanhong; Yu, Hai; Lau, Kam; Huang, Shengshu; Chokhawala, Harshal A.; Chen, Xi; Zhu, X. D.

2013-11-01

A biological state is equilibrium of multiple concurrent biomolecular reactions. The relative importance of these reactions depends on physiological temperature typically between 10 °C and 50 °C. Experimentally the temperature dependence of binding reaction constants reveals thermodynamics and thus details of these biomolecular processes. We developed a variable-temperature opto-fluidic system for real-time measurement of multiple (400-10 000) biomolecular binding reactions on solid supports from 10 °C to 60 °C within ±0.1 °C. We illustrate the performance of this system with investigation of binding reactions of plant lectins (carbohydrate-binding proteins) with 24 synthetic glycans (i.e., carbohydrates). We found that the lectin-glycan reactions in general can be enthalpy-driven, entropy-driven, or both, and water molecules play critical roles in the thermodynamics of these reactions.

Quantifying the topography of the intrinsic energy landscape of flexible biomolecular recognition

PubMed Central

Chu, Xiakun; Gan, Linfeng; Wang, Erkang; Wang, Jin

2013-01-01

Biomolecular functions are determined by their interactions with other molecules. Biomolecular recognition is often flexible and associated with large conformational changes involving both binding and folding. However, the global and physical understanding for the process is still challenging. Here, we quantified the intrinsic energy landscapes of flexible biomolecular recognition in terms of binding–folding dynamics for 15 homodimers by exploring the underlying density of states, using a structure-based model both with and without considering energetic roughness. By quantifying three individual effective intrinsic energy landscapes (one for interfacial binding, two for monomeric folding), the association mechanisms for flexible recognition of 15 homodimers can be classified into two-state cooperative “coupled binding–folding” and three-state noncooperative “folding prior to binding” scenarios. We found that the association mechanism of flexible biomolecular recognition relies on the interplay between the underlying effective intrinsic binding and folding energy landscapes. By quantifying the whole global intrinsic binding–folding energy landscapes, we found strong correlations between the landscape topography measure Λ (dimensionless ratio of energy gap versus roughness modulated by the configurational entropy) and the ratio of the thermodynamic stable temperature versus trapping temperature, as well as between Λ and binding kinetics. Therefore, the global energy landscape topography determines the binding–folding thermodynamics and kinetics, crucial for the feasibility and efficiency of realizing biomolecular function. We also found “U-shape” temperature-dependent kinetic behavior and a dynamical cross-over temperature for dividing exponential and nonexponential kinetics for two-state homodimers. Our study provides a unique way to bridge the gap between theory and experiments. PMID:23754431

Two-bead polarizable water models combined with a two-bead multipole force field (TMFF) for coarse-grained simulation of proteins.

PubMed

Li, Min; Zhang, John Z H

2017-03-08

The development of polarizable water models at coarse-grained (CG) levels is of much importance to CG molecular dynamics simulations of large biomolecular systems. In this work, we combined the newly developed two-bead multipole force field (TMFF) for proteins with the two-bead polarizable water models to carry out CG molecular dynamics simulations for benchmark proteins. In our simulations, two different two-bead polarizable water models are employed, the RTPW model representing five water molecules by Riniker et al. and the LTPW model representing four water molecules. The LTPW model is developed in this study based on the Martini three-bead polarizable water model. Our simulation results showed that the combination of TMFF with the LTPW model significantly stabilizes the protein's native structure in CG simulations, while the use of the RTPW model gives better agreement with all-atom simulations in predicting the residue-level fluctuation dynamics. Overall, the TMFF coupled with the two-bead polarizable water models enables one to perform an efficient and reliable CG dynamics study of the structural and functional properties of large biomolecules.

Multi-scale Visualization of Molecular Architecture Using Real-Time Ambient Occlusion in Sculptor.

PubMed

Wahle, Manuel; Wriggers, Willy

2015-10-01

The modeling of large biomolecular assemblies relies on an efficient rendering of their hierarchical architecture across a wide range of spatial level of detail. We describe a paradigm shift currently under way in computer graphics towards the use of more realistic global illumination models, and we apply the so-called ambient occlusion approach to our open-source multi-scale modeling program, Sculptor. While there are many other higher quality global illumination approaches going all the way up to full GPU-accelerated ray tracing, they do not provide size-specificity of the features they shade. Ambient occlusion is an aspect of global lighting that offers great visual benefits and powerful user customization. By estimating how other molecular shape features affect the reception of light at some surface point, it effectively simulates indirect shadowing. This effect occurs between molecular surfaces that are close to each other, or in pockets such as protein or ligand binding sites. By adding ambient occlusion, large macromolecular systems look much more natural, and the perception of characteristic surface features is strongly enhanced. In this work, we present a real-time implementation of screen space ambient occlusion that delivers realistic cues about tunable spatial scale characteristics of macromolecular architecture. Heretofore, the visualization of large biomolecular systems, comprising e.g. hundreds of thousands of atoms or Mega-Dalton size electron microscopy maps, did not take into account the length scales of interest or the spatial resolution of the data. Our approach has been uniquely customized with shading that is tuned for pockets and cavities of a user-defined size, making it useful for visualizing molecular features at multiple scales of interest. This is a feature that none of the conventional ambient occlusion approaches provide. Actual Sculptor screen shots illustrate how our implementation supports the size-dependent rendering of molecular surface features.

Analysis of biomolecular solvation sites by 3D-RISM theory.

PubMed

Sindhikara, Daniel J; Hirata, Fumio

2013-06-06

We derive, implement, and apply equilibrium solvation site analysis for biomolecules. Our method utilizes 3D-RISM calculations to quickly obtain equilibrium solvent distributions without either necessity of simulation or limits of solvent sampling. Our analysis of these distributions extracts highest likelihood poses of solvent as well as localized entropies, enthalpies, and solvation free energies. We demonstrate our method on a structure of HIV-1 protease where excellent structural and thermodynamic data are available for comparison. Our results, obtained within minutes, show systematic agreement with available experimental data. Further, our results are in good agreement with established simulation-based solvent analysis methods. This method can be used not only for visual analysis of active site solvation but also for virtual screening methods and experimental refinement.

Multicanonical molecular dynamics simulations combined with Metadynamics for the free energy landscape of a biomolecular system with high energy barriers

NASA Astrophysics Data System (ADS)

Yonezawa, Yasushige; Shimoyama, Hiromitsu; Nakamura, Haruki

2011-01-01

Multicanonical molecular-dynamics (McMD) simulation and Metadynamics (MetaD) are useful for obtaining the free-energies, and can be mutually complementary. We combined McMD with MetaD, and applied it to the conformational free energy calculations of a proline dipeptide. First, MetaD was performed along the dihedral angle at the prolyl bond and we obtained a coarse biasing potential. After adding the biasing potential to the dihedral angle potential energy, we conducted McMD with the modified potential energy. Enhanced sampling was achieved for all degrees-of-freedom, and the sampling of the dihedral angle space was facilitated. After reweighting, we obtained an accurate free energy landscape.

Free energy calculation of permeant-membrane interactions using molecular dynamics simulations.

PubMed

Elvati, Paolo; Violi, Angela

2012-01-01

Nanotoxicology, the science concerned with the safe use of nanotechnology and nanostructure design for biological applications, is a field of research that has recently received great attention, as a result of the rapid growth in nanotechnology. Many nanostructures are of a scale and chemical composition similar to many biomolecular environments, and recent papers have reported evident toxicity of selected nanoparticles. Molecular simulations can help develop a mechanistic understanding of how structural properties affect bioactivity. In this chapter, we describe how to compute the free energy of interactions between cellular membranes and benzene, the main constituent of some toxic carbonaceous particles, with well-tempered metadynamics. This algorithm reconstructs the free energy surface and accelerates rare events in a coarse-grained representation of the system.

Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation.

PubMed

Miao, Yinglong; Feher, Victoria A; McCammon, J Andrew

2015-08-11

A Gaussian accelerated molecular dynamics (GaMD) approach for simultaneous enhanced sampling and free energy calculation of biomolecules is presented. By constructing a boost potential that follows Gaussian distribution, accurate reweighting of the GaMD simulations is achieved using cumulant expansion to the second order. Here, GaMD is demonstrated on three biomolecular model systems: alanine dipeptide, chignolin folding, and ligand binding to the T4-lysozyme. Without the need to set predefined reaction coordinates, GaMD enables unconstrained enhanced sampling of these biomolecules. Furthermore, the free energy profiles obtained from reweighting of the GaMD simulations allow us to identify distinct low-energy states of the biomolecules and characterize the protein-folding and ligand-binding pathways quantitatively.

Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation

PubMed Central

2016-01-01

A Gaussian accelerated molecular dynamics (GaMD) approach for simultaneous enhanced sampling and free energy calculation of biomolecules is presented. By constructing a boost potential that follows Gaussian distribution, accurate reweighting of the GaMD simulations is achieved using cumulant expansion to the second order. Here, GaMD is demonstrated on three biomolecular model systems: alanine dipeptide, chignolin folding, and ligand binding to the T4-lysozyme. Without the need to set predefined reaction coordinates, GaMD enables unconstrained enhanced sampling of these biomolecules. Furthermore, the free energy profiles obtained from reweighting of the GaMD simulations allow us to identify distinct low-energy states of the biomolecules and characterize the protein-folding and ligand-binding pathways quantitatively. PMID:26300708

Final Scientific Report - Electromagnetic Interactions in Self-Assembled Metallo-Dielectric Biomaterials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dragnea, Bogdan G.

Achievements which resulted from previous DOE funding include: templated virus-like particle assembly thermodynamics, development of single particle photothermal absorption spectroscopy and dark- field spectroscopy instrumentation for the measurement of optical properties of virus-like nanoparticles, electromagnetic simulations of coupled nanoparticle cluster systems, virus contact mechanics, energy transfer and fluorescence quenching in multichromophore systems supported on biomolecular templates, and photo physical work on virus-aptamer systems. A current total of eight published research articles and a book chapter are acknowledging DOE support for the period 2013-2016.

Electrodynamic ratchet motor.

PubMed

Lim, Jiufu; Sader, John E; Mulvaney, Paul

2009-03-01

Brownian ratchets produce directed motion through rectification of thermal fluctuations and have been used for separation processes and colloidal transport. We propose a flashing ratchet motor that enables the transduction of electrical energy into rotary micromechanical work. This is achieved through torque generation provided by boundary shaping of equipotential surfaces. The present device contrasts to previous implementations that focus on translational motion. Stochastic simulations elucidate the performance characteristics of this device as a function of its geometry. Miniaturization to nanoscale dimensions yields rotational speeds in excess of 1 kHz, which is comparable to biomolecular motors of similar size.

Biotechnology: The Forging of Multidisciplinary Strategies for Research in Biomolecular Electronics, Materials Sciences and Microecology.

DTIC Science & Technology

1982-12-01

be investigated both by modifying the sites chemically and by modifying the genes which code for the protei ns. b. Protein stability as well as...spectroscopy is used to determine chemical composition of samples. In a program administered through the Department of Physics, EXAFS (Extended X-ray...soy bean lipoxygenase and hemoglobin). -. .I.. .-I4 t , -. A-16 ELECTRON IMAGING AND ANALYSIS OF BIOLOGICAL SPECIMENS AND MICROCIRCUITS J.S. Hanker

Naval Medical Research And Development News. Volume 7, Issue 8

DTIC Science & Technology

2015-08-01

their bionomics, distribution, and taxonomy to have the best tools to carry out our preventive medicine programs.” In fact , the Navy has been employing...areas on Earth , so there are many amazing and interesting discoveries yet to be made.” New Sand Fly Species and Potential Vector of Leishmaniasis...Laboratory’s Center for Bio/Molecular Science and Engineering in Washington, D.C. began a collaboration to re-design amalgam separators. These efforts began

Ultrasensitive biomolecular assays with amplifying nanowire FET biosensors

NASA Astrophysics Data System (ADS)

Chui, Chi On; Shin, Kyeong-Sik; Mao, Yufei

2013-09-01

In this paper, we review our recent development and validation of the ultrasensitive electronic biomolecular assays enabled by our novel amplifying nanowire field-effect transistor (nwFET) biosensors. Our semiconductor nwFET biosensor platform technology performs extreme proximity signal amplification in the electrical domain that requires neither labeling nor enzymes nor optics. We have designed and fabricated the biomolecular assay prototypes and developed the corresponding analytical procedures. We have also confirmed their analytical performance in quantitating key protein biomarker in human serum, demonstrating an ultralow limit of detection and concurrently high output current level for the first time.

Biomolecular engineering for nanobio/bionanotechnology

NASA Astrophysics Data System (ADS)

Nagamune, Teruyuki

2017-04-01

Biomolecular engineering can be used to purposefully manipulate biomolecules, such as peptides, proteins, nucleic acids and lipids, within the framework of the relations among their structures, functions and properties, as well as their applicability to such areas as developing novel biomaterials, biosensing, bioimaging, and clinical diagnostics and therapeutics. Nanotechnology can also be used to design and tune the sizes, shapes, properties and functionality of nanomaterials. As such, there are considerable overlaps between nanotechnology and biomolecular engineering, in that both are concerned with the structure and behavior of materials on the nanometer scale or smaller. Therefore, in combination with nanotechnology, biomolecular engineering is expected to open up new fields of nanobio/bionanotechnology and to contribute to the development of novel nanobiomaterials, nanobiodevices and nanobiosystems. This review highlights recent studies using engineered biological molecules (e.g., oligonucleotides, peptides, proteins, enzymes, polysaccharides, lipids, biological cofactors and ligands) combined with functional nanomaterials in nanobio/bionanotechnology applications, including therapeutics, diagnostics, biosensing, bioanalysis and biocatalysts. Furthermore, this review focuses on five areas of recent advances in biomolecular engineering: (a) nucleic acid engineering, (b) gene engineering, (c) protein engineering, (d) chemical and enzymatic conjugation technologies, and (e) linker engineering. Precisely engineered nanobiomaterials, nanobiodevices and nanobiosystems are anticipated to emerge as next-generation platforms for bioelectronics, biosensors, biocatalysts, molecular imaging modalities, biological actuators, and biomedical applications.

In vitro release of organophosphorus acid anhydrolase from functionalized mesoporous silica against nerve agents.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Baowei; Shah, Saumil S.; Shin, Yongsoon

We report here that under different physiological conditions, biomolecular drugs can be stockpiled in a nanoporous support and afterward can be instantly released when needed for acute responses, and the biomolecular drug molecules can also be gradually released from the nanoporous support over a long time for a complete recovery. Organophosphorus acid anhydrolase (OPAA) was spontaneously and largely entrapped in functionalized mesoporous silica (FMS) due to the dominant electrostatic interaction. The OPAA-FMS composite exhibited a burst release in a pH 9.0 NaHCO(3)-Na(2)CO(3) buffer system and a gradual release in pH 7.4 simulated body fluid. The binding of OPAA to NH(2)-FMSmore » can result in less tyrosinyl and tryptophanyl exposure OPAA molecules to aqueous environment. The bound OPAA in FMS displayed lower activity than the free OPAA in solution prior to the enzyme entrapment. However, the released enzyme maintained the native conformational structure and the same high enzymatic activity as that prior to the enzyme entrapment. The in vitro results in the rabbit serum demonstrate that both OPAA-FMS and the released OPAA may be used as a medical countermeasure against the organophosphorus nerve agents.« less

Extracting physics of life at the molecular level: A review of single-molecule data analyses.

PubMed

Colomb, Warren; Sarkar, Susanta K

2015-06-01

Studying individual biomolecules at the single-molecule level has proved very insightful recently. Single-molecule experiments allow us to probe both the equilibrium and nonequilibrium properties as well as make quantitative connections with ensemble experiments and equilibrium thermodynamics. However, it is important to be careful about the analysis of single-molecule data because of the noise present and the lack of theoretical framework for processes far away from equilibrium. Biomolecular motion, whether it is free in solution, on a substrate, or under force, involves thermal fluctuations in varying degrees, which makes the motion noisy. In addition, the noise from the experimental setup makes it even more complex. The details of biologically relevant interactions, conformational dynamics, and activities are hidden in the noisy single-molecule data. As such, extracting biological insights from noisy data is still an active area of research. In this review, we will focus on analyzing both fluorescence-based and force-based single-molecule experiments and gaining biological insights at the single-molecule level. Inherently nonequilibrium nature of biological processes will be highlighted. Simulated trajectories of biomolecular diffusion will be used to compare and validate various analysis techniques. Copyright © 2015 Elsevier B.V. All rights reserved.

Free Energy Perturbation Hamiltonian Replica-Exchange Molecular Dynamics (FEP/H-REMD) for Absolute Ligand Binding Free Energy Calculations.

PubMed

Jiang, Wei; Roux, Benoît

2010-07-01

Free Energy Perturbation with Replica Exchange Molecular Dynamics (FEP/REMD) offers a powerful strategy to improve the convergence of free energy computations. In particular, it has been shown previously that a FEP/REMD scheme allowing random moves within an extended replica ensemble of thermodynamic coupling parameters "lambda" can improve the statistical convergence in calculations of absolute binding free energy of ligands to proteins [J. Chem. Theory Comput. 2009, 5, 2583]. In the present study, FEP/REMD is extended and combined with an accelerated MD simulations method based on Hamiltonian replica-exchange MD (H-REMD) to overcome the additional problems arising from the existence of kinetically trapped conformations within the protein receptor. In the combined strategy, each system with a given thermodynamic coupling factor lambda in the extended ensemble is further coupled with a set of replicas evolving on a biased energy surface with boosting potentials used to accelerate the inter-conversion among different rotameric states of the side chains in the neighborhood of the binding site. Exchanges are allowed to occur alternatively along the axes corresponding to the thermodynamic coupling parameter lambda and the boosting potential, in an extended dual array of coupled lambda- and H-REMD simulations. The method is implemented on the basis of new extensions to the REPDSTR module of the biomolecular simulation program CHARMM. As an illustrative example, the absolute binding free energy of p-xylene to the nonpolar cavity of the L99A mutant of T4 lysozyme was calculated. The tests demonstrate that the dual lambda-REMD and H-REMD simulation scheme greatly accelerates the configurational sampling of the rotameric states of the side chains around the binding pocket, thereby improving the convergence of the FEP computations.

DockScreen: A database of in silico biomolecular interactions to support computational toxicology

EPA Science Inventory

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...

BIOMOLECULAR SENSING FOR BIOLOGICAL PROCESSES AND ENVIRONMENTAL MONITORING APPLICATIONS

EPA Science Inventory

Biomolecular recognition is being increasingly employed as the basis for a variety of analytical methods such as biosensors. he sensitivity, selectivity, and format versatility inherent in these methods may allow them to be adapted to solving a number of analytical problems. ltho...

A self-regulating biomolecular comparator for processing oscillatory signals

PubMed Central

Agrawal, Deepak K.; Franco, Elisa; Schulman, Rebecca

2015-01-01

While many cellular processes are driven by biomolecular oscillators, precise control of a downstream on/off process by a biochemical oscillator signal can be difficult: over an oscillator's period, its output signal varies continuously between its amplitude limits and spends a significant fraction of the time at intermediate values between these limits. Further, the oscillator's output is often noisy, with particularly large variations in the amplitude. In electronic systems, an oscillating signal is generally processed by a downstream device such as a comparator that converts a potentially noisy oscillatory input into a square wave output that is predominantly in one of two well-defined on and off states. The comparator's output then controls downstream processes. We describe a method for constructing a synthetic biochemical device that likewise produces a square-wave-type biomolecular output for a variety of oscillatory inputs. The method relies on a separation of time scales between the slow rate of production of an oscillatory signal molecule and the fast rates of intermolecular binding and conformational changes. We show how to control the characteristics of the output by varying the concentrations of the species and the reaction rates. We then use this control to show how our approach could be applied to process different in vitro and in vivo biomolecular oscillators, including the p53-Mdm2 transcriptional oscillator and two types of in vitro transcriptional oscillators. These results demonstrate how modular biomolecular circuits could, in principle, be combined to build complex dynamical systems. The simplicity of our approach also suggests that natural molecular circuits may process some biomolecular oscillator outputs before they are applied downstream. PMID:26378119

Optimization of a Nucleic Acids united-RESidue 2-Point model (NARES-2P) with a maximum-likelihood approach

NASA Astrophysics Data System (ADS)

He, Yi; Liwo, Adam; Scheraga, Harold A.

2015-12-01

Coarse-grained models are useful tools to investigate the structural and thermodynamic properties of biomolecules. They are obtained by merging several atoms into one interaction site. Such simplified models try to capture as much as possible information of the original biomolecular system in all-atom representation but the resulting parameters of these coarse-grained force fields still need further optimization. In this paper, a force field optimization method, which is based on maximum-likelihood fitting of the simulated to the experimental conformational ensembles and least-squares fitting of the simulated to the experimental heat-capacity curves, is applied to optimize the Nucleic Acid united-RESidue 2-point (NARES-2P) model for coarse-grained simulations of nucleic acids recently developed in our laboratory. The optimized NARES-2P force field reproduces the structural and thermodynamic data of small DNA molecules much better than the original force field.

Exploring RNA structure and dynamics through enhanced sampling simulations.

PubMed

Mlýnský, Vojtěch; Bussi, Giovanni

2018-04-01

RNA function is intimately related to its structural dynamics. Molecular dynamics simulations are useful for exploring biomolecular flexibility but are severely limited by the accessible timescale. Enhanced sampling methods allow this timescale to be effectively extended in order to probe biologically relevant conformational changes and chemical reactions. Here, we review the role of enhanced sampling techniques in the study of RNA systems. We discuss the challenges and promises associated with the application of these methods to force-field validation, exploration of conformational landscapes and ion/ligand-RNA interactions, as well as catalytic pathways. Important technical aspects of these methods, such as the choice of the biased collective variables and the analysis of multi-replica simulations, are examined in detail. Finally, a perspective on the role of these methods in the characterization of RNA dynamics is provided. Copyright © 2018 Elsevier Ltd. All rights reserved.

A software platform for continuum modeling of ion channels based on unstructured mesh

NASA Astrophysics Data System (ADS)

Tu, B.; Bai, S. Y.; Chen, M. X.; Xie, Y.; Zhang, L. B.; Lu, B. Z.

2014-01-01

Most traditional continuum molecular modeling adopted finite difference or finite volume methods which were based on a structured mesh (grid). Unstructured meshes were only occasionally used, but an increased number of applications emerge in molecular simulations. To facilitate the continuum modeling of biomolecular systems based on unstructured meshes, we are developing a software platform with tools which are particularly beneficial to those approaches. This work describes the software system specifically for the simulation of a typical, complex molecular procedure: ion transport through a three-dimensional channel system that consists of a protein and a membrane. The platform contains three parts: a meshing tool chain for ion channel systems, a parallel finite element solver for the Poisson-Nernst-Planck equations describing the electrodiffusion process of ion transport, and a visualization program for continuum molecular modeling. The meshing tool chain in the platform, which consists of a set of mesh generation tools, is able to generate high-quality surface and volume meshes for ion channel systems. The parallel finite element solver in our platform is based on the parallel adaptive finite element package PHG which wass developed by one of the authors [1]. As a featured component of the platform, a new visualization program, VCMM, has specifically been developed for continuum molecular modeling with an emphasis on providing useful facilities for unstructured mesh-based methods and for their output analysis and visualization. VCMM provides a graphic user interface and consists of three modules: a molecular module, a meshing module and a numerical module. A demonstration of the platform is provided with a study of two real proteins, the connexin 26 and hemolysin ion channels.

Low-Latency Telerobotic Sample Return and Biomolecular Sequencing for Deep Space Gateway

NASA Astrophysics Data System (ADS)

Lupisella, M.; Bleacher, J.; Lewis, R.; Dworkin, J.; Wright, M.; Burton, A.; Rubins, K.; Wallace, S.; Stahl, S.; John, K.; Archer, D.; Niles, P.; Regberg, A.; Smith, D.; Race, M.; Chiu, C.; Russell, J.; Rampe, E.; Bywaters, K.

2018-02-01

Low-latency telerobotics, crew-assisted sample return, and biomolecular sequencing can be used to acquire and analyze lunar farside and/or Apollo landing site samples. Sequencing can also be used to monitor and study Deep Space Gateway environment and crew health.

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

Dual-Mode Electro-Optical Techniques for Biosensing Applications: A Review

PubMed Central

Johnson, Steven

2017-01-01

The monitoring of biomolecular interactions is a key requirement for the study of complex biological processes and the diagnosis of disease. Technologies that are capable of providing label-free, real-time insight into these interactions are of great value for the scientific and clinical communities. Greater understanding of biomolecular interactions alongside increased detection accuracy can be achieved using technology that can provide parallel information about multiple parameters of a single biomolecular process. For example, electro-optical techniques combine optical and electrochemical information to provide more accurate and detailed measurements that provide unique insights into molecular structure and function. Here, we present a comparison of the main methods for electro-optical biosensing, namely, electrochemical surface plasmon resonance (EC-SPR), electrochemical optical waveguide lightmode spectroscopy (EC-OWLS), and the recently reported silicon-based electrophotonic approach. The comparison considers different application spaces, such as the detection of low concentrations of biomolecules, integration, the tailoring of light-matter interaction for the understanding of biomolecular processes, and 2D imaging of biointeractions on a surface. PMID:28880211

Biomolecular electrostatics and solvation: a computational perspective

PubMed Central

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.

PubMed

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.

Biomolecular Force Field Parameterization via Atoms-in-Molecule Electron Density Partitioning.

PubMed

Cole, Daniel J; Vilseck, Jonah Z; Tirado-Rives, Julian; Payne, Mike C; Jorgensen, William L

2016-05-10

Molecular mechanics force fields, which are commonly used in biomolecular modeling and computer-aided drug design, typically treat nonbonded interactions using a limited library of empirical parameters that are developed for small molecules. This approach does not account for polarization in larger molecules or proteins, and the parametrization process is labor-intensive. Using linear-scaling density functional theory and atoms-in-molecule electron density partitioning, environment-specific charges and Lennard-Jones parameters are derived directly from quantum mechanical calculations for use in biomolecular modeling of organic and biomolecular systems. The proposed methods significantly reduce the number of empirical parameters needed to construct molecular mechanics force fields, naturally include polarization effects in charge and Lennard-Jones parameters, and scale well to systems comprised of thousands of atoms, including proteins. The feasibility and benefits of this approach are demonstrated by computing free energies of hydration, properties of pure liquids, and the relative binding free energies of indole and benzofuran to the L99A mutant of T4 lysozyme.

Dual-Mode Electro-Optical Techniques for Biosensing Applications: A Review.

PubMed

Juan-Colás, José; Johnson, Steven; Krauss, Thomas F

2017-09-07

The monitoring of biomolecular interactions is a key requirement for the study of complex biological processes and the diagnosis of disease. Technologies that are capable of providing label-free, real-time insight into these interactions are of great value for the scientific and clinical communities. Greater understanding of biomolecular interactions alongside increased detection accuracy can be achieved using technology that can provide parallel information about multiple parameters of a single biomolecular process. For example, electro-optical techniques combine optical and electrochemical information to provide more accurate and detailed measurements that provide unique insights into molecular structure and function. Here, we present a comparison of the main methods for electro-optical biosensing, namely, electrochemical surface plasmon resonance (EC-SPR), electrochemical optical waveguide lightmode spectroscopy (EC-OWLS), and the recently reported silicon-based electrophotonic approach. The comparison considers different application spaces, such as the detection of low concentrations of biomolecules, integration, the tailoring of light-matter interaction for the understanding of biomolecular processes, and 2D imaging of biointeractions on a surface.

CHARMM additive and polarizable force fields for biophysics and computer-aided drug design.

PubMed

Vanommeslaeghe, K; MacKerell, A D

2015-05-01

Molecular Mechanics (MM) is the method of choice for computational studies of biomolecular systems owing to its modest computational cost, which makes it possible to routinely perform molecular dynamics (MD) simulations on chemical systems of biophysical and biomedical relevance. As one of the main factors limiting the accuracy of MD results is the empirical force field used, the present paper offers a review of recent developments in the CHARMM additive force field, one of the most popular biomolecular force fields. Additionally, we present a detailed discussion of the CHARMM Drude polarizable force field, anticipating a growth in the importance and utilization of polarizable force fields in the near future. Throughout the discussion emphasis is placed on the force fields' parametrization philosophy and methodology. Recent improvements in the CHARMM additive force field are mostly related to newly found weaknesses in the previous generation of additive force fields. Beyond the additive approximation is the newly available CHARMM Drude polarizable force field, which allows for MD simulations of up to 1μs on proteins, DNA, lipids and carbohydrates. Addressing the limitations ensures the reliability of the new CHARMM36 additive force field for the types of calculations that are presently coming into routine computational reach while the availability of the Drude polarizable force fields offers an inherently more accurate model of the underlying physical forces driving macromolecular structures and dynamics. This article is part of a Special Issue entitled "Recent developments of molecular dynamics". Copyright © 2014 Elsevier B.V. All rights reserved.

Tackling sampling challenges in biomolecular simulations.

PubMed

Barducci, Alessandro; Pfaendtner, Jim; Bonomi, Massimiliano

2015-01-01

Molecular dynamics (MD) simulations are a powerful tool to give an atomistic insight into the structure and dynamics of proteins. However, the time scales accessible in standard simulations, which often do not match those in which interesting biological processes occur, limit their predictive capabilities. Many advanced sampling techniques have been proposed over the years to overcome this limitation. This chapter focuses on metadynamics, a method based on the introduction of a time-dependent bias potential to accelerate sampling and recover equilibrium properties of a few descriptors that are able to capture the complexity of a process at a coarse-grained level. The theory of metadynamics and its combination with other popular sampling techniques such as the replica exchange method is briefly presented. Practical applications of these techniques to the study of the Trp-Cage miniprotein folding are also illustrated. The examples contain a guide for performing these calculations with PLUMED, a plugin to perform enhanced sampling simulations in combination with many popular MD codes.

Molecular dynamics simulations using temperature-enhanced essential dynamics replica exchange.

PubMed

Kubitzki, Marcus B; de Groot, Bert L

2007-06-15

Today's standard molecular dynamics simulations of moderately sized biomolecular systems at full atomic resolution are typically limited to the nanosecond timescale and therefore suffer from limited conformational sampling. Efficient ensemble-preserving algorithms like replica exchange (REX) may alleviate this problem somewhat but are still computationally prohibitive due to the large number of degrees of freedom involved. Aiming at increased sampling efficiency, we present a novel simulation method combining the ideas of essential dynamics and REX. Unlike standard REX, in each replica only a selection of essential collective modes of a subsystem of interest (essential subspace) is coupled to a higher temperature, with the remainder of the system staying at a reference temperature, T(0). This selective excitation along with the replica framework permits efficient approximate ensemble-preserving conformational sampling and allows much larger temperature differences between replicas, thereby considerably enhancing sampling efficiency. Ensemble properties and sampling performance of the method are discussed using dialanine and guanylin test systems, with multi-microsecond molecular dynamics simulations of these test systems serving as references.

Direct simulation of amphiphilic nanoparticle mediated membrane interactions

NASA Astrophysics Data System (ADS)

Tahir, Mukarram; Alexander-Katz, Alfredo

Membrane fusion is a critical step in the transport of biological cargo through membrane-bound compartments like vesicles. Membrane proteins that alleviate energy barriers for initial stalk formation and eventual rupture of the hemifusion intermediate during fusion generally assist this process. Gold nanoparticles functionalized with a combination of hydrophobic and hydrophilic alkanethiol ligands have recently been shown to induce membrane re-arrangements that are similar to those associated with these fusion proteins. In this work, we utilize molecular dynamics simulation to systematically design nanoparticles that exhibit targeted interactions with membranes. We introduce a method for rapidly parameterizing nanoparticle topology for the MARTINI biomolecular force field to permit long timescale simulation of their interactions with lipid bilayers. We leverage this model to investigate how ligand chemistry governs the nanoparticle's insertion efficacy and the perturbations it generates in the membrane environment. We further demonstrate through unbiased simulations that these nanoparticles can direct the fusion of lipid assemblies such as micelles and vesicles in a manner that mimics the function of biological fusion peptides and SNARE proteins.

Automatic Selection of Order Parameters in the Analysis of Large Scale Molecular Dynamics Simulations.

PubMed

Sultan, Mohammad M; Kiss, Gert; Shukla, Diwakar; Pande, Vijay S

2014-12-09

Given the large number of crystal structures and NMR ensembles that have been solved to date, classical molecular dynamics (MD) simulations have become powerful tools in the atomistic study of the kinetics and thermodynamics of biomolecular systems on ever increasing time scales. By virtue of the high-dimensional conformational state space that is explored, the interpretation of large-scale simulations faces difficulties not unlike those in the big data community. We address this challenge by introducing a method called clustering based feature selection (CB-FS) that employs a posterior analysis approach. It combines supervised machine learning (SML) and feature selection with Markov state models to automatically identify the relevant degrees of freedom that separate conformational states. We highlight the utility of the method in the evaluation of large-scale simulations and show that it can be used for the rapid and automated identification of relevant order parameters involved in the functional transitions of two exemplary cell-signaling proteins central to human disease states.

Supporting Representational Competence in High School Biology with Computer-Based Biomolecular Visualizations

ERIC Educational Resources Information Center

Wilder, Anna; Brinkerhoff, Jonathan

2007-01-01

This study assessed the effectiveness of computer-based biomolecular visualization activities on the development of high school biology students' representational competence as a means of understanding and visualizing protein structure/function relationships. Also assessed were students' attitudes toward these activities. Sixty-nine students…

iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D

PubMed Central

Liluashvili, Vaja; Kalayci, Selim; Fluder, Eugene; Wilson, Manda; Gabow, Aaron

2017-01-01

Abstract Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity. We present an open source software platform, interactome-CAVE (iCAVE), for visualizing large and complex biomolecular interaction networks in 3D. Users can explore networks (i) in 3D using a desktop, (ii) in stereoscopic 3D using 3D-vision glasses and a desktop, or (iii) in immersive 3D within a CAVE environment. iCAVE introduces 3D extensions of known 2D network layout, clustering, and edge-bundling algorithms, as well as new 3D network layout algorithms. Furthermore, users can simultaneously query several built-in databases within iCAVE for network generation or visualize their own networks (e.g., disease, drug, protein, metabolite). iCAVE has modular structure that allows rapid development by addition of algorithms, datasets, or features without affecting other parts of the code. Overall, iCAVE is the first freely available open source tool that enables 3D (optionally stereoscopic or immersive) visualizations of complex, dense, or multi-layered biomolecular networks. While primarily designed for researchers utilizing biomolecular networks, iCAVE can assist researchers in any field. PMID:28814063

iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D.

PubMed

Liluashvili, Vaja; Kalayci, Selim; Fluder, Eugene; Wilson, Manda; Gabow, Aaron; Gümüs, Zeynep H

2017-08-01

Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity. We present an open source software platform, interactome-CAVE (iCAVE), for visualizing large and complex biomolecular interaction networks in 3D. Users can explore networks (i) in 3D using a desktop, (ii) in stereoscopic 3D using 3D-vision glasses and a desktop, or (iii) in immersive 3D within a CAVE environment. iCAVE introduces 3D extensions of known 2D network layout, clustering, and edge-bundling algorithms, as well as new 3D network layout algorithms. Furthermore, users can simultaneously query several built-in databases within iCAVE for network generation or visualize their own networks (e.g., disease, drug, protein, metabolite). iCAVE has modular structure that allows rapid development by addition of algorithms, datasets, or features without affecting other parts of the code. Overall, iCAVE is the first freely available open source tool that enables 3D (optionally stereoscopic or immersive) visualizations of complex, dense, or multi-layered biomolecular networks. While primarily designed for researchers utilizing biomolecular networks, iCAVE can assist researchers in any field. © The Authors 2017. Published by Oxford University Press.

Electroporating Fields Target Oxidatively Damaged Areas in the Cell Membrane

PubMed Central

Vernier, P. Thomas; Levine, Zachary A.; Wu, Yu-Hsuan; Joubert, Vanessa; Ziegler, Matthew J.; Mir, Lluis M.; Tieleman, D. Peter

2009-01-01

Reversible electropermeabilization (electroporation) is widely used to facilitate the introduction of genetic material and pharmaceutical agents into living cells. Although considerable knowledge has been gained from the study of real and simulated model membranes in electric fields, efforts to optimize electroporation protocols are limited by a lack of detailed understanding of the molecular basis for the electropermeabilization of the complex biomolecular assembly that forms the plasma membrane. We show here, with results from both molecular dynamics simulations and experiments with living cells, that the oxidation of membrane components enhances the susceptibility of the membrane to electropermeabilization. Manipulation of the level of oxidative stress in cell suspensions and in tissues may lead to more efficient permeabilization procedures in the laboratory and in clinical applications such as electrochemotherapy and electrotransfection-mediated gene therapy. PMID:19956595

Nolan Wilson | NREL

Science.gov Websites

Nolan Wilson Nolan Wilson Postdoctoral Researcher-Chemical Engineering Nolan.Wilson@nrel.gov | 303 Ph.D., Chemical and Biomolecular Engineering, Clemson University, 2014 M.S., Chemical and Biomolecular Engineering, Clemson University, 2012 B.S., Chemical Engineering, Auburn University, 2007 Professional

A COMPUTATIONAL LIBRARY OF THE BIOMOLECULAR TARGETS FOR TOXICITY: RECEPTORS IN THE ENDOCRINE SYSTEM

EPA Science Inventory

A Computational Library of the Biomolecular Targets for Toxicity: Receptors in the Endocrine System

Authors: James R. Rabinowitz and Stephen B. Little, MTB/ECD/NHEERL/ORD, and Huajun Fan, Curriculum in Toxicology, University of North Carolina
Structure activity models ...

Student Learning about Biomolecular Self-Assembly Using Two Different External Representations

ERIC Educational Resources Information Center

Host, Gunnar E.; Larsson, Caroline; Olson, Arthur; Tibell, Lena A. E.

2013-01-01

Self-assembly is the fundamental but counterintuitive principle that explains how ordered biomolecular complexes form spontaneously in the cell. This study investigated the impact of using two external representations of virus self-assembly, an interactive tangible three-dimensional model and a static two-dimensional image, on student learning…

From classical to quantum and back: Hamiltonian adaptive resolution path integral, ring polymer, and centroid molecular dynamics

NASA Astrophysics Data System (ADS)

Kreis, Karsten; Kremer, Kurt; Potestio, Raffaello; Tuckerman, Mark E.

2017-12-01

Path integral-based methodologies play a crucial role for the investigation of nuclear quantum effects by means of computer simulations. However, these techniques are significantly more demanding than corresponding classical simulations. To reduce this numerical effort, we recently proposed a method, based on a rigorous Hamiltonian formulation, which restricts the quantum modeling to a small but relevant spatial region within a larger reservoir where particles are treated classically. In this work, we extend this idea and show how it can be implemented along with state-of-the-art path integral simulation techniques, including path-integral molecular dynamics, which allows for the calculation of quantum statistical properties, and ring-polymer and centroid molecular dynamics, which allow the calculation of approximate quantum dynamical properties. To this end, we derive a new integration algorithm that also makes use of multiple time-stepping. The scheme is validated via adaptive classical-path-integral simulations of liquid water. Potential applications of the proposed multiresolution method are diverse and include efficient quantum simulations of interfaces as well as complex biomolecular systems such as membranes and proteins.

Coarse-grained simulations of protein-protein association: an energy landscape perspective.

PubMed

Ravikumar, Krishnakumar M; Huang, Wei; Yang, Sichun

2012-08-22

Understanding protein-protein association is crucial in revealing the molecular basis of many biological processes. Here, we describe a theoretical simulation pipeline to study protein-protein association from an energy landscape perspective. First, a coarse-grained model is implemented and its applications are demonstrated via molecular dynamics simulations for several protein complexes. Second, an enhanced search method is used to efficiently sample a broad range of protein conformations. Third, multiple conformations are identified and clustered from simulation data and further projected on a three-dimensional globe specifying protein orientations and interacting energies. Results from several complexes indicate that the crystal-like conformation is favorable on the energy landscape even if the landscape is relatively rugged with metastable conformations. A closer examination on molecular forces shows that the formation of associated protein complexes can be primarily electrostatics-driven, hydrophobics-driven, or a combination of both in stabilizing specific binding interfaces. Taken together, these results suggest that the coarse-grained simulations and analyses provide an alternative toolset to study protein-protein association occurring in functional biomolecular complexes. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Magnetic levitation-based Martian and Lunar gravity simulator

NASA Technical Reports Server (NTRS)

Valles, J. M. Jr; Maris, H. J.; Seidel, G. M.; Tang, J.; Yao, W.

2005-01-01

Missions to Mars will subject living specimens to a range of low gravity environments. Deleterious biological effects of prolonged exposure to Martian gravity (0.38 g), Lunar gravity (0.17 g), and microgravity are expected, but the mechanisms involved and potential for remedies are unknown. We are proposing the development of a facility that provides a simulated Martian and Lunar gravity environment for experiments on biological systems in a well controlled laboratory setting. The magnetic adjustable gravity simulator will employ intense, inhomogeneous magnetic fields to exert magnetic body forces on a specimen that oppose the body force of gravity. By adjusting the magnetic field, it is possible to continuously adjust the total body force acting on a specimen. The simulator system considered consists of a superconducting solenoid with a room temperature bore sufficiently large to accommodate small whole organisms, cell cultures, and gravity sensitive bio-molecular solutions. It will have good optical access so that the organisms can be viewed in situ. This facility will be valuable for experimental observations and public demonstrations of systems in simulated reduced gravity. c2005 Published by Elsevier Ltd on behalf of COSPAR.

