Author

Divyanshu Shukla

Iowa State UniversityORCID 0009-0004-5495-9863Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Approach:deep learning· 3 Research Focus:protein design· 2 Assay:protein sequence· 2 Assay:protein structure· 2 Research Focus:sequence-to-function modeling· 2 Approach:Bayesian inference· 1 Research Focus:protein folding & dynamics· 1 Approach:statistical model· 1

Frequent Co-Authors

Davit A. PotoyaniD· 3 shared Faruck MorcosiD· 2 shared Jonathan MartiniD· 2 shared Dulitha Prasanna KulathungaiD· 1 shared

Activity by Year

2025-2026 · peak 2/yr

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4 top collaborators · 4 mutual co-author links

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3 shared papersBiophysics

Davit A. PotoyanORCID

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3 papers

Recent·Most cited

A Structure-Aware Generative Framework for Exploring Protein Sequence and Function Space

Divyanshu Shukla, Jonathan Martin, Faruck Morcos, Davit A. Potoyan

This paper introduces a structure-aware generative framework that integrates geometric encoding and coevolutionary constraints to map, cluster, and design protein sequences, improving homology detection and structure-guided sequence generation.

Proceedings of the National Academy of Sciences · Oct 2, 2026Peer-reviewedBiophysics

Coevolution-informed Bayesian optimization for sample-efficient protein design

Dulitha Prasanna Kulathunga, Divyanshu Shukla, Davit A. Potoyan

This paper introduces ALSEBO, a Bayesian optimization method for protein design that efficiently finds optimal sequences with few evaluations by leveraging coevolutionary statistics.

bioRxiv · Aug 7, 2026 · PreprintBiophysics

Thermal Adaptation of Cytosolic Malate Dehydrogenase Revealed by Deep Learning and Coevolutionary Analysis

Divyanshu Shukla, Jonathan Martin, Faruck Morcos, Davit A. Potoyan

This study uses deep learning and coevolutionary analysis to explore how sequence variation and structural dynamics influence thermal adaptation in cytosolic malate dehydrogenase.

Journal of Chemical Theory and Computation · Mar 13, 2025Peer-reviewedBiophysics