Global analysis of protein folding using massively parallel design, synthesis, and testing

Scikit-learn: Machine Learning in Python

Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Müller, A., Nothman, J., Louppe, G., et al. (2012) · arXiv · doi:10.48550/arxiv.1201.0490 · Cited by 71,016 · see citing works

PROCHECK: a program to check the stereochemical quality of protein structures

Laskowski, R. A., MacArthur, M. W., Moss, D. S., & Thornton, J. M. (1993) · Journal of Applied Crystallography · doi:10.1107/s0021889892009944 · Cited by 24,581 · see citing works

NMRPipe: A multidimensional spectral processing system based on UNIX pipes

Delaglio, F., Grzesiek, S., Vuister, G. W., Zhu, G., Pfeifer, J., & Bax, A. (1995) · Journal of Biomolecular NMR · doi:10.1007/bf00197809 · Cited by 15,994 · see citing works

Crystallography & NMR System: A New Software Suite for Macromolecular Structure Determination

Brünger, A. T., Adams, P. D., Clore, G. M., DeLano, W. L., Gros, P., Grosse‐Kunstleve, R. W., Jiang, J., Kuszewski, J. J., Nilges, M., Pannu, N., et al. (1998) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444998003254 · Cited by 15,720 · see citing works

Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features

Kabsch, W., & Sander, C. (1983) · Biopolymers · doi:10.1002/bip.360221211 · Cited by 15,320 · see citing works

WebLogo: A Sequence Logo Generator: Figure 1Preprint

Crooks, G. E., Hon, G. C., Chandonia, J., & Brenner, S. E. (2004) · Genome Research · doi:10.1101/gr.849004 · Cited by 12,433 · see citing works

Enzymatic assembly of DNA molecules up to several hundred kilobases

Gibson, D. G., Young, L., Chuang, R.-Y., Venter, J. C., Hutchison, C. A., & Smith, H. O. (2009) · Nature Methods · doi:10.1038/nmeth.1318 · Cited by 9,742 · see citing works

Protein production by auto-induction in high-density shaking cultures

Studier, F. W. (2005) · Protein Expression and Purification · doi:10.1016/j.pep.2005.01.016 · Cited by 5,949 · see citing works

Protein secondary structure prediction based on position-specific scoring matrices.

Jones, D. C. (1999) · Journal of Molecular Biology · doi:10.1006/jmbi.1999.3091 · Cited by 5,741 · see citing works

PEAR: a fast and accurate Illumina Paired-End reAd mergeR

Zhang, J., Kobert, K., Flouri, T., & Stamatakis, A. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btt593 · Cited by 4,497 · see citing works

How to measure and predict the molar absorption coefficient of a protein

Pace, C., Vajdos, F., Fee, L. R., Grimsley, G., & Gray, T. (1995) · Protein Science · doi:10.1002/pro.5560041120 · Cited by 3,924 · see citing works

Dominant forces in protein folding

Dill, K. A. (1990) · Biochemistry · doi:10.1021/bi00483a001 · Cited by 3,824 · see citing works

HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment

Remmert, M., Biegert, A., Hauser, A., & Söding, J. (2012) · Nature Methods · doi:10.1038/nmeth.1818 · Cited by 2,288 · see citing works

How fast-folding proteins fold

Lindorff-Larsen, K., Piana, S., Dror, R. O., & Shaw, D. E. (2011) · Science · doi:10.1126/science.1208351 · Cited by 1,980 · see citing works

Learning Bayesian Networks with the bnlearn R Package

Scutari, M. (2010) · Journal of Statistical Software · doi:10.18637/jss.v035.i03 · Cited by 1,798 · see citing works

Yeast surface display for screening combinatorial polypeptide libraries

Boder, E. T., & Wittrup, K. D. (1997) · Nature Biotechnology · doi:10.1038/nbt0697-553 · Cited by 1,774 · see citing works

Protein Structure Prediction Using Rosetta

Rohl, C. A., Strauss, C. E. M., Misura, K. M. S., & Baker, D. A. (2004) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/s0076-6879(04)83004-0 · Cited by 1,711 · see citing works

Unfolding free energy changes determined by the linear extrapolation method. 1. Unfolding of phenylmethanesulfonyl .alpha.-chymotrypsin using different denaturants

