Author

Praveen Muralikrishnan

University of MinnesotaORCID 0009-0002-8170-0561Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:mechanistic / dynamical model· 1 Research Focus:protein folding & dynamics· 1 Assay:protein structure· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Caryn L. HeldtiD· 2 shared Jonathan W. P. ZajaciD· 2 shared Sapna SarupriaiD· 2 shared Sarah L. PerryiD· 2 shared Idris Tohidian· 1 shared Xianci ZengiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

6 top collaborators · 14 mutual co-author links

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2 shared papersBiophysics

Caryn L. HeldtORCID

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2 papers

Recent·Most cited

BiophysicsbioRxivPreprintJun 15, 2026

Protein-Solvent Shape Complementarity as a Unifying Principle in Excipient-Mediated Protein Thermal Stability

Jonathan W. P. Zajac, Praveen Muralikrishnan, Xianci Zeng…·Sapna Sarupria

The paper uses molecular dynamics simulations to identify a unifying mechanism for excipient-mediated protein thermal stability based on shape complementarity between proteins and solvents.

DOI 10.64898/2026.06.12.731979

protein structuremechanistic / dynamical model

𝕏 PostBluesky

BiophysicsJournal of Chemical Theory and ComputationPeer-reviewedFeb 25, 2026

Cracking the Capsid Code: A Computationally-Feasible Approach for Investigating Virus-Excipient Interactions in Biologics Design

Jonathan W. P. Zajac, Idris Tohidian, Praveen Muralikrishnan…·Sapna Sarupria

This paper introduces CapSACIN, a computational framework to study virus-excipient interactions, showing it effectively models PPV stability and excipient effects.

2 citations

structural biologydeep learning

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