Free Energy by Molecular Simulation. In: Lipkowitz KB, Boyd DB, editors. Reviews in Computational Chemistry. Hoboken: John Wiley & Sons, Inc.; 1996. pp. 81-127. [DOI: 10.1002/9780470125861.ch2]

CLiB - a novel cardiolipin-binder isolated via data-driven and in vitro screening

Cardiolipin, the mitochondria marker lipid, is crucially involved in stabilizing the inner mitochondrial membrane and is vital for the activity of mitochondrial proteins and protein complexes. Directly targeting cardiolipin by a chemical-biology approach and thereby altering the cellular concentration of "available" cardiolipin eventually allows to systematically study the dependence of cellular processes on cardiolipin availability. In the present study, physics-based coarse-grained free energy calculations allowed us to identify the physical and chemical properties indicative of cardiolipin selectivity and to apply these to screen a compound database for putative cardiolipin-binders. The membrane binding properties of the 22 most promising molecules identified in the in silico approach were screened in vitro, using model membrane systems finally resulting in the identification of a single molecule, CLiB (CardioLipin-Binder). CLiB clearly affects respiration of cardiolipin-containing intact bacterial cells as well as of isolated mitochondria. Thus, the structure and function of mitochondrial membranes and membrane proteins might be (indirectly) targeted and controlled by CLiB for basic research and, potentially, also for therapeutic purposes.

NWChem: Past, present, and future

Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts and for the prediction of atomistic and electronic properties. In this regard, electronic structure packages have played a special role by using first-principle-driven methodologies to model complex chemical and materials processes. Over the past few decades, the rapid development of computing technologies and the tremendous increase in computational power have offered a unique chance to study complex transformations using sophisticated and predictive many-body techniques that describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, novel parallel algorithms have been able to take advantage of computational resources to address the polynomial scaling of electronic structure methods. In this paper, we briefly review the NWChem computational chemistry suite, including its history, design principles, parallel tools, current capabilities, outreach, and outlook.

Uncertainty Quantification in Alchemical Free Energy Methods

Alchemical free energy methods have gained much importance recently from several reports of improved ligand–protein binding affinity predictions based on their implementation using molecular dynamics simulations. A large number of variants of such methods implementing different accelerated sampling techniques and free energy estimators are available, each claimed to be better than the others in its own way. However, the key features of reproducibility and quantification of associated uncertainties in such methods have barely been discussed. Here, we apply a systematic protocol for uncertainty quantification to a number of popular alchemical free energy methods, covering both absolute and relative free energy predictions. We show that a reliable measure of error estimation is provided by ensemble simulation—an ensemble of independent MD simulations—which applies irrespective of the free energy method. The need to use ensemble methods is fundamental and holds regardless of the duration of time of the molecular dynamics simulations performed.

Atomistic level molecular dynamics simulation on the solubilization mechanism of aromatic molecules in anionic micelles

Benzene is solubilized in the palisade layer, toluene in the core (or central region), phenol at the surface and pyridine in micelle–water interface. During micellar enhanced ultrafiltration, phenol will have least rejection while benzene is maximum.

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.

Alchemical free energy calculations and multiple conformational substates

Thermodynamic integration (TI) was combined with (adaptive) umbrella sampling to improve the convergence of alchemical free energy simulations in which multiple conformational substates are present. The approach, which we refer to as non-Boltzmann TI (NBTI), was tested by computing the free energy differences between three five-atomic model systems, as well as the free energy difference of solvation between leucine and asparagine. In both cases regular TI failed to give converged results, whereas the NBTI results were free from hysteresis and had standard deviations well below +/-0.7 kcal/mole. We also present theoretical considerations that make it possible to compute free energy differences between simple molecules, such as the five-atomic model systems, by numerical integration of the partition functions at the respective end points.

Robust and accurate method for free-energy calculation of charged molecular systems

A new approach is presented to eliminate the problem of creation and/or annihilation of atoms in free-energy calculations of charged molecular systems. The method employs a damping potential in the Ewald summation scheme, which is an exact solution of the electrostatics for three-dimensional periodic systems. The proposed method enables entire molecules to be mutated from a noninteracting (ideal) state in an efficient and robust way, thus providing a means by which accurate absolute free energies of structurally complex molecules can be determined. This methodology will enable chemical and phase equilibria to be determined for large molecular species with significant charge distributions, e.g., biomolecules and drugs.

Getting it right: modeling of pH, solvent and “nearly” everything else in virtual screening of biological targets

"Getting it right" refers to the careful modeling of all elements in the living system, i.e. biological macromolecules, ligands and water molecules. In addition, careful attention should be paid to the protonation state of ionizable functional groups on the ligands and residues at the active site. Computational technology based on the empirical HINT program is described to: (1) calculate free energy scores for ligand binding; (2) include the implicit and explicit effects of water in and around the ligand binding site; and (3) incorporate the effects of global and local pH in molecular models. This last point argues for the simultaneous consideration of a number of molecular models, each with different protonation profiles. Data from recent studies of protein-ligand systems (trypsin, thrombin, neuraminidase, HIV-1 protease and others) are used to illustrate the concepts in the paper. Also discussed are experimental factors related to accurate free energy predictions with this and other computational technologies.

Fast prediction of hydration free energies from molecular interaction fields

A novel empirical model is presented that allows the fast computation of hydration free energies with high accuracy. The linear model is based upon the separation of the free energy of hydration into a cavity and an interaction term. The cavity contribution is modeled as a linear combination of molecular volume and surface terms. The interaction part is derived from the statistical three-dimensional (3D) free energy density and is modeled approximately as a molecular interaction field using the program GRID. A compression scheme is employed to represent this 3D information on the molecular surface by means of a linear combination of surface functions. A set of 81 small organic molecules with known experimental hydration free energies is used to determine the coefficients of the linear model by least squares regression. The fit is statistically significant yielding a correlation coefficient of 0.99, a root mean square error of 0.27 kcal/mol for the 81 molecules belonging to the training set, and 0.63 kcal/mol for an independent test set of 10 molecules.

Monte Carlo calculations on HIV-1 reverse transcriptase complexed with the non-nucleoside inhibitor 8-Cl TIBO: contribution of the L100I and Y181C variants to protein stability and biological activity

A computational model of the non-nucleoside inhibitor 8-Cl TIBO complexed with HIV-1 reverse transcriptase (RT) was constructed in order to determine the binding free energies. Using Monte Carlo simulations, both free energy perturbation and linear response calculations were carried out for the transformation of wild-type RT to two key mutants, Y181C and L100I. The newer linear response method estimates binding free energies based on changes in electrostatic and van der Waals energies and solvent-accessible surface areas. In addition, the change in stability of the protein between the folded and unfolded states was estimated for each of these mutations, which are known to emerge upon treatment with the inhibitor. Results from the calculations revealed that there is a large hydrophobic contribution to protein stability in the native, folded state. The calculated absolute free energies of binding from both the linear response, and also the more rigorous free energy perturbation method, gave excellent agreement with the experimental differences in activity. The success of the relatively rapid linear response method in predicting experimental activities holds promise for estimating the activity of the inhibitors not only against the wild-type RT, but also against key protein variants whose emergence undermines the efficacy of the drugs.

Structure-based drug design: computational advances

Structure-based computational methods continue to enhance progress in the discovery and refinement of therapeutic agents. Several such methods and their applications are described. These include molecular visualization and molecular modeling, docking, fragment methods, 3-D database techniques, and free-energy perturbation. Related issues that are discussed include the use of simplified potential energy functions and the determination of the positions of tightly bound waters. Strengths and weaknesses of the various methods are described.