Computational optimization of antibody humanness and stability by systematic energy-based ranking

Tennenhouse A., Khmelnitsky L., Khalaila R., Yeshaya N., Noronha A., Lindzen M., Makowski E. K., Zaretsky I., Sirkis Y. F., Galon-Wolfenson Y., Tessier P. M., Abramson J., Yarden Y., Fass D. & Fleishman S. J. (2024) Nature Biomedical Engineering. 8, p. 30-44

Preclinical Development of a Stabilized RH5 Virus-Like Particle Vaccine that Induces Improved Anti-Malarial Antibodies

King L. D. W., Pulido D., Barrett J. R., Davies H., Quinkert D., Lias A. M., Silk S. E., Pattinson D. J., Diouf A., Williams B. G., McHugh K., Rodrigues A., Rigby C. A., Strazza V., Suurbaar J., Rees-Spear C., Dabbs R. A., Ishizuka A. S., Zhou Y., Gupta G., Jin J., Li Y., Carnrot C., Minassian A. M., Campeotto I., Fleishman S. J., Noe A. R., MacGill R. S., King C. R., Birkett A. J., Soisson L. A., Long C. A., Miura K., Ashfield R., Skinner K., Howarth M., Biswas S. & Draper S. J. (2024) BioRxiv.

Functionally Diverse Peroxygenases by AlphaFold2, Design, and Signal Peptide Shuffling

Münch J., Dietz N., Barber-Zucker S., Seifert F., Matschi S., Püllmann P., Fleishman S. J. & Weissenborn M. J. (2024) ACS Catalysis. 14, 7, p. 4738-4748

Opportunities and challenges in design and optimization of protein function

Listov D., Goverde C. A., Correia B. E. & Fleishman S. J. (2024) Nature Reviews Molecular Cell Biology.


Combinatorial assembly and design of enzymes

Lipsh-Sokolik R., Khersonsky O., Schröder S. P., de Boer C., Hoch S., Davies G. J., Overkleeft H. S. & Fleishman S. J. (2023) Science (American Association for the Advancement of Science). 379, 6628, p. 195-201

Repertoire of Computationally Designed Peroxygenases for Enantiodivergent C-H Oxyfunctionalization Reactions

Gomez de Santos P., Mateljak I., Hoang M. D., Fleishman S. J., Hollmann F. & Alcalde M. (2023) Journal of the American Chemical Society. 145, 6, p. 3443-3453

Design of a stable human acid-β-glucosidase: towards improved Gaucher disease therapy and mutation classification

Pokorna S., Khersonsky O., Lipsh-Sokolik R., Goldenzweig A., Nielsen R., Ashani Y., Peleg Y., Unger T., Albeck S., Dym O., Tirosh A., Tarayra R., Hocquemiller M., Laufer R., Ben-Dor S., Silman I., Sussman J. L., Fleishman S. J. & Futerman A. H. (2023) The FEBS journal. 290, 13, p. 3383-3399

Computational design and molecular dynamics simulations suggest the mode of substrate binding in ceramide synthases

Zelnik I. D., Mestre B., Weinstein J. J., Dingjan T., Izrailov S., Ben-Dor S., Fleishman S. J. & Futerman A. H. (2023) Nature Communications. 14, 1, 2330.

Designed active-site library reveals thousands of functional GFP variants

Weinstein J. Y., Martí-Gómez C., Lipsh-Sokolik R., Hoch S. Y., Liebermann D., Nevo R., Weissman H., Petrovich-Kopitman E., Margulies D., Ivankov D., McCandlish D. M. & Fleishman S. J. (2023) Nature Communications. 14, 2890.

Computational design of BclxL inhibitors that target transmembrane domain interactions

Duart G., Elazar A., Weinstein J. Y., Gadea-Salom L., Ortiz-Mateu J., Fleishman S. J., Mingarro I. & Martinez-Gil L. (2023) Proceedings of the National Academy of Sciences - PNAS. 120, 11, p. e2219648120-e2219648120

Stable Mammalian Serum Albumins Designed for Bacterial Expression

Khersonsky O., Goldsmith M., Zaretsky I., Hamer-Rogotner S., Dym O., Unger T., Yona M., Fridmann-Sirkis Y. & Fleishman S. J. (2023) Journal of Molecular Biology. 435, 17, 168191.

