Response of Small-Scale, Methyl Rotors to Protein−Ligand Association: A Simulation Analysis of Calmodulin−Peptide Binding

Changes in the free energy barrier (ΔE), entropy, and motional parameters associated with the rotation of methyl groups in a protein (calmodulin (CaM)) on binding a ligand (the calmodulin-binding domain of smooth-muscle myosin (smMLCKp)) are investigated using molecular dynamics simulation. In both the bound and uncomplexed forms of CaM, the methyl rotational free energy barriers follow skewed-Gaussian distributions that are not altered significantly upon ligand binding. However, site-specific perturbations are found. Around 11% of the methyl groups in CaM exhibit changes in ΔE greater than 0.7 kcal/mol on binding. The rotational entropies of the methyl groups exhibit a nonlinear dependence on ΔE. The relations are examined between motional parameters (the methyl rotational NMR order parameter and the relaxation time) and ΔE. Low-barrier methyl group rotational order parameters deviate from ideal tetrahedrality by up to ∼20%. There is a correlation between rotational barrier changes and proximity to the protein-peptide binding interface. Methyl groups that exhibit large changes in ΔE are found to report on elements in the protein undergoing structural change on binding

REACH: A program for coarse-grained biomolecular simulation

Abstract REACH (Realistic Extension Algorithm via Covariance Hessian) is a program package for residue-scale coarse-grained biomolecular simulation. The program calculates the force constants of a residue-scale elastic network model in single-domain proteins using the variance–covariance matrix obtained from atomistic molecular dynamics simulation. Secondary-structure dependence of the force constants is integrated. The method involves self-consistent, direct mapping of atomistic simulation results o... Title of program: REACH Catalogue Id: AEDA_v1_0 Nature of problem A direct calculation of force field for residue-scale coarse-grained biomolecular simulation derived from atomistic molecular dynamics trajectory. Versions of this program held in the CPC repository in Mendeley Data AEDA_v1_0; REACH; 10.1016/j.cpc.2009.01.007 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019

SERENA: a program for calculating X-ray diffuse scattering intensities from molecular dynamics trajectories

Abstract Displacements of atoms from their ideal periodic positions in molecular crystals lead to X-ray diffuse scattering. The program SERENA calculates the diffuse scattering from a collection of atomic configurations. This enables diffuse scattering to be calculated from a molecular dynamics simulation and directly compared with experiment. Title of program: SERENA, Version 1.0 Catalogue Id: ADBQ_v1_0 Nature of problem X-ray diffuse scattering intensities from computer simulations. Versions of this program held in the CPC repository in Mendeley Data ADBQ_v1_0; SERENA, Version 1.0; 10.1016/0010-4655(95)00057-M This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019

Low-Temperature Protein Dynamics: A Simulation Analysis of Interprotein Vibrations and the Boson Peak at 150 K

An understanding of low-frequency, collective protein dynamics at low temperatures can furnish valuable information on functional protein energy landscapes, on the origins of the protein glass transition and on protein−protein interactions. Here, molecular dynamics (MD) simulations and normal-mode analyses are performed on various models of crystalline myoglobin in order to characterize intra- and interprotein vibrations at 150 K. Principal component analysis of the MD trajectories indicates that the Boson peak, a broad peak in the dynamic structure factor centered at about ∼2−2.5 meV, originates from ∼102 collective, harmonic vibrations. An accurate description of the environment is found to be essential in reproducing the experimental Boson peak form and position. At lower energies other strong peaks are found in the calculated dynamic structure factor. Characterization of these peaks shows that they arise from harmonic vibrations of proteins relative to each other. These vibrations are likely to furnish valuable information on the physical nature of protein−protein interactions

Reconstruction of Protein Side-Chain Conformational Free Energy Surfaces From NMR-Derived Methyl Axis Order Parameters

An analytical approach is developed for reconstructing site-specific methyl-bearing protein side-chain conformational energy surfaces from NMR methyl axis order parameters (<i>O</i>_axis²). Application of an enhanced sampling algorithm (adaptive biasing force) to molecular dynamics simulation of a protein, calcium-bound calmodulin, reveals a nonlinear correlation between <i>O</i>_axis² and the populations of rotamer states of protein side-chains, permitting the rotamer populations to be extracted directly from <i>O</i>_axis². The analytical approach yields side-chain conformational distributions that are in excellent agreement with those obtained from the enhanced-sampling MD results

Capturing Deuteration Effects in a Molecular Mechanics Force Field: Deuterated THF and the THF–Water Miscibility Gap

Deuteration is a common chemical modification used in conjunction with experiments such as neutron scattering, NMR, and Fourier-transform infrared for the study of molecular systems. Under the Born–Oppenheimer (BO) approximation, while the underlying potential energy surface remains unchanged by isotopic substitutions, isotopic substitution still alters intramolecular vibrations, which in turn may alter intermolecular interactions. Molecular mechanics (MM) force fields used in classical molecular dynamics simulations are assumed to represent local approximations of the BO potential energy surfaces, and hence, MD simulations using simple isotopic mass substitutions should capture BO-compatible isotope effects. However, standard MM force-field parameterizations do not directly fit to the local harmonic quantum mechanical (QM) Hessian that describes the BO surface, but rather to QM normal-modes and/or mass-dependent internal-coordinate derived distortion energies. Here, using tetrahydrofuran (THF)–water mixtures as our model system, we show that not only does a simple mass-substitution approach fail to capture an experimentally characterized deuteration effect (the loss of the closed-loop miscibility gap associated with the complete deuteration of THF) but also it is necessary to generate new MM force-field parameters that correctly describe isotopic dependent vibrations to capture the experimental deuteration effect. We show that the origin of this failure is a result of using mass-dependent features to fit the THF MM force field, which unintentionally biases the bonded terms of the force field to represent only the isotopologue used during the original force-field parameterization. In addition, we make use of our isotopologue-corrected force field for D8THF to examine the molecular origins of the isotope-dependent loss of the THF–water miscibility gap

Setup for enzyme reaction in CelS with QM/MM method.

<p>QM region (VDW representation) consists of catalytic residues (Asp255 and Glu87), nucleophilic water (W1), and active part of substrate (subsites −1, and +1), while rest of enzyme (green), substrate (orange), and water (cyan) are in MM region. Inset shows only QM region and hydrogen link atoms (pink) used as boundary between MM and QM.</p

Schematic representation of inverting reaction mechanism in CelS for hydrolysis of glycosidic bond C1-O4.

<p>The catalytic residues Glu87, Asp255, and nucleophilic water molecule (W1) are shown. Anomeric carbon atom at subsite −1 and leaving group oxygen atom at subsite +1 are C1 and O4, respectively. The thin arrows represent electron transfer between atoms. Distances between atoms are shown in red.</p

Additional file 2 of HLA-Clus: HLA class I clustering based on 3D structure

Additional file2. Table S1: Example output of the Processing_pipeline function. Table S2: Example output of HC_pipeline function. Table S3: Example of anchor_dictionary parameter for NN_pipeline function. Table S4: Example output of NN_pipeline output

Potential of mean force for hydrolysis reaction.

<p>Potential of mean force for hydrolysis reaction.</p