Santoro, M. M., & Bolen, D. W. (1988) · Biochemistry · doi:10.1021/bi00421a014 · Cited by 1,585 · see citing works

The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design

Alford, R. F., Leaver-Fay, A., Jeliazkov, J. R., O’Meara, M. J., DiMaio, F. P., Park, H., Shapovalov, M. V., Renfrew, P. D., Mulligan, V. K., Kappel, K., et al. (2017) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.7b00125 · Cited by 1,532 · see citing works

The coming of age of de novo protein design

Huang, P.-S., Boyken, S. E., & Baker, D. (2016) · Nature · doi:10.1038/nature19946 · Cited by 1,478 · see citing works

Automated NMR Structure Calculation With CYANA

Güntert, P. (2004) · Humana Press eBooks · doi:10.1385/1-59259-809-9:353 · Cited by 1,354 · see citing works

De Novo Protein Design: Fully Automated Sequence Selection

Dahiyat, B. I., & Mayo, S. L. (1997) · Science · doi:10.1126/science.278.5335.82 · Cited by 1,142 · see citing works

Isolating and engineering human antibodies using yeast surface display

Chao, G., Lau, W. L., Hackel, B. J., Sazinsky, S. L., Lippow, S. M., & Wittrup, K. D. (2006) · Nature Protocols · doi:10.1038/nprot.2006.94 · Cited by 913 · see citing works

Large-scale de novo DNA synthesis: technologies and applications

Kosuri, S., & Church, G. M. (2014) · Nature Methods · doi:10.1038/nmeth.2918 · Cited by 869 · see citing works

Protein Design by Binary Patterning of Polar and Nonpolar Amino Acids

Kamtekar, S., Schiffer, J. M., Xiong, H., Babik, J. M., & Hecht, M. H. (1993) · Science · doi:10.1126/science.8259512 · Cited by 731 · see citing works

Evaluating protein structures determined by structural genomics consortia

Bhattacharya, A., Tejero, R., & Montelione, G. T. (2006) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.21165 · Cited by 729 · see citing works

PyMC: Bayesian Stochastic Modelling inPython

Patil, A. P., Huard, D., & Fonnesbeck, C. (2010) · Journal of Statistical Software · doi:10.18637/jss.v035.i04 · Cited by 719 · see citing works

A relationship between protein stability and protein function.

Shoichet, B. K., Baase, W. A., Kuroki, R., & Matthews, B. W. (1995) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.92.2.452 · Cited by 712 · see citing works

Structural basis for phosphoserine-proline recognition by group IV WW domains.

Verdecia, M. A., Bowman, M. E., Lu, K. P., Hunter, T. R., & Noel, J. P. (2000) · Nature Structural Biology · doi:10.1038/77929 · Cited by 694 · see citing works

Protein Structure and the Energetics of Protein Stability

Robertson, A. D., & Murphy, K. P. (1997) · Chemical Reviews · doi:10.1021/cr960383c · Cited by 680 · see citing works

Refinement of protein structures in explicit solvent

Linge, J. P., Williams, M. A., Spronk, C. A. E. M., Bonvin, A. M. J. J., & Nilges, M. (2003) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.10299 · Cited by 607 · see citing works

Contribution of hydrogen bonds to protein stability

Pace, C. N., Fu, H., Fryar, K. L., Landua, J. D., Trevino, S. R., Schell, D., Thurlkill, R. L., Imura, S., Scholtz, J. M., Gajiwala, K. S., et al. (2014) · Protein Science · doi:10.1002/pro.2449 · Cited by 599 · see citing works

Principles for designing ideal protein structures

Koga, N., Tatsumi-Koga, R., Liu, G., Xiao, R., Acton, T. B., Montelione, G. T., & Baker, D. (2012) · Nature · doi:10.1038/nature11600 · Cited by 564 · see citing works

Simultaneous Optimization of Biomolecular Energy Functions on Features from Small Molecules and Macromolecules

Park, H., Bradley, P. H., Greisen, P. J., Liu, Y., Mulligan, V. K., Kim, D. E., Baker, D. A., & DiMaio, F. (2016) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.6b00819 · Cited by 564 · see citing works

Accelerated NMR Spectroscopy by Using Compressed Sensing

Kazimierczuk, K., & Orekhov, V. (2011) · Angewandte Chemie International Edition · doi:10.1002/anie.201100370 · Cited by 550 · see citing works

