COSTBI-1228; NO. OF PAGES 2
Available online at www.sciencedirect.com
ScienceDirect Editorial overview: Theory and simulation: Tools for solving the insolvable Rommie E Amaro and Manju Bansal Current Opinion in Structural Biology 2014, 25:xx–yy
http://dx.doi.org/10.1016/j.sbi.2014.04.004 0959-440X/# 2014 Elsevier Ltd. All rights reserved.
Rommie E Amaro Chemistry, University of California at San Diego, USA e-mail: [email protected] Rommie E. Amaro is faculty in the Department of Chemistry and Biochemistry at the University of California, San Diego (UCSD). She received her B.S. (Chemical Engineering, 1999) and Ph.D. (Chemistry, 2005) from the University of Illinois at Urbana-Champaign. She was a NIH postdoctoral fellow with McCammon (UCSD). She is the recipient of an NIH New Innovator Award, the Presidential Early Career Award for Scientists and Engineers, and the ACS COMP Outstanding Junior Faculty Award. Research in her lab is broadly concerned with the development and application of state-of-the-art computational and theoretical techniques to investigate the structure, function, and dynamics of complex biological systems. The lab focuses mainly on targeting neglected diseases, Chlamydia, influenza, and cancer, and works closely with experimental collaborators to catalyze the discovery of new potential therapeutic agents. The Amaro Lab is also keenly interested in developing new multiscale simulation methods and novel modeling paradigms that scale from the level of atoms to whole cells, and beyond.
Manju Bansal Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560012, India e-mail: [email protected] Manju Bansal is a professor at Molecular Biophysics Unit, of Indian Institute of Science, Bangalore. Her group has been developing new computational tools and using them for analysis and prediction of biologically relevant features in proteins and nucleic acids. In particular her work focuses on analysis of helical structures in proteins, modeling and simulations of sequence dependent duplex, triplex and G-quadruplex structures of nucleic acids and identification of structural properties of regulatory regions in non-coding DNA, at whole genome level.
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The 2013 Nobel prize in chemistry has been awarded to Martin Karplus, Michael Levitt and Arieh Warshel for their contribution to development of multiscale models of complex chemical systems. The citation also mentions that the work being awarded focuses on methods which use both chemical and quantum mechanical theory and are used to model complex chemical systems and reactions. The same ‘multiscale modelling’ methods are increasingly being used to simulate large biological systems, by combining quantum chemical modelling of the core region of interest (such as an enzyme active site or ligand binding pocket) with classical (molecular mechanics) modelling of the surrounding molecular environment. This issue of COSTBI contains articles outlining the progress made in recent years in simulation of complex biological systems at atomic as well as coarse grain level, and state-of-the-art simulations that bridge the molecular and subcellular scales(?). In silico modelling and energy calculations also play an important role in analysis of X-ray diffraction, NMR and electron microscopy data, to arrive at detailed biological structures. New algorithms for prediction of protein function from binding site comparison and identification of promoter regions in genomic DNA from their structural properties, are also reviewed. All these developments provide new insights into biological processes by bridging theory and experiment. To quote again from the Nobel write-up, ‘‘fruitful cooperation between theory and experiment has made many otherwise unsolvable problems solvable’’. A commonly used type of theoretical simulation is molecular dynamics which, with scalable computer codes and high-speed parallel computers, can now be carried out for milliseconds for smaller systems, while systems with millions of atoms are being simulated for hundreds of nanoseconds. However in the context of time scale of biological phenomenon, these still represent only a snapshot of the real system. This has led to rapid development in methods for coarse graining (wherein groups of atoms/ molecules are treated as single quasi particles) as well as multiscale modelling and simulations. This approach requires a clear understanding of the scale at which the ‘coarse graining’ is to be performed and how to couple an atomic scale dimension to one or more mesoscale dimension, which in turn could be coupled to a near-continuum scale. Theoretical frameworks for modelling at different scales and interfacing between these various scales is outlined in the article by Zhou, along with some illustrative examples. One of the important constraints in simulations of dynamics of biological molecules is to replicate the in vivo conditions, particularly the solvent environment. While current computational power allows an atomistic Current Opinion in Structural Biology 2014, 25:1–2
Please cite this article in press as: Amaro RE, Bansal M: Editorial overview: Theory and simulation: Tools for solving the insolvable, Curr Opin Struct Biol (2014), http://dx.doi.org/10.1016/ j.sbi.2014.04.004
COSTBI-1228; NO. OF PAGES 2
2 Macromolecular Machines