Allosteric regulation of the 20S proteasome by the Catalytic Core Regulators (CCRs) family

Deshmukh F. K., Ben-Nissan G., Olshina M. A., Füzesi-Levi M. G., Polkinghorn C., Arkind G., Leushkin Y., Fainer I., Fleishman S. J., Tawfik D. & Sharon M. (2023) Nature Communications. 14, 3126.

The C-terminal tail of CSNAP attenuates the CSN complex

Füzesi-Levi M. G., Ben-Nissan G., Listov D., Fridmann Sirkis Y., Hayouka Z., Fleishman S. & Sharon M. (2023) Life Science Alliance. 6, 10, e202201634.


Computationally designed dual-color MRI reporters for noninvasive imaging of transgene expression

Allouche-Arnon H., Khersonsky O., Tirukoti N. D., Peleg Y., Dym O., Albeck S., Brandis A., Mehlman T., Avram L., Harris T., Yadav N. N., Fleishman S. J. & Bar-Shir A. (2022) Nature biotechnology. 40, 7, p. 1143-1149

Structure and receptor recognition by the Lassa virus spike complex

Katz M., Weinstein J., Eilon-Ashkenazy M., Gehring K., Cohen-Dvashi H., Elad N., Fleishman S. J. & Diskin R. (2022) Nature. 603, 7899, p. 174-179

Stable and Functionally Diverse Versatile Peroxidases Designed Directly from Sequences

Barber-Zucker S., Mindel V., Garcia-Ruiz E., Weinstein J. J., Alcalde M. & Fleishman S. J. (2022) Journal of the American Chemical Society. 144, 8, p. 3564-3571

What Have We Learned from Design of Function in Large Proteins?

Khersonsky O. & Fleishman S. J. (2022) BioDesign Research. 2022, 9787581.

Computer-aided engineering of staphylokinase toward enhanced affinity and selectivity for plasmin

Nikitin D., Mican J., Toul M., Bednar D., Peskova M., Kittova P., Thalerova S., Vitecek J., Damborsky J., Mikulik R., Fleishman S. J., Prokop Z. & Marek M. (2022) Computational and Structural Biotechnology Journal. 20, p. 1366-1377

Highly Specific Monoclonal Antibody Targeting the Botulinum Neurotoxin Type E Exposed SNAP-25 Neoepitope

Mechaly A., Diamant E., Alcalay R., Ben David A., Dor E., Torgeman A., Barnea A., Girshengorn M., Levin L., Epstein E., Tennenhouse A., Fleishman S. J., Zichel R. & Mazor O. (2022) Antibodies (Basel). 11, 1, 21.

Stabilization of the SARS-CoV-2 receptor binding domain by protein core redesign and deep mutational scanning

Leonard A. C., Weinstein J. J., Steiner P. J., Erbse A. H., Fleishman S. J. & Whitehead T. A. (2022) Protein Engineering, Design and Selection. 35, gzac002.

De novo-designed transmembrane domains tune engineered receptor functions

Elazar A., Chandler N. J., Davey A. S., Weinstein J. Y., Nguyen J. V., Trenker R., Cross R. S., Jenkins M. R., Call M. J., Call M. E. & Fleishman S. J. (2022) eLife. 11, e75660.

Computationally designed hyperactive Cas9 enzymes

D V. P., Giulia R., L M. J., J S. S., P G. A., Mitchell B., A R. S., Olga K., J F. S., Aleksandra F. & Oliver R. (2022) Nature Communications. 13, 3023.

Assessing and enhancing foldability in designed proteins

Listov D., Lipsh R., Rosset S. R., Yang C., Correia B. E. & Fleishman S. (2022) Protein science : a publication of the Protein Society. 31, 9, e4400.

Protein quaternary structures in solution are a mixture of multiple forms

Marciano S., Dey D., Listov D., Fleishman S. J., Sonn-Segev A., Mertens H., Busch F., Kim Y., Harvey S. R., Wysocki V. H. & Schreiber G. (2022) Chemical science (Cambridge). 13, 39, p. 11680-11695

Anti-SARS-CoV-2 immunoadhesin remains effective against Omicron and other emerging variants of concern

Cohen-Dvashi H., Weinstein J., Katz M., Ashkenazy-Eilon M., Mor Y., Shimon A., Achdout H., Tamir H., Israely T., Strobelt R., Shemesh M., Stoler-Barak L., Shulman Z., Paran N., Fleishman S. J. & Diskin R. (2022) iScience. 25, 10, 105193.

