Author

Charles A. Laughton

University of NottinghamORCID 0000-0003-4090-3960Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:experimental assay· 1 Assay:protein structure· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1

Frequent Co-Authors

Andrei LeitãoiD· 1 shared Andrew D. YatesiD· 1 shared Athina MeletiouiD· 1 shared Brian Jiménez‐GarcíaiD· 1 shared Carlos Alberto MontanariiD· 1 shared David CastilloiD· 1 shared Diana BuitragoiD· 1 shared Dmitry RepchevskyiD· 1 shared

Activity by Year

2019-2019 · peak 2/yr

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10 top collaborators · 24 mutual co-author links

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1 shared paperBioinformatics

Andrei LeitãoORCID

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2 papers

Recent·Most cited

BioinformaticsPLoS ONEPeer-reviewedDec 19, 2019

Ligand-induced Conformational Selection Predicts the Selectivity of Cysteine Protease Inhibitors

G. Sartori, Andrei Leitão, Carlos Alberto Montanari, Charles A. Laughton

The paper uses molecular dynamics simulations to predict the selectivity of cysteine protease inhibitors by analyzing ligand-induced conformational changes.

12 citations

protein structurestatistical model

𝕏 PostBluesky

BioinformaticsbioRxivPreprintApr 9, 2019

MuGVRE. A virtual research environment for 3D/4D genomics

Laia Codó, Genís Bayarri, J. Álvarez Cid-Fuentes…·Josep Lluis Gelpí

MuGVRE provides a cloud-based infrastructure for 3D/4D genomics analysis, supporting both high-computational and high-throughput applications.

2 citations

experimental assay

𝕏 PostBluesky