Molecular dynamics (MD) simulations have become increasingly popular in studying the motions and functions of biomolecules. The accuracy of the simulation, however, is highly determined by the ...molecular mechanics (MM) force field (FF), a set of functions with adjustable parameters to compute the potential energies from atomic positions. However, the overall quality of the FF, such as our previously published ff99SB and ff14SB, can be limited by assumptions that were made years ago. In the updated model presented here (ff19SB), we have significantly improved the backbone profiles for all 20 amino acids. We fit coupled φ/ψ parameters using 2D φ/ψ conformational scans for multiple amino acids, using as reference data the entire 2D quantum mechanics (QM) energy surface. We address the polarization inconsistency during dihedral parameter fitting by using both QM and MM in aqueous solution. Finally, we examine possible dependency of the backbone fitting on side chain rotamer. To extensively validate ff19SB parameters, and to compare to results using other Amber models, we have performed a total of ∼5 ms MD simulations in explicit solvent. Our results show that after amino-acid-specific training against QM data with solvent polarization, ff19SB not only reproduces the differences in amino-acid-specific Protein Data Bank (PDB) Ramachandran maps better but also shows significantly improved capability to differentiate amino-acid-dependent properties such as helical propensities. We also conclude that an inherent underestimation of helicity is present in ff14SB, which is (inexactly) compensated for by an increase in helical content driven by the TIP3P bias toward overly compact structures. In summary, ff19SB, when combined with a more accurate water model such as OPC, should have better predictive power for modeling sequence-specific behavior, protein mutations, and also rational protein design. Of the explicit water models tested here, we recommend use of OPC with ff19SB.
Since the first attempts at structure-based drug design about four decades ago, molecular modelling techniques for drug design have developed enormously, along with the increasing computational power ...and structural and biological information of active compounds and potential target molecules. Nowadays, molecular modeling can be considered to be an integral component of the modern drug discovery and development toolbox. Nevertheless, there are still many methodological challenges to be overcome in the application of molecular modeling approaches to drug discovery. The eight original research and five review articles collected in this book provide a snapshot of the state-of-the-art of molecular modeling in drug design, illustrating recent advances and critically discussing important challenges. The topics covered include virtual screening and pharmacophore modelling, chemoinformatic applications of artificial intelligence and machine learning, molecular dynamics simulation and enhanced sampling to investigate contributions of molecular flexibility to drug–receptor interactions, the modeling of drug–receptor solvation, hydrogen bonding and polarization, and drug design against protein–protein interfaces and membrane protein receptors.
The description of coherent features of fluid flow is essential to our understanding of fluid-dynamical and transport processes. A method is introduced that is able to extract dynamic information ...from flow fields that are either generated by a (direct) numerical simulation or visualized/measured in a physical experiment. The extracted dynamic modes, which can be interpreted as a generalization of global stability modes, can be used to describe the underlying physical mechanisms captured in the data sequence or to project large-scale problems onto a dynamical system of significantly fewer degrees of freedom. The concentration on subdomains of the flow field where relevant dynamics is expected allows the dissection of a complex flow into regions of localized instability phenomena and further illustrates the flexibility of the method, as does the description of the dynamics within a spatial framework. Demonstrations of the method are presented consisting of a plane channel flow, flow over a two-dimensional cavity, wake flow behind a flexible membrane and a jet passing between two cylinders.
•A complete modeling procedure is applied including the modeling of gear mesh stiffness, transmission error and gear pair.•The analytical gear mesh stiffness shows a good agreement with the published ...result of finite element approach.•The numerical results of proposed dynamic model match well with the published experimental data.•The effects of several essential gear parameters are investigated.•Deeper properties of gear vibration are revealed to guide the actual design and control of gear dynamics.