Designed High-Redox Potential Laccases Exhibit High Functional Diversity

Barber-Zucker S., Mateljak I., Goldsmith M., Kupervaser M., Alcalde M. & Fleishman S. J. (2022) ACS Catalysis. 12, 21, p. 13164-13173

Enhancing the Thermal and Kinetic Stability of Ketol-Acid Reductoisomerase, a Central Catalyst of a Cell-Free Enzyme Cascade for the Manufacture of Platform Chemicals

Lv Y., Zheng S., Goldenzweig A., Liu F., Gao Y., Yang X., Kandale A., McGeary R. P., Williams S., Kobe B., Schembri M. A., Landsberg M. J., Wu B., Brück T. B., Sieber V., Boden M., Rao Z., Fleishman S. J., Schenk G. & Guddat L. W. (2022) Applied Biosciences. 1, 2, p. 163-178


Local Mutations Can Serve as a Game Changer for Global Protein Solvent Interaction

Adams E. M., Pezzotti S., Ahlers J., Rüttermann M., Levin M., Goldenzweig A., Peleg Y., Fleishman S. J., Sagi I. & Havenith M. (2021) JACS Au. 1, 7, p. 1076-1085

A Rationally and Computationally Designed Fluorescent Biosensor for D-Serine

Vongsouthi V., Whitfield J. H., Unichenko P., Mitchell J. A., Breithausen B., Khersonsky O., Kremers L., Janovjak H., Monai H., Hirase H., Fleishman S. J., Henneberger C. & Jackson C. J. (2021) ACS Sensors. 6, 11, p. 4193-4205

Obituary: Dan S Tawfik (1955–2021)

Aharoni A. & Fleishman S. J. (2021) The FEBS journal. 288, 13, p. 3880-3883

The neutralization potency of anti-SARS-CoV-2 therapeutic human monoclonal antibodies is retained against viral variants

Makdasi E., Zvi A., Alcalay R., Noy-Porat T., Peretz E., Mechaly A., Levy Y., Epstein E., Chitlaru T., Tennenhouse A., Aftalion M., Gur D., Paran N., Tamir H., Zimhony O., Weiss S., Mandelboim M., Mendelson E., Zuckerman N., Nemet I., Kliker L., Yitzhaki S., Shapira S. C., Israely T., Fleishman S. J., Mazor O. & Rosenfeld R. (2021) Cell reports (Cambridge). 36, 10, 109679.

Computational Enzyme Engineering Pipelines for Optimized Production of Renewable Chemicals

Scherer M., Fleishman S. J., Jones P. R., Dandekar T. & Bencurova E. (2021) Frontiers in Bioengineering and Biotechnology. 9, 673005.

The AbDesign computational pipeline for modular backbone assembly and design of binders and enzymes

Lipsh‐Sokolik R., Listov D. & Fleishman S. J. (2021) Protein Science. 30, 1, p. 151-159

Community-Wide Experimental Evaluation of the PROSS Stability-Design Method

Peleg Y., Vincentelli R., Collins B. M., Chen K., Livingstone E. K., Weeratunga S., Leneva N., Guo Q., Remans K., Perez K., Bjerga G. E., Larsen Ø., Vaněk O., Skořepa O., Jacquemin S., Poterszman A., Kjaer S., Christodoulou E., Albeck S., Dym O., Ainbinder E., Unger T., Schuetz A., Matthes S., Bader M., de Marco A., Storici P., Semrau M. S., Stolt-Bergner P., Aigner C., Suppmann S., Goldenzweig A. & Fleishman S. J. (2021) Journal of Molecular Biology. 433, 13, 166964.

Extending the New Generation of Structure Predictors to Account for Dynamics and Allostery

Fleishman S. J. & Horovitz A. (2021) Journal of Molecular Biology. 433, 20, 167007.

PROSS 2: a new server for the design of stable and highly expressed protein variants

Weinstein J. J., Goldenzweig A., Hoch S. & Fleishman S. J. (2021) Bioinformatics (Oxford, England). 37, 1, p. 123-125

Computationally designed pyocyanin demethylase acts synergistically with tobramycin to kill recalcitrant Pseudomonas aeruginosa biofilms

VanDrisse C. M., Lipsh-Sokolik R., Khersonsky O., Fleishman S. J. & Newman D. K. (2021) Proceedings of the National Academy of Sciences - PNAS. 118, 12, e202201211.

