A molecular simulation protocol to avoid sampling redundancy and discover new states

Bacci, Marco; Vitalis, Andreas; Caflisch, Amedeo

doi:10.1016/j.bbagen.2014.08.013

Cited by 25 publications

(42 citation statements)

References 70 publications

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“…Furthermore, knowledge from additional experimental structures of designed ArmRP, in combination with protocols for enhanced sampling by MD [37], will likely allow a manipulation of curvature accurate enough to obtain modular binding over wide distances.…”

Section: Peptide Binding By Darmrpsmentioning

confidence: 99%

Computationally Designed Armadillo Repeat Proteins for Modular Peptide Recognition

Reichen

Hansen

Forzani

et al. 2016

Journal of Molecular Biology

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Armadillo repeat proteins (ArmRP) recognize their target peptide in extended conformation and bind, in a first approximation, two residues per repeat. They may thus form the basis for building a modular system, in which each repeat is complementary to a piece of the target peptide. Accordingly, preselected repeats could be assembled into specific binding proteins on demand and thereby avoid the traditional generation of every new binding molecule by an independent selection from a library.Stacked armadillo repeats, each consisting of 42 amino acids arranged in three α-helices, build an elongated superhelical structure. Here, we analyzed curvature variations in natural ArmRPs, and identified a repeat pair from yeast importin-α as having the optimal curvature geometry to be complementary to a peptide over its whole length. We employed a symmetric in silico design to obtain a uniform sequence for a stackable repeat while maintaining the desired curvature geometry.Computationally designed armadillo repeat proteins (dArmRPs) had to be stabilized by mutations to remove regions of higher flexibility, which were identified by molecular dynamics (MD) simulations in explicit solvent. Using an N-capping repeat from the consensus-design approach, two different crystal structures of dArmRP were determined. Although the experimental structures of dArmRP deviated from the designed curvature, the insertion of the most conserved binding pockets of natural ArmRPs onto the surface of dArmRPs resulted in binders against the expected peptide with low nanomolar affinities, similar to the binders from the consensus-design series.

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Section: Peptide Binding By Darmrpsmentioning

confidence: 99%

Computationally Designed Armadillo Repeat Proteins for Modular Peptide Recognition

Reichen

Hansen

Forzani

et al. 2016

Journal of Molecular Biology

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“…Reseeding techniques attempt to avoid equilibrium traps in MD simulations by detecting trapped simulations, stopping them, and restarting the dynamics from more promising thermodynamic states. The choice of restart condition in reseeding techniques is carried out by various methods including RMSD (82), principal component analysis (PCA) (83), conformational clustering (84), progress index (85), and free energy (86). …”

Section: Computational Tools For Simulating Drug-protein Binding Kmentioning

confidence: 99%

Understanding ligand-receptor non-covalent binding kinetics using molecular modeling

2017

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Kinetic properties may serve as critical differentiators and predictors of drug efficacy and safety, in addition to the traditionally focused binding affinity. However the quantitative structure-kinetics relationship (QSKR) for modeling and ligand design is still poorly understood. This review provides an introduction to the kinetics of drug binding from a fundamental chemistry perspective. We focus on recent developments of computational tools and their applications to non-covalent binding kinetics.

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“…20–25 Another common strategy is selecting significantly deviated structures from existing MD trajectories to initiate multiple MD simulations. 17,26,27 Enhanced sampling methods that alter the potential energy surface or provide additional forces to speed up conformational sampling include metadynamics, random accelerated MD, and self-guided MD (SGMD). 2,28–37 Other methods use soft potentials to smooth the potential energy surface.…”

Section: Introductionmentioning

confidence: 99%

Systematic Dissociation Pathway Searches Guided by Principal Component Modes

Tang

Chang

2017

J. Chem. Theory Comput.

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We introduce a novel method, Pathway Search guided by Internal Motions (PSIM), that efficiently finds molecular dissociation pathways of a ligand–receptor system with guidance from principal component (PC) modes obtained from molecular dynamics (MD) simulations. Modeling ligand–receptor dissociation pathways can provide insights into molecular recognition and has practical applications, including understanding kinetic mechanisms and barriers to binding/unbinding as well as design of drugs with desired kinetic properties. PSIM uses PC modes in multilayer internal coordinates to identify natural molecular motions that guide the search for conformational switches and unbinding pathways. The new multilayer internal coordinates overcome problems with Cartesian and classical internal coordinates that fail to smoothly present dihedral rotation or generate nonphysical distortions. We used HIV-1 protease, which has large-scale flap motions, as an example protein to demonstrate use of the multilayer internal coordinates. We provide examples of algorithms and implementation of PSIM with alanine dipeptide and chemical host–guest systems, 2-naphthyl ethanol–β-cyclodextrin and tetramethylammonium– cryptophane complexes. Tetramethylammonium–cryptophane has slow binding/unbinding kinetics. Its residence time, the length to dissociate tetramethylammonium from the host, is ~14 s from experiments, and PSIM revealed 4 dissociation pathways in approximately 150 CPU h. We also searched the releasing pathways for the product glyceraldehyde-3-phosphate from tryptophan synthase, and one complete dissociation pathway was constructed after running multiple search iterations in approximately 300 CPU h. With guidance by internal PC modes from MD simulations, the PSIM method has advantages over simulation-based methods to search for dissociation pathways of molecular systems with slow noncovalent kinetic behavior.

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A molecular simulation protocol to avoid sampling redundancy and discover new states

Cited by 25 publications

References 70 publications

Computationally Designed Armadillo Repeat Proteins for Modular Peptide Recognition

Computationally Designed Armadillo Repeat Proteins for Modular Peptide Recognition

Understanding ligand-receptor non-covalent binding kinetics using molecular modeling

Systematic Dissociation Pathway Searches Guided by Principal Component Modes

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