CHARMM: The biomolecular simulation program

CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecular simulation program. It has been developed over the last three decades with a primary focus on molecules of biological interest, including proteins, peptides, lipids, nucleic acids, carbohydrates, and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estimators, molecular minimization, dynamics, and analysis techniques, and model-building capabilities. The CHARMM program is applicable to problems involving a much broader class of many-particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numerous platforms in both serial and parallel architectures. This article provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM article in 1983. © 2009 Wiley Periodicals, Inc.J Comput Chem, 2009.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63074/1/21287_ftp.pd

RE-EDS Using GAFF Topologies: Application to Relative Hydration Free-Energy Calculations for Large Sets of Molecules

Free-energy differences between pairs of end-states can be estimated based on molecular dynamics (MD) simulations using standard pathway-dependent methods such as thermodynamic integration (TI), free-energy perturbation, or Bennett's acceptance ratio. Replica-exchange enveloping distribution sampling (RE-EDS), on the other hand, allows for the sampling of multiple end-states in a single simulation without the specification of any pathways. In this work, we use the RE-EDS method as implemented in GROMOS together with generalized AMBER force field (GAFF) topologies, converted to a GROMOS-compatible format with a newly developed GROMOS++ program amber2gromos, to compute relative hydration free energies for a series of benzene derivatives. The results obtained with RE-EDS are compared to the experimental data as well as calculated values from the literature. In addition, the estimated free-energy differences in water and in vacuum are compared to values from TI calculations carried out with GROMACS. The hydration free energies obtained using RE-EDS for multiple molecules are found to be in good agreement with both the experimental data and the results calculated using other free-energy methods. While all considered free-energy methods delivered accurate results, the RE-EDS calculations required the least amount of total simulation time. This work serves as a validation for the use of GAFF topologies with the GROMOS simulation package and the RE-EDS approach. Furthermore, the performance of RE-EDS for a large set of 28 end-states is assessed with promising results

Modeling the Binding of Neurotransmitter Transporter Inhibitors with Molecular Dynamics and Free Energy Calculations

The monoamine transporter (MAT) proteins responsible for the reuptake of the neurotransmitter substrates, dopamine, serotonin, and norepinephrine, are drug targets for the treatment of psychiatric disorders including depression, anxiety, and attention deficit hyperactivity disorder. Small molecules that inhibit these proteins can serve as useful therapeutic agents. However, some dopamine transporter (DAT) inhibitors, such as cocaine and methamphetamine, are highly addictive and abusable. Efforts have been made to develop small molecules that will inhibit the transporters and elucidate specific binding site interactions. This work provides knowledge of molecular interactions associated with MAT inhibitors by offering an atomistic perspective that can guide designs of new pharmacotherapeutics with enhanced activity. The work described herein evaluates intermolecular interactions using computational methods to reveal the mechanistic detail of inhibitors binding in the DAT. Because cocaine recognizes the extracellular-facing or outward-facing (OF) DAT conformation and benztropine recognizes the intracellular-facing or inward-facing (IF) conformation, it was postulated that behaviorally “typical” (abusable, locomotor psychostimulant) inhibitors stabilize the OF DAT and “atypical” (little or no abuse potential) inhibitors favor IF DAT. Indeed, behaviorally-atypical cocaine analogs have now been shown to prefer the OF DAT conformation. Specifically, the binding interactions of two cocaine analogs, LX10 and LX11, were studied in the OF DAT using molecular dynamics simulations. LX11 was able to interact with residues of transmembrane helix 8 and bind in a fashion that allowed for hydration of the primary binding site (S1) from the intracellular space, thus impacting the intracellular interaction network capable of regulating conformational transitions in DAT. Additionally, a novel serotonin transporter (SERT) inhibitor previously discovered through virtual screening at the SERT secondary binding site (S2) was studied. Intermolecular interactions between SM11 and SERT have been assessed using binding free energy calculations to predict the ligand-binding site and optimize ligand-binding interactions. Results indicate the addition of atoms to the 4-chlorobenzyl moiety were most energetically favorable. The simulations carried out in DAT and SERT were supported by experimental results. Furthermore, the co-crystal structures of DAT and SERT share similar ligand-binding interactions with the homology models used in this study

What to Make of Zero: Resolving the Statistical Noise from Conformational Reorganization in Alchemical Binding Free Energy Estimates with Metadynamics Sampling

