scholarly journals Combining Monte Carlo and Molecular Dynamics Simulations for Enhanced Binding Free Energy Estimation through Markov State Models

2020 ◽  
Vol 60 (11) ◽  
pp. 5529-5539 ◽  
Author(s):  
Joan F. Gilabert ◽  
Oriol Gracia Carmona ◽  
Anders Hogner ◽  
Victor Guallar
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Free Energy ◽  
Molecular Dynamics Simulations ◽  
Binding Free Energy ◽  
Energy Estimation ◽  
Markov State ◽  
Markov State Models ◽  
State Models ◽  
Dynamics Simulations

scholarly journals The mechanism of RNA base fraying: Molecular dynamics simulations analyzed with core-set Markov state models

2019 ◽  
Vol 150 (15) ◽  
pp. 154123 ◽  
Author(s):  
Giovanni Pinamonti ◽  
Fabian Paul ◽  
Frank Noé ◽  
Alex Rodriguez ◽  
Giovanni Bussi
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Markov State ◽  
Markov State Models ◽  
Core Set ◽  
State Models ◽  
Dynamics Simulations

scholarly journals Markov State Models and Molecular Dynamics Simulations Provide Understanding of the Nucleotide-Dependent Dimerization-Based Activation of LRRK2 ROC Domain

Molecules ◽  
2021 ◽  
Vol 26 (18) ◽  
pp. 5647
Author(s):  
Xinyi Li ◽  
Zengxin Qi ◽  
Duan Ni ◽  
Shaoyong Lu ◽  
Liang Chen ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Structural Rearrangement ◽  
Catalytic Triad ◽  
Gtpase Domain ◽  
Markov State ◽  
Markov State Models ◽  
Activated State ◽  
State Models ◽  
Dynamics Simulations

Mutations in leucine-rich repeat kinase 2 (LRRK2) are recognized as the most frequent cause of Parkinson’s disease (PD). As a multidomain ROCO protein, LRRK2 is characterized by the presence of both a Ras-of-complex (ROC) GTPase domain and a kinase domain connected through the C-terminal of an ROC domain (COR). The bienzymatic ROC–COR–kinase catalytic triad indicated the potential role of GTPase domain in regulating kinase activity. However, as a functional GTPase, the detailed intrinsic regulation of the ROC activation cycle remains poorly understood. Here, combining extensive molecular dynamics simulations and Markov state models, we disclosed the dynamic structural rearrangement of ROC’s homodimer during nucleotide turnover. Our study revealed the coupling between dimerization extent and nucleotide-binding state, indicating a nucleotide-dependent dimerization-based activation scheme adopted by ROC GTPase. Furthermore, inspired by the well-known R1441C/G/H PD-relevant mutations within the ROC domain, we illuminated the potential allosteric molecular mechanism for its pathogenetic effects through enabling faster interconversion between inactive and active states, thus trapping ROC in a prolonged activated state, while the implicated allostery could provide further guidance for identification of regulatory allosteric pockets on the ROC complex. Our investigations illuminated the thermodynamics and kinetics of ROC homodimer during nucleotide-dependent activation for the first time and provided guidance for further exploiting ROC as therapeutic targets for controlling LRRK2 functionality in PD treatment.

scholarly journals Cover Feature: Ligand Binding Rate Constants in Heme Proteins Using Markov State Models and Molecular Dynamics Simulations (ChemPhysChem 19/2019)

ChemPhysChem ◽  
2019 ◽  
Vol 20 (19) ◽  
pp. 2401-2401
Author(s):  
Mauro Bringas ◽  
Leandro E. Lombardi ◽  
F. Javier Luque ◽  
Darío A. Estrin ◽  
Luciana Capece
Keyword(s):  
Molecular Dynamics ◽  
Ligand Binding ◽  
Molecular Dynamics Simulations ◽  
Rate Constants ◽  
Heme Proteins ◽  
Markov State ◽  
Markov State Models ◽  
Binding Rate ◽  
State Models ◽  
Dynamics Simulations

scholarly journals Ligand Binding Rate Constants in Heme Proteins Using Markov State Models and Molecular Dynamics Simulations

ChemPhysChem ◽  
2019 ◽  
Vol 20 (19) ◽  
pp. 2451-2460
Author(s):  
Mauro Bringas ◽  
Leandro E. Lombardi ◽  
F. Javier Luque ◽  
Darío A. Estrin ◽  
Luciana Capece
Keyword(s):  
Molecular Dynamics ◽  
Ligand Binding ◽  
Molecular Dynamics Simulations ◽  
Rate Constants ◽  
Heme Proteins ◽  
Markov State ◽  
Markov State Models ◽  
Binding Rate ◽  
State Models ◽  
Dynamics Simulations
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