Skip to main content
SpringerLink
Log in

Achievements and Challenges in Computational Protein Design

  • Protocol
  • First Online:
Computational Protein Design

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1529))

Abstract

Computational protein design (CPD), a yet evolving field, includes computer-aided engineering for partial or full de novo designs of proteins of interest. Designs are defined by a requested structure, function, or working environment. This chapter describes the birth and maturation of the field by presenting 101 CPD examples in a chronological order emphasizing achievements and pending challenges. Integrating these aspects presents the plethora of CPD approaches with the hope of providing a “CPD 101”. These reflect on the broader structural bioinformatics and computational biophysics field and include: (1) integration of knowledge-based and energy-based methods, (2) hierarchical designated approach towards local, regional, and global motifs and the integration of high- and low-resolution design schemes that fit each such region, (3) systematic differential approaches towards different protein regions, (4) identification of key hot-spot residues and the relative effect of remote regions, (5) assessment of shape-complementarity, electrostatics and solvation effects, (6) integration of thermal plasticity and functional dynamics, (7) negative design, (8) systematic integration of experimental approaches, (9) objective cross-assessment of methods, and (10) successful ranking of potential designs. Future challenges also include dissemination of CPD software to the general use of life-sciences researchers and the emphasis of success within an in vivo milieu. CPD increases our understanding of protein structure and function and the relationships between the two along with the application of such know-how for the benefit of mankind. Applied aspects range from biological drugs, via healthier and tastier food products to nanotechnology and environmentally friendly enzymes replacing toxic chemicals utilized in the industry.

“The abundance of substances of which animals and plants are composed of, the remarkable processes whereby they are formed and then broken down again claimed the attention of mankind, and hence from the early days they also persistently captivated the interest of chemists. … To determine the structure of the molecule the chemist proceeds in a similar way to the anatomist. By chemical actions he breaks the system down into its components and continues with this division until familiar substances emerge. Where this decomposition has taken different directions, the structure of the original system can be inferred from the decomposition products. Usually, however, the structure will only be finally elucidated by the reverse method, by building up the molecule from the decomposition products or similar substances, i.e. by what is termed synthesis. Nevertheless, the chemical enigma of Life will not be solved until organic chemistry has mastered another, even more difficult subject, the proteins, in the same way as it has mastered the carbohydrates. It is hence understandable that the organic and physiological chemists are increasingly turning their attention to it. …”

Emil Fischer, Nobel Lecture, December, 12th 1902

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Fischer E (1966) In: Nobelstiftelsen (ed) Nobel lectures, chemistry 1901–1921, vol 1. Elsevier, Amsterdam, p 21–35

    Google Scholar 

  2. Anfinsen CB, Harrington WF, Hvidt A, Linderstrom-Lang K, Ottesen M, Schellman J (1989) Studies on the structural basis of ribonuclease activity. 1955. Biochim Biophys Acta 1000:200–201

    CAS  PubMed  Google Scholar 

  3. Drexler KE (1981) Molecular engineering: an approach to the development of general capabilities for molecular manipulation. Proc Natl Acad Sci U S A 78(9):5275–5278

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Pabo C (1983) Molecular technology. Designing proteins and peptides. Nature 301(5897):200

    Article  CAS  PubMed  Google Scholar 

  5. Jaramillo A, Wernisch L, Hery S, Wodak SJ (2002) Folding free energy function selects native-like protein sequences in the core but not on the surface. Proc Natl Acad Sci U S A 99(21):13554–13559. doi:10.1073/pnas.212068599

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Wernisch L, Hery S, Wodak SJ (2000) Automatic protein design with all atom force-fields by exact and heuristic optimization. J Mol Biol 301(3):713–736. doi:10.1006/jmbi.2000.3984

    Article  CAS  PubMed  Google Scholar 

  7. DeGrado WF, Prendergast FG, Wolfe HR Jr, Cox JA (1985) The design, synthesis, and characterization of tight-binding inhibitors of calmodulin. J Cell Biochem 29(2):83–93. doi:10.1002/jcb.240290204

