Author

Madhusudan Rajendran

Rochester Institute of TechnologyORCID 0000-0003-4451-9608Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Organism:human· 2 Assay:protein structure· 2 Approach:machine learning (classical)· 1 Organism:mouse· 1 Research Focus:protein structure prediction· 1 Approach:simulation· 1 Approach:statistical model· 1

Frequent Co-Authors

Gregory A. BabbittiD· 3 shared Maureen C. FerraniD· 2 shared Eric T. Everingham· 1 shared Leora Mouli· 1 shared Miranda L. LynchiD· 1 shared

Activity by Year

2021-2022 · peak 2/yr

Co-Author Collaboration Network

5 top collaborators · 10 mutual co-author links

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3 shared papersBioinformatics

Gregory A. BabbittORCID

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3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintNov 22, 2022

Evolution of drug resistance drives progressive destabilizations in functionally conserved molecular dynamics of the flap region of the HIV-1 protease

Madhusudan Rajendran, Maureen C. Ferran, Leora Mouli…·Miranda L. Lynch

The paper uses machine learning and molecular dynamics to analyze how drug-resistant mutations in HIV-1 protease affect flap region dynamics and function.

DOI 10.1101/2022.11.22.517502

humanprotein structure

𝕏 PostBluesky

BioinformaticsRoyal Society Open SciencePeer-reviewedNov 1, 2022

Persistent cross-species SARS-CoV-2 variant infectivity predicted via comparative molecular dynamics simulation

Madhusudan Rajendran, Gregory A. Babbitt

The paper uses molecular dynamics simulations to assess cross-species infectivity of SARS-CoV-2 variants between humans and bats, finding that some variants retain significant binding affinity to bat ACE2.

12 citations

humanmouse

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BioinformaticsbioRxivPreprintDec 6, 2021

Identifying protein sites contributing to vaccine escape via statistical comparisons of short-term molecular dynamics simulations

Madhusudan Rajendran, Maureen C. Ferran, Gregory A. Babbitt

The paper identifies protein sites contributing to vaccine escape by comparing molecular dynamics simulations of viral antigens with and without antibodies.

DOI 10.1101/2021.12.06.471374

protein structurestatistical model

𝕏 PostBluesky