Coarse-Grained Simulations of Protein-Protein Association: An Energy Landscape Perspective

PubMed Central

Ravikumar, Krishnakumar M.; Huang, Wei; Yang, Sichun

2012-01-01

Understanding protein-protein association is crucial in revealing the molecular basis of many biological processes. Here, we describe a theoretical simulation pipeline to study protein-protein association from an energy landscape perspective. First, a coarse-grained model is implemented and its applications are demonstrated via molecular dynamics simulations for several protein complexes. Second, an enhanced search method is used to efficiently sample a broad range of protein conformations. Third, multiple conformations are identified and clustered from simulation data and further projected on a three-dimensional globe specifying protein orientations and interacting energies. Results from several complexes indicate that the crystal-like conformation is favorable on the energy landscape even if the landscape is relatively rugged with metastable conformations. A closer examination on molecular forces shows that the formation of associated protein complexes can be primarily electrostatics-driven, hydrophobics-driven, or a combination of both in stabilizing specific binding interfaces. Taken together, these results suggest that the coarse-grained simulations and analyses provide an alternative toolset to study protein-protein association occurring in functional biomolecular complexes. PMID:22947945

Magnetic levitation-based Martian and Lunar gravity simulator.

PubMed

Valles, J M; Maris, H J; Seidel, G M; Tang, J; Yao, W

2005-01-01

Missions to Mars will subject living specimens to a range of low gravity environments. Deleterious biological effects of prolonged exposure to Martian gravity (0.38 g), Lunar gravity (0.17 g), and microgravity are expected, but the mechanisms involved and potential for remedies are unknown. We are proposing the development of a facility that provides a simulated Martian and Lunar gravity environment for experiments on biological systems in a well controlled laboratory setting. The magnetic adjustable gravity simulator will employ intense, inhomogeneous magnetic fields to exert magnetic body forces on a specimen that oppose the body force of gravity. By adjusting the magnetic field, it is possible to continuously adjust the total body force acting on a specimen. The simulator system considered consists of a superconducting solenoid with a room temperature bore sufficiently large to accommodate small whole organisms, cell cultures, and gravity sensitive bio-molecular solutions. It will have good optical access so that the organisms can be viewed in situ. This facility will be valuable for experimental observations and public demonstrations of systems in simulated reduced gravity. c2005 Published by Elsevier Ltd on behalf of COSPAR.

Pressure effects on collective density fluctuations in water and protein solutions

PubMed Central

Russo, Daniela; Laloni, Alessio; Filabozzi, Alessandra; Heyden, Matthias

2017-01-01

Neutron Brillouin scattering and molecular dynamics simulations have been used to investigate protein hydration water density fluctuations as a function of pressure. Our results show significant differences between the pressure and density dependence of collective dynamics in bulk water and in concentrated protein solutions. Pressure-induced changes in the tetrahedral order of the water HB network have direct consequences for the high-frequency sound velocity and damping coefficients, which we find to be a sensitive probe for changes in the HB network structure as well as the wetting of biomolecular surfaces. PMID:29073065

Optical biosensors using surface plasmon resonance

NASA Astrophysics Data System (ADS)

Homola, Jiri; Brynda, Eduard; Tobiska, Petr; Tichy, Ivo; Skvor, Jiri

1999-12-01

We present a surface plasmon resonance sensor base on prism excitation of surface plasmons and spectral interrogation. For specific detection of biomolecular analytes, multilayers of monoclonal antibodies are immobilized on the surface of the sensor. Detection of biomolecular analytes such as human (beta) -2)-microglobulin, choriogonadotropin, hepatitis B surface antigen, salmonella enteritidis is demonstrated.

Dynamic and label-free high-throughput detection of biomolecular interactions based on phase-shift interferometry

NASA Astrophysics Data System (ADS)

Li, Qiang; Huang, Guoliang; Gan, Wupeng; Chen, Shengyi

2009-08-01

Biomolecular interactions can be detected by many established technologies such as fluorescence imaging, surface plasmon resonance (SPR)[1-4], interferometry and radioactive labeling of the analyte. In this study, we have designed and constructed a label-free, real-time sensing platform and its operating imaging instrument that detects interactions using optical phase differences from the accumulation of biological material on solid substrates. This system allows us to monitor biomolecular interactions in real time and quantify concentration changes during micro-mixing processes by measuring the changes of the optical path length (OPD). This simple interferometric technology monitors the optical phase difference resulting from accumulated biomolecular mass. A label-free protein chip that forms a 4×4 probe array was designed and fabricated using a commercial microarray robot spotter on solid substrates. Two positive control probe lines of BSA (Bovine Serum Albumin) and two experimental human IgG and goat IgG was used. The binding of multiple protein targets was performed and continuously detected by using this label-free and real-time sensing platform.

Retroactivity in the Context of Modularly Structured Biomolecular Systems

PubMed Central

Pantoja-Hernández, Libertad; Martínez-García, Juan Carlos

2015-01-01

Synthetic biology has intensively promoted the technical implementation of modular strategies in the fabrication of biological devices. Modules are considered as networks of reactions. The behavior displayed by biomolecular systems results from the information processes carried out by the interconnection of the involved modules. However, in natural systems, module wiring is not a free-of-charge process; as a consequence of interconnection, a reactive phenomenon called retroactivity emerges. This phenomenon is characterized by signals that propagate from downstream modules (the modules that receive the incoming signals upon interconnection) to upstream ones (the modules that send the signals upon interconnection). Such retroactivity signals, depending of their strength, may change and sometimes even disrupt the behavior of modular biomolecular systems. Thus, analysis of retroactivity effects in natural biological and biosynthetic systems is crucial to achieve a deeper understanding of how this interconnection between functionally characterized modules takes place and how it impacts the overall behavior of the involved cell. By discussing the modules interconnection in natural and synthetic biomolecular systems, we propose that such systems should be considered as quasi-modular. PMID:26137457

Bond Graph Modeling of Chemiosmotic Biomolecular Energy Transduction.

PubMed

Gawthrop, Peter J

2017-04-01

Engineering systems modeling and analysis based on the bond graph approach has been applied to biomolecular systems. In this context, the notion of a Faraday-equivalent chemical potential is introduced which allows chemical potential to be expressed in an analogous manner to electrical volts thus allowing engineering intuition to be applied to biomolecular systems. Redox reactions, and their representation by half-reactions, are key components of biological systems which involve both electrical and chemical domains. A bond graph interpretation of redox reactions is given which combines bond graphs with the Faraday-equivalent chemical potential. This approach is particularly relevant when the biomolecular system implements chemoelectrical transduction - for example chemiosmosis within the key metabolic pathway of mitochondria: oxidative phosphorylation. An alternative way of implementing computational modularity using bond graphs is introduced and used to give a physically based model of the mitochondrial electron transport chain To illustrate the overall approach, this model is analyzed using the Faraday-equivalent chemical potential approach and engineering intuition is used to guide affinity equalisation: a energy based analysis of the mitochondrial electron transport chain.

Exploiting Sub-threshold and above-threshold characteristics in a silver-enhanced gold nanoparticle based biochip.

PubMed

Liu, Yang; Alocilja, Evangelyn; Chakrabartty, Shantanu

2009-01-01

Silver-enhanced labeling is a technique used in immunochromatographic assays for improving the sensitivity of pathogen detection. In this paper, we employ the silver enhancement approach for constructing a biomolecular transistor that uses a high-density interdigitated electrode to detect rabbit IgG. We show that the response of the biomolecular transistor comprises of: (a) a sub-threshold region where the conductance change is an exponential function of the enhancement time and; (b) an above-threshold region where the conductance change is a linear function with respect to the enhancement time. By exploiting both these regions of operation, it is shown that the silver enhancing time is a reliable indicator of the IgG concentration. The method provides a relatively straightforward alternative to biomolecular signal amplification techniques. The measured results using a biochip prototype fabricated in silicon show that 240 pg/mL rabbit IgG can be detected at the silver enhancing time of 42 min. Also, the biomolecular transistor is compatible with silicon based processing making it ideal for designing integrated CMOS biosensors.

Construction of artificial cilia from microtubules and kinesins through a well-designed bottom-up approach.

PubMed

Sasaki, Ren; Kabir, Arif Md Rashedul; Inoue, Daisuke; Anan, Shizuka; Kimura, Atsushi P; Konagaya, Akihiko; Sada, Kazuki; Kakugo, Akira

2018-04-05

Self-organized structures of biomolecular motor systems, such as cilia and flagella, play key roles in the dynamic processes of living organisms, like locomotion or the transportation of materials. Although fabrication of such self-organized structures from reconstructed biomolecular motor systems has attracted much attention in recent years, a systematic construction methodology is still lacking. In this work, through a bottom-up approach, we fabricated artificial cilia from a reconstructed biomolecular motor system, microtubule/kinesin. The artificial cilia exhibited a beating motion upon the consumption, by the kinesins, of the chemical energy obtained from the hydrolysis of adenosine triphosphate (ATP). Several design parameters, such as the length of the microtubules, the density of the kinesins along the microtubules, the depletion force among the microtubules, etc., have been identified, which permit tuning of the beating frequency of the artificial cilia. The beating frequency of the artificial cilia increases upon increasing the length of the microtubules, but declines for the much longer microtubules. A high density of the kinesins along the microtubules is favorable for the beating motion of the cilia. The depletion force induced bundling of the microtubules accelerated the beating motion of the artificial cilia and increased the beating frequency. This work helps understand the role of self-assembled structures of the biomolecular motor systems in the dynamics of living organisms and is expected to expedite the development of artificial nanomachines, in which the biomolecular motors may serve as actuators.

Engineering fluid flow using sequenced microstructures

NASA Astrophysics Data System (ADS)

Amini, Hamed; Sollier, Elodie; Masaeli, Mahdokht; Xie, Yu; Ganapathysubramanian, Baskar; Stone, Howard A.; di Carlo, Dino

2013-05-01

Controlling the shape of fluid streams is important across scales: from industrial processing to control of biomolecular interactions. Previous approaches to control fluid streams have focused mainly on creating chaotic flows to enhance mixing. Here we develop an approach to apply order using sequences of fluid transformations rather than enhancing chaos. We investigate the inertial flow deformations around a library of single cylindrical pillars within a microfluidic channel and assemble these net fluid transformations to engineer fluid streams. As these transformations provide a deterministic mapping of fluid elements from upstream to downstream of a pillar, we can sequentially arrange pillars to apply the associated nested maps and, therefore, create complex fluid structures without additional numerical simulation. To show the range of capabilities, we present sequences that sculpt the cross-sectional shape of a stream into complex geometries, move and split a fluid stream, perform solution exchange and achieve particle separation. A general strategy to engineer fluid streams into a broad class of defined configurations in which the complexity of the nonlinear equations of fluid motion are abstracted from the user is a first step to programming streams of any desired shape, which would be useful for biological, chemical and materials automation.

Constructing Optimal Coarse-Grained Sites of Huge Biomolecules by Fluctuation Maximization.

PubMed

Li, Min; Zhang, John Zenghui; Xia, Fei

2016-04-12

Coarse-grained (CG) models are valuable tools for the study of functions of large biomolecules on large length and time scales. The definition of CG representations for huge biomolecules is always a formidable challenge. In this work, we propose a new method called fluctuation maximization coarse-graining (FM-CG) to construct the CG sites of biomolecules. The defined residual in FM-CG converges to a maximal value as the number of CG sites increases, allowing an optimal CG model to be rigorously defined on the basis of the maximum. More importantly, we developed a robust algorithm called stepwise local iterative optimization (SLIO) to accelerate the process of coarse-graining large biomolecules. By means of the efficient SLIO algorithm, the computational cost of coarse-graining large biomolecules is reduced to within the time scale of seconds, which is far lower than that of conventional simulated annealing. The coarse-graining of two huge systems, chaperonin GroEL and lengsin, indicates that our new methods can coarse-grain huge biomolecular systems with up to 10,000 residues within the time scale of minutes. The further parametrization of CG sites derived from FM-CG allows us to construct the corresponding CG models for studies of the functions of huge biomolecular systems.

DIFFUSED SOLUTE-SOLVENT INTERFACE WITH POISSON-BOLTZMANN ELECTROSTATICS: FREE-ENERGY VARIATION AND SHARP-INTERFACE LIMIT.

PubMed

Li, B O; Liu, Yuan

A phase-field free-energy functional for the solvation of charged molecules (e.g., proteins) in aqueous solvent (i.e., water or salted water) is constructed. The functional consists of the solute volumetric and solute-solvent interfacial energies, the solute-solvent van der Waals interaction energy, and the continuum electrostatic free energy described by the Poisson-Boltzmann theory. All these are expressed in terms of phase fields that, for low free-energy conformations, are close to one value in the solute phase and another in the solvent phase. A key property of the model is that the phase-field interpolation of dielectric coefficient has the vanishing derivative at both solute and solvent phases. The first variation of such an effective free-energy functional is derived. Matched asymptotic analysis is carried out for the resulting relaxation dynamics of the diffused solute-solvent interface. It is shown that the sharp-interface limit is exactly the variational implicit-solvent model that has successfully captured capillary evaporation in hydrophobic confinement and corresponding multiple equilibrium states of underlying biomolecular systems as found in experiment and molecular dynamics simulations. Our phase-field approach and analysis can be used to possibly couple the description of interfacial fluctuations for efficient numerical computations of biomolecular interactions.

Recipes for free energy calculations in biomolecular systems.

PubMed

Moradi, Mahmoud; Babin, Volodymyr; Sagui, Celeste; Roland, Christopher

2013-01-01

During the last decade, several methods for sampling phase space and calculating various free energies in biomolecular systems have been devised or refined for molecular dynamics (MD) simulations. Thus, state-of-the-art methodology and the ever increasing computer power allow calculations that were forbidden a decade ago. These calculations, however, are not trivial as they require knowledge of the methods, insight into the system under study, and, quite often, an artful combination of different methodologies in order to avoid the various traps inherent in an unknown free energy landscape. In this chapter, we illustrate some of these concepts with two relatively simple systems, a sugar ring and proline oligopeptides, whose free energy landscapes still offer considerable challenges. In order to explore the configurational space of these systems, and to surmount the various free energy barriers, we combine three complementary methods: a nonequilibrium umbrella sampling method (adaptively biased MD, or ABMD), replica-exchange molecular dynamics (REMD), and steered molecular dynamics (SMD). In particular, ABMD is used to compute the free energy surface of a set of collective variables; REMD is used to improve the performance of ABMD, to carry out sampling in space complementary to the collective variables, and to sample equilibrium configurations directly; and SMD is used to study different transition mechanisms.

Acceleration of Linear Finite-Difference Poisson-Boltzmann Methods on Graphics Processing Units.

PubMed

Qi, Ruxi; Botello-Smith, Wesley M; Luo, Ray

2017-07-11

Electrostatic interactions play crucial roles in biophysical processes such as protein folding and molecular recognition. Poisson-Boltzmann equation (PBE)-based models have emerged as widely used in modeling these important processes. Though great efforts have been put into developing efficient PBE numerical models, challenges still remain due to the high dimensionality of typical biomolecular systems. In this study, we implemented and analyzed commonly used linear PBE solvers for the ever-improving graphics processing units (GPU) for biomolecular simulations, including both standard and preconditioned conjugate gradient (CG) solvers with several alternative preconditioners. Our implementation utilizes the standard Nvidia CUDA libraries cuSPARSE, cuBLAS, and CUSP. Extensive tests show that good numerical accuracy can be achieved given that the single precision is often used for numerical applications on GPU platforms. The optimal GPU performance was observed with the Jacobi-preconditioned CG solver, with a significant speedup over standard CG solver on CPU in our diversified test cases. Our analysis further shows that different matrix storage formats also considerably affect the efficiency of different linear PBE solvers on GPU, with the diagonal format best suited for our standard finite-difference linear systems. Further efficiency may be possible with matrix-free operations and integrated grid stencil setup specifically tailored for the banded matrices in PBE-specific linear systems.

PREFACE: India-Japan Workshop on Biomolecular Electronics & Organic Nanotechnology for Environment Preservation

NASA Astrophysics Data System (ADS)

Onoda, Mitsuyoshi; Malhotra, Bansi D.

2012-04-01

The 'India-Japan Workshop on Biomolecular Electronics & Organic Nanotechnology for Environment Preservation' (IJWBME 2011) will be held on 7-10 December 2011 at EGRET Himeji, Himeji, Hyogo, Japan. This workshop was held for the first time on 17-19 December 2009 at NPL, New Delhi. Keeping in mind the importance of organic nanotechnology and biomolecular electronics for environmental preservation and their anticipated impact on the economics of both the developing and the developed world, IJWBME 2009 was jointly organized by the Department of Biological Functions, Graduate School of Life Sciences and Systems Engineering, the Kyushu Institute of Technology (KIT), Kitakyushu, Japan, and the Department of Science & Technology Centre on Biomolecular Electronics (DSTCBE), National Physical Laboratory (NPL). Much progress in the field of biomolecular electronics and organic nanotechnology for environmental preservation is expected for the 21st Century. Organic optoelectronic devices, such as organic electroluminescent devices, organic thin-film transistors, organic sensors, biological systems and so on have especially attracted much attention. The main purpose of this workshop is to provide an opportunity for researchers interested in biomolecular electronics and organic nanotechnology for environmental preservation, to come together in an informal and friendly atmosphere and exchange technical knowledge and experience. We are sure that this workshop will be very useful and fruitful for all participants in summarizing the recent progress in biomolecular electronics and organic nanotechnology for environmental preservation and preparing new ground for the next generation. Many papers have been submitted from India and Japan and more than 30 papers have been accepted for presentation. The main topics of interest are as follows: Bioelectronics Biomolecular Electronics Fabrication Techniques Self-assembled Monolayers Nano-sensors Environmental Monitoring Organic Devices Organic Functional Materials We would like to express our sincere thanks to the organizing committee members of this workshop and the many organizations such as the Japan Society for the Promotion of Science (JSPS), Japan, the Department of Science & Technology (DST), India, the Society of Organic Nanometric Interfacial Controlled Electronic (NICE) Devices, the Japan Society of Applied Physics, Himeji City, Himeji Convention & Visitors Bureau, Delhi Technological University, Delhi, India and the University of Hyogo for their financial support. Thanks are also given to The Japan Society of Applied Physics, Division of Molecular Electronics and Bioelectronics, The Japan Society of Applied Physics (M & BE), the Technical Committee on Dielectric and Electrical Insulation Materials of the Institute of Electrical Engineering in Japan (IEEJ), the Technical Group on Organic Molecular Electronics, Electronics Society of the Institute of Electronics, Information and Communication Engineers (IEICE), and the IEEE Dielectrics and Electrical Insulation Society, Japan Chapter, for their cooperation. Finally, we hope that the many young and active researchers who are participating will enjoy stimulating discussions and exchange ideas with each other at IJWBME 2011, Himeji, Japan. 7 April 2011 IJWBME 2011 Chairs Mitsuyoshi Onoda Graduate School of Engineering, University of Hyogo, Himeji, Japan Bansi D Malhotra Department of Biotechnology, Delhi Technological University, Delhi, India Conference photograph Participants of the India-Japan Workshop on Biomolecular Electronics & Organic Nanotechnology for Environment Preservation 2011, December 7-10 2011, EGRET Himeji, Japan The PDF also contains a list of sponsors.

Engineering self-contained DNA circuit for proximity recognition and localized signal amplification of target biomolecules

PubMed Central

Ang, Yan Shan; Yung, Lin-Yue Lanry

2014-01-01

Biomolecular interactions have important cellular implications, however, a simple method for the sensing of such proximal events is lacking in the current molecular toolbox. We designed a dynamic DNA circuit capable of recognizing targets in close proximity to initiate a pre-programmed signal transduction process resulting in localized signal amplification. The entire circuit was engineered to be self-contained, i.e. it can self-assemble onto individual target molecules autonomously and form localized signal with minimal cross-talk. α-thrombin was used as a model protein to evaluate the performance of the individual modules and the overall circuit for proximity interaction under physiologically relevant buffer condition. The circuit achieved good selectivity in presence of non-specific protein and interfering serum matrix and successfully detected for physiologically relevant α-thrombin concentration (50 nM–5 μM) in a single mixing step without any further washing. The formation of localized signal at the interaction site can be enhanced kinetically through the control of temperature and probe concentration. This work provides a basic general framework from which other circuit modules can be adapted for the sensing of other biomolecular or cellular interaction of interest. PMID:25056307

New solution decomposition and minimization schemes for Poisson-Boltzmann equation in calculation of biomolecular electrostatics

NASA Astrophysics Data System (ADS)

Xie, Dexuan

2014-10-01

The Poisson-Boltzmann equation (PBE) is one widely-used implicit solvent continuum model in the calculation of electrostatic potential energy for biomolecules in ionic solvent, but its numerical solution remains a challenge due to its strong singularity and nonlinearity caused by its singular distribution source terms and exponential nonlinear terms. To effectively deal with such a challenge, in this paper, new solution decomposition and minimization schemes are proposed, together with a new PBE analysis on solution existence and uniqueness. Moreover, a PBE finite element program package is developed in Python based on the FEniCS program library and GAMer, a molecular surface and volumetric mesh generation program package. Numerical tests on proteins and a nonlinear Born ball model with an analytical solution validate the new solution decomposition and minimization schemes, and demonstrate the effectiveness and efficiency of the new PBE finite element program package.

Lattice-free prediction of three-dimensional structure of programmed DNA assemblies

PubMed Central

Pan, Keyao; Kim, Do-Nyun; Zhang, Fei; Adendorff, Matthew R.; Yan, Hao; Bathe, Mark

2014-01-01

DNA can be programmed to self-assemble into high molecular weight 3D assemblies with precise nanometer-scale structural features. Although numerous sequence design strategies exist to realize these assemblies in solution, there is currently no computational framework to predict their 3D structures on the basis of programmed underlying multi-way junction topologies constrained by DNA duplexes. Here, we introduce such an approach and apply it to assemblies designed using the canonical immobile four-way junction. The procedure is used to predict the 3D structure of high molecular weight planar and spherical ring-like origami objects, a tile-based sheet-like ribbon, and a 3D crystalline tensegrity motif, in quantitative agreement with experiments. Our framework provides a new approach to predict programmed nucleic acid 3D structure on the basis of prescribed secondary structure motifs, with possible application to the design of such assemblies for use in biomolecular and materials science. PMID:25470497

Investigation of the Human Disease Osteogenesis Imperfecta: A Research-Based Introduction to Concepts and Skills in Biomolecular Analysis

ERIC Educational Resources Information Center

Mate, Karen; Sim, Alistair; Weidenhofer, Judith; Milward, Liz; Scott, Judith

2013-01-01

A blended approach encompassing problem-based learning (PBL) and structured inquiry was used in this laboratory exercise based on the congenital disease Osteogenesis imperfecta (OI), to introduce commonly used techniques in biomolecular analysis within a clinical context. During a series of PBL sessions students were presented with several…

Detection of biomolecular interaction between biotin and streptavidin on a self-assembled monolayer using magnetic nanoparticles.

PubMed

Arakaki, Atsushi; Hideshima, Sho; Nakagawa, Takahito; Niwa, Daisuke; Tanaka, Tsuyoshi; Matsunaga, Tadashi; Osaka, Tetsuya

2004-11-20

For developing a magnetic bioassay system, an investigation to determine the presence of a specific biomolecular interaction between biotin and streptavidin was done using magnetic nanoparticles and a silicon substrate with a self-assembled monolayer. Streptavidin was immobilized on the magnetic particles, and biotin was attached to the monolayer-modified substrate. The reaction of streptavidin-modified magnetic particles on the biotin-modified substrate was clearly observed under an optical microscope. The magnetic signals from the particles were detected using a magnetic force microscope. The results of this study demonstrate that the combination of a monolayer-modified substrate with biomolecule-modified magnetic particles is useful for detecting biomolecular interactions in medical and diagnostic analyses. (c) 2004 Wiley Periodicals, Inc

Biomolecular conformational changes and ligand binding: from kinetics to thermodynamics† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc01627a

PubMed Central

Wang, Yong; Martins, João Miguel

2017-01-01

The behaviour of biomolecular systems is governed by their thermodynamic and kinetic properties. It is thus important to be able to calculate, for example, both the affinity and rate of binding and dissociation of a protein–ligand complex, or the populations and exchange rates between distinct conformational states. Because these are typically rare events, calculating these properties from long molecular dynamics simulations remains extremely difficult. Instead, one often adopts a divide-and-conquer strategy in which equilibrium free-energy differences and the fastest state-to-state transition (e.g. ligand association or minor-to-major state conversion) are combined to estimate the slow rate (e.g. ligand dissociation) using a two-state assumption. Here we instead address these problems by using a previously developed method to calculate both the forward and backward rates directly from simulations. We then estimate the thermodynamics from the rates, and validate these values by independent means. We applied the approach to three systems of increasing complexity, including the association and dissociation of benzene to a fully buried cavity inside the L99A mutant variant of T4 lysozyme. In particular, we were able to determine both millisecond association and dissociation rates, and the affinity, of the protein–ligand system by directly observing dozens of rare events in atomic detail. Our approach both sheds light on the precision of methods for calculating kinetics and further provides a generally useful test for the internal consistency of kinetics and thermodynamics. We also expect our route to be useful for obtaining both the kinetics and thermodynamics at the same time in more challenging cases. PMID:29619200

Molecular simulation insights on the in vacuo adsorption of amino acids on graphene oxide surfaces with varying surface oxygen densities

NASA Astrophysics Data System (ADS)

Rahmani, Farzin; Nouranian, Sasan; Mahdavi, Mina; Al-Ostaz, Ahmed

2016-11-01

In this fundamental study, a series of molecular dynamics simulations were performed in vacuo to investigate the energetics and select geometries of 20 standard amino acids (AAs) on pristine graphene (PG) and graphene oxide (GO) surfaces as a function of graphene surface oxygen density. These interactions are of key interest to graphene/biomolecular systems. Our results indicate that aromatic AAs exhibit the strongest total interactions with the PG surfaces due to π-π stacking. Tryptophan (Trp) has the highest aromaticity due to its indole side chain and, hence, has the strongest interaction among all AAs (-16.66 kcal/mol). Aliphatic, polar, and charged AAs show various levels of affinity to the PG sheets depending on the strength of their side chain hydrophobic interactions. For example, arginine (Arg) with its guanidinium side chain exhibits the strongest interaction with the PG sheets (-13.81 kcal/mol) following aromatic AAs. Also, glycine (Gly; a polar AA) has the weakest interaction with the PG sheets (-7.29 kcal/mol). When oxygen-containing functional groups are added to the graphene sheets, the π-π stacking in aromatic AAs becomes disrupted and perfect parallelism of the aromatic rings is lost. Moreover, hydrogen bonding and/or electrostatic interactions become more pronounced. Charged AAs exhibit the strongest interactions with the GO surfaces. In general, the AA-GO interactions increase with increasing surface oxygen density, and the effect is more pronounced at higher O/C ratios. This study provides a quantitative measure of AA-graphene interactions for the design and tuning of biomolecular systems suitable for biosensing, drug delivery, and gene delivery applications.

EMISSIONS FROM COMBUSTION OF POST-CONSUMER ...

EPA Pesticide Factsheets

Symposium Paper The Portland cement industry is interested in the utilization of post-consumer carpet as a fuel to replace a portion of its traditional fuels. In response to this interest, the Carpet and Rug Institute, US Department of Energy, Georgia Institute of Technology School of Chemical and Biomolecular Engineering, US Environmental Protection Agency, Lehigh Cement Company, and the American Society of Mechanical Engineers Research Committee on Industrial and Municipal Waste are performing a collaborative program to assess the feasibility of using cement kilns for the destruction of post-consumer carpet.

Biomolecularmodeling and simulation: a field coming of age

PubMed Central

Schlick, Tamar; Collepardo-Guevara, Rosana; Halvorsen, Leif Arthur; Jung, Segun; Xiao, Xia

2013-01-01

We assess the progress in biomolecular modeling and simulation, focusing on structure prediction and dynamics, by presenting the field’s history, metrics for its rise in popularity, early expressed expectations, and current significant applications. The increases in computational power combined with improvements in algorithms and force fields have led to considerable success, especially in protein folding, specificity of ligand/biomolecule interactions, and interpretation of complex experimental phenomena (e.g. NMR relaxation, protein-folding kinetics and multiple conformational states) through the generation of structural hypotheses and pathway mechanisms. Although far from a general automated tool, structure prediction is notable for proteins and RNA that preceded the experiment, especially by knowledge-based approaches. Thus, despite early unrealistic expectations and the realization that computer technology alone will not quickly bridge the gap between experimental and theoretical time frames, ongoing improvements to enhance the accuracy and scope of modeling and simulation are propelling the field onto a productive trajectory to become full partner with experiment and a field on its own right. PMID:21226976

MDTraj: A Modern Open Library for the Analysis of Molecular Dynamics Trajectories.

PubMed

McGibbon, Robert T; Beauchamp, Kyle A; Harrigan, Matthew P; Klein, Christoph; Swails, Jason M; Hernández, Carlos X; Schwantes, Christian R; Wang, Lee-Ping; Lane, Thomas J; Pande, Vijay S

2015-10-20

As molecular dynamics (MD) simulations continue to evolve into powerful computational tools for studying complex biomolecular systems, the necessity of flexible and easy-to-use software tools for the analysis of these simulations is growing. We have developed MDTraj, a modern, lightweight, and fast software package for analyzing MD simulations. MDTraj reads and writes trajectory data in a wide variety of commonly used formats. It provides a large number of trajectory analysis capabilities including minimal root-mean-square-deviation calculations, secondary structure assignment, and the extraction of common order parameters. The package has a strong focus on interoperability with the wider scientific Python ecosystem, bridging the gap between MD data and the rapidly growing collection of industry-standard statistical analysis and visualization tools in Python. MDTraj is a powerful and user-friendly software package that simplifies the analysis of MD data and connects these datasets with the modern interactive data science software ecosystem in Python. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fath, L., E-mail: lukas.fath@kit.edu; Hochbruck, M., E-mail: marlis.hochbruck@kit.edu; Singh, C.V., E-mail: chandraveer.singh@utoronto.ca

Classical integration methods for molecular dynamics are inherently limited due to resonance phenomena occurring at certain time-step sizes. The mollified impulse method can partially avoid this problem by using appropriate filters based on averaging or projection techniques. However, existing filters are computationally expensive and tedious in implementation since they require either analytical Hessians or they need to solve nonlinear systems from constraints. In this work we follow a different approach based on corotation for the construction of a new filter for (flexible) biomolecular simulations. The main advantages of the proposed filter are its excellent stability properties and ease of implementationmore » in standard softwares without Hessians or solving constraint systems. By simulating multiple realistic examples such as peptide, protein, ice equilibrium and ice–ice friction, the new filter is shown to speed up the computations of long-range interactions by approximately 20%. The proposed filtered integrators allow step sizes as large as 10 fs while keeping the energy drift less than 1% on a 50 ps simulation.« less

Protein dynamics and enzyme catalysis: insights from simulations.

PubMed

McGeagh, John D; Ranaghan, Kara E; Mulholland, Adrian J

2011-08-01

The role of protein dynamics in enzyme catalysis is one of the most active and controversial areas in enzymology today. Some researchers claim that protein dynamics are at the heart of enzyme catalytic efficiency, while others state that dynamics make no significant contribution to catalysis. What is the biochemist - or student - to make of the ferocious arguments in this area? Protein dynamics are complex and fascinating, as molecular dynamics simulations and experiments have shown. The essential question is: do these complex motions have functional significance? In particular, how do they affect or relate to chemical reactions within enzymes, and how are chemical and conformational changes coupled together? Biomolecular simulations can analyse enzyme reactions and dynamics in atomic detail, beyond that achievable in experiments: accurate atomistic modelling has an essential part to play in clarifying these issues. This article is part of a Special Issue entitled: Protein Dynamics: Experimental and Computational Approaches. Copyright © 2010 Elsevier B.V. All rights reserved.

MDTraj: A Modern Open Library for the Analysis of Molecular Dynamics Trajectories

PubMed Central

McGibbon, Robert T.; Beauchamp, Kyle A.; Harrigan, Matthew P.; Klein, Christoph; Swails, Jason M.; Hernández, Carlos X.; Schwantes, Christian R.; Wang, Lee-Ping; Lane, Thomas J.; Pande, Vijay S.

2015-01-01

As molecular dynamics (MD) simulations continue to evolve into powerful computational tools for studying complex biomolecular systems, the necessity of flexible and easy-to-use software tools for the analysis of these simulations is growing. We have developed MDTraj, a modern, lightweight, and fast software package for analyzing MD simulations. MDTraj reads and writes trajectory data in a wide variety of commonly used formats. It provides a large number of trajectory analysis capabilities including minimal root-mean-square-deviation calculations, secondary structure assignment, and the extraction of common order parameters. The package has a strong focus on interoperability with the wider scientific Python ecosystem, bridging the gap between MD data and the rapidly growing collection of industry-standard statistical analysis and visualization tools in Python. MDTraj is a powerful and user-friendly software package that simplifies the analysis of MD data and connects these datasets with the modern interactive data science software ecosystem in Python. PMID:26488642

Extended Phase-Space Methods for Enhanced Sampling in Molecular Simulations: A Review.

PubMed

Fujisaki, Hiroshi; Moritsugu, Kei; Matsunaga, Yasuhiro; Morishita, Tetsuya; Maragliano, Luca

2015-01-01

Molecular Dynamics simulations are a powerful approach to study biomolecular conformational changes or protein-ligand, protein-protein, and protein-DNA/RNA interactions. Straightforward applications, however, are often hampered by incomplete sampling, since in a typical simulated trajectory the system will spend most of its time trapped by high energy barriers in restricted regions of the configuration space. Over the years, several techniques have been designed to overcome this problem and enhance space sampling. Here, we review a class of methods that rely on the idea of extending the set of dynamical variables of the system by adding extra ones associated to functions describing the process under study. In particular, we illustrate the Temperature Accelerated Molecular Dynamics (TAMD), Logarithmic Mean Force Dynamics (LogMFD), and Multiscale Enhanced Sampling (MSES) algorithms. We also discuss combinations with techniques for searching reaction paths. We show the advantages presented by this approach and how it allows to quickly sample important regions of the free-energy landscape via automatic exploration.

Scaling of Multimillion-Atom Biological Molecular Dynamics Simulation on a Petascale Supercomputer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schulz, Roland; Lindner, Benjamin; Petridis, Loukas

2009-01-01

A strategy is described for a fast all-atom molecular dynamics simulation of multimillion-atom biological systems on massively parallel supercomputers. The strategy is developed using benchmark systems of particular interest to bioenergy research, comprising models of cellulose and lignocellulosic biomass in an aqueous solution. The approach involves using the reaction field (RF) method for the computation of long-range electrostatic interactions, which permits efficient scaling on many thousands of cores. Although the range of applicability of the RF method for biomolecular systems remains to be demonstrated, for the benchmark systems the use of the RF produces molecular dipole moments, Kirkwood G factors,more » other structural properties, and mean-square fluctuations in excellent agreement with those obtained with the commonly used Particle Mesh Ewald method. With RF, three million- and five million atom biological systems scale well up to 30k cores, producing 30 ns/day. Atomistic simulations of very large systems for time scales approaching the microsecond would, therefore, appear now to be within reach.« less

Scaling of Multimillion-Atom Biological Molecular Dynamics Simulation on a Petascale Supercomputer.

PubMed

Schulz, Roland; Lindner, Benjamin; Petridis, Loukas; Smith, Jeremy C

2009-10-13

A strategy is described for a fast all-atom molecular dynamics simulation of multimillion-atom biological systems on massively parallel supercomputers. The strategy is developed using benchmark systems of particular interest to bioenergy research, comprising models of cellulose and lignocellulosic biomass in an aqueous solution. The approach involves using the reaction field (RF) method for the computation of long-range electrostatic interactions, which permits efficient scaling on many thousands of cores. Although the range of applicability of the RF method for biomolecular systems remains to be demonstrated, for the benchmark systems the use of the RF produces molecular dipole moments, Kirkwood G factors, other structural properties, and mean-square fluctuations in excellent agreement with those obtained with the commonly used Particle Mesh Ewald method. With RF, three million- and five million-atom biological systems scale well up to ∼30k cores, producing ∼30 ns/day. Atomistic simulations of very large systems for time scales approaching the microsecond would, therefore, appear now to be within reach.

Pattern Discovery in Biomolecular Data – Tools, Techniques, and Applications | Center for Cancer Research

Cancer.gov

Finding patterns in biomolecular data, particularly in DNA and RNA, is at the center of modern biological research. These data are complex and growing rapidly, so the search for patterns requires increasingly sophisticated computer methods. This book provides a summary of principal techniques. Each chapter describes techniques that are drawn from many fields, including graph

A consistent S-Adenosylmethionine force field improved by dynamic Hirshfeld-I atomic charges for biomolecular simulation

NASA Astrophysics Data System (ADS)

Saez, David Adrian; Vöhringer-Martinez, Esteban

2015-10-01

S-Adenosylmethionine (AdoMet) is involved in many biological processes as cofactor in enzymes transferring its sulfonium methyl group to various substrates. Additionally, it is used as drug and nutritional supplement to reduce the pain in osteoarthritis and against depression. Due to the biological relevance of AdoMet it has been part of various computational simulation studies and will also be in the future. However, to our knowledge no rigorous force field parameter development for its simulation in biological systems has been reported. Here, we use electronic structure calculations combined with molecular dynamics simulations in explicit solvent to develop force field parameters compatible with the AMBER99 force field. Additionally, we propose new dynamic Hirshfeld-I atomic charges which are derived from the polarized electron density of AdoMet in aqueous solution to describe its electrostatic interactions in biological systems. The validation of the force field parameters and the atomic charges is performed against experimental interproton NOE distances of AdoMet in aqueous solution and crystal structures of AdoMet in the cavity of three representative proteins.

Fixed-Charge Atomistic Force Fields for Molecular Dynamics Simulations in the Condensed Phase: An Overview.

PubMed

Riniker, Sereina

2018-03-26

In molecular dynamics or Monte Carlo simulations, the interactions between the particles (atoms) in the system are described by a so-called force field. The empirical functional form of classical fixed-charge force fields dates back to 1969 and remains essentially unchanged. In a fixed-charge force field, the polarization is not modeled explicitly, i.e. the effective partial charges do not change depending on conformation and environment. This simplification allows, however, a dramatic reduction in computational cost compared to polarizable force fields and in particular quantum-chemical modeling. The past decades have shown that simulations employing carefully parametrized fixed-charge force fields can provide useful insights into biological and chemical questions. This overview focuses on the four major force-field families, i.e. AMBER, CHARMM, GROMOS, and OPLS, which are based on the same classical functional form and are continuously improved to the present day. The overview is aimed at readers entering the field of (bio)molecular simulations. More experienced users may find the comparison and historical development of the force-field families interesting.

Aligning Biomolecular Networks Using Modular Graph Kernels

NASA Astrophysics Data System (ADS)

Towfic, Fadi; Greenlee, M. Heather West; Honavar, Vasant

Comparative analysis of biomolecular networks constructed using measurements from different conditions, tissues, and organisms offer a powerful approach to understanding the structure, function, dynamics, and evolution of complex biological systems. We explore a class of algorithms for aligning large biomolecular networks by breaking down such networks into subgraphs and computing the alignment of the networks based on the alignment of their subgraphs. The resulting subnetworks are compared using graph kernels as scoring functions. We provide implementations of the resulting algorithms as part of BiNA, an open source biomolecular network alignment toolkit. Our experiments using Drosophila melanogaster, Saccharomyces cerevisiae, Mus musculus and Homo sapiens protein-protein interaction networks extracted from the DIP repository of protein-protein interaction data demonstrate that the performance of the proposed algorithms (as measured by % GO term enrichment of subnetworks identified by the alignment) is competitive with some of the state-of-the-art algorithms for pair-wise alignment of large protein-protein interaction networks. Our results also show that the inter-species similarity scores computed based on graph kernels can be used to cluster the species into a species tree that is consistent with the known phylogenetic relationships among the species.

A new strategy for imaging biomolecular events through interactions between liquid crystals and oil-in-water emulsions.

PubMed

Hu, Qiong-Zheng; Jang, Chang-Hyun

2012-11-21

In this study, we demonstrate a new strategy to image biomolecular events through interactions between liquid crystals (LCs) and oil-in-water emulsions. The optical response had a dark appearance when a nematic LC, 4-cyano-4'-pentylbiphenyl (5CB), is in contact with emulsion droplets of glyceryl trioleate (GT). In contrast, the optical response had a bright appearance when 5CB is in contact with GT emulsions decorated with surfactants such as sodium oleate. Since lipase can hydrolyze GT and produce oleic acid, the optical response also displays a bright appearance after 5CB has been in contact with a mixture of lipase and GT emulsions. These results indicate the feasibility of monitoring biomolecular events through interactions between LCs and oil-in-water emulsions.

Programmable ion-sensitive transistor interfaces. II. Biomolecular sensing and manipulation.

