Improvements in Markov State Model Construction Reveal Many Non-Native Interactions in the Folding of NTL9

Cited by (573)

Items 101–200 of 573

1. A kinetic ensemble of the Alzheimer’s Aβ peptide
   Löhr, Thomas, Kohlhoff, Kai, Heller, Gabriella T., Camilloni, Carlo, Vendruscolo, Michele · 2021 · Nature Computational Science
2. Investigating Molecular Kinetics by Variationally Optimized Diffusion Maps
   Lorenzo Boninsegna, Gianpaolo Gobbo, Frank Noé, Cecilia Clementi · 2015 · Journal of Chemical Theory and Computation
3. Targeted Protein Degradation: Advances, Challenges, and Prospects for Computational Methods
   Barmak Mostofian, Holli‐Joi Martin, Asghar M. Razavi, Shivam Patel, Bryce K. Allen, Woody Sherman, Jesús A. Izaguirre · 2023 · Journal of Chemical Information and Modeling
4. Automated Markov state models for molecular dynamics simulations of aggregation and self-assembly.
   Ushnish Sengupta, Martín Carballo-Pacheco, B. Strodel · 2019 · Journal of Chemical Physics
5. Kinetic and thermodynamic insights into sodium ion translocation through the μ-opioid receptor from molecular dynamics and machine learning analysis
   Xiaohu Hu, Yibo Wang, Amanda Hunkele, D. Provasi, G. Pasternak, M. Filizola · 2019 · PLoS Comput. Biol.
6. Deep learning collective variables from transition path ensemble.
   Dhiman Ray, Enrico Trizio, M. Parrinello · 2023 · Journal of Chemical Physics
7. Computational methods for exploring protein conformations
   Jane R. Allison · 2020 · Biochemical Society Transactions
8. Introduction to Markov state modeling with the PyEMMA software [Article v1.0]
   C. Wehmeyer, Martin K. Scherer, Tim Hempel, B. Husic, S. Olsson, Frank Noé · 2018 · Living journal of computational molecular science
9. Elucidation of the Dynamics of Transcription Elongation by RNA Polymerase II using Kinetic Network Models
   Lu Zhang, Fátima Pardo‐Ávila, Ilona Christy Unarta, Peter Pak‐Hang Cheung, Wang Guo, Dong Wang, Xuhui Huang · 2016 · Accounts of Chemical Research
10. Overcoming the barrier of orbital-free density functional theory for molecular systems using deep learning
    He Zhang, Siyuan Liu, Jiacheng You, Chang Liu, Shuxin Zheng, Ziheng Lu, Tong Wang, Nanning Zheng, Bin Shao · 2024 · Nature Computational Science
11. Breathing and Tilting: Mesoscale Simulations Illuminate Influenza Glycoprotein Vulnerabilities
    L. Casalino, C. Seitz, Julia Lederhofer, Y. Tsybovsky, Ian A. Wilson, M. Kanekiyo, R. Amaro · 2022 · ACS Central Science
12. The next revolution in computational simulations: Harnessing AI and quantum computing in molecular dynamics.
    Anna Lappala · 2024 · Current Opinion in Structural Biology
13. Molecular latent space simulators
    Hythem Sidky, Wei Chen, Andrew L. Ferguson · 2020 · Chemical Science
14. Clustering algorithms to analyze molecular dynamics simulation trajectories for complex chemical and biological systems
    Junhui Peng, Wei Wang, Yeqing Yu, Han-Lin Gu, Xu-Hui Huang · 2018 · Chinese Journal of Chemical Physics
15. A Molecular Interpretation of 2D IR Protein Folding Experiments with Markov State Models
    Baiz, Carlos R., Lin, Yu-Shan, Peng, Chunte Sam, Beauchamp, Kyle A., Voelz, Vincent A., Pande, Vijay S., Tokmakoff, Andrei · 2014 · Biophysical Journal
16. GraphVAMPNet, using graph neural networks and variational approach to Markov processes for dynamical modeling of biomolecules
    Mahdi Ghorbani, Samarjeet Prasad, Jeffery B. Klauda, Bernard R. Brooks · 2022 · The Journal of Chemical Physics
17. A combination of machine learning and infrequent metadynamics to efficiently predict kinetic rates, transition states, and molecular determinants of drug dissociation from G protein-coupled receptors
    João Marcelo Lamim Ribeiro, D. Provasi, M. Filizola · 2020 · Journal of Chemical Physics
18. Ensemble learning of coarse-grained molecular dynamics force fields with a kernel approach
    Jiang Wang, Stefan Chmiela, Klaus‐Robert Müller, Frank Noé, Cecilia Clementi · 2020 · The Journal of Chemical Physics
