Advances in protein structure prediction and design

ImageNet classification with deep convolutional neural networks

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155 · see citing works

Deep learning

LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126 · see citing works

Gapped BLAST and PSI-BLAST: a new generation of protein database search programs

Altschul, S. (1997) · Nucleic Acids Research · doi:10.1093/nar/25.17.3389 · Cited by 73,302 · see citing works

The Protein Data Bank

Berman, H. M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.235 · Cited by 40,196 · see citing works

Equation of State Calculations by Fast Computing Machines

Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953) · The Journal of Chemical Physics · doi:10.1063/1.1699114 · Cited by 37,192 · 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

SWISS-MODEL: homology modelling of protein structures and complexes

Waterhouse, A. M., Bertoni, M., Bienert, S., Studer, G., Tauriello, G., Gumienny, R., Heer, F. T., de Beer, T., Rempfer, C., Bordoli, L., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky427 · Cited by 13,005 · see citing works

Principles that Govern the Folding of Protein Chains

Anfinsen, C. B. (1973) · Science · doi:10.1126/science.181.4096.223 · Cited by 7,096 · see citing works

CHARMM36m: An Improved Force Field for Folded and Intrinsically Disordered Proteins

Huang, J., Rauscher, S., Nawrocki, G., Ran, T., Feig, M., de Groot, B. L., Grubmüller, H., & MacKerell, A. (2016) · Nature Methods · doi:10.1038/nmeth.4067 · Cited by 6,708 · 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

The I-TASSER Suite: protein structure and function prediction

Yang, J., Yan, R., Roy, A., Xu, D., Poisson, J., & Zhang, Y. (2015) · Nature Methods · doi:10.1038/nmeth.3213 · Cited by 5,596 · see citing works

Profile hidden Markov models

Eddy, S. R. (1998) · Bioinformatics · doi:10.1093/bioinformatics/14.9.755 · Cited by 5,515 · see citing works

Dominant forces in protein folding

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

A Method to Identify Protein Sequences That Fold into a Known Three-Dimensional Structure

Bowie, J. U., Lüthy, R., & Eisenberg, D. (1991) · Science · doi:10.1126/science.1853201 · Cited by 2,851 · see citing works

Funnels, pathways, and the energy landscape of protein folding: A synthesis

Bryngelson, J. D., Onuchic, J. N., Socci, N. D., & Wolynes, P. G. (1995) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.340210302 · Cited by 2,648 · see citing works

The MARTINI Coarse-Grained Force Field: Extension to Proteins

Monticelli, L., Kandasamy, S. K., Périole, X., Larson, R. G., Tieleman, D. P., & Marrink, ‪. J. (2008) · Journal of Chemical Theory and Computation · doi:10.1021/ct700324x · Cited by 2,491 · see citing works

Protein homology detection by HMM–HMM comparison

Söding, J. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bti125 · Cited by 2,381 · 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

Untitled work

Leaver-Fay (2011) · doi:10.1016/b978-0-12-381270-4.00019-6 · Cited by 1,904 · see citing works

Protein Structure Modeling with MODELLER

Eswar, N., Eramian, D., Webb, B., Shen, M., & Šali, A. (2008) · Methods in molecular biology · doi:10.1007/978-1-60327-058-8_8 · Cited by 1,781 · see citing works

Design of a Novel Globular Protein Fold with Atomic-Level Accuracy

Kuhlman, B. A., Dantas, G. A., Ireton, G. C., Varani, G., Stoddard, B. L., & Baker, D. A. (2003) · Science · doi:10.1126/science.1089427 · Cited by 1,666 · 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

Direct-coupling analysis of residue coevolution captures native contacts across many protein families

Morcos, F., Pagnani, A., Lunt, B., Bertolino, A., Marks, D. S., Sander, C., Zecchina, R., Onuchic, J. N., Hwa, T., & Weigt, M. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1111471108 · Cited by 1,434 · see citing works

Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and bayesian scoring functions

Simons, K. T., Kooperberg, C. L., Huang, E. S., & Baker, D. A. (1997) · Journal of Molecular Biology · doi:10.1006/jmbi.1997.0959 · Cited by 1,387 · see citing works

Improved prediction of protein side‐chain conformations with SCWRL4

Krivov, G. G., Shapovalov, M. V., & Dunbrack, R. L. (2009) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22488 · Cited by 1,312 · see citing works

