Enhancing DFT-based energy landscape exploration by coupling quantum mechanics and static modes.

Unravelling the atomic scale diffusion that can occur at the surface, at the interface or into the bulk is challenging: multi-scale modelling approaches usually require intensive prospective calculations and moreover huge human investment. In this article, the Static Mode (SM) approach is coupled with Quantum Mechanics (QM) calculations in order to guide the exploration of the energy landscape, by optimizing the choice of events that are significant for the evolution of the system. SM enable the determination of the strain field of a set of atoms submitted to external and localized stresses, like atomic displacements. Here, we present a workflow based on the systematic SM exploration, with the objective to reduce both exploration time and human load when used with ab initio level calculations. The QMSM coupling allows the screening, scoring and selection of relevant directions that are further used to initiate and study diffusion in atomic systems. The most relevant deformations are then refined and relaxed with DFT calculations. In this paper, the overall QMSM approach is described and we discuss its use for the identification of atomic diffusion in two different systems of interest: grafting of a molecule on an oxide surface and studying the dynamical behavior of a point-defect in a bulk crystalline material.

Finding Reaction Pathways and Transition States: r-ARTn and d-ARTn as an Efficient and Versatile Alternative to String Approaches.

Finding transition states and diffusion pathways is essential to understand the evolution of materials and chemical reactions. Such characterization is hampered by the heavy computation costs associated with exploring energy landscapes at ab initio accuracy. Here, we revisit the activation-relaxation technique (ARTn) to considerably reduce its costs when used with the density functional theory and propose three adapted versions of the algorithm to efficiently (i) explore the energy landscape of complex materials with the knowledge of a single minimum (ARTn); (ii) identify a transition state when two minima or a guess transition state is given (refining ART or r-ART); and (iii) reconstruct complex pathways between two given states (directed ART or d-ART). We show the application of these three variants on benchmark examples and on various complex defects in silicon. For the latter, the presented improvements to ART lead to much more precise transition states while being 2 to 6 times faster than the commonly used string methods such as the climbing image nudged elastic band method (CI-NEB).

Water Distribution within Wild-Type NRas Protein and Q61 Mutants during Unrestrained QM/MM Dynamics.

Point mutations in p21ras are associated with ∼30% of human tumors by disrupting its GTP hydrolysis cycle, which is critical to its molecular switch function in cellular signaling pathways. In this work, we investigate the impact of Gln 61 substitutions in the structure of the p21N-ras active site and particularly focus on water reorganization around GTP, which appears to be crucial to evaluate favorable and unfavorable hydration sites for hydrolysis. The NRas-GTP complex is analyzed using a hybrid quantum mechanics/molecular mechanics approach, treating for the first time to our knowledge transient water molecules at the ab initio level and leading to results that account for the electrostatic coupling between the protein complex and the solvent. We show that for the wild-type protein, water molecules are found around the GTP γ-phosphate group, forming an arch extended from residues 12 to 35. Two density peaks are observed, supporting previous results that suggest the presence of two water molecules in the active site, one in the vicinity of residue 35 and a second one stabilized by hydrogen bonds formed with nitrogen backbone atoms of residues 12 and 60. The structural changes observed in NRas Gln 61 mutants result in the drastic delocalization of water molecules that we discuss. In mutants Q61H and Q61K, for which water distribution is overlocalized next to residue 60, the second density peak supports the hypothesis of a second water molecule. We also conclude that Gly 60 indirectly participates in GTP hydrolysis by correctly positioning transient water molecules in the protein complex and that Gln 61 has an indirect steric effect in stabilizing the preorganized catalytic site.

A perfect wetting of Mg monolayer on Ag(111) under atomic scale investigation: First principles calculations, scanning tunneling microscopy, and Auger spectroscopy.

First principles calculations, scanning tunneling microscopy, and Auger spectroscopy experiments of the adsorption of Mg on Ag(111) substrate are conducted. This detailed study reveals that an atomic scale controlled deposition of a metallic Mg monolayer perfectly wets the silver substrate without any alloy formation at the interface at room temperature. A liquid-like behavior of the Mg species on the Ag substrate is highlighted as no dot formation is observed when coverage increases. Finally a layer-by-layer growth mode of Mg on Ag(111) can be predicted, thanks to density functional theory calculations as observed experimentally.

Toward in silico biomolecular manipulation through static modes: atomic scale characterization of HIV-1 protease flexibility.

Probing biomolecular flexibility with atomic-scale resolution is a challenging task in current computational biology for fundamental understanding and prediction of biomolecular interactions and associated functions. This paper makes use of the static mode method to study HIV-1 protease considered as a model system to investigate the full biomolecular flexibility at the atomic scale, the screening of active site biomechanical properties, the blind prediction of allosteric sites, and the design of multisite strategies to target deformations of interest. Relying on this single calculation run of static modes, we demonstrate that in silico predictive design of an infinite set of complex excitation fields is reachable, thanks to the storage of the static modes in a data bank that can be used to mimic single or multiatom contact and efficiently anticipate conformational changes arising from external stimuli. All along this article, we compare our results to data previously published and propose a guideline for efficient, predictive, and custom in silico experiments.

A computational chemist approach to gas sensors: modeling the response of SnO2 to CO, O2, and H2O gases.

A general bottom-up modeling strategy for gas sensor response to CO, O(2), H(2)O, and related mixtures exposure is demonstrated. In a first stage, we present first principles calculations that aimed at giving an unprecedented review of basic chemical mechanisms taking place at the sensor surface. Then, simulations of an operating gas sensor are performed via a mesoscopic model derived from calculated density functional theory data into a set of differential equations. Significant presence of catalytic oxidation reaction is highlighted.

The electrostatic probe: a tool for the investigation of the Aß(1-16) peptide deformations using the static modes.

We investigate the conformational changes of the Amyloid ß(1-16) peptide induced by moving Zn(2+) ions in the solvent, which we call the electrostatic probe. We use our recently developed approach of static modes which allows treating the flexibility of biological molecules at the atomic scale. Starting from an experimental apostructure, we find that several ion impacts allow the transition of the peptide toward its folded conformation, observed experimentally in the presence of Zn(2+) ions. This result shows the ability of our model and its associated software tool to describe properly the conformational changes and opens a new path toward the molecule/molecule docking problem.

Atomic scale determination of enzyme flexibility and active site stability through static modes: case of dihydrofolate reductase.

A Static Mode approach is used to screen the biomechanical properties of DHFR. In this approach, a specific external stimulus may be designed at the atomic scale granularity to arrive at a proper molecular mechanism. In this frame, we address the issues related to the overall molecular flexibility versus loop motions and versus enzymatic activity. We show that backbone motions are particularly important to ensure DHFR domain communication and notably highlight the role of a α-helix in Met20 loop motion. We also investigate the active site flexibility in different bound states. Whereas in the occluded conformation the Met20 loop is highly flexible, in the closed conformation backbone motions are no longer significant, the Met20 loop is rigidified by new intra- and intermolecular weak bonds, which stabilizes the complex and promotes the hydride transfer. Finally, while various simulations, including I14 V and I14A mutations, confirm that Ile14 is a key residue in catalytic activity, we isolate and characterize at the atomic scale how a specific intraresidue chemical group makes it possible to assist ligand positioning, to direct the nicotinamide ring toward the folate ring.