Author

R. Appadurai

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

Signature Assays, Organisms & Methods

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Research Focus:protein folding & dynamics· 4 Approach:statistical model· 3 Approach:deep learning· 2 Assay:proteomics· 2 Assay:DNA methylation· 1 Research Focus:drug response / drug discovery· 1 Approach:mechanistic / dynamical model· 1 Assay:protein structure· 1

Frequent Co-Authors

A. Srivastava· 4 shared H. SureshKumar· 1 shared I. Roy· 1 shared J. Krishna· 1 shared J. Nagesh· 1 shared M. Bonomi· 1 shared P. Robustelli· 1 shared S. Balasubramanian· 1 shared

Activity by Year

2021-2023 · peak 2/yr

Co-Author Collaboration Network

8 top collaborators · 11 mutual co-author links

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4 shared papersBiophysics

A. Srivastava

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4 papers

Recent·Most cited

hnRNPA1 RGG-box acts a "catalyst" in UP1-induced destabilization of RNA and DNA telomeric G-Quadruplexes

S. Balasubramanian, I. Roy, R. Appadurai, A. Srivastava

This study investigates how the RGG-box of hnRNPA1 interacts with telomeric G-quadruplexes, showing it preferentially binds to specific structures and can destabilize them, aiding hnRNPA1-UP1 in telomere maintenance.

bioRxiv · Aug 21, 2023 · PreprintBiophysics

Glycans modulate lipid binding in Lili-Mip lipocalin protein

H. SureshKumar, R. Appadurai, A. Srivastava

This study investigates how glycans affect lipid binding in Lili-Mip lipocalin using molecular dynamics simulations and structural analysis.

bioRxiv · Mar 6, 2023 · PreprintBiophysics

Clustering conformational ensembles of intrinsically disordered proteins with t-distributed stochastic neighbor embedding

R. Appadurai, J. Krishna, M. Bonomi, P. Robustelli, A. Srivastava

This paper uses t-SNE to cluster conformations of intrinsically disordered proteins, revealing structurally similar groups and insights into ligand binding mechanisms.

bioRxiv · Nov 11, 2022 · PreprintBiophysics

High resolution ensemble description of metamorphic and intrinsically disordered proteins using an efficient hybrid parallel tempering scheme

R. Appadurai, J. Nagesh, A. Srivastava

The paper introduces an efficient hybrid parallel tempering method to accurately sample conformational ensembles of metamorphic and intrinsically disordered proteins, matching experimental data without reweighting.

Nature Communications · Feb 11, 2021Peer-reviewedBiophysics