Kemp elimination catalysts by computational enzyme design

Röthlisberger, D., Khersonsky, O., Wollacott, A. M., Jiang, L., DeChancie, J., Betker, J. L., Gallaher, J. L., Althoff, E. A., Zanghellini, A., Dym, O., et al. (2008) · Nature · doi:10.1038/nature06879 · Cited by 1,299 · see citing works

A new approach to protein fold recognition

Jones, D. T., Taylort, W. R., & Thornton, J. M. (1992) · Nature · doi:10.1038/358086a0 · Cited by 1,221 · see citing works

THE KINETICS OF FORMATION OF NATIVE RIBONUCLEASE DURING OXIDATION OF THE REDUCED POLYPEPTIDE CHAIN

Anfinsen, C. B., Haber, E., Sela, M., & White, F. H. (1961) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.47.9.1309 · Cited by 1,182 · see citing works

The Protein Folding Problem

Dill, K. A., Ozkan, S. B., Shell, M. S., & Weikl, T. R. (2008) · Annual Review of Biophysics · doi:10.1146/annurev.biophys.37.092707.153558 · Cited by 1,163 · see citing works

Protein 3D Structure Computed from Evolutionary Sequence Variation

Marks, D. S., Colwell, L. J., Sheridan, R., Hopf, T. A., Pagnani, A., Zecchina, R., & Sander, C. (2011) · PLoS ONE · doi:10.1371/journal.pone.0028766 · Cited by 1,144 · see citing works

Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks

Shen, Y., & Bax, A. (2013) · Journal of Biomolecular NMR · doi:10.1007/s10858-013-9741-y · Cited by 1,123 · see citing works

High-Resolution Comparative Modeling with RosettaCM

Song, Y., DiMaio, F., Wang, R. Y., Kim, D. E., Miles, C., Brunette, T., Thompson, J., & Baker, D. A. (2013) · Structure · doi:10.1016/j.str.2013.08.005 · Cited by 1,079 · see citing works

Computer simulation of protein folding

Levitt, M., & Warshel, A. (1975) · Nature · doi:10.1038/253694a0 · Cited by 1,051 · see citing works

SCRATCH: a protein structure and structural feature prediction server

Cheng, J. J., Randall, A. Z., Sweredoski, M. J., & Baldi, P. (2005) · Nucleic Acids Research · doi:10.1093/nar/gki396 · Cited by 1,036 · see citing works

Identification of direct residue contacts in protein–protein interaction by message passing

Weigt, M., White, R. A., Szurmant, H., Hoch, J. A., & Hwa, T. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0805923106 · Cited by 1,025 · see citing works

Experimental and Theoretical Aspects of Protein Folding

Anfinsen, C. B., & Scheraga, H. A. (1975) · Advances in protein chemistry · doi:10.1016/s0065-3233(08)60413-1 · Cited by 973 · see citing works

Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model

Wang, S., Sun, S., Li, Z., Zhang, R., & Xu, J. (2017) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005324 · Cited by 931 · see citing works

Conformation Changes of Proteins

Lumry, R. W., & Eyring, H. B. (1954) · The Journal of Physical Chemistry · doi:10.1021/j150512a005 · Cited by 868 · see citing works

Ab initio protein structure assembly using continuous structure fragments and optimized knowledge‐based force field

Xu, D. H., & Zhang, Y. (2012) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24065 · Cited by 853 · see citing works

Native protein sequences are close to optimal for their structures

Kuhlman, B. A., & Baker, D. A. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.19.10383 · Cited by 814 · see citing works

Coarse-grained models for proteins

Tozzini, V. (2005) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2005.02.005 · Cited by 813 · see citing works

PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments

Jones, D. T., Buchan, D. W. A., Cozzetto, D., & Pontil, M. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr638 · Cited by 760 · see citing works

Using known substructures in protein model building and crystallography.

