Sampling of slow diffusive conformational transitions with accelerated molecular dynamics

Hamelberg, Donald; Oliveira, César Augusto F. de; McCammon, J. Andrew

doi:10.1063/1.2789432

Cited by 228 publications

(300 citation statements)

References 30 publications

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“…be enhanced by either increasing the boost energy or decreasing α. In the present work, we have implemented a "dual boost" AMD approach (29), in which two acceleration potentials are applied simultaneously to the system: The first acceleration potential is applied to the torsional terms only, and a second, weaker acceleration is applied across the entire potential. For each of the three systems, thrombin, thrombin:TM56, and thrombin:TM456 dualboost AMD simulations were performed at two (torsional) acceleration levels.…”

Section: Methodsmentioning

confidence: 99%

Allosteric networks in thrombin distinguish procoagulant vs. anticoagulant activities

Gasper¹,

Fuglestad²,

Komives³

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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141

169

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The serine protease α-thrombin is a dual-action protein that mediates the blood-clotting cascade. Thrombin alone is a procoagulant, cleaving fibrinogen to make the fibrin clot, but the thrombinthrombomodulin (TM) complex initiates the anticoagulant pathway by cleaving protein C. A TM fragment consisting of only the fifth and sixth EGF-like domains (TM56) is sufficient to bind thrombin, but the presence of the fourth EGF-like domain (TM456) is critical to induce the anticoagulant activity of thrombin. Crystallography of the thrombin-TM456 complex revealed no significant structural changes in thrombin, suggesting that TM4 may only provide a scaffold for optimal alignment of protein C for its cleavage by thrombin. However, a variety of experimental data have suggested that the presence of TM4 may affect the dynamic properties of the active site loops. In the present work, we have used both conventional and accelerated molecular dynamics simulation to study the structural dynamic properties of thrombin, thrombin: TM56, and thrombin:TM456 across a broad range of time scales.Two distinct yet interrelated allosteric pathways are identified that mediate both the pro-and anticoagulant activities of thrombin. One allosteric pathway, which is present in both thrombin: TM56 and thrombin:TM456, directly links the TM5 domain to the thrombin active site. The other allosteric pathway, which is only present on slow time scales in the presence of the TM4 domain, involves an extended network of correlated motions linking the TM4 and TM5 domains and the active site loops of thrombin.allostery | thrombosis

show abstract

Section: Methodsmentioning

confidence: 99%

Allosteric networks in thrombin distinguish procoagulant vs. anticoagulant activities

Gasper¹,

Fuglestad²,

Komives³

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

141

169

View full text Add to dashboard Cite

show abstract

“…25,[27][28][29][30][31][32][33][34][35][36] The end-to-end contact formation dynamics of the penta-peptide Cys-Ala-Gly-Gln-Trp (CAGQW) has been experimentally studied with triplet quenching. 22 The time scale of the end-to-end contact formation of this peptide was determined to be on the order of 100 ns, a time-scale which is accessible in atomically detailed MD simulations.…”

Section: Introductionmentioning

confidence: 99%

Structure and Dynamics of End-to-End Loop Formation of the Penta-Peptide Cys-Ala-Gly-Gln-Trp in Implicit Solvents

Yeh

Wallqvist

2009

J. Phys. Chem. B

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To investigate the effects of implicit solvents on peptide structure and dynamics, we performed extensive molecular dynamics simulations on the penta-peptide Cys-Ala-Gly-Gln-Trp. Two different implicit solvent models based on the CHARMM22 all-atom force field were used. Structural properties of the peptide such as distributions of end-to-end distances and dihedral angles obtained from molecular dynamics simulations with implicit solvent models were in a good agreement with those obtained from a previous explicit solvent simulation using the same force field. Representative structures observed in explicit solvent were sampled by implicit solvent models but with different relative probabilities. However, we observed significant differences in dynamical properties in explicit and implicit solvent models when we used traditional methods for the temperature control, such as Nosé-Hoover or Berendsen thermostats. The explicitly solvated peptide displayed the slowest dynamics in both end-to-end contact formation and intrinsic diffusive motion of end-to-end distances. A closer agreement between implicit and explicit solvated peptide dynamics was observed when Langevin dynamics with a friction coefficient of 10 ps -1 was used to maintain the temperature of the systems.

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“…A boost energy, E, of 2,000 kcal/mol was added to the average dihedral energy, and a tuning parameter, ␣, of 200 kcal/ mol was used. The dual boost was also applied to accelerate the diffusive and solvent dynamics as previously described (39). The simulation conditions were similar to that of the normal MD simulations above.…”

mentioning

confidence: 99%

Identification of an l-Phenylalanine Binding Site Enhancing the Cooperative Responses of the Calcium-sensing Receptor to Calcium

Zhang

Huang

Jiang

et al. 2014

Journal of Biological Chemistry

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Sampling of slow diffusive conformational transitions with accelerated molecular dynamics

Cited by 228 publications

References 30 publications

Allosteric networks in thrombin distinguish procoagulant vs. anticoagulant activities

Allosteric networks in thrombin distinguish procoagulant vs. anticoagulant activities

Structure and Dynamics of End-to-End Loop Formation of the Penta-Peptide Cys-Ala-Gly-Gln-Trp in Implicit Solvents

Identification of an l-Phenylalanine Binding Site Enhancing the Cooperative Responses of the Calcium-sensing Receptor to Calcium

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