representation of solvent to be considered, implicit solvent models still prove very efficient in model refinement of large systems and in multiscale simulations. Kleinjung and Fraternali describe the physical basis of different types of implicit solvent models, their accuracy and computational load, implicit solvent parameterization based on explicit solvation force matching approaches. The application of implicit solvent models to molecular dynamics and replica exchange sampling, Monte-Carlo sampling, protein structure modelling, folding and free energy calculations, as well as nucleic acid and membrane modelling are discussed. A major challenge to structural biology is understanding how DNA not only encodes genomic information, but how it regulates such information through diverse sequence and structural mechanisms. Unraveling such intricate mechanisms around the promoter regions, located upstream of transcription start sites, will inform scientists how gene expression is ultimately carried out. Bansal et al. review emerging new methods for locating and analyzing transcription start sites and promoter sequences, focusing on sequence motif based methods, methods that focus on exploiting the unique structural features of promoter regions across diverse organisms, and signals encoded within B-DNA microstructures. Large macromolecular complexes are not amenable to X-ray diffraction analysis and are routinely being studied using cryo-electron microscopy (EM), which provides structural information at subnanometer and near atomic (3–20 A˚) resolution. Various techniques are used in fitting atomic level models of the various components of a large biomolecular assembly into a low-resolution cryoEM map. Villa and Lasker review rigid, flexible and de novo integrative fitting methods into EM maps. In this rapidly evolving field, model refinement is still influenced by problems of over fitting and noise, with the refined model being affected by quality of input data, sampling algorithms used and scoring function used. Hence map and model validation plays a significant role in arriving at reliable structures and current efforts towards arriving at unified criteria for these are discussed. Allosteric signalling plays a major role in a variety of biological processes. Identification of atomistic level allosteric pathway is expected to be particularly useful in drug discovery. Advances in computational methods for mapping allosteric pathways mediated by intra or inter molecular residue networks are reviewed by Feher et al. Strengths and limitations of different computational approaches are summarized and information about web-servers and freely available programs is provided. A large number of proteins whose structures are available in the Protein Data Bank do not have a function assigned
Current Opinion in Structural Biology 2014, 25:1–2
to them and the number of such proteins of ‘unknown function’ is continuously growing. As binding sites are expected to be evolutionarily more conserved than other parts of the protein, binding site comparison can be used to identify functional relationships between evolutionarily distant proteins. Konc and Janezic review recent advances in algorithms and web-based tools developed for binding site comparison and their application to detecting sites in related proteins and their function. Particularly interesting are the new methods for dealing with distant similarities when protein dynamics may lead to alteration in the binding site structures. Several new tools for addressing this problem, as well as possible applications, are discussed. A major scientific challenge relates to how we create unified models of system behavior using information derived from multiple scales of biological organization. How we build up our understanding from molecular level detail, through cellular systems, up to whole-organ and whole-systems models is a major challenge that when addressed, should allow us to develop more informative and predictive models of emergent behavior. Roberts reviews recent advances in the use of molecular and cellular structure to model the behavior of cells. New and notable advances in techniques that will allow either a hierarchical or simultaneous multiscale approach are discussed. In a related review, Hake et al. present recent advancements in microscopy and subcellular modelling that are now enabling accurate dynamical mesoscale models of calcium release units. Here, high-resolution images from microscopy are being used in conjunction with new meshing and geometric modelling techniques to generate spatially accurate models at micron length scales. The integration of discrete atomic and continuum dynamical models is also discussed. Despite the huge advances in computing power, a key challenge in molecular biophysics is how we can simulate and understand longer timescales using molecular dynamics simulations. The combination of Markov state modelling with statistical simulations is one approach that has seen rapid development in recent years. The review by Chodera and Noe´ covers the newest advances, with emphasis on new theories, software tools, and applications. These reviews collectively describe the current state-ofthe-art in theoretical and computational modelling techniques, with a thoughtful eye towards where each field is headed. Continuing improvement in the theory, algorithms, computational approaches for biological modelling, coupled with radical advances in experimental approaches – and the full integration of all these components together – promises to deliver new understandings and insights never before achieved.
www.sciencedirect.com
Please cite this article in press as: Amaro RE, Bansal M: Editorial overview: Theory and simulation: Tools for solving the insolvable, Curr Opin Struct Biol (2014), http://dx.doi.org/10.1016/ j.sbi.2014.04.004
Available online at www.sciencedirect.com
ScienceDirect Editorial overview: Theory and simulation: Tools for solving the insolvable Rommie E Amaro and Manju Bansal Current Opinion in Structural Biology 2014, 25:xx–yy
http://dx.doi.org/10.1016/j.sbi.2014.04.004 0959-440X/# 2014 Elsevier Ltd. All rights reserved.