This study is concerned with the nonlinear frequency response characteristics of a spur gear pair system, in which the modeling of time varying mesh stiffness (TVMS) and static transmission error (STE) is stressed. Firstly, a complete modeling procedure is constructed by adopting existing models of TVMS, STE and gear pair, so that the basic gear features and design parameters are contained in the overall gear model. On this basis, a 1 degree-of-freedom (DOF) spur gear pair model is established including the TVMS, STE and nonlinear backlash. Then, to show the validity and reliability, theoretical solutions of the dynamic model are verified by the published numerical results and experimental data. Besides, the stability of the gear system is investigated analytically to obtain the boundaries that separate stable and unstable regions. Finally, parametric studies are conducted to reveal the effects of several key parameters, such as the contact ratio, spacing error, transmitted load and damping ratio. The results show that the modeling of TVMS and STE should be considered and emphasized to obtain precise predictions of system responses and to reveal in depth properties of gear dynamics. Furthermore, the parametric studies and stability analysis offer useful suggestions for researchers and engineers to achieve desirable design and control of dynamic behaviors of gear system.
Autonomous unmanned aerial vehicles (UAVs) that can execute aggressive (i.e., high-speed and high-acceleration) maneuvers have attracted significant attention in the past few years. This article ...focuses on accurate tracking of aggressive quadcopter trajectories. We propose a novel control law for tracking of position and yaw angle and their derivatives of up to fourth order, specifically velocity, acceleration, jerk, and snap along with yaw rate and yaw acceleration. Jerk and snap are tracked using feedforward inputs for angular rate and angular acceleration based on the differential flatness of the quadcopter dynamics. Snap tracking requires direct control of body torque, which we achieve using closed-loop motor speed control based on measurements from optical encoders attached to the motors. The controller utilizes incremental nonlinear dynamic inversion (INDI) for robust tracking of linear and angular accelerations despite external disturbances, such as aerodynamic drag forces. Hence, prior modeling of aerodynamic effects is not required. We rigorously analyze the proposed control law through response analysis and demonstrate it in experiments. The controller enables a quadcopter UAV to track complex 3-D trajectories, reaching speeds up to 12.9 m/s and accelerations up to 2.1 g, while keeping the root-mean-square tracking error down to 6.6 cm, in a flight volume that is roughly 18 m <inline-formula> <tex-math notation="LaTeX">\times 7 </tex-math></inline-formula> m and 3-m tall. We also demonstrate the robustness of the controller by attaching a drag plate to the UAV in flight tests and by pulling on the UAV with a rope during hover.
Low-dimensional systems provide beautiful examples of many-body quantum physics. For one-dimensional (1D) systems, the Luttinger liquid approach provides insight into universal properties. Much is ...known of the equilibrium state, both in the weakly and strongly interacting regimes. However, it remains a challenge to probe the dynamics by which this equilibrium state is reached. Here we present a direct experimental study of the coherence dynamics in both isolated and coupled degenerate 1D Bose gases. Dynamic splitting is used to create two 1D systems in a phase coherent state. The time evolution of the coherence is revealed through local phase shifts of the subsequently observed interference patterns. Completely isolated 1D Bose gases are observed to exhibit universal sub-exponential coherence decay, in excellent agreement with recent predictions. For two coupled 1D Bose gases, the coherence factor is observed to approach a non-zero equilibrium value, as predicted by a Bogoliubov approach. This coupled-system decay to finite coherence is the matter wave equivalent of phase-locking two lasers by injection. The non-equilibrium dynamics of superfluids has an important role in a wide range of physical systems, such as superconductors, quantum Hall systems, superfluid helium and spin systems. Our experiments studying coherence dynamics show that 1D Bose gases are ideally suited for investigating this class of phenomena.
This is the first book to combine classical vehicle dynamics with electronic control. The equation-based presentation of the theory behind vehicle dynamics enables readers to develop a thorough ...understanding of the key attribute to both a vehicle's driveability and its active safety. Supported by MATLAB tools, the key areas that affect vehicle dynamics are explored including tire mechanics, the steering system, vehicle roll, traction and braking, 4WS and vehicle dynamics, vehicle dynamics by vehicle and human control, and controllabiliy. As a professional reference volume, this book is an essential addition to the resources available to anyone working in vehicle design and development. Written by a leading authority in the field (who himself has considerable practical experience), the book has a unique blend of theory and practice that will be of immense value in this applications based field.