PubMed

Jayant, Krishna; Auluck, Kshitij; Funke, Mary; Anwar, Sharlin; Phelps, Joshua B; Gordon, Philip H; Rajwade, Shantanu R; Kan, Edwin C

2013-07-01

The chemoreceptive neuron metal-oxide-semiconductor transistor described in the preceding paper is further used to monitor the adsorption and interaction of DNA molecules and subsequently manipulate the adsorbed biomolecules with injected static charge. Adsorption of DNA molecules onto poly-L-lysine-coated sensing gates (SGs) modulates the floating gate (FG) potential ψ(O), which is reflected as a threshold voltage shift measured from the control gate (CG) V(th_CG). The asymmetric capacitive coupling between the CG and SG to the FG results in V(th_CG) amplification. The electric field in the SG oxide E(SG_ox) is fundamentally different when we drive the current readout with V(CG) and V(ref) (i.e., the potential applied to the CG and reference electrode, respectively). The V(CG)-driven readout induces a larger E(SG_ox), leading to a larger V(th_CG) shift when DNA is present. Simulation studies indicate that the counterion screening within the DNA membrane is responsible for this effect. The DNA manipulation mechanism is enabled by tunneling electrons (program) or holes (erase) onto FGs to produce repulsive or attractive forces. Programming leads to repulsion and eventual desorption of DNA, while erasing reestablishes adsorption. We further show that injected holes or electrons prior to DNA addition either aids or disrupts the immobilization process, which can be used for addressable sensor interfaces. To further substantiate DNA manipulation, we used impedance spectroscopy with a split ac-dc technique to reveal the net interface impedance before and after charge injection.

Efficient Monte Carlo Methods for Biomolecular Simulations.

NASA Astrophysics Data System (ADS)

Bouzida, Djamal

A new approach to efficient Monte Carlo simulations of biological molecules is presented. By relaxing the usual restriction to Markov processes, we are able to optimize performance while dealing directly with the inhomogeneity and anisotropy inherent in these systems. The advantage of this approach is that we can introduce a wide variety of Monte Carlo moves to deal with complicated motions of the molecule, while maintaining full optimization at every step. This enables the use of a variety of collective rotational moves that relax long-wavelength modes. We were able to show by explicit simulations that the resulting algorithms substantially increase the speed of the simulation while reproducing the correct equilibrium behavior. This approach is particularly intended for simulations of macromolecules, although we expect it to be useful in other situations. The dynamic optimization of the new Monte Carlo methods makes them very suitable for simulated annealing experiments on all systems whose state space is continuous in general, and to the protein folding problem in particular. We introduce an efficient annealing schedule using preferential bias moves. Our simulated annealing experiments yield structures whose free energies were lower than the equilibrated X-ray structure, which leads us to believe that the empirical energy function used does not fully represent the interatomic interactions. Furthermore, we believe that the largest discrepancies involve the solvent effects in particular.

Combining Ion Mobility and Cryogenic Spectroscopy for Structural and Analytical Studies of Biomolecular Ions.

PubMed

Kamrath, Michael Z; Rizzo, Thomas R

2018-05-10

Ion mobility spectrometry (IMS) has become a valuable tool in biophysical and bioanalytical chemistry because of its ability to separate and characterize the structure of gas-phase biomolecular ions on the basis of their collisional cross section (CCS). Its importance has grown with the realization that in many cases, biomolecular ions retain important structural characteristics when produced in the gas phase by electrospray ionization (ESI). While a CCS can help distinguish between structures of radically different types, one cannot expect a single number to differentiate similar conformations of a complex molecule. Molecular spectroscopy has also played an increasingly important role for structural characterization of biomolecular ions. Spectroscopic measurements, particularly when performed at cryogenic temperatures, can be extremely sensitive to small changes in a molecule's conformation and provide tight constraints for calculations of biomolecular structures. However, spectra of complex molecules can be heavily congested due to the presence of multiple stable conformations, each of which can have a distinct spectrum. This congestion can inhibit spectral analysis and complicate the extraction of structural information. Even when a single conformation is present, the conformational search process needed to match a measured spectrum with a computed structure can be overwhelming for peptides of more than a few amino acids, for example. We have recently combined ion mobility spectrometry and cryogenic ion spectroscopy (CIS) to characterize the structures of gas-phase biomolecular ions. In this Account, we illustrate how the coupling of IMS and CIS is by nature synergistic. On the one hand, IMS can be used as a conformational filter to reduce spectral congestion that arises from heterogeneous samples, facilitating structural analysis. On the other hand, highly resolved, cryogenic spectra can serve as a selective detector for IMS that can increase the effective resolution and hence the maximum number of distinct species that can be detected. Taken together, spectra and CCS measurements on the same system facilitates structural analysis and strengthens the conclusions that can be drawn from each type of data. After describing different approaches to combining these two techniques in such a way as to simplify the data obtained from each one separately, we present two examples that illustrate the type of insight gained from using spectra and CCS data together for characterizing gas-phase biomolecular ions. In one example, the CCS is used as a constraint for quantum chemical structure calculations of kinetically trapped species, where a lowest-energy criterion is not applicable. In a second example, we use both the CCS and a cryogenic infrared spectrum as a means to distinguish isomeric glycans.

Free energy calculation of single molecular interaction using Jarzynski's identity method: the case of HIV-1 protease inhibitor system

NASA Astrophysics Data System (ADS)

Li, De-Chang; Ji, Bao-Hua

2012-06-01

Jarzynski' identity (JI) method was suggested a promising tool for reconstructing free energy landscape of biomolecular interactions in numerical simulations and experiments. However, JI method has not yet been well tested in complex systems such as ligand-receptor molecular pairs. In this paper, we applied a huge number of steered molecular dynamics (SMD) simulations to dissociate the protease of human immunodeficiency type I virus (HIV-1 protease) and its inhibitors. We showed that because of intrinsic complexity of the ligand-receptor system, the energy barrier predicted by JI method at high pulling rates is much higher than experimental results. However, with a slower pulling rate and fewer switch times of simulations, the predictions of JI method can approach to the experiments. These results suggested that the JI method is more appropriate for reconstructing free energy landscape using the data taken from experiments, since the pulling rates used in experiments are often much slower than those in SMD simulations. Furthermore, we showed that a higher loading stiffness can produce higher precision of calculation of energy landscape because it yields a lower mean value and narrower bandwidth of work distribution in SMD simulations.

Chemical Frustration in the Protein Folding Landscape: Grand Canonical Ensemble Simulations of Cytochrome c

PubMed Central

Weinkam, Patrick; Romesberg, Floyd E.; Wolynes, Peter G.

2010-01-01

A grand canonical formalism is developed to combine discrete simulations for chemically distinct species in equilibrium. Each simulation is based on a perturbed funneled landscape. The formalism is illustrated using the alkaline-induced transitions of cytochrome c as observed by FTIR spectroscopy and with various other experimental approaches. The grand canonical simulation method accounts for the acid/base chemistry of deprotonation, the inorganic chemistry of heme ligation and misligation, and the minimally frustrated folding energy landscape, thus elucidating the physics of protein folding involved with an acid/base titration of a protein. The formalism combines simulations for each of the relevant chemical species, varying by protonation and ligation states. In contrast to models based on perfectly funneled energy landscapes that contain only contacts found in the native structure, the current study introduces “chemical frustration” from deprotonation and misligation that gives rise to many intermediates at alkaline pH. While the nature of these intermediates cannot be easily inferred from available experimental data, the current study provides specific structural details of these intermediates thus extending our understanding of how cytochrome c changes with increasing pH. The results demonstrate the importance of chemical frustration for understanding biomolecular energy landscapes. PMID:19199810

Molecular Dynamics Simulation of Tau Peptides for the Investigation of Conformational Changes Induced by Specific Phosphorylation Patterns.

PubMed

Gandhi, Neha S; Kukic, Predrag; Lippens, Guy; Mancera, Ricardo L

2017-01-01

The Tau protein plays an important role due to its biomolecular interactions in neurodegenerative diseases. The lack of stable structure and various posttranslational modifications such as phosphorylation at various sites in the Tau protein pose a challenge for many experimental methods that are traditionally used to study protein folding and aggregation. Atomistic molecular dynamics (MD) simulations can help around deciphering relationship between phosphorylation and various intermediate and stable conformations of the Tau protein which occur on longer timescales. This chapter outlines protocols for the preparation, execution, and analysis of all-atom MD simulations of a 21-amino acid-long phosphorylated Tau peptide with the aim of generating biologically relevant structural and dynamic information. The simulations are done in explicit solvent and starting from nearly extended configurations of the peptide. The scaled MD method implemented in AMBER14 was chosen to achieve enhanced conformational sampling in addition to a conventional MD approach, thereby allowing the characterization of folding for such an intrinsically disordered peptide at 293 K. Emphasis is placed on the analysis of the simulation trajectories to establish correlations with NMR data (i.e., chemical shifts and NOEs). Finally, in-depth discussions are provided for commonly encountered problems.

Human depression: a new approach in quantitative psychiatry

PubMed Central

2010-01-01

The biomolecular approach to major depression disorder is explained by the different steps that involve cell membrane viscosity, Gsα protein and tubulin. For the first time it is hypothesised that a biomolecular pathway exists, moving from cell membrane viscosity through Gsα protein and Tubulin, which can condition the conscious state and is measurable by electroencephalogram study of the brain's γ wave synchrony. PMID:20525273

Future Technology-Driven Revolutions in Military Operations. Results of a Workshop

DTIC Science & Technology

1994-01-01

sensor missions. "• Biomolecular Electronics - The use of techniques from molecular biology and biotechnology to develop new molecular electronic materials...34* Biomolecular electronics - The use of techniques from molecular biology and biotechnology to develop new molecular electronic materials, components, and...occurring in molecular biology . 42 Biotechnology Molecular Biologists Arm Develoni "Magical" Caoabilitles "• To mynthsieh genm (frm satch) with conboi

Hybrid fuzzy cluster ensemble framework for tumor clustering from biomolecular data.

PubMed

Yu, Zhiwen; Chen, Hantao; You, Jane; Han, Guoqiang; Li, Le

2013-01-01

Cancer class discovery using biomolecular data is one of the most important tasks for cancer diagnosis and treatment. Tumor clustering from gene expression data provides a new way to perform cancer class discovery. Most of the existing research works adopt single-clustering algorithms to perform tumor clustering is from biomolecular data that lack robustness, stability, and accuracy. To further improve the performance of tumor clustering from biomolecular data, we introduce the fuzzy theory into the cluster ensemble framework for tumor clustering from biomolecular data, and propose four kinds of hybrid fuzzy cluster ensemble frameworks (HFCEF), named as HFCEF-I, HFCEF-II, HFCEF-III, and HFCEF-IV, respectively, to identify samples that belong to different types of cancers. The difference between HFCEF-I and HFCEF-II is that they adopt different ensemble generator approaches to generate a set of fuzzy matrices in the ensemble. Specifically, HFCEF-I applies the affinity propagation algorithm (AP) to perform clustering on the sample dimension and generates a set of fuzzy matrices in the ensemble based on the fuzzy membership function and base samples selected by AP. HFCEF-II adopts AP to perform clustering on the attribute dimension, generates a set of subspaces, and obtains a set of fuzzy matrices in the ensemble by performing fuzzy c-means on subspaces. Compared with HFCEF-I and HFCEF-II, HFCEF-III and HFCEF-IV consider the characteristics of HFCEF-I and HFCEF-II. HFCEF-III combines HFCEF-I and HFCEF-II in a serial way, while HFCEF-IV integrates HFCEF-I and HFCEF-II in a concurrent way. HFCEFs adopt suitable consensus functions, such as the fuzzy c-means algorithm or the normalized cut algorithm (Ncut), to summarize generated fuzzy matrices, and obtain the final results. The experiments on real data sets from UCI machine learning repository and cancer gene expression profiles illustrate that 1) the proposed hybrid fuzzy cluster ensemble frameworks work well on real data sets, especially biomolecular data, and 2) the proposed approaches are able to provide more robust, stable, and accurate results when compared with the state-of-the-art single clustering algorithms and traditional cluster ensemble approaches.

Microfluidic Examination of the "Hard" Biomolecular Corona Formed on Engineered Particles in Different Biological Milieu.

PubMed

Weiss, Alessia C G; Kempe, Kristian; Förster, Stephan; Caruso, Frank

2018-04-18

The formation of a biomolecular corona around engineered particles determines, in large part, their biological behavior in vitro and in vivo. To gain a fundamental understanding of how particle design and the biological milieu influence the formation of the "hard" biomolecular corona, we conduct a series of in vitro studies using microfluidics. This setup allows the generation of a dynamic incubation environment with precise control over the applied flow rate, stream orientation, and channel dimensions, thus allowing accurate control of the fluid flow and the shear applied to the proteins and particles. We used mesoporous silica particles, poly(2-methacryloyloxyethylphosphorylcholine) (PMPC)-coated silica hybrid particles, and PMPC replica particles (obtained by removal of the silica particle templates), representing high-, intermediate-, and low-fouling particle systems, respectively. The protein source used in the experiments was either human serum or human full blood. The effects of flow, particle surface properties, incubation medium, and incubation time on the formation of the biomolecular corona formation are examined. Our data show that protein adhesion on particles is enhanced after incubation in human blood compared to human serum and that dynamic incubation leads to a more complex corona. By varying the incubation time from 2 s to 15 min, we demonstrate that the "hard" biomolecular corona is kinetically subdivided into two phases comprising a tightly bound layer of proteins interacting directly with the particle surface and a loosely associated protein layer. Understanding the influence of particle design parameters and biological factors on the corona composition, as well as its dynamic assembly, may facilitate more accurate prediction of corona formation and therefore assist in the design of advanced drug delivery vehicles.

Field-effect sensors - from pH sensing to biosensing: sensitivity enhancement using streptavidin-biotin as a model system.

PubMed

Lowe, Benjamin M; Sun, Kai; Zeimpekis, Ioannis; Skylaris, Chris-Kriton; Green, Nicolas G

2017-11-06

Field-Effect Transistor sensors (FET-sensors) have been receiving increasing attention for biomolecular sensing over the last two decades due to their potential for ultra-high sensitivity sensing, label-free operation, cost reduction and miniaturisation. Whilst the commercial application of FET-sensors in pH sensing has been realised, their commercial application in biomolecular sensing (termed BioFETs) is hindered by poor understanding of how to optimise device design for highly reproducible operation and high sensitivity. In part, these problems stem from the highly interdisciplinary nature of the problems encountered in this field, in which knowledge of biomolecular-binding kinetics, surface chemistry, electrical double layer physics and electrical engineering is required. In this work, a quantitative analysis and critical review has been performed comparing literature FET-sensor data for pH-sensing with data for sensing of biomolecular streptavidin binding to surface-bound biotin systems. The aim is to provide the first systematic, quantitative comparison of BioFET results for a single biomolecular analyte, specifically streptavidin, which is the most commonly used model protein in biosensing experiments, and often used as an initial proof-of-concept for new biosensor designs. This novel quantitative and comparative analysis of the surface potential behaviour of a range of devices demonstrated a strong contrast between the trends observed in pH-sensing and those in biomolecule-sensing. Potential explanations are discussed in detail and surface-chemistry optimisation is shown to be a vital component in sensitivity-enhancement. Factors which can influence the response, yet which have not always been fully appreciated, are explored and practical suggestions are provided on how to improve experimental design.

Multi-Conformation Monte Carlo: A Method for Introducing Flexibility in Efficient Simulations of Many-Protein Systems.

PubMed

Prytkova, Vera; Heyden, Matthias; Khago, Domarin; Freites, J Alfredo; Butts, Carter T; Martin, Rachel W; Tobias, Douglas J

2016-08-25

We present a novel multi-conformation Monte Carlo simulation method that enables the modeling of protein-protein interactions and aggregation in crowded protein solutions. This approach is relevant to a molecular-scale description of realistic biological environments, including the cytoplasm and the extracellular matrix, which are characterized by high concentrations of biomolecular solutes (e.g., 300-400 mg/mL for proteins and nucleic acids in the cytoplasm of Escherichia coli). Simulation of such environments necessitates the inclusion of a large number of protein molecules. Therefore, computationally inexpensive methods, such as rigid-body Brownian dynamics (BD) or Monte Carlo simulations, can be particularly useful. However, as we demonstrate herein, the rigid-body representation typically employed in simulations of many-protein systems gives rise to certain artifacts in protein-protein interactions. Our approach allows us to incorporate molecular flexibility in Monte Carlo simulations at low computational cost, thereby eliminating ambiguities arising from structure selection in rigid-body simulations. We benchmark and validate the methodology using simulations of hen egg white lysozyme in solution, a well-studied system for which extensive experimental data, including osmotic second virial coefficients, small-angle scattering structure factors, and multiple structures determined by X-ray and neutron crystallography and solution NMR, as well as rigid-body BD simulation results, are available for comparison.

Altered Micro-RNA Degradation Promotes Tumor Heterogeneity: A Result from Boolean Network Modeling.

PubMed

Wu, Yunyi; Krueger, Gerhard R F; Wang, Guanyu

2016-02-01

Cancer heterogeneity may reflect differential dynamical outcomes of the regulatory network encompassing biomolecules at both transcriptional and post-transcriptional levels. In other words, differential gene-expression profiles may correspond to different stable steady states of a mathematical model for simulation of biomolecular networks. To test this hypothesis, we simplified a regulatory network that is important for soft-tissue sarcoma metastasis and heterogeneity, comprising of transcription factors, micro-RNAs, and signaling components of the NOTCH pathway. We then used a Boolean network model to simulate the dynamics of this network, and particularly investigated the consequences of differential miRNA degradation modes. We found that efficient miRNA degradation is crucial for sustaining a homogenous and healthy phenotype, while defective miRNA degradation may lead to multiple stable steady states and ultimately to carcinogenesis and heterogeneity. Copyright© 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Calculating the free energy of transfer of small solutes into a model lipid membrane: Comparison between metadynamics and umbrella sampling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bochicchio, Davide; Panizon, Emanuele; Ferrando, Riccardo

2015-10-14

We compare the performance of two well-established computational algorithms for the calculation of free-energy landscapes of biomolecular systems, umbrella sampling and metadynamics. We look at benchmark systems composed of polyethylene and polypropylene oligomers interacting with lipid (phosphatidylcholine) membranes, aiming at the calculation of the oligomer water-membrane free energy of transfer. We model our test systems at two different levels of description, united-atom and coarse-grained. We provide optimized parameters for the two methods at both resolutions. We devote special attention to the analysis of statistical errors in the two different methods and propose a general procedure for the error estimation inmore » metadynamics simulations. Metadynamics and umbrella sampling yield the same estimates for the water-membrane free energy profile, but metadynamics can be more efficient, providing lower statistical uncertainties within the same simulation time.« less

Multiscale simulations of anisotropic particles combining molecular dynamics and Green's function reaction dynamics

NASA Astrophysics Data System (ADS)

Vijaykumar, Adithya; Ouldridge, Thomas E.; ten Wolde, Pieter Rein; Bolhuis, Peter G.

2017-03-01

The modeling of complex reaction-diffusion processes in, for instance, cellular biochemical networks or self-assembling soft matter can be tremendously sped up by employing a multiscale algorithm which combines the mesoscopic Green's Function Reaction Dynamics (GFRD) method with explicit stochastic Brownian, Langevin, or deterministic molecular dynamics to treat reactants at the microscopic scale [A. Vijaykumar, P. G. Bolhuis, and P. R. ten Wolde, J. Chem. Phys. 143, 214102 (2015)]. Here we extend this multiscale MD-GFRD approach to include the orientational dynamics that is crucial to describe the anisotropic interactions often prevalent in biomolecular systems. We present the novel algorithm focusing on Brownian dynamics only, although the methodology is generic. We illustrate the novel algorithm using a simple patchy particle model. After validation of the algorithm, we discuss its performance. The rotational Brownian dynamics MD-GFRD multiscale method will open up the possibility for large scale simulations of protein signalling networks.

VAMPnets for deep learning of molecular kinetics.

PubMed

Mardt, Andreas; Pasquali, Luca; Wu, Hao; Noé, Frank

2018-01-02

There is an increasing demand for computing the relevant structures, equilibria, and long-timescale kinetics of biomolecular processes, such as protein-drug binding, from high-throughput molecular dynamics simulations. Current methods employ transformation of simulated coordinates into structural features, dimension reduction, clustering the dimension-reduced data, and estimation of a Markov state model or related model of the interconversion rates between molecular structures. This handcrafted approach demands a substantial amount of modeling expertise, as poor decisions at any step will lead to large modeling errors. Here we employ the variational approach for Markov processes (VAMP) to develop a deep learning framework for molecular kinetics using neural networks, dubbed VAMPnets. A VAMPnet encodes the entire mapping from molecular coordinates to Markov states, thus combining the whole data processing pipeline in a single end-to-end framework. Our method performs equally or better than state-of-the-art Markov modeling methods and provides easily interpretable few-state kinetic models.

Graphene plasmonic nanogratings for biomolecular sensing in liquid

NASA Astrophysics Data System (ADS)

Chorsi, Meysam T.; Chorsi, Hamid T.

2017-12-01

We design a surface plasmon resonance (SPR) molecular sensor based on graphene and biomolecule adsorption at graphene-liquid interfaces. The sensor configuration consists of two opposing arrays of graphene nanograting mounted on a substrate, with a liquid-phase sensing medium confined between them. We characterize the design in simulation on a variety of substrates by altering the refractive index of the sensing medium and varying the absorbance-transmittance characteristics. The influence of various parameters on the biosensor's performance, including the Fermi level of graphene, the dielectric constant of the substrate, and the incident angle for plasmon excitation, is investigated. Numerical simulations demonstrate the sensitivity higher than 3000 nm/RIU (refractive index unit). The device supports a wide range of substrates in which graphene can be epitaxially grown. The proposed biosensor works independent of the incident angle and can be tuned to cover a broadband wavelength range.

NMR paves the way for atomic level descriptions of sparsely populated, transiently formed biomolecular conformers.

PubMed

Sekhar, Ashok; Kay, Lewis E

2013-08-06

The importance of dynamics to biomolecular function is becoming increasingly clear. A description of the structure-function relationship must, therefore, include the role of motion, requiring a shift in paradigm from focus on a single static 3D picture to one where a given biomolecule is considered in terms of an ensemble of interconverting conformers, each with potentially diverse activities. In this Perspective, we describe how recent developments in solution NMR spectroscopy facilitate atomic resolution studies of sparsely populated, transiently formed biomolecular conformations that exchange with the native state. Examples of how this methodology is applied to protein folding and misfolding, ligand binding, and molecular recognition are provided as a means of illustrating both the power of the new techniques and the significant roles that conformationally excited protein states play in biology.

Recommendations of the wwPDB NMR Validation Task Force

PubMed Central

Montelione, Gaetano T.; Nilges, Michael; Bax, Ad; Güntert, Peter; Herrmann, Torsten; Richardson, Jane S.; Schwieters, Charles; Vranken, Wim F.; Vuister, Geerten W.; Wishart, David S.; Berman, Helen M.; Kleywegt, Gerard J.; Markley, John L.

2013-01-01

As methods for analysis of biomolecular structure and dynamics using nuclear magnetic resonance spectroscopy (NMR) continue to advance, the resulting 3D structures, chemical shifts, and other NMR data are broadly impacting biology, chemistry, and medicine. Structure model assessment is a critical area of NMR methods development, and is an essential component of the process of making these structures accessible and useful to the wider scientific community. For these reasons, the Worldwide Protein Data Bank (wwPDB) has convened an NMR Validation Task Force (NMR-VTF) to work with the wwPDB partners in developing metrics and policies for biomolecular NMR data harvesting, structure representation, and structure quality assessment. This paper summarizes the recommendations of the NMR-VTF, and lays the groundwork for future work in developing standards and metrics for biomolecular NMR structure quality assessment. PMID:24010715

Poisson-Nernst-Planck Equations for Simulating Biomolecular Diffusion-Reaction Processes I: Finite Element Solutions

PubMed Central

Lu, Benzhuo; Holst, Michael J.; McCammon, J. Andrew; Zhou, Y. C.

2010-01-01

In this paper we developed accurate finite element methods for solving 3-D Poisson-Nernst-Planck (PNP) equations with singular permanent charges for electrodiffusion in solvated biomolecular systems. The electrostatic Poisson equation was defined in the biomolecules and in the solvent, while the Nernst-Planck equation was defined only in the solvent. We applied a stable regularization scheme to remove the singular component of the electrostatic potential induced by the permanent charges inside biomolecules, and formulated regular, well-posed PNP equations. An inexact-Newton method was used to solve the coupled nonlinear elliptic equations for the steady problems; while an Adams-Bashforth-Crank-Nicolson method was devised for time integration for the unsteady electrodiffusion. We numerically investigated the conditioning of the stiffness matrices for the finite element approximations of the two formulations of the Nernst-Planck equation, and theoretically proved that the transformed formulation is always associated with an ill-conditioned stiffness matrix. We also studied the electroneutrality of the solution and its relation with the boundary conditions on the molecular surface, and concluded that a large net charge concentration is always present near the molecular surface due to the presence of multiple species of charged particles in the solution. The numerical methods are shown to be accurate and stable by various test problems, and are applicable to real large-scale biophysical electrodiffusion problems. PMID:21709855

Poisson-Nernst-Planck Equations for Simulating Biomolecular Diffusion-Reaction Processes I: Finite Element Solutions.

PubMed

Lu, Benzhuo; Holst, Michael J; McCammon, J Andrew; Zhou, Y C

2010-09-20

In this paper we developed accurate finite element methods for solving 3-D Poisson-Nernst-Planck (PNP) equations with singular permanent charges for electrodiffusion in solvated biomolecular systems. The electrostatic Poisson equation was defined in the biomolecules and in the solvent, while the Nernst-Planck equation was defined only in the solvent. We applied a stable regularization scheme to remove the singular component of the electrostatic potential induced by the permanent charges inside biomolecules, and formulated regular, well-posed PNP equations. An inexact-Newton method was used to solve the coupled nonlinear elliptic equations for the steady problems; while an Adams-Bashforth-Crank-Nicolson method was devised for time integration for the unsteady electrodiffusion. We numerically investigated the conditioning of the stiffness matrices for the finite element approximations of the two formulations of the Nernst-Planck equation, and theoretically proved that the transformed formulation is always associated with an ill-conditioned stiffness matrix. We also studied the electroneutrality of the solution and its relation with the boundary conditions on the molecular surface, and concluded that a large net charge concentration is always present near the molecular surface due to the presence of multiple species of charged particles in the solution. The numerical methods are shown to be accurate and stable by various test problems, and are applicable to real large-scale biophysical electrodiffusion problems.

Computational Sensing and in vitro Classification of GMOs and Biomolecular Events

DTIC Science & Technology

2008-12-01

COMPUTATIONAL SENSING AND IN VITRO CLASSIFICATION OF GMOs AND BIOMOLECULAR EVENTS Elebeoba May1∗, Miler T. Lee2†, Patricia Dolan1, Paul Crozier1...modified organisms ( GMOs ) in the pres- ence of non-lethal agents. Using an information and coding- theoretic framework we develop a de novo method for...high through- put screening, distinguishing genetically modified organisms ( GMOs ), molecular computing, differentiating biological mark- ers

Application of biomolecular recognition via magnetic nanoparticle in nanobiotechnology

NASA Astrophysics Data System (ADS)

Shen, Wei-Zheng; Cetinel, Sibel; Montemagno, Carlo

2018-05-01

The marriage of biomolecular recognition and magnetic nanoparticle creates tremendous opportunities in the development of advanced technology both in academic research and in industrial sectors. In this paper, we review current progress on the magnetic nanoparticle-biomolecule hybrid systems, particularly employing the recognition pairs of DNA-DNA, DNA-protein, protein-protein, and protein-inorganics in several nanobiotechnology application areas, including molecular biology, diagnostics, medical treatment, industrial biocatalysts, and environmental separations.

PDB-wide collection of binding data: current status of the PDBbind database.

PubMed

Liu, Zhihai; Li, Yan; Han, Li; Li, Jie; Liu, Jie; Zhao, Zhixiong; Nie, Wei; Liu, Yuchen; Wang, Renxiao

2015-02-01

Molecular recognition between biological macromolecules and organic small molecules plays an important role in various life processes. Both structural information and binding data of biomolecular complexes are indispensable for depicting the underlying mechanism in such an event. The PDBbind database was created to collect experimentally measured binding data for the biomolecular complexes throughout the Protein Data Bank (PDB). It thus provides the linkage between structural information and energetic properties of biomolecular complexes, which is especially desirable for computational studies or statistical analyses. Since its first public release in 2004, the PDBbind database has been updated on an annual basis. The latest release (version 2013) provides experimental binding affinity data for 10,776 biomolecular complexes in PDB, including 8302 protein-ligand complexes and 2474 other types of complexes. In this article, we will describe the current methods used for compiling PDBbind and the updated status of this database. We will also review some typical applications of PDBbind published in the scientific literature. All contents of this database are freely accessible at the PDBbind-CN Web server at http://www.pdbbind-cn.org/. wangrx@mail.sioc.ac.cn. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Autobiography of Ronald W. Rousseau.

PubMed

Rousseau, Ronald W

2018-03-01

This article provides a synopsis of my professional career, from the decision to study chemical engineering to leadership of one of the top academic programs in that field. I describe how I chose to devote my research to phenomena associated with crystallization as practiced for separation and purification and then made the transition to leader of an academic program. Embedded in the coverage are descriptions of research advances coming from exploration of secondary nucleation, especially how collisions of crystals in supersaturated environments dominate the behavior of industrially relevant crystallization processes. I recount some of the challenges associated with becoming a school chair and how the program I led grew. The story illuminates the contributions of my many mentors, colleagues, and students. Expected final online publication date for the Annual Review of Chemical and Biomolecular Engineering Volume 9 is June 7, 2018. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

An autonomous molecular computer for logical control of gene expression.

PubMed

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.

A New Look at NASA: Strategic Research In Information Technology

NASA Technical Reports Server (NTRS)

Alfano, David; Tu, Eugene (Technical Monitor)

2002-01-01

This viewgraph presentation provides information on research undertaken by NASA to facilitate the development of information technologies. Specific ideas covered here include: 1) Bio/nano technologies: biomolecular and nanoscale systems and tools for assembly and computing; 2) Evolvable hardware: autonomous self-improving, self-repairing hardware and software for survivable space systems in extreme environments; 3) High Confidence Software Technologies: formal methods, high-assurance software design, and program synthesis; 4) Intelligent Controls and Diagnostics: Next generation machine learning, adaptive control, and health management technologies; 5) Revolutionary computing: New computational models to increase capability and robustness to enable future NASA space missions.

A QM-MD simulation approach to the analysis of FRET processes in (bio)molecular systems. A case study: complexes of E. coli purine nucleoside phosphorylase and its mutants with formycin A.

PubMed

Sobieraj, M; Krzyśko, K A; Jarmuła, A; Kalinowski, M W; Lesyng, B; Prokopowicz, M; Cieśla, J; Gojdź, A; Kierdaszuk, B

2015-04-01

Predicting FRET pathways in proteins using computer simulation techniques is very important for reliable interpretation of experimental data. A novel and relatively simple methodology has been developed and applied to purine nucleoside phosphorylase (PNP) complexed with a fluorescent ligand - formycin A (FA). FRET occurs between an excited Tyr residue (D*) and FA (A). This study aims to interpret experimental data that, among others, suggests the absence of FRET for the PNPF159A mutant in complex with FA, based on novel theoretical methodology. MD simulations for the protein molecule containing D*, and complexed with A, are carried out. Interactions of D* with its molecular environment are accounted by including changes of the ESP charges in S1, compared to S0, and computed at the SCF-CI level. FRET probability W F depends on the inverse six-power of the D*-A distance, R da . The orientational factor 0 < k(2) < 4 between D* and A is computed and included in the analysis. Finally W F is time-averaged over the MD trajectories resulting in its mean value. The red-shift of the tyrosinate anion emission and thus lack of spectral overlap integral and thermal energy dissipation are the reasons for the FRET absence in the studied mutants at pH 7 and above. The presence of the tyrosinate anion results in a competitive energy dissipation channel and red-shifted emission, thus in consequence in the absence of FRET. These studies also indicate an important role of the phenyl ring of Phe159 for FRET in the wild-type PNP, which does not exist in the Ala159 mutant, and for the effective association of PNP with FA. In a more general context, our observations point out very interesting and biologically important properties of the tyrosine residue in its excited state, which may undergo spontaneous deprotonation in the biomolecular systems, resulting further in unexpected physical and/or biological phenomena. Until now, this observation has not been widely discussed in the literature.

Bacteriorhodopsin as an electronic conduction medium for biomolecular electronics.

PubMed

Jin, Yongdong; Honig, Tal; Ron, Izhar; Friedman, Noga; Sheves, Mordechai; Cahen, David

2008-11-01

Interfacing functional proteins with solid supports for device applications is a promising route to possible applications in bio-electronics, -sensors, and -optics. Various possible applications of bacteriorhodopsin (bR) have been explored and reviewed since the discovery of bR. This tutorial review discusses bR as a medium for biomolecular optoelectronics, emphasizing ways in which it can be interfaced, especially as a thin film, solid-state current-carrying electronic element.

A 3D printing method for droplet-based biomolecular materials

NASA Astrophysics Data System (ADS)

Challita, Elio J.; Najem, Joseph S.; Freeman, Eric C.; Leo, Donald J.

2017-04-01

The field of developing biomolecular droplet-based materials using a bottom-up approach remains underexplored. Producing tissue-like materials, from entirely synthetic components, presents an innovative method to reconstruct the functions of life within artificial materials. Aqueous droplets, encased with lipid monolayers, may be linked via bilayer interfaces to make up structures that resemble biological tissues. Here we present the design and development of an easy-to-build 3D printer for the fabrication of tissue-like biomolecular materials from cell-sized aqueous droplets. The droplets are generated using a snap off technique, capable of generating 30 droplets per minute. The printed network of droplets may also be functionalized with various types of membrane proteins to achieve desired engineering applications like sensing and actuation, or to mimic electrical communication in biological systems. Voltage sensitive channels are introduced into selected droplets to create a conductive path with the material in the presence of an external field.

BIND: the Biomolecular Interaction Network Database

PubMed Central

Bader, Gary D.; Betel, Doron; Hogue, Christopher W. V.

2003-01-01

The Biomolecular Interaction Network Database (BIND: http://bind.ca) archives biomolecular interaction, complex and pathway information. A web-based system is available to query, view and submit records. BIND continues to grow with the addition of individual submissions as well as interaction data from the PDB and a number of large-scale interaction and complex mapping experiments using yeast two hybrid, mass spectrometry, genetic interactions and phage display. We have developed a new graphical analysis tool that provides users with a view of the domain composition of proteins in interaction and complex records to help relate functional domains to protein interactions. An interaction network clustering tool has also been developed to help focus on regions of interest. Continued input from users has helped further mature the BIND data specification, which now includes the ability to store detailed information about genetic interactions. The BIND data specification is available as ASN.1 and XML DTD. PMID:12519993

Design of an embedded inverse-feedforward biomolecular tracking controller for enzymatic reaction processes.

PubMed

Foo, Mathias; Kim, Jongrae; Sawlekar, Rucha; Bates, Declan G

2017-04-06

Feedback control is widely used in chemical engineering to improve the performance and robustness of chemical processes. Feedback controllers require a 'subtractor' that is able to compute the error between the process output and the reference signal. In the case of embedded biomolecular control circuits, subtractors designed using standard chemical reaction network theory can only realise one-sided subtraction, rendering standard controller design approaches inadequate. Here, we show how a biomolecular controller that allows tracking of required changes in the outputs of enzymatic reaction processes can be designed and implemented within the framework of chemical reaction network theory. The controller architecture employs an inversion-based feedforward controller that compensates for the limitations of the one-sided subtractor that generates the error signals for a feedback controller. The proposed approach requires significantly fewer chemical reactions to implement than alternative designs, and should have wide applicability throughout the fields of synthetic biology and biological engineering.

A biomolecular detection method based on charge pumping in a nanogap embedded field-effect-transistor biosensor

NASA Astrophysics Data System (ADS)

Kim, Sungho; Ahn, Jae-Hyuk; Park, Tae Jung; Lee, Sang Yup; Choi, Yang-Kyu

2009-06-01

A unique direct electrical detection method of biomolecules, charge pumping, was demonstrated using a nanogap embedded field-effect-transistor (FET). With aid of a charge pumping method, sensitivity can fall below the 1 ng/ml concentration regime in antigen-antibody binding of an avian influenza case. Biomolecules immobilized in the nanogap are mainly responsible for the acute changes of the interface trap density due to modulation of the energy level of the trap. This finding is supported by a numerical simulation. The proposed detection method for biomolecules using a nanogap embedded FET represents a foundation for a chip-based biosensor capable of high sensitivity.

Capillarity theory for the fly-casting mechanism

PubMed Central

Trizac, Emmanuel; Levy, Yaakov; Wolynes, Peter G.

2010-01-01

Biomolecular folding and function are often coupled. During molecular recognition events, one of the binding partners may transiently or partially unfold, allowing more rapid access to a binding site. We describe a simple model for this fly-casting mechanism based on the capillarity approximation and polymer chain statistics. The model shows that fly casting is most effective when the protein unfolding barrier is small and the part of the chain which extends toward the target is relatively rigid. These features are often seen in known examples of fly casting in protein–DNA binding. Simulations of protein–DNA binding based on well-funneled native-topology models with electrostatic forces confirm the trends of the analytical theory. PMID:20133683

Application of Multiplexed Replica Exchange Molecular Dynamics to the UNRES Force Field: Tests with alpha and alpha+beta Proteins.

PubMed

Czaplewski, Cezary; Kalinowski, Sebastian; Liwo, Adam; Scheraga, Harold A

2009-03-10

The replica exchange (RE) method is increasingly used to improve sampling in molecular dynamics (MD) simulations of biomolecular systems. Recently, we implemented the united-residue UNRES force field for mesoscopic MD. Initial results from UNRES MD simulations show that we are able to simulate folding events that take place in a microsecond or even a millisecond time scale. To speed up the search further, we applied the multiplexing replica exchange molecular dynamics (MREMD) method. The multiplexed variant (MREMD) of the RE method, developed by Rhee and Pande, differs from the original RE method in that several trajectories are run at a given temperature. Each set of trajectories run at a different temperature constitutes a layer. Exchanges are attempted not only within a single layer but also between layers. The code has been parallelized and scales up to 4000 processors. We present a comparison of canonical MD, REMD, and MREMD simulations of protein folding with the UNRES force-field. We demonstrate that the multiplexed procedure increases the power of replica exchange MD considerably and convergence of the thermodynamic quantities is achieved much faster.

Application of Multiplexed Replica Exchange Molecular Dynamics to the UNRES Force Field: Tests with α and α+β Proteins

PubMed Central

Czaplewski, Cezary; Kalinowski, Sebastian; Liwo, Adam; Scheraga, Harold A.

2009-01-01

The replica exchange (RE) method is increasingly used to improve sampling in molecular dynamics (MD) simulations of biomolecular systems. Recently, we implemented the united-residue UNRES force field for mesoscopic MD. Initial results from UNRES MD simulations show that we are able to simulate folding events that take place in a microsecond or even a millisecond time scale. To speed up the search further, we applied the multiplexing replica exchange molecular dynamics (MREMD) method. The multiplexed variant (MREMD) of the RE method, developed by Rhee and Pande, differs from the original RE method in that several trajectories are run at a given temperature. Each set of trajectories run at a different temperature constitutes a layer. Exchanges are attempted not only within a single layer but also between layers. The code has been parallelized and scales up to 4000 processors. We present a comparison of canonical MD, REMD, and MREMD simulations of protein folding with the UNRES force-field. We demonstrate that the multiplexed procedure increases the power of replica exchange MD considerably and convergence of the thermodynamic quantities is achieved much faster. PMID:20161452

Molecular dynamics simulation of the partitioning of benzocaine and phenytoin into a lipid bilayer.

PubMed

Martin, Lewis J; Chao, Rebecca; Corry, Ben

2014-01-01

Molecular dynamics simulations were used to examine the partitioning behaviour of the local anaesthetic benzocaine and the anti-epileptic phenytoin into lipid bilayers, a factor that is critical to their mode of action. Free energy methods are used to quantify the thermodynamics of drug movement between water and octanol as well as for permeation across a POPC membrane. Both drugs are shown to favourably partition into the lipid bilayer from water and are likely to accumulate just inside the lipid headgroups where they may alter bilayer properties or interact with target proteins. Phenytoin experiences a large barrier to cross the centre of the bilayer due to less favourable energetic interactions in this less dense region of the bilayer. Remarkably, in our simulations both drugs are able to pull water into the bilayer, creating water chains that extend back to bulk, and which may modify the local bilayer properties. We find that the choice of atomic partial charges can have a significant impact on the quantitative results, meaning that careful validation of parameters for new drugs, such as performed here, should be performed prior to their use in biomolecular simulations. Copyright © 2013 Elsevier B.V. All rights reserved.

Gay-Berne and electrostatic multipole based coarse-grain potential in implicit solvent

NASA Astrophysics Data System (ADS)

Wu, Johnny; Zhen, Xia; Shen, Hujun; Li, Guohui; Ren, Pengyu

2011-10-01

A general, transferable coarse-grain (CG) framework based on the Gay-Berne potential and electrostatic point multipole expansion is presented for polypeptide simulations. The solvent effect is described by the Generalized Kirkwood theory. The CG model is calibrated using the results of all-atom simulations of model compounds in solution. Instead of matching the overall effective forces produced by atomic models, the fundamental intermolecular forces such as electrostatic, repulsion-dispersion, and solvation are represented explicitly at a CG level. We demonstrate that the CG alanine dipeptide model is able to reproduce quantitatively the conformational energy of all-atom force fields in both gas and solution phases, including the electrostatic and solvation components. Replica exchange molecular dynamics and microsecond dynamic simulations of polyalanine of 5 and 12 residues reveal that the CG polyalanines fold into "alpha helix" and "beta sheet" structures. The 5-residue polyalanine displays a substantial increase in the "beta strand" fraction relative to the 12-residue polyalanine. The detailed conformational distribution is compared with those reported from recent all-atom simulations and experiments. The results suggest that the new coarse-graining approach presented in this study has the potential to offer both accuracy and efficiency for biomolecular modeling.

