Configurational Sampling of All-Atom Solvated Membranes Using Hybrid Nonequilibrium Molecular Dynamics Monte Carlo Simulations.

All-atom simulations are a powerful approach to study the structure and dynamics of biological membranes. However, sampling the atomic configurations of inhomogeneous membranes can be challenging due to the slow lateral diffusion of the various constituents. To address this issue, a hybrid nonequilibrium molecular dynamics Monte Carlo (neMD/MC) simulation method is proposed in which randomly chosen lipid molecules are swapped to generate configurations that are subsequently accepted or rejected according to a Metropolis criterion based on the alchemical work for the attempted swap calculated via a short trajectory. A dual-topology framework constraining the common atoms of the exchanging molecules yields a good acceptance probability using switching trajectories as short as 10 ps. The performance of the hybrid neMD/MC algorithm and its ability to sample the distribution of lipids near a transmembrane helix carrying a net charge are illustrated for a binary mixture of charged and zwitterionic lipids.

Computational Assessment of Protein-Protein Binding Specificity within a Family of Synaptic Surface Receptors.

Atomic-level information is essential to explain the formation of specific protein complexes in terms of structure and dynamics. The set of Dpr and DIP proteins, which play a key role in the neuromorphogenesis in the nervous system of Drosophila melanogaster, offer a rich paradigm to learn about protein-protein recognition. Many members of the DIP subfamily cross-react with several members of the Dpr family and vice versa. While there exists a total of 231 possible Dpr-DIP heterodimer complexes from the 21 Dpr and 11 DIP proteins, only 57 "cognate" pairs have been detected by surface plasmon resonance (SPR) experiments, suggesting that the remaining 174 pairs have low or unreliable binding affinity. Our goal is to assess the performance of computational approaches to characterize the global set of interactions between Dpr and DIP proteins and identify the specificity of binding between each DIP with their corresponding Dpr binding partners. In addition, we aim to characterize how mutations influence the specificity of the binding interaction. In this work, a wide range of knowledge-based and physics-based approaches are utilized, including mutual information, linear discriminant analysis, homology modeling, molecular dynamics simulations, Poisson-Boltzmann continuum electrostatics calculations, and alchemical free energy perturbation to decipher the origin of binding specificity of the Dpr-DIP complexes examined. Ultimately, the results show that those two broad strategies are complementary, with different strengths and limitations. Biological inter-relations are more clearly revealed through knowledge-based approaches combining evolutionary and structural features, the molecular determinants controlling binding specificity can be predicted accurately with physics-based approaches based on atomic models.

Accurate determination of protein:ligand standard binding free energies from molecular dynamics simulations.

Designing a reliable computational methodology to calculate protein:ligand standard binding free energies is extremely challenging. The large change in configurational enthalpy and entropy that accompanies the association of ligand and protein is notoriously difficult to capture in naive brute-force simulations. Addressing this issue, the present protocol rests upon a rigorous statistical mechanical framework for the determination of protein:ligand binding affinities together with the comprehensive Binding Free-Energy Estimator 2 (BFEE2) application software. With the knowledge of the bound state, available from experiments or docking, application of the BFEE2 protocol with a reliable force field supplies in a matter of days standard binding free energies within chemical accuracy, for a broad range of protein:ligand complexes. Limiting undesirable human intervention, BFEE2 assists the end user in preparing all the necessary input files and performing the post-treatment of the simulations towards the final estimate of the binding affinity.

Capturing the dynamic association between a tris-dipicolinate lanthanide complex and a decapeptide: a combined paramagnetic NMR and molecular dynamics exploration.

In the realm of biomolecules, peptides can present a large diversity of structures. Our study sheds new light on the structural interplay between a tris-dipicolinate lanthanide probe and a decapeptide SASYKTLPRG. Although a rather trivial, electrostatically driven interaction was expected, the combination of paramagnetic NMR and molecular dynamics simulations reveals a highly dynamic association process and allows for providing extensive insights into the interaction sites and their occupancy. This study highlights the importance of a large conformational sampling to reconcile characteristic time in NMR with molecular dynamics simulations, where sampling in the microsecond range is needed. This study opens the door for a detailed mechanistic elucidation of the early steps of lanthanide complex-peptide or lanthanide complex-protein interaction or self-assembly processes.

Molecular Dynamics Approach for Capturing Calixarene-Protein Interactions: The Case of Cytochrome C.

Functionalized supramolecular cages are of growing importance in biology and biochemistry. They have recently been proposed as efficient auxiliaries to obtain high-resolution cocrystallized proteins. Here, we propose a molecular dynamics investigation of the supramolecular association of sulfonated calix-[8]-arenes to cytochrome c starting from initially distant proteins and ligands. We characterize two main binding sites for the sulfonated calixarene on the cytochrome c surface which are in perfect agreement with the previous experiments with regard to the structure (comparison with the X-ray structure PDB 6GD8) and the binding free energies [comparison between the molecular mechanics Poisson-Boltzmann surface area analysis and the isothermal titration calorimetry measurements]. The per-residue decomposition of the interaction energies reveals the detailed picture of this electrostatically driven association and notably the role of arginine R13 as a bridging residue between the two main anchoring sites. In addition, the analysis of the residue behavior by means of a supervised machine learning protocol unveils the formation of a hydrogen bond network far from the binding sites, increasing the rigidity of the protein. This study paves the way toward an automated procedure to predict the supramolecular protein-cage association, with the possibility of a computational screening of new promising derivatives for controlled protein assembly and protein surface recognition processes.

Inertial capillary uptake of drops.

Uptake of liquid drops into capillary tubes has been experimentally studied and quantitatively analyzed. In experiments, drops of water and aqueous glycerol (≤50 wt %) were drawn into cylindrical borosilicate glass and quartz tubes with an inner diameter of 0.50-0.75 mm. The meniscus height rise was measured using high-speed images captured at 4000 frames per second, and results within a conservatively defined inertial regime indicate constant uptake velocity. An increase in the inertial velocity with drop curvature was observed due to increasing Laplace pressure in the drop, as drop sizes were comparable to the width of the capillary tubes. Measured velocities were slower than predicted by a purely inertial-capillary model and best described by introducing a contact line friction, consistent with the observed variability and viscosity dependence of the results. Mean friction coefficients in borosilicate capillaries ranged from 169±1 for 50 wt % glycerol drops to 218±1 for water drops. Peaks in the instantaneous Laplace pressure caused by surface oscillations were also measured. Correlations with uptake velocity were qualitatively apparent, with a delay between peaks of similar magnitude to the inertial-capillary oscillation time.