@article {2020|2142,
	title = {Scalable molecular dynamics on CPU and GPU architectures with NAMD},
	journal = {The Journal of Chemical Physics},
	volume = {153},
	year = {2020},
	chapter = {044130},
	abstract = {<p>NAMD is a molecular dynamics program designed for high-performance simulations of very large biological objects on CPU- and GPU-based architectures. NAMD offers scalable performance on petascale parallel supercomputers consisting of hundreds of thousands of cores, as well as on inexpensive commodity clusters commonly found in academic environments. It is written in C++ and leans on Charm++ parallel objects for optimal performance on low-latency architectures. NAMD is a versatile, multipurpose code that gathers state-of-the-art algorithms to carry out simulations in apt thermodynamic ensembles, using the widely popular CHARMM, AMBER, OPLS, and GROMOS biomolecular force fields. Here, we review the main features of NAMD that allow both equilibrium and enhanced-sampling molecular dynamics simulations with numerical efficiency. We describe the underlying concepts utilized by NAMD and their implementation, most notably for handling long-range electrostatics; controlling the temperature, pressure, and pH; applying external potentials on tailored grids; leveraging massively parallel resources in multiple-copy simulations; and hybrid quantum-mechanical/molecular-mechanical descriptions. We detail the variety of options offered by NAMD for enhanced-sampling simulations aimed at determining free-energy differences of either alchemical or geometrical transformations and outline their applicability to specific problems. Last, we discuss the roadmap for the development of NAMD and our current efforts toward achieving optimal performance on GPU-based architectures, for pushing back the limitations that have prevented biologically realistic billion-atom objects to be fruitfully simulated, and for making large-scale simulations less expensive and easier to set up, run, and analyze. NAMD is distributed free of charge with its source code at www.ks.uiuc.edu.</p>
},
	keywords = {NAMD},
	doi = {10.1063/5.0014475},
	url = {https://aip.scitation.org/doi/10.1063/5.0014475},
	author = {James Phillips and David Hardy and Julio Maia and John Stone and Joao Ribeiro and Rafael Bernardi and Ronak Buch and Giacomo Fiorin and J{\'e}r{\^o}me H{\'e}nin and Wei Jiang and Ryan McGreevy and Melo, Marcelo Cardoso dos Reis and Brian Radak and Robert Skeel and Abhishek Singharoy and Yi Wang and Benoit Roux and Aleksei Aksimentiev and Zan Luthey-Schulten and Laxmikant Kale and Klaus Schulten and Christophe Chipot and Emad Tajkhorshid}
}
@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 = {<p>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.</p>},
	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 {2010|1851,
	title = {Exploring Multidimensional Free Energy Landscapes Using Time-Dependent Biases on Collective Variables},
	journal = {J. Chem. Theory Comput.},
	volume = {6},
	number = {1},
	year = {2010},
	pages = {35{\textendash}47},
	author = {J{\'e}r{\^o}me H{\'e}nin and Giacomo Fiorin and Christophe Chipot and Michael L Klein}
}
@article {2008|1603,
	title = {Diffusion of glycerol through Escherichia coli aquaglyceroporin GlpF},
	journal = {Biophys. J.},
	volume = {94},
	number = {3},
	year = {2008},
	pages = {832{\textendash}839},
	abstract = {The glycerol uptake facilitator, GlpF, a major intrinsic protein found in Escherichia coli, selectively conducts water and glycerol across the inner membrane. The free energy landscape characterizing the assisted transport of glycerol by this homotetrameric aquaglyceroporin has been explored by means of equilibrium molecular dynamics over a timescale spanning 0.12 micros. To overcome the free energy barriers of the conduction pathway, an adaptive biasing force is applied to the glycerol molecule confined in each of the four channels. The results illuminate the critical role played by intramolecular relaxation on the diffusion properties of the permeant. These free energy calculations reveal that glycerol tumbles and isomerizes on a timescale comparable to that spanned by its adaptive-biasing-force-assisted conduction in GlpF. As a result, reorientation and conformational equilibrium of glycerol in GlpF constitute a bottleneck in the molecular simulations of the permeation event. A profile characterizing the position-dependent diffusion of the permeant has been determined, allowing reaction rate theory to be applied for investigating conduction kinetics based on the measured free energy landscape.},
	keywords = {Aquaporins, Chemical, Computer Simulation, Diffusion, Escherichia coli Proteins, Glycerol, Ion Channel Gating, Models, Molecular, Molecular Conformation, Porosity},
	doi = {10.1529/biophysj.107.115105},
	author = {J{\'e}r{\^o}me H{\'e}nin and Emad Tajkhorshid and Klaus Schulten and Christophe Chipot}
}
@article {2006|1860,
	title = {Conformational equilibrium in alanine-rich peptides probed by reversible stretching simulations},
	journal = {J. Phys. Chem. B},
	volume = {110},
	number = {33},
	year = {2006},
	pages = {16718{\textendash}16723},
	doi = {10.1021/jp0601116},
	author = {J{\'e}r{\^o}me H{\'e}nin and Schulten, K. and Christophe Chipot}