Adaptive resolution simulation of an atomistic protein in MARTINI water

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zavadlav, Julija; Melo, Manuel Nuno; Marrink, Siewert J., E-mail: s.j.marrink@rug.nl

2014-02-07

We present an adaptive resolution simulation of protein G in multiscale water. We couple atomistic water around the protein with mesoscopic water, where four water molecules are represented with one coarse-grained bead, farther away. We circumvent the difficulties that arise from coupling to the coarse-grained model via a 4-to-1 molecule coarse-grain mapping by using bundled water models, i.e., we restrict the relative movement of water molecules that are mapped to the same coarse-grained bead employing harmonic springs. The water molecules change their resolution from four molecules to one coarse-grained particle and vice versa adaptively on-the-fly. Having performed 15 ns long molecularmore » dynamics simulations, we observe within our error bars no differences between structural (e.g., root-mean-squared deviation and fluctuations of backbone atoms, radius of gyration, the stability of native contacts and secondary structure, and the solvent accessible surface area) and dynamical properties of the protein in the adaptive resolution approach compared to the fully atomistically solvated model. Our multiscale model is compatible with the widely used MARTINI force field and will therefore significantly enhance the scope of biomolecular simulations.« less

Adaptive resolution simulation of an atomistic protein in MARTINI water.

PubMed

Zavadlav, Julija; Melo, Manuel Nuno; Marrink, Siewert J; Praprotnik, Matej

2014-02-07

We present an adaptive resolution simulation of protein G in multiscale water. We couple atomistic water around the protein with mesoscopic water, where four water molecules are represented with one coarse-grained bead, farther away. We circumvent the difficulties that arise from coupling to the coarse-grained model via a 4-to-1 molecule coarse-grain mapping by using bundled water models, i.e., we restrict the relative movement of water molecules that are mapped to the same coarse-grained bead employing harmonic springs. The water molecules change their resolution from four molecules to one coarse-grained particle and vice versa adaptively on-the-fly. Having performed 15 ns long molecular dynamics simulations, we observe within our error bars no differences between structural (e.g., root-mean-squared deviation and fluctuations of backbone atoms, radius of gyration, the stability of native contacts and secondary structure, and the solvent accessible surface area) and dynamical properties of the protein in the adaptive resolution approach compared to the fully atomistically solvated model. Our multiscale model is compatible with the widely used MARTINI force field and will therefore significantly enhance the scope of biomolecular simulations.

Bayesian energy landscape tilting: towards concordant models of molecular ensembles.

PubMed

Beauchamp, Kyle A; Pande, Vijay S; Das, Rhiju

2014-03-18

Predicting biological structure has remained challenging for systems such as disordered proteins that take on myriad conformations. Hybrid simulation/experiment strategies have been undermined by difficulties in evaluating errors from computational model inaccuracies and data uncertainties. Building on recent proposals from maximum entropy theory and nonequilibrium thermodynamics, we address these issues through a Bayesian energy landscape tilting (BELT) scheme for computing Bayesian hyperensembles over conformational ensembles. BELT uses Markov chain Monte Carlo to directly sample maximum-entropy conformational ensembles consistent with a set of input experimental observables. To test this framework, we apply BELT to model trialanine, starting from disagreeing simulations with the force fields ff96, ff99, ff99sbnmr-ildn, CHARMM27, and OPLS-AA. BELT incorporation of limited chemical shift and (3)J measurements gives convergent values of the peptide's α, β, and PPII conformational populations in all cases. As a test of predictive power, all five BELT hyperensembles recover set-aside measurements not used in the fitting and report accurate errors, even when starting from highly inaccurate simulations. BELT's principled framework thus enables practical predictions for complex biomolecular systems from discordant simulations and sparse data. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Free-energy landscape of intrinsically disordered proteins investigated by all-atom multicanonical molecular dynamics.

PubMed

Higo, Junichi; Umezawa, Koji

2014-01-01

We introduce computational studies on intrinsically disordered proteins (IDPs). Especially, we present our multicanonical molecular dynamics (McMD) simulations of two IDP-partner systems: NRSF-mSin3 and pKID-KIX. McMD is one of enhanced conformational sampling methods useful for conformational sampling of biomolecular systems. IDP adopts a specific tertiary structure upon binding to its partner molecule, although it is unstructured in the unbound state (i.e. the free state). This IDP-specific property is called "coupled folding and binding". The McMD simulation treats the biomolecules with an all-atom model immersed in an explicit solvent. In the initial configuration of simulation, IDP and its partner molecules are set to be distant from each other, and the IDP conformation is disordered. The computationally obtained free-energy landscape for coupled folding and binding has shown that native- and non-native-complex clusters distribute complicatedly in the conformational space. The all-atom simulation suggests that both of induced-folding and population-selection are coupled complicatedly in the coupled folding and binding. Further analyses have exemplified that the conformational fluctuations (dynamical flexibility) in the bound and unbound states are essentially important to characterize IDP functioning.

Vibrational Raman optical activity of 1-phenylethanol and 1-phenylethylamine: revisiting old friends.

PubMed

Kapitán, Josef; Johannessen, Christian; Bour, Petr; Hecht, Lutz; Barron, Laurence D

2009-01-01

The samples used for the first observations of vibrational Raman optical activity (ROA) in 1972, namely both enantiomers of 1-phenylethanol and 1-phenylethylamine, have been revisited using a modern commercial ROA instrument together with state-of-the-art ab initio calculations. The simulated ROA spectra reveal for the first time the vibrational origins of the first reported ROA signals, which comprised similar couplets in the alcohol and amine in the spectral range approximately 280-400 cm(-1). The results demonstrate how easy and routine ROA measurements have become, and how current ab initio quantum-chemical calculations are capable of simulating experimental ROA spectra quite closely provided sufficient averaging over accessible conformations is included. Assignment of absolute configuration is, inter alia, completely secure from results of this quality. Anharmonic corrections provided small improvements in the simulated Raman and ROA spectra. The importance of conformational averaging emphasized by this and previous related work provides the underlying theoretical background to ROA studies of dynamic aspects of chiral molecular and biomolecular structure and behavior. (c) 2009 Wiley-Liss, Inc.

Preparation of stimulus responsive multiple emulsions by membrane emulsification using con a as biochemical sensor.

PubMed

Piacentini, Emma; Drioli, Enrico; Giorno, Lidietta

2011-04-01

In this work, a novel strategy for the controlled fabrication of biomolecular stimulus responsive water-in-oil-in-water (W/O/W) multiple emulsion using the membrane emulsification process was investigated. The emulsions interface was functionalized with a biomolecule able to function as a receptor for a target compound. The interaction between the biomolecular receptor and target stimulus activated the release of bioactive molecules contained within the structured emulsion. A glucose sensitive emulsion was investigated as a model study case. Concanavalin A (Con A) was used as the biomolecular glucose sensor. Various physicochemical strategies for stimulus responsive materials formulation are available in literature, but the preparation of biomolecule-responsive emulsions has been explored for the first time in this paper. The development of novel drug delivery systems requires advanced and highly precise techniques to obtain their particular properties and targeting requirements. The present study has proven the flexibility and suitability of membrane emulsification for the preparation of stable and functional multiple emulsions containing Con A as interfacial biomolecular receptor able to activate the release of a bioactive molecule as a consequence of interaction with the glucose target molecule. The influence of emulsion interfacial composition and membrane emulsification operating conditions on droplets stability and functional properties have been investigated. The release of the bioactive molecule as a function of glucose stimulus and its concentration has been demonstrated. Copyright © 2010 Wiley Periodicals, Inc.

NMRbox: A Resource for Biomolecular NMR Computation.

PubMed

Maciejewski, Mark W; Schuyler, Adam D; Gryk, Michael R; Moraru, Ion I; Romero, Pedro R; Ulrich, Eldon L; Eghbalnia, Hamid R; Livny, Miron; Delaglio, Frank; Hoch, Jeffrey C

2017-04-25

Advances in computation have been enabling many recent advances in biomolecular applications of NMR. Due to the wide diversity of applications of NMR, the number and variety of software packages for processing and analyzing NMR data is quite large, with labs relying on dozens, if not hundreds of software packages. Discovery, acquisition, installation, and maintenance of all these packages is a burdensome task. Because the majority of software packages originate in academic labs, persistence of the software is compromised when developers graduate, funding ceases, or investigators turn to other projects. To simplify access to and use of biomolecular NMR software, foster persistence, and enhance reproducibility of computational workflows, we have developed NMRbox, a shared resource for NMR software and computation. NMRbox employs virtualization to provide a comprehensive software environment preconfigured with hundreds of software packages, available as a downloadable virtual machine or as a Platform-as-a-Service supported by a dedicated compute cloud. Ongoing development includes a metadata harvester to regularize, annotate, and preserve workflows and facilitate and enhance data depositions to BioMagResBank, and tools for Bayesian inference to enhance the robustness and extensibility of computational analyses. In addition to facilitating use and preservation of the rich and dynamic software environment for biomolecular NMR, NMRbox fosters the development and deployment of a new class of metasoftware packages. NMRbox is freely available to not-for-profit users. Copyright © 2017 Biophysical Society. All rights reserved.

Biomolecular recognition and detection using gold-based nanoprobes

NASA Astrophysics Data System (ADS)

Crew, Elizabeth

The ability to control the biomolecular interactions is important for developing bioanalytical probes used in biomolecule and biomarker detections. This work aims at a fundamental understanding of the interactions and reactivities involving DNA, miRNA, and amino acids using gold-based nanoparticles as nanoprobes, which has implications for developing new strategies for the early detection of diseases, such as cancer, and controlled delivery of drugs. Surface modifications of the nanoprobes with DNA, miRNA, and amino acids and the nanoprobe directed biomolecular reactivities, such as complementary-strand binding, enzymatic cutting and amino acid interactions, have been investigated. Among various analytical techniques employed for the analysis of the biomolecule-nanoprobe interactions, surface enhanced Raman scattering spectroscopy (SERS) has been demonstrated to provide a powerful tool for real time monitoring of the DNA assembly and enzymatic cutting processes in solutions. This demonstration harnesses the "hot-spot" characteristic tuned by the interparticle biomolecular-regulated interactions and distances. The assembly of gold nanoparticles has also been exploited as sensing thin films on chemiresistor arrays for the detection of volatile organic compounds, including biomarker molecules associated with diabetes. Important findings of the nanoprobes in delivering miRNA to cells, detecting DNA hybridization kinetics, discerning chiral recognition with enantiomeric cysteines, and sensing biomarker molecules with the nanostructured thin films will be discussed, along with their implications to enhancing sensitivity, selectivity and limits of detection.

Biomolecular Interaction Analysis Using an Optical Surface Plasmon Resonance Biosensor: The Marquardt Algorithm vs Newton Iteration Algorithm

PubMed Central

Hu, Jiandong; Ma, Liuzheng; Wang, Shun; Yang, Jianming; Chang, Keke; Hu, Xinran; Sun, Xiaohui; Chen, Ruipeng; Jiang, Min; Zhu, Juanhua; Zhao, Yuanyuan

2015-01-01

Kinetic analysis of biomolecular interactions are powerfully used to quantify the binding kinetic constants for the determination of a complex formed or dissociated within a given time span. Surface plasmon resonance biosensors provide an essential approach in the analysis of the biomolecular interactions including the interaction process of antigen-antibody and receptors-ligand. The binding affinity of the antibody to the antigen (or the receptor to the ligand) reflects the biological activities of the control antibodies (or receptors) and the corresponding immune signal responses in the pathologic process. Moreover, both the association rate and dissociation rate of the receptor to ligand are the substantial parameters for the study of signal transmission between cells. A number of experimental data may lead to complicated real-time curves that do not fit well to the kinetic model. This paper presented an analysis approach of biomolecular interactions established by utilizing the Marquardt algorithm. This algorithm was intensively considered to implement in the homemade bioanalyzer to perform the nonlinear curve-fitting of the association and disassociation process of the receptor to ligand. Compared with the results from the Newton iteration algorithm, it shows that the Marquardt algorithm does not only reduce the dependence of the initial value to avoid the divergence but also can greatly reduce the iterative regression times. The association and dissociation rate constants, ka, kd and the affinity parameters for the biomolecular interaction, KA, KD, were experimentally obtained 6.969×105 mL·g-1·s-1, 0.00073 s-1, 9.5466×108 mL·g-1 and 1.0475×10-9 g·mL-1, respectively from the injection of the HBsAg solution with the concentration of 16ng·mL-1. The kinetic constants were evaluated distinctly by using the obtained data from the curve-fitting results. PMID:26147997

Allosteric activation transitions in enzymes and biomolecular motors: insights from atomistic and coarse-grained simulations.

PubMed

Daily, Michael D; Yu, Haibo; Phillips, George N; Cui, Qiang

2013-01-01

The chemical step in enzymes is usually preceded by a kinetically distinct activation step that involves large-scale conformational transitions. In "simple" enzymes this step corresponds to the closure of the active site; in more complex enzymes, such as biomolecular motors, the activation step is more complex and may involve interactions with other biomolecules. These activation transitions are essential to the function of enzymes and perturbations in the scale and/or rate of these transitions are implicated in various serious human diseases; incorporating key flexibilities into engineered enzymes is also considered a major remaining challenge in rational enzyme design. Therefore it is important to understand the underlying mechanism of these transitions. This is a significant challenge to both experimental and computational studies because of the allosteric and multi-scale nature of such transitions. Using our recent studies of two enzyme systems, myosin and adenylate kinase (AK), we discuss how atomistic and coarse-grained simulations can be used to provide insights into the mechanism of activation transitions in realistic systems. Collectively, the results suggest that although many allosteric transitions can be viewed as domain displacements mediated by flexible hinges, there are additional complexities and various deviations. For example, although our studies do not find any evidence for "cracking" in AK, our results do underline the contribution of intra-domain properties (e.g., dihedral flexibility) to the rate of the transition. The study of mechanochemical coupling in myosin highlights that local changes important to chemistry require stabilization from more extensive structural changes; in this sense, more global structural transitions are needed to activate the chemistry in the active site. These discussions further emphasize the importance of better understanding factors that control the degree of co-operativity for allosteric transitions, again hinting at the intimate connection between protein stability and functional flexibility. Finally, a number of topics of considerable future interest are briefly discussed.

Instrumental biosensors: new perspectives for the analysis of biomolecular interactions.

PubMed

Nice, E C; Catimel, B

1999-04-01

The use of instrumental biosensors in basic research to measure biomolecular interactions in real time is increasing exponentially. Applications include protein-protein, protein-peptide, DNA-protein, DNA-DNA, and lipid-protein interactions. Such techniques have been applied to, for example, antibody-antigen, receptor-ligand, signal transduction, and nuclear receptor studies. This review outlines the principles of two of the most commonly used instruments and highlights specific operating parameters that will assist in optimising experimental design, data generation, and analysis.

Efficient designs for powering microscale devices with nanoscale biomolecular motors.

PubMed

Lin, Chih-Ting; Kao, Ming-Tse; Kurabayashi, Katsuo; Meyhöfer, Edgar

2006-02-01

Current MEMS and microfluidic designs require external power sources and actuators, which principally limit such technology. To overcome these limitations, we have developed a number of microfluidic systems into which we can seamlessly integrate a biomolecular motor, kinesin, that transports microtubules by extracting chemical energy from its aqueous working environment. Here we establish that our microfabricated structures, the self-assembly of the bio-derived transducer, and guided, unidirectional transport of microtubules are ideally suited to create engineered arrays for efficiently powering nano- and microscale devices.

Three-dimensional reconstruction for coherent diffraction patterns obtained by XFEL.

PubMed

Nakano, Miki; Miyashita, Osamu; Jonic, Slavica; Song, Changyong; Nam, Daewoong; Joti, Yasumasa; Tama, Florence

2017-07-01

The three-dimensional (3D) structural analysis of single particles using an X-ray free-electron laser (XFEL) is a new structural biology technique that enables observations of molecules that are difficult to crystallize, such as flexible biomolecular complexes and living tissue in the state close to physiological conditions. In order to restore the 3D structure from the diffraction patterns obtained by the XFEL, computational algorithms are necessary as the orientation of the incident beam with respect to the sample needs to be estimated. A program package for XFEL single-particle analysis based on the Xmipp software package, that is commonly used for image processing in 3D cryo-electron microscopy, has been developed. The reconstruction program has been tested using diffraction patterns of an aerosol nanoparticle obtained by tomographic coherent X-ray diffraction microscopy.

A new class of enhanced kinetic sampling methods for building Markov state models

NASA Astrophysics Data System (ADS)

Bhoutekar, Arti; Ghosh, Susmita; Bhattacharya, Swati; Chatterjee, Abhijit

2017-10-01

Markov state models (MSMs) and other related kinetic network models are frequently used to study the long-timescale dynamical behavior of biomolecular and materials systems. MSMs are often constructed bottom-up using brute-force molecular dynamics (MD) simulations when the model contains a large number of states and kinetic pathways that are not known a priori. However, the resulting network generally encompasses only parts of the configurational space, and regardless of any additional MD performed, several states and pathways will still remain missing. This implies that the duration for which the MSM can faithfully capture the true dynamics, which we term as the validity time for the MSM, is always finite and unfortunately much shorter than the MD time invested to construct the model. A general framework that relates the kinetic uncertainty in the model to the validity time, missing states and pathways, network topology, and statistical sampling is presented. Performing additional calculations for frequently-sampled states/pathways may not alter the MSM validity time. A new class of enhanced kinetic sampling techniques is introduced that aims at targeting rare states/pathways that contribute most to the uncertainty so that the validity time is boosted in an effective manner. Examples including straightforward 1D energy landscapes, lattice models, and biomolecular systems are provided to illustrate the application of the method. Developments presented here will be of interest to the kinetic Monte Carlo community as well.

Raman spectroscopic analysis of geological and biogeological specimens of relevance to the ExoMars mission.

PubMed

Edwards, Howell G M; Hutchinson, Ian B; Ingley, Richard; Parnell, John; Vítek, Petr; Jehlička, Jan

2013-06-01

A novel miniaturized Raman spectrometer is scheduled to fly as part of the analytical instrumentation package on an ESA remote robotic lander in the ESA/Roscosmos ExoMars mission to search for evidence for extant or extinct life on Mars in 2018. The Raman spectrometer will be part of the first-pass analytical stage of the sampling procedure, following detailed surface examination by the PanCam scanning camera unit on the ExoMars rover vehicle. The requirements of the analytical protocol are stringent and critical; this study represents a laboratory blind interrogation of specimens that form a list of materials that are of relevance to martian exploration and at this stage simulates a test of current laboratory instrumentation to highlight the Raman technique strengths and possible weaknesses that may be encountered in practice on the martian surface and from which future studies could be formulated. In this preliminary exercise, some 10 samples that are considered terrestrial representatives of the mineralogy and possible biogeologically modified structures that may be identified on Mars have been examined with Raman spectroscopy, and conclusions have been drawn about the viability of the unambiguous spectral identification of biomolecular life signatures. It is concluded that the Raman spectroscopic technique does indeed demonstrate the capability to identify biomolecular signatures and the mineralogy in real-world terrestrial samples with a very high degree of success without any preconception being made about their origin and classification.

Technology Development of Miniaturized Far-Infrared Sources for Biomolecular Spectroscopy

NASA Technical Reports Server (NTRS)

Kono, Junichiro

2003-01-01

The objective of this project was to develop a purely solid-state based, thus miniaturized, far-infrared (FIR) (also known as terahertz (THz)) wave source using III-V semiconductor nanostructures for biomolecular detection and sensing. Many biomolecules, such as DNA and proteins, have distinct spectroscopic features in the FIR wavelength range as a result of vibration-rotation-tunneling motions and various inter- and intra-molecule collective motions. Spectroscopic characterization of such molecules requires narrow linewidth, sufficiently high power, tunable (in wavelength), and coherent FIR sources. Unfortunately, the FIR frequency is one of the least technologically developed ranges in the electromagnetic spectrum. Currently available FIR sources based on non-solid state technology are bulky, inefficient, and very often incoherent. In this project we investigated antimonide based compound semiconductor (ABCS) nanostructures as the active medium to generate FIR radiation. The final goal of this project was to demonstrate a semiconductor THz source integrated with a pumping diode laser module to achieve a compact system for biomolecular applications.

Biologically inspired design of feedback control systems implemented using DNA strand displacement reactions.

PubMed

Foo, Mathias; Sawlekar, Rucha; Kulkarni, Vishwesh V; Bates, Declan G

2016-08-01

The use of abstract chemical reaction networks (CRNs) as a modelling and design framework for the implementation of computing and control circuits using enzyme-free, entropy driven DNA strand displacement (DSD) reactions is starting to garner widespread attention in the area of synthetic biology. Previous work in this area has demonstrated the theoretical plausibility of using this approach to design biomolecular feedback control systems based on classical proportional-integral (PI) controllers, which may be constructed from CRNs implementing gain, summation and integrator operators. Here, we propose an alternative design approach that utilises the abstract chemical reactions involved in cellular signalling cycles to implement a biomolecular controller - termed a signalling-cycle (SC) controller. We compare the performance of the PI and SC controllers in closed-loop with a nonlinear second-order chemical process. Our results show that the SC controller outperforms the PI controller in terms of both performance and robustness, and also requires fewer abstract chemical reactions to implement, highlighting its potential usefulness in the construction of biomolecular control circuits.

Simultaneous optimization of biomolecular energy function on features from small molecules and macromolecules

PubMed Central

Park, Hahnbeom; Bradley, Philip; Greisen, Per; Liu, Yuan; Mulligan, Vikram Khipple; Kim, David E.; Baker, David; DiMaio, Frank

2017-01-01

Most biomolecular modeling energy functions for structure prediction, sequence design, and molecular docking, have been parameterized using existing macromolecular structural data; this contrasts molecular mechanics force fields which are largely optimized using small-molecule data. In this study, we describe an integrated method that enables optimization of a biomolecular modeling energy function simultaneously against small-molecule thermodynamic data and high-resolution macromolecular structural data. We use this approach to develop a next-generation Rosetta energy function that utilizes a new anisotropic implicit solvation model, and an improved electrostatics and Lennard-Jones model, illustrating how energy functions can be considerably improved in their ability to describe large-scale energy landscapes by incorporating both small-molecule and macromolecule data. The energy function improves performance in a wide range of protein structure prediction challenges, including monomeric structure prediction, protein-protein and protein-ligand docking, protein sequence design, and prediction of the free energy changes by mutation, while reasonably recapitulating small-molecule thermodynamic properties. PMID:27766851

A common-path phase-shift interferometry surface plasmon imaging system

NASA Astrophysics Data System (ADS)

Su, Y.-T.; Chen, Shean-Jen; Yeh, T.-L.

2005-03-01

A biosensing imaging system is proposed based on the integration of surface plasmon resonance (SPR) and common-path phase-shift interferometry (PSI) techniques to measure the two-dimensional spatial phase variation caused by biomolecular interactions upon a sensing chip. The SPR phase imaging system can offer high resolution and high-throughout screening capabilities to analyze microarray biomolecular interaction without the need for additional labeling. With the long-term stability advantage of the common-path PSI technique even with external disturbances such as mechanical vibration, buffer flow noise, and laser unstable issue, the system can match the demand of real-time kinetic study for biomolecular interaction analysis (BIA). The SPR-PSI imaging system has achieved a detection limit of 2×10-7 refraction index change, a long-term phase stability of 2.5x10-4π rms over four hours, and a spatial phase resolution of 10-3 π with a lateral resolution of 100μm.

The Biomolecular Interaction Network Database and related tools 2005 update

PubMed Central

Alfarano, C.; Andrade, C. E.; Anthony, K.; Bahroos, N.; Bajec, M.; Bantoft, K.; Betel, D.; Bobechko, B.; Boutilier, K.; Burgess, E.; Buzadzija, K.; Cavero, R.; D'Abreo, C.; Donaldson, I.; Dorairajoo, D.; Dumontier, M. J.; Dumontier, M. R.; Earles, V.; Farrall, R.; Feldman, H.; Garderman, E.; Gong, Y.; Gonzaga, R.; Grytsan, V.; Gryz, E.; Gu, V.; Haldorsen, E.; Halupa, A.; Haw, R.; Hrvojic, A.; Hurrell, L.; Isserlin, R.; Jack, F.; Juma, F.; Khan, A.; Kon, T.; Konopinsky, S.; Le, V.; Lee, E.; Ling, S.; Magidin, M.; Moniakis, J.; Montojo, J.; Moore, S.; Muskat, B.; Ng, I.; Paraiso, J. P.; Parker, B.; Pintilie, G.; Pirone, R.; Salama, J. J.; Sgro, S.; Shan, T.; Shu, Y.; Siew, J.; Skinner, D.; Snyder, K.; Stasiuk, R.; Strumpf, D.; Tuekam, B.; Tao, S.; Wang, Z.; White, M.; Willis, R.; Wolting, C.; Wong, S.; Wrong, A.; Xin, C.; Yao, R.; Yates, B.; Zhang, S.; Zheng, K.; Pawson, T.; Ouellette, B. F. F.; Hogue, C. W. V.

2005-01-01

The Biomolecular Interaction Network Database (BIND) (http://bind.ca) archives biomolecular interaction, reaction, complex and pathway information. Our aim is to curate the details about molecular interactions that arise from published experimental research and to provide this information, as well as tools to enable data analysis, freely to researchers worldwide. BIND data are curated into a comprehensive machine-readable archive of computable information and provides users with methods to discover interactions and molecular mechanisms. BIND has worked to develop new methods for visualization that amplify the underlying annotation of genes and proteins to facilitate the study of molecular interaction networks. BIND has maintained an open database policy since its inception in 1999. Data growth has proceeded at a tremendous rate, approaching over 100 000 records. New services provided include a new BIND Query and Submission interface, a Standard Object Access Protocol service and the Small Molecule Interaction Database (http://smid.blueprint.org) that allows users to determine probable small molecule binding sites of new sequences and examine conserved binding residues. PMID:15608229

Biomolecular filters for improved separation of output signals in enzyme logic systems applied to biomedical analysis.

PubMed

Halámek, Jan; Zhou, Jian; Halámková, Lenka; Bocharova, Vera; Privman, Vladimir; Wang, Joseph; Katz, Evgeny

2011-11-15

Biomolecular logic systems processing biochemical input signals and producing "digital" outputs in the form of YES/NO were developed for analysis of physiological conditions characteristic of liver injury, soft tissue injury, and abdominal trauma. Injury biomarkers were used as input signals for activating the logic systems. Their normal physiological concentrations were defined as logic-0 level, while their pathologically elevated concentrations were defined as logic-1 values. Since the input concentrations applied as logic 0 and 1 values were not sufficiently different, the output signals being at low and high values (0, 1 outputs) were separated with a short gap making their discrimination difficult. Coupled enzymatic reactions functioning as a biomolecular signal processing system with a built-in filter property were developed. The filter process involves a partial back-conversion of the optical-output-signal-yielding product, but only at its low concentrations, thus allowing the proper discrimination between 0 and 1 output values.

Robust and Efficient Biomolecular Clustering of Tumor Based on ${p}$ -Norm Singular Value Decomposition.

PubMed

Kong, Xiang-Zhen; Liu, Jin-Xing; Zheng, Chun-Hou; Hou, Mi-Xiao; Wang, Juan

2017-07-01

High dimensionality has become a typical feature of biomolecular data. In this paper, a novel dimension reduction method named p-norm singular value decomposition (PSVD) is proposed to seek the low-rank approximation matrix to the biomolecular data. To enhance the robustness to outliers, the Lp-norm is taken as the error function and the Schatten p-norm is used as the regularization function in the optimization model. To evaluate the performance of PSVD, the Kmeans clustering method is then employed for tumor clustering based on the low-rank approximation matrix. Extensive experiments are carried out on five gene expression data sets including two benchmark data sets and three higher dimensional data sets from the cancer genome atlas. The experimental results demonstrate that the PSVD-based method outperforms many existing methods. Especially, it is experimentally proved that the proposed method is more efficient for processing higher dimensional data with good robustness, stability, and superior time performance.

Monolayers of derivatized poly(l-lysine)-grafted poly(ethylene glycol) on metal oxides as a class of biomolecular interfaces

PubMed Central

Ruiz-Taylor, L. A.; Martin, T. L.; Zaugg, F. G.; Witte, K.; Indermuhle, P.; Nock, S.; Wagner, P.

2001-01-01

We report on the design and characterization of a class of biomolecular interfaces based on derivatized poly(l-lysine)-grafted poly(ethylene glycol) copolymers adsorbed on negatively charged surfaces. As a model system, we synthesized biotin-derivatized poly(l-lysine)-grafted poly(ethylene glycol) copolymers, PLL-g-[(PEGm)(1−x) (PEG-biotin)x], where x varies from 0 to 1. Monolayers were produced on titanium dioxide substrates and characterized by x-ray photoelectron spectroscopy. The specific biorecognition properties of these biotinylated surfaces were investigated with the use of radiolabeled streptavidin alone and within complex protein mixtures. The PLL-g-PEG-biotin monolayers specifically capture streptavidin, even from a complex protein mixture, while still preventing nonspecific adsorption of other proteins. This streptavidin layer can subsequently capture biotinylated proteins. Finally, with the use of microfluidic networks and protein arraying, we demonstrate the potential of this class of biomolecular interfaces for applications based on protein patterning. PMID:11158560

Biomolecular solid state NMR with magic-angle spinning at 25K.

PubMed

Thurber, Kent R; Tycko, Robert

2008-12-01

A magic-angle spinning (MAS) probe has been constructed which allows the sample to be cooled with helium, while the MAS bearing and drive gases are nitrogen. The sample can be cooled to 25K using roughly 3 L/h of liquid helium, while the 4-mm diameter rotor spins at 6.7 kHz with good stability (+/-5 Hz) for many hours. Proton decoupling fields up to at least 130 kHz can be applied. This helium-cooled MAS probe enables a variety of one-dimensional and two-dimensional NMR experiments on biomolecular solids and other materials at low temperatures, with signal-to-noise proportional to 1/T. We show examples of low-temperature (13)C NMR data for two biomolecular samples, namely the peptide Abeta(14-23) in the form of amyloid fibrils and the protein HP35 in frozen glycerol/water solution. Issues related to temperature calibration, spin-lattice relaxation at low temperatures, paramagnetic doping of frozen solutions, and (13)C MAS NMR linewidths are discussed.

The challenges of informatics in synthetic biology: from biomolecular networks to artificial organisms

PubMed Central

Ramoni, Marco F.

2010-01-01

The field of synthetic biology holds an inspiring vision for the future; it integrates computational analysis, biological data and the systems engineering paradigm in the design of new biological machines and systems. These biological machines are built from basic biomolecular components analogous to electrical devices, and the information flow among these components requires the augmentation of biological insight with the power of a formal approach to information management. Here we review the informatics challenges in synthetic biology along three dimensions: in silico, in vitro and in vivo. First, we describe state of the art of the in silico support of synthetic biology, from the specific data exchange formats, to the most popular software platforms and algorithms. Next, we cast in vitro synthetic biology in terms of information flow, and discuss genetic fidelity in DNA manipulation, development strategies of biological parts and the regulation of biomolecular networks. Finally, we explore how the engineering chassis can manipulate biological circuitries in vivo to give rise to future artificial organisms. PMID:19906839

Rapid prototyping of nanofluidic systems using size-reduced electrospun nanofibers for biomolecular analysis.

PubMed

Park, Seung-Min; Huh, Yun Suk; Szeto, Kylan; Joe, Daniel J; Kameoka, Jun; Coates, Geoffrey W; Edel, Joshua B; Erickson, David; Craighead, Harold G

2010-11-05

Biomolecular transport in nanofluidic confinement offers various means to investigate the behavior of biomolecules in their native aqueous environments, and to develop tools for diverse single-molecule manipulations. Recently, a number of simple nanofluidic fabrication techniques has been demonstrated that utilize electrospun nanofibers as a backbone structure. These techniques are limited by the arbitrary dimension of the resulting nanochannels due to the random nature of electrospinning. Here, a new method for fabricating nanofluidic systems from size-reduced electrospun nanofibers is reported and demonstrated. As it is demonstrated, this method uses the scanned electrospinning technique for generation of oriented sacrificial nanofibers and exposes these nanofibers to harsh, but isotropic etching/heating environments to reduce their cross-sectional dimension. The creation of various nanofluidic systems as small as 20 nm is demonstrated, and practical examples of single biomolecular handling, such as DNA elongation in nanochannels and fluorescence correlation spectroscopic analysis of biomolecules passing through nanochannels, are provided.

An autonomous molecular computer for logical control of gene expression

PubMed Central

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

SASSIE: A program to study intrinsically disordered biological molecules and macromolecular ensembles using experimental scattering restraints

NASA Astrophysics Data System (ADS)

Curtis, Joseph E.; Raghunandan, Sindhu; Nanda, Hirsh; Krueger, Susan

2012-02-01

A program to construct ensembles of biomolecular structures that are consistent with experimental scattering data are described. Specifically, we generate an ensemble of biomolecular structures by varying sets of backbone dihedral angles that are then filtered using experimentally determined restraints to rapidly determine structures that have scattering profiles that are consistent with scattering data. We discuss an application of these tools to predict a set of structures for the HIV-1 Gag protein, an intrinsically disordered protein, that are consistent with small-angle neutron scattering experimental data. We have assembled these algorithms into a program called SASSIE for structure generation, visualization, and analysis of intrinsically disordered proteins and other macromolecular ensembles using neutron and X-ray scattering restraints. Program summaryProgram title: SASSIE Catalogue identifier: AEKL_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEKL_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License v3 No. of lines in distributed program, including test data, etc.: 3 991 624 No. of bytes in distributed program, including test data, etc.: 826 Distribution format: tar.gz Programming language: Python, C/C++, Fortran Computer: PC/Mac Operating system: 32- and 64-bit Linux (Ubuntu 10.04, Centos 5.6) and Mac OS X (10.6.6) RAM: 1 GB Classification: 3 External routines: Python 2.6.5, numpy 1.4.0, swig 1.3.40, scipy 0.8.0, Gnuplot-py-1.8, Tcl 8.5, Tk 8.5, Mac installation requires aquaterm 1.0 (or X window system) and Xcode 3 development tools. Nature of problem: Open source software to generate structures of disordered biological molecules that subsequently allow for the comparison of computational and experimental results is limiting the use of scattering resources. Solution method: Starting with an all atom model of a protein, for example, users can input regions to vary dihedral angles, ensembles of structures can be generated. Additionally, simple two-body rigid-body rotations are supported with and without disordered regions. Generated structures can then be used to calculate small-angle scattering profiles which can then be filtered against experimentally determined data. Filtered structures can be visualized individually or as an ensemble using density plots. In the modular and expandable program framework the user can easily access our subroutines and structural coordinates can be easily obtained for study using other computational physics methods. Additional comments: The distribution file for this program is over 159 Mbytes and therefore is not delivered directly when download or Email is requested. Instead an html file giving details of how the program can be obtained is sent. Running time: Varies depending on application. Typically 10 minutes to 24 hours depending on the number of generated structures.

Changes in biomolecular profile in a single nucleolus during cell fixation.

PubMed

Kuzmin, Andrey N; Pliss, Artem; Prasad, Paras N

2014-11-04

Fixation of biological sample is an essential technique applied in order to "freeze" in time the intracellular molecular content. However, fixation induces changes of the cellular molecular structure, which mask physiological distribution of biomolecules and bias interpretation of results. Accurate, sensitive, and comprehensive characterization of changes in biomolecular composition, occurring during fixation, is crucial for proper analysis of experimental data. Here we apply biomolecular component analysis for Raman spectra measured in the same nucleoli of HeLa cells before and after fixation by either formaldehyde solution or by chilled ethanol. It is found that fixation in formaldehyde does not strongly affect the Raman spectra of nucleolar biomolecular components, but may significantly decrease the nucleolar RNA concentration. At the same time, ethanol fixation leads to a proportional increase (up to 40%) in concentrations of nucleolar proteins and RNA, most likely due to cell shrinkage occurring in the presence of coagulant fixative. Ethanol fixation also triggers changes in composition of nucleolar proteome, as indicated by an overall reduction of the α-helical structure of proteins and increase in the concentration of proteins containing the β-sheet conformation. We conclude that cross-linking fixation is a more appropriate protocol for mapping of proteins in situ. At the same time, ethanol fixation is preferential for studies of RNA-containing macromolecules. We supplemented our quantitative Raman spectroscopic measurements with mapping of the protein and lipid macromolecular groups in live and fixed cells using coherent anti-Stokes Raman scattering nonlinear optical imaging.

Specificity and Affinity Quantification of Flexible Recognition from Underlying Energy Landscape Topography

PubMed Central

Chu, Xiakun; Wang, Jin

2014-01-01

Flexibility in biomolecular recognition is essential and critical for many cellular activities. Flexible recognition often leads to moderate affinity but high specificity, in contradiction with the conventional wisdom that high affinity and high specificity are coupled. Furthermore, quantitative understanding of the role of flexibility in biomolecular recognition is still challenging. Here, we meet the challenge by quantifying the intrinsic biomolecular recognition energy landscapes with and without flexibility through the underlying density of states. We quantified the thermodynamic intrinsic specificity by the topography of the intrinsic binding energy landscape and the kinetic specificity by association rate. We found that the thermodynamic and kinetic specificity are strongly correlated. Furthermore, we found that flexibility decreases binding affinity on one hand, but increases binding specificity on the other hand, and the decreasing or increasing proportion of affinity and specificity are strongly correlated with the degree of flexibility. This shows more (less) flexibility leads to weaker (stronger) coupling between affinity and specificity. Our work provides a theoretical foundation and quantitative explanation of the previous qualitative studies on the relationship among flexibility, affinity and specificity. In addition, we found that the folding energy landscapes are more funneled with binding, indicating that binding helps folding during the recognition. Finally, we demonstrated that the whole binding-folding energy landscapes can be integrated by the rigid binding and isolated folding energy landscapes under weak flexibility. Our results provide a novel way to quantify the affinity and specificity in flexible biomolecular recognition. PMID:25144525

Specificity and affinity quantification of flexible recognition from underlying energy landscape topography.

PubMed

Chu, Xiakun; Wang, Jin

2014-08-01

Flexibility in biomolecular recognition is essential and critical for many cellular activities. Flexible recognition often leads to moderate affinity but high specificity, in contradiction with the conventional wisdom that high affinity and high specificity are coupled. Furthermore, quantitative understanding of the role of flexibility in biomolecular recognition is still challenging. Here, we meet the challenge by quantifying the intrinsic biomolecular recognition energy landscapes with and without flexibility through the underlying density of states. We quantified the thermodynamic intrinsic specificity by the topography of the intrinsic binding energy landscape and the kinetic specificity by association rate. We found that the thermodynamic and kinetic specificity are strongly correlated. Furthermore, we found that flexibility decreases binding affinity on one hand, but increases binding specificity on the other hand, and the decreasing or increasing proportion of affinity and specificity are strongly correlated with the degree of flexibility. This shows more (less) flexibility leads to weaker (stronger) coupling between affinity and specificity. Our work provides a theoretical foundation and quantitative explanation of the previous qualitative studies on the relationship among flexibility, affinity and specificity. In addition, we found that the folding energy landscapes are more funneled with binding, indicating that binding helps folding during the recognition. Finally, we demonstrated that the whole binding-folding energy landscapes can be integrated by the rigid binding and isolated folding energy landscapes under weak flexibility. Our results provide a novel way to quantify the affinity and specificity in flexible biomolecular recognition.

Peptide crystal simulations reveal hidden dynamics

PubMed Central

Janowski, Pawel A.; Cerutti, David S.; Holton, James; Case, David A.

2013-01-01

Molecular dynamics simulations of biomolecular crystals at atomic resolution have the potential to recover information on dynamics and heterogeneity hidden in the X-ray diffraction data. We present here 9.6 microseconds of dynamics in a small helical peptide crystal with 36 independent copies of the unit cell. The average simulation structure agrees with experiment to within 0.28 Å backbone and 0.42 Å all-atom rmsd; a model refined against the average simulation density agrees with the experimental structure to within 0.20 Å backbone and 0.33 Å all-atom rmsd. The R-factor between the experimental structure factors and those derived from this unrestrained simulation is 23% to 1.0 Å resolution. The B-factors for most heavy atoms agree well with experiment (Pearson correlation of 0.90), but B-factors obtained by refinement against the average simulation density underestimate the coordinate fluctuations in the underlying simulation where the simulation samples alternate conformations. A dynamic flow of water molecules through channels within the crystal lattice is observed, yet the average water density is in remarkable agreement with experiment. A minor population of unit cells is characterized by reduced water content, 310 helical propensity and a gauche(−) side-chain rotamer for one of the valine residues. Careful examination of the experimental data suggests that transitions of the helices are a simulation artifact, although there is indeed evidence for alternate valine conformers and variable water content. This study highlights the potential for crystal simulations to detect dynamics and heterogeneity in experimental diffraction data, as well as to validate computational chemistry methods. PMID:23631449

Van’t Hoff global analyses of variable temperature isothermal titration calorimetry data

PubMed Central

Freiburger, Lee A.; Auclair, Karine; Mittermaier, Anthony K.

