Author

K. Ngo

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· 2 Bioengineering· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:deep learning· 2 Assay:protein structure· 2 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1 Research Focus:protein folding & dynamics· 1 Assay:proteomics· 1

Frequent Co-Authors

C. E. Clancy· 2 shared I. Vorobyov· 2 shared V. Yarov-Yarovoy· 2 shared A. Goncharov· 1 shared A. O' Kula· 1 shared A. Ozcan· 1 shared B. Palanisamy· 1 shared D. Di Carlo· 1 shared

Activity by Year

2023-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersBiophysics

C. E. Clancy

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Harnessing AlphaFold to reveal hERG channel conformational state secrets

K. Ngo, P.-C. Yang, V. Yarov-Yarovoy, C. E. Clancy, I. Vorobyov

This paper uses AlphaFold to predict discrete conformational states of hERG channels, revealing structural features and drug interactions that improve drug safety screening.

bioRxiv · Jan 27, 2024Biophysics

Single-tier point-of-care serodiagnosis of Lyme disease

R. Ghosh, H.-A. Joung, A. Goncharov, B. Palanisamy, K. Ngo, K. Pejcinovic, N. Krockenberger, E. J. Horn, O. B. Garner, E. Ghazal, A. O' Kula, P. M. Arnaboldi, R. J. Dattwyler, A. Ozcan, D. Di Carlo

This paper develops a single-tier point-of-care serodiagnostic test for Lyme disease using synthetic peptides and machine learning, achieving sensitivity and specificity comparable to traditional two-tier lab tests.

bioRxiv · Jun 14, 2023 · PreprintBioengineering

Elucidating Molecular Mechanisms of Protoxin-2 State-specific Binding to the Human NaV1.7 Channel

K. Ngo, D. L. Mateos, Y. Han, K. C. Rouen, S.-H. Ahn, H. Wulff, C. E. Clancy, V. Yarov-Yarovoy, I. Vorobyov

This study uses computational modeling to investigate how protoxin-2 binds to different states of the hNaV1.7 channel, identifying key residues and lipid interactions that contribute to its selectivity.

bioRxiv · Feb 27, 2023Biophysics