scholarly journals Multiscale Free Energy Simulations: An Efficient Method for Connecting Classical MD Simulations to QM or QM/MM Free Energies Using Non-Boltzmann Bennett Reweighting Schemes

2014 ◽  
Vol 10 (4) ◽  
pp. 1406-1419 ◽  
Author(s):  
Gerhard König ◽  
Phillip S. Hudson ◽  
Stefan Boresch ◽  
H. Lee Woodcock
Keyword(s):  
Free Energy ◽  
Efficient Method ◽  
Md Simulations ◽  
Free Energies ◽  
Energy Simulations

scholarly journals Thermodynamics and free energy landscape of BAR-domain dimerization from molecular simulations

2020 ◽  
Author(s):  
Adip Jhaveri ◽  
Dhruw Maisuria ◽  
Matthew Varga ◽  
Dariush Mohammadyani ◽  
Margaret E Johnson
Keyword(s):  
Free Energy ◽  
Energy Surface ◽  
Md Simulations ◽  
Coarse Grained ◽  
Enhanced Sampling ◽  
Free Energies ◽  
Free Energy Surface ◽  
Bar Domain ◽  
Bar Domains ◽  
Protein Models

AbstractNearly all proteins interact specifically with other proteins, often forming reversible bound structures whose stability is critical to function. Proteins with BAR domains function to bind to, bend, and remodel biological membranes, where the dimerization of BAR domains is a key step in this function. Here we characterize the binding thermodynamics of homodimerization between the LSP1 BAR domain proteins in solution, using Molecular Dynamics (MD) simulations. By combining the MARTINI coarse-grained protein models with enhanced sampling through metadynamics, we construct a two-dimensional free energy surface quantifying the bound versus unbound ensembles as a function of two distance variables. Our simulations portray a heterogeneous and extraordinarily stable bound ensemble for these modeled LSP1 proteins. The proper crystal structure dimer has a large hydrophobic interface that is part of a stable minima on the free energy surface, which is enthalpically the minima of all bound structures. However, we also find several other stable nonspecific dimers with comparable free energies to the specific dimer. Through structure-based clustering of these bound structures, we find that some of these ‘nonspecific’ contacts involve extended tail regions that help stabilize the higher-order oligomers formed by BAR-domains, contacts that are separated from the homodimer interface. We find that the known membrane-binding residues of the LSP1 proteins rarely participate in any of the bound interfaces, but that both patches of residues are aligned to interact with the membrane in the specific dimer. Hence, we would expect a strong selection of the specific dimer in binding to the membrane. The effect of a 100mM NaCl buffer reduces the relative stability of nonspecific dimers compared to the specific dimer, indicating that it would help prevent aggregation of the proteins. With these results, we provide the first free energy characterization of interaction pathways in this important class of membrane sculpting domains, revealing a variety of interfacial contacts outside of the specific dimer that may help stabilize its oligomeric assemblies.

scholarly journals The Good, the Bad, and the Ugly: “HiPen”, a New Dataset for Validating (S)QM/MM Free Energy Simulations

Molecules ◽  
2019 ◽  
Vol 24 (4) ◽  
pp. 681 ◽  
Author(s):  
Fiona Kearns ◽  
Luke Warrensford ◽  
Stefan Boresch ◽  
H. Woodcock
Keyword(s):  
Free Energy ◽  
Gas Phase ◽  
Convergence Criteria ◽  
Free Energies ◽  
Acceptance Ratio ◽  
Current State ◽  
Energy Perturbation ◽  
Energy Simulations ◽  
Molecular Description ◽  
Bennett’S Acceptance Ratio