2016-01-01

Isothermal titration calorimetry (ITC) can provide detailed information on the thermodynamics of biomolecular interactions in the form of equilibrium constants, KA, and enthalpy changes, ΔHA. A powerful application of this technique involves analyzing the temperature dependences of ITC-derived KA and ΔHA values to gain insight into thermodynamic linkage between binding and additional equilibria, such as protein folding. We recently developed a general method for global analysis of variable temperature ITC data that significantly improves the accuracy of extracted thermodynamic parameters and requires no prior knowledge of the coupled equilibria. Here we report detailed validation of this method using Monte Carlo simulations and an application to study coupled folding and binding in an aminoglycoside acetyltransferase enzyme. PMID:28018008

Communication: Probing anomalous diffusion in frequency space

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stachura, Sławomir; Synchrotron Soleil, L’Orme de Merisiers, 91192 Gif-sur-Yvette; Kneller, Gerald R., E-mail: gerald.kneller@cnrs-orleans.fr

Anomalous diffusion processes are usually detected by analyzing the time-dependent mean square displacement of the diffusing particles. The latter evolves asymptotically as W(t) ∼ 2D{sub α}t{sup α}, where D{sub α} is the fractional diffusion constant and 0 < α < 2. In this article we show that both D{sub α} and α can also be extracted from the low-frequency Fourier spectrum of the corresponding velocity autocorrelation function. This offers a simple method for the interpretation of quasielastic neutron scattering spectra from complex (bio)molecular systems, in which subdiffusive transport is frequently encountered. The approach is illustrated and validated by analyzing molecularmore » dynamics simulations of molecular diffusion in a lipid POPC bilayer.« less

Numerical simulation studies for optical properties of biomaterials

NASA Astrophysics Data System (ADS)

Krasnikov, I.; Seteikin, A.

2016-11-01

Biophotonics involves understanding how light interacts with biological matter, from molecules and cells, to tissues and even whole organisms. Light can be used to probe biomolecular events, such as gene expression and protein-protein interaction, with impressively high sensitivity and specificity. The spatial and temporal distribution of biochemical constituents can also be visualized with light and, thus, the corresponding physiological dynamics in living cells, tissues, and organisms in real time. Computer-based Monte Carlo (MC) models of light transport in turbid media take a different approach. In this paper, the optical and structural properties of biomaterials discussed. We explain the numerical simulationmethod used for studying the optical properties of biomaterials. Applications of the Monte-Carlo method in photodynamic therapy, skin tissue optics, and bioimaging described.

A current affair: electrotherapy in wound healing

PubMed Central

Hunckler, Jerome; de Mel, Achala

2017-01-01

New developments in accelerating wound healing can have immense beneficial socioeconomic impact. The wound healing process is a highly orchestrated series of mechanisms where a multitude of cells and biological cascades are involved. The skin battery and current of injury mechanisms have become topics of interest for their influence in chronic wounds. Electrostimulation therapy of wounds has shown to be a promising treatment option with no-device-related adverse effects. This review presents an overview of the understanding and use of applied electrical current in various aspects of wound healing. Rapid clinical translation of the evolving understanding of biomolecular mechanisms underlying the effects of electrical simulation on wound healing would positively impact upon enhancing patient’s quality of life. PMID:28461755

Effect of flavonols on wine astringency and their interaction with human saliva.

PubMed

Ferrer-Gallego, Raúl; Brás, Natércia F; García-Estévez, Ignacio; Mateus, Nuno; Rivas-Gonzalo, Julián C; de Freitas, Victor; Escribano-Bailón, M Teresa

2016-10-15

The addition of external phenolic compounds to wines in order to improve their sensory quality is an established winemaking practice. This study was aimed at evaluating the effect of the addition of quercetin 3-O-glucoside on the astringency and bitterness of wines. Sensory results showed that the addition of this flavonol to wines results in an increase in astringency and bitterness. Additionally, flavonol-human salivary protein interactions were studied using fluorescence spectroscopy, dynamic light scattering and molecular dynamic simulations (MD). The apparent Stern-Volmer (KsvApp) and the apparent bimolecular quenching constants (kqApp) were calculated from fluorescence spectra. The KsvApp was 12620±390M(-1), and the apparent biomolecular constant was 3.94×10(12)M(-1)s(-1), which suggests that a complex was formed between the human salivary proteins and quercetin 3-O-glucoside. MD simulations showed that the quercetin 3-O-glucoside molecules have the ability to bind to the IB937 model peptide. Copyright © 2016 Elsevier Ltd. All rights reserved.

Frequency adaptive metadynamics for the calculation of rare-event kinetics

NASA Astrophysics Data System (ADS)

Wang, Yong; Valsson, Omar; Tiwary, Pratyush; Parrinello, Michele; Lindorff-Larsen, Kresten

2018-08-01

The ability to predict accurate thermodynamic and kinetic properties in biomolecular systems is of both scientific and practical utility. While both remain very difficult, predictions of kinetics are particularly difficult because rates, in contrast to free energies, depend on the route taken. For this reason, specific enhanced sampling methods are needed to calculate long-time scale kinetics. It has recently been demonstrated that it is possible to recover kinetics through the so-called "infrequent metadynamics" simulations, where the simulations are biased in a way that minimally corrupts the dynamics of moving between metastable states. This method, however, requires the bias to be added slowly, thus hampering applications to processes with only modest separations of time scales. Here we present a frequency-adaptive strategy which bridges normal and infrequent metadynamics. We show that this strategy can improve the precision and accuracy of rate calculations at fixed computational cost and should be able to extend rate calculations for much slower kinetic processes.

A new force field including charge directionality for TMAO in aqueous solution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Usui, Kota; Nagata, Yuki, E-mail: sulpizi@uni-mainz.de, E-mail: nagata@mpip-mainz.mpg.de; Hunger, Johannes

We propose a new force field for trimethylamine N-oxide (TMAO), which is designed to reproduce the long-lived and highly directional hydrogen bond between the TMAO oxygen (O{sub TMAO}) atom and surrounding water molecules. Based on the data obtained by ab initio molecular dynamics simulations, we introduce three dummy sites around O{sub TMAO} to mimic the O{sub TMAO} lone pairs and we migrate the negative charge on the O{sub TMAO} to the dummy sites. The force field model developed here improves both structural and dynamical properties of aqueous TMAO solutions. Moreover, it reproduces the experimentally observed dependence of viscosity upon increasingmore » TMAO concentration quantitatively. The simple procedure of the force field construction makes it easy to implement in molecular dynamics simulation packages and makes it compatible with the existing biomolecular force fields. This paves the path for further investigation of protein-TMAO interaction in aqueous solutions.« less

An overview of tools for the validation of protein NMR structures.

PubMed

Vuister, Geerten W; Fogh, Rasmus H; Hendrickx, Pieter M S; Doreleijers, Jurgen F; Gutmanas, Aleksandras

2014-04-01

Biomolecular structures at atomic resolution present a valuable resource for the understanding of biology. NMR spectroscopy accounts for 11% of all structures in the PDB repository. In response to serious problems with the accuracy of some of the NMR-derived structures and in order to facilitate proper analysis of the experimental models, a number of program suites are available. We discuss nine of these tools in this review: PROCHECK-NMR, PSVS, GLM-RMSD, CING, Molprobity, Vivaldi, ResProx, NMR constraints analyzer and QMEAN. We evaluate these programs for their ability to assess the structural quality, restraints and their violations, chemical shifts, peaks and the handling of multi-model NMR ensembles. We document both the input required by the programs and output they generate. To discuss their relative merits we have applied the tools to two representative examples from the PDB: a small, globular monomeric protein (Staphylococcal nuclease from S. aureus, PDB entry 2kq3) and a small, symmetric homodimeric protein (a region of human myosin-X, PDB entry 2lw9).

Raman Optical Activity of Biological Molecules

NASA Astrophysics Data System (ADS)

Blanch, Ewan W.; Barron, Laurence D.

Now an incisive probe of biomolecular structure, Raman optical activity (ROA) measures a small difference in Raman scattering from chiral molecules in right- and left-circularly polarized light. As ROA spectra measure vibrational optical activity, they contain highly informative band structures sensitive to the secondary and tertiary structures of proteins, nucleic acids, viruses and carbohydrates as well as the absolute configurations of small molecules. In this review we present a survey of recent studies on biomolecular structure and dynamics using ROA and also a discussion of future applications of this powerful new technique in biomedical research.

GENESIS: a hybrid-parallel and multi-scale molecular dynamics simulator with enhanced sampling algorithms for biomolecular and cellular simulations.

PubMed

Jung, Jaewoon; Mori, Takaharu; Kobayashi, Chigusa; Matsunaga, Yasuhiro; Yoda, Takao; Feig, Michael; Sugita, Yuji

2015-07-01

GENESIS (Generalized-Ensemble Simulation System) is a new software package for molecular dynamics (MD) simulations of macromolecules. It has two MD simulators, called ATDYN and SPDYN. ATDYN is parallelized based on an atomic decomposition algorithm for the simulations of all-atom force-field models as well as coarse-grained Go-like models. SPDYN is highly parallelized based on a domain decomposition scheme, allowing large-scale MD simulations on supercomputers. Hybrid schemes combining OpenMP and MPI are used in both simulators to target modern multicore computer architectures. Key advantages of GENESIS are (1) the highly parallel performance of SPDYN for very large biological systems consisting of more than one million atoms and (2) the availability of various REMD algorithms (T-REMD, REUS, multi-dimensional REMD for both all-atom and Go-like models under the NVT, NPT, NPAT, and NPγT ensembles). The former is achieved by a combination of the midpoint cell method and the efficient three-dimensional Fast Fourier Transform algorithm, where the domain decomposition space is shared in real-space and reciprocal-space calculations. Other features in SPDYN, such as avoiding concurrent memory access, reducing communication times, and usage of parallel input/output files, also contribute to the performance. We show the REMD simulation results of a mixed (POPC/DMPC) lipid bilayer as a real application using GENESIS. GENESIS is released as free software under the GPLv2 licence and can be easily modified for the development of new algorithms and molecular models. WIREs Comput Mol Sci 2015, 5:310-323. doi: 10.1002/wcms.1220.

Complex molecular assemblies at hand via interactive simulations.

PubMed

Delalande, Olivier; Férey, Nicolas; Grasseau, Gilles; Baaden, Marc

2009-11-30

Studying complex molecular assemblies interactively is becoming an increasingly appealing approach to molecular modeling. Here we focus on interactive molecular dynamics (IMD) as a textbook example for interactive simulation methods. Such simulations can be useful in exploring and generating hypotheses about the structural and mechanical aspects of biomolecular interactions. For the first time, we carry out low-resolution coarse-grain IMD simulations. Such simplified modeling methods currently appear to be more suitable for interactive experiments and represent a well-balanced compromise between an important gain in computational speed versus a moderate loss in modeling accuracy compared to higher resolution all-atom simulations. This is particularly useful for initial exploration and hypothesis development for rare molecular interaction events. We evaluate which applications are currently feasible using molecular assemblies from 1900 to over 300,000 particles. Three biochemical systems are discussed: the guanylate kinase (GK) enzyme, the outer membrane protease T and the soluble N-ethylmaleimide-sensitive factor attachment protein receptors complex involved in membrane fusion. We induce large conformational changes, carry out interactive docking experiments, probe lipid-protein interactions and are able to sense the mechanical properties of a molecular model. Furthermore, such interactive simulations facilitate exploration of modeling parameters for method improvement. For the purpose of these simulations, we have developed a freely available software library called MDDriver. It uses the IMD protocol from NAMD and facilitates the implementation and application of interactive simulations. With MDDriver it becomes very easy to render any particle-based molecular simulation engine interactive. Here we use its implementation in the Gromacs software as an example. Copyright 2009 Wiley Periodicals, Inc.

In silico concurrent multisite pH titration in proteins.

PubMed

Hu, Hao; Shen, Lin

2014-07-30

The concurrent proton binding at multiple sites in macromolecules such as proteins and nucleic acids is an important yet challenging problem in biochemistry. We develop an efficient generalized Hamiltonian approach to attack this issue. Based on the previously developed generalized-ensemble methods, an effective potential energy is constructed which combines the contributions of all (relevant) protonation states of the molecule. The effective potential preserves important phase regions of all states and, thus, allows efficient sampling of these regions in one simulation. The need for intermediate states in alchemical free energy simulations is greatly reduced. Free energy differences between different protonation states can be determined accurately and enable one to construct the grand canonical partition function. Therefore, the complicated concurrent multisite proton titration process of protein molecules can be satisfactorily simulated. Application of this method to the simulation of the pKa of Glu49, Asp50, and C-terminus of bovine pancreatic trypsin inhibitor shows reasonably good agreement with published experimental work. This method provides an unprecedented vivid picture of how different protonation states change their relative population upon pH titration. We believe that the method will be very useful in deciphering the molecular mechanism of pH-dependent biomolecular processes in terms of a detailed atomistic description. Copyright © 2014 Wiley Periodicals, Inc.

Distance-Based Configurational Entropy of Proteins from Molecular Dynamics Simulations

PubMed Central

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.

PubMed

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.

Molecular Dynamics based on a Generalized Born solvation model: application to protein folding

NASA Astrophysics Data System (ADS)

Onufriev, Alexey

2004-03-01

An accurate description of the aqueous environment is essential for realistic biomolecular simulations, but may become very expensive computationally. We have developed a version of the Generalized Born model suitable for describing large conformational changes in macromolecules. The model represents the solvent implicitly as continuum with the dielectric properties of water, and include charge screening effects of salt. The computational cost associated with the use of this model in Molecular Dynamics simulations is generally considerably smaller than the cost of representing water explicitly. Also, compared to traditional Molecular Dynamics simulations based on explicit water representation, conformational changes occur much faster in implicit solvation environment due to the absence of viscosity. The combined speed-up allow one to probe conformational changes that occur on much longer effective time-scales. We apply the model to folding of a 46-residue three helix bundle protein (residues 10-55 of protein A, PDB ID 1BDD). Starting from an unfolded structure at 450 K, the protein folds to the lowest energy state in 6 ns of simulation time, which takes about a day on a 16 processor SGI machine. The predicted structure differs from the native one by 2.4 A (backbone RMSD). Analysis of the structures seen on the folding pathway reveals details of the folding process unavailable form experiment.

Gay-Berne and electrostatic multipole based coarse-grain potential in implicit solvent

PubMed Central

Wu, Johnny; Zhen, Xia; Shen, Hujun; Li, Guohui; Ren, Pengyu

2011-01-01

A general, transferable coarse-grain (CG) framework based on the Gay-Berne potential and electrostatic point multipole expansion is presented for polypeptide simulations. The solvent effect is described by the Generalized Kirkwood theory. The CG model is calibrated using the results of all-atom simulations of model compounds in solution. Instead of matching the overall effective forces produced by atomic models, the fundamental intermolecular forces such as electrostatic, repulsion-dispersion, and solvation are represented explicitly at a CG level. We demonstrate that the CG alanine dipeptide model is able to reproduce quantitatively the conformational energy of all-atom force fields in both gas and solution phases, including the electrostatic and solvation components. Replica exchange molecular dynamics and microsecond dynamic simulations of polyalanine of 5 and 12 residues reveal that the CG polyalanines fold into “alpha helix” and “beta sheet” structures. The 5-residue polyalanine displays a substantial increase in the “beta strand” fraction relative to the 12-residue polyalanine. The detailed conformational distribution is compared with those reported from recent all-atom simulations and experiments. The results suggest that the new coarse-graining approach presented in this study has the potential to offer both accuracy and efficiency for biomolecular modeling. PMID:22029338

Integrating atomistic molecular dynamics simulations, experiments, and network analysis to study protein dynamics: strength in unity.

PubMed

Papaleo, Elena

2015-01-01

In the last years, we have been observing remarkable improvements in the field of protein dynamics. Indeed, we can now study protein dynamics in atomistic details over several timescales with a rich portfolio of experimental and computational techniques. On one side, this provides us with the possibility to validate simulation methods and physical models against a broad range of experimental observables. On the other side, it also allows a complementary and comprehensive view on protein structure and dynamics. What is needed now is a better understanding of the link between the dynamic properties that we observe and the functional properties of these important cellular machines. To make progresses in this direction, we need to improve the physical models used to describe proteins and solvent in molecular dynamics, as well as to strengthen the integration of experiments and simulations to overcome their own limitations. Moreover, now that we have the means to study protein dynamics in great details, we need new tools to understand the information embedded in the protein ensembles and in their dynamic signature. With this aim in mind, we should enrich the current tools for analysis of biomolecular simulations with attention to the effects that can be propagated over long distances and are often associated to important biological functions. In this context, approaches inspired by network analysis can make an important contribution to the analysis of molecular dynamics simulations.

A generic implementation of replica exchange with solute tempering (REST2) algorithm in NAMD for complex biophysical simulations

NASA Astrophysics Data System (ADS)

Jo, Sunhwan; Jiang, Wei

2015-12-01

Replica Exchange with Solute Tempering (REST2) is a powerful sampling enhancement algorithm of molecular dynamics (MD) in that it needs significantly smaller number of replicas but achieves higher sampling efficiency relative to standard temperature exchange algorithm. In this paper, we extend the applicability of REST2 for quantitative biophysical simulations through a robust and generic implementation in greatly scalable MD software NAMD. The rescaling procedure of force field parameters controlling REST2 "hot region" is implemented into NAMD at the source code level. A user can conveniently select hot region through VMD and write the selection information into a PDB file. The rescaling keyword/parameter is written in NAMD Tcl script interface that enables an on-the-fly simulation parameter change. Our implementation of REST2 is within communication-enabled Tcl script built on top of Charm++, thus communication overhead of an exchange attempt is vanishingly small. Such a generic implementation facilitates seamless cooperation between REST2 and other modules of NAMD to provide enhanced sampling for complex biomolecular simulations. Three challenging applications including native REST2 simulation for peptide folding-unfolding transition, free energy perturbation/REST2 for absolute binding affinity of protein-ligand complex and umbrella sampling/REST2 Hamiltonian exchange for free energy landscape calculation were carried out on IBM Blue Gene/Q supercomputer to demonstrate efficacy of REST2 based on the present implementation.

Insight into Factors Affecting the Presence, Degree, and Temporal Stability of Fluorescence Intensification on ZnO Nanorod Ends

PubMed Central

Singh, Manpreet; Jiang, Ruibin; Coia, Heidi; Choi, Daniel S.; Alabanza, Anginelle; Chang, Jae Young; Wang, Jianfang; Hahm, Jong-in

2014-01-01

We have carried out a combined experimental and simulation study identifying the key physical and optical parameters affecting the presence and degree of fluorescence intensification measured on zinc oxide nanorod (ZnO NR) ends. Previously, we reported on the highly localized, intensified, and prolonged fluorescence signal measured on the NR ends, termed as fluorescence intensification on NR ends (FINE). As a step towards understanding the mechanism of FINE, the present study aims to provide an insight into the unique optical phenomenon of FINE through experimental and simulation approaches and to elucidate the key factors affecting the occurrence, degree, and temporal stability of FINE. Specifically, we examined the effect of the length, width, and growth orientation of single ZnO NRs on the NR-enhanced biomolecular emission profile after decorating the NR surfaces with different amounts and types of fluorophore-coupled protein molecules. We quantitatively and qualitatively profiled the biomolecular fluorescence signal from individual ZnO NRs as a function of both position along the NR long axis and time. Regardless of the physical dimensions and growth orientations of the NRs, we confirmed the presence of FINE from all ZnO NRs tested by using a range of protein concentrations. We also showed that the manifestation of FINE is not dependent on the spectroscopic signatures of the fluorophores employed. We further observed that the degree of FINE is dependent on the length of the NR with longer NRs showing increased levels of FINE. We also demonstrated that vertically oriented NRs exhibit much stronger fluorescence intensity at the NR ends and a higher level of FINE than the laterally oriented NRs. Additionally, we employed finite-difference time-domain (FDTD) methods to understand the experimental outcomes and to promote our understanding of the mechanism of FINE. Particularly, we utilized the electrodynamic simulations to examine both near-field and far-field emission characteristics when considering various scenarios of fluorophore locations, polarizations, spectroscopic characteristics, and NR dimensions. Our efforts may provide a deeper insight into the unique optical phenomenon of FINE and further be beneficial to highly miniaturized biodetection favoring the use of single ZnO NRs in low-volume and high-throughput protein assays. PMID:25504319

Nature does not rely on long-lived electronic quantum coherence for photosynthetic energy transfer.

PubMed

Duan, Hong-Guang; Prokhorenko, Valentyn I; Cogdell, Richard J; Ashraf, Khuram; Stevens, Amy L; Thorwart, Michael; Miller, R J Dwayne

2017-08-08

During the first steps of photosynthesis, the energy of impinging solar photons is transformed into electronic excitation energy of the light-harvesting biomolecular complexes. The subsequent energy transfer to the reaction center is commonly rationalized in terms of excitons moving on a grid of biomolecular chromophores on typical timescales [Formula: see text]100 fs. Today's understanding of the energy transfer includes the fact that the excitons are delocalized over a few neighboring sites, but the role of quantum coherence is considered as irrelevant for the transfer dynamics because it typically decays within a few tens of femtoseconds. This orthodox picture of incoherent energy transfer between clusters of a few pigments sharing delocalized excitons has been challenged by ultrafast optical spectroscopy experiments with the Fenna-Matthews-Olson protein, in which interference oscillatory signals up to 1.5 ps were reported and interpreted as direct evidence of exceptionally long-lived electronic quantum coherence. Here, we show that the optical 2D photon echo spectra of this complex at ambient temperature in aqueous solution do not provide evidence of any long-lived electronic quantum coherence, but confirm the orthodox view of rapidly decaying electronic quantum coherence on a timescale of 60 fs. Our results can be considered as generic and give no hint that electronic quantum coherence plays any biofunctional role in real photoactive biomolecular complexes. Because in this structurally well-defined protein the distances between bacteriochlorophylls are comparable to those of other light-harvesting complexes, we anticipate that this finding is general and directly applies to even larger photoactive biomolecular complexes.

3D Printed Programmable Release Capsules.

PubMed

Gupta, Maneesh K; Meng, Fanben; Johnson, Blake N; Kong, Yong Lin; Tian, Limei; Yeh, Yao-Wen; Masters, Nina; Singamaneni, Srikanth; McAlpine, Michael C

2015-08-12

The development of methods for achieving precise spatiotemporal control over chemical and biomolecular gradients could enable significant advances in areas such as synthetic tissue engineering, biotic-abiotic interfaces, and bionanotechnology. Living organisms guide tissue development through highly orchestrated gradients of biomolecules that direct cell growth, migration, and differentiation. While numerous methods have been developed to manipulate and implement biomolecular gradients, integrating gradients into multiplexed, three-dimensional (3D) matrices remains a critical challenge. Here we present a method to 3D print stimuli-responsive core/shell capsules for programmable release of multiplexed gradients within hydrogel matrices. These capsules are composed of an aqueous core, which can be formulated to maintain the activity of payload biomolecules, and a poly(lactic-co-glycolic) acid (PLGA, an FDA approved polymer) shell. Importantly, the shell can be loaded with plasmonic gold nanorods (AuNRs), which permits selective rupturing of the capsule when irradiated with a laser wavelength specifically determined by the lengths of the nanorods. This precise control over space, time, and selectivity allows for the ability to pattern 2D and 3D multiplexed arrays of enzyme-loaded capsules along with tunable laser-triggered rupture and release of active enzymes into a hydrogel ambient. The advantages of this 3D printing-based method include (1) highly monodisperse capsules, (2) efficient encapsulation of biomolecular payloads, (3) precise spatial patterning of capsule arrays, (4) "on the fly" programmable reconfiguration of gradients, and (5) versatility for incorporation in hierarchical architectures. Indeed, 3D printing of programmable release capsules may represent a powerful new tool to enable spatiotemporal control over biomolecular gradients.

Solution NMR views of dynamical ordering of biomacromolecules.

PubMed

Ikeya, Teppei; Ban, David; Lee, Donghan; Ito, Yutaka; Kato, Koichi; Griesinger, Christian

2018-02-01

To understand the mechanisms related to the 'dynamical ordering' of macromolecules and biological systems, it is crucial to monitor, in detail, molecular interactions and their dynamics across multiple timescales. Solution nuclear magnetic resonance (NMR) spectroscopy is an ideal tool that can investigate biophysical events at the atomic level, in near-physiological buffer solutions, or even inside cells. In the past several decades, progress in solution NMR has significantly contributed to the elucidation of three-dimensional structures, the understanding of conformational motions, and the underlying thermodynamic and kinetic properties of biomacromolecules. This review discusses recent methodological development of NMR, their applications and some of the remaining challenges. Although a major drawback of NMR is its difficulty in studying the dynamical ordering of larger biomolecular systems, current technologies have achieved considerable success in the structural analysis of substantially large proteins and biomolecular complexes over 1MDa and have characterised a wide range of timescales across which biomolecular motion exists. While NMR is well suited to obtain local structure information in detail, it contributes valuable and unique information within hybrid approaches that combine complementary methodologies, including solution scattering and microscopic techniques. For living systems, the dynamic assembly and disassembly of macromolecular complexes is of utmost importance for cellular homeostasis and, if dysregulated, implied in human disease. It is thus instructive for the advancement of the study of the dynamical ordering to discuss the potential possibilities of solution NMR spectroscopy and its applications. This article is part of a Special Issue entitled "Biophysical Exploration of Dynamical Ordering of Biomolecular Systems" edited by Dr. Koichi Kato. Copyright © 2017 Elsevier B.V. All rights reserved.

Nature does not rely on long-lived electronic quantum coherence for photosynthetic energy transfer

NASA Astrophysics Data System (ADS)

Duan, Hong-Guang; Prokhorenko, Valentyn I.; Cogdell, Richard J.; Ashraf, Khuram; Stevens, Amy L.; Thorwart, Michael; Miller, R. J. Dwayne

2017-08-01

During the first steps of photosynthesis, the energy of impinging solar photons is transformed into electronic excitation energy of the light-harvesting biomolecular complexes. The subsequent energy transfer to the reaction center is commonly rationalized in terms of excitons moving on a grid of biomolecular chromophores on typical timescales <<100 fs. Today’s understanding of the energy transfer includes the fact that the excitons are delocalized over a few neighboring sites, but the role of quantum coherence is considered as irrelevant for the transfer dynamics because it typically decays within a few tens of femtoseconds. This orthodox picture of incoherent energy transfer between clusters of a few pigments sharing delocalized excitons has been challenged by ultrafast optical spectroscopy experiments with the Fenna-Matthews-Olson protein, in which interference oscillatory signals up to 1.5 ps were reported and interpreted as direct evidence of exceptionally long-lived electronic quantum coherence. Here, we show that the optical 2D photon echo spectra of this complex at ambient temperature in aqueous solution do not provide evidence of any long-lived electronic quantum coherence, but confirm the orthodox view of rapidly decaying electronic quantum coherence on a timescale of 60 fs. Our results can be considered as generic and give no hint that electronic quantum coherence plays any biofunctional role in real photoactive biomolecular complexes. Because in this structurally well-defined protein the distances between bacteriochlorophylls are comparable to those of other light-harvesting complexes, we anticipate that this finding is general and directly applies to even larger photoactive biomolecular complexes.

Systematic methods for defining coarse-grained maps in large biomolecules.

PubMed

Zhang, Zhiyong

2015-01-01

Large biomolecules are involved in many important biological processes. It would be difficult to use large-scale atomistic molecular dynamics (MD) simulations to study the functional motions of these systems because of the computational expense. Therefore various coarse-grained (CG) approaches have attracted rapidly growing interest, which enable simulations of large biomolecules over longer effective timescales than all-atom MD simulations. The first issue in CG modeling is to construct CG maps from atomic structures. In this chapter, we review the recent development of a novel and systematic method for constructing CG representations of arbitrarily complex biomolecules, in order to preserve large-scale and functionally relevant essential dynamics (ED) at the CG level. In this ED-CG scheme, the essential dynamics can be characterized by principal component analysis (PCA) on a structural ensemble, or elastic network model (ENM) of a single atomic structure. Validation and applications of the method cover various biological systems, such as multi-domain proteins, protein complexes, and even biomolecular machines. The results demonstrate that the ED-CG method may serve as a very useful tool for identifying functional dynamics of large biomolecules at the CG level.

Replica Exchange Gaussian Accelerated Molecular Dynamics: Improved Enhanced Sampling and Free Energy Calculation.

PubMed

Huang, Yu-Ming M; McCammon, J Andrew; Miao, Yinglong

2018-04-10

Through adding a harmonic boost potential to smooth the system potential energy surface, Gaussian accelerated molecular dynamics (GaMD) provides enhanced sampling and free energy calculation of biomolecules without the need of predefined reaction coordinates. This work continues to improve the acceleration power and energy reweighting of the GaMD by combining the GaMD with replica exchange algorithms. Two versions of replica exchange GaMD (rex-GaMD) are presented: force constant rex-GaMD and threshold energy rex-GaMD. During simulations of force constant rex-GaMD, the boost potential can be exchanged between replicas of different harmonic force constants with fixed threshold energy. However, the algorithm of threshold energy rex-GaMD tends to switch the threshold energy between lower and upper bounds for generating different levels of boost potential. Testing simulations on three model systems, including the alanine dipeptide, chignolin, and HIV protease, demonstrate that through continuous exchanges of the boost potential, the rex-GaMD simulations not only enhance the conformational transitions of the systems but also narrow down the distribution width of the applied boost potential for accurate energetic reweighting to recover biomolecular free energy profiles.

Gallium arsenide based surface plasmon resonance for glucose monitoring

NASA Astrophysics Data System (ADS)

Patil, Harshada; Sane, Vani; Sriram, G.; Indumathi, T. S; Sharan, Preeta

2015-07-01

The recent trends in the semiconductor and microwave industries has enabled the development of scalable microfabrication technology which produces a superior set of performance as against its counterparts. Surface Plasmon Resonance (SPR) based biosensors are a special class of optical sensors that become affected by electromagnetic waves. It is found that bio-molecular recognition element immobilized on the SPR sensor surface layer reveals a characteristic interaction with various sample solutions during the passage of light. The present work revolves around developing painless glucose monitoring systems using fluids containing glucose like saliva, urine, sweat or tears instead of blood samples. Non-invasive glucose monitoring has long been simulated using label free detection mechanisms and the same concept is adapted. In label-free detection, target molecules are not labeled or altered, and are detected in their natural forms. Label-free detection mechanisms involves the measurement of refractive index (RI) change induced by molecular interactions. These interactions relates the sample concentration or surface density, instead of total sample mass. After simulation it has been observed that the result obtained is highly accurate and sensitive. The structure used here is SPR sensor based on channel waveguide. The tools used for simulation are RSOFT FULLWAVE, MEEP and MATLAB etc.

Tailoring the Variational Implicit Solvent Method for New Challenges: Biomolecular Recognition and Assembly

PubMed Central

Ricci, Clarisse Gravina; Li, Bo; Cheng, Li-Tien; Dzubiella, Joachim; McCammon, J. Andrew

2018-01-01

Predicting solvation free energies and describing the complex water behavior that plays an important role in essentially all biological processes is a major challenge from the computational standpoint. While an atomistic, explicit description of the solvent can turn out to be too expensive in large biomolecular systems, most implicit solvent methods fail to capture “dewetting” effects and heterogeneous hydration by relying on a pre-established (i.e., guessed) solvation interface. Here we focus on the Variational Implicit Solvent Method, an implicit solvent method that adds water “plasticity” back to the picture by formulating the solvation free energy as a functional of all possible solvation interfaces. We survey VISM's applications to the problem of molecular recognition and report some of the most recent efforts to tailor VISM for more challenging scenarios, with the ultimate goal of including thermal fluctuations into the framework. The advances reported herein pave the way to make VISM a uniquely successful approach to characterize complex solvation properties in the recognition and binding of large-scale biomolecular complexes. PMID:29484300

A compact imaging spectroscopic system for biomolecular detections on plasmonic chips.

PubMed

Lo, Shu-Cheng; Lin, En-Hung; Wei, Pei-Kuen; Tsai, Wan-Shao

2016-10-17

In this study, we demonstrate a compact imaging spectroscopic system for high-throughput detection of biomolecular interactions on plasmonic chips, based on a curved grating as the key element of light diffraction and light focusing. Both the curved grating and the plasmonic chips are fabricated on flexible plastic substrates using a gas-assisted thermal-embossing method. A fiber-coupled broadband light source and a camera are included in the system. Spectral resolution within 1 nm is achieved in sensing environmental index solutions and protein bindings. The detected sensitivities of the plasmonic chip are comparable with a commercial spectrometer. An extra one-dimensional scanning stage enables high-throughput detection of protein binding on a designed plasmonic chip consisting of several nanoslit arrays with different periods. The detected resonance wavelengths match well with the grating equation under an air environment. Wavelength shifts between 1 and 9 nm are detected for antigens of various concentrations binding with antibodies. A simple, mass-productive and cost-effective method has been demonstrated on the imaging spectroscopic system for real-time, label-free, highly sensitive and high-throughput screening of biomolecular interactions.

The HADDOCK2.2 Web Server: User-Friendly Integrative Modeling of Biomolecular Complexes.

PubMed

van Zundert, G C P; Rodrigues, J P G L M; Trellet, M; Schmitz, C; Kastritis, P L; Karaca, E; Melquiond, A S J; van Dijk, M; de Vries, S J; Bonvin, A M J J

2016-02-22

The prediction of the quaternary structure of biomolecular macromolecules is of paramount importance for fundamental understanding of cellular processes and drug design. In the era of integrative structural biology, one way of increasing the accuracy of modeling methods used to predict the structure of biomolecular complexes is to include as much experimental or predictive information as possible in the process. This has been at the core of our information-driven docking approach HADDOCK. We present here the updated version 2.2 of the HADDOCK portal, which offers new features such as support for mixed molecule types, additional experimental restraints and improved protocols, all of this in a user-friendly interface. With well over 6000 registered users and 108,000 jobs served, an increasing fraction of which on grid resources, we hope that this timely upgrade will help the community to solve important biological questions and further advance the field. The HADDOCK2.2 Web server is freely accessible to non-profit users at http://haddock.science.uu.nl/services/HADDOCK2.2. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Investigating biomolecular recognition at the cell surface using atomic force microscopy.

PubMed

Wang, Congzhou; Yadavalli, Vamsi K

2014-05-01

Probing the interaction forces that drive biomolecular recognition on cell surfaces is essential for understanding diverse biological processes. Force spectroscopy has been a widely used dynamic analytical technique, allowing measurement of such interactions at the molecular and cellular level. The capabilities of working under near physiological environments, combined with excellent force and lateral resolution make atomic force microscopy (AFM)-based force spectroscopy a powerful approach to measure biomolecular interaction forces not only on non-biological substrates, but also on soft, dynamic cell surfaces. Over the last few years, AFM-based force spectroscopy has provided biophysical insight into how biomolecules on cell surfaces interact with each other and induce relevant biological processes. In this review, we focus on describing the technique of force spectroscopy using the AFM, specifically in the context of probing cell surfaces. We summarize recent progress in understanding the recognition and interactions between macromolecules that may be found at cell surfaces from a force spectroscopy perspective. We further discuss the challenges and future prospects of the application of this versatile technique. Copyright © 2014 Elsevier Ltd. All rights reserved.

A detailed experimental study of a DNA computer with two endonucleases.

PubMed

Sakowski, Sebastian; Krasiński, Tadeusz; Sarnik, Joanna; Blasiak, Janusz; Waldmajer, Jacek; Poplawski, Tomasz

2017-07-14

Great advances in biotechnology have allowed the construction of a computer from DNA. One of the proposed solutions is a biomolecular finite automaton, a simple two-state DNA computer without memory, which was presented by Ehud Shapiro's group at the Weizmann Institute of Science. The main problem with this computer, in which biomolecules carry out logical operations, is its complexity - increasing the number of states of biomolecular automata. In this study, we constructed (in laboratory conditions) a six-state DNA computer that uses two endonucleases (e.g. AcuI and BbvI) and a ligase. We have presented a detailed experimental verification of its feasibility. We described the effect of the number of states, the length of input data, and the nondeterminism on the computing process. We also tested different automata (with three, four, and six states) running on various accepted input words of different lengths such as ab, aab, aaab, ababa, and of an unaccepted word ba. Moreover, this article presents the reaction optimization and the methods of eliminating certain biochemical problems occurring in the implementation of a biomolecular DNA automaton based on two endonucleases.

Construction of RNA-Quantum Dot Chimera for Nanoscale Resistive Biomemory Application.

PubMed

Lee, Taek; Yagati, Ajay Kumar; Pi, Fengmei; Sharma, Ashwani; Choi, Jeong-Woo; Guo, Peixuan

2015-07-28

RNA nanotechnology offers advantages to construct thermally and chemically stable nanoparticles with well-defined shape and structure. Here we report the development of an RNA-QD (quantum dot) chimera for resistive biomolecular memory application. Each QD holds two copies of the pRNA three-way junction (pRNA-3WJ) of the bacteriophage phi29 DNA packaging motor. The fixed quantity of two RNAs per QD was achieved by immobilizing the pRNA-3WJ with a Sephadex aptamer for resin binding. Two thiolated pRNA-3WJ serve as two feet of the chimera that stand on the gold plate. The RNA nanostructure served as both an insulator and a mediator to provide defined distance between the QD and gold. Immobilization of the chimera nanoparticle was confirmed with scanning tunneling microscopy. As revealed by scanning tunneling spectroscopy, the conjugated pRNA-3WJ-QD chimera exhibited an excellent electrical bistability signal for biomolecular memory function, demonstrating great potential for the development of resistive biomolecular memory and a nano-bio-inspired electronic device for information processing and computing.

Biomolecular logic systems: applications to biosensors and bioactuators

NASA Astrophysics Data System (ADS)

Katz, Evgeny

2014-05-01

The paper presents an overview of recent advances in biosensors and bioactuators based on the biocomputing concept. Novel biosensors digitally process multiple biochemical signals through Boolean logic networks of coupled biomolecular reactions and produce output in the form of YES/NO response. Compared to traditional single-analyte sensing devices, biocomputing approach enables a high-fidelity multi-analyte biosensing, particularly beneficial for biomedical applications. Multi-signal digital biosensors thus promise advances in rapid diagnosis and treatment of diseases by processing complex patterns of physiological biomarkers. Specifically, they can provide timely detection and alert to medical emergencies, along with an immediate therapeutic intervention. Application of the biocomputing concept has been successfully demonstrated for systems performing logic analysis of biomarkers corresponding to different injuries, particularly exemplified for liver injury. Wide-ranging applications of multi-analyte digital biosensors in medicine, environmental monitoring and homeland security are anticipated. "Smart" bioactuators, for example for signal-triggered drug release, were designed by interfacing switchable electrodes and biocomputing systems. Integration of novel biosensing and bioactuating systems with the biomolecular information processing systems keeps promise for further scientific advances and numerous practical applications.

Role of biomolecular logic systems in biosensors and bioactuators

NASA Astrophysics Data System (ADS)

Mailloux, Shay; Katz, Evgeny

2014-09-01

An overview of recent advances in biosensors and bioactuators based on biocomputing systems is presented. Biosensors digitally process multiple biochemical signals through Boolean logic networks of coupled biomolecular reactions and produce an output in the form of a YES/NO response. Compared to traditional single-analyte sensing devices, the biocomputing approach enables high-fidelity multianalyte biosensing, which is particularly beneficial for biomedical applications. Multisignal digital biosensors thus promise advances in rapid diagnosis and treatment of diseases by processing complex patterns of physiological biomarkers. Specifically, they can provide timely detection and alert medical personnel of medical emergencies together with immediate therapeutic intervention. Application of the biocomputing concept has been successfully demonstrated for systems performing logic analysis of biomarkers corresponding to different injuries, particularly as exemplified for liver injury. Wide-ranging applications of multianalyte digital biosensors in medicine, environmental monitoring, and homeland security are anticipated. "Smart" bioactuators, for signal-triggered drug release, for example, were designed by interfacing switchable electrodes with biocomputing systems. Integration of biosensing and bioactuating systems with biomolecular information processing systems advances the potential for further scientific innovations and various practical applications.

An Overview of Biomolecular Event Extraction from Scientific Documents

PubMed Central

Vanegas, Jorge A.; Matos, Sérgio; González, Fabio; Oliveira, José L.

2015-01-01

This paper presents a review of state-of-the-art approaches to automatic extraction of biomolecular events from scientific texts. Events involving biomolecules such as genes, transcription factors, or enzymes, for example, have a central role in biological processes and functions and provide valuable information for describing physiological and pathogenesis mechanisms. Event extraction from biomedical literature has a broad range of applications, including support for information retrieval, knowledge summarization, and information extraction and discovery. However, automatic event extraction is a challenging task due to the ambiguity and diversity of natural language and higher-level linguistic phenomena, such as speculations and negations, which occur in biological texts and can lead to misunderstanding or incorrect interpretation. Many strategies have been proposed in the last decade, originating from different research areas such as natural language processing, machine learning, and statistics. This review summarizes the most representative approaches in biomolecular event extraction and presents an analysis of the current state of the art and of commonly used methods, features, and tools. Finally, current research trends and future perspectives are also discussed. PMID:26587051

Construction of RNA-Quantum Dot Chimera for Nanoscale Resistive Biomemory Application

PubMed Central

Lee, Taek; Yagati, Ajay Kumar; Pi, Fengmei; Sharma, Ashwani; Choi, Jeong-Woo; Guo, Peixuan

2015-01-01

RNA nanotechnology offer advantages to construct thermally and chemically stable nanoparticles with well-defined shape and structure. Here we report the development of an RNA-Qd (quantum dot) chimera for resistive biomolecular memory application. Each Qd holds two copies of the pRNA three-way junction (pRNA-3WJ) of bacteriophage phi29 DNA-packaging motor. The fixed quantity of two RNA per Qd was achieved by immobilizing pRNA-3WJ harboring Sephadex aptamer for resin binding. Two thiolated pRNA-3WJ serves as two feet of the chimera to stand on the gold plate. The RNA nanostructure served as both an insulator and a mediator to provide defined distance between Qd and gold. Immobilization of chimera nanoparticle was confirmed through scanning tunneling microscopy (STM). As revealed by scanning tunneling spectroscopy (STS), the conjugated pRNA-3WJ-Qd chimera exhibited excellent electrical bi-stability signal for biomolecular memory function, demonstrating great potential for the development of resistive biomolecular memory and nanobio-inspired electronic device for information processing and computing. PMID:26135474

Illuminating the Reaction Pathways of Viromimetic Assembly.