Biomolecular Recognition of the Glycan Neoantigen CA19-9 by Distinct Antibodies

Borenstein-Katz A., Warszawski S., Amon R., Eilon M., Cohen-Dvashi H., Leviatan Ben-Arye S., Tasnima N., Yu H., Chen X., Padler-Karavani V., Fleishman S. J. & Diskin R. (2021) Journal of Molecular Biology. 433, 15, 167099.


Design of a basigin-mimicking inhibitor targeting the malaria invasion protein RH5

Warszawski S., Dekel E., Campeotto I., Marshall J. M., Wright K. E., Lyth O., Knop O., Regev-Rudzki N., Higgins M. K., Draper S. J., Baum J. & Fleishman S. J. (2020) Proteins-Structure Function And Bioinformatics. 88, 1, p. 187-195

Practically useful protein-design methods combining phylogenetic and atomistic calculations

Weinstein J., Khersonsky O. & Fleishman S. J. (2020) Current Opinion in Structural Biology. 63, p. 58-64

One-step sequence and structure-guided optimization of HIV-1 envelope gp140

Malladi S. K., Schreiber D., Pramanick I., Sridevi M. A., Goldenzweig A., Dutta S., Fleishman S. J. & Varadarajan R. (2020) Current Research in Structural Biology. 2, p. 45-55


AbPredict 2: a server for accurate and unstrained structure prediction of antibody variable domains

Lapidoth G., Parker J., Prilusky J. & Fleishman S. J. (2019) Bioinformatics. 35, 9, p. 1591-1593

Optimizing antibody affinity and stability by the automated design of the variable light-heavy chain interfaces

Warszawski S., Katz A. B., Lipsh R., Khmelnitsky L., Ben Nissan G., Javitt G., Dym O., Unger T., Knop O., Albeck S., Diskin R., Fass D., Sharon M. & Fleishman S. J. (2019) PLoS Computational Biology. 15, 8, e1007207.

A lipophilicity-based energy function for membrane-protein modelling and design

Weinstein J. Y., Elazar A. & Fleishman S. J. (2019) PLoS Computational Biology. 15, 8, e1007318.


Highly active enzymes by automated combinatorial backbone assembly and sequence design

Lapidoth G., Khersonsky O., Lipsh R., Dym O., Albeck S., Rogotner S. & Fleishman S. J. (2018) Nature Communications. 9, 2780.

A combined computational-experimental approach to define the structural origin of antibody recognition of sialyl-Tn, a tumor-associated carbohydrate antigen

Amon R., Grant O. C., Ben-Arye S. L., Makeneni S., Nivedha A. K., Marshanski T., Norn C., Yu H., Glushka J. N., Fleishman S. J., Chen X., Woods R. J. & Padler-Karavani V. (2018) Scientific Reports. 8, 10786.

Manipulating the Folding Landscape of a Multi-Domain Protein

Kantaev R., Riven I., Goldenzweig A., Barak Y., Dym O., Peleg Y., Albeck S., Fleishman S. J. & Haran G. (2018) Journal of Physical Chemistry B. 122, 49, p. 11030-11038

Estimating Interprotein Pairwise Interaction Energies in Cell Lysates from a Single Native Mass Spectrum

Cveticanin J., Netzer R., Arkind G., Fleishman S. J., Horovitz A. & Sharon M. (2018) Analytical Chemistry. 90, 17, p. 10090-10094

Automated Design of Efficient and Functionally Diverse Enzyme Repertoires

Khersonsky O., Lipsh R., Avizemer Z., Ashani Y., Goldsmith M., Leader H., Dym O., Rogotner S., Trudeau D. L., Prilusky J., Amengual-Rigo P., Guallar V., Tawfik D. S. & Fleishman S. J. (2018) Molecular Cell. 72, 1, p. 178-186.e5

Ultrahigh specificity in a network of computationally designed protein-interaction pairs

Netzer R., Listov D., Lipsh R., Dym O., Albeck S., Knop O., Kleanthous C. & Fleishman S. J. (2018) Nature Communications. 9, 1, 5286.