Rommie E Amaro Chemistry, University of California at San Diego, USA e-mail: [email protected] Rommie E. Amaro is faculty in the Department of Chemistry and Biochemistry at the University of California, San Diego (UCSD). She received her B.S. (Chemical Engineering, 1999) and Ph.D. (Chemistry, 2005) from the University of Illinois at Urbana-Champaign. She was a NIH postdoctoral fellow with McCammon (UCSD). She is the recipient of an NIH New Innovator Award, the Presidential Early Career Award for Scientists and Engineers, and the ACS COMP Outstanding Junior Faculty Award. Research in her lab is broadly concerned with the development and application of state-of-the-art computational and theoretical techniques to investigate the structure, function, and dynamics of complex biological systems. The lab focuses mainly on targeting neglected diseases, Chlamydia, influenza, and cancer, and works closely with experimental collaborators to catalyze the discovery of new potential therapeutic agents. The Amaro Lab is also keenly interested in developing new multiscale simulation methods and novel modeling paradigms that scale from the level of atoms to whole cells, and beyond.
Manju Bansal Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560012, India e-mail: [email protected] Manju Bansal is a professor at Molecular Biophysics Unit, of Indian Institute of Science, Bangalore. Her group has been developing new computational tools and using them for analysis and prediction of biologically relevant features in proteins and nucleic acids. In particular her work focuses on analysis of helical structures in proteins, modeling and simulations of sequence dependent duplex, triplex and G-quadruplex structures of nucleic acids and identification of structural properties of regulatory regions in non-coding DNA, at whole genome level.
www.sciencedirect.com
The 2013 Nobel prize in chemistry has been awarded to Martin Karplus, Michael Levitt and Arieh Warshel for their contribution to development of multiscale models of complex chemical systems. The citation also mentions that the work being awarded focuses on methods which use both chemical and quantum mechanical theory and are used to model complex chemical systems and reactions. The same ‘multiscale modelling’ methods are increasingly being used to simulate large biological systems, by combining quantum chemical modelling of the core region of interest (such as an enzyme active site or ligand binding pocket) with classical (molecular mechanics) modelling of the surrounding molecular environment. This issue of COSTBI contains articles outlining the progress made in recent years in simulation of complex biological systems at atomic as well as coarse grain level, and state-of-the-art simulations that bridge the molecular and subcellular scales(?). In silico modelling and energy calculations also play an important role in analysis of X-ray diffraction, NMR and electron microscopy data, to arrive at detailed biological structures. New algorithms for prediction of protein function from binding site comparison and identification of promoter regions in genomic DNA from their structural properties, are also reviewed. All these developments provide new insights into biological processes by bridging theory and experiment. To quote again from the Nobel write-up, ‘‘fruitful cooperation between theory and experiment has made many otherwise unsolvable problems solvable’’. A commonly used type of theoretical simulation is molecular dynamics which, with scalable computer codes and high-speed parallel computers, can now be carried out for milliseconds for smaller systems, while systems with millions of atoms are being simulated for hundreds of nanoseconds. However in the context of time scale of biological phenomenon, these still represent only a snapshot of the real system. This has led to rapid development in methods for coarse graining (wherein groups of atoms/ molecules are treated as single quasi particles) as well as multiscale modelling and simulations. This approach requires a clear understanding of the scale at which the ‘coarse graining’ is to be performed and how to couple an atomic scale dimension to one or more mesoscale dimension, which in turn could be coupled to a near-continuum scale. Theoretical frameworks for modelling at different scales and interfacing between these various scales is outlined in the article by Zhou, along with some illustrative examples. One of the important constraints in simulations of dynamics of biological molecules is to replicate the in vivo conditions, particularly the solvent environment. While current computational power allows an atomistic Current Opinion in Structural Biology 2014, 25:1–2
Please cite this article in press as: Amaro RE, Bansal M: Editorial overview: Theory and simulation: Tools for solving the insolvable, Curr Opin Struct Biol (2014), http://dx.doi.org/10.1016/ j.sbi.2014.04.004
COSTBI-1228; NO. OF PAGES 2
2 Macromolecular Machines