19. How Effectively Can Adaptive Sampling Methods Capture Spontaneous Ligand Binding?
    Robin M. Betz, R. Dror · 2019 · Journal of Chemical Theory and Computation
20. A Small Molecule Stabilizes the Disordered Native State of the Alzheimer’s Aβ Peptide
    T. Löhr, Kai J. Kohlhoff, Gabriella T. Heller, C. Camilloni, M. Vendruscolo · 2022 · ACS Chemical Neuroscience
21. Transition rate theory, spectral analysis, and reactive paths
    B. Roux · 2022 · Journal of Chemical Physics
22. Millisecond dynamics of BTK reveal kinome-wide conformational plasticity within the apo kinase domain
    M. M. Sultan, R. Denny, R. Unwalla, F. Lovering, V. Pande · 2017 · Scientific Reports
23. Adaptive Markov state model estimation using short reseeding trajectories.
    Hongbin Wan, Vincent A. Voelz · 2019 · Journal of Chemical Physics
24. Predicting the Conformational Variability of Abl Tyrosine Kinase using Molecular Dynamics Simulations and Markov State Models
    Yilin Meng, Cen Gao, David K. Clawson, S. Atwell, Marijane Russell, Michal Vieth, Benoı̂t Roux · 2018 · Journal of Chemical Theory and Computation
25. Dynamic Profiling of β-Coronavirus 3CL Mpro Protease Ligand-Binding Sites
    Eunice Cho, M. Rosa, Ruhi Anjum, Saman Mehmood, Mariya Soban, Moniza Mujtaba, Khair Bux, S. T. Moin, Mohammad Tanweer, S. Dantu et al. · 2021 · Journal of Chemical Information and Modeling
26. Computational Screening and Selection of Cyclic Peptide Hairpin Mimetics by Molecular Simulation and Kinetic Network Models
    Asghar M. Razavi, William M. Wuest, Vincent A. Voelz · 2014 · Journal of Chemical Information and Modeling
27. Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning
    Shuxin Zheng, Jiyan He, Chang Liu, Yu Shi, Zi-Heng Lu, Weitao Feng, Fusong Ju, Jia-Xian Wang, Jianwei Zhu, Yaosen Min et al. · 2023 · arXiv.org
28. A Blueprint for High Affinity SARS-CoV-2 Mpro Inhibitors from Activity-Based Compound Library Screening Guided by Analysis of Protein Dynamics
    Jonas Gossen, Simone Albani, A. Hanke, B. Joseph, Cathrine Bergh, M. Kuzikov, E. Costanzi, C. Manelfi, P. Storici, P. Gribbon et al. · 2020 · bioRxiv
29. Long-timescale predictions from short-trajectory data: A benchmark analysis of the trp-cage miniprotein
    J. Strahan, Adam Antoszewski, Chatipat Lorpaiboon, B. P. Vani, J. Weare, A. Dinner · 2020 · Journal of Chemical Theory and Computation
