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Predicting Experimental Quantities in Protein Folding Kinetics Using Stochastic Roadmap Simulation [chapter]

Tsung-Han Chiang, Mehmet Serkan Apaydin, Douglas L. Brutlag, David Hsu, Jean-Claude Latombe
2006 Lecture Notes in Computer Science  
It uses the recently introduced Stochastic Roadmap Simulation (SRS) method to estimate the transition state ensemble (TSE) and predict the rates and Φ-values for protein folding.  ...  This paper presents a new method for studying protein folding kinetics.  ...  Estimating the TSE Using Stochastic Roadmap Simulation SRS is an efficient method for exploring protein folding kinetics by examining many folding pathways simultaneously.  ... 
doi:10.1007/11732990_34 fatcat:uunypasdnbh4fbpnpkkdgmgxni

Using Stochastic Roadmap Simulation to Predict Experimental Quantities in Protein Folding Kinetics: Folding Rates and Phi-Values

Tsung-Han Chiang, Mehmet Serkan Apaydin, Douglas L. Brutlag, David Hsu, Jean-Claude Latombe
2007 Journal of Computational Biology  
It uses the recently introduced Stochastic Roadmap Simulation (SRS) method to estimate the transition state ensemble (TSE) and predict the rates and the Φ-values for protein folding.  ...  The results on Φ-value predictions are mixed, possibly due to the simple energy model used in the tests.  ...  Estimating the TSE through Stochastic Roadmap Simulation SRS is an efficient method for exploring protein folding kinetics by examining many folding pathways simultaneously.  ... 
doi:10.1089/cmb.2007.r004 pmid:17683262 fatcat:tws4zbwfmrgetnmev3idh76r5y

Roadmap Methods for Protein Folding [chapter]

Mark Moll, David Schwarz, Lydia E. Kavraki
2008 Protein Structure Prediction  
e goal of these methods is not to predict the folded structure of a protein, but rather to analyze the folding kinetics. It is assumed that the folded state is known.  ...  Protein folding refers to the process whereby a protein assumes its intricate three-dimensional shape. is chapter reviews a class of methods for studying the folding process called roadmap methods.  ...  TZ has previously been simulated on Folding@Home [] . Some of this data was used to build a stochastic roadmap.  ... 
doi:10.1007/978-1-59745-574-9_9 pmid:18075168 fatcat:x5j72w7puzchvlmqge3vwuc3ce

Stochastic Conformational Roadmaps for Computing Ensemble Properties of Molecular Motion [chapter]

Mehmet Serkan Apaydın, Douglas L. Brutlag, Carlos Guestrin, David Hsu, Jean-Claude Latombe
2004 Springer Tracts in Advanced Robotics  
A salient feature of this new approach is that it examines all the paths in the roadmap simultaneously, rather than one at a time as classic methods such as Monte Carlo (MC) simulation would do.  ...  We construct a directed graph, called stochastic conformational roadmap, whose nodes are randomly sampled molecule conformations. A roadmap compactly encodes many molecular motion pathways.  ...  Varma for preparing the energy files for some of the ligand-protein complexes.  ... 
doi:10.1007/978-3-540-45058-0_9 fatcat:q4nkvg5lgvczrcgpz7g3tqztya

Stochastic Roadmap Simulation: An Efficient Representation and Algorithm for Analyzing Molecular Motion

Mehmet Serkan Apaydin, Douglas L. Brutlag, Carlos Guestrin, David Hsu, Jean-Claude Latombe, Chris Varma
2003 Journal of Computational Biology  
This paper introduces Stochastic Roadmap Simulation (SRS) as a new computational approach for exploring the kinetics of molecular motion by simultaneously examining multiple pathways.  ...  Comparison with MC simulations on protein folding shows that SRS produces arguably more accurate results, while reducing computation time by several orders of magnitude.  ...  Singh for the ligand-protein modelling software. We also thank the anonymous reviewers for their valuable comments.  ... 
doi:10.1089/10665270360688011 pmid:12935328 fatcat:pd7tieovcfhdvmpavaw2swagoe

A Motion Planning Approach to Studying Molecular Motions

Nancy M. Amato, Lydia Tapia, Shawna Thomas
2010 Communications in Information and Systems  
We have validated against experimental data and have demonstrated that our method can capture biological results such as stochastic folding pathways, population kinetics of various conformations, and relative  ...  Knowledge of the stability, folding, kinetics and detailed mechanics of the folding process may help provide insight into how proteins and RNAs fold.  ...  This research supported in part by NSF Grants EIA-01037-  ... 
doi:10.4310/cis.2010.v10.n1.a4 fatcat:utj34vgxezeczkkffxskxeo5py

Markov dynamic models for long-timescale protein motion

T.-H. Chiang, D. Hsu, J.-C. Latombe
2010 Bioinformatics  
We also used the constructed Markov models to estimate important kinetic and dynamic quantities for protein folding, in particular, mean first-passage time.  ...  In this direction, we propose to use Markov models with hidden states, in which the Markovian states represent potentially overlapping probabilistic distributions over protein conformations.  ...  We thank Vijay Pande and Nina Singhal, who provided us MD simulation data for alanine dipeptide and villin.  ... 
doi:10.1093/bioinformatics/btq177 pmid:20529916 pmcid:PMC2881362 fatcat:aiapo337jvakncr7dzppczfme4

