Collective Variable Approaches for Single Molecule Flexible Fitting and Enhanced Sampling

Vashisth, Harish; Skiniotis, Georgios; Brooks, Charles L.

doi:10.1021/cr4005988

Cited by 25 publications

(25 citation statements)

References 181 publications

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“…We have previously shown that molecular dynamics (MD) simulations conducted in explicit solvent with all-atom structural models and enhanced sampling algorithms ( 53 ) are highly promising tools to understand conformational flexibility of receptor structures and their ligand-binding mechanisms ( 8 , 54 – 58 ). In this work, we aim to study the structure, orientation, and conformational variability of TMDs of IR and IGF1R in an explicit lipid bilayer environment.…”

Section: Introductionmentioning

confidence: 99%

All-Atom Structural Models of the Transmembrane Domains of Insulin and Type 1 Insulin-Like Growth Factor Receptors

Mohammadiarani

Vashisth

2016

Front. Endocrinol.

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The receptor tyrosine kinase superfamily comprises many cell-surface receptors including the insulin receptor (IR) and type 1 insulin-like growth factor receptor (IGF1R) that are constitutively homodimeric transmembrane glycoproteins. Therefore, these receptors require ligand-triggered domain rearrangements rather than receptor dimerization for activation. Specifically, binding of peptide ligands to receptor ectodomains transduces signals across the transmembrane domains for trans-autophosphorylation in cytoplasmic kinase domains. The molecular details of these processes are poorly understood in part due to the absence of structures of full-length receptors. Using MD simulations and enhanced conformational sampling algorithms, we present all-atom structural models of peptides containing 51 residues from the transmembrane and juxtamembrane regions of IR and IGF1R. In our models, the transmembrane regions of both receptors adopt helical conformations with kinks at Pro961 (IR) and Pro941 (IGF1R), but the C-terminal residues corresponding to the juxtamembrane region of each receptor adopt unfolded and flexible conformations in IR as opposed to a helix in IGF1R. We also observe that the N-terminal residues in IR form a kinked-helix sitting at the membrane–solvent interface, while homologous residues in IGF1R are unfolded and flexible. These conformational differences result in a larger tilt-angle of the membrane-embedded helix in IGF1R in comparison to IR to compensate for interactions with water molecules at the membrane–solvent interfaces. Our metastable/stable states for the transmembrane domain of IR, observed in a lipid bilayer, are consistent with a known NMR structure of this domain determined in detergent micelles, and similar states in IGF1R are consistent with a previously reported model of the dimerized transmembrane domains of IGF1R. Our all-atom structural models suggest potentially unique structural organization of kinase domains in each receptor.

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Section: Introductionmentioning

confidence: 99%

All-Atom Structural Models of the Transmembrane Domains of Insulin and Type 1 Insulin-Like Growth Factor Receptors

Mohammadiarani

Vashisth

2016

Front. Endocrinol.

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“…Herein the values of the correction forces can be solved using the low-level and high-level atomic forces through Eqs. (5) and (7). Similarly, the internal force corrections at time t + ∆t can be derived from Eq.…”

Section: Theoretical Foundationmentioning

confidence: 99%

“…The free energy change along the reaction coordinate (RC), or the potential of mean force (PMF), is a central quantity for describing the pathways and barriers of a chemical reaction. [1][2][3][4][5] Based on chemical intuition, one or a set of collective variables of the molecular structure is often defined as RC to capture the major geometric change in a chemical process. The PMF can be calculated from molecular dynamics (MD) simulations.…”

Section: Introductionmentioning

confidence: 99%

Internal force corrections with machine learning for quantum mechanics/molecular mechanics simulations

Shen

Yang

2017

The Journal of Chemical Physics

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Ab initio quantum mechanics/molecular mechanics (QM/MM) molecular dynamics simulation is a useful tool to calculate thermodynamic properties such as potential of mean force for chemical reactions but intensely time consuming. In this paper, we developed a new method using the internal force correction for low-level semiempirical QM/MM molecular dynamics samplings with a predefined reaction coordinate. As a correction term, the internal force was predicted with a machine learning scheme, which provides a sophisticated force field, and added to the atomic forces on the reaction coordinate related atoms at each integration step. We applied this method to two reactions in aqueous solution and reproduced potentials of mean force at the ab initio QM/MM level. The saving in computational cost is about 2 orders of magnitude. The present work reveals great potentials for machine learning in QM/MM simulations to study complex chemical processes.

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“…In the following, we briefly describe two such techniques, temperature-accelerated molecular dynamics (TAMD) and the string method in collective variables (CVs), which have been jointly used to study conformational changes in the C-terminus of the insulin B chain and in the activation loop of the IR kinase domain [ 191 , 192 ]. For more details on enhanced sampling techniques, we refer interested readers to recent reviews [ 193 , 194 ].…”

Section: Modeling and Simulation Techniquesmentioning

confidence: 99%

Theoretical and Computational Studies of Peptides and Receptors of the Insulin Family

Vashisth

2015

Membranes

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Synergistic interactions among peptides and receptors of the insulin family are required for glucose homeostasis, normal cellular growth and development, proliferation, differentiation and other metabolic processes. The peptides of the insulin family are disulfide-linked single or dual-chain proteins, while receptors are ligand-activated transmembrane glycoproteins of the receptor tyrosine kinase (RTK) superfamily. Binding of ligands to the extracellular domains of receptors is known to initiate signaling via activation of intracellular kinase domains. While the structure of insulin has been known since 1969, recent decades have seen remarkable progress on the structural biology of apo and liganded receptor fragments. Here, we review how this useful structural information (on ligands and receptors) has enabled large-scale atomically-resolved simulations to elucidate the conformational dynamics of these biomolecules. Particularly, applications of molecular dynamics (MD) and Monte Carlo (MC) simulation methods are discussed in various contexts, including studies of isolated ligands, apo-receptors, ligand/receptor complexes and intracellular kinase domains. The review concludes with a brief overview and future outlook for modeling and computational studies in this family of proteins.

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Collective Variable Approaches for Single Molecule Flexible Fitting and Enhanced Sampling

Cited by 25 publications

References 181 publications

All-Atom Structural Models of the Transmembrane Domains of Insulin and Type 1 Insulin-Like Growth Factor Receptors

All-Atom Structural Models of the Transmembrane Domains of Insulin and Type 1 Insulin-Like Growth Factor Receptors

Internal force corrections with machine learning for quantum mechanics/molecular mechanics simulations

Theoretical and Computational Studies of Peptides and Receptors of the Insulin Family

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