30. Ward Clustering Improves Cross-Validated Markov State Models of Protein Folding.
    B. Husic, V. Pande · 2017 · Journal of Chemical Theory and Computation
31. Polarizable and non-polarizable force fields: Protein folding, unfolding, and misfolding.
    A. S. Kamenik, P. Handle, Florian Hofer, Ursula Kahler, Johannes Kraml, K. Liedl · 2020 · Journal of Chemical Physics
32. MHC class II complexes sample intermediate states along the peptide exchange pathway
    Marek Wieczorek, Jana Sticht, Sebastian Stolzenberg, Sebastian Günther, Christoph Wehmeyer, Zeina El Habre, Miguel Álvaro‐Benito, Frank Noé, Christian Freund · 2016 · Nature Communications
33. Complex pathways in folding of protein G explored by simulation and experiment.
    Lisa J. Lapidus, Srabasti Acharya, Christian R. Schwantes, Ling Wu, D. Shukla, Michael King, Stephen J. DeCamp, V. Pande · 2014 · Biophysical Journal
34. String Method with Swarms-of-Trajectories, Mean Drifts, Lag Time, and Committor
    Benoı̂t Roux · 2021 · The Journal of Physical Chemistry A
35. Mapping the Ligand Binding Landscape
    Alex Dickson · 2018 · bioRxiv
36. Beyond expectations: residual dynamic mode decomposition and variance for stochastic dynamical systems
    Matthew J. Colbrook, Qin Li, Ryan V. Raut, Alex Townsend · 2023 · Nonlinear Dynamics
37. Statistically Optimal Force Aggregation for Coarse-Graining Molecular Dynamics.
    Andreas Krämer, Aleksander E. P. Durumeric, N. Charron, Yao-Yi Chen, Cecilia Clementi, Frank No'e · 2023 · Journal of Physical Chemistry Letters
38. Modeling the mechanism of CLN025 beta-hairpin formation.
    K. McKiernan, B. Husic, V. Pande · 2017 · Journal of Chemical Physics
39. Ensuring thermodynamic consistency with invertible coarse-graining.
    Shriram Chennakesavalu, David Toomer, Grant M. Rotskoff · 2022 · Journal of Chemical Physics
40. Collective variable discovery in the age of machine learning: reality, hype and everything in between
    S. Bhakat · 2021 · RSC Advances
41. Dissociation Process of a MDM2/p53 Complex Investigated by Parallel Cascade Selection Molecular Dynamics and the Markov State Model
    Duy Phuoc Tran, Akio Kitao · 2019 · The Journal of Physical Chemistry B
42. Stochastic steps in secondary active sugar transport
    Joshua L. Adelman, C. Ghezzi, P. Bisignano, D. Loo, S. Choe, J. Abramson, J. Rosenberg, E. M. Wright, M. Grabe · 2016 · Proceedings of the National Academy of Sciences of the United States of America
43. A Maximum-Caliber Approach to Predicting Perturbed Folding Kinetics Due to Mutations.
    Hongbin Wan, Guangfeng Zhou, Vincent A. Voelz · 2016 · Journal of Chemical Theory and Computation
44. Automatic State Partitioning for Multibody Systems (APM): An Efficient Algorithm for Constructing Markov State Models To Elucidate Conformational Dynamics of Multibody Systems
    Fu Kit Sheong, Daniel‐Adriano Silva, Luming Meng, Yutong Zhao, Xuhui Huang · 2014 · Journal of Chemical Theory and Computation
45. Active Learning of the Conformational Ensemble of Proteins using Maximum Entropy VAMPNets
    D. Kleiman, Diwakar Shukla · 2023 · bioRxiv
46. Enzyme dynamics: Looking beyond a single structure
    P. Agarwal, David N. Bernard, Khushboo Bafna, N. Doucet · 2020 · ChemCatChem
47. Linking time-series of single-molecule experiments with molecular dynamics simulations by machine learning
    Y. Matsunaga, Yuji Sugita · 2018 · eLife
48. Simulations meet machine learning in structural biology
    Adrià Pérez, Gerard Martínez-Rosell, Gianni De Fabritiis · 2018 · Current Opinion in Structural Biology
49. Exploring the Dynamics of Propeller Loops in Human Telomeric DNA Quadruplexes Using Atomistic Simulations
    Barira Islam, Petr Stadlbauer, Alejandro Gil-Ley, G. Pérez-Hernández, S. Haider, S. Neidle, G. Bussi, P. Banáš, M. Otyepka, J. Šponer · 2017 · Journal of Chemical Theory and Computation
50. Role of bacterial RNA polymerase gate opening dynamics in DNA loading and antibiotics inhibition elucidated by quasi-Markov State Model
    Ilona Christy Unarta, Siqin Cao, Shintaroh Kubo, Wei Wang, Peter Pak‐Hang Cheung, Xin Gao, Shoji Takada, Xuhui Huang · 2021 · Proceedings of the National Academy of Sciences
