Michel A. Cuendet

SwissParam: A fast force field generation tool for small organic molecules

The drug discovery process has been deeply transformed recently by the use of computational ligand‐based or structure‐based methods, helping the lead compounds identification and optimization, and finally the delivery of new drug candidates more quickly and at lower cost. Structure‐based computational methods for drug discovery mainly involve ligand‐protein docking and rapid binding free energy estimation, both of which require force field parameterization for many drug candidates. Here, we present a fast force field generation tool, called SwissParam, able to generate, for arbitrary small organic molecule, topologies, and parameters based on the Merck molecular force field, but in a functional form that is compatible with the CHARMM force field. Output files can be used with CHARMM or GROMACS. The topologies and parameters generated by SwissParam are used by the docking software EADock2 and EADock DSS to describe the small molecules to be docked, whereas the protein is described by the CHARMM force field, and allow them to reach success rates ranging from 56 to 78%. We have also developed a rapid binding free energy estimation approach, using SwissParam for ligands and CHARMM22/27 for proteins, which requires only a short minimization to reproduce the experimental binding free energy of 214 ligand‐protein complexes involving 62 different proteins, with a standard error of 2.0 kcal mol−1, and a correlation coefficient of 0.74. Together, these results demonstrate the relevance of using SwissParam topologies and parameters to describe small organic molecules in computer‐aided drug design applications, together with a CHARMM22/27 description of the target protein. SwissParam is available free of charge for academic users at www.swissparam.ch.

Implementation of the CHARMM Force Field in GROMACS : Analysis of Protein Stability Effects from Correction Maps, Virtual Interaction Sites, and Water Models

CHARMM27 is a widespread and popular force field for biomolecular simulation, and several recent algorithms such as implicit solvent models have been developed specifically for it. We have here implemented the CHARMM force field and all necessary extended functional forms in the GROMACS molecular simulation package, to make CHARMM-specific features available and to test them in combination with techniques for extended time steps, to make all major force fields available for comparison studies in GROMACS, and to test various solvent model optimizations, in particular the effect of Lennard-Jones interactions on hydrogens. The implementation has full support both for CHARMM-specific features such as multiple potentials over the same dihedral angle and the grid-based energy correction map on the ϕ, ψ protein backbone dihedrals, as well as all GROMACS features such as virtual hydrogen interaction sites that enable 5 fs time steps. The medium-to-long time effects of both the correction maps and virtual sites have been tested by performing a series of 100 ns simulations using different models for water representation, including comparisons between CHARMM and traditional TIP3P. Including the correction maps improves sampling of near native-state conformations in our systems, and to some extent it is even able to refine distorted protein conformations. Finally, we show that this accuracy is largely maintained with a new implicit solvent implementation that works with virtual interaction sites, which enables performance in excess of 250 ns/day for a 900-atom protein on a quad-core desktop computer.

Protein-Protein Interaction Investigated by Steered Molecular Dynamics: The TCR-pMHC Complex

We present a novel steered molecular dynamics scheme to induce the dissociation of large protein-protein complexes. We apply this scheme to study the interaction of a T cell receptor (TCR) with a major histocompatibility complex (MHC) presenting a peptide (p). Two TCR-pMHC complexes are considered, which only differ by the mutation of a single amino acid on the peptide; one is a strong agonist that produces T cell activation in vivo, while the other is an antagonist. We investigate the interaction mechanism from a large number of unbinding trajectories by analyzing van der Waals and electrostatic interactions and by computing energy changes in proteins and solvent. In addition, dissociation potentials of mean force are calculated with the Jarzynski identity, using an averaging method developed for our steering scheme. We analyze the convergence of the Jarzynski exponential average, which is hampered by the large amount of dissipative work involved and the complexity of the system. The resulting dissociation free energies largely underestimate experimental values, but the simulations are able to clearly differentiate between wild-type and mutated TCR-pMHC and give insights into the dissociation mechanism.

Transport domain unlocking sets the uptake rate of an aspartate transporter

Glutamate transporters terminate neurotransmission by clearing synaptically released glutamate from the extracellular space, allowing repeated rounds of signalling and preventing glutamate-mediated excitotoxicity. Crystallographic studies of a glutamate transporter homologue from the archaeon Pyrococcus horikoshii, GltPh, showed that distinct transport domains translocate substrates into the cytoplasm by moving across the membrane within a central trimerization scaffold. Here we report direct observations of these ‘elevator-like’ transport domain motions in the context of reconstituted proteoliposomes and physiological ion gradients using single-molecule fluorescence resonance energy transfer (smFRET) imaging. We show that GltPh bearing two mutations introduced to impart characteristics of the human transporter exhibits markedly increased transport domain dynamics, which parallels an increased rate of substrate transport, thereby establishing a direct temporal relationship between transport domain motion and substrate uptake. Crystallographic and computational investigations corroborated these findings by revealing that the ‘humanizing’ mutations favour structurally ‘unlocked’ intermediate states in the transport cycle exhibiting increased solvent occupancy at the interface between the transport domain and the trimeric scaffold.

Heating and flooding: A unified approach for rapid generation of free energy surfaces

We propose a general framework for the efficient sampling of conformational equilibria in complex systems and the generation of associated free energy hypersurfaces in terms of a set of collective variables. The method is a strategic synthesis of the adiabatic free energy dynamics approach, previously introduced by us and others, and existing schemes using Gaussian-based adaptive bias potentials to disfavor previously visited regions. In addition, we suggest sampling the thermodynamic force instead of the probability density to reconstruct the free energy hypersurface. All these elements are combined into a robust extended phase-space formalism that can be easily incorporated into existing molecular dynamics packages. The unified scheme is shown to outperform both metadynamics and adiabatic free energy dynamics in generating two-dimensional free energy surfaces for several example cases including the alanine dipeptide in the gas and aqueous phases and the met-enkephalin oligopeptide. In addition, the method can efficiently generate higher dimensional free energy landscapes, which we demonstrate by calculating a four-dimensional surface in the Ramachandran angles of the gas-phase alanine tripeptide.

