Climate change effects on bread wheat phenology and grain quality: A case study in the north of Italy.

Increasing temperatures, heat waves, and reduction of annual precipitation are all the expressions of climate change (CC), strongly affecting bread wheat ( L.) grain yield in Southern Europe. Being temperature the major driving force of plants' phenological development, these variations also have effects on wheat phenology, with possible consequences on grain quality, and gluten protein accumulation.

Development of Force Field Parameters for the Simulation of Single- and Double-Stranded DNA Molecules and DNA-Protein Complexes.

Although molecular dynamics (MD) simulations have been used extensively to study the structural dynamics of proteins, the role of MD simulation in studies of nucleic acid based systems has been more limited. One contributing factor to this disparity is the historically lower level of accuracy of the physical models used in such simulations to describe interactions involving nucleic acids. By modifying nonbonded and torsion parameters of a force field from the Amber family of models, we recently developed force field parameters for RNA that achieve a level of accuracy comparable to that of state-of-the-art protein force fields.

Mechanism of Coupled Folding-upon-Binding of an Intrinsically Disordered Protein.

Intrinsically disordered proteins (IDPs), which in isolation do not adopt a well-defined tertiary structure but instead populate a structurally heterogeneous ensemble of interconverting states, play important roles in many biological pathways. IDPs often fold into ordered states upon binding to their physiological interaction partners (a so-called "folding-upon-binding" process), but it has proven difficult to obtain an atomic-level description of the structural mechanisms by which they do so. Here, we describe in atomic detail the folding-upon-binding mechanism of an IDP segment to its binding partner, as observed in unbiased molecular dynamics simulations.

Development of a Force Field for the Simulation of Single-Chain Proteins and Protein-Protein Complexes.

The accuracy of atomistic physics-based force fields for the simulation of biological macromolecules has typically been benchmarked experimentally using biophysical data from simple, often single-chain systems. In the case of proteins, the careful refinement of force field parameters associated with torsion-angle potentials and the use of improved water models have enabled a great deal of progress toward the highly accurate simulation of such monomeric systems in both folded and, more recently, disordered states. In living organisms, however, proteins constantly interact with other macromolecules, such as proteins and nucleic acids, and these interactions are often essential for proper biological function.

Atomic-Level Description of Protein Folding inside the GroEL Cavity.

Chaperonins (ubiquitous facilitators of protein folding) sequester misfolded proteins within an internal cavity, thus preventing protein aggregation during the process of refolding. GroEL, a tetradecameric bacterial chaperonin, is one of the most studied chaperonins, but the role of the internal cavity in the refolding process is still unclear. It has been suggested that rather than simply isolating proteins while they refold, the GroEL cavity actively promotes protein folding.

Developing a molecular dynamics force field for both folded and disordered protein states.

Molecular dynamics (MD) simulation is a valuable tool for characterizing the structural dynamics of folded proteins and should be similarly applicable to disordered proteins and proteins with both folded and disordered regions. It has been unclear, however, whether any physical model (force field) used in MD simulations accurately describes both folded and disordered proteins. Here, we select a benchmark set of 21 systems, including folded and disordered proteins, simulate these systems with six state-of-the-art force fields, and compare the results to over 9,000 available experimental data points.

RNA force field with accuracy comparable to state-of-the-art protein force fields.

Molecular dynamics (MD) simulation has become a powerful tool for characterizing at an atomic level of detail the conformational changes undergone by proteins. The application of such simulations to RNA structures, however, has proven more challenging, due in large part to the fact that the physical models ("force fields") available for MD simulations of RNA molecules are substantially less accurate in many respects than those currently available for proteins. Here, we introduce an extensive revision of a widely used RNA force field in which the parameters have been modified, based on quantum mechanical calculations and existing experimental information, to more accurately reflect the fundamental forces that stabilize RNA structures.

Picosecond to Millisecond Structural Dynamics in Human Ubiquitin.

Human ubiquitin has been extensively characterized using a variety of experimental and computational methods and has become an important model for studying protein dynamics. Nevertheless, it has proven difficult to characterize the microsecond time scale dynamics of this protein with atomistic resolution. Here we use an unbiased computer simulation to describe the structural dynamics of ubiquitin on the picosecond to millisecond time scale.

Demonstrating an Order-of-Magnitude Sampling Enhancement in Molecular Dynamics Simulations of Complex Protein Systems.

