Author

J. Vant

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biophysics· 4 Biochemistry· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 3 Assay:cryo-EM· 2 Approach:experimental assay· 2 Research Focus:protein folding & dynamics· 2 Research Focus:chromatin & epigenetic regulation· 1 Organism:human· 1 Approach:mechanistic / dynamical model· 1 Assay:multiome· 1

Frequent Co-Authors

A. Singharoy· 5 shared C. Gupta· 2 shared D. Sarkar· 2 shared J. K. Cava· 2 shared J. Miratsky· 2 shared A. Mondal· 1 shared A. Ourmazd· 1 shared A. Perez· 1 shared

Activity by Year

2020-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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5 shared papersBiophysics

A. Singharoy

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Author profile →

5 papers

Recent·Most cited

Structural mechanism of HP1-dependent transcriptional repression and chromatin compaction

V. Sokolova, J. Miratsky, V. Svetlov, M. Brenowitz, J. Vant, T. S. Lewis, K. Dryden, G. L. Lee, S. L. Sarkar, E. Nudler, A. Singharoy, D. Tan

This study determines the cryo-EM structure of HP1 bound to an H2A.Z nucleosome, revealing two binding sites and their roles in transcriptional repression and chromatin compaction.

bioRxiv · Nov 30, 2023Biochemistry

Learning Free Energy Pathways through Reinforcement Learning of Adaptive Steered Molecular Dynamics

N. Ho, J. K. Cava, J. Vant, A. Shukla, J. Miratsky, P. Turaga, R. Maciejewski, A. Singharoy

This paper develops a reinforcement learning framework to compute low free energy pathways between states using adaptive steered molecular dynamics and robotics planning.

bioRxiv · Oct 4, 2022 · PreprintBiophysics

Energy Landscape of the SARS-CoV-2 Reveals Extensive Conformational Heterogeneity

G. Mashayekhi, J. Vant, A. Singharoy, A. Ourmazd

The paper uses cryo-EM to analyze the energy landscape of the SARS-CoV-2 spike protein, revealing conformational heterogeneity and dynamic behavior not captured by static models.

bioRxiv · May 11, 2021Biophysics

CryoFold: Ab-initio structure determination from electron density maps using molecular dynamics

M. Shekhar, G. Terashi, C. Gupta, D. Sarkar, G. Debussche, N. Sisco, J. Nguyen, A. Mondal, J. Zook, J. Vant, P. Fromme, W. D. van Horn, D. Kihara, E. Tajkhorshid, K. Dill, , A. Singharoy

CryoFold determines protein structures from electron density maps using molecular dynamics and physical knowledge, producing ensembles of low-energy conformations validated experimentally.

bioRxiv · Aug 3, 2020 · PreprintBiophysics

Mind reading of the proteins: Deep-learning to forecast molecular dynamics

C. Gupta, J. K. Cava, D. Sarkar, E. A. Wilson, J. Vant, S. Murray, A. Singharoy, S. K. Karmaker

This paper uses deep learning to predict molecular dynamics from simulation data, finding that non-equilibrium MD is easier to train and performance improves with atom independence assumptions.

bioRxiv · Jul 28, 2020 · PreprintBiophysics