How T cell receptors interact with peptide-MHCs: A multiple steered molecular dynamics study

The T‐cell receptor (TCR) interaction with antigenic peptides (p) presented by the major histocompatibility complex (MHC) molecule is a key determinant of immune response. In addition, TCR‐pMHC interactions offer examples of features more generally pertaining to protein‐protein recognition: subtle specificity and cross‐reactivity. Despite their importance, molecular details determining the TCR‐pMHC binding remain unsolved. However, molecular simulation provides the opportunity to investigate some of these aspects. In this study, we perform extensive equilibrium and steered molecular dynamics simulations to study the unbinding of three TCR‐pMHC complexes. As a function of the dissociation reaction coordinate, we are able to obtain converged H‐bond counts and energy decompositions at different levels of detail, ranging from the full proteins, to separate residues and water molecules, down to single atoms at the interface. Many observed features do not support a previously proposed two‐step model for TCR recognition. Our results also provide keys to interpret experimental point‐mutation results. We highlight the role of water both in terms of interface resolvation and of water molecules trapped in the bound complex. Importantly, we illustrate how two TCRs with similar reactivity and structures can have essentially different binding strategies. Proteins 2011;

Allosteric Mechanisms of Molecular Machines at the Membrane: Transport by Sodium-Coupled Symporters

Solute transport across cell membranes is ubiquitous in biology as an essential physiological process. Secondary active transporters couple the unfavorable process of solute transport against its concentration gradient to the energetically favorable transport of one or several ions. The study of such transporters over several decades indicates that their function involves complex allosteric mechanisms that are progressively being revealed in atomistic detail. We focus on two well-characterized sodium-coupled symporters: the bacterial amino acid transporter LeuT, which is the prototype for the gated pore mechanism in the mammalian synaptic monoamine transporters, and the archaeal GltPh, which is the prototype for the elevator mechanism in the mammalian excitatory amino acid transporters. We present the evidence for the role of allostery in the context of a quantitative formalism that can reconcile biochemical and biophysical data and thereby connects directly to recent insights into the molecular structure and dynamics of these proteins. We demonstrate that, while the structures and mechanisms of these transporters are very different, the available data suggest a common role of specific models of allostery in their functions. We argue that such allosteric mechanisms appear essential not only for sodium-coupled symport in general but also for the function of other types of molecular machines in the membrane.

Use of the FACTS solvation model for protein-ligand docking calculations. Application to EADock.

Protein–ligand docking has made important progress during the last decade and has become a powerful tool for drug development, opening the way to virtual high throughput screening and in silico structure‐based ligand design. Despite the flattering picture that has been drawn, recent publications have shown that the docking problem is far from being solved, and that more developments are still needed to achieve high successful prediction rates and accuracy. Introducing an accurate description of the solvation effect upon binding is thought to be essential to achieve this goal. In particular, EADock uses the Generalized Born Molecular Volume 2 (GBMV2) solvent model, which has been shown to reproduce accurately the desolvation energies calculated by solving the Poisson equation. Here, the implementation of the Fast Analytical Continuum Treatment of Solvation (FACTS) as an implicit solvation model in small molecules docking calculations has been assessed using the EADock docking program. Our results strongly support the use of FACTS for docking. The success rates of EADock/FACTS and EADock/GBMV2 are similar, i.e. around 75% for local docking and 65% for blind docking. However, these results come at a much lower computational cost: FACTS is 10 times faster than GBMV2 in calculating the total electrostatic energy, and allows a speed up of EADock by a factor of 4. This study also supports the EADock development strategy relying on the CHARMM package for energy calculations, which enables straightforward implementation and testing of the latest developments in the field of Molecular Modeling. Copyright

Free Energy Reconstruction from Metadynamics or Adiabatic Free Energy Dynamics Simulations.

In molecular dynamics simulations, most enhanced sampling methods are traditionally associated with one particular estimator to calculate the free energy surface (FES), such as the histogram, the mean force, or the bias potential. Here, we start from the realization that four enhanced sampling methods, metadynamics and well-tempered metadynamics (in their extended Lagrangian form), as well as driven adiabatic free energy dynamics (dAFED) and unified free energy dynamics (UFED), can be used in combination with any of the three above-mentioned FES estimators. We compare the convergence properties of these estimators on the alanine dipeptide and a sodium ion solvation shell. We find that the mean force estimator is superior in all cases. We also show that it can be marginally beneficial to combine information from the histogram and the force, provided that both are of comparable accuracy.

How accurately do current force fields predict experimental peptide conformations? An adiabatic free energy dynamics study

The quality of classical biomolecular simulations is inevitably limited by two problems: the accuracy of the force field used and the comprehensiveness of configuration space sampling. In this work we tackle the sampling problem by carrying out driven adiabatic free energy dynamics to obtain converged free energy surfaces of dipeptides in the gas phase and in solution using selected dihedral angles as collective variables. To calculate populations of conformational macrostates observed in experiment, we introduce a fuzzy clustering algorithm in collective-variable space, which delineates macrostates without prior definition of arbitrary boundaries. With this approach, we calculate the conformational preferences of small peptides with six biomolecular force fields chosen from among the most recent and widely used. We assess the accuracy of each force field against recently published Raman or IR-UV spectroscopy measurements of conformer populations for the dipeptides in solution or in the gas phase.