Indirect (S)QM/MM free energy simulations (FES) are vital to efficiently incorporating sufficient sampling and accurate (QM) energetic evaluations when estimating free energies of practical/experimental interest. Connecting between levels of theory, i.e., calculating Δ A l o w → h i g h , remains to be the most challenging step within an indirect FES protocol. To improve calculations of Δ A l o w → h i g h , we must: (1) compare the performance of all FES methods currently available; and (2) compile and maintain datasets of Δ A l o w → h i g h calculated for a wide-variety of molecules so that future practitioners may replicate or improve upon the current state-of-the-art. Towards these two aims, we introduce a new dataset, “HiPen”, which tabulates Δ A g a s M M → 3 o b (the free energy associated with switching from an M M to an S C C − D F T B molecular description using the 3ob parameter set in gas phase), calculated for 22 drug-like small molecules. We compare the calculation of this value using free energy perturbation, Bennett’s acceptance ratio, Jarzynski’s equation, and Crooks’ equation. We also predict the reliability of each calculated Δ A g a s M M → 3 o b by evaluating several convergence criteria including sample size hysteresis, overlap statistics, and bias metric ( Π ). Within the total dataset, three distinct categories of molecules emerge: the “good” molecules, for which we can obtain converged Δ A g a s M M → 3 o b using Jarzynski’s equation; “bad” molecules which require Crooks’ equation to obtain a converged Δ A g a s M M → 3 o b ; and “ugly” molecules for which we cannot obtain reliably converged Δ A g a s M M → 3 o b with either Jarzynski’s or Crooks’ equations. We discuss, in depth, results from several example molecules in each of these categories and describe how dihedral discrepancies between levels of theory cause convergence failures even for these gas phase free energy simulations.

Calculation of free energy changes due to mutations from alchemical free energy simulations

2015 ◽  
Vol 14 (03) ◽  
pp. 1550023 ◽  
Author(s):  
M. Harunur Rashid ◽  
Germano Heinzelmann ◽  
Serdar Kuyucak
Keyword(s):  
Free Energy ◽  
Fundamental Problem ◽  
Binding Free Energy ◽  
Computational Design ◽  
Md Simulations ◽  
Binding Mode ◽  
Free Energy Calculations ◽  
Energy Calculations ◽  
Energy Simulations ◽  
Alchemical Free Energy

How a mutation affects the binding free energy of a ligand is a fundamental problem in molecular biology/biochemistry with many applications in pharmacology and biotechnology, e.g. design of drugs and enzymes. Free energy change due to a mutation can be determined most accurately by performing alchemical free energy calculations in molecular dynamics (MD) simulations. Here we discuss the necessary conditions for success of free energy calculations using toxin peptides that bind to ion channels as examples. We show that preservation of the binding mode is an essential requirement but this condition is not always satisfied, especially when the mutation involves a charged residue. Otherwise problems with accuracy of results encountered in mutation of charged residues can be overcome by performing the mutation on the ligand in the binding site and bulk simultaneously and in the same system. The proposed method will be useful in improving the affinity and selectivity profiles of drug leads and enzymes via computational design and protein engineering.

Prediction of Alkanolamine pKa Values by Combined Molecular Dynamics Free Energy Simulations and ab initio Calculations

2019 ◽  
Author(s):  
Javad Noroozi ◽  
William Smith
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Ab Initio Calculations ◽  
Gas Phase ◽  
Quantum Chemical ◽  
Phase Reaction ◽  
Pka Values ◽  
Gas Phase Reaction ◽  
Reaction Free Energy ◽  
Energy Simulations

We use molecular dynamics free energy simulations in conjunction with quantum chemical calculations of gas phase reaction free energy to predict alkanolamines pka values. <br>

SAMPL6 Octanol-Water Partition Coefficients from Alchemical Free Energy Calculations with MBIS Atomic Charges

2019 ◽  
Author(s):  
Maximiliano Riquelme ◽  
Esteban Vöhringer-Martinez
Keyword(s):  
Free Energy ◽  
Electron Density ◽  
Free Energy Calculations ◽  
Basis Set ◽  
Energetic Cost ◽  
Atomic Charges ◽  
Free Energies ◽  
Energy Calculations ◽  
Alchemical Free Energy ◽  
Alchemical Free Energy Calculations

In molecular modeling the description of the interactions between molecules forms the basis for a correct prediction of macroscopic observables. Here, we derive atomic charges from the implicitly polarized electron density of eleven molecules in the SAMPL6 challenge using the Hirshfeld-I and Minimal Basis Set Iterative Stockholder(MBIS) partitioning method. These atomic charges combined with other parameters in the GAFF force field and different water/octanol models were then used in alchemical free energy calculations to obtain hydration and solvation free energies, which after correction for the polarization cost, result in the blind prediction of the partition coefficient. From the tested partitioning methods and water models the S-MBIS atomic charges with the TIP3P water model presented the smallest deviation from the experiment. Conformational dependence of the free energies and the energetic cost associated with the polarization of the electron density are discussed.

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