Jones, T. A., & Thirup, S. (1986) · The EMBO Journal · doi:10.1002/j.1460-2075.1986.tb04287.x · Cited by 755 · see citing works

Computational Design of Self-Assembling Protein Nanomaterials with Atomic Level Accuracy

King, N. P., Sheffler, W., Sawaya, M. R., Vollmar, B. S., Sumida, J. P., André, I., Gonen, T., Yeates, T. O., & Baker, D. A. (2012) · Science · doi:10.1126/science.1219364 · Cited by 651 · see citing works

Rotamer Libraries in the 21st Century

Dunbrack, R. L. (2002) · Current Opinion in Structural Biology · doi:10.1016/s0959-440x(02)00344-5 · Cited by 645 · see citing works

Engineering an improved light-induced dimer (iLID) for controlling the localization and activity of signaling proteins

Guntas, G., Hallett, R. A., Zimmerman, S. P., Williams, T., Yumerefendi, H., Bear, J. E., & Kuhlman, B. A. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1417910112 · Cited by 641 · see citing works

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 · doi:10.1126/science.1202617 · Cited by 585 · see citing works

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., et al. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.06.012 · Cited by 575 · 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

Accurate design of megadalton-scale two-component icosahedral protein complexes

Bale, J. B., Gonen, S., Liu, Y., Sheffler, W., Ellis, D., Thomas, C. P., Cascio, D., Yeates, T. O., Gonen, T., King, N. P., et al. (2016) · Science · doi:10.1126/science.aaf8818 · Cited by 563 · see citing works

A large‐scale experiment to assess protein structure prediction methods

Moult, J., Pedersen, J. T., Judson, R., & Fidelis, K. (1995) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.340230303 · Cited by 555 · see citing works

Proof of principle for epitope-focused vaccine design

Correia, B. E., Bates, J. T., Loomis, R. J., Baneyx, G., Carrico, C., Jardine, J. G., Rupert, P., Correnti, C., Kalyuzhniy, O., Vittal, V., et al. (2014) · Nature · doi:10.1038/nature12966 · Cited by 555 · see citing works

De novo design of potent and selective mimics of IL-2 and IL-15

Silva, D.-A., Yu, S., Ulge, U. Y., Spangler, J. B., Jude, K. M., Labão-Almeida, C., Ali, L. R., Quijano-Rubio, A., Ruterbusch, M., Leung, I., et al. (2019) · Nature · doi:10.1038/s41586-018-0830-7 · Cited by 531 · see citing works

Accurate design of coassembling multi-component protein nanomaterials

King, N., Bale, J., Sheffler, W., McNamara, D., Gonen, S., Gonen, T., Yeates, T., & Baker, D. (2014) · Nature · doi:10.1038/nature13404 · Cited by 523 · see citing works

Protein structure determination using metagenome sequence data

Ovchinnikov, S., Park, H., Varghese, N., Huang, P.-S., Pavlopoulos, G. A., Kim, D. E., Kamisetty, H., Kyrpides, N. C., & Baker, D. (2017) · Science · doi:10.1126/science.aah4043 · Cited by 520 · see citing works

Three-Dimensional Structures of Membrane Proteins from Genomic Sequencing

Hopf, T. A., Colwell, L. J., Sheridan, R., Rost, B., Sander, C., & Marks, D. S. (2012) · Cell · doi:10.1016/j.cell.2012.04.012 · Cited by 501 · see citing works

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

Rocklin, G. J., Chidyausiku, T. M., Goreshnik, I., Ford, A., Houliston, S., Lemak, A., Carter, L., Ravichandran, R., Mulligan, V. K., Chevalier, A., et al. (2017) · Science · doi:10.1126/science.aan0693 · Cited by 501 · see citing works

PROTEIN COAGULATION AND ITS REVERSAL

Anson, M. L., & Mirsky, A. E. (1930) · Journal of General Physiology · doi:10.1085/jgp.13.4.469 · Cited by 497 · see citing works

Computational Enzyme Design

Kiss, G., Çelebi‐Ölçüm, N., Moretti, R., Baker, D. A., & Houk, K. N. (2013) · Angewandte Chemie International Edition · doi:10.1002/anie.201204077 · Cited by 493 · see citing works

High-Resolution Protein Design with Backbone Freedom

Harbury, P. B., Plecs, J. J., Tidor, B., Alber, T., & Kim, P. S. (1998) · Science · doi:10.1126/science.282.5393.1462 · Cited by 458 · 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

Effective energy functions for protein structure prediction

Lazaridis, T. (2000) · Current Opinion in Structural Biology · doi:10.1016/s0959-440x(00)00063-4 · Cited by 445 · see citing works

Computational design of ligand-binding proteins with high affinity and selectivity