    Article  CAS  PubMed  Google Scholar 

  8. Craik CS, Largman C, Fletcher T, Roczniak S, Barr PJ, Fletterick R, Rutter WJ (1985) Redesigning trypsin: alteration of substrate specificity. Science 228(4697):291–297

    Article  CAS  PubMed  Google Scholar 

  9. Vonderviszt F, Matrai G, Simon I (1986) Characteristic sequential residue environment of amino acids in proteins. Int J Pept Protein Res 27(5):483–492

    Article  CAS  PubMed  Google Scholar 

  10. Hecht MH, Richardson JS, Richardson DC, Ogden RC (1990) De novo design, expression, and characterization of Felix: a four-helix bundle protein of native-like sequence. Science 249(4971):884–891

    Article  CAS  PubMed  Google Scholar 

  11. Hellinga HW, Caradonna JP, Richards FM (1991) Construction of new ligand binding sites in proteins of known structure. II. Grafting of a buried transition metal binding site into Escherichia coli thioredoxin. J Mol Biol 222(3):787–803

    Article  CAS  PubMed  Google Scholar 

  12. Wilson C, Mace JE, Agard DA (1991) Computational method for the design of enzymes with altered substrate specificity. J Mol Biol 220(2):495–506

    Article  CAS  PubMed  Google Scholar 

  13. Hurley JH, Baase WA, Matthews BW (1992) Design and structural analysis of alternative hydrophobic core packing arrangements in bacteriophage T4 lysozyme. J Mol Biol 224(4):1143–1159

    Article  CAS  PubMed  Google Scholar 

  14. Quinn TP, Tweedy NB, Williams RW, Richardson JS, Richardson DC (1994) Betadoublet: de novo design, synthesis, and characterization of a beta-sandwich protein. Proc Natl Acad Sci U S A 91(19):8747–8751

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Desjarlais JR, Handel TM (1995) De novo design of the hydrophobic cores of proteins. Protein Sci 4(10):2006–2018. doi:10.1002/pro.5560041006

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Lazar GA, Desjarlais JR, Handel TM (1997) De novo design of the hydrophobic core of ubiquitin. Protein Sci 6(6):1167–1178. doi:10.1002/pro.5560060605

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Johnson EC, Lazar GA, Desjarlais JR, Handel TM (1999) Solution structure and dynamics of a designed hydrophobic core variant of ubiquitin. Structure 7(8):967–976

    Article  CAS  PubMed  Google Scholar 

  18. Dahiyat BI, Mayo SL (1997) De novo protein design: fully automated sequence selection. Science 278(5335):82–87

    Article  CAS  PubMed  Google Scholar 

  19. Dahiyat BI, Sarisky CA, Mayo SL (1997) De novo protein design: towards fully automated sequence selection. J Mol Biol 273(4):789–796. doi:10.1006/jmbi.1997.1341

    Article  CAS  PubMed  Google Scholar 

  20. Malakauskas SM, Mayo SL (1998) Design, structure and stability of a hyperthermophilic protein variant. Nat Struct Biol 5(6):470–475

    Article  CAS  PubMed  Google Scholar 

  21. Harbury PB, Plecs JJ, Tidor B, Alber T, Kim PS (1998) High-resolution protein design with backbone freedom. Science 282(5393):1462–1467

    Article  CAS  PubMed  Google Scholar 

  22. Bryson JW, Desjarlais JR, Handel TM, DeGrado WF (1998) From coiled coils to small globular proteins: design of a native-like three-helix bundle. Protein Sci 7(6):1404–1414. doi:10.1002/pro.5560070617

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Walsh ST, Cheng H, Bryson JW, Roder H, DeGrado WF (1999) Solution structure and dynamics of a de novo designed three-helix bundle protein. Proc Natl Acad Sci U S A 96(10):5486–5491

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Domingues H, Cregut D, Sebald W, Oschkinat H, Serrano L (1999) Rational design of a GCN4-derived mimetic of interleukin-4. Nat Struct Biol 6(7):652–656. doi:10.1038/10706

    Article  CAS  PubMed  Google Scholar 

  25. Kuhlman B, O’Neill JW, Kim DE, Zhang KY, Baker D (2001) Conversion of monomeric protein L to an obligate dimer by computational protein design. Proc Natl Acad Sci U S A 98(19):10687–10691. doi:10.1073/pnas.181354398