Improving catalytic function by ProSAR-driven enzyme evolution

Fox, R. J., Davis, S. C., Mundorff, E. C., Newman, L. M., Gavrilovic, V., Ma, S. K., Chung, L., Ching, C., Tam, S., Muley, S., et al. (2007) · Nature Biotechnology · doi:10.1038/nbt1286 · Cited by 540 · see citing works

DNAWorks: an automated method for designing oligonucleotides for PCR-based gene synthesis

Hoover, D. M. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.10.e43 · Cited by 521 · see citing works

Assessing the accuracy of physical models used in protein-folding simulations: quantitative evidence from long molecular dynamics simulations

Piana, S., Klepeis, J. L., & Shaw, D. E. (2014) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2013.12.006 · Cited by 513 · see citing works

Contribution of Hydrophobic Interactions to Protein Stability

Pace, C. N., Fu, H., Fryar, K. L., Landua, J. D., Trevino, S. R., Shirley, B. A., McNutt, M., Iimura, S., Gajiwala, K. S., Scholtz, J. M., et al. (2011) · Journal of Molecular Biology · doi:10.1016/j.jmb.2011.02.053 · Cited by 460 · see citing works

Accurate de novo design of hyperstable constrained peptides

Bhardwaj, G., Mulligan, V. K., Bahl, C. D., Gilmore, J. M., Harvey, P. J., Cheneval, O., Buchko, G. W., Pulavarti, S. V. S. R. K., Kaas, Q., Eletsky, A., et al. (2016) · Nature · doi:10.1038/nature19791 · Cited by 442 · see citing works

An improved yeast transformation method for the generation of very large human antibody libraries

Benatuil, L., Perez, J. M., Belk, J., & Hsieh, C.-M. (2010) · Protein Engineering Design and Selection · doi:10.1093/protein/gzq002 · Cited by 435 · see citing works

ProTherm and ProNIT: thermodynamic databases for proteins and protein-nucleic acid interactions

Kumar, M. D. S. (2005) · Nucleic Acids Research · doi:10.1093/nar/gkj103 · Cited by 416 · see citing works

Cell-wide analysis of protein thermal unfolding reveals determinants of thermostability

Leuenberger, P., Ganscha, S., Kahraman, A., Cappelletti, V., Boersema, P. J., von Mering, C., Claassen, M., & Picotti, P. (2017) · Science · doi:10.1126/science.aai7825 · Cited by 413 · see citing works

Forces stabilizing proteins

Pace, C. N., Scholtz, J. M., & Grimsley, G. R. (2014) · FEBS Letters · doi:10.1016/j.febslet.2014.05.006 · Cited by 390 · see citing works

The MPI bioinformatics Toolkit as an integrative platform for advanced protein sequence and structure analysis

Alva, V., Nam, S.-Z., Söding, J., & Lupas, A. (2016) · Nucleic Acids Res. · doi:10.1093/nar/gkw348 · Cited by 382 · see citing works

RosettaRemodel: A Generalized Framework for Flexible Backbone Protein Design

Huang, P., Ban, Y. A., Richter, F. M., André, I., Vernon, R. M., Schief, W. R., & Baker, D. A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0024109 · Cited by 373 · see citing works

Relationship of sidechain hydrophobicity and α‐helical propensity on the stability of the single‐stranded amphipathic α‐helix

Monera, O. D., Sereda, T. J., Zhou, N., et al. (1995) · Journal of Peptide Science · doi:10.1002/psc.310010507 · Cited by 369 · see citing works

Navigating the protein fitness landscape with Gaussian processes

Romero, P. A., Krause, A., & Arnold, F. H. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1215251110 · Cited by 346 · see citing works

Protein folding kinetics and thermodynamics from atomistic simulation

Piana, S., Lindorff‐Larsen, K., & Shaw, D. E. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1201811109 · Cited by 303 · see citing works

Pulse proteolysis: A simple method for quantitative determination of protein stability and ligand binding

Park, C., & Marqusee, S. (2005) · Nature Methods · doi:10.1038/nmeth740 · Cited by 283 · see citing works

De novo proteins from designed combinatorial libraries

Hecht, M. H., Das, A., Go, A., Bradley, L. H., & Wei, Y. (2004) · Protein Science · doi:10.1110/ps.04690804 · Cited by 268 · see citing works