We introduce the self-Relative Binding Free Energy (self-RBFE) approach to evaluate the intrinsic statistical variance of dual-topology alchemical binding free energy estimators. The self-RBFE is the relative binding free energy between a ligand and a copy of the same ligand, and its true value is zero. Nevertheless, because the two copies of the ligand move independently, the self-RBFE value produced by a finite-length simulation fluctuates and can be used to measure the variance of the model. The results of this validation provide evidence that a significant fraction of the errors observed in benchmark studies reflect the statistical fluctuations of unconverged estimates rather than the models' accuracy. Furthermore, we find that ligand reorganization is a significant contributing factor to the statistical variance of binding free energy estimates and that metadynamics-accelerated conformational sampling of torsional degrees of freedom of the ligand can drastically reduce the time to convergence

Reproducibility of Free Energy Calculations Across Different Molecular Simulation Software

<div> <div> <div> <p>Alchemical free energy calculations are an increasingly important modern simulation technique. Contemporary molecular simulation software such as AMBER, CHARMM, GROMACS and SOMD include support for the method. Implementation details vary among those codes but users expect reliability and reproducibility, i.e. for a given molec- ular model and set of forcefield parameters, comparable free energy should be obtained within statistical bounds regardless of the code used. Relative alchemical free energy (RAFE) simulation is increasingly used to support molecule discovery projects, yet the reproducibility of the methodology has been less well tested than its absolute counter- part. Here we present RAFE calculations of hydration free energies for a set of small organic molecules and demonstrate that free energies can be reproduced to within about 0.2 kcal/mol with aforementioned codes. Achieving this level of reproducibility requires considerable attention to detail and package–specific simulation protocols, and no uni- versally applicable protocol emerges. The benchmarks and protocols reported here should be useful for the community to validate new and future versions of software for free energy calculations.</p></div></div></div

Conformations and coherences in structure determination by ultrafast electron diffraction

In this article we consider consequences of spatial coherences and conformations in diffraction of (macro)molecules with different potential energy landscapes. The emphasis is on using this understanding to extract structural and temporal information from diffraction experiments. The theoretical analysis of structural interconversions spans an increased range of complexity, from small hydrocarbons to proteins. For each molecule considered, we construct the potential energy landscape and assess the characteristic conformational states available. For molecules that are quasiharmonic in the vicinity of energy minima, we find that the distinct conformer model is sufficient even at high temperatures. If, however, the energy surface is either locally flat around the minima or the molecule includes many degrees of conformational freedom, a Boltzmann ensemble must be used, in what we define as the pseudoconformer approach, to reproduce the diffraction. For macromolecules with numerous energy minima, the ensemble of hundreds of structures is considered, but we also utilize the concept of the persistence length to provide information on orientational coherence and its use to assess the degree of resonance contribution to diffraction. It is shown that the erosion of the resonant features in diffraction which are characteristic of some quasiperiodic structural motifs can be exploited in experimental studies of conformational interconversions triggered by a laser-induced temperature jump

Accelerate sampling in atomistic energy landscapes using topology-based coarse-grained models

We describe a multiscale enhanced sampling (MSES) method where efficient topology-based coarse-grained models are coupled with all-atom ones to enhance the sampling of atomistic protein energy landscape. The bias from the coupling is removed by Hamiltonian replica exchange, thus allowing one to benefit simultaneously from faster transitions of coarse-grained modeling and accuracy of atomistic force fields. The method is demonstrated by calculating the conformational equilibria of several small but nontrivial β-hairpins with varied stabilities

Performance and Analysis of the Alchemical Transfer Method for Binding Free Energy Predictions of Diverse Ligands

The Alchemical Transfer Method (ATM) is herein validated against the relative binding free energies of a diverse set of protein-ligand complexes. We employed a streamlined setup workflow, a bespoke force field, and the AToM-OpenMM software to compute the relative binding free energies (RBFE) of the benchmark set prepared by Schindler and collaborators at Merck KGaA. This benchmark set includes examples of standard small R-group ligand modifications as well as more challenging scenarios, such as large R-group changes, scaffold hopping, formal charge changes, and charge-shifting transformations. The novel coordinate perturbation scheme and a dual-topology approach of ATM address some of the challenges of single-topology alchemical relative binding free energy methods. Specifically, ATM eliminates the need for splitting electrostatic and Lennard-Jones interactions, atom mapping, defining ligand regions, and post-corrections for charge-changing perturbations. Thus, ATM is simpler and more broadly applicable than conventional alchemical methods, especially for scaffold-hopping and charge-changing transformations. Here, we performed well over 500 relative binding free energy calculations for eight protein targets and found that ATM achieves accuracy comparable to existing state-of-the-art methods, albeit with larger statistical fluctuations. We discuss insights into specific strengths and weaknesses of the ATM method that will inform future deployments. This study confirms that ATM is applicable as a production tool for relative binding free energy (RBFE) predictions across a wide range of perturbation types within a unified, open-source framework