Molecular dynamics (MD) simulations can describe protein motions in atomic detail, but transitions between protein conformational states sometimes take place on time scales that are infeasible or very expensive to reach by direct simulation. Enhanced sampling methods, the aim of which is to increase the sampling efficiency of MD simulations, have thus been extensively employed. The effectiveness of such methods when applied to complex biological systems like proteins, however, has been difficult to establish because even enhanced sampling simulations of such systems do not typically reach time scales at which convergence is extensive enough to reliably quantify sampling efficiency.

An investigation of the 'female camouflage effect' in autism using a computerized ADOS-2 and a test of sex/gender differences.

Background: Autism spectrum conditions (autism) are diagnosed more frequently in boys than in girls. Females with autism may have been under-identified due to not only a male-biased understanding of autism but also females' camouflaging. The study describes a new technique that allows automated coding of non-verbal mode of communication (gestures) and offers the possibility of objective, evaluation of gestures, independent of human judgment.

Assessment of the utility of contact-based restraints in accelerating the prediction of protein structure using molecular dynamics simulations.

Molecular dynamics (MD) simulation is a well-established tool for the computational study of protein structure and dynamics, but its application to the important problem of protein structure prediction remains challenging, in part because extremely long timescales can be required to reach the native structure. Here, we examine the extent to which the use of low-resolution information in the form of residue-residue contacts, which can often be inferred from bioinformatics or experimental studies, can accelerate the determination of protein structure in simulation. We incorporated sets of 62, 31, or 15 contact-based restraints in MD simulations of ubiquitin, a benchmark system known to fold to the native state on the millisecond timescale in unrestrained simulations.

Identifying localized changes in large systems: Change-point detection for biomolecular simulations.

Research on change-point detection, the classical problem of detecting abrupt changes in sequential data, has focused predominantly on datasets with a single observable. A growing number of time series datasets, however, involve many observables, often with the property that a given change typically affects only a few of the observables. We introduce a general statistical method that, given many noisy observables, detects points in time at which various subsets of the observables exhibit simultaneous changes in data distribution and explicitly identifies those subsets.

Interaction Networks in Protein Folding via Atomic-Resolution Experiments and Long-Time-Scale Molecular Dynamics Simulations.

The integration of atomic-resolution experimental and computational methods offers the potential for elucidating key aspects of protein folding that are not revealed by either approach alone. Here, we combine equilibrium NMR measurements of thermal unfolding and long molecular dynamics simulations to investigate the folding of gpW, a protein with two-state-like, fast folding dynamics and cooperative equilibrium unfolding behavior. Experiments and simulations expose a remarkably complex pattern of structural changes that occur at the atomic level and from which the detailed network of residue-residue couplings associated with cooperative folding emerges.

Water dispersion interactions strongly influence simulated structural properties of disordered protein states.

Many proteins can be partially or completely disordered under physiological conditions. Structural characterization of these disordered states using experimental methods can be challenging, since they are composed of a structurally heterogeneous ensemble of conformations rather than a single dominant conformation. Molecular dynamics (MD) simulations should in principle provide an ideal tool for elucidating the composition and behavior of disordered states at an atomic level of detail.

Assessing the accuracy of physical models used in protein-folding simulations: quantitative evidence from long molecular dynamics simulations.

Advances in computer hardware, software and algorithms have now made it possible to run atomistically detailed, physics-based molecular dynamics simulations of sufficient length to observe multiple instances of protein folding and unfolding within a single equilibrium trajectory. Although such studies have already begun to provide new insights into the process of protein folding, realizing the full potential of this approach will depend not only on simulation speed, but on the accuracy of the physical models ('force fields') on which such simulations are based. While experimental data are not available for comparison with all of the salient characteristics observable in long protein-folding simulations, we examine here the extent to which current force fields reproduce (and fail to reproduce) certain relevant properties for which such comparisons are possible.

Atomistic description of the folding of a dimeric protein.

Equilibrium molecular dynamics simulations are increasingly being used to describe the folding of individual proteins and protein domains at an atomic level of detail. Isolated protein domains, however, are rarely observed in vivo, where multidomain proteins and multimeric assemblies are far more common. It is clear that the folding of such proteins is often inextricably coupled with the process of dimerization; indeed, many protein monomers and protein domains are not stable in isolation, and fold to their native structures only when stabilized by interactions with other members of a protein complex.

Atomic-level description of ubiquitin folding.