PubMed

Cingil, Hande E; Boz, Emre B; Biondaro, Giovanni; de Vries, Renko; Cohen Stuart, Martien A; Kraft, Daniela J; van der Schoot, Paul; Sprakel, Joris

2017-04-05

The coassembly of well-defined biological nanostructures relies on a delicate balance between attractive and repulsive interactions between biomolecular building blocks. Viral capsids are a prototypical example, where coat proteins exhibit not only self-interactions but also interact with the cargo they encapsulate. In nature, the balance between antagonistic and synergistic interactions has evolved to avoid kinetic trapping and polymorphism. To date, it has remained a major challenge to experimentally disentangle the complex kinetic reaction pathways that underlie successful coassembly of biomolecular building blocks in a noninvasive approach with high temporal resolution. Here we show how macromolecular force sensors, acting as a genome proxy, allow us to probe the pathways through which a viromimetic protein forms capsids. We uncover the complex multistage process of capsid assembly, which involves recruitment and complexation, followed by allosteric growth of the proteinaceous coat. Under certain conditions, the single-genome particles condense into capsids containing multiple copies of the template. Finally, we derive a theoretical model that quantitatively describes the kinetics of recruitment and growth. These results shed new light on the origins of the pathway complexity in biomolecular coassembly.

Molecular dynamics simulations of pea (Pisum sativum) lectin structure with octyl glucoside detergents: the ligand interactions and dynamics.

PubMed

Konidala, Praveen; Niemeyer, Bernd

2007-07-01

The mitogenic pea (Pisum sativum) lectin is a legume protein of non-immunoglobulin nature capable of specific recognition of glucose derivatives without altering its structure. Molecular dynamics simulations were performed in a realistic environment to investigate the structure and interaction properties of pea lectin with various concentrations of n-octyl-beta-d-glucopyranoside (OG) detergent monomers distributed inside explicit solvent cell. In addition, the diffusion coefficients of the ligands (OG, Ca2+, Mn2+, and Cl-) and the water molecules were also reported. The structural flexibility of the lectin was conserved in all simulations. The self-assembly of OG monomers into a small micelle at the hydrophobic site of the lectin was noticed in the simulation with 20 OG monomers. The interaction energy analysis concludes that the lectin was appropriately termed an adaptive structure. One or rarely two binding sites were observed at an instant in each simulation that were electrostatically favoured for the OG to interact with the surface amino acid residues. Enhanced binding of OG to the pea lectin was quantified in the system containing only Ca2+ divalent ions. Interestingly, no binding was observed in the simulation without divalent ions. Furthermore, the lectin-ligand complex was stabilized by multiple hydrogen bonds and at least one water bridge. Finally, the work was also in accordance with the published work elsewhere that the simulations performed with different initial conditions and using higher nonbonded cutoffs for the van der Waals and electrostatic interactions provide more accurate information and clues than the single large simulation of the biomolecular system of interest.

Recent advances in QM/MM free energy calculations using reference potentials.

PubMed

Duarte, Fernanda; Amrein, Beat A; Blaha-Nelson, David; Kamerlin, Shina C L

2015-05-01

Recent years have seen enormous progress in the development of methods for modeling (bio)molecular systems. This has allowed for the simulation of ever larger and more complex systems. However, as such complexity increases, the requirements needed for these models to be accurate and physically meaningful become more and more difficult to fulfill. The use of simplified models to describe complex biological systems has long been shown to be an effective way to overcome some of the limitations associated with this computational cost in a rational way. Hybrid QM/MM approaches have rapidly become one of the most popular computational tools for studying chemical reactivity in biomolecular systems. However, the high cost involved in performing high-level QM calculations has limited the applicability of these approaches when calculating free energies of chemical processes. In this review, we present some of the advances in using reference potentials and mean field approximations to accelerate high-level QM/MM calculations. We present illustrative applications of these approaches and discuss challenges and future perspectives for the field. The use of physically-based simplifications has shown to effectively reduce the cost of high-level QM/MM calculations. In particular, lower-level reference potentials enable one to reduce the cost of expensive free energy calculations, thus expanding the scope of problems that can be addressed. As was already demonstrated 40 years ago, the usage of simplified models still allows one to obtain cutting edge results with substantially reduced computational cost. This article is part of a Special Issue entitled Recent developments of molecular dynamics. Copyright © 2014. Published by Elsevier B.V.

Raman Spectroscopic Analysis of Geological and Biogeological Specimens of Relevance to the ExoMars Mission

PubMed Central

Edwards, Howell G.M.; Ingley, Richard; Parnell, John; Vítek, Petr; Jehlička, Jan

2013-01-01

Abstract A novel miniaturized Raman spectrometer is scheduled to fly as part of the analytical instrumentation package on an ESA remote robotic lander in the ESA/Roscosmos ExoMars mission to search for evidence for extant or extinct life on Mars in 2018. The Raman spectrometer will be part of the first-pass analytical stage of the sampling procedure, following detailed surface examination by the PanCam scanning camera unit on the ExoMars rover vehicle. The requirements of the analytical protocol are stringent and critical; this study represents a laboratory blind interrogation of specimens that form a list of materials that are of relevance to martian exploration and at this stage simulates a test of current laboratory instrumentation to highlight the Raman technique strengths and possible weaknesses that may be encountered in practice on the martian surface and from which future studies could be formulated. In this preliminary exercise, some 10 samples that are considered terrestrial representatives of the mineralogy and possible biogeologically modified structures that may be identified on Mars have been examined with Raman spectroscopy, and conclusions have been drawn about the viability of the unambiguous spectral identification of biomolecular life signatures. It is concluded that the Raman spectroscopic technique does indeed demonstrate the capability to identify biomolecular signatures and the mineralogy in real-world terrestrial samples with a very high degree of success without any preconception being made about their origin and classification. Key Words: Biosignatures—Mars Exploration Rovers—Raman spectroscopy—Search for life (biosignatures)—Planetary instrumentation. Astrobiology 13, 543–549. PMID:23758166

A bio-molecular inspired electronic architecture: bio-based device concepts for enhanced sensing (Invited Paper)

NASA Astrophysics Data System (ADS)

Woolard, Dwight L.; Luo, Ying; Gelmont, Boris L.; Globus, Tatiana; Jensen, James O.

2005-05-01

A biological(bio)-molecular inspired electronic architecture is presented that offers the potential for defining nanoscale sensor platforms with enhanced capabilities for sensing terahertz (THz) frequency bio-signatures. This architecture makes strategic use of integrated biological elements to enable communication and high-level function within densely-packed nanoelectronic systems. In particular, this architecture introduces a new paradigm for establishing hybrid Electro-THz-Optical (ETO) communication channels where the THz-frequency spectral characteristics that are uniquely associated with the embedded bio-molecules are utilized directly. Since the functionality of this architecture is built upon the spectral characteristics of bio-molecules, this immediately allows for defining new methods for enhanced sensing of THz bio-signatures. First, this integrated sensor concept greatly facilitates the collection of THz bio-signatures associated with embedded bio-molecules via interactions with the time-dependent signals propagating through the nanoelectronic circuit. Second, it leads to a new Multi-State Spectral Sensing (MS3) approach where bio-signature information can be collected from multiple metastable state conformations. This paper will also introduce a new class of prototype devices that utilize THz-sensitive bio-molecules to achieve molecular-level sensing and functionality. Here, new simulation results are presented for a class of bio-molecular components that exhibit the prescribed type of ETO characteristics required for realizing integrated sensor platforms. Most noteworthy, this research derives THz spectral bio-signatures for organic molecules that are amenable to photo-induced metastable-state conformations and establishes an initial scientific foundation and design blueprint for an enhanced THz bio-signature sensing capability.

Independent Metrics for Protein Backbone and Side-Chain Flexibility: Time Scales and Effects of Ligand Binding.

PubMed

Fuchs, Julian E; Waldner, Birgit J; Huber, Roland G; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R

2015-03-10

Conformational dynamics are central for understanding biomolecular structure and function, since biological macromolecules are inherently flexible at room temperature and in solution. Computational methods are nowadays capable of providing valuable information on the conformational ensembles of biomolecules. However, analysis tools and intuitive metrics that capture dynamic information from in silico generated structural ensembles are limited. In standard work-flows, flexibility in a conformational ensemble is represented through residue-wise root-mean-square fluctuations or B-factors following a global alignment. Consequently, these approaches relying on global alignments discard valuable information on local dynamics. Results inherently depend on global flexibility, residue size, and connectivity. In this study we present a novel approach for capturing positional fluctuations based on multiple local alignments instead of one single global alignment. The method captures local dynamics within a structural ensemble independent of residue type by splitting individual local and global degrees of freedom of protein backbone and side-chains. Dependence on residue type and size in the side-chains is removed via normalization with the B-factors of the isolated residue. As a test case, we demonstrate its application to a molecular dynamics simulation of bovine pancreatic trypsin inhibitor (BPTI) on the millisecond time scale. This allows for illustrating different time scales of backbone and side-chain flexibility. Additionally, we demonstrate the effects of ligand binding on side-chain flexibility of three serine proteases. We expect our new methodology for quantifying local flexibility to be helpful in unraveling local changes in biomolecular dynamics.

Polarizable multipolar electrostatics for cholesterol

NASA Astrophysics Data System (ADS)

Fletcher, Timothy L.; Popelier, Paul L. A.

2016-08-01

FFLUX is a novel force field under development for biomolecular modelling, and is based on topological atoms and the machine learning method kriging. Successful kriging models have been obtained for realistic electrostatics of amino acids, small peptides, and some carbohydrates but here, for the first time, we construct kriging models for a sizeable ligand of great importance, which is cholesterol. Cholesterol's mean total (internal) electrostatic energy prediction error amounts to 3.9 kJ mol-1, which pleasingly falls below the threshold of 1 kcal mol-1 often cited for accurate biomolecular modelling. We present a detailed analysis of the error distributions.

Towards sensitive, high-throughput, biomolecular assays based on fluorescence lifetime

NASA Astrophysics Data System (ADS)

Ioanna Skilitsi, Anastasia; Turko, Timothé; Cianfarani, Damien; Barre, Sophie; Uhring, Wilfried; Hassiepen, Ulrich; Léonard, Jérémie

2017-09-01

Time-resolved fluorescence detection for robust sensing of biomolecular interactions is developed by implementing time-correlated single photon counting in high-throughput conditions. Droplet microfluidics is used as a promising platform for the very fast handling of low-volume samples. We illustrate the potential of this very sensitive and cost-effective technology in the context of an enzymatic activity assay based on fluorescently-labeled biomolecules. Fluorescence lifetime detection by time-correlated single photon counting is shown to enable reliable discrimination between positive and negative control samples at a throughput as high as several hundred samples per second.

Chemical Kinetics for Bridging Molecular Mechanisms and Macroscopic Measurements of Amyloid Fibril Formation.

PubMed

Michaels, Thomas C T; Šarić, Anđela; Habchi, Johnny; Chia, Sean; Meisl, Georg; Vendruscolo, Michele; Dobson, Christopher M; Knowles, Tuomas P J

2018-04-20

Understanding how normally soluble peptides and proteins aggregate to form amyloid fibrils is central to many areas of modern biomolecular science, ranging from the development of functional biomaterials to the design of rational therapeutic strategies against increasingly prevalent medical conditions such as Alzheimer's and Parkinson's diseases. As such, there is a great need to develop models to mechanistically describe how amyloid fibrils are formed from precursor peptides and proteins. Here we review and discuss how ideas and concepts from chemical reaction kinetics can help to achieve this objective. In particular, we show how a combination of theory, experiments, and computer simulations, based on chemical kinetics, provides a general formalism for uncovering, at the molecular level, the mechanistic steps that underlie the phenomenon of amyloid fibril formation.

Chemical Kinetics for Bridging Molecular Mechanisms and Macroscopic Measurements of Amyloid Fibril Formation

NASA Astrophysics Data System (ADS)

Michaels, Thomas C. T.; Šarić, Anđela; Habchi, Johnny; Chia, Sean; Meisl, Georg; Vendruscolo, Michele; Dobson, Christopher M.; Knowles, Tuomas P. J.

2018-04-01

Understanding how normally soluble peptides and proteins aggregate to form amyloid fibrils is central to many areas of modern biomolecular science, ranging from the development of functional biomaterials to the design of rational therapeutic strategies against increasingly prevalent medical conditions such as Alzheimer's and Parkinson's diseases. As such, there is a great need to develop models to mechanistically describe how amyloid fibrils are formed from precursor peptides and proteins. Here we review and discuss how ideas and concepts from chemical reaction kinetics can help to achieve this objective. In particular, we show how a combination of theory, experiments, and computer simulations, based on chemical kinetics, provides a general formalism for uncovering, at the molecular level, the mechanistic steps that underlie the phenomenon of amyloid fibril formation.

Counting the ions surrounding nucleic acids

PubMed Central

2017-01-01

Abstract Nucleic acids are strongly negatively charged, and thus electrostatic interactions—screened by ions in solution—play an important role in governing their ability to fold and participate in biomolecular interactions. The negative charge creates a region, known as the ion atmosphere, in which cation and anion concentrations are perturbed from their bulk values. Ion counting experiments quantify the ion atmosphere by measuring the preferential ion interaction coefficient: the net total number of excess ions above, or below, the number expected due to the bulk concentration. The results of such studies provide important constraints on theories, which typically predict the full three-dimensional distribution of the screening cloud. This article reviews the state of nucleic acid ion counting measurements and critically analyzes their ability to test both analytical and simulation-based models. PMID:28034959

Explicit polarization (X-Pol) potential using ab initio molecular orbital theory and density functional theory.

PubMed

Song, Lingchun; Han, Jaebeom; Lin, Yen-lin; Xie, Wangshen; Gao, Jiali

2009-10-29

The explicit polarization (X-Pol) method has been examined using ab initio molecular orbital theory and density functional theory. The X-Pol potential was designed to provide a novel theoretical framework for developing next-generation force fields for biomolecular simulations. Importantly, the X-Pol potential is a general method, which can be employed with any level of electronic structure theory. The present study illustrates the implementation of the X-Pol method using ab initio Hartree-Fock theory and hybrid density functional theory. The computational results are illustrated by considering a set of bimolecular complexes of small organic molecules and ions with water. The computed interaction energies and hydrogen bond geometries are in good accord with CCSD(T) calculations and B3LYP/aug-cc-pVDZ optimizations.

Use of UV-vis-NIR spectroscopy to monitor label-free interaction between molecular recognition elements and erythropoietin on a gold-coated polycarbonate platform.

PubMed

Citartan, Marimuthu; Gopinath, Subash C B; Tominaga, Junji; Chen, Yeng; Tang, Thean-Hock

2014-08-01

Label-free-based detection is pivotal for real-time monitoring of biomolecular interactions and to eliminate the need for labeling with tags that can occupy important binding sites of biomolecules. One simplest form of label-free-based detection is ultraviolet-visible-near-infrared (UV-vis-NIR) spectroscopy, which measure changes in reflectivity as a means to monitor immobilization and interaction of biomolecules with their corresponding partners. In biosensor development, the platform used for the biomolecular interaction should be suitable for different molecular recognition elements. In this study, gold (Au)-coated polycarbonate was used as a platform and as a proof-of-concept, erythropoietin (EPO), a doping substance widely abused by the athletes was used as the target. The interaction of EPO with its corresponding molecular recognition elements (anti-EPO monoclonal antibody and anti-EPO DNA aptamer) is monitored by UV-vis-NIR spectroscopy. Prior to this, to show that UV-vis-NIR spectroscopy is a suitable method for measuring biomolecular interaction, the interaction between biotin and streptavidin was demonstrated via this strategy and reflectivity of this interaction decreased by 25%. Subsequent to this, interaction of the EPO with anti-EPO monoclonal antibody and anti-EPO DNA aptamer resulted in the decrease of reflectivity by 5% and 10%, respectively. The results indicated that Au-coated polycarbonate could be an ideal biosensor platform for monitoring biomolecular interactions using UV-vis-NIR spectroscopy. A smaller version of the Au-coated polycarbonate substrates can be derived from the recent set-up, to be applied towards detecting EPO abuse among atheletes. Copyright © 2014 Elsevier B.V. All rights reserved.

GENESIS: a hybrid-parallel and multi-scale molecular dynamics simulator with enhanced sampling algorithms for biomolecular and cellular simulations

PubMed Central

Jung, Jaewoon; Mori, Takaharu; Kobayashi, Chigusa; Matsunaga, Yasuhiro; Yoda, Takao; Feig, Michael; Sugita, Yuji

2015-01-01

GENESIS (Generalized-Ensemble Simulation System) is a new software package for molecular dynamics (MD) simulations of macromolecules. It has two MD simulators, called ATDYN and SPDYN. ATDYN is parallelized based on an atomic decomposition algorithm for the simulations of all-atom force-field models as well as coarse-grained Go-like models. SPDYN is highly parallelized based on a domain decomposition scheme, allowing large-scale MD simulations on supercomputers. Hybrid schemes combining OpenMP and MPI are used in both simulators to target modern multicore computer architectures. Key advantages of GENESIS are (1) the highly parallel performance of SPDYN for very large biological systems consisting of more than one million atoms and (2) the availability of various REMD algorithms (T-REMD, REUS, multi-dimensional REMD for both all-atom and Go-like models under the NVT, NPT, NPAT, and NPγT ensembles). The former is achieved by a combination of the midpoint cell method and the efficient three-dimensional Fast Fourier Transform algorithm, where the domain decomposition space is shared in real-space and reciprocal-space calculations. Other features in SPDYN, such as avoiding concurrent memory access, reducing communication times, and usage of parallel input/output files, also contribute to the performance. We show the REMD simulation results of a mixed (POPC/DMPC) lipid bilayer as a real application using GENESIS. GENESIS is released as free software under the GPLv2 licence and can be easily modified for the development of new algorithms and molecular models. WIREs Comput Mol Sci 2015, 5:310–323. doi: 10.1002/wcms.1220 PMID:26753008

DNA origami based Au-Ag-core-shell nanoparticle dimers with single-molecule SERS sensitivity

NASA Astrophysics Data System (ADS)

Prinz, J.; Heck, C.; Ellerik, L.; Merk, V.; Bald, I.

2016-03-01

DNA origami nanostructures are a versatile tool to arrange metal nanostructures and other chemical entities with nanometer precision. In this way gold nanoparticle dimers with defined distance can be constructed, which can be exploited as novel substrates for surface enhanced Raman scattering (SERS). We have optimized the size, composition and arrangement of Au/Ag nanoparticles to create intense SERS hot spots, with Raman enhancement up to 1010, which is sufficient to detect single molecules by Raman scattering. This is demonstrated using single dye molecules (TAMRA and Cy3) placed into the center of the nanoparticle dimers. In conjunction with the DNA origami nanostructures novel SERS substrates are created, which can in the future be applied to the SERS analysis of more complex biomolecular targets, whose position and conformation within the SERS hot spot can be precisely controlled.DNA origami nanostructures are a versatile tool to arrange metal nanostructures and other chemical entities with nanometer precision. In this way gold nanoparticle dimers with defined distance can be constructed, which can be exploited as novel substrates for surface enhanced Raman scattering (SERS). We have optimized the size, composition and arrangement of Au/Ag nanoparticles to create intense SERS hot spots, with Raman enhancement up to 1010, which is sufficient to detect single molecules by Raman scattering. This is demonstrated using single dye molecules (TAMRA and Cy3) placed into the center of the nanoparticle dimers. In conjunction with the DNA origami nanostructures novel SERS substrates are created, which can in the future be applied to the SERS analysis of more complex biomolecular targets, whose position and conformation within the SERS hot spot can be precisely controlled. Electronic supplementary information (ESI) available: Additional information about materials and methods, designs of DNA origami templates, height profiles, additional SERS spectra, assignment of DNA bands, SEM images, additional AFM images, FDTD simulations, additional reference spectra for Cy3 and detailed description of EF estimation, simulated absorption and scattering spectra. See DOI: 10.1039/c5nr08674d

Regulation Effects by Programmed Molecules for Transcription-Based Diagnostic Automata towards Therapeutic Use

NASA Astrophysics Data System (ADS)

Hirabayashi, Miki; Ohashi, Hirotada; Kubo, Tai

We have presented experimental analysis on the controllability of our transcription-based diagnostic biomolecular automata by programmed molecules. Focusing on the noninvasive transcriptome diagnosis by salivary mRNAs, we already proposed the novel concept of diagnostic device using DNA computation. This system consists of the main computational element which has a stem shaped promoter region and a pseudo-loop shaped read-only memory region for transcription regulation through the conformation change caused by the recognition of disease-related biomarkers. We utilize the transcription of malachite green aptamer sequence triggered by the target recognition for observation of detection. This algorithm makes it possible to release RNA-aptamer drugs multiply, different from the digestion-based systems by the restriction enzyme which was proposed previously, for the in-vivo use, however, the controllability of aptamer release is not enough at the previous stage. In this paper, we verified the regulation effect on aptamer transcription by programmed molecules in basic conditions towards the developm! ent of therapeutic automata. These results would bring us one step closer to the realization of new intelligent diagnostic and therapeutic automata based on molecular circuits.

Entropy in bimolecular simulations: A comprehensive review of atomic fluctuations-based methods.

PubMed

Kassem, Summer; Ahmed, Marawan; El-Sheikh, Salah; Barakat, Khaled H

2015-11-01

Entropy of binding constitutes a major, and in many cases a detrimental, component of the binding affinity in biomolecular interactions. While the enthalpic part of the binding free energy is easier to calculate, estimating the entropy of binding is further more complicated. A precise evaluation of entropy requires a comprehensive exploration of the complete phase space of the interacting entities. As this task is extremely hard to accomplish in the context of conventional molecular simulations, calculating entropy has involved many approximations. Most of these golden standard methods focused on developing a reliable estimation of the conformational part of the entropy. Here, we review these methods with a particular emphasis on the different techniques that extract entropy from atomic fluctuations. The theoretical formalisms behind each method is explained highlighting its strengths as well as its limitations, followed by a description of a number of case studies for each method. We hope that this brief, yet comprehensive, review provides a useful tool to understand these methods and realize the practical issues that may arise in such calculations. Copyright © 2015 Elsevier Inc. All rights reserved.

Simulation of Two Dimensional Ultraviolet (2DUV) Spectroscopy of Amyloid Fibrils

PubMed Central

Jiang, Jun; Abramavicius, Darius; Falvo, Cyril; Bulheller, Benjamin M.; Hirst, Jonathan D.; Mukamel, Shaul

2010-01-01

Revealing the structure and aggregation mechanism of amyloid fibrils is essential for the treatment of over 20 diseases related to protein misfolding. Coherent two dimensional (2D) infrared spectroscopy is a novel tool that provides a wealth of new insight into the structure and dynamics of biomolecular systems. Recently developed ultrafast laser sources are extending multidimensional spectroscopy into the ultraviolet (UV) region, and this opens up new opportunities for probing fibrils. In a simulation study, we show that 2DUV spectra of the backbone of a 32-residue β-amyloid (Aβ9–40) fibril associated with Alzheimer’s disease, and two intermediate prefibrillar structures carry characteristic signatures of fibril size and geometry that could be used to monitor its formation kinetics. The dependence of these signals on the fibril size and geometry is explored. We demonstrate that the dominant features of the β-amyloid fibril spectra are determined by intramolecular interactions within a single Aβ9–40, while intermolecular interactions at the “external interface” have clear signatures in the fine details of these signals. PMID:20795695

Mitochondrial fusion through membrane automata.

PubMed

Giannakis, Konstantinos; Andronikos, Theodore

2015-01-01

Studies have shown that malfunctions in mitochondrial processes can be blamed for diseases. However, the mechanism behind these operations is yet not sufficiently clear. In this work we present a novel approach to describe a biomolecular model for mitochondrial fusion using notions from the membrane computing. We use a case study defined in BioAmbient calculus and we show how to translate it in terms of a P automata variant. We combine brane calculi with (mem)brane automata to produce a new scheme capable of describing simple, realistic models. We propose the further use of similar methods and the test of other biomolecular models with the same behaviour.

Multiplexed evaluation of capture agent binding kinetics using arrays of silicon photonic microring resonators.

PubMed

Byeon, Ji-Yeon; Bailey, Ryan C

2011-09-07

High affinity capture agents recognizing biomolecular targets are essential in the performance of many proteomic detection methods. Herein, we report the application of a label-free silicon photonic biomolecular analysis platform for simultaneously determining kinetic association and dissociation constants for two representative protein capture agents: a thrombin-binding DNA aptamer and an anti-thrombin monoclonal antibody. The scalability and inherent multiplexing capability of the technology make it an attractive platform for simultaneously evaluating the binding characteristics of multiple capture agents recognizing the same target antigen, and thus a tool complementary to emerging high-throughput capture agent generation strategies.

Semiconductor Microcavity Flow Spectroscopy of Intracellular Protein in Human Cells

NASA Astrophysics Data System (ADS)

Gourley, Paul; Cox, Jim; Hendricks, Judy; McDonald, Anthony; Copeland, Guild; Sasaki, Darryl; Skirboll, Steve; Curry, Mark

2001-03-01

The speed of light through a biofluid or biological cell is inversely related to the biomolecular concentration of proteins and other complex molecules that modify the refractive index at wavelengths accessible to semiconductor lasers. By placing a fluid or cell into a semiconductor microcavity laser, these decreases in light speed can be sensitively recorded in picoseconds as frequency red-shifts in the laser output spectrum. This biocavity laser equipped with microfluidics for transporting cells at high speed through the laser microcavity has shown potential for rapid analysis of biomolecular mass of normal and malignant human cells in their physiologic condition without time-consuming fixing, staining, or tagging. We have used biocavity laser spectroscopy to measure the optical properties of solutions of standard biomolecules (sugars, proteins, DNA, and ions) and human cells. The technique determines the frequency shift, relative to that of water, of spontaneous or stimulated emission from cavity filled with a biomolecular solution. The shift was also measured in human glioblastoma cells that had been sorted by conventional fluorescence-activated cell sorting according to protein content. The results show a direct correlation between protein measured by fluorescence and the frequency shift observed in the microcavity laser.

Microtubule-based nanomaterials: Exploiting nature's dynamic biopolymers

DOE PAGES

Bachand, George D.; Stevens, Mark J.; Spoerke, Erik David

2015-04-09

For more than a decade now, biomolecular systems have served as an inspiration for the development of synthetic nanomaterials and systems that are capable of reproducing many of unique and emergent behaviors of living systems. In addition, one intriguing element of such systems may be found in a specialized class of proteins known as biomolecular motors that are capable of performing useful work across multiple length scales through the efficient conversion of chemical energy. Microtubule (MT) filaments may be considered within this context as their dynamic assembly and disassembly dissipate energy, and perform work within the cell. MTs are onemore » of three cytoskeletal filaments in eukaryotic cells, and play critical roles in a range of cellular processes including mitosis and vesicular trafficking. Based on their function, physical attributes, and unique dynamics, MTs also serve as a powerful archetype of a supramolecular filament that underlies and drives multiscale emergent behaviors. In this review, we briefly summarize recent efforts to generate hybrid and composite nanomaterials using MTs as biomolecular scaffolds, as well as computational and synthetic approaches to develop synthetic one-dimensional nanostructures that display the enviable attributes of the natural filaments.« less

Atom-scale depth localization of biologically important chemical elements in molecular layers.

PubMed

Schneck, Emanuel; Scoppola, Ernesto; Drnec, Jakub; Mocuta, Cristian; Felici, Roberto; Novikov, Dmitri; Fragneto, Giovanna; Daillant, Jean

2016-08-23

In nature, biomolecules are often organized as functional thin layers in interfacial architectures, the most prominent examples being biological membranes. Biomolecular layers play also important roles in context with biotechnological surfaces, for instance, when they are the result of adsorption processes. For the understanding of many biological or biotechnologically relevant phenomena, detailed structural insight into the involved biomolecular layers is required. Here, we use standing-wave X-ray fluorescence (SWXF) to localize chemical elements in solid-supported lipid and protein layers with near-Ångstrom precision. The technique complements traditional specular reflectometry experiments that merely yield the layers' global density profiles. While earlier work mostly focused on relatively heavy elements, typically metal ions, we show that it is also possible to determine the position of the comparatively light elements S and P, which are found in the most abundant classes of biomolecules and are therefore particularly important. With that, we overcome the need of artificial heavy atom labels, the main obstacle to a broader application of high-resolution SWXF in the fields of biology and soft matter. This work may thus constitute the basis for the label-free, element-specific structural investigation of complex biomolecular layers and biological surfaces.

Synthetic Approach to biomolecular science by cyborg supramolecular chemistry.

PubMed

Kurihara, Kensuke; Matsuo, Muneyuki; Yamaguchi, Takumi; Sato, Sota

2018-02-01

To imitate the essence of living systems via synthetic chemistry approaches has been attempted. With the progress in supramolecular chemistry, it has become possible to synthesize molecules of a size and complexity close to those of biomacromolecules. Recently, the combination of precisely designed supramolecules with biomolecules has generated structural platforms for designing and creating unique molecular systems. Bridging between synthetic chemistry and biomolecular science is also developing methodologies for the creation of artificial cellular systems. This paper provides an overview of the recently expanding interdisciplinary research to fuse artificial molecules with biomolecules, that can deepen our understanding of the dynamical ordering of biomolecules. Using bottom-up approaches based on the precise chemical design, synthesis and hybridization of artificial molecules with biological materials have been realizing the construction of sophisticated platforms having the fundamental functions of living systems. The effective hybrid, molecular cyborg, approaches enable not only the establishment of dynamic systems mimicking nature and thus well-defined models for biophysical understanding, but also the creation of those with highly advanced, integrated functions. This article is part of a Special Issue entitled "Biophysical Exploration of Dynamical Ordering of Biomolecular Systems" edited by Dr. Koichi Kato. Copyright © 2017 Elsevier B.V. All rights reserved.

Demonstration and Characterization of Biomolecular Enrichment on Microfluidic Aptamer-Functionalized Surfaces

PubMed Central

Nguyen, Thai Huu; Pei, Renjun; Stojanovic, Milan; Lin, Qiao

2010-01-01

This paper demonstrates and systematically characterizes the enrichment of biomolecular compounds using aptamer-functionalized surfaces within a microfluidic device. The device consists of a microchamber packed with aptamer-functionalized microbeads and integrated with a microheater and temperature sensor to enable thermally controlled binding and release of biomolecules by the aptamer. We first present an equilibrium binding-based analytical model to understand the enrichment process. The characteristics of the aptamer-analyte binding and enrichment are then experimentally studied, using adenosine monophosphate (AMP) and a specific RNA aptamer as a model system. The temporal process of AMP binding to the aptamer is found to be primarily determined by the aptamer-AMP binding kinetics. The temporal process of aptamer-AMP dissociation at varying temperatures is also obtained and observed to occur relatively rapidly (< 2 s). The specificity of the enrichment is next confirmed by performing selective enrichment of AMP from a sample containing biomolecular impurities. Finally, we investigate the enrichment of AMP by either discrete or continuous introduction of a dilute sample into the microchamber, demonstrating enrichment factors ranging from 566 to 686×, which agree with predictions of the analytical model. PMID:21765612

Atom-scale depth localization of biologically important chemical elements in molecular layers

PubMed Central

Schneck, Emanuel; Scoppola, Ernesto; Drnec, Jakub; Mocuta, Cristian; Felici, Roberto; Novikov, Dmitri; Fragneto, Giovanna; Daillant, Jean

2016-01-01

In nature, biomolecules are often organized as functional thin layers in interfacial architectures, the most prominent examples being biological membranes. Biomolecular layers play also important roles in context with biotechnological surfaces, for instance, when they are the result of adsorption processes. For the understanding of many biological or biotechnologically relevant phenomena, detailed structural insight into the involved biomolecular layers is required. Here, we use standing-wave X-ray fluorescence (SWXF) to localize chemical elements in solid-supported lipid and protein layers with near-Ångstrom precision. The technique complements traditional specular reflectometry experiments that merely yield the layers’ global density profiles. While earlier work mostly focused on relatively heavy elements, typically metal ions, we show that it is also possible to determine the position of the comparatively light elements S and P, which are found in the most abundant classes of biomolecules and are therefore particularly important. With that, we overcome the need of artificial heavy atom labels, the main obstacle to a broader application of high-resolution SWXF in the fields of biology and soft matter. This work may thus constitute the basis for the label-free, element-specific structural investigation of complex biomolecular layers and biological surfaces. PMID:27503887

Biomolecular inflammatory response to surgical energy usage in laparoscopic surgery: results of a randomized study.

PubMed

Agarwal, Brij B; Nanavati, Juhil D; Agarwal, Nayan; Sharma, Naveen; Agarwal, Krishna A; Manish, Kumar; Saluja, Satish; Agarwal, Sneh

2016-05-01

Use of surgical energy is integral to laparoscopic surgery (LS). Energized dissection (ED) has a potential to impact the biomolecular expression of inflammation due to ED-induced collateral inflammation. We did this triple-blind randomized controlled (RCT) study to assess this biomolecular footprint in an index LS, i.e., laparoscopic cholecystectomy (LC). This RCT was conducted in collaboration with tertiary-level institutions, from January 2014 to December 2014 with institutional review board clearance. Consecutive, unselected, consenting candidates for LC were randomized (after anesthesia induction) into group I (ED) and group II (non-ED). They were managed with compliance to universal protocols for ethics, informed consent, anesthesia, drug usage and clinical pathway with blinded observers. Biomolecular inflammatory markers, i.e., interleukin 6 (IL-6), tumor necrosis factor-alpha (TNF-α) and highly sensitive CRP (HS-CRP), were measured with blood drawn juxta-preoperatively (H0), at 4 h (H4) and at 24 h (H24). The quantitative changes induced by ED on IL-6, TNF-α and HS-CRP at H0, H4 and H24 with their kinetic behavior were the study endpoint. Prospective data were analyzed statistically with a p value of <0.05 being significant. Two cases from the ED group had biliary injury and hence were withdrawn from analysis. The ED (n = 49) and non-ED (n = 51) groups had similar demographic, clinical and H0 biomolecular variables. There was a significant increase in IL-6, TNF-α and HS-CRP from H0 to H4 in both the groups (p values <0.001). From H4 to H24, all three cytokines showed significant increase in ED group (p < 0.05), whereas in the non-ED group, IL-6 showed significant fall (p = 0.004) and TNF-α showed no significant change (p = 0.063). Both the groups showed H4-H24 elevation of HS-CRP (p = 0.000). Energized dissection adds to the cytokine-mediated postoperative inflammation. The additional ED-induced inflammation can be measured objectively by IL-6 and TNF-α levels. Clinical Trials Registry, India (REF/2014/06/007153).

Insights Into the Bifunctional Aphidicolan-16-ß-ol Synthase Through Rapid Biomolecular Modeling Approaches.

PubMed

Hirte, Max; Meese, Nicolas; Mertz, Michael; Fuchs, Monika; Brück, Thomas B

2018-01-01

Diterpene synthases catalyze complex, multi-step C-C coupling reactions thereby converting the universal, aliphatic precursor geranylgeranyl diphosphate into diverse olefinic macrocylces that form the basis for the structural diversity of the diterpene natural product family. Since catalytically relevant crystal structures of diterpene synthases are scarce, homology based biomolecular modeling techniques offer an alternative route to study the enzyme's reaction mechanism. However, precise identification of catalytically relevant amino acids is challenging since these models require careful preparation and refinement techniques prior to substrate docking studies. Targeted amino acid substitutions in this protein class can initiate premature quenching of the carbocation centered reaction cascade. The structural characterization of those alternative cyclization products allows for elucidation of the cyclization reaction cascade and provides a new source for complex macrocyclic synthons. In this study, new insights into structure and function of the fungal, bifunctional Aphidicolan-16-ß-ol synthase were achieved using a simplified biomolecular modeling strategy. The applied refinement methodologies could rapidly generate a reliable protein-ligand complex, which provides for an accurate in silico identification of catalytically relevant amino acids. Guided by our modeling data, ACS mutations lead to the identification of the catalytically relevant ACS amino acid network I626, T657, Y658, A786, F789, and Y923. Moreover, the ACS amino acid substitutions Y658L and D661A resulted in a premature termination of the cyclization reaction cascade en-route from syn-copalyl diphosphate to Aphidicolan-16-ß-ol. Both ACS mutants generated the diterpene macrocycle syn-copalol and a minor, non-hydroxylated labdane related diterpene, respectively. Our biomolecular modeling and mutational studies suggest that the ACS substrate cyclization occurs in a spatially restricted location of the enzyme's active site and that the geranylgeranyl diphosphate derived pyrophosphate moiety remains in the ACS active site thereby directing the cyclization process. Our cumulative data confirm that amino acids constituting the G-loop of diterpene synthases are involved in the open to the closed, catalytically active enzyme conformation. This study demonstrates that a simple and rapid biomolecular modeling procedure can predict catalytically relevant amino acids. The approach reduces computational and experimental screening efforts for diterpene synthase structure-function analyses.

Insights into the bifunctional Aphidicolan-16-ß-ol synthase through rapid biomolecular modelling approaches

NASA Astrophysics Data System (ADS)

Hirte, Max; Meese, Nicolas; Mertz, Michael; Fuchs, Monika; Brück, Thomas B.

2018-04-01

Diterpene synthases catalyze complex, multi-step C-C coupling reactions thereby converting the universal, aliphatic precursor geranylgeranyl diphosphate into diverse olefinic macrocylces that form the basis for the structural diversity of the diterpene natural product family. Since catalytically relevant crystal structures of diterpene synthases are scarce, homology based biomolecular modelling techniques offer an alternative route to study the enzyme’s reaction mechanism. However, precise identification of catalytically relevant amino acids is challenging since these models require careful preparation and refinement techniques prior to substrate docking studies. Targeted amino acid substitutions in this protein class can initiate premature quenching of the carbocation centered reaction cascade. The structural characterization of those alternative cyclization products allows for elucidation of the cyclization reaction cascade and provides a new source for complex macrocyclic synthons. In this study, new insights into structure and function of the fungal, bifunctional Aphidicolan-16-ß-ol synthase were achieved using a simplified biomolecular modelling strategy. The applied refinement methodologies could rapidly generate a reliable protein-ligand complex, which provides for an accurate in silico identification of catalytically relevant amino acids. Guided by our modelling data, ACS mutations lead to the identification of the catalytically relevant ACS amino acid network I626, T657, Y658, A786, F789 and Y923. Moreover, the ACS amino acid substitutions Y658L and D661A resulted in a premature termination of the cyclization reaction cascade en-route from syn-copalyl diphosphate to Aphidicolan-16-ß-ol. Both ACS mutants generated the diterpene macrocycle syn-copalol and a minor, non-hydroxylated labdane related diterpene, respectively. Our biomolecular modelling and mutational studies suggest that the ACS substrate cyclization occurs in a spatially restricted location of the enzyme’s active site and that the geranylgeranyl diphosphate derived pyrophosphate moiety remains in the ACS active site thereby directing the cyclization process. Our cumulative data confirm that amino acids constituting the G-loop of diterpene synthases are involved in the open to the closed, catalytically active enzyme conformation. This study demonstrates that a simple and rapid biomolecular modelling procedure can predict catalytically relevant amino acids. The approach reduces computational and experimental screening efforts for diterpene synthase structure-function analyses.

Rapid Convergence of Energy and Free Energy Profiles with Quantum Mechanical Size in Quantum Mechanical-Molecular Mechanical Simulations of Proton Transfer in DNA.

PubMed

Das, Susanta; Nam, Kwangho; Major, Dan Thomas

2018-03-13

In recent years, a number of quantum mechanical-molecular mechanical (QM/MM) enzyme studies have investigated the dependence of reaction energetics on the size of the QM region using energy and free energy calculations. In this study, we revisit the question of QM region size dependence in QM/MM simulations within the context of energy and free energy calculations using a proton transfer in a DNA base pair as a test case. In the simulations, the QM region was treated with a dispersion-corrected AM1/d-PhoT Hamiltonian, which was developed to accurately describe phosphoryl and proton transfer reactions, in conjunction with an electrostatic embedding scheme using the particle-mesh Ewald summation method. With this rigorous QM/MM potential, we performed rather extensive QM/MM sampling, and found that the free energy reaction profiles converge rapidly with respect to the QM region size within ca. ±1 kcal/mol. This finding suggests that the strategy of QM/MM simulations with reasonably sized and selected QM regions, which has been employed for over four decades, is a valid approach for modeling complex biomolecular systems. We point to possible causes for the sensitivity of the energy and free energy calculations to the size of the QM region, and potential implications.

Toward optimized potential functions for protein-protein interactions in aqueous solutions: osmotic second virial coefficient calculations using the MARTINI coarse-grained force field

PubMed Central

Stark, Austin C.; Andrews, Casey T.