51. Dynamic graphical models of molecular kinetics
    Simon Olsson, Frank Noé · 2019 · Proceedings of the National Academy of Sciences
52. Markov State Models and tICA Reveal a Nonnative Folding Nucleus in Simulations of NuG2.
    Christian R. Schwantes, D. Shukla, V. Pande · 2016 · Biophysical Journal
53. Exploring transition states of protein conformational changes via out-of-distribution detection in the hyperspherical latent space
    Bojun Liu, Jordan G. Boysen, Ilona Christy Unarta, Xuefeng Du, Yixuan Li, Xuhui Huang · 2025 · Nature Communications
54. Collective Variable-Based Enhanced Sampling: From Human Learning to Machine Learning.
    Hao-Hao Fu, H. Bian, Xue-Guang Shao, Wen-Sheng Cai · 2024 · Journal of Physical Chemistry Letters
55. Driving and characterizing nucleation of urea and glycine polymorphs in water
    Ziyue Zou, E. Beyerle, Sun-Ting Tsai, P. Tiwary · 2022 · Proceedings of the National Academy of Sciences of the United States of America
56. Accelerated estimation of long-timescale kinetics from weighted ensemble simulation via non-Markovian “microbin” analysis
    J. Copperman, D. Zuckerman · 2020 · Journal of Chemical Theory and Computation
57. Capabilities and Limitations of Time-lagged Autoencoders for Slow Mode Discovery in Dynamical Systems
    Wei Chen, Hythem Sidky, Andrew L. Ferguson · 2019 · Journal of Chemical Physics
58. Optimal Data-Driven Estimation of Generalized Markov State Models for Non-Equilibrium Dynamics
    P. Koltai, Hao Wu, Frank Noé, C. Schütte · 2018 · De Computis
59. Specific PIP2 binding promotes calcium activation of TMEM16A chloride channels
    Zhiguang Jia, Jianhan Chen · 2021 · Communications Biology
60. Rapid Calculation of Molecular Kinetics Using Compressed Sensing
    Florian Litzinger, Lorenzo Boninsegna, Hao Wu, Feliks Nüske, Raajen Patel, Richard G. Baraniuk, Frank Noé, Cecilia Clementi · 2018 · Journal of Chemical Theory and Computation
61. REDOR NMR Reveals Multiple Conformers for a Protein Kinase C Ligand in a Membrane Environment
    Hao Yang, Daryl Staveness, Steven M. Ryckbosch, Alison Donnelly Axtman, Brian A. Loy, Alexander B. Barnes, Vijay S. Pande, Jacob Schaefer, Paul A. Wender, Lynette Cegelski · 2018 · ACS Central Science
62. Building insightful, memory-enriched models to capture long-time biochemical processes from short-time simulations
    Anthony J. Dominic, Thomas Sayer, Siqin Cao, Thomas E. Markland, Xuhui Huang, Andrés Montoya−Castillo · 2023 · Proceedings of the National Academy of Sciences
63. Human Learning for Molecular Simulations: The Collective Variables Dashboard in VMD.
    Jérôme Hénin, Laura J. S. Lopes, G. Fiorin · 2021 · Journal of Chemical Theory and Computation