A stochastic roadmap method to model protein structural transitions

Kevin Molloy, Rudy Clausen, Amarda Shehu
2015 Robotica (Cambridge. Print)  
This paper investigates an efficient algorithmic realization of the stochastic roadmap simulation framework to model structural transitions in wildtype and variants of proteins implicated in human disorders  ...  Our results indicate that the algorithm is able to extract useful information on the impact of mutations on protein structure and function.  ...  Treating the roadmap as a Markov state model allows using transition state theory to obtain measurements approximating kinetic quantities of interest.  ... 
doi:10.1017/s0263574715001058 fatcat:y7pqtfn2y5ch3oinrm6e3hxgqe

Computational Models of Protein Kinematics and Dynamics: Beyond Simulation

Bryant Gipson, David Hsu, Lydia E. Kavraki, Jean-Claude Latombe
2012 Annual Review of Analytical Chemistry  
Such simulations can be prohibitively difficult or lengthy, however, for large proteins or in probing the lower resolution, long-timescale behaviors of proteins generally.  ...  In particular, the review focuses on methods that address kinematics and dynamics, as well as on methods that address larger organizational questions and are capable of quickly yielding useful information  ...  The method was later extended to predict experimental measures of folding kinetics, such as folding rates, transition state ensembles, and Φ-values of residues (103).  ... 
doi:10.1146/annurev-anchem-062011-143024 pmid:22524225 pmcid:PMC4866812 fatcat:t4btthioyrdt7hu3tpbnwum3kq

Stochastic roadmap simulation for the study of ligand-protein interactions

M. S. Apaydin, C. E. Guestrin, C. Varma, D. L. Brutlag, J.-C. Latombe
2002 Bioinformatics  
In this paper, we establish the use of Stochastic Roadmap Simulation (SRS) for the study of ligand-protein interactions through two studies.  ...  SRS compactly represents many Monte Carlo (MC) simulation paths in a compact graph structure, or roadmap. Furthermore, SRS allows us to analyze all the paths in this roadmap simultaneously.  ...  Singh for his ligand-protein modeling code.  ... 
doi:10.1093/bioinformatics/18.suppl_2.s18 pmid:12385979 fatcat:vztq5amzijbutfdrqq7pu7uhjm

Kinetic Network Study of the Diversity and Temperature Dependence of Trp-Cage Folding Pathways: Combining Transition Path Theory with Stochastic Simulations

Weihua Zheng, Emilio Gallicchio, Nanjie Deng, Michael Andrec, Ronald M. Levy
2011 Journal of Physical Chemistry B  
swaps between MD trajectories, it is not straightforward to obtain kinetic information from such simulations. 29, 39, 42, 52 We have made use of a kinetic network model 53 in which we take advantage of  ...  (REMD) simulations for conformational sampling, transition path theory (TPT) for constructing folding pathways, and stochastic simulations for sampling the pathways in a high dimensional structure space  ...  The analysis of folding fluxes based on stochastic simulations on the network confirms the transition path theory predictions, as shown in Table 1 and Figure 5 .  ... 
doi:10.1021/jp1089596 pmid:21254767 pmcid:PMC3059588 fatcat:f7ycca3cnfh3jhhoxyvhq6ggsi

Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics

Tatiana Maximova, Ryan Moffatt, Buyong Ma, Ruth Nussinov, Amarda Shehu, Bert L. de Groot
2016 PLoS Computational Biology  
Significant advances have been made toward this end in silico, with a growing number of computational methods proposed yearly to study and simulate various aspects of macromolecular structure and dynamics  ...  This review aims to provide an overview of recent advances, focusing primarily on methods proposed for exploring the structure space of macromolecules in isolation and in assemblies for the purpose of  ...  Kinetic clustering continues to be useful and has been used successfully to characterize protein folding through very long MD simulations [147] .  ... 
doi:10.1371/journal.pcbi.1004619 pmid:27124275 pmcid:PMC4849799 fatcat:gys3apbbbbb4tjr42k7yi3twpy

Progress and challenges in the automated construction of Markov state models for full protein systems

Gregory R. Bowman, Kyle A. Beauchamp, George Boxer, Vijay S. Pande
2009 Journal of Chemical Physics  
In this work we demonstrate the application of MSMBUILDER to the villin headpiece ͑HP-35 NleNle͒, one of the smallest and fastest folding proteins.  ...  As a first step toward experimental validation of our methodology we show that our model provides accurate structure prediction and that the longest timescale events correspond to folding.  ...  MSMs are better able to capture the stochastic nature of processes such as protein folding than traditional analysis techniques, allowing more quantitative comparisons with and predictions of experimental  ... 
doi:10.1063/1.3216567 pmid:19791846 pmcid:PMC2766407 fatcat:422ymi4pebb6dnwemvb6jkbru4

Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning

Gennady M. Verkhivker, Steve Agajanian, Guang Hu, Peng Tao
2020 Frontiers in Molecular Biosciences  
characterization of allosteric mechanisms in proteins.  ...  In this review, we discuss simulation-based multiscale approaches, experiment-informed Markovian models, and network modeling of allostery and information-theoretical approaches that can describe the thermodynamics  ...  interactions and inhibit protein folding events (Zaiter et al., 2019 ).  ... 
doi:10.3389/fmolb.2020.00136 pmid:32733918 pmcid:PMC7363947 fatcat:vxoqxun6ebhdveqlbwi7l7rfui

Exploring zipping and assembly as a protein folding principle

Vincent A. Voelz, Ken A. Dill
2006 Proteins: Structure, Function, and Bioinformatics  
We believe these insights may be useful for developing faster protein conformational search algorithms.  ...  We believe these insights may be useful for developing faster protein conformational search algorithms.  ...  Vincent Voelz was supported in part by a Burroughs Wellcome Fund Interfaces in Science Fellowship.  ... 
doi:10.1002/prot.21234 pmid:17154424 fatcat:quzci4nuhrgbxekcoguee7kida
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