Folding Simulations for Proteins with Diverse Topologies Are Accessible in Days with a Physics-Based Force Field and Implicit Solvent

Nguyen, T. H. H., Maier, J., Huang, H., Perrone, V., & Simmerling, C. L. (2014) · Journal of the American Chemical Society · doi:10.1021/ja5032776 · Cited by 244 · see citing works

A fundamental protein property, thermodynamic stability, revealed solely from large-scale measurements of protein function

Araya, C. L., Fowler, D. M., Chen, W., Muniez, I., Kelly, J. W., & Fields, S. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1209751109 · Cited by 230 · see citing works

Structure-function-folding relationship in a WW domain.

Jäger, M., Zhang, Y., Bieschke, J., Nguyen, H., Dendle, M. T. A., Bowman, M. E., Noel, J., Gruebele, M., & Kelly, J. (2006) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.0600511103 · Cited by 214 · see citing works

Selecting proteins with improved stability by a phage-based method

Sieber, V., Plückthun, A., & Schmid, F. X. (1998) · Nature Biotechnology · doi:10.1038/nbt1098-955 · Cited by 192 · see citing works

Prediction of functionally important residues based solely on the computed energetics of protein structure 1 1Edited by B. Honig

Elcock, A. H. (2001) · Journal of Molecular Biology · doi:10.1006/jmbi.2001.5009 · Cited by 190 · see citing works

Scientific Benchmarks for Guiding Macromolecular Energy Function Improvement

Leaver‐Fay, A., O’Meara, M. J., Tyka, M., Jacak, R., Song, Y., Kellogg, E. H., Thompson, J., Davis, I., Pache, R. A., Lyskov, S., et al. (2013) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/b978-0-12-394292-0.00006-0 · Cited by 189 · see citing works

Optimizing resolution in multidimensional NMR by three-way decomposition

Orekhov, V., Ibraghimov, I. V., & BILLETER, M. A. (2003) · Journal of Biomolecular NMR · doi:10.1023/a:1024944720653 · Cited by 185 · see citing works

Folded proteins occur frequently in libraries of random amino acid sequences.

Davidson, A. R., & Sauer, R. T. (1994) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.91.6.2146 · Cited by 185 · see citing works

Arginine Topology Controls Escape of Minimally Cationic Proteins from Early Endosomes to the Cytoplasm

Appelbaum, J., LaRochelle, J. R., Smith, B. A., Balkin, D. M., Holub, J. M., & Schepartz, A. (2012) · Chemistry & Biology · doi:10.1016/j.chembiol.2012.05.022 · Cited by 169 · see citing works

Protein stability: computation, sequence statistics, and new experimental methods

Magliery, T. J. (2015) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2015.09.002 · Cited by 153 · see citing works

Control over overall shape and size in de novo designed proteins

Lin, Y., Koga, N., Koga, R., Liu, G., Clouser, A. F., Montelione, G. T., & Baker, D. A. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1509508112 · Cited by 134 · see citing works

Fluorescence Correlation Spectroscopy Reveals Highly Efficient Cytosolic Delivery of Certain Penta-Arg Proteins and Stapled Peptides

LaRochelle, J. R., Cobb, G., Steinauer, A., Rhoades, E. R., & Schepartz, A. (2015) · Journal of the American Chemical Society · doi:10.1021/ja510391n · Cited by 118 · see citing works

Cysteine Scanning Mutagenesis at 40 of 76 Positions in Villin Headpiece Maps the F-Actin Binding Site and Structural Features of the Domain

Doering, D. S., & Matsudaira, P. T. (1996) · Biochemistry · doi:10.1021/bi9615699 · Cited by 103 · see citing works

Structural Basis for the Versatile Interactions of Smad7 with Regulator WW Domains in TGF-β Pathways

Aragón, E., Goerner, N., Xi, Q., Gomes, T., Gao, S., Massagué, J., & Macias, M. J. (2012) · Structure · doi:10.1016/j.str.2012.07.014 · Cited by 99 · see citing works

The specificity of chymotrypsin

Schellenberger, V., BRAUNE, K., Hofmann, H., et al. (1991) · European Journal of Biochemistry · doi:10.1111/j.1432-1033.1991.tb16163.x · Cited by 97 · see citing works