64. Efficient maximum likelihood parameterization of continuous-time Markov processes.
    R. McGibbon, V. Pande · 2015 · Journal of Chemical Physics
65. Weighted ensemble milestoning (WEM): A combined approach for rare event simulations.
    Dhiman Ray, I. Andricioaei · 2019 · Journal of Chemical Physics
66. Neural Canonical Transformation with Symplectic Flows
    Shuo-Hui Li, Chenxiao Dong, Linfeng Zhang, Lei Wang · 2020 · Physical Review X
67. Memory Unlocks the Future of Biomolecular Dynamics: Transformative Tools to Uncover Physical Insights Accurately and Efficiently
    Anthony J. Dominic, Siqin Cao, Andrés Montoya−Castillo, Xuhui Huang · 2023 · Journal of the American Chemical Society
68. Role of internal loop dynamics in antibiotic permeability of outer membrane porins
    A. Vasan, Nandan Haloi, R. Ulrich, M. E. Metcalf, Po-Chao Wen, William W. Metcalf, P. Hergenrother, D. Shukla, E. Tajkhorshid · 2022 · Proceedings of the National Academy of Sciences of the United States of America
69. Discovery of a hidden transient state in all bromodomain families
    L. Raich, K. Meier, Judith Günther, Clara D. Christ, Frank Noé, S. Olsson · 2020 · Proceedings of the National Academy of Sciences of the United States of America
70. Revealing Molecular Determinants of hERG Blocker and Activator Binding
    Callum J. Dickson, Camilo Velez-Vega, J. Duca · 2019 · Journal of Chemical Information and Modeling
71. Kernel methods for detecting coherent structures in dynamical data.
    Stefan Klus, B. Husic, Mattes Mollenhauer, Frank Noé · 2019 · Chaos
72. T7 RNA polymerase translocation is facilitated by a helix opening on the fingers domain that may also prevent backtracking
    Lin-Tai Da, E. Chao, Yao Shuai, Shaogui Wu, Xiao-Dong Su, Jin Yu · 2017 · Nucleic Acids Research
73. Girsanov Reweighting Enhanced Sampling Technique (GREST): On-the-Fly Data-Driven Discovery of and Enhanced Sampling in Slow Collective Variables.
    Kirill Shmilovich, Andrew L. Ferguson · 2023 · Journal of Physical Chemistry A
74. Gaussian-Accelerated Molecular Dynamics with the Weighted Ensemble Method: A Hybrid Method Improves Thermodynamic and Kinetic Sampling
    Surl-Hee Ahn, Anupam Anand Ojha, R. Amaro, J. McCammon · 2021 · Journal of Chemical Theory and Computation
75. Elucidating molecular mechanisms of functional conformational changes of proteins via Markov state models
    Xiaowei Wang, Ilona Christy Unarta, Peter Pak‐Hang Cheung, Xuhui Huang · 2020 · Current Opinion in Structural Biology
76. Machine Learning for Molecular Dynamics on Long Timescales
    Frank Noé · 2020 · Lecture notes in physics
77. Identification of kinetic order parameters for non-equilibrium dynamics
    Fabian Paul, Hao Wu, Maximilian Vossel, Bert L. de Groot, Frank Noé · 2019 · The Journal of Chemical Physics
78. Integrative generalized master equation: A method to study long-timescale biomolecular dynamics via the integrals of memory kernels
    Siqin Cao, Yunrui Qiu, Michael L. Kalin, Xuhui Huang · 2023 · The Journal of Chemical Physics
79. An Efficient Path Classification Algorithm Based on Variational Autoencoder to Identify Metastable Path Channels for Complex Conformational Changes
    Yunrui Qiu, Michael S. O’Connor, Mingyi Xue, Bojun Liu, Xuhui Huang · 2023 · Journal of Chemical Theory and Computation
80. Data-Driven Molecular Dynamics: A Multifaceted Challenge
    Mattia Bernetti, Martina Bertazzo, Matteo Masetti · 2020 · Pharmaceuticals
81. Target search and recognition mechanisms of glycosylase AlkD revealed by scanning FRET-FCS and Markov state models
    Sijia Peng, Xiaowei Wang, Lu Zhang, Shanshan He, Xin Sheng Zhao, Xuhui Huang, Chunlai Chen · 2020 · Proceedings of the National Academy of Sciences