Equilibrium molecular dynamics simulations, in which proteins spontaneously and repeatedly fold and unfold, have recently been used to help elucidate the mechanistic principles that underlie the folding of fast-folding proteins. The extent to which the conclusions drawn from the analysis of such proteins, which fold on the microsecond timescale, apply to the millisecond or slower folding of naturally occurring proteins is, however, unclear. As a first attempt to address this outstanding issue, we examine here the folding of ubiquitin, a 76-residue-long protein found in all eukaryotes that is known experimentally to fold on a millisecond timescale.

Protein folding kinetics and thermodynamics from atomistic simulation.

Advances in simulation techniques and computing hardware have created a substantial overlap between the timescales accessible to atomic-level simulations and those on which the fastest-folding proteins fold. Here we demonstrate, using simulations of four variants of the human villin headpiece, how simulations of spontaneous folding and unfolding can provide direct access to thermodynamic and kinetic quantities such as folding rates, free energies, folding enthalpies, heat capacities, Φ-values, and temperature-jump relaxation profiles. The quantitative comparison of simulation results with various forms of experimental data probing different aspects of the folding process can facilitate robust assessment of the accuracy of the calculations while providing a detailed structural interpretation for the experimental observations.

Evaluating the effects of cutoffs and treatment of long-range electrostatics in protein folding simulations.

The use of molecular dynamics simulations to provide atomic-level descriptions of biological processes tends to be computationally demanding, and a number of approximations are thus commonly employed to improve computational efficiency. In the past, the effect of these approximations on macromolecular structure and stability has been evaluated mostly through quantitative studies of small-molecule systems or qualitative observations of short-timescale simulations of biological macromolecules. Here we present a quantitative evaluation of two commonly employed approximations, using a test system that has been the subject of a number of previous protein folding studies--the villin headpiece.

Refinement of protein structure homology models via long, all-atom molecular dynamics simulations.

Accurate computational prediction of protein structure represents a longstanding challenge in molecular biology and structure-based drug design. Although homology modeling techniques are widely used to produce low-resolution models, refining these models to high resolution has proven difficult. With long enough simulations and sufficiently accurate force fields, molecular dynamics (MD) simulations should in principle allow such refinement, but efforts to refine homology models using MD have for the most part yielded disappointing results.

Systematic validation of protein force fields against experimental data.

Molecular dynamics simulations provide a vehicle for capturing the structures, motions, and interactions of biological macromolecules in full atomic detail. The accuracy of such simulations, however, is critically dependent on the force field--the mathematical model used to approximate the atomic-level forces acting on the simulated molecular system. Here we present a systematic and extensive evaluation of eight different protein force fields based on comparisons of experimental data with molecular dynamics simulations that reach a previously inaccessible timescale.

Structure and dynamics of an unfolded protein examined by molecular dynamics simulation.

The accurate characterization of the structure and dynamics of proteins in disordered states is a difficult problem at the frontier of structural biology whose solution promises to further our understanding of protein folding and intrinsically disordered proteins. Molecular dynamics (MD) simulations have added considerably to our understanding of folded proteins, but the accuracy with which the force fields used in such simulations can describe disordered proteins is unclear. In this work, using a modern force field, we performed a 200 μs unrestrained MD simulation of the acid-unfolded state of an experimentally well-characterized protein, ACBP, to explore the extent to which state-of-the-art simulation can describe the structural and dynamical features of a disordered protein.

How fast-folding proteins fold.

An outstanding challenge in the field of molecular biology has been to understand the process by which proteins fold into their characteristic three-dimensional structures. Here, we report the results of atomic-level molecular dynamics simulations, over periods ranging between 100 μs and 1 ms, that reveal a set of common principles underlying the folding of 12 structurally diverse proteins. In simulations conducted with a single physics-based energy function, the proteins, representing all three major structural classes, spontaneously and repeatedly fold to their experimentally determined native structures.

How robust are protein folding simulations with respect to force field parameterization?

Molecular dynamics simulations hold the promise of providing an atomic-level description of protein folding that cannot easily be obtained from experiments. Here, we examine the extent to which the molecular mechanics force field used in such simulations might influence the observed folding pathways. To that end, we performed equilibrium simulations of a fast-folding variant of the villin headpiece using four different force fields.

Computational design and experimental testing of the fastest-folding β-sheet protein.

One of the most important and elusive goals of molecular biology is the formulation of a detailed, atomic-level understanding of the process of protein folding. Fast-folding proteins with low free-energy barriers have proved to be particularly productive objects of investigation in this context, but the design of fast-folding proteins was previously driven largely by experiment. Dramatic advances in the attainable length of molecular dynamics simulations have allowed us to characterize in atomic-level detail the folding mechanism of the fast-folding all-β WW domain FiP35.