Design and in vitro realization of carbon-conserving photorespiration

Trudeau D. L., Edlich-Muth C., Zarzycki J., Scheffen M., Goldsmith M., Khersonsky O., Avizemer Z., Fleishman S. J., Cotton C. A. R., Erb T. J., Tawfik D. S. & Bar-Even A. (2018) Proceedings Of The National Academy Of Sciences Of The United States Of America-Physical Sciences. 115, 49, p. E11455-E11464

Rapid characterization of secreted recombinant proteins by native mass spectrometry

Ben-Nissan G., Vimer S., Warszawski S., Katz A., Yona M., Unger T., Peleg Y., Morgenstern D., Cohen-Dvashi H., Diskin R., Fleishman S. J. & Sharon M. (2018) Communications Biology. 1, 213.

Principles of Protein Stability and Their Application in Computational Design

Goldenzweig A. & Fleishman S. J. (2018) Annual Review of Biochemistry. 87, p. 105-129


One-step design of a stable variant of the malaria invasion protein RH5 for use as a vaccine immunogen

Campeotto I., Goldenzweig A., Davey J., Barfod L., Marshall J. M., Silk S. E., Wright K. E., Draper S. J., Higgins M. K. & Fleishman S. J. (2017) Proceedings of the National Academy of Sciences of the United States of America. 114, 5, p. 998-1002

High-accuracy modeling of antibody structures by a search for minimum-energy recombination of backbone fragments

Norn C. H., Lapidoth G. & Fleishman S. J. (2017) Proteins-Structure Function And Bioinformatics. 85, 1, p. 30-38

Collective repacking reveals that the structures of protein cores are uniquely specified by steric repulsive interactions

Gaines J. C., Virrueta A., Buch D. A., Fleishman S. J., O'Hern C. S. & Regan L. (2017) Protein Engineering, Design and Selection. 30, 5, p. 387-394

Overcoming an optimization plateau in the directed evolution of highly efficient nerve agent bioscavengers

Goldsmith M., Aggarwal N., Ashani Y., Jubran H., Greisen P. J., Ovchinnikov S., Leader H., Baker D., Sussman J., Goldenzweig A., Fleishman S. J. & Tawfik D. (2017) Protein Engineering, Design and Selection. 30, 4, p. 333-345

Principles for computational design of binding antibodies

Baran D., Pszolla M. G., Lapidoth G. D., Norn C., Dym O., Unger T., Albeck S., Tyka M. D. & Fleishman S. J. (2017) Proceedings of the National Academy of Sciences of the United States of America. 114, 41, p. 10900-10905

Incorporating an allosteric regulatory site in an antibody through backbone design

Khersonsky O. & Fleishman S. J. (2017) Protein Science. 26, 4, p. 807-813

Local energetic frustration affects the dependence of green fluorescent protein folding on the chaperonin GroEL

Bandyopadhyay B., Goldenzweig A., Unger T., Adato O., Fleishman S. J., Unger R. & Horovitz A. (2017) Journal of Biological Chemistry. 292, 50, p. 20583-20591

Improved antibody-based ricin neutralization by affinity maturation is correlated with slower off-rate values

Rosenfeld R., Alcalay R., Mechaly A., Lapidoth G., Epstein E., Kronman C., Fleishman S. J. & Mazor O. (2017) Protein Engineering, Design and Selection. 30, 9, p. 611-617


Mutational scanning reveals the determinants of protein insertion and association energetics in the plasma membrane

Assaf E., Weinstein J., Biran I., Fridman Y., Bibi E. & Fleishman S. (2016) eLife. 5, JANUARY2016, e12125.

Overcoming a species-specificity barrier in development of an inhibitory antibody targeting a modulator of tumor stroma

Grossman I., Ilani T., Fleishman S. & Fass D. (2016) Protein engineering, design & selection : PEDS. 29, 4, p. 135-147

Why reinvent the wheel? Building new proteins based on ready-made parts

Khersonsky O. & Fleishman S. J. (2016) Protein Science. p. 1179-1187

Automated Structure- and Sequence-Based Design of Proteins for High Bacterial Expression and Stability

Goldenzweig A., Goldsmith M., Hill S. E., Gertman O., Laurino P., Ashani Y., Dym O., Unger T., Albeck S., Prilusky J., Lieberman R. L., Aharoni A., Silman I., Sussman J., Tawfik D. & Fleishman S. J. (2016) Molecular Cell. 63, 2, p. 337-346