Tinberg, C. E., Khare, S. D., Dou, J., Doyle, L., Nelson, J., Schena, A., Jankowski, W., Kalodimos, C. G., Johnsson, K., Stoddard, B. L., et al. (2013) · Nature · doi:10.1038/nature12443 · Cited by 432 · see citing works

Induction of Potent Neutralizing Antibody Responses by a Designed Protein Nanoparticle Vaccine for Respiratory Syncytial Virus

Marcandalli, J., Fiala, B., Ols, S., Perotti, M., de van der Schueren, W. J., Snijder, J., Hodge, E. A., Benhaim, M., Ravichandran, R., Carter, L., et al. (2019) · Cell · doi:10.1016/j.cell.2019.01.046 · Cited by 431 · see citing works

IMG/M: integrated genome and metagenome comparative data analysis system

Chen, I.-M. A., Markowitz, V. M., Chu, K., Palaniappan, K., Szeto, E., Pillay, M., Ratner, A., Huang, J., Andersen, E., Huntemann, M., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw929 · Cited by 425 · see citing works

Protein Structure Modeling with MODELLER

Webb, B., & Šali, A. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-7231-9_4 · Cited by 416 · 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

Design, structure and stability of a hyperthermophilic protein variant

Malakauskas, S. M., & Mayo, S. L. (1998) · Nature Structural Biology · doi:10.1038/nsb0698-470 · Cited by 350 · see citing works

MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins

Jones, D. T., Singh, T., Kościółek, T., & Tetchner, S. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu791 · Cited by 345 · see citing works

Computational design of water-soluble α-helical barrels

Thomson, A. R., Wood, C. W., Burton, A. J., Bartlett, G. J., Sessions, R. B., Brady, R. L., & Woolfson, D. N. (2014) · Science · doi:10.1126/science.1257452 · Cited by 330 · see citing works

Learning generative models for protein fold families

Balakrishnan, S., Kamisetty, H., Carbonell, J. G., Lee, S., & Langmead, C. J. (2011) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.22934 · Cited by 316 · see citing works

A Large Scale Test of Computational Protein Design: Folding and Stability of Nine Completely Redesigned Globular Proteins

Dantas, G. A., Kuhlman, B. A., Callender, D. R., Wong, M., & Baker, D. A. (2003) · Journal of Molecular Biology · doi:10.1016/s0022-2836(03)00888-x · Cited by 315 · see citing works

The Fourier transform of a coiled-coil

Crick, F. H. C. (1953) · Acta Crystallographica · doi:10.1107/s0365110x53001952 · Cited by 313 · see citing works

De novo design of a transmembrane Zn 2+ -transporting four-helix bundle

Joh, N. H., Wang, T., Bhate, M., Acharya, R., Wu, Y., Grabe, M., Hong, M., Grigoryan, G., & DeGrado, W. F. (2014) · Science · doi:10.1126/science.1261172 · Cited by 301 · see citing works

De novo design of protein homo-oligomers with modular hydrogen-bond network–mediated specificity

Boyken, S. E., Chen, Z., Groves, B., Langan, R. A., Oberdorfer, G., Ford, A., Gilmore, J. M., Xu, C., DiMaio, F., Pereira, J. H., et al. (2016) · Science · doi:10.1126/science.aad8865 · Cited by 297 · see citing works

Structural basis for nucleotide exchange in heterotrimeric G proteins

Dror, R. O., Mildorf, T. J., Hilger, D., Manglik, A., Borhani, D. W., Arlow, D. H., Philippsen, A., Villanueva, N., Yang, Z., Lerch, M. T., et al. (2015) · Science · doi:10.1126/science.aaa5264 · Cited by 292 · see citing works

Principles of Protein Stability and Their Application in Computational Design

Goldenzweig, A., & Fleishman, S. J. (2018) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-062917-012102 · Cited by 283 · see citing works

The consensus concept for thermostability engineering of proteins

Lehmann, M., Pasamontes, L., Lassen, S. F., & Wyss, M. (2000) · Biochimica et Biophysica Acta (BBA) - Protein Structure and Molecular Enzymology · doi:10.1016/s0167-4838(00)00238-7 · Cited by 281 · see citing works

Structure of a 16-nm Cage Designed by Using Protein Oligomers

Lai, Y., Cascio, D., & Yeates, T. O. (2012) · Science · doi:10.1126/science.1219351 · Cited by 279 · see citing works

