Comment on 'Valid molecular dynamics simulations of human hemoglobin require a surprisingly large box size'.

A recent molecular dynamics investigation into the stability of hemoglobin concluded that the unliganded protein is only stable in the T state when a solvent box is used in the simulations that is ten times larger than what is usually employed (El Hage et al., 2018). Here, we express three main concerns about that study. In addition, we find that with an order of magnitude more statistics, the reported box size dependence is not reproducible. Overall, no significant effects on the kinetics or thermodynamics of conformational transitions were observed

Predicting kinase inhibitor resistance: Physics-based and data-driven approaches.

Resistance to small molecule drugs often emerges in cancer cells, viruses, and bacteria as a result of the evolutionary pressure exerted by the therapy. Protein mutations that directly impair drug binding are frequently involved in resistance, and the ability to anticipate these mutations would be beneficial in drug development and clinical practice. Here, we evaluate the ability of three distinct computational methods to predict ligand binding affinity changes upon protein mutation for the cancer target Abl kinase. These structure-based approaches rely on first-principle statistical mechanics, mixed physics- and knowledge-based potentials, and machine learning, and were able to estimate binding affinity changes and identify resistant mutations with remarkable accuracy. We expect that these complementary approaches will enable the routine prediction of resistance-causing mutations in a variety of other target proteins

Outcome Measurement and Functional Prognosis in early Multiple Sclerosis

Bouter, L.M. [Promotor]Lankhorst, G.J. [Promotor]Polman, C.H. [Promotor]Beckerman, H. [Copromotor

Comment on "Deficiencies in molecular dynamics simulation-based prediction of protein-DNA binding free energy landscapes"

Sequence-specific DNA binding transcription factors play an essential role in the transcriptional regulation of all organisms. The development of reliable in silico methods to predict the binding affinity landscapes of transcription factors thus promises to provide rapid screening of transcription factor specificities and, at the same time, yield valuable insight into the atomistic details of the interactions driving those specificities. Recent literature has reported highly discrepant results on the current ability of state-of-the-art atomistic molecular dynamics simulations to reproduce experimental binding free energy landscapes for transcription factors. Here, we resolve one important discrepancy by noting that in the case of alchemical free energy calculations involving base pair mutations, a common convention used in improving end point convergence of mixed potentials in fact can lead to erroneous results. The underlying cause for inaccurate double free energy difference estimates is specific to the particular implementation of the alchemical transformation protocol. Using the Gromacs simulation package, which is not affected by this issue, we obtain free energy landscapes in agreement with the experimental measurements; equivalent results are obtained for a small set of test cases with a modified version of the AMBER package. Our findings provide a consistent and optimistic outlook on the current state of prediction of protein-DNA binding free energy interactions using molecular dynamics simulations and an important precaution for appropriate end point handling in a broad range of free energy calculations

Observation of negative differential conductance in a reverse-biased Ni/Ge Schottky diode

We report the experimental observation of negative differential conductance in a Ni/Ge Schottky diode. With the aid of theoretical models and numerical simulation we show that, at reverse bias, electons tunnel into the high electric field of the depletion region. This scatters the electrons into the upper valley of the Ge conduction band, which has a lower mobility. The observed negative differential conductance is hence attributed to the transferred-electron effect. This shows that Schottky contacts can be used to create hot electrons for transferred-electron devices

Speed limits for quantum gates in multi-qubit systems

We use analytical and numerical calculations to obtain speed limits for various unitary quantum operations in multiqubit systems under typical experimental conditions. The operations that we consider include single-, two-, and three-qubit gates, as well as quantum-state transfer in a chain of qubits. We find in particular that simple methods for implementing two-qubit gates generally provide the fastest possible implementations of these gates. We also find that the three-qubit Toffoli gate time varies greatly depending on the type of interactions and the system's geometry, taking only slightly longer than a two-qubit controlled-NOT (CNOT) gate for a triangle geometry. The speed limit for quantum-state transfer across a qubit chain is set by the maximum spin-wave speed in the chain.Comment: 7 pages (two-column), 2 figures, 2 table

Hard thermal loops with a background plasma velocity

I consider the calculation of the two and three-point functions for QED at finite temperature in the presence of a background plasma velocity. The final expressions are consistent with Lorentz invariance, gauge invariance and current conservation, pointing to a straightforward generalization of the hard thermal loop formalism to this physical situation. I also give the resulting expression for the effective action and identify the various terms.Comment: 11 pages, no figure

On the importance of statistics in molecular simulations for thermodynamics, kinetics and simulation box size

Computational simulations, akin to wetlab experimentation, are subject to statistical fluctuations. Assessing the magnitude of these fluctuations, that is, assigning uncertainties to the computed results, is of critical importance to drawing statistically reliable conclusions. Here, we use a simulation box size as an independent variable, to demonstrate how crucial it is to gather sufficient amounts of data before drawing any conclusions about the potential thermodynamic and kinetic effects. In various systems, ranging from solvation free energies to protein conformational transition rates, we showcase how the proposed simulation box size effect disappears with increased sampling. This indicates that, if at all, the simulation box size only minimally affects both the thermodynamics and kinetics of the type of biomolecular systems presented in this work