representation of solvent to be considered, implicit solvent models still prove very efficient in model refinement of large systems and in multiscale simulations. Kleinjung and Fraternali describe the physical basis of different types of implicit solvent models, their accuracy and computational load, implicit solvent parameterization based on explicit solvation force matching approaches. The application of implicit solvent models to molecular dynamics and replica exchange sampling, Monte-Carlo sampling, protein structure modelling, folding and free energy calculations, as well as nucleic acid and membrane modelling are discussed. A major challenge to structural biology is understanding how DNA not only encodes genomic information, but how it regulates such information through diverse sequence and structural mechanisms. Unraveling such intricate mechanisms around the promoter regions, located upstream of transcription start sites, will inform scientists how gene expression is ultimately carried out. Bansal et al. review emerging new methods for locating and analyzing transcription start sites and promoter sequences, focusing on sequence motif based methods, methods that focus on exploiting the unique structural features of promoter regions across diverse organisms, and signals encoded within B-DNA microstructures. Large macromolecular complexes are not amenable to X-ray diffraction analysis and are routinely being studied using cryo-electron microscopy (EM), which provides structural information at subnanometer and near atomic (3–20 A˚) resolution. Various techniques are used in fitting atomic level models of the various components of a large biomolecular assembly into a low-resolution cryoEM map. Villa and Lasker review rigid, flexible and de novo integrative fitting methods into EM maps. In this rapidly evolving field, model refinement is still influenced by problems of over fitting and noise, with the refined model being affected by quality of input data, sampling algorithms used and scoring function used. Hence map and model validation plays a significant role in arriving at reliable structures and current efforts towards arriving at unified criteria for these are discussed. Allosteric signalling plays a major role in a variety of biological processes. Identification of atomistic level allosteric pathway is expected to be particularly useful in drug discovery. Advances in computational methods for mapping allosteric pathways mediated by intra or inter molecular residue networks are reviewed by Feher et al. Strengths and limitations of different computational approaches are summarized and information about web-servers and freely available programs is provided. A large number of proteins whose structures are available in the Protein Data Bank do not have a function assigned
Current Opinion in Structural Biology 2014, 25:1–2
to them and the number of such proteins of ‘unknown function’ is continuously growing. As binding sites are expected to be evolutionarily more conserved than other parts of the protein, binding site comparison can be used to identify functional relationships between evolutionarily distant proteins. Konc and Janezic review recent advances in algorithms and web-based tools developed for binding site comparison and their application to detecting sites in related proteins and their function. Particularly interesting are the new methods for dealing with distant similarities when protein dynamics may lead to alteration in the binding site structures. Several new tools for addressing this problem, as well as possible applications, are discussed. A major scientific challenge relates to how we create unified models of system behavior using information derived from multiple scales of biological organization. How we build up our understanding from molecular level detail, through cellular systems, up to whole-organ and whole-systems models is a major challenge that when addressed, should allow us to develop more informative and predictive models of emergent behavior. Roberts reviews recent advances in the use of molecular and cellular structure to model the behavior of cells. New and notable advances in techniques that will allow either a hierarchical or simultaneous multiscale approach are discussed. In a related review, Hake et al. present recent advancements in microscopy and subcellular modelling that are now enabling accurate dynamical mesoscale models of calcium release units. Here, high-resolution images from microscopy are being used in conjunction with new meshing and geometric modelling techniques to generate spatially accurate models at micron length scales. The integration of discrete atomic and continuum dynamical models is also discussed. Despite the huge advances in computing power, a key challenge in molecular biophysics is how we can simulate and understand longer timescales using molecular dynamics simulations. The combination of Markov state modelling with statistical simulations is one approach that has seen rapid development in recent years. The review by Chodera and Noe´ covers the newest advances, with emphasis on new theories, software tools, and applications. These reviews collectively describe the current state-ofthe-art in theoretical and computational modelling techniques, with a thoughtful eye towards where each field is headed. Continuing improvement in the theory, algorithms, computational approaches for biological modelling, coupled with radical advances in experimental approaches – and the full integration of all these components together – promises to deliver new understandings and insights never before achieved.
www.sciencedirect.com
Please cite this article in press as: Amaro RE, Bansal M: Editorial overview: Theory and simulation: Tools for solving the insolvable, Curr Opin Struct Biol (2014), http://dx.doi.org/10.1016/ j.sbi.2014.04.004