* Get a thorough understand of why vehicles respond they way they do with a complete treatment of vehicle dynamics from theory to application* Full of case studies and worked examples using MATLAB/Simulink * Covers all variables of vehicle dynamics including tire and vehicle motion, control aspects, human control and external disturbances
Robot and Multibody Dynamics: Analysis and Algorithms provides a comprehensive and detailed exposition of a new mathematical approach, referred to as the Spatial Operator Algebra (SOA), for studying ...the dynamics of articulated multibody systems. The approach is useful in a wide range of applications including robotics, aerospace systems, articulated mechanisms, bio-mechanics and molecular dynamics simulation. The book also: -Treats algorithms for simulation, including an analysis of complexity of the algorithms -Describes one universal, robust, and analytically sound approach to formulating the equations that govern the motion of complex multi-body systems -Covers a range of more advanced topics including under-actuated systems, flexible systems, linearization, diagonalized dynamics and space manipulators. Robot and Multibody Dynamics: Analysis and Algorithms will be a valuable resource for researchers and engineers looking for new mathematical approaches to finding engineering solutions in robotics and dynamics.
We propose a general dynamic reduced-order modelling framework for typical experimental data: time-resolved sensor data and optional non-time-resolved particle image velocimetry (PIV) snapshots. This ...framework can be decomposed into four building blocks. First, the sensor signals are lifted to a dynamic feature space without false neighbours. Second, we identify a sparse human-interpretable nonlinear dynamical system for the feature state based on the sparse identification of nonlinear dynamics (SINDy). Third, if PIV snapshots are available, a local linear mapping from the feature state to the velocity field is performed to reconstruct the full state of the system. Fourth, a generalized feature-based modal decomposition identifies coherent structures that are most dynamically correlated with the linear and nonlinear interaction terms in the sparse model, adding interpretability. Steps 1 and 2 define a black-box model. Optional steps 3 and 4 lift the black-box dynamics to a grey-box model in terms of the identified coherent structures, if non-time-resolved full-state data are available. This grey-box modelling strategy is successfully applied to the transient and post-transient laminar cylinder wake, and compares favourably with a proper orthogonal decomposition model. We foresee numerous applications of this highly flexible modelling strategy, including estimation, prediction and control. Moreover, the feature space may be based on intrinsic coordinates, which are unaffected by a key challenge of modal expansion: the slow change of low-dimensional coherent structures with changing geometry and varying parameters.
Complexes of I--lactalbumin and oleic acid have previously been shown to be cytotoxic to cancer cells. In this study oleic acid is replaced by the more soluble sodium oleate and complexes of ...I--lactalbumin and sodium oleate are formed. Dynamic light scattering results showed that there was a small linear increase in the particle size of I--lactalbumin when it was titrated with sodium oleate. The fluorescence spectra of I--lactalbumin showed a linear increase in the emission maximum when sodium oleate was added up to a molar ratio of 8a11 oleate molecules per I--lactalbumin. Differential scanning calorimetry results show that the thermal unfolding of I--lactalbumin is altered by the presence of the sodium oleate. There is a decrease in size of the endothermic peak of apo I--lactalbumin when sodium oleate is added. The temperature at which unfolding occurred decreased for both apo and holo I--lactalbumin. FTIR measurements showed no significant effect of sodium oleate in the amide I region of the I--lactalbumin spectrum indicating the presence of oleate has little or no effect on the secondary structure of I--lactalbumin. The interactions between I--lactalbumin and sodium oleate/oleic acid are pH dependent, turbidity and dynamic light scattering measurements showed that the association between the two was optimal between pH 6.0 and 8.0.
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