Interplay between hydrophobicity and the positiveinside rule in determining membrane-protein topology

Assaf E., Weinstein J. J., Prilusky J. & Fleishman S. (2016) Proceedings of the National Academy of Sciences of the United States of America. 113, 37, p. 10340-10345


AbDesign: An algorithm for combinatorial backbone design guided by natural conformations and sequences

Lapidoth G., Baran D., Pszolla G., Norn C., Alon A., Tyka M. & Fleishman S. (2015) Proteins-Structure Function And Bioinformatics. 83, 8, p. 1385-1406

Dominant Mutations in the Autoimmune Regulator AIRE Are Associated with Common Organ-Specific Autoimmune Diseases

Oftedal B., Hellesen A., Erichsen M., Bratland E., Vardi A., Perheentupa J., Kemp E., Fiskerstrand T., Viken M., Weetman A., Fleishman S., Banka S., Newman W., Sewell W., Sozaeva L., Zayats T., Haugarvoll K., Orlova E., Haavik J., Johansson S., Knappskog P., Lovas K., Wolff A., Abramson J. & Husebye E. (2015) Immunity. 42, 6, p. 1185-1196

Combined crystal structure of a type I cohesin: Mutation and affinity binding studies reveal structural determinants of Cohesin-dockerin specificities

Cameron K., Weinstein J., Zhivin O., Bule P., Fleishman S., Alves V., Gilbert H., Ferreira L., Fontes C., Bayer E. & Najmudin S. (2015) Journal of Biological Chemistry. 290, 26, p. 16215-16225

Editorial overview: Protein design and evolution-new protein architectures, evolutionary fine-tuning and analysis

Fleishman S. J. & Pluckthun A. (2015) Current Opinion in Structural Biology. 33, p. v-vi


A "fuzzy"-logic language for encoding multiple physical traits in biomolecules

Warszawski S., Netzer R., Tawfik D. S. & Fleishman S. J. (2014) Journal of Molecular Biology. 426, 24, p. 4125-4138

Computational design of a pH-sensitive IgG binding protein

Strauch E. M., Fleishman S. J. & Baker D. (2014) Proceedings of the National Academy of Sciences of the United States of America. 111, 2, p. 675-680


Computational protein design suggests that human PCNA-partner interactions are not optimized for affinity

Fridman Y., Gur E., Fleishman S. J. & Aharoni A. (2013) Proteins: Structure, Function and Bioinformatics. 81, 2, p. 341-348

Computational design of novel protein binders and experimental affinity maturation

Whitehead T. A., Baker D. & Fleishman S. J. (2013) Methods in Protein Design . p. 1-19

Computational design of a protein-based enzyme inhibitor

Procko E., Hedman R., Hamilton K., Seetharaman J., Fleishman S. J., Su M., Aramini J., Kornhaber G., Hunt J. F., Tong L., Montelione G. T. & Baker D. (2013) Journal of Molecular Biology. 425, 18, p. 3563-3575

Computational design of protein-protein interactions

Schreiber G. & Fleishman S. J. (2013) Current Opinion in Structural Biology. 23, 6, p. 903-910

Emerging themes in the computational design of novel enzymes and protein-protein interfaces

Khare S. D. & Fleishman S. J. (2013) FEBS Letters. 587, 8, p. 1147-1154

Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions

Moretti R., Fleishman S. J., Agius R., Torchala M., Bates P. A., Kastritis P. L., Rodrigues J. P. G. L. M., Trellet M., Bonvin A. M. J. J., Cui M., Rooman M., Gillis D., Dehouck Y., Moal I., Romero-Durana M., Perez-Cano L., Pallara C., Jimenez B. & Fernandez-Recio J. (2013) Proteins-Structure Function And Bioinformatics. 81, 11, p. 1980-1987


Structure of the ultra-high-affinity colicin E2 DNase-Im2 complex

Wojdyla J. A., Fleishman S. J., Baker D. & Kleanthous C. (2012) Journal of Molecular Biology. 417, 1-2, p. 79-94

Optimization of affinity, specificity and function of designed influenza inhibitors using deep sequencing

Whitehead T. A., Chevalier A., Song Y., Dreyfus C., Fleishman S. J., De Mattos C., Myers C. A., Kamisetty H., Blair P., Wilson I. A. & Baker D. (2012) Nature Biotechnology. 30, 6, p. 543-548