2013-01-01

Coarse-grained (CG) simulation methods are now widely used to model the structure and dynamics of large biomolecular systems. One important issue for using such methods – especially with regard to using them to model, for example, intracellular environments – is to demonstrate that they can reproduce experimental data on the thermodynamics of protein-protein interactions in aqueous solutions. To examine this issue, we describe here simulations performed using the popular coarse-grained MARTINI force field, aimed at computing the thermodynamics of lysozyme and chymotrypsinogen self-interactions in aqueous solution. Using molecular dynamics simulations to compute potentials of mean force between a pair of protein molecules, we show that the original parameterization of the MARTINI force field is likely to significantly overestimate the strength of protein-protein interactions to the extent that the computed osmotic second virial coefficients are orders of magnitude more negative than experimental estimates. We then show that a simple down-scaling of the van der Waals parameters that describe the interactions between protein pseudo-atoms can bring the simulated thermodynamics into much closer agreement with experiment. Overall, the work shows that it is feasible to test explicit-solvent CG force fields directly against thermodynamic data for proteins in aqueous solutions, and highlights the potential usefulness of osmotic second virial coefficient measurements for fully parameterizing such force fields. PMID:24223529

Toward optimized potential functions for protein-protein interactions in aqueous solutions: osmotic second virial coefficient calculations using the MARTINI coarse-grained force field.

PubMed

Stark, Austin C; Andrews, Casey T; Elcock, Adrian H

2013-09-10

Coarse-grained (CG) simulation methods are now widely used to model the structure and dynamics of large biomolecular systems. One important issue for using such methods - especially with regard to using them to model, for example, intracellular environments - is to demonstrate that they can reproduce experimental data on the thermodynamics of protein-protein interactions in aqueous solutions. To examine this issue, we describe here simulations performed using the popular coarse-grained MARTINI force field, aimed at computing the thermodynamics of lysozyme and chymotrypsinogen self-interactions in aqueous solution. Using molecular dynamics simulations to compute potentials of mean force between a pair of protein molecules, we show that the original parameterization of the MARTINI force field is likely to significantly overestimate the strength of protein-protein interactions to the extent that the computed osmotic second virial coefficients are orders of magnitude more negative than experimental estimates. We then show that a simple down-scaling of the van der Waals parameters that describe the interactions between protein pseudo-atoms can bring the simulated thermodynamics into much closer agreement with experiment. Overall, the work shows that it is feasible to test explicit-solvent CG force fields directly against thermodynamic data for proteins in aqueous solutions, and highlights the potential usefulness of osmotic second virial coefficient measurements for fully parameterizing such force fields.

Thermal denaturing of mutant lysozyme with both the OPLSAA and the CHARMM force fields.

PubMed

Eleftheriou, Maria; Germain, Robert S; Royyuru, Ajay K; Zhou, Ruhong

2006-10-18

Biomolecular simulations enabled by massively parallel supercomputers such as BlueGene/L promise to bridge the gap between the currently accessible simulation time scale and the experimental time scale for many important protein folding processes. In this study, molecular dynamics simulations were carried out for both the wild-type and the mutant hen lysozyme (TRP62GLY) to study the single mutation effect on lysozyme stability and misfolding. Our thermal denaturing simulations at 400-500 K with both the OPLSAA and the CHARMM force fields show that the mutant structure is indeed much less stable than the wild-type, which is consistent with the recent urea denaturing experiment (Dobson et al. Science 2002, 295, 1719-1722; Nature 2003, 424, 783-788). Detailed results also reveal that the single mutation TRP62GLY first induces the loss of native contacts in the beta-domain region of the lysozyme protein at high temperatures, and then the unfolding process spreads into the alpha-domain region through Helix C. Even though the OPLSAA force field in general shows a more stable protein structure than does the CHARMM force field at high temperatures, the two force fields examined here display qualitatively similar results for the misfolding process, indicating that the thermal denaturing of the single mutation is robust and reproducible with various modern force fields.

GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit

PubMed Central

Pronk, Sander; Páll, Szilárd; Schulz, Roland; Larsson, Per; Bjelkmar, Pär; Apostolov, Rossen; Shirts, Michael R.; Smith, Jeremy C.; Kasson, Peter M.; van der Spoel, David; Hess, Berk; Lindahl, Erik

2013-01-01

Motivation: Molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources. Results: Here, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations. Availability: GROMACS is an open source and free software available from http://www.gromacs.org. Contact: erik.lindahl@scilifelab.se Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23407358

Competitive Adsorption and Ordered Packing of Counterions near Highly Charged Surfaces: From Mean-Field Theory to Monte Carlo Simulations

PubMed Central

Wen, Jiayi; Zhou, Shenggao; Xu, Zhenli; Li, Bo

2013-01-01

Competitive adsorption of counterions of multiple species to charged surfaces is studied by a size-effect included mean-field theory and Monte Carlo (MC) simulations. The mean-field electrostatic free-energy functional of ionic concentrations, constrained by Poisson’s equation, is numerically minimized by an augmented Lagrangian multiplier method. Unrestricted primitive models and canonical ensemble MC simulations with the Metropolis criterion are used to predict the ionic distributions around a charged surface. It is found that, for a low surface charge density, the adsorption of ions with a higher valence is preferable, agreeing with existing studies. For a highly charged surface, both of the mean-field theory and MC simulations demonstrate that the counterions bind tightly around the charged surface, resulting in a stratification of counterions of different species. The competition between mixed entropy and electrostatic energetics leads to a compromise that the ionic species with a higher valence-to-volume ratio has a larger probability to form the first layer of stratification. In particular, the MC simulations confirm the crucial role of ionic valence-to-volume ratios in the competitive adsorption to charged surfaces that had been previously predicted by the mean-field theory. The charge inversion for ionic systems with salt is predicted by the MC simulations but not by the mean-field theory. This work provides a better understanding of competitive adsorption of counterions to charged surfaces and calls for further studies on the ionic size effect with application to large-scale biomolecular modeling. PMID:22680474

Competitive adsorption and ordered packing of counterions near highly charged surfaces: From mean-field theory to Monte Carlo simulations.

PubMed

Wen, Jiayi; Zhou, Shenggao; Xu, Zhenli; Li, Bo

2012-04-01

Competitive adsorption of counterions of multiple species to charged surfaces is studied by a size-effect-included mean-field theory and Monte Carlo (MC) simulations. The mean-field electrostatic free-energy functional of ionic concentrations, constrained by Poisson's equation, is numerically minimized by an augmented Lagrangian multiplier method. Unrestricted primitive models and canonical ensemble MC simulations with the Metropolis criterion are used to predict the ionic distributions around a charged surface. It is found that, for a low surface charge density, the adsorption of ions with a higher valence is preferable, agreeing with existing studies. For a highly charged surface, both the mean-field theory and the MC simulations demonstrate that the counterions bind tightly around the charged surface, resulting in a stratification of counterions of different species. The competition between mixed entropy and electrostatic energetics leads to a compromise that the ionic species with a higher valence-to-volume ratio has a larger probability to form the first layer of stratification. In particular, the MC simulations confirm the crucial role of ionic valence-to-volume ratios in the competitive adsorption to charged surfaces that had been previously predicted by the mean-field theory. The charge inversion for ionic systems with salt is predicted by the MC simulations but not by the mean-field theory. This work provides a better understanding of competitive adsorption of counterions to charged surfaces and calls for further studies on the ionic size effect with application to large-scale biomolecular modeling.

Structural Dynamics of Carbon Dots in Water and N, N-Dimethylformamide Probed by All-Atom Molecular Dynamics Simulations.

PubMed

Paloncýová, Markéta; Langer, Michal; Otyepka, Michal

2018-04-10

Carbon dots (CDs), one of the youngest members of the carbon nanostructure family, are now widely experimentally studied for their tunable fluorescence properties, bleaching resistance, and biocompatibility. Their interaction with biomolecular systems has also been explored experimentally. However, many atomistic details still remain unresolved. Molecular dynamics (MD) simulations enabling atomistic and femtosecond resolutions simultaneously are a well-established tool of computational chemistry which can provide useful insights into investigated systems. Here we present a full procedure for performing MD simulations of CDs. We developed a builder for generating CDs of a desired size and with various oxygen-containing surface functional groups. Further, we analyzed the behavior of various CDs differing in size, surface functional groups, and degrees of functionalization by MD simulations. These simulations showed that surface functionalized CDs are stable in a water environment through the formation of an extensive hydrogen bonding network. We also analyzed the internal dynamics of individual layers of CDs and evaluated the role of surface functional groups on CD stability. We observed that carboxyl groups interconnected the neighboring layers and decreased the rate of internal rotations. Further, we monitored changes in the CD shape caused by an excess of charged carboxyl groups or carbonyl groups. In addition to simulations in water, we analyzed the behavior of CDs in the organic solvent DMF, which decreased the stability of pure CDs but increased the level of interlayer hydrogen bonding. We believe that the developed protocol, builder, and parameters will facilitate future studies addressing various aspects of structural features of CDs and nanocomposites containing CDs.

Real-space Wigner-Seitz Cells Imaging of Potassium on Graphite via Elastic Atomic Manipulation

PubMed Central

Yin, Feng; Koskinen, Pekka; Kulju, Sampo; Akola, Jaakko; Palmer, Richard E.

2015-01-01

Atomic manipulation in the scanning tunnelling microscopy, conventionally a tool to build nanostructures one atom at a time, is here employed to enable the atomic-scale imaging of a model low-dimensional system. Specifically, we use low-temperature STM to investigate an ultra thin film (4 atomic layers) of potassium created by epitaxial growth on a graphite substrate. The STM images display an unexpected honeycomb feature, which corresponds to a real-space visualization of the Wigner-Seitz cells of the close-packed surface K atoms. Density functional simulations indicate that this behaviour arises from the elastic, tip-induced vertical manipulation of potassium atoms during imaging, i.e. elastic atomic manipulation, and reflects the ultrasoft properties of the surface under strain. The method may be generally applicable to other soft e.g. molecular or biomolecular systems. PMID:25651973

SynBioSS-aided design of synthetic biological constructs.

PubMed

Kaznessis, Yiannis N

2011-01-01

We present walkthrough examples of using SynBioSS to design, model, and simulate synthetic gene regulatory networks. SynBioSS stands for Synthetic Biology Software Suite, a platform that is publicly available with Open Licenses at www.synbioss.org. An important aim of computational synthetic biology is the development of a mathematical modeling formalism that is applicable to a wide variety of simple synthetic biological constructs. SynBioSS-based modeling of biomolecular ensembles that interact away from the thermodynamic limit and not necessarily at steady state affords for a theoretical framework that is generally applicable to known synthetic biological systems, such as bistable switches, AND gates, and oscillators. Here, we discuss how SynBioSS creates links between DNA sequences and targeted dynamic phenotypes of these simple systems. Copyright © 2011 Elsevier Inc. All rights reserved.

Antiprotozoal Nitazoxanide Derivatives: Synthesis, Bioassays and QSAR Study Combined with Docking for Mechanistic Insight

PubMed Central

Scior, Thomas; Lozano-Aponte, Jorge; Ajmani, Subhash; Hernández-Montero, Eduardo; Chávez-Silva, Fabiola; Hernández-Núñez, Emanuel; Moo-Puc, Rosa; Fraguela-Collar, Andres; Navarrete-Vázquez, Gabriel

2015-01-01

In view of the serious health problems concerning infectious diseases in heavily populated areas, we followed the strategy of lead compound diversification to evaluate the near-by chemical space for new organic compounds. To this end, twenty derivatives of nitazoxanide (NTZ) were synthesized and tested for activity against Entamoeba histolytica parasites. To ensure drug-likeliness and activity relatedness of the new compounds, the synthetic work was assisted by a quantitative structure-activity relationships study (QSAR). Many of the inherent downsides – well-known to QSAR practitioners – we circumvented thanks to workarounds which we proposed in prior QSAR publication. To gain further mechanistic insight on a molecular level, ligand-enzyme docking simulations were carried out since NTZ is known to inhibit the protozoal pyruvate ferredoxin oxidoreductase (PFOR) enzyme as its biomolecular target. PMID:25872791

Thermodynamic geometry of minimum-dissipation driven barrier crossing

NASA Astrophysics Data System (ADS)

Sivak, David A.; Crooks, Gavin E.

2016-11-01

We explore the thermodynamic geometry of a simple system that models the bistable dynamics of nucleic acid hairpins in single molecule force-extension experiments. Near equilibrium, optimal (minimum-dissipation) driving protocols are governed by a generalized linear response friction coefficient. Our analysis demonstrates that the friction coefficient of the driving protocols is sharply peaked at the interface between metastable regions, which leads to minimum-dissipation protocols that drive rapidly within a metastable basin, but then linger longest at the interface, giving thermal fluctuations maximal time to kick the system over the barrier. Intuitively, the same principle applies generically in free energy estimation (both in steered molecular dynamics simulations and in single-molecule experiments), provides a design principle for the construction of thermodynamically efficient coupling between stochastic objects, and makes a prediction regarding the construction of evolved biomolecular motors.

Thermodynamic geometry of minimum-dissipation driven barrier crossing

NASA Astrophysics Data System (ADS)

Sivak, David; Crooks, Gavin

We explore the thermodynamic geometry of a simple system that models the bistable dynamics of nucleic acid hairpins in single molecule force-extension experiments. Near equilibrium, optimal (minimum-dissipation) driving protocols are governed by a generalized linear response friction coefficient. Our analysis demonstrates that the friction coefficient of the driving protocols is sharply peaked at the interface between metastable regions, which leads to minimum-dissipation protocols that drive rapidly within a metastable basin, but then linger longest at the interface, giving thermal fluctuations maximal time to kick the system over the barrier. Intuitively, the same principle applies generically in free energy estimation (both in steered molecular dynamics simulations and in single-molecule experiments), provides a design principle for the construction of thermodynamically efficient coupling between stochastic objects, and makes a prediction regarding the construction of evolved biomolecular motors.

PB-AM: An open-source, fully analytical linear poisson-boltzmann solver

DOE Office of Scientific and Technical Information (OSTI.GOV)

Felberg, Lisa E.; Brookes, David H.; Yap, Eng-Hui

2016-11-02

We present the open source distributed software package Poisson-Boltzmann Analytical Method (PB-AM), a fully analytical solution to the linearized Poisson Boltzmann equation. The PB-AM software package includes the generation of outputs files appropriate for visualization using VMD, a Brownian dynamics scheme that uses periodic boundary conditions to simulate dynamics, the ability to specify docking criteria, and offers two different kinetics schemes to evaluate biomolecular association rate constants. Given that PB-AM defines mutual polarization completely and accurately, it can be refactored as a many-body expansion to explore 2- and 3-body polarization. Additionally, the software has been integrated into the Adaptive Poisson-Boltzmannmore » Solver (APBS) software package to make it more accessible to a larger group of scientists, educators and students that are more familiar with the APBS framework.« less

Biased Brownian dynamics for rate constant calculation.

PubMed

Zou, G; Skeel, R D; Subramaniam, S

2000-08-01

An enhanced sampling method-biased Brownian dynamics-is developed for the calculation of diffusion-limited biomolecular association reaction rates with high energy or entropy barriers. Biased Brownian dynamics introduces a biasing force in addition to the electrostatic force between the reactants, and it associates a probability weight with each trajectory. A simulation loses weight when movement is along the biasing force and gains weight when movement is against the biasing force. The sampling of trajectories is then biased, but the sampling is unbiased when the trajectory outcomes are multiplied by their weights. With a suitable choice of the biasing force, more reacted trajectories are sampled. As a consequence, the variance of the estimate is reduced. In our test case, biased Brownian dynamics gives a sevenfold improvement in central processing unit (CPU) time with the choice of a simple centripetal biasing force.

Exploration of protein-protein interaction effects on α-2-macroglobulin in an inhibition of serine protease through gene expression and molecular simulations studies.

PubMed

Sivakamavalli, Jeyachandran; Selvaraj, Chandrabose; Singh, Sanjeev Kumar; Vaseeharan, Baskaralingam

2014-01-01

In Prophenoloxidase (ProPO) cascade, two targets namely serine protease and α-2-macroglobulin are key regulators involved in the defense system of crustaceans. In biological systems, routine role of cell systems requires the understanding in protein-protein interactions through experimental and theoretical concepts, which might yield useful insights into the cellular responses. Response of cells to regulating the immune system is governed by the interactions-involved biomolecular simulations. Unfortunately, studies on the inhibitors (SP and α-2M) that negatively regulate the proPO system or melanization in penaeid shrimp are not yet available. In order to understand how these interactions change the proPO mechanism in Indian white shrimp Fenneropenaeus indicus was determined. In F. indicus, innate immune system is in a sensitive balance of intricate interactions; elucidating these interactions by the integration of in silico and in vitro has great potential. We have determined the expression of both the SP and α-2M enzymes in regulatory mechanism, which are analyzed through qRT-PCR, protein-protein docking, and simulation studies. From this work, we propose a novel approach for studying an organism at the systems level by integrating genome-wide computational analysis and the gene expression data.

Nonparametric density estimation and optimal bandwidth selection for protein unfolding and unbinding data

NASA Astrophysics Data System (ADS)

Bura, E.; Zhmurov, A.; Barsegov, V.

2009-01-01

Dynamic force spectroscopy and steered molecular simulations have become powerful tools for analyzing the mechanical properties of proteins, and the strength of protein-protein complexes and aggregates. Probability density functions of the unfolding forces and unfolding times for proteins, and rupture forces and bond lifetimes for protein-protein complexes allow quantification of the forced unfolding and unbinding transitions, and mapping the biomolecular free energy landscape. The inference of the unknown probability distribution functions from the experimental and simulated forced unfolding and unbinding data, as well as the assessment of analytically tractable models of the protein unfolding and unbinding requires the use of a bandwidth. The choice of this quantity is typically subjective as it draws heavily on the investigator's intuition and past experience. We describe several approaches for selecting the "optimal bandwidth" for nonparametric density estimators, such as the traditionally used histogram and the more advanced kernel density estimators. The performance of these methods is tested on unimodal and multimodal skewed, long-tailed distributed data, as typically observed in force spectroscopy experiments and in molecular pulling simulations. The results of these studies can serve as a guideline for selecting the optimal bandwidth to resolve the underlying distributions from the forced unfolding and unbinding data for proteins.

Determination of partial molar volumes from free energy perturbation theory†

PubMed Central

Vilseck, Jonah Z.; Tirado-Rives, Julian

2016-01-01

Partial molar volume is an important thermodynamic property that gives insights into molecular size and intermolecular interactions in solution. Theoretical frameworks for determining the partial molar volume (V°) of a solvated molecule generally apply Scaled Particle Theory or Kirkwood–Buff theory. With the current abilities to perform long molecular dynamics and Monte Carlo simulations, more direct methods are gaining popularity, such as computing V° directly as the difference in computed volume from two simulations, one with a solute present and another without. Thermodynamically, V° can also be determined as the pressure derivative of the free energy of solvation in the limit of infinite dilution. Both approaches are considered herein with the use of free energy perturbation (FEP) calculations to compute the necessary free energies of solvation at elevated pressures. Absolute and relative partial molar volumes are computed for benzene and benzene derivatives using the OPLS-AA force field. The mean unsigned error for all molecules is 2.8 cm3 mol−1. The present methodology should find use in many contexts such as the development and testing of force fields for use in computer simulations of organic and biomolecular systems, as a complement to related experimental studies, and to develop a deeper understanding of solute–solvent interactions. PMID:25589343

Determination of partial molar volumes from free energy perturbation theory.

PubMed

Vilseck, Jonah Z; Tirado-Rives, Julian; Jorgensen, William L

2015-04-07

Partial molar volume is an important thermodynamic property that gives insights into molecular size and intermolecular interactions in solution. Theoretical frameworks for determining the partial molar volume (V°) of a solvated molecule generally apply Scaled Particle Theory or Kirkwood-Buff theory. With the current abilities to perform long molecular dynamics and Monte Carlo simulations, more direct methods are gaining popularity, such as computing V° directly as the difference in computed volume from two simulations, one with a solute present and another without. Thermodynamically, V° can also be determined as the pressure derivative of the free energy of solvation in the limit of infinite dilution. Both approaches are considered herein with the use of free energy perturbation (FEP) calculations to compute the necessary free energies of solvation at elevated pressures. Absolute and relative partial molar volumes are computed for benzene and benzene derivatives using the OPLS-AA force field. The mean unsigned error for all molecules is 2.8 cm(3) mol(-1). The present methodology should find use in many contexts such as the development and testing of force fields for use in computer simulations of organic and biomolecular systems, as a complement to related experimental studies, and to develop a deeper understanding of solute-solvent interactions.

A hybrid approach to simulation of electron transfer in complex molecular systems

PubMed Central

Kubař, Tomáš; Elstner, Marcus

2013-01-01

Electron transfer (ET) reactions in biomolecular systems represent an important class of processes at the interface of physics, chemistry and biology. The theoretical description of these reactions constitutes a huge challenge because extensive systems require a quantum-mechanical treatment and a broad range of time scales are involved. Thus, only small model systems may be investigated with the modern density functional theory techniques combined with non-adiabatic dynamics algorithms. On the other hand, model calculations based on Marcus's seminal theory describe the ET involving several assumptions that may not always be met. We review a multi-scale method that combines a non-adiabatic propagation scheme and a linear scaling quantum-chemical method with a molecular mechanics force field in such a way that an unbiased description of the dynamics of excess electron is achieved and the number of degrees of freedom is reduced effectively at the same time. ET reactions taking nanoseconds in systems with hundreds of quantum atoms can be simulated, bridging the gap between non-adiabatic ab initio simulations and model approaches such as the Marcus theory. A major recent application is hole transfer in DNA, which represents an archetypal ET reaction in a polarizable medium. Ongoing work focuses on hole transfer in proteins, peptides and organic semi-conductors. PMID:23883952

Identification of a new binding site in E. coli FabH using Molecular dynamics simulations: validation by computational alanine mutagenesis and docking studies.

PubMed

Ramamoorthy, Divya; Turos, Edward; Guida, Wayne C

2013-05-24

FabH (Fatty acid biosynthesis, enzyme H, also referred to as β-ketoacyl-ACP-synthase III) is a key condensing enzyme in the type II fatty acid synthesis (FAS) system. The FAS pathway in bacteria is essential for growth and survival and vastly differs from the human FAS pathway. Enzymes involved in this pathway have arisen as promising biomolecular targets for discovery of new antibacterial drugs. However, currently there are no clinical drugs that selectively target FabH, and known inhibitors of FabH all act within the active site. FabH exerts its catalytic function as a dimer, which could potentially be exploited in developing new strategies for inhibitor design. The aim of this study was to elucidate structural details of the dimer interface region by means of computational modeling, including molecular dynamics (MD) simulations, in order to derive information for the structure-based design of new FabH inhibitors. The dimer interface region was analyzed by MD simulations, trajectory snapshots were collected for further analyses, and docking studies were performed with potential small molecule disruptors. Alanine mutation and docking studies strongly suggest that the dimer interface could be a potential target for anti-infection drug discovery.

Recent advances in QM/MM free energy calculations using reference potentials☆

PubMed Central

Duarte, Fernanda; Amrein, Beat A.; Blaha-Nelson, David; Kamerlin, Shina C.L.

2015-01-01

Background Recent years have seen enormous progress in the development of methods for modeling (bio)molecular systems. This has allowed for the simulation of ever larger and more complex systems. However, as such complexity increases, the requirements needed for these models to be accurate and physically meaningful become more and more difficult to fulfill. The use of simplified models to describe complex biological systems has long been shown to be an effective way to overcome some of the limitations associated with this computational cost in a rational way. Scope of review Hybrid QM/MM approaches have rapidly become one of the most popular computational tools for studying chemical reactivity in biomolecular systems. However, the high cost involved in performing high-level QM calculations has limited the applicability of these approaches when calculating free energies of chemical processes. In this review, we present some of the advances in using reference potentials and mean field approximations to accelerate high-level QM/MM calculations. We present illustrative applications of these approaches and discuss challenges and future perspectives for the field. Major conclusions The use of physically-based simplifications has shown to effectively reduce the cost of high-level QM/MM calculations. In particular, lower-level reference potentials enable one to reduce the cost of expensive free energy calculations, thus expanding the scope of problems that can be addressed. General significance As was already demonstrated 40 years ago, the usage of simplified models still allows one to obtain cutting edge results with substantially reduced computational cost. This article is part of a Special Issue entitled Recent developments of molecular dynamics. PMID:25038480

Exploring the Conformational Transitions of Biomolecular Systems Using a Simple Two-State Anisotropic Network Model

PubMed Central

Jo, Sunhwan; Bahar, Ivet; Roux, Benoît

2014-01-01

Biomolecular conformational transitions are essential to biological functions. Most experimental methods report on the long-lived functional states of biomolecules, but information about the transition pathways between these stable states is generally scarce. Such transitions involve short-lived conformational states that are difficult to detect experimentally. For this reason, computational methods are needed to produce plausible hypothetical transition pathways that can then be probed experimentally. Here we propose a simple and computationally efficient method, called ANMPathway, for constructing a physically reasonable pathway between two endpoints of a conformational transition. We adopt a coarse-grained representation of the protein and construct a two-state potential by combining two elastic network models (ENMs) representative of the experimental structures resolved for the endpoints. The two-state potential has a cusp hypersurface in the configuration space where the energies from both the ENMs are equal. We first search for the minimum energy structure on the cusp hypersurface and then treat it as the transition state. The continuous pathway is subsequently constructed by following the steepest descent energy minimization trajectories starting from the transition state on each side of the cusp hypersurface. Application to several systems of broad biological interest such as adenylate kinase, ATP-driven calcium pump SERCA, leucine transporter and glutamate transporter shows that ANMPathway yields results in good agreement with those from other similar methods and with data obtained from all-atom molecular dynamics simulations, in support of the utility of this simple and efficient approach. Notably the method provides experimentally testable predictions, including the formation of non-native contacts during the transition which we were able to detect in two of the systems we studied. An open-access web server has been created to deliver ANMPathway results. PMID:24699246

Advanced nanoelectronic architectures for THz-based biological agent detection

NASA Astrophysics Data System (ADS)

Woolard, Dwight L.; Jensen, James O.

2009-02-01

The U.S. Army Research Office (ARO) and the U.S. Army Edgewood Chemical Biological Center (ECBC) jointly lead and support novel research programs that are advancing the state-of-the-art in nanoelectronic engineering in application areas that have relevance to national defense and security. One fundamental research area that is presently being emphasized by ARO and ECBC is the exploratory investigation of new bio-molecular architectural concepts that can be used to achieve rapid, reagent-less detection and discrimination of biological warfare (BW) agents, through the control of multi-photon and multi-wavelength processes at the nanoscale. This paper will overview an ARO/ECBC led multidisciplinary research program presently under the support of the U.S. Defense Threat Reduction Agency (DTRA) that seeks to develop new devices and nanoelectronic architectures that are effective for extracting THz signatures from target bio-molecules. Here, emphasis will be placed on the new nanosensor concepts and THz/Optical measurement methodologies for spectral-based sequencing/identification of genetic molecules.

Target Control in Logical Models Using the Domain of Influence of Nodes.

PubMed

Yang, Gang; Gómez Tejeda Zañudo, Jorge; Albert, Réka

2018-01-01

Dynamical models of biomolecular networks are successfully used to understand the mechanisms underlying complex diseases and to design therapeutic strategies. Network control and its special case of target control, is a promising avenue toward developing disease therapies. In target control it is assumed that a small subset of nodes is most relevant to the system's state and the goal is to drive the target nodes into their desired states. An example of target control would be driving a cell to commit to apoptosis (programmed cell death). From the experimental perspective, gene knockout, pharmacological inhibition of proteins, and providing sustained external signals are among practical intervention techniques. We identify methodologies to use the stabilizing effect of sustained interventions for target control in Boolean network models of biomolecular networks. Specifically, we define the domain of influence (DOI) of a node (in a certain state) to be the nodes (and their corresponding states) that will be ultimately stabilized by the sustained state of this node regardless of the initial state of the system. We also define the related concept of the logical domain of influence (LDOI) of a node, and develop an algorithm for its identification using an auxiliary network that incorporates the regulatory logic. This way a solution to the target control problem is a set of nodes whose DOI can cover the desired target node states. We perform greedy randomized adaptive search in node state space to find such solutions. We apply our strategy to in silico biological network models of real systems to demonstrate its effectiveness.

Markov state models from short non-equilibrium simulations—Analysis and correction of estimation bias

NASA Astrophysics Data System (ADS)

Nüske, Feliks; Wu, Hao; Prinz, Jan-Hendrik; Wehmeyer, Christoph; Clementi, Cecilia; Noé, Frank

2017-03-01

Many state-of-the-art methods for the thermodynamic and kinetic characterization of large and complex biomolecular systems by simulation rely on ensemble approaches, where data from large numbers of relatively short trajectories are integrated. In this context, Markov state models (MSMs) are extremely popular because they can be used to compute stationary quantities and long-time kinetics from ensembles of short simulations, provided that these short simulations are in "local equilibrium" within the MSM states. However, over the last 15 years since the inception of MSMs, it has been controversially discussed and not yet been answered how deviations from local equilibrium can be detected, whether these deviations induce a practical bias in MSM estimation, and how to correct for them. In this paper, we address these issues: We systematically analyze the estimation of MSMs from short non-equilibrium simulations, and we provide an expression for the error between unbiased transition probabilities and the expected estimate from many short simulations. We show that the unbiased MSM estimate can be obtained even from relatively short non-equilibrium simulations in the limit of long lag times and good discretization. Further, we exploit observable operator model (OOM) theory to derive an unbiased estimator for the MSM transition matrix that corrects for the effect of starting out of equilibrium, even when short lag times are used. Finally, we show how the OOM framework can be used to estimate the exact eigenvalues or relaxation time scales of the system without estimating an MSM transition matrix, which allows us to practically assess the discretization quality of the MSM. Applications to model systems and molecular dynamics simulation data of alanine dipeptide are included for illustration. The improved MSM estimator is implemented in PyEMMA of version 2.3.

Simulated Tempering Distributed Replica Sampling, Virtual Replica Exchange, and Other Generalized-Ensemble Methods for Conformational Sampling.

PubMed

Rauscher, Sarah; Neale, Chris; Pomès, Régis

2009-10-13

Generalized-ensemble algorithms in temperature space have become popular tools to enhance conformational sampling in biomolecular simulations. A random walk in temperature leads to a corresponding random walk in potential energy, which can be used to cross over energetic barriers and overcome the problem of quasi-nonergodicity. In this paper, we introduce two novel methods: simulated tempering distributed replica sampling (STDR) and virtual replica exchange (VREX). These methods are designed to address the practical issues inherent in the replica exchange (RE), simulated tempering (ST), and serial replica exchange (SREM) algorithms. RE requires a large, dedicated, and homogeneous cluster of CPUs to function efficiently when applied to complex systems. ST and SREM both have the drawback of requiring extensive initial simulations, possibly adaptive, for the calculation of weight factors or potential energy distribution functions. STDR and VREX alleviate the need for lengthy initial simulations, and for synchronization and extensive communication between replicas. Both methods are therefore suitable for distributed or heterogeneous computing platforms. We perform an objective comparison of all five algorithms in terms of both implementation issues and sampling efficiency. We use disordered peptides in explicit water as test systems, for a total simulation time of over 42 μs. Efficiency is defined in terms of both structural convergence and temperature diffusion, and we show that these definitions of efficiency are in fact correlated. Importantly, we find that ST-based methods exhibit faster temperature diffusion and correspondingly faster convergence of structural properties compared to RE-based methods. Within the RE-based methods, VREX is superior to both SREM and RE. On the basis of our observations, we conclude that ST is ideal for simple systems, while STDR is well-suited for complex systems.

Design and Implementation of a Biomolecular Concentration Tracker

PubMed Central

2015-01-01

As a field, synthetic biology strives to engineer increasingly complex artificial systems in living cells. Active feedback in closed loop systems offers a dynamic and adaptive way to ensure constant relative activity independent of intrinsic and extrinsic noise. In this work, we use synthetic protein scaffolds as a modular and tunable mechanism for concentration tracking through negative feedback. Input to the circuit initiates scaffold production, leading to colocalization of a two-component system and resulting in the production of an inhibitory antiscaffold protein. Using a combination of modeling and experimental work, we show that the biomolecular concentration tracker circuit achieves dynamic protein concentration tracking in Escherichia coli and that steady state outputs can be tuned. PMID:24847683

Looking towards label-free biomolecular interaction analysis in a high-throughput format: a review of new surface plasmon resonance technologies.

PubMed

Boozer, Christina; Kim, Gibum; Cong, Shuxin; Guan, Hannwen; Londergan, Timothy

2006-08-01

Surface plasmon resonance (SPR) biosensors have enabled a wide range of applications in which researchers can monitor biomolecular interactions in real time. Owing to the fact that SPR can provide affinity and kinetic data, unique features in applications ranging from protein-peptide interaction analysis to cellular ligation experiments have been demonstrated. Although SPR has historically been limited by its throughput, new methods are emerging that allow for the simultaneous analysis of many thousands of interactions. When coupled with new protein array technologies, high-throughput SPR methods give users new and improved methods to analyze pathways, screen drug candidates and monitor protein-protein interactions.

In situ monitoring of biomolecular processes in living systems using surface-enhanced Raman scattering

NASA Astrophysics Data System (ADS)

Altunbek, Mine; Kelestemur, Seda; Culha, Mustafa

2015-12-01

Surface-enhanced Raman scattering (SERS) continues to strive to gather molecular level information from dynamic biological systems. It is our ongoing effort to utilize the technique for understanding of the biomolecular processes in living systems such as eukaryotic and prokaryotic cells. In this study, the technique is investigated to identify cell death mechanisms in 2D and 3D in vitro cell culture models, which is a very important process in tissue engineering and pharmaceutical applications. Second, in situ biofilm formation monitoring is investigated to understand how microorganisms respond to the environmental stimuli, which inferred information can be used to interfere with biofilm formation and fight against their pathogenic activity.

Silicon-nanomembrane-based photonic crystal nanostructures for chip-integrated open sensor systems

NASA Astrophysics Data System (ADS)

Chakravarty, Swapnajit; Lai, Wei-Cheng; Zou, Yi; Lin, Cheyun; Wang, Xiaolong; Chen, Ray T.

2011-11-01

We experimentally demonstrate two devices on the photonic crystal platform for chip-integrated optical absorption spectroscopy and chip-integrated biomolecular microarray assays. Infrared optical absorption spectroscopy and biomolecular assays based on conjugate-specific binding principles represent two dominant sensing mechanisms for a wide spectrum of applications in environmental pollution sensing in air and water, chem-bio agents and explosives detection for national security, microbial contamination sensing in food and beverages to name a few. The easy scalability of photonic crystal devices to any wavelength ensures that the sensing principles hold across a wide electromagnetic spectrum. Silicon, the workhorse of the electronics industry, is an ideal platform for the above optical sensing applications.

A new approach to implement absorbing boundary condition in biomolecular electrostatics.

PubMed

Goni, Md Osman

2013-01-01

This paper discusses a novel approach to employ the absorbing boundary condition in conjunction with the finite-element method (FEM) in biomolecular electrostatics. The introduction of Bayliss-Turkel absorbing boundary operators in electromagnetic scattering problem has been incorporated by few researchers. However, in the area of biomolecular electrostatics, this boundary condition has not been investigated yet. The objective of this paper is twofold. First, to solve nonlinear Poisson-Boltzmann equation using Newton's method and second, to find an efficient and acceptable solution with minimum number of unknowns. In this work, a Galerkin finite-element formulation is used along with a Bayliss-Turkel absorbing boundary operator that explicitly accounts for the open field problem by mapping the Sommerfeld radiation condition from the far field to near field. While the Bayliss-Turkel condition works well when the artificial boundary is far from the scatterer, an acceptable tolerance of error can be achieved with the second order operator. Numerical results on test case with simple sphere show that the treatment is able to reach the same level of accuracy achieved by the analytical method while using a lower grid density. Bayliss-Turkel absorbing boundary condition (BTABC) combined with the FEM converges to the exact solution of scattering problems to within discretization error.

Biomolecular signatures of diabetic wound healing by structural mass spectrometry

PubMed Central

Hines, Kelly M.; Ashfaq, Samir; Davidson, Jeffrey M.; Opalenik, Susan R.; Wikswo, John P.; McLean, John A.

2013-01-01

Wound fluid is a complex biological sample containing byproducts associated with the wound repair process. Contemporary techniques, such as immunoblotting and enzyme immunoassays, require extensive sample manipulation and do not permit the simultaneous analysis of multiple classes of biomolecular species. Structural mass spectrometry, implemented as ion mobility-mass spectrometry (IM-MS), comprises two sequential, gas-phase dispersion techniques well suited for the study of complex biological samples due to its ability to separate and simultaneously analyze multiple classes of biomolecules. As a model of diabetic wound healing, polyvinyl alcohol (PVA) sponges were inserted subcutaneously into non-diabetic (control) and streptozotocin-induced diabetic rats to elicit a granulation tissue response and to collect acute wound fluid. Sponges were harvested at days 2 or 5 to capture different stages of the early wound healing process. Utilizing IM-MS, statistical analysis, and targeted ultra-performance liquid chromatography (UPLC) analysis, biomolecular signatures of diabetic wound healing have been identified. The protein S100-A8 was highly enriched in the wound fluids collected from day 2 diabetic rats. Lysophosphatidylcholine (20:4) and cholic acid also contributed significantly to the differences between diabetic and control groups. This report provides a generalized workflow for wound fluid analysis demonstrated with a diabetic rat model. PMID:23452326

Discriminative and informative features for biomolecular text mining with ensemble feature selection.

PubMed

Van Landeghem, Sofie; Abeel, Thomas; Saeys, Yvan; Van de Peer, Yves

2010-09-15

In the field of biomolecular text mining, black box behavior of machine learning systems currently limits understanding of the true nature of the predictions. However, feature selection (FS) is capable of identifying the most relevant features in any supervised learning setting, providing insight into the specific properties of the classification algorithm. This allows us to build more accurate classifiers while at the same time bridging the gap between the black box behavior and the end-user who has to interpret the results. We show that our FS methodology successfully discards a large fraction of machine-generated features, improving classification performance of state-of-the-art text mining algorithms. Furthermore, we illustrate how FS can be applied to gain understanding in the predictions of a framework for biomolecular event extraction from text. We include numerous examples of highly discriminative features that model either biological reality or common linguistic constructs. Finally, we discuss a number of insights from our FS analyses that will provide the opportunity to considerably improve upon current text mining tools. The FS algorithms and classifiers are available in Java-ML (http://java-ml.sf.net). The datasets are publicly available from the BioNLP'09 Shared Task web site (http://www-tsujii.is.s.u-tokyo.ac.jp/GENIA/SharedTask/).

Smartphones for cell and biomolecular detection.

PubMed

Liu, Xiyuan; Lin, Tung-Yi; Lillehoj, Peter B

2014-11-01

Recent advances in biomedical science and technology have played a significant role in the development of new sensors and assays for cell and biomolecular detection. Generally, these efforts are aimed at reducing the complexity and costs associated with diagnostic testing so that it can be performed outside of a laboratory or hospital setting, requiring minimal equipment and user involvement. In particular, point-of-care (POC) testing offers immense potential for many important applications including medical diagnosis, environmental monitoring, food safety, and biosecurity. When coupled with smartphones, POC systems can offer portability, ease of use and enhanced functionality while maintaining performance. This review article focuses on recent advancements and developments in smartphone-based POC systems within the last 6 years with an emphasis on cell and biomolecular detection. These devices typically comprise multiple components, such as detectors, sample processors, disposable chips, batteries, and software, which are integrated with a commercial smartphone. One of the most important aspects of developing these systems is the integration of these components onto a compact and lightweight platform that requires minimal power. Researchers have demonstrated several promising approaches employing various detection schemes and device configurations, and it is expected that further developments in biosensors, battery technology and miniaturized electronics will enable smartphone-based POC technologies to become more mainstream tools in the scientific and biomedical communities.

Mathematical Modeling of RNA-Based Architectures for Closed Loop Control of Gene Expression.

PubMed

Agrawal, Deepak K; Tang, Xun; Westbrook, Alexandra; Marshall, Ryan; Maxwell, Colin S; Lucks, Julius; Noireaux, Vincent; Beisel, Chase L; Dunlop, Mary J; Franco, Elisa

2018-05-08

Feedback allows biological systems to control gene expression precisely and reliably, even in the presence of uncertainty, by sensing and processing environmental changes. Taking inspiration from natural architectures, synthetic biologists have engineered feedback loops to tune the dynamics and improve the robustness and predictability of gene expression. However, experimental implementations of biomolecular control systems are still far from satisfying performance specifications typically achieved by electrical or mechanical control systems. To address this gap, we present mathematical models of biomolecular controllers that enable reference tracking, disturbance rejection, and tuning of the temporal response of gene expression. These controllers employ RNA transcriptional regulators to achieve closed loop control where feedback is introduced via molecular sequestration. Sensitivity analysis of the models allows us to identify which parameters influence the transient and steady state response of a target gene expression process, as well as which biologically plausible parameter values enable perfect reference tracking. We quantify performance using typical control theory metrics to characterize response properties and provide clear selection guidelines for practical applications. Our results indicate that RNA regulators are well-suited for building robust and precise feedback controllers for gene expression. Additionally, our approach illustrates several quantitative methods useful for assessing the performance of biomolecular feedback control systems.

Force Field Model of Periodic Trends in Biomolecular Halogen Bonds

PubMed Central

Scholfield, Matthew R.; Ford, Melissa Coates; Vander Zanden, Crystal M.; Billman, M. Marie; Ho, P. Shing; Rappé, Anthony K.