COMPASS: A Tool for Comparison of Multiple Protein Alignments with Assessment of Statistical Significance

Sadreyev, R. I., & Grishin, N. V. (2003) · Journal of Molecular Biology · doi:10.1016/s0022-2836(02)01371-2 · Cited by 279 · see citing works

High thermodynamic stability of parametrically designed helical bundles

Huang, P.-S., Oberdorfer, G., Xu, C., Pei, X. Y., Nannenga, B. L., Rogers, J. M., DiMaio, F., Gonen, T., Luisi, B., & Baker, D. (2014) · Science · doi:10.1126/science.1257481 · Cited by 277 · see citing works

The Levinthal paradox: yesterday and today

Karplus, M. (1997) · Folding and Design · doi:10.1016/s1359-0278(97)00067-9 · Cited by 265 · see citing works

Correlations Among Amino Acid Sites in bHLH Protein Domains: An Information Theoretic Analysis

Atchley, W. R., Wollenberg, K. R., Fitch, W. M., Terhalle, W. F., & Dress, A. (2000) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a026229 · Cited by 256 · see citing works

De novo design of a four-fold symmetric TIM-barrel protein with atomic-level accuracy

Huang, P., Feldmeier, K., Parmeggiani, F., Fernández‐Velasco, D. A., Höcker, B., & Baker, D. A. (2015) · Nature Chemical Biology · doi:10.1038/nchembio.1966 · Cited by 253 · see citing works

Exploring the repeat protein universe through computational protein design

Brunette, T., Parmeggiani, F., Huang, P., Bhabha, G., Ekiert, D. C., Tsutakawa, S. E., Hura, G. L., Tainer, J. A., & Baker, D. A. (2015) · Nature · doi:10.1038/nature16162 · Cited by 252 · see citing works

SPINE X: Improving protein secondary structure prediction by multistep learning coupled with prediction of solvent accessible surface area and backbone torsion angles

Faraggi, E., Zhang, T., Yang, Y., Kurgan, L., & Zhou, Y. (2011) · Journal of Computational Chemistry · doi:10.1002/jcc.21968 · Cited by 245 · see citing works

Engineering extrinsic disorder to control protein activity in living cells

Dağliyan, O., Tarnawski, M., Chu, P.-H., Shirvanyants, D. G., Schlichting, I., Dokholyan, N. V., & Hahn, K. M. (2016) · Science · doi:10.1126/science.aah3404 · Cited by 241 · see citing works

Influence of conservation on calculations of amino acid covariance in multiple sequence alignments

Fodor, A. A., & Aldrich, R. W. (2004) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.20098 · Cited by 238 · see citing works

Generation of bispecific IgG antibodies by structure-based design of an orthogonal Fab interface

Lewis, S. M., Wu, X., Pustilnik, A., Sereno, A., Huang, F., Rick, H. L., Guntas, G., Leaver‐Fay, A., Smith, E. M., Ho, C., et al. (2014) · Nature Biotechnology · doi:10.1038/nbt.2797 · Cited by 234 · see citing works

A comparison of successful and failed protein interface designs highlights the challenges of designing buried hydrogen bonds

Stranges, P. B., & Kuhlman, B. A. (2012) · Protein Science · doi:10.1002/pro.2187 · Cited by 233 · see citing works

Combined Covalent-Electrostatic Model of Hydrogen Bonding Improves Structure Prediction with Rosetta

O’Meara, M. J., Leaver‐Fay, A., Tyka, M. D., Stein, A., Houlihan, K., DiMaio, F., Bradley, P. H., Kortemme, T., Baker, D. A., Snoeyink, J. S., et al. (2015) · Journal of Chemical Theory and Computation · doi:10.1021/ct500864r · Cited by 232 · see citing works

RosettaAntibodyDesign (RAbD): a general framework for computational antibody design

Adolf-Bryfogle, J., Kalyuzhniy, O., Kubitz, M., Weitzner, B. D., Hu, X., Adachi, Y., Schief, W. R., & Dunbrack, R. L. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006112 · Cited by 227 · see citing works

Design of ordered two-dimensional arrays mediated by noncovalent protein-protein interfaces

Gonen, S., DiMaio, F., Gonen, T., & Baker, D. A. (2015) · Science · doi:10.1126/science.aaa9897 · Cited by 226 · see citing works

Bispecific antibodies for cancer therapy: A review

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