Role of the biomolecular energy gap in protein design, structure, and evolution

Fleishman S. J. & Baker D. (2012) Cell. 149, 2, p. 262-273


Community-wide assessment of protein-interface modeling suggests improvements to design methodology

Fleishman S. J., Whitehead T. A., Strauch E., Corn J. E., Qin S., Zhou H., Mitchell J. C., Demerdash O. N. A., Takeda-Shitaka M., Terashi G., Moal I. H., Li X., Bates P. A., Zacharias M., Park H., Ko J., Lee H., Seok C., Bourquard T., Bernauer J., Poupon A., Aze J., Soner S., Ovali S. K., Ozbek P., Ben Tal N., Haliloglu T., Hwang H., Vreven T., Pierce B. G., Weng Z., Perez-Cano L., Pons C., Fernandez-Recio J., Jiang F., Yang F., Gong X., Cao L., Xu X., Liu B., Wang P., Li C., Wang C., Robert C. H., Guharoy M., Liu S., Huang Y., Li L., Guo D., Chen Y., Xiao Y., London N., Itzhaki Z., Schueler-Furman O., Inbar Y., Potapov V., Cohen M., Schreiber G., Tsuchiya Y., Kanamori E., Standley D. M., Nakamura H., Kinoshita K., Driggers C. M., Hall R. G., Morgan J. L., Hsu V. L., Zhan J., Yang Y., Zhou Y., Kastritis P. L., Bonvin A. M. J. J., Zhang W., Camacho C. J., Kilambi K. P., Sircar A., Gray J. J., Ohue M., Uchikoga N., Matsuzaki Y., Ishida T., Akiyama Y., Khashan R., Bush S., Fouches D., Tropsha A., Esquivel-Rodriguez J., Kihara D., Stranges P. B., Jacak R., Kuhlman B., Huang S., Zou X., Wodak S. J., Janin J. & Baker D. (2011) Journal of Molecular Biology. 414, 2, p. 289-302

Computational design of proteins targeting the conserved stem region of influenza hemagglutinin

Fleishman S. J., Whitehead T. A., Ekiert D. C., Dreyfus C., Corn J. E., Strauch E. M., Wilson I. A. & Baker D. (2011) Science. 332, 6031, p. 816-821

Restricted sidechain plasticity in the structures of native proteins and complexes

Fleishman S. J., Khare S. D., Koga N. & Baker D. (2011) Protein Science. 20, 4, p. 753-757

Rosettascripts: A scripting language interface to the Rosetta Macromolecular modeling suite

Fleishman S. J., Leaver-Fay A., Corn J. E., Strauch E. M., Khare S. D., Koga N., Ashworth J., Murphy P., Richter F., Lemmon G., Meiler J. & Baker D. (2011) PLoS ONE. 6, 6, e20161.

Hotspot-centric de novo design of protein binders

Fleishman S. J., Corn J. E., Strauch E. M., Whitehead T. A., Karanicolas J. & Baker D. (2011) Journal of Molecular Biology. 413, 5, p. 1047-1062

Rosetta3: An object-oriented software suite for the simulation and design of macromolecules

Leaver-Fay A., Tyka M., Lewis S. M., Lange O. F., Thompson J., Jacak R., Kaufman K., Renfrew P. D., Smith C. A., Sheffler W., Davis I. W., Cooper S., Treuille A., Mandell D. J., Richter F., Ban Y. E. A., Fleishman S. J., Corn J. E., Kim D. E., Lyskov S., Berrondo M., Mentzer S., Popović Z., Havranek J. J., Karanicolas J., Das R., Meiler J., Kortemme T., Gray J. J., Kuhlman B., Baker D. & Bradley P. (2011) Computer Methods : Part C . C ed. Vol. C. p. 545-574


High-resolution mapping of protein sequence-function relationships

Fowler D. M., Araya C. L., Fleishman S. J., Kellogg E. H., Stephany J. J., Baker D. & Fields S. (2010) Nature Methods. 7, 9, p. 741-746

Rosetta in CAPRI rounds 13-19

Fleishman S. J., Corn J. E., Strauch E. M., Whitehead T. A., Andre I., Thompson J., Havranek J. J., Das R., Bradley P. & Baker D. (2010) Proteins: Structure, Function and Bioinformatics. 78, 15, p. 3212-3218