2016-01-01

The study of the noncovalent interaction now defined as a halogen bond (X-bond) has become one of the fastest growing areas in experimental and theoretical chemistry—its applications as a design tool are highly extensive. The significance of the interaction in biology has only recently been recognized, but has now become important in medicinal chemistry. We had previously derived a set of empirical potential energy functions to model the structure-energy relationships for bromines in biomolecular X-bonds (BXBs). Here, we have extended this force field for BXBs (ffBXB) to the halogens (Cl, Br, and I) that are commonly seen to form stable X-bonds. The ffBXB calculated energies show a remarkable one-to-one linear relationship to explicit BXB energies determined from an experimental DNA junction system, thereby validating the approach and the model. The resulting parameters allow us to interpret the stabilizing effects of BXBs in terms of well-defined physical properties of the halogen atoms, including their size, shape, and charge, showing periodic trends that are predictable along the Group VII column of elements. Consequently, we have established the ffBXB as accurate computational tool that can be applied to, for example, for the design of new therapeutic compounds against clinically important targets and new biomolecular based materials. PMID:25338128

Programmable DNA scaffolds for spatially-ordered protein assembly

NASA Astrophysics Data System (ADS)

Chandrasekaran, Arun Richard

2016-02-01

Ever since the notion of using DNA as a material was realized, it has been employed in the construction of complex structures that facilitate the assembly of nanoparticles or macromolecules with nanometer-scale precision. Specifically, tiles fashioned from DNA strands and DNA origami sheets have been shown to be suitable as scaffolds for immobilizing proteins with excellent control over their spatial positioning. Supramolecular assembly of proteins into periodic arrays in one or more dimensions is one of the most challenging aspects in the design of scaffolds for biomolecular investigations and macromolecular crystallization. This review provides a brief overview of how various biomolecular interactions with high degree of specificity such as streptavidin-biotin, antigen-antibody, and aptamer-protein interactions have been used to fabricate linear and multidimensional assemblies of structurally intact and functional proteins. The use of DNA-binding proteins as adaptors, polyamide recognition on DNA scaffolds and oligonucleotide linkers for protein assembly are also discussed.Ever since the notion of using DNA as a material was realized, it has been employed in the construction of complex structures that facilitate the assembly of nanoparticles or macromolecules with nanometer-scale precision. Specifically, tiles fashioned from DNA strands and DNA origami sheets have been shown to be suitable as scaffolds for immobilizing proteins with excellent control over their spatial positioning. Supramolecular assembly of proteins into periodic arrays in one or more dimensions is one of the most challenging aspects in the design of scaffolds for biomolecular investigations and macromolecular crystallization. This review provides a brief overview of how various biomolecular interactions with high degree of specificity such as streptavidin-biotin, antigen-antibody, and aptamer-protein interactions have been used to fabricate linear and multidimensional assemblies of structurally intact and functional proteins. The use of DNA-binding proteins as adaptors, polyamide recognition on DNA scaffolds and oligonucleotide linkers for protein assembly are also discussed. Dedicated to my advisor Ned Seeman on the occasion of his 70th birthday.

Raman spectroscopy detects biomolecular changes associated with nanoencapsulated hesperetin treatment in experimental oral carcinogenesis

NASA Astrophysics Data System (ADS)

Gurushankar, K.; Gohulkumar, M.; Kumar, Piyush; Krishna, C. Murali; Krishnakumar, N.

2016-03-01

Recently it has been shown that Raman spectroscopy possesses great potential in the investigation of biomolecular changes of tumor tissues with therapeutic drug response in a non-invasive and label-free manner. The present study is designed to investigate the antitumor effect of hespertin-loaded nanoparticles (HETNPs) relative to the efficacy of native hesperetin (HET) in modifying the biomolecular changes during 7,12-dimethyl benz(a)anthracene (DMBA)-induced oral carcinogenesis using a Raman spectroscopic technique. Significant differences in the intensity and shape of the Raman spectra between the control and the experimental tissues at 1800-500 cm-1 were observed. Tumor tissues are characterized by an increase in the relative amount of proteins, nucleic acids, tryptophan and phenylalanine and a decrease in the percentage of lipids when compared to the control tissues. Further, oral administration of HET and its nanoparticulates restored the status of the lipids and significantly decreased the levels of protein and nucleic acid content. Treatment with HETNPs showed a more potent antitumor effect than treatment with native HET, which resulted in an overall reduction in the intensity of several biochemical Raman bands in DMBA-induced oral carcinogenesis being observed. Principal component and linear discriminant analysis (PC-LDA), together with leave-one-out cross validation (LOOCV) on Raman spectra yielded diagnostic sensitivities of 100%, 80%, 91.6% and 65% and specificities of 100%, 65%, 60% and 55% for classification of control versus DMBA, DMBA versus DMBA  +  HET, DMBA versus DMBA  +  HETNPs and DMBA  +  HET versus DMBA  +  HETNPs treated tissue groups, respectively. These results further demonstrate that Raman spectroscopy associated with multivariate statistical algorithms could be a valuable tool for developing a comprehensive understanding of the process of biomolecular changes, and could reveal the signatures of the antitumor response of drugs.

Investigation of the human disease osteogenesis imperfecta: a research-based introduction to concepts and skills in biomolecular analysis.

PubMed

Mate, Karen; Sim, Alistair; Weidenhofer, Judith; Milward, Liz; Scott, Judith

2013-01-01

A blended approach encompassing problem-based learning (PBL) and structured inquiry was used in this laboratory exercise based on the congenital disease Osteogenesis imperfecta (OI), to introduce commonly used techniques in biomolecular analysis within a clinical context. During a series of PBL sessions students were presented with several scenarios involving a 2 year old child, who had experienced numerous fractures. Key learning goals related to both the theory and practical aspects of the course, covering biomolecular analysis and functional genomics, were identified in successive PBL sessions. The laboratory exercises were conducted in 3 hour blocks over six weeks, focused firstly on protein analysis, followed by nucleic acids. Students isolated collagen from normal and OI affected fibroblast cultures. Analysis by SDS-PAGE demonstrated α1 and α2 of collagen Type I chains at approximately 95 kDa and 92 kDa, respectively. Subtle differences in protein mobility between the control and OI samples were observed by some students, but most considered it inconclusive as a diagnostic tool. The nucleic acid module involved isolation of RNA from OI affected fibroblasts. The RNA was reverse transcribed and used as template to amplify a 354 bp COL1A1 fragment. Students were provided with the sequence of the OI affected COL1A1 PCR product aligned with the normal COL1A1 sequence, allowing identification of the mutation, as the substitution of Arg for Gly(976) of the triple helical region. Our experience with student cohorts over several years is that presentation of this laboratory exercise within a relevant clinical context, and the opportunity for active engagement with the experimental procedures via PBL sessions, supported the learning of basic theory and practical techniques of biomolecular analysis. Copyright © 2013 International Union of Biochemistry and Molecular Biology, Inc.

Evaluation of kinetic constants of biomolecular interaction on optical surface plasmon resonance sensor with Newton Iteration Method

NASA Astrophysics Data System (ADS)

Zhao, Yuanyuan; Jiang, Guoliang; Hu, Jiandong; Hu, Fengjiang; Wei, Jianguang; Shi, Liang

2010-10-01

In the immunology, there are two important types of biomolecular interaction: antigens-antibodies and receptors-ligands. Monitoring the response rate and affinity of biomolecular interaction can help analyze the protein function, drug discover, genomics and proteomics research. Moreover the association rate constant and dissociation rate constant of receptors-ligands are the important parameters for the study of signal transmission between cells. Recent advances in bioanalyzer instruments have greatly simplified the measurement of the kinetics of molecular interactions. Non-destructive and real-time monitoring the response to evaluate the parameters between antigens and antibodies can be performed by using optical surface plasmon resonance (SPR) biosensor technology. This technology provides a quantitative analysis that is carried out rapidly with label-free high-throughput detection using the binding curves of antigens-antibodies. Consequently, the kinetic parameters of interaction between antigens and antibodies can be obtained. This article presents a low cost integrated SPR-based bioanalyzer (HPSPR-6000) designed by ourselves. This bioanalyzer is mainly composed of a biosensor TSPR1K23, a touch-screen monitor, a microprocessor PIC24F128, a microflow cell with three channels, a clamp and a photoelectric conversion device. To obtain the kinetic parameters, sensorgrams may be modeled using one of several binding models provided with BIAevaluation software 3.0, SensiQ or Autolab. This allows calculation of the association rate constant (ka) and the dissociation rate constant (kd). The ratio of ka to kd can be used to estimate the equilibrium constant. Another kind is the analysis software OriginPro, which can process the obtained data by nonlinear fitting and then get some correlative parameters, but it can't be embedded into the bioanalyzer, so the bioanalyzer don't support the use of OriginPro. This paper proposes a novel method to evaluate the kinetic parameters of biomolecular interaction by using Newton Iteration Method and Least Squares Method. First, the pseudo first order kinetic model of biomolecular interaction was established. Then the data of molecular interaction of HBsAg and HBsAb was obtained by bioanalyzer. Finally, we used the optical SPR bioanalyzer software which was written by ourselves to make nonlinear fit about the association and dissociation curves. The correlation coefficient R-squared is 0.99229 and 0.99593, respectively. Furthermore, the kinetic parameters and affinity constants were evaluated using the obtained data from the fitting results.

Surface plasmon resonance-based molecular detection of Hb S [beta6(A3)Glu-->Val, GAG-->GTG] at the gene level.

PubMed

Atalay, Erol O; Ustel, Emre; Yildiz, Sanem; Atalay, Ayfer

2006-01-01

The surface plasmon resonance (SPR) approach, being a relatively novel biophysical method, is used to detect many different targets by biomolecular interaction. The SPR system uses optical and evanescent wave phenomenon. This approach does not need any labels, such as enzymes or isotopes, and the monitored interactions are in real time. In DNA-DNA interaction, the SPR approach is Tm-independent. Here we report our preliminary results for the molecular detection of the Hb S (GAG -->GTG) mutation at codon 6 of the human beta-globin gene. Our preliminary results show that the SPR approach could be applied as an inexpensive and fast routine test system for the molecular diagnosis of abnormal hemoglobins (Hbs), especially in premarital screening programs.

Hamiltonian adaptive resolution molecular dynamics simulation of infrared dielectric functions of liquids

NASA Astrophysics Data System (ADS)

Wang, C. C.; Tan, J. Y.; Liu, L. H.

2018-05-01

Hamiltonian adaptive resolution scheme (H-AdResS), which allows to simulate materials by treating different domains of the system at different levels of resolution, is a recently proposed atomistic/coarse-grained multiscale model. In this work, a scheme to calculate the dielectric functions of liquids on account of H-AdResS is presented. In the proposed H-AdResS dielectric-function calculation scheme (DielectFunctCalS), the corrected molecular dipole moments are calculated by multiplying molecular dipole moment by the weighting fraction of the molecular mapping point. As the widths of all-atom and hybrid regions show different degrees of influence on the dielectric functions, a prefactor is multiplied to eliminate the effects of all-atom and hybrid region widths. Since one goal of using the H-AdResS method is to reduce computational costs, widths of the all-atom region and the hybrid region can be reduced considering that the coarse-grained simulation is much more timesaving compared to atomistic simulation. Liquid water and ethanol are taken as test cases to validate the DielectFunctCalS. The H-AdResS DielectFunctCalS results are in good agreement with all-atom molecular dynamics simulations. The accuracy of the H-AdResS results, together with all-atom molecular dynamics results, depends heavily on the choice of the force field and force field parameters. The H-AdResS DielectFunctCalS allows us to calculate the dielectric functions of macromolecule systems with high efficiency and makes the dielectric function calculations of large biomolecular systems possible.

Surface-Tension Replica-Exchange Molecular Dynamics Method for Enhanced Sampling of Biological Membrane Systems.

PubMed

Mori, Takaharu; Jung, Jaewoon; Sugita, Yuji

2013-12-10

Conformational sampling is fundamentally important for simulating complex biomolecular systems. The generalized-ensemble algorithm, especially the temperature replica-exchange molecular dynamics method (T-REMD), is one of the most powerful methods to explore structures of biomolecules such as proteins, nucleic acids, carbohydrates, and also of lipid membranes. T-REMD simulations have focused on soluble proteins rather than membrane proteins or lipid bilayers, because explicit membranes do not keep their structural integrity at high temperature. Here, we propose a new generalized-ensemble algorithm for membrane systems, which we call the surface-tension REMD method. Each replica is simulated in the NPγT ensemble, and surface tensions in a pair of replicas are exchanged at certain intervals to enhance conformational sampling of the target membrane system. We test the method on two biological membrane systems: a fully hydrated DPPC (1,2-dipalmitoyl-sn-glycero-3-phosphatidylcholine) lipid bilayer and a WALP23-POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) membrane system. During these simulations, a random walk in surface tension space is realized. Large-scale lateral deformation (shrinking and stretching) of the membranes takes place in all of the replicas without collapse of the lipid bilayer structure. There is accelerated lateral diffusion of DPPC lipid molecules compared with conventional MD simulation, and a much wider range of tilt angle of the WALP23 peptide is sampled due to large deformation of the POPC lipid bilayer and through peptide-lipid interactions. Our method could be applicable to a wide variety of biological membrane systems.

Combining experimental and simulation data of molecular processes via augmented Markov models.

PubMed

Olsson, Simon; Wu, Hao; Paul, Fabian; Clementi, Cecilia; Noé, Frank

2017-08-01

Accurate mechanistic description of structural changes in biomolecules is an increasingly important topic in structural and chemical biology. Markov models have emerged as a powerful way to approximate the molecular kinetics of large biomolecules while keeping full structural resolution in a divide-and-conquer fashion. However, the accuracy of these models is limited by that of the force fields used to generate the underlying molecular dynamics (MD) simulation data. Whereas the quality of classical MD force fields has improved significantly in recent years, remaining errors in the Boltzmann weights are still on the order of a few [Formula: see text], which may lead to significant discrepancies when comparing to experimentally measured rates or state populations. Here we take the view that simulations using a sufficiently good force-field sample conformations that are valid but have inaccurate weights, yet these weights may be made accurate by incorporating experimental data a posteriori. To do so, we propose augmented Markov models (AMMs), an approach that combines concepts from probability theory and information theory to consistently treat systematic force-field error and statistical errors in simulation and experiment. Our results demonstrate that AMMs can reconcile conflicting results for protein mechanisms obtained by different force fields and correct for a wide range of stationary and dynamical observables even when only equilibrium measurements are incorporated into the estimation process. This approach constitutes a unique avenue to combine experiment and computation into integrative models of biomolecular structure and dynamics.

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview.

PubMed

Šponer, Jiří; Bussi, Giovanni; Krepl, Miroslav; Banáš, Pavel; Bottaro, Sandro; Cunha, Richard A; Gil-Ley, Alejandro; Pinamonti, Giovanni; Poblete, Simón; Jurečka, Petr; Walter, Nils G; Otyepka, Michal

2018-04-25

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.

Blood analysis by Raman spectroscopy.

PubMed

Enejder, Annika M K; Koo, Tae-Woong; Oh, Jeankun; Hunter, Martin; Sasic, Slobodan; Feld, Michael S; Horowitz, Gary L

2002-11-15

Concentrations of multiple analytes were simultaneously measured in whole blood with clinical accuracy, without sample processing, using near-infrared Raman spectroscopy. Spectra were acquired with an instrument employing nonimaging optics, designed using Monte Carlo simulations of the influence of light-scattering-absorbing blood cells on the excitation and emission of Raman light in turbid medium. Raman spectra were collected from whole blood drawn from 31 individuals. Quantitative predictions of glucose, urea, total protein, albumin, triglycerides, hematocrit, and hemoglobin were made by means of partial least-squares (PLS) analysis with clinically relevant precision (r(2) values >0.93). The similarity of the features of the PLS calibration spectra to those of the respective analyte spectra illustrates that the predictions are based on molecular information carried by the Raman light. This demonstrates the feasibility of using Raman spectroscopy for quantitative measurements of biomolecular contents in highly light-scattering and absorbing media.

How Actuated Particles Effectively Capture Biomolecular Targets

PubMed Central

2017-01-01

Because of their high surface-to-volume ratio and adaptable surface functionalization, particles are widely used in bioanalytical methods to capture molecular targets. In this article, a comprehensive study is reported of the effectiveness of protein capture by actuated magnetic particles. Association rate constants are quantified in experiments as well as in Brownian dynamics simulations for different particle actuation configurations. The data reveal how the association rate depends on the particle velocity, particle density, and particle assembly characteristics. Interestingly, single particles appear to exhibit target depletion zones near their surface, caused by the high density of capture molecules. The depletion effects are even more limiting in cases with high particle densities. The depletion effects are overcome and protein capture rates are enhanced by applying dynamic particle actuation, resulting in an increase in the association rate constants by up to 2 orders of magnitude. PMID:28192952

Molecular modeling of the conformational dynamics of the cellular prion protein

NASA Astrophysics Data System (ADS)

Nguyen, Charles; Colling, Ian; Bartz, Jason; Soto, Patricia

2014-03-01

Prions are infectious agents responsible for transmissible spongiform encephalopathies (TSEs), a type of fatal neurodegenerative disease in mammals. Prions propagate biological information by conversion of the non-pathological version of the prion protein to the infectious conformation, PrPSc. A wealth of knowledge has shed light on the nature and mechanism of prion protein conversion. In spite of the significance of this problem, we are far from fully understanding the conformational dynamics of the cellular isoform. To remedy this situation we employ multiple biomolecular modeling techniques such as docking and molecular dynamics simulations to map the free energy landscape and determine what specific regions of the prion protein are most conductive to binding. The overall goal is to characterize the conformational dynamics of the cell form of the prion protein, PrPc, to gain insight into inhibition pathways against misfolding. NE EPSCoR FIRST Award to Patricia Soto.

Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm.

PubMed

Yu, Isseki; Mori, Takaharu; Ando, Tadashi; Harada, Ryuhei; Jung, Jaewoon; Sugita, Yuji; Feig, Michael

2016-11-01

Biological macromolecules function in highly crowded cellular environments. The structure and dynamics of proteins and nucleic acids are well characterized in vitro, but in vivo crowding effects remain unclear. Using molecular dynamics simulations of a comprehensive atomistic model cytoplasm we found that protein-protein interactions may destabilize native protein structures, whereas metabolite interactions may induce more compact states due to electrostatic screening. Protein-protein interactions also resulted in significant variations in reduced macromolecular diffusion under crowded conditions, while metabolites exhibited significant two-dimensional surface diffusion and altered protein-ligand binding that may reduce the effective concentration of metabolites and ligands in vivo. Metabolic enzymes showed weak non-specific association in cellular environments attributed to solvation and entropic effects. These effects are expected to have broad implications for the in vivo functioning of biomolecules. This work is a first step towards physically realistic in silico whole-cell models that connect molecular with cellular biology.

Anomalous Dynamics of Water Confined in Protein-Protein and Protein-DNA Interfaces.

PubMed

Chong, Song-Ho; Ham, Sihyun

2016-10-06

Confined water often exhibits anomalous properties not observable in the bulk phase. Although water in hydrophobic confinement has been the focus of intense investigation, the behavior of water confined between hydrophilic surfaces, which are more frequently found in biological systems, has not been fully explored. Here, we investigate using molecular dynamics simulations dynamical properties of the water confined in hydrophilic protein-protein and protein-DNA interfaces. We find that the interfacial water exhibits glassy slow relaxations even at 300 K. In particular, the rotational dynamics show a logarithmic decay that was observed in glass-forming liquids at deeply supercooled states. We argue that such slow water dynamics are indeed induced by the hydrophilic binding surfaces, which is in opposition to the picture that the hydration water slaves protein motions. Our results will significantly impact the view on the role of water in biomolecular interactions.

Structure of a low-population intermediate state in the release of an enzyme product.

PubMed

De Simone, Alfonso; Aprile, Francesco A; Dhulesia, Anne; Dobson, Christopher M; Vendruscolo, Michele

2015-01-09

Enzymes can increase the rate of biomolecular reactions by several orders of magnitude. Although the steps of substrate capture and product release are essential in the enzymatic process, complete atomic-level descriptions of these steps are difficult to obtain because of the transient nature of the intermediate conformations, which makes them largely inaccessible to standard structure determination methods. We describe here the determination of the structure of a low-population intermediate in the product release process by human lysozyme through a combination of NMR spectroscopy and molecular dynamics simulations. We validate this structure by rationally designing two mutations, the first engineered to destabilise the intermediate and the second to stabilise it, thus slowing down or speeding up, respectively, product release. These results illustrate how product release by an enzyme can be facilitated by the presence of a metastable intermediate with transient weak interactions between the enzyme and product.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wolf, Steffen; Gerwert, Klaus, E-mail: gerwert@bph.rub.de; Department of Biophysics, Chinese Academy of Sciences, Max-Planck-Gesellschaft Partner Institute for Computational Biology, 320 Yue Yang Road, 200031 Shanghai

Proton conduction along protein-bound “water wires” is an essential feature in membrane proteins. Here, we analyze in detail a transient water wire, which conducts protons via a hydrophobic barrier within a membrane protein to create a proton gradient. It is formed only for a millisecond out of three water molecules distributed at inactive positions in a polar environment in the ground state. The movement into a hydrophobic environment causes characteristic shifts of the water bands reflecting their different chemical properties. These band shifts are identified by time-resolved Fourier Transform Infrared difference spectroscopy and analyzed by biomolecular Quantum Mechanical/Molecular Mechanical simulations.more » A non-hydrogen bonded (“dangling”) O–H stretching vibration band and a broad continuum absorbance caused by a combined vibration along the water wire are identified as characteristic marker bands of such water wires in a hydrophobic environment. The results provide a basic understanding of water wires in hydrophobic environments.« less

Calculation and Visualization of Atomistic Mechanical Stresses in Nanomaterials and Biomolecules

PubMed Central

Gilson, Michael K.

2014-01-01

Many biomolecules have machine-like functions, and accordingly are discussed in terms of mechanical properties like force and motion. However, the concept of stress, a mechanical property that is of fundamental importance in the study of macroscopic mechanics, is not commonly applied in the biomolecular context. We anticipate that microscopical stress analyses of biomolecules and nanomaterials will provide useful mechanistic insights and help guide molecular design. To enable such applications, we have developed Calculator of Atomistic Mechanical Stress (CAMS), an open-source software package for computing atomic resolution stresses from molecular dynamics (MD) simulations. The software also enables decomposition of stress into contributions from bonded, nonbonded and Generalized Born potential terms. CAMS reads GROMACS topology and trajectory files, which are easily generated from AMBER files as well; and time-varying stresses may be animated and visualized in the VMD viewer. Here, we review relevant theory and present illustrative applications. PMID:25503996

Markov state models and molecular alchemy

NASA Astrophysics Data System (ADS)

Schütte, Christof; Nielsen, Adam; Weber, Marcus

2015-01-01

In recent years, Markov state models (MSMs) have attracted a considerable amount of attention with regard to modelling conformation changes and associated function of biomolecular systems. They have been used successfully, e.g. for peptides including time-resolved spectroscopic experiments, protein function and protein folding , DNA and RNA, and ligand-receptor interaction in drug design and more complicated multivalent scenarios. In this article, a novel reweighting scheme is introduced that allows to construct an MSM for certain molecular system out of an MSM for a similar system. This permits studying how molecular properties on long timescales differ between similar molecular systems without performing full molecular dynamics simulations for each system under consideration. The performance of the reweighting scheme is illustrated for simple test cases, including one where the main wells of the respective energy landscapes are located differently and an alchemical transformation of butane to pentane where the dimension of the state space is changed.

All-atom calculation of protein free-energy profiles

NASA Astrophysics Data System (ADS)

Orioli, S.; Ianeselli, A.; Spagnolli, G.; Faccioli, P.

2017-10-01

The Bias Functional (BF) approach is a variational method which enables one to efficiently generate ensembles of reactive trajectories for complex biomolecular transitions, using ordinary computer clusters. For example, this scheme was applied to simulate in atomistic detail the folding of proteins consisting of several hundreds of amino acids and with experimental folding time of several minutes. A drawback of the BF approach is that it produces trajectories which do not satisfy microscopic reversibility. Consequently, this method cannot be used to directly compute equilibrium observables, such as free energy landscapes or equilibrium constants. In this work, we develop a statistical analysis which permits us to compute the potential of mean-force (PMF) along an arbitrary collective coordinate, by exploiting the information contained in the reactive trajectories calculated with the BF approach. We assess the accuracy and computational efficiency of this scheme by comparing its results with the PMF obtained for a small protein by means of plain molecular dynamics.

Electron and positron interaction with pyrimidine: A theoretical investigation

NASA Astrophysics Data System (ADS)

Sinha, Nidhi; Antony, Bobby

2018-03-01

Pyrimidine (C4H4N2) is considered as the building block of nucleobases, viz., cytosine, thymine and uracil. They provide a blueprint for probing the scattering of radiation by DNA and RNA bases. In this article, we report the elastic and total scattering cross-sections for electron and positron scattering from the pyrimidine molecule, employing a spherical complex optical potential (SCOP) formalism for an extensive energy range of 10 eV to 5 keV. In the case of positron scattering, the original SCOP formalism is modified to adequately solve the positron-target dynamics. Moreover, a reasonable agreement is observed between the present results and other available datasets, for both electron and positron scattering. The cross-sections for electron and positron impact scattering by pyrimidine are necessary input data for codes that seek to simulate radiation damage, and hence are useful to model biomolecular systems.

Ndarts

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.

PB-AM: An open-source, fully analytical linear poisson-boltzmann solver.

PubMed

Felberg, Lisa E; Brookes, David H; Yap, Eng-Hui; Jurrus, Elizabeth; Baker, Nathan A; Head-Gordon, Teresa

2017-06-05

We present the open source distributed software package Poisson-Boltzmann Analytical Method (PB-AM), a fully analytical solution to the linearized PB equation, for molecules represented as non-overlapping spherical cavities. The PB-AM software package includes the generation of outputs files appropriate for visualization using visual molecular dynamics, a Brownian dynamics scheme that uses periodic boundary conditions to simulate dynamics, the ability to specify docking criteria, and offers two different kinetics schemes to evaluate biomolecular association rate constants. Given that PB-AM defines mutual polarization completely and accurately, it can be refactored as a many-body expansion to explore 2- and 3-body polarization. Additionally, the software has been integrated into the Adaptive Poisson-Boltzmann Solver (APBS) software package to make it more accessible to a larger group of scientists, educators, and students that are more familiar with the APBS framework. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Calculation and visualization of atomistic mechanical stresses in nanomaterials and biomolecules.

PubMed

Fenley, Andrew T; Muddana, Hari S; Gilson, Michael K

2014-01-01

Many biomolecules have machine-like functions, and accordingly are discussed in terms of mechanical properties like force and motion. However, the concept of stress, a mechanical property that is of fundamental importance in the study of macroscopic mechanics, is not commonly applied in the biomolecular context. We anticipate that microscopical stress analyses of biomolecules and nanomaterials will provide useful mechanistic insights and help guide molecular design. To enable such applications, we have developed Calculator of Atomistic Mechanical Stress (CAMS), an open-source software package for computing atomic resolution stresses from molecular dynamics (MD) simulations. The software also enables decomposition of stress into contributions from bonded, nonbonded and Generalized Born potential terms. CAMS reads GROMACS topology and trajectory files, which are easily generated from AMBER files as well; and time-varying stresses may be animated and visualized in the VMD viewer. Here, we review relevant theory and present illustrative applications.

Biomolecular structure manipulation using tailored electromagnetic radiation: a proof of concept on a simplified model of the active site of bacterial DNA topoisomerase.

PubMed

Jarukanont, Daungruthai; Coimbra, João T S; Bauerhenne, Bernd; Fernandes, Pedro A; Patel, Shekhar; Ramos, Maria J; Garcia, Martin E

2014-10-21

We report on the viability of breaking selected bonds in biological systems using tailored electromagnetic radiation. We first demonstrate, by performing large-scale simulations, that pulsed electric fields cannot produce selective bond breaking. Then, we present a theoretical framework for describing selective energy concentration on particular bonds of biomolecules upon application of tailored electromagnetic radiation. The theory is based on the mapping of biomolecules to a set of coupled harmonic oscillators and on optimal control schemes to describe optimization of temporal shape, the phase and polarization of the external radiation. We have applied this theory to demonstrate the possibility of selective bond breaking in the active site of bacterial DNA topoisomerase. For this purpose, we have focused on a model that was built based on a case study. Results are given as a proof of concept.

Infrared spectral marker bands characterizing a transient water wire inside a hydrophobic membrane protein.

PubMed

Wolf, Steffen; Freier, Erik; Cui, Qiang; Gerwert, Klaus

2014-12-14

Proton conduction along protein-bound "water wires" is an essential feature in membrane proteins. Here, we analyze in detail a transient water wire, which conducts protons via a hydrophobic barrier within a membrane protein to create a proton gradient. It is formed only for a millisecond out of three water molecules distributed at inactive positions in a polar environment in the ground state. The movement into a hydrophobic environment causes characteristic shifts of the water bands reflecting their different chemical properties. These band shifts are identified by time-resolved Fourier Transform Infrared difference spectroscopy and analyzed by biomolecular Quantum Mechanical/Molecular Mechanical simulations. A non-hydrogen bonded ("dangling") O-H stretching vibration band and a broad continuum absorbance caused by a combined vibration along the water wire are identified as characteristic marker bands of such water wires in a hydrophobic environment. The results provide a basic understanding of water wires in hydrophobic environments.

Engineering the entropy-driven free-energy landscape of a dynamic nanoporous protein assembly.

PubMed

Alberstein, Robert; Suzuki, Yuta; Paesani, Francesco; Tezcan, F Akif

2018-04-30

De novo design and construction of stimuli-responsive protein assemblies that predictably switch between discrete conformational states remains an essential but highly challenging goal in biomolecular design. We previously reported synthetic, two-dimensional protein lattices self-assembled via disulfide bonding interactions, which endows them with a unique capacity to undergo coherent conformational changes without losing crystalline order. Here, we carried out all-atom molecular dynamics simulations to map the free-energy landscape of these lattices, validated this landscape through extensive structural characterization by electron microscopy and established that it is predominantly governed by solvent reorganization entropy. Subsequent redesign of the protein surface with conditionally repulsive electrostatic interactions enabled us to predictably perturb the free-energy landscape and obtain a new protein lattice whose conformational dynamics can be chemically and mechanically toggled between three different states with varying porosities and molecular densities.

Coarse-graining of proteins based on elastic network models

NASA Astrophysics Data System (ADS)

Sinitskiy, Anton V.; Voth, Gregory A.

2013-08-01

To simulate molecular processes on biologically relevant length- and timescales, coarse-grained (CG) models of biomolecular systems with tens to even hundreds of residues per CG site are required. One possible way to build such models is explored in this article: an elastic network model (ENM) is employed to define the CG variables. Free energy surfaces are approximated by Taylor series, with the coefficients found by force-matching. CG potentials are shown to undergo renormalization due to roughness of the energy landscape and smoothing of it under coarse-graining. In the case study of hen egg-white lysozyme, the entropy factor is shown to be of critical importance for maintaining the native structure, and a relationship between the proposed ENM-mode-based CG models and traditional CG-bead-based models is discussed. The proposed approach uncovers the renormalizable character of CG models and offers new opportunities for automated and computationally efficient studies of complex free energy surfaces.

Bioassays Based on Molecular Nanomechanics

DOE PAGES

Majumdar, Arun

2002-01-01

Recent experiments have shown that when specific biomolecular interactions are confined to one surface of a microcantilever beam, changes in intermolecular nanomechanical forces provide sufficient differential torque to bend the cantilever beam. This has been used to detect single base pair mismatches during DNA hybridization, as well as prostate specific antigen (PSA) at concentrations and conditions that are clinically relevant for prostate cancer diagnosis. Since cantilever motion originates from free energy change induced by specific biomolecular binding, this technique is now offering a common platform for label-free quantitative analysis of protein-protein binding, DNA hybridization DNA-protein interactions, and in general receptor-ligandmore » interactions. Current work is focused on developing “universal microarrays” of microcantilever beams for high-throughput multiplexed bioassays.« less

Chiral symmetry breaking during the self-assembly of monolayers from achiral purine molecules.

PubMed

Sowerby, S J; Heckl, W M; Petersen, G B

1996-11-01

Scanning tunneling microscopy was used to investigate the structure of the two-dimensional adsorbate formed by molecular self-assembly of the purine base, adenine, on the surfaces of the naturally occurring mineral molybdenite and the synthetic crystal highly oriented pyrolytic graphite. Although formed from adenine, which is achiral, the observed adsorbate surface structures were enantiomorphic on molybdenite. This phenomenon suggests a mechanism for the introduction of a localized chiral symmetry break by the spontaneous crystallization of these prebiotically available molecules on inorganic surfaces and may have some role in the origin of biomolecular optical asymmetry. The possibility that purine-pyrimidine arrays assembled on naturally occurring mineral surfaces might act as possible templates for biomolecular assembly is discussed.

Biomolecular computing systems: principles, progress and potential.

PubMed

Benenson, Yaakov

2012-06-12

The task of information processing, or computation, can be performed by natural and man-made 'devices'. Man-made computers are made from silicon chips, whereas natural 'computers', such as the brain, use cells and molecules. Computation also occurs on a much smaller scale in regulatory and signalling pathways in individual cells and even within single biomolecules. Indeed, much of what we recognize as life results from the remarkable capacity of biological building blocks to compute in highly sophisticated ways. Rational design and engineering of biological computing systems can greatly enhance our ability to study and to control biological systems. Potential applications include tissue engineering and regeneration and medical treatments. This Review introduces key concepts and discusses recent progress that has been made in biomolecular computing.

Review of MEMS differential scanning calorimetry for biomolecular study

NASA Astrophysics Data System (ADS)

Yu, Shifeng; Wang, Shuyu; Lu, Ming; Zuo, Lei

2017-12-01

Differential scanning calorimetry (DSC) is one of the few techniques that allow direct determination of enthalpy values for binding reactions and conformational transitions in biomolecules. It provides the thermodynamics information of the biomolecules which consists of Gibbs free energy, enthalpy and entropy in a straightforward manner that enables deep understanding of the structure function relationship in biomolecules such as the folding/unfolding of protein and DNA, and ligand bindings. This review provides an up to date overview of the applications of DSC in biomolecular study such as the bovine serum albumin denaturation study, the relationship between the melting point of lysozyme and the scanning rate. We also introduce the recent advances of the development of micro-electro-mechanic-system (MEMS) based DSCs.

Entropy–enthalpy transduction caused by conformational shifts can obscure the forces driving protein–ligand binding

PubMed Central

Fenley, Andrew T.; Muddana, Hari S.; Gilson, Michael K.

2012-01-01

Molecular dynamics simulations of unprecedented duration now can provide new insights into biomolecular mechanisms. Analysis of a 1-ms molecular dynamics simulation of the small protein bovine pancreatic trypsin inhibitor reveals that its main conformations have different thermodynamic profiles and that perturbation of a single geometric variable, such as a torsion angle or interresidue distance, can select for occupancy of one or another conformational state. These results establish the basis for a mechanism that we term entropy–enthalpy transduction (EET), in which the thermodynamic character of a local perturbation, such as enthalpic binding of a small molecule, is camouflaged by the thermodynamics of a global conformational change induced by the perturbation, such as a switch into a high-entropy conformational state. It is noted that EET could occur in many systems, making measured entropies and enthalpies of folding and binding unreliable indicators of actual thermodynamic driving forces. The same mechanism might also account for the high experimental variance of measured enthalpies and entropies relative to free energies in some calorimetric studies. Finally, EET may be the physical mechanism underlying many cases of entropy–enthalpy compensation. PMID:23150595

Computational screening of biomolecular adsorption and self-assembly on nanoscale surfaces.

PubMed

Heinz, Hendrik

2010-05-01

The quantification of binding properties of ions, surfactants, biopolymers, and other macromolecules to nanometer-scale surfaces is often difficult experimentally and a recurring challenge in molecular simulation. A simple and computationally efficient method is introduced to compute quantitatively the energy of adsorption of solute molecules on a given surface. Highly accurate summation of Coulomb energies as well as precise control of temperature and pressure is required to extract the small energy differences in complex environments characterized by a large total energy. The method involves the simulation of four systems, the surface-solute-solvent system, the solute-solvent system, the solvent system, and the surface-solvent system under consideration of equal molecular volumes of each component under NVT conditions using standard molecular dynamics or Monte Carlo algorithms. Particularly in chemically detailed systems including thousands of explicit solvent molecules and specific concentrations of ions and organic solutes, the method takes into account the effect of complex nonbond interactions and rotational isomeric states on the adsorption behavior on surfaces. As a numerical example, the adsorption of a dodecapeptide on the Au {111} and mica {001} surfaces is described in aqueous solution. Copyright 2009 Wiley Periodicals, Inc.

The effect of copolymers on the interfaces in incompatible homopolymers blend: Molecular dynamics study

NASA Astrophysics Data System (ADS)

Ryu, Jiho; Lee, Won Bo

2015-03-01

Using molecular dynamics simulations the effect of copolymers as compatibilizer for reducing interfacial tension and enhancement of interfacial adhesion at the interface of thermodynamic unfavorable homopolymers blend is studied with block- and graft-copolymers. We have calculated local pressure tensor of system along the axis perpendicular to interface, varying bending potential energy of one part, which consist of just one kind of beads, of copolymer chain to examine the effect of stiffness of surfactin molecules. Here we consider symmetric diblock copolymer (f =1/2) having 1/2 N make of beads of type A and the other part made of beads of type B, and graft copolymer having backbone linear chain consist of 1/2 N beads of type of A and branched with two side-chain consist of 1/4 N beads of type B. All simulations were performed under the constant NPT ensemble at T* =1, ρ* ~0.85. Also we studied changes of effect of copolymers with increasing pairwise repulsive interaction potential between two beads of types A and B while homopolymers chain length are fixed, N =30. Chemical and Biomolecular Engineering, Sogang University, Seoul, South Korea.

High-resolution AFM structure of DNA G-wires in aqueous solution.

PubMed

Bose, Krishnashish; Lech, Christopher J; Heddi, Brahim; Phan, Anh Tuân

2018-05-17

We investigate the self-assembly of short pieces of the Tetrahymena telomeric DNA sequence d[G 4 T 2 G 4 ] in physiologically relevant aqueous solution using atomic force microscopy (AFM). Wire-like structures (G-wires) of 3.0 nm height with well-defined surface periodic features were observed. Analysis of high-resolution AFM images allowed their classification based on the periodicity of these features. A major species is identified with periodic features of 4.3 nm displaying left-handed ridges or zigzag features on the molecular surface. A minor species shows primarily left-handed periodic features of 2.2 nm. In addition to 4.3 and 2.2 nm ridges, background features with periodicity of 0.9 nm are also observed. Using molecular modeling and simulation, we identify a molecular structure that can explain both the periodicity and handedness of the major G-wire species. Our results demonstrate the potential structural diversity of G-wire formation and provide valuable insight into the structure of higher-order intermolecular G-quadruplexes. Our results also demonstrate how AFM can be combined with simulation to gain insight into biomolecular structure.

The allosteric communication pathways in KIX domain of CBP.

PubMed

Palazzesi, Ferruccio; Barducci, Alessandro; Tollinger, Martin; Parrinello, Michele

2013-08-27

Allosteric regulation plays an important role in a myriad of biomacromolecular processes. Specifically, in a protein, the process of allostery refers to the transmission of a local perturbation, such as ligand binding, to a distant site. Decades after the discovery of this phenomenon, models built on static images of proteins are being reconsidered with the knowledge that protein dynamics plays an important role in its function. Molecular dynamics simulations are a valuable tool for studying complex biomolecular systems, providing an atomistic description of their structure and dynamics. Unfortunately, their predictive power has been limited by the complexity of the biomolecule free-energy surface and by the length of the allosteric timescale (in the order of milliseconds). In this work, we are able to probe the origins of the allosteric changes that transcription factor mixed lineage leukemia (MLL) causes to the interactions of KIX domain of CREB-binding protein (CBP) with phosphorylated kinase inducible domain (pKID), by combing all-atom molecular dynamics with enhanced sampling methods recently developed in our group. We discuss our results in relation to previous NMR studies. We also develop a general simulations protocol to study allosteric phenomena and many other biological processes that occur in the micro/milliseconds timescale.

Reproducing kernel potential energy surfaces in biomolecular simulations: Nitric oxide binding to myoglobin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Soloviov, Maksym; Meuwly, Markus, E-mail: m.meuwly@unibas.ch

2015-09-14

Multidimensional potential energy surfaces based on reproducing kernel-interpolation are employed to explore the energetics and dynamics of free and bound nitric oxide in myoglobin (Mb). Combining a force field description for the majority of degrees of freedom and the higher-accuracy representation for the NO ligand and the Fe out-of-plane motion allows for a simulation approach akin to a mixed quantum mechanics/molecular mechanics treatment. However, the kernel-representation can be evaluated at conventional force-field speed. With the explicit inclusion of the Fe-out-of-plane (Fe-oop) coordinate, the dynamics and structural equilibrium after photodissociation of the ligand are correctly described compared to experiment. Experimentally, themore » Fe-oop coordinate plays an important role for the ligand dynamics. This is also found here where the isomerization dynamics between the Fe–ON and Fe–NO state is significantly affected whether or not this co-ordinate is explicitly included. Although the Fe–ON conformation is metastable when considering only the bound {sup 2}A state, it may disappear once the {sup 4}A state is included. This explains the absence of the Fe–ON state in previous experimental investigations of MbNO.« less