Role of the S' Subsites in Serine Protease Catalysis. Active-Site Mapping of Rat Chymotrypsin, Rat Trypsin, .alpha.-Lytic Protease, and Cercarial Protease from Schistosoma mansoni

Schellenberger, V., Turck, C. W., & Rutter, W. J. (1994) · Biochemistry · doi:10.1021/bi00180a020 · Cited by 92 · see citing works

Local and macroscopic electrostatic interactions in single α-helices

Baker, E. G., Bartlett, G. J., Crump, M. P., Sessions, R. B., Linden, N., Faul, C. F. J., & Woolfson, D. N. (2015) · Nature Chemical Biology · doi:10.1038/nchembio.1739 · Cited by 91 · see citing works

Fast protein folding kinetics

Gelman, H., & Gruebele, M. (2014) · Quarterly Reviews of Biophysics · doi:10.1017/s003358351400002x · Cited by 88 · see citing works

Energy Functions in De Novo Protein Design: Current Challenges and Future Prospects

Li, Z., Yang, Y., Zhan, J., Dai, L., & Zhou, Y. (2013) · Annual Review of Biophysics · doi:10.1146/annurev-biophys-083012-130315 · Cited by 86 · see citing works

Mapping the S' subsites of serine proteases using acyl transfer to mixtures of peptide nucleophiles

Schellenberger, V., Turck, C. W., Hedstrom, L., et al. (1993) · Biochemistry · doi:10.1021/bi00067a026 · Cited by 82 · see citing works

Energetics-based Protein Profiling on a Proteomic Scale: Identification of Proteins Resistant to Proteolysis

Park, C., Zhou, S., Gilmore, J., & Marqusee, S. (2007) · Journal of Molecular Biology · doi:10.1016/j.jmb.2007.02.091 · Cited by 79 · see citing works

Sequence determinants of thermodynamic stability in a WW domain—An all‐β‐sheet protein

Jäger, M., Dendle, M. A., & Kelly, J. W. (2009) · Protein Science · doi:10.1002/pro.172 · Cited by 68 · see citing works

Core-Directed Protein Design. I. An Experimental Method for Selecting Stable Proteins from Combinatorial Libraries

Finucane, M. D., Tuna, M., Lees, J. H., & Woolfson, D. N. (1999) · Biochemistry · doi:10.1021/bi990765n · Cited by 67 · see citing works

An Expanded WW Domain Recognition Motif Revealed by the Interaction between Smad7 and the E3 Ubiquitin Ligase Smurf2

Chong, P. A., Lin, H., Wrana, J. L., & Forman-Kay, J. D. (2006) · Journal of Biological Chemistry · doi:10.1074/jbc.m601493200 · Cited by 59 · see citing works

Yeast surface display of a noncovalent MHC class II heterodimer complexed with antigenic peptide

Boder, E. T., Bill, J. R., Nields, A. W., et al. (2005) · Biotechnology and Bioengineering · doi:10.1002/bit.20616 · Cited by 57 · see citing works

Rational modification of protein stability by targeting surface sites leads to complicated results

Xiao, S., Patsalo, V., Shan, B., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1222245110 · Cited by 57 · see citing works

High-Resolution Crystal Structures of Villin Headpiece and Mutants with Reduced F-Actin Binding Activity,

Meng, J., Vardar‐Ulu, D., Wang, Y., et al. (2005) · Biochemistry · doi:10.1021/bi050850x · Cited by 56 · see citing works

A novel strategy for NMR resonance assignment and protein structure determination

Lemak, A. S., Gutmanas, A., Chitayat, S., et al. (2010) · Journal of Biomolecular NMR · doi:10.1007/s10858-010-9458-0 · Cited by 54 · see citing works

De Novo Design of a βαβ Motif

Liang, H., Chen, H., Fan, K., Wei, P., Guo, X., Jin, C., Zeng, C., Tang, C., & Lai, L. (2009) · Angewandte Chemie International Edition · doi:10.1002/anie.200805476 · Cited by 50 · see citing works

Sequence specific resonance assignment via Multicanonical Monte Carlo search using an ABACUS approach

Lemak, A. S., Steren, C. A., Arrowsmith, C. H., et al. (2008) · Journal of Biomolecular NMR · doi:10.1007/s10858-008-9238-2 · Cited by 47 · see citing works