The structural and energetic basis for high selectivity in a high-affinity protein-protein interaction

Meenan N. A., Sharma A., Fleishman S. J., MacDonald C. J., Morel B., Boetzel R., Moore G. R., Baker D. & Kleanthous C. (2010) Proceedings of the National Academy of Sciences of the United States of America. 107, 22, p. 10080-10085


A New Twist in TCR Diversity Revealed by a Forbidden αβ TCR

McBeth C., Seamons A., Pizarro J. C., Fleishman S. J., Baker D., Kortemme T., Goverman J. M. & Strong R. K. (2008) Journal of Molecular Biology. 375, 5, p. 1306-1319


RosettaDock in CAPRI rounds 6-12

Wang C., Schueler-Furman O., Andre I., London N., Fleishman S. J., Bradley P., Qian B. & Baker D. (2007) Proteins: Structure, Function and Genetics. 69, 4, p. 758-763

Co-evolving residues in membrane proteins

Fuchs A., Martin-Galiano A. J., Kalman M., Fleishman S., Ben-Tal N. & Frishman D. (2007) Bioinformatics. 23, 24, p. 3312-3319

Prediction and simulation of motion in pairs of transmembrane α-helices

Enosh A., Fleishman S. J., Ben-Tal N. & Halperin D. (2007) Bioinformatics. 23, 2, p. e212-e218


The structural context of disease-causing mutations in gap junctions

Fleishman S. J., Sabag A. D., Ophir E., Avraham K. B. & Ben-Tal N. (2006) Journal of Biological Chemistry. 281, 39, p. 28958-28963

Transmembrane protein structures without X-rays

Fleishman S. J., Unger V. M. & Ben-Tal N. (2006) Trends in Biochemical Sciences. 31, 2, p. 106-113

Has the code for protein translocation been broken?

Shental-Bechor D., Fleishman S. J. & Ben-Tal N. (2006) Trends in Biochemical Sciences. 31, 4, p. 192-196

Quasi-symmetry in the Cryo-EM Structure of EmrE Provides the Key to Modeling its Transmembrane Domain

Fleishman S. J., Harrington S. E., Enosh A., Halperin D., Tate C. G. & Ben-Tal N. (2006) Journal of Molecular Biology. 364, 1, p. 54-67

Progress in structure prediction of α-helical membrane proteins

Fleishman S. J. & Ben-Tal N. (2006) Current Opinion in Structural Biology. 16, 4, p. 496-504


Free diffusion of steroid hormones across biomembranes: A simplex search with implicit solvent model calculations

Oren I., Fleishman S. J., Kessel A. & Ben-Tal N. (2004) Biophysical Journal. 87, 2, p. 768-779

An automatic method for predicting transmembrane protein structures using cryo-EM and evolutionary data

Fleishman S. J., Harrington S., Friesner R. A., Honig B. & Ben-Tal N. (2004) Biophysical Journal. 87, 5, p. 3448-3459

Assigning transmembrane segments to helices in intermediate-resolution structures

Enosh A., Fleishman S. J., Ben-Tal N. & Halperin D. (2004) Bioinformatics. 20, SUPPL. 1, p. i122-i129

An evolutionarily conserved network of amino acids mediates gating in voltage-dependent potassium channels

Fleishman S. J., Yifrach O. & Ben-Tal N. (2004) Journal of Molecular Biology. 340, 2, p. 307-318

A Cα model for the transmembrane α helices of gap junction intercellular channels

Fleishman S. J., Unger V. M., Yeager M. & Ben-Tal N. (2004) Molecular Cell. 15, 6, p. 879-888


pANT: A Method for the Pairwise Assessment of Nonfunctionalization Times of Processed Pseudogenes

Fleishman S. J., Dagan T. & Graur D. (2003) Molecular Biology and Evolution. 20, 11, p. 1876-1880


A novel scoring function for predicting the conformations of tightly packed pairs of transmembrane α-helices

Fleishman S. J. & Ben-Tal N. (2002) Journal of Molecular Biology. 321, 2, p. 363-378

A putative molecular-activation switch in the transmembrane domain of erbB2

Fleishman S. J., Schlessinger J. & Ben-Tal N. (2002) Proceedings of the National Academy of Sciences of the United States of America. 99, 25, p. 15937-15940