@article {2015|1667, title = {The adaptive biasing force method: everything you always wanted to know but were afraid to ask.}, journal = {J. Phys. Chem. B}, volume = {119}, year = {2015}, month = {jan}, pages = {1129{\textendash}51}, abstract = {

In the host of numerical schemes devised to calculate free energy differences by way of geometric transformations, the adaptive biasing force algorithm has emerged as a promising route to map complex free-energy landscapes. It relies upon the simple concept that as a simulation progresses, a continuously updated biasing force is added to the equations of motion, such that in the long-time limit it yields a Hamiltonian devoid of an average force acting along the transition coordinate of interest. This means that sampling proceeds uniformly on a flat free-energy surface, thus providing reliable free-energy estimates. Much of the appeal of the algorithm to the practitioner is in its physically intuitive underlying ideas and the absence of any requirements for prior knowledge about free-energy landscapes. Since its inception in 2001, the adaptive biasing force scheme has been the subject of considerable attention, from in-depth mathematical analysis of convergence properties to novel developments and extensions. The method has also been successfully applied to many challenging problems in chemistry and biology. In this contribution, the method is presented in a comprehensive, self-contained fashion, discussing with a critical eye its properties, applicability, and inherent limitations, as well as introducing novel extensions. Through free-energy calculations of prototypical molecular systems, many methodological aspects are examined, from stratification strategies to overcoming the so-called hidden barriers in orthogonal space, relevant not only to the adaptive biasing force algorithm but also to other importance-sampling schemes. On the basis of the discussions in this paper, a number of good practices for improving the efficiency and reliability of the computed free-energy differences are proposed.

}, issn = {1520-5207}, doi = {10.1021/jp506633n}, author = {Comer, Jeffrey and Gumbart, James C and J{\'e}r{\^o}me H{\'e}nin and Leli{\`e}vre, Tony and Pohorille, Andrew and Christophe Chipot} } @article {2014|1792, title = {Allosteric regulation of pentameric ligand-gated ion channels: An emerging mechanistic perspective}, journal = {Channels}, volume = {8}, number = {4}, year = {2014}, pages = {350{\textendash}360}, keywords = {Allosteric Regulation, Animals, chemistry/metabolism, Humans, Ion Channel Gating, Ligand-Gated Ion Channels, metabolism, Models, Molecular, Protein Multimerization, Small Molecule Libraries}, author = {Antoine Taly and J{\'e}r{\^o}me H{\'e}nin and Changeux, Jean-Pierre and Cecchini, Marco} } @article {2010|1865, title = {An atomistic model for simulations of the general anesthetic isoflurane}, journal = {J. Phys. Chem. B}, volume = {114}, number = {1}, year = {2010}, pages = {604{\textendash}612}, publisher = {Laboratoire d{\textquoteright}Ing{\'e}nierie des Syst{\`e}mes Macromol{\'e}culaires, CNRS, Marseille, France. jhenin@ifr88.cnrs-mrs.fr}, abstract = {An atomistic model of isoflurane is constructed and calibrated to describe its conformational preferences and intermolecular interactions. The model, which is compatible with the CHARMM force field for biomolecules, is based on target quantities including bulk liquid properties, molecular conformations, and local interactions with isolated water molecules. Reference data is obtained from tabulated thermodynamic properties and high-resolution structural information from gas-phase electron diffraction, as well as DFT calculations at the B3LYP level. The model is tested against experimentally known solvation properties in water and oil, and shows quantitative agreement. In particular, isoflurane is faithfully described as lipophilic, yet nonhydrophobic, a combination of properties critical to its pharmacological activity. Intermolecular interactions of the model are further probed through simulations of the binding of isoflurane to a binding site in horse spleen apoferritin (HSAF). The observed binding mode compares well with crystallographic data, and the calculated binding affinities are compatible with experimental results, although both computational and experimental measurements are challenging and provide results with limited precision. The model is expected to be useful for detailed simulations of the elementary molecular processes associated with anesthesia. Full parameters are provided as Supporting Information.}, doi = {10.1021/jp9088035}, author = {J{\'e}r{\^o}me H{\'e}nin and Grace Brannigan and William P Dailey and Roderic G Eckenhoff and Michael L Klein} }