}
@article {2006|1794,
	title = {Hydrogen-bonding patterns of cholesterol in lipid membranes},
	journal = {Chem. Phys. Lett.},
	volume = {425},
	year = {2006},
	pages = {329{\textendash}335},
	abstract = {Correlation between the rotation of the cholesterol hydroxyl group and the formation of hydrogen bonds with its lipid environment is examined through molecular dynamics (MD) simulations and compared with recently reported NMR experiments. All atom MD simulations of a fully hydrated 1:2 cholesterol-dimyristoylphosphatidylcholine bilayer have been performed. Precise reproduction of the cholesterol cell parameters via simulation of its P1-group crystal validates the force field utilized. The lipid-cholesterol hydrogen-bonding pattern reflects the coexistence of alternative dimer motifs with comparable conformer populations, in line with the estimated free energy differences for the rotamers of the cholesterol CO bond.},
	url = {http://www.sciencedirect.com/science/article/B6TFN-4JYTJ8F-1/2/20363e602ea4fdd317abf97ba8e91987},
	author = {J{\'e}r{\^o}me H{\'e}nin and Christophe Chipot}
}
@article {2006|1604,
	title = {Probing a model of a {GPCR}/ligand complex in an explicit membrane environment: The human cholecystokinin-1 receptor},
	journal = {Biophys. J.},
	volume = {90},
	number = {4},
	year = {2006},
	pages = {1232{\textendash}1240},
	abstract = {A three-dimensional model structure of a complex formed by a G-protein-coupled receptor (GPCR) and an agonist ligand is probed and refined using molecular-dynamics simulations and free energy calculations in a realistic environment. The model of the human receptor of cholecystokinin associated to agonist ligand CCK9 was obtained from a synergistic procedure combining site-directed mutagenesis experiments and in silico modeling. The 31-ns molecular-dynamics simulation in an explicit membrane environment indicates that both the structure of the receptor and its interactions with the ligand are robust. Whereas the secondary structure of the {alpha}-helix bundle is well preserved, the region of the intracellular loops exhibits a significant flexibility likely to be ascribed to the absence of G-protein subunits in the model. New insight into the structural features of the binding pocket is gained, in particular, the interplay of the ligand with both the receptor and internal water molecules. Water-mediated interactions are shown to participate in the binding, hence, suggesting additional site-directed mutagenesis experiments. Accurate free energy calculations on mutated ligands provide differences in the receptor-ligand binding affinity, thus offering a direct, quantitative comparison to experiment. We propose that this detailed consistency-checking procedure be used as a routine refinement step of in vacuo GPCR models, before further investigation and application to structure-based drug design.},
	url = {http://www.biophysj.org/cgi/content/abstract/90/4/1232},
	author = {J{\'e}r{\^o}me H{\'e}nin and Maigret, B. and Mounir Tarek and Escrieut, C. and Fourmy, D. and Christophe Chipot}
}
@article {2005|1847,
	title = {Exploring the free energy landscape of a short peptide using an average force},
	journal = {J. Chem. Phys.},
	volume = {123},
	year = {2005},
	pages = {244906},
	author = {Christophe Chipot and J{\'e}r{\^o}me H{\'e}nin}
}
@article {2005|1839,
	title = {Insights into the recognition and association of transmembrane $\alpha$-helices. {T}he free energy of $\alpha$-helix dimerization in glycophorin {A}},
	journal = {J. Am. Chem. Soc.},
	volume = {127},
	number = {23},
	year = {2005},
	pages = {8478{\textendash}8484},
	abstract = {The free energy of alpha-helix dimerization of the transmembrane (TM) region of glycophorin A was estimated from a 125-ns molecular dynamics (MD) simulation in a membrane mimetic. The free energy profile was obtained by allowing the TM helical segments to diffuse reversibly along the reaction pathway. Partition of the potential of mean force into free energy components illuminates the critical steps of alpha-helix recognition and association. At large separations, the TM segments are pushed together by the solvent, allowing initial, but not necessarily native, interhelical interactions to occur. This early recognition stage precedes the formation of native contacts, which is accompanied by a tilt of the helices, characteristic of the dimeric structure. This step is primarily driven by the van der Waals helix-helix interactions. Free energy perturbation calculations of the L75A and I76A point mutations reveal a disruption in helix-helix association due to a loss of favorable dispersion interactions. Additional MD simulations of the native TM dimer and of a single alpha-helix confirm that, prior to association, individual alpha-helices are independently stable, in agreement with the "two-stage" model of integral membrane protein folding.},
	doi = {10.1021/ja050581y},
	author = {J{\'e}r{\^o}me H{\'e}nin and A. Pohorille and Christophe Chipot}
}
@article {2004|1846,
	title = {Overcoming free energy barriers using unconstrained molecular dynamics simulations},
	journal = {J. Chem. Phys.},
	volume = {121},
	year = {2004},
	pages = {2904{\textendash}2914},
	author = {J{\'e}r{\^o}me H{\'e}nin and Christophe Chipot}
}
