A Constant-pH Hybrid Monte Carlo Method with a Configuration-Selection Scheme Using the Zero Energy Difference Condition: Elucidation of Molecular Diffusivity Correlated with a pH-Dependent Solvation Shell

2021 ◽  
Vol 17 (2) ◽  
pp. 1030-1044
Author(s):  
Yukichi Kitamura ◽  
Masataka Nagaoka
Keyword(s):  
Monte Carlo ◽  
Energy Difference ◽  
Solvation Shell ◽  
Zero Energy ◽  
Selection Scheme ◽  
Hybrid Monte Carlo ◽  
Molecular Diffusivity ◽  
Constant Ph ◽  
Configuration Selection ◽  
Ph Dependent

scholarly journals Computational Prediction of Heteromeric Protein Complex Disassembly Order with Hybrid Monte Carlo/Molecular Dynamics Simulation

2022 ◽  
Author(s):  
Ikuo Kurisaki ◽  
Shigenori Tanaka
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Protein Complex ◽  
Protein Complexes ◽  
Structural Bioinformatics ◽  
Dynamics Simulation ◽  
Tryptophan Synthase ◽  
Selection Scheme ◽  
Hybrid Monte Carlo ◽  
Multimeric Protein

The physicochemical entity of biological phenomenon in the cell is a network of biochemical reactions and the activity of such a network is regulated by multimeric protein complexes. Mass spectroscopy (MS) experiments and multimeric protein docking simulations based on structural bioinformatics techniques have revealed the molecular-level stoichiometry and static configuration of subcomplexes in their bound forms, then revealing the subcomplex populations and formation orders. Meanwhile, these methodologies are not designed to straightforwardly examine temporal dynamics of multimeric protein assembly and disassembly, essential physicochemical properties to understand functional expression mechanisms of proteins in the biological environment. To address the problem, we had developed an atomistic simulation in the framework of the hybrid Monte Carlo/Molecular Dynamics (hMC/MD) method and succeeded in observing disassembly of homomeric pentamer of the serum amyloid P component protein in experimentally consistent order. In this study, we improved the hMC/MD method to examine disassembly processes of the tryptophan synthase tetramer, a paradigmatic heteromeric protein complex in MS studies. We employed the likelihood-based selection scheme to determine a dissociation-prone subunit pair at each hMC/MD simulation cycle and achieved highly reliable predictions of the disassembly orders with the success rate over 0.9 without a priori knowledge of the MS experiments and structural bioinformatics simulations. We similarly succeeded in reliable predictions for the other three tetrameric protein complexes. These achievements indicate the potential availability of our hMC/MD approach as the general purpose methodology to obtain microscopic and physicochemical insights into multimeric protein complex formation.

scholarly journals Anti-TNF Alpha Antibody Humira with pH-dependent Binding Characteristics: A constant-pH Molecular Dynamics, Gaussian Accelerated Molecular Dynamics, and In Vitro Study

Biomolecules ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 334
Author(s):  
Shih-Ting Hong ◽  
Yu-Cheng Su ◽  
Yu-Jen Wang ◽  
Tian-Lu Cheng ◽  
Yeng-Tseng Wang
Keyword(s):  
Molecular Dynamics ◽  
Tnf Alpha ◽  
Complex Structures ◽  
Binding Characteristics ◽  
Accelerated Molecular Dynamics ◽  
Constant Ph ◽  
Ph Dependent ◽  
Constant Ph Molecular Dynamics ◽  
Antibody Drug

Humira is a monoclonal antibody that binds to TNF alpha, inactivates TNF alpha receptors, and inhibits inflammation. Neonatal Fc receptors can mediate the transcytosis of Humira–TNF alpha complex structures and process them toward degradation pathways, which reduces the therapeutic effect of Humira. Allowing the Humira–TNF alpha complex structures to dissociate to Humira and soluble TNF alpha in the early endosome to enable Humira recycling is crucial. We used the cytoplasmic pH (7.4), the early endosomal pH (6.0), and pKa of histidine side chains (6.0–6.4) to mutate the residues of complementarity-determining regions with histidine. Our engineered Humira (W1-Humira) can bind to TNF alpha in plasma at neutral pH and dissociate from the TNF alpha in the endosome at acidic pH. We used the constant-pH molecular dynamics, Gaussian accelerated molecular dynamics, two-dimensional potential mean force profiles, and in vitro methods to investigate the characteristics of W1-Humira. Our results revealed that the proposed Humira can bind TNF alpha with pH-dependent affinity in vitro. The W1-Humira was weaker than wild-type Humira at neutral pH in vitro, and our prediction results were close to the in vitro results. Furthermore, our approach displayed a high accuracy in antibody pH-dependent binding characteristics prediction, which may facilitate antibody drug design. Advancements in computational methods and computing power may further aid in addressing the challenges in antibody drug design.

scholarly journals The Ising model with Hybrid Monte Carlo

2021 ◽  
Vol 265 ◽  
pp. 107978
Author(s):  
Johann Ostmeyer ◽  
Evan Berkowitz ◽  
Thomas Luu ◽  
Marcus Petschlies ◽  
Ferenc Pittler
Keyword(s):  
Monte Carlo ◽  
Ising Model ◽  
Hybrid Monte Carlo

scholarly journals Testing a Fourier-accelerated hybrid Monte Carlo algorithm

2002 ◽  
Vol 528 (3-4) ◽  
pp. 301-305 ◽  
Author(s):  
Simon Catterall ◽  
Sergey Karamov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Algorithm ◽  
Hybrid Monte Carlo

scholarly journals COMPARISON OF UPDATE ALGORITHMS FOR PURE GAUGE SU(3)

1988 ◽  
Vol 03 (14) ◽  
pp. 1367-1378 ◽  
Author(s):  
RAJAN GUPTA ◽  
GREGORY W. KILCUP ◽  
APOORVA PATEL ◽  
STEPHEN R. SHARPE ◽  
PHILIPPE DE FORCRAND
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Algorithm ◽  
Hybrid Monte Carlo ◽  
Pure Gauge

We show that the overrelaxed algorithm of Creutz and of Brown and Woch is the optimal local update algorithm for simulation of pure gauge SU(3). Our comparison criterion includes computer efficiency and decorrelation times. We also investigate the rate of decorrelation for the Hybrid Monte Carlo algorithm.

Reduction of Computing Time and Improvement of Convergence Stability of the Monte Carlo Method Applied to Radiative Heat Transfer With Variable Properties

1989 ◽  
Vol 111 (1) ◽  
pp. 135-140 ◽  
Author(s):  
M. Kobiyama
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Computing Time ◽  
Energy Difference ◽  
Radiative Properties ◽  
Radiative Energy ◽  
Control Element ◽  
The Monte Carlo Method ◽  
The Difference ◽  
Convergence Stability

A modified Monte Carlo method is suggested to reduce the computing time and improve the convergence stability of iterative calculations without losing other excellent features of the conventional Monte Carlo method. In this method, two kinds of radiative bundle are used: energy correcting bundles and property correcting bundles. The energy correcting bundles are used for correcting the radiative energy difference between two successive iterative cycles, and the property correcting bundles are used for correcting the radiative properties. The number of radiative energy bundles emitted from each control element is proportional to the difference in emissive energy between two successive iterative cycles.

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