Author

L. F. Milles

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· 5 Biochemistry· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 4 Research Focus:protein design· 4 Approach:experimental assay· 3 Research Focus:host-pathogen & immune response· 3 Organism:human· 3 Assay:protein sequence· 3 Assay:protein structure· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

D. Baker· 4 shared J. Dauparas· 4 shared A. Kang· 3 shared B. I. M. Wicky· 3 shared H. E. Gaub· 3 shared J. Lipfert· 3 shared M. S. Bauer· 3 shared S. Gruber· 3 shared

Activity by Year

2020-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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4 shared papersBiochemistry

D. Baker

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Author profile →

7 papers

Recent·Most cited

Improving protein expression, stability, and function with ProteinMPNN

K. H. Sumida, R. Nunez Franco, I. Kalvet, S. J. Pellock, B. I. M. Wicky, L. F. Milles, J. Dauparas, J. Wang, Y. Kipnis, N. Jameson, A. Kang, J. De La Cruz, B. Sankaran, A. K. Bera, G. Jimenez Oses, D. Baker

This paper introduces ProteinMPNN, a deep learning model that improves protein expression, stability, and function by incorporating evolutionary and structural information.

bioRxiv · Oct 3, 2023Biochemistry

Effects of Variants of Concern Mutations on the Force-Stability of the SARS-CoV-2:ACE2 Interface and Virus Transmissibility

M. S. Bauer, S. Gruber, A. Hausch, M. C. R. Melo, P. S. F. C. Gomes, T. Nicolaus, L. F. Milles, R. C. Bernardi, H. E. Gaub, J. Lipfert

This study examines how mutations in SARS-CoV-2 variants affect the force-stability of the SARS-CoV-2:ACE2 interface and virus transmissibility.

bioRxiv · Jan 6, 2023 · PreprintBiophysics

Hallucinating protein assemblies

B. I. M. Wicky, L. F. Milles, A. Courbet, R. J. Ragotte, J. Dauparas, E. Kinfu, S. Tipps, R. D. Kibler, M. Baek, F. DiMaio, X. Li, L. Carter, A. Kang, H. Nguyen, A. K. Bera, D. Baker

Deep network-based protein design generates symmetric homo-oligomers with high structural accuracy, demonstrating the potential for creating novel nanomachines and biomaterials.

Science · Oct 7, 2022Peer-reviewedBiophysics

Robust deep learning based protein sequence design using ProteinMPNN

J. Dauparas, I. Anishchenko, N. Bennett, H. Bai, R. J. Ragotte, L. F. Milles, B. I. M. Wicky, A. Courbet, R. J. de Haas, N. Bethel, P. J. Y. Leung, T. F. Huddy, S. Pellock, D. Tischer, F. Chan, , D. Baker

A deep learning method for protein sequence design shows high performance in both simulations and experiments, applicable to various design challenges.

bioRxiv · Jun 3, 2022Biophysics

Deep learning methods for designing proteins scaffolding functional sites

J. Wang, S. Lisanza, D. Juergens, D. Tischer, I. Anishchenko, M. Baek, J. L. Watson, J.-H. Chun, L. F. Milles, J. Dauparas, M. Exposit, W. Yang, A. Saragovi, S. Ovchinnikov, D. Baker

This paper introduces two deep learning methods for designing proteins with specific functional sites, showing they can generate diverse proteins with desired properties.

bioRxiv · Nov 10, 2021Biochemistry

A Tethered Ligand Assay to Probe SARS-CoV-2:ACE2 Interactions

M. S. Bauer, S. Gruber, A. Hausch, L. F. Milles, T. Nicolaus, L. C. Schendel, P. Lopez Navajas, E. Procko, D. Lietha, R. C. Bernardi, H. E. Gaub, J. Lipfert

This paper introduces a tethered ligand assay to study SARS-CoV-2:ACE2 interactions under mechanical force, showing higher stability and lower dissociation rates compared to SARS-CoV-1.

bioRxiv · Aug 8, 2021 · PreprintBiophysics

A Tethered Ligand Assay to Probe the SARS-CoV-2 ACE2 Interaction under Constant Force

M. S. Bauer, S. Gruber, L. F. Milles, T. Nicolaus, L. C. Schendel, H. E. Gaub, J. Lipfert

This paper introduces a tethered ligand assay to study SARS-CoV-2 ACE2 interactions under constant force and finds that the interaction is more mechanically stable and has a slower off-rate compared to SARS-CoV-1.

bioRxiv · Sep 27, 2020 · PreprintBiophysics