Increasing protein stability using a rational approach combining sequence homology and structural alignment: Stabilizing the WW domain

Jiang, X., Kowalski, J. A., & Kelly, J. W. (2001) · Protein Science · doi:10.1110/ps.640101 · Cited by 45 · see citing works

Protein engineering by highly parallel screening of computationally designed variants

Sun, M. G. F., Seo, M.-H., Nim, S., Corbi-Verge, C., & Kim, P. M. (2016) · Science Advances · doi:10.1126/sciadv.1600692 · Cited by 41 · see citing works

Quantitative proteomics reveals the kinetics of trypsin-catalyzed protein digestion

Pan, Y., Cheng, K., Mao, J., et al. (2014) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-014-8071-6 · Cited by 37 · see citing works

The Folding Mechanism of BBL: Plasticity of Transition-State Structure Observed within an Ultrafast Folding Protein Family

Neuweiler, H., Sharpe, T., Rutherford, T. J., et al. (2009) · Journal of Molecular Biology · doi:10.1016/j.jmb.2009.05.011 · Cited by 35 · see citing works

Analysis of Core Packing in a Cooperatively Folded Miniature Protein: The Ultrafast Folding Villin Headpiece Helical Subdomain

Xiao, S., Bi, Y., Shan, B., et al. (2009) · Biochemistry · doi:10.1021/bi8021763 · Cited by 33 · see citing works

Tertiary Structural Propensities Reveal Fundamental Sequence/Structure Relationships

Zheng, F., Zhang, J., & Grigoryan, G. (2015) · Structure · doi:10.1016/j.str.2015.03.015 · Cited by 29 · see citing works

Erratum: Corrigendum: Local and macroscopic electrostatic interactions in single α-helices

Baker, E. G., Bartlett, G. J., Crump, M. P., et al. (2015) · Nature Chemical Biology · doi:10.1038/nchembio0915-741e · Cited by 13 · see citing works

Unified rational protein engineering with sequence-based deep representation learning

Alley, E. C., Khimulya, G., Biswas, S., AlQuraishi, M., & Church, G. M. (2019) · Nature Methods · doi:10.1038/s41592-019-0598-1 · Cited by 1,131 · see citing works

ProteinBERT: a universal deep-learning model of protein sequence and function

Brandes, N., Ofer, D., Peleg, Y., Rappoport, N., & Linial, M. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac020 · Cited by 1,009 · see citing works

Macromolecular modeling and design in Rosetta: recent methods and frameworks

Leman, J. K., Weitzner, B. D., Lewis, S. M., Adolf-Bryfogle, J., Alam, N., Alford, R. F., Aprahamian, M., Baker, D., Barlow, K. A., Barth, P., et al. (2020) · Nature Methods · doi:10.1038/s41592-020-0848-2 · Cited by 888 · see citing works

Advances in protein structure prediction and design

Kuhlman, B., & Bradley, P. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-019-0163-x · Cited by 806 · see citing works

Evaluating Protein Transfer Learning with TAPE

Rao, R., Bhattacharya, N., Thomas, N., Duan, Y., Chen, X., Canny, J., Abbeel, P., & Song, Y. S. (2019) · doi:10.1101/676825 · Cited by 719 · see citing works

Design of protein-binding proteins from the target structure alone

Cao, L., Coventry, B., Goreshnik, I., Huang, B., Sheffler, W., Park, J. S., Jude, K. M., Marković, I., Kadam, R. U., Verschueren, K. H. G., et al. (2022) · Nature · doi:10.1038/s41586-022-04654-9 · Cited by 577 · see citing works

Massively parallel de novo protein design for targeted therapeutics

Chevalier, A., Silva, D.-A., Rocklin, G. J., Hicks, D. R., Vergara, R., Murapa, P., Bernard, S. M., Zhang, L., Lam, K.-H., Yao, G., et al. (2017) · Nature · doi:10.1038/nature23912 · Cited by 453 · see citing works

Low-N protein engineering with data-efficient deep learning

Biswas, S., Khimulya, G., Alley, E. C., Esvelt, K. M., & Church, G. M. (2021) · Nature Methods · doi:10.1038/s41592-021-01100-y · Cited by 422 · see citing works

Improving de novo protein binder design with deep learning

Bennett, N. R., Coventry, B., Goreshnik, I., Huang, B., Allen, A., Vafeados, D., Peng, Y. P., Dauparas, J., Baek, M., Stewart, L., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-38328-5 · Cited by 402 · see citing works

