MSMBuilder: Statistical Models for Biomolecular Dynamics

Harrigan, Matthew P.; Sultan, Mohammad M.; Hernández, Carlos X.; Husic, Brooke E.; Eastman, Peter; Schwantes, Christian R.; Beauchamp, Kyle A.; McGibbon, Robert T.; Pande, Vijay S.

doi:10.1016/j.bpj.2016.10.042

Cited by 260 publications

(297 citation statements)

References 31 publications

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“…tICA, clustering, and MSM construction were implemented using MSMBuilder 3.4 python package. 50 The iteration processes to estimate GMRQ scores for MSMs were performed using Osprey, which is a tool for hyperparameter optimization of machine learning algorithms. 51 The graphs were plotted using the Matplotlib 3.1.1 python package.…”

Section: Msm Construction and Hyperparameter Selectionmentioning

confidence: 99%

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Molecular Mechanism of Brassinosteroids Perception by the Plant Growth Receptor BRI1

Aldukhi

Deb

Zhao

et al. 2019

Preprint

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Brassinosteroids (BRs) are essential phytohormones which bind to the plant receptor, BRI1, to regulate various physiological processes. The molecular mechanism of the perception of BRs by the ectodomain of BRI1 remains not fully understood. It also remains elusive why a substantial difference in biological activity exists between the BRs. In this work, we study the binding mechanisms of the two most bioactive BRs, brassinolide (BLD) and castasterone (CAT) using molecular dynamics simulations. We report free energy landscapes of the binding processes of both ligands as well as detailed ligand binding pathways. Our results suggest that CAT has lower binding affinity compared to BLD due to its inability to form hydrogen bonding interactions with a tyrosine residue in the island domain of BRI1. We uncover a conserved non-productive binding state for both BLD and CAT, which is more stable for CAT and may further contribute to the bioactivity difference. Finally, we validate past observations about the conformational restructuring and ordering of the island domain upon BLD binding. Overall, this study provides new insights into the fundamental mechanism of the perception of two most bioactive BRs, which may create new avenues for genetic and agrochemical control of their signaling cascade.

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Section: Msm Construction and Hyperparameter Selectionmentioning

confidence: 99%

“…The transition pathways were estimated using the MSMBuilder 3.4 python package. 50 Root mean square fluctuation analysis of the island domain…”

Section: Transition Path Theory Analysis Of Ligand Binding Processesmentioning

confidence: 99%

Molecular Mechanism of Brassinosteroids Perception by the Plant Growth Receptor BRI1

Aldukhi

Deb

Zhao

et al. 2019

Preprint

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“…To find the desired TICs, we have followed the procedure described in references 9,14 with the following steps: (1) We have run 200 unbiased (100 ns each) MD simulations starting from the conformations obtained after the clustering of 303 K REMD data, (2) then, five dimensional time series data of five traditional and frequently used CVs, namely, Rg of all backbone heavy atoms, RMSD of all backbone heavy atoms with respect to the crystal structure, fraction of native contacts (NC), the number of backbone-backbone hydrogen bonds(NHB), and the number of water molecules around 5 Angstrom of peptide (NW) were used as input to build the TICA model (which is a linear combination of the input CVs) with a lag time of 1 ns using MSMBuilder3 package 42 . The steps to build TICA models are:…”

Section: B Time-structured Independent Component Analysismentioning

confidence: 99%

Assessment and Optimization of Collective Variables for Protein Conformational Landscape: GB1 β-hairpin as a Case Study