82. Role of substrate recognition in modulating strigolactone receptor selectivity in witchweed
    Jiming Chen, Alexandra R. F. White, David C. Nelson, D. Shukla · 2020 · bioRxiv
83. A kernel-based approach to molecular conformation analysis
    Stefan Klus, Andreas Bittracher, I. Schuster, C. Schütte · 2018 · Journal of Chemical Physics
84. Base-flipping dynamics from an intrahelical to an extrahelical state exerted by thymine DNA glycosylase during DNA repair process
    Lin-Tai Da, Jin Yu · 2018 · Nucleic Acids Research
85. MSM/RD: Coupling Markov state models of molecular kinetics with reaction-diffusion simulations
    Manuel Dibak, Mauricio J. del Razo, David De Sancho, Christof Schütte, Frank Noé · 2018 · The Journal of Chemical Physics
86. Mechanistic Models of Chemical Exchange Induced Relaxation in Protein NMR
    Simon Olsson, Frank Noé · 2016 · Journal of the American Chemical Society
87. Nonlinear machine learning in simulations of soft and biological materials
    Jiang Wang, Andrew L. Ferguson · 2017 · Molecular Simulation
88. How structural elements evolving from bacterial to human SLC6 transporters enabled new functional properties
    Asghar M. Razavi, G. Khelashvili, H. Weinstein · 2018 · BMC Biology
89. Progress in studying intrinsically disordered proteins with atomistic simulations.
    Nathaniel H. Stanley, Santi Esteban-Martín, G. de Fabritiis · 2015 · Progress in Biophysics and Molecular Biology
90. Transferable Implicit Solvation via Contrastive Learning of Graph Neural Networks
    J. Airas, Xin-Qiang Ding, Bin Zhang · 2023 · ACS Central Science
91. Exploring the Regulatory Function of the N‐terminal Domain of SARS‐CoV‐2 Spike Protein through Molecular Dynamics Simulation
    Yao Li, Tong Wang, Juanrong Zhang, Bin Shao, Haipeng Gong, Yusong Wang, Xinheng He, Siyuan Liu, Tie‐Yan Liu · 2021 · Advanced Theory and Simulations
92. Structural basis for ligand modulation of the CCR2 conformational landscape
    Bryn C. Taylor, Christopher T. Lee, R. Amaro · 2018 · Proceedings of the National Academy of Sciences of the United States of America
93. Recruiting machine learning methods for molecular simulations of proteins
    S. Mittal, D. Shukla · 2018 · Molecular Simulation
94. GraphVAMPnets for uncovering slow collective variables of self-assembly dynamics
    Bojun Liu, Mingyi Xue, Yunrui Qiu, Kirill A. Konovalov, Michael S. O’Connor, Xuhui Huang · 2023 · The Journal of Chemical Physics
95. MHC-II dynamics are maintained in HLA-DR allotypes to ensure catalyzed peptide exchange
    Esam T. Abualrous, S. Stolzenberg, J. Sticht, M. Wieczorek, Y. Roske, M. Günther, Steffen Dähn, B. Boesen, Marcos Martínez Calvo, Charlotte Biese et al. · 2023 · Nature Chemical Biology
96. Collective Variables for Crystallization Simulations─from Early Developments to Recent Advances
    Neha Neha, Vikas Tiwari, Soumya Mondal, Nisha Kumari, Tarak Karmakar · 2022 · ACS Omega
97. Variational Identification of Markovian Transition States
    Linda Martini, Adam Kells, Roberto Covino, Gerhard Hummer, Nicolae‐Viorel Buchete, Edina Rosta · 2017 · Physical Review X
98. Dynamical coring of Markov state models
    Daniel Nagel, Anna Weber, Benjamin Lickert, Gerhard Stock · 2019 · The Journal of Chemical Physics
99. Kinetic Network Models of Tryptophan Mutations in β-Hairpins Reveal the Importance of Non-Native Interactions
    Asghar M. Razavi, Vincent A. Voelz · 2015 · Journal of Chemical Theory and Computation
100. Relaxation mode analysis and Markov state relaxation mode analysis for chignolin in aqueous solution near a transition temperature
     Ayori Mitsutake, Hiroshi Takano · 2015 · The Journal of Chemical Physics