De novo design of a fluorescence-activating β-barrel

Dou, J., Vorobieva, A. A., Sheffler, W., Doyle, L. A., Park, H., Bick, M. J., Mao, B., Foight, G. W., Lee, M. Y., Gagnon, L. A., et al. (2018) · Nature · doi:10.1038/s41586-018-0509-0 · Cited by 351 · see citing works

Perturbing the energy landscape for improved packing during computational protein design

Maguire, J. B., Haddox, H. K., Strickland, D., Halabiya, S. F., Coventry, B., Griffin, J. R., Pulavarti, S. V. S. R. K., Cummins, M., Thieker, D. F., Klavins, E., et al. (2021) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26030 · Cited by 169 · see citing works

Rapid protein stability prediction using deep learning representations

Blaabjerg, L. M., Kassem, M. M., Good, L. L., Jonsson, N., Cagiada, M., Johansson, K. E., Boomsma, W., Stein, A., & Lindorff-Larsen, K. (2023) · eLife · doi:10.7554/elife.82593 · Cited by 177 · see citing works

Continuous Automated Model EvaluatiOn (CAMEO) complementing the critical assessment of structure prediction in CASP12

Haas, J., Barbato, A., Behringer, D., Studer, G., Roth, S., Bertoni, M., Mostaguir, K., Gumienny, R., & Schwede, T. (2018) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.25431 · Cited by 168 · see citing works

An engineered decoy receptor for SARS-CoV-2 broadly binds protein S sequence variants

Chan, K. K., Tan, T. J. C., Narayanan, K. K., & Procko, E. (2021) · Science Advances · doi:10.1126/sciadv.abf1738 · Cited by 152 · see citing works

Protein sequence design by conformational landscape optimization

Norn, C., Wicky, B. I. M., Juergens, D., Liu, S., Kim, D., Tischer, D., Koepnick, B., Anishchenko, I., Players, F., Baker, D., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2017228118 · Cited by 144 · see citing works

Convolutions are competitive with transformers for protein sequence pretraining

Yang, K. K., Fusi, N., & Lu, A. X. (2024) · Cell Systems · doi:10.1016/j.cels.2024.01.008 · Cited by 137 · see citing works

Protein design via deep learning

Ding, W., Nakai, K., & Gong, H. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac102 · Cited by 66 · see citing works

Bayesian genome scale modelling identifies thermal determinants of yeast metabolism

Li, G., Hu, Y., Zrimec, J., Luo, H., Wang, H., Zelezniak, A., Ji, B., & Nielsen, J. (2021) · Nature Communications · doi:10.1038/s41467-020-20338-2 · Cited by 57 · see citing works

Recent advances in automated protein design and its future challenges

Setiawan, D., Brender, J., & Zhang, Y. (2018) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2018.1465922 · Cited by 26 · see citing works

Sampling of Structure and Sequence Space of Small Protein Folds

Linsky, T., Noble, K., Tobin, A., Crow, R., Carter, L., Urbauer, J., Baker, D., & Strauch, E. (2021) · doi:10.1101/2021.03.10.434454

[Protein engineering: from directed evolution to computational design].

Qu, G., Zhu, T., Jiang, Y., et al. (2019) · PubMed · doi:10.13345/j.cjb.190221 · Cited by 13 · see citing works

Patents and literature

Dordick, J. S., Backman, K. C., Balakrishnan, R., et al. (1990) · Applied Biochemistry and Biotechnology · doi:10.1007/bf02798396 · Cited by 1 · see citing works

Protein engineering design from directed evolution to de novo synthesis

Xiong, W., Liu, B., Shen, Y., Jing, K., & Savage, T. (2021) · Biochemical Engineering Journal · doi:10.1016/j.bej.2021.108096 · Cited by 94 · see citing works

Rational-Design Engineering to Improve Enzyme Thermostability

Pongsupasa, V., Anuwan, P., Maenpuen, S., et al. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1826-4_9 · Cited by 35 · see citing works

Directed evolution strategies for improved enzymatic performance

Hibbert, E. G., & Dalby, P. A. (2005) · Microbial Cell Factories · doi:10.1186/1475-2859-4-29 · Cited by 104 · see citing works