Ahalawat

Mondal

2018

Preprint

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Collective variables (CV), when chosen judiciously, can play an important role in recognizing rate-limiting processes and rare events in any biomolecular systems. However, high dimensionality and inherent complexities associated with such biochemical systems render the identification of an optimal CV a challenging task, which in turn precludes the elucidation of underlying conformational landscape in su cient details. In this context, a relevant model system is presented by 16-residue -hairpin of GB1 protein. Despite being the target of numerous theoretical and computational studies for understanding the protein folding, the set of CVs optimally characterizing the conformational landscape of -hairpin of GB1 protein has remained elusive, resulting in a lack of consensus on its folding mechanism. Here we address this by proposing a pair of optimal CVs which can resolve the underlying free energy landscape of GB1 hairpin quite e ciently. Expressed as a linear combination of a number of traditional CVs, the optimal CV for this system is derived by employing recently introduced Time-structured Independent Component Analysis (TICA) approach on a large number of independent unbiased simulations. By projecting the replica-exchange simulated trajectories along these pair of optimized CVs, the resulting free energy landscape of this system are able to resolve four distinct well-separated metastable states encompassing the extensive ensembles of folded,unfolded and molten globule states. Importantly, the optimized CVs were found to be capable of automatically recovering a novel partial helical state of this protein, without needing to explicitly invoke helicity as a constituent CV. Furthermore, a quantitative sensitivity analysis of each constituent in the optimized CV provided key insights on the relative contributions of the constituent CVs in the overall free energy landscapes. Finally, the kinetic pathways connecting these metastable states, constructed using a Markov State Model, provide an optimum description of underlying folding mechanism of the peptide. Taken together, this work o↵ers a quantitatively robust approach towards comprehensive mapping of the underlying folding landscape of a quintessential model system along its optimized collective variables.

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“…MSM analysis was accomplished using MSMBuilder 3.7 [103]. The MD datasets were featurized using the signed φ, ψ, χ 1 , and χ 2 dihedral angles for all residues in the CLC-2 SF.…”

Section: Markov State Modelingmentioning

confidence: 99%

Dynamical model of the CLC-2 ion channel exhibits a two-step gating mechanism

McKiernan

Koster

Maduke

et al. 2017

Preprint

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AbstractThis work reports a dynamical Markov state model of CLC-2 “fast” (pore) gating, based on 600 microseconds of molecular dynamics (MD) simulation. In the starting conformation of our CLC-2 model, both outer and inner channel gates are closed. The first conformational change in our dataset involves rotation of the inner-gate backbone along residues S168-G169-I170. This change is strikingly similar to that observed in the cryo-EM structure of the bovine CLC-K channel, though the volume of the intracellular (inner) region of the ion conduction pathway is further expanded in our model. From this state (inner gate open and outer gate closed), two additional states are observed, each involving a unique rotameric flip of the outer-gate residue GLUex. Both additional states involve conformational changes that orient GLUex away from the extracellular (outer) region of the ion conduction pathway. In the first additional state, the rotameric flip of GLUex results in an open, or near-open, channel pore. The equilibrium population of this state is low (∼1%), consistent with the low open probability of CLC-2 observed experimentally in the absence of a membrane potential stimulus (0 mV). In the second additional state, GLUex rotates to occlude the channel pore. This state, which has a low equilibrium population (∼1%), is only accessible when GLUex is protonated. Together, these pathways model the opening of both an inner and outer gate within the CLC-2 selectivity filter, as a function of GLUex protonation. Collectively, our findings are consistent with published experimental analyses of CLC-2 gating and provide a high-resolution structural model to guide future investigations.Author summaryIn the brain, the roles and mechanisms of sodium-, potassium-, and calcium-selective ion channels are well established. In contrast, chloride-selective channels have been studied much less and are not sufficiently understood, despite known associations of chloride-channel defects with brain disorders. The most broadly expressed voltage-activated chloride channel in the brain is CLC-2 (one of 9 human CLC homologs). In this work, we use simulations to model the conformational dynamics of the CLC-2 chloride ion channel selectivity filter (SF), which is the part of the protein that controls whether the channel is in an ion-conducting or non-conducting state. Our analysis identifies four primary conformational states and a specific progression through these states. Our results are consistent with structural and functional data in the literature and provide a high-resolution model for guiding further studies of CLC-2. These results will inform our understanding of how CLC-2 governs electrical activity and ion homeostasis in the brain.

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MSMBuilder: Statistical Models for Biomolecular Dynamics

Cited by 260 publications

References 31 publications

Molecular Mechanism of Brassinosteroids Perception by the Plant Growth Receptor BRI1

Molecular Mechanism of Brassinosteroids Perception by the Plant Growth Receptor BRI1

Assessment and Optimization of Collective Variables for Protein Conformational Landscape: GB1 β-hairpin as a Case Study

Dynamical model of the CLC-2 ion channel exhibits a two-step gating mechanism

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