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Lopez de la Paz M, Lacroix E, Ramirez-Alvarado M, Serrano L (2001) Computer-aided design of beta-sheet peptides. J Mol Biol 312(1):229–246. doi:10.1006/jmbi.2001.4918

    Article  CAS  PubMed  Google Scholar 

  27. Bolon DN, Mayo SL (2001) Enzyme-like proteins by computational design. Proc Natl Acad Sci U S A 98(25):14274–14279. doi:10.1073/pnas.251555398

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Keating AE, Malashkevich VN, Tidor B, Kim PS (2001) Side-chain repacking calculations for predicting structures and stabilities of heterodimeric coiled coils. Proc Natl Acad Sci U S A 98(26):14825–14830. doi:10.1073/pnas.261563398

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Summa CM, Rosenblatt MM, Hong JK, Lear JD, DeGrado WF (2002) Computational de novo design, and characterization of an A(2)B(2) diiron protein. J Mol Biol 321(5):923–938

    Article  CAS  PubMed  Google Scholar 

  30. Ventura S, Vega MC, Lacroix E, Angrand I, Spagnolo L, Serrano L (2002) Conformational strain in the hydrophobic core and its implications for protein folding and design. Nat Struct Biol 9(6):485–493. doi:10.1038/nsb799

    Article  CAS  PubMed  Google Scholar 

  31. Shifman JM, Mayo SL (2002) Modulating calmodulin binding specificity through computational protein design. J Mol Biol 323(3):417–423

    Article  CAS  PubMed  Google Scholar 

  32. Shifman JM, Mayo SL (2003) Exploring the origins of binding specificity through the computational redesign of calmodulin. Proc Natl Acad Sci U S A 100(23):13274–13279. doi:10.1073/pnas.2234277100

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Hayes RJ, Bentzien J, Ary ML, Hwang MY, Jacinto JM, Vielmetter J, Kundu A, Dahiyat BI (2002) Combining computational and experimental screening for rapid optimization of protein properties. Proc Natl Acad Sci U S A 99(25):15926–15931. doi:10.1073/pnas.212627499

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Filikov AV, Hayes RJ, Luo P, Stark DM, Chan C, Kundu A, Dahiyat BI (2002) Computational stabilization of human growth hormone. Protein Sci 11(6):1452–1461. doi:10.1110/ps.3500102

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Luo P, Hayes RJ, Chan C, Stark DM, Hwang MY, Jacinto JM, Juvvadi P, Chung HS, Kundu A, Ary ML, Dahiyat BI (2002) Development of a cytokine analog with enhanced stability using computational ultrahigh throughput screening. Protein Sci 11(5):1218–1226. doi:10.1110/ps.4580102

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Chevalier BS, Kortemme T, Chadsey MS, Baker D, Monnat RJ, Stoddard BL (2002) Design, activity, and structure of a highly specific artificial endonuclease. Mol Cell 10(4):895–905

    Article  CAS  PubMed  Google Scholar 

  37. Ogata K, Jaramillo A, Cohen W, Briand JP, Connan F, Choppin J, Muller S, Wodak SJ (2003) Automatic sequence design of major histocompatibility complex class I binding peptides impairing CD8+ T cell recognition. J Biol Chem 278(2):1281–1290. doi:10.1074/jbc.M206853200

    Article  CAS  PubMed  Google Scholar 

  38. Slovic AM, Summa CM, Lear JD, DeGrado WF (2003) Computational design of a water-soluble analog of phospholamban. Protein Sci 12(2):337–348. doi:10.1110/ps.0226603

    Article  PubMed  PubMed Central  Google Scholar 

  39. Slovic AM, Stayrook SE, North B, Degrado WF (2005) X-ray structure of a water-soluble analog of the membrane protein phospholamban: sequence determinants defining the topology of tetrameric and pentameric coiled coils. J Mol Biol 348(3):777–787. doi:10.1016/j.jmb.2005.02.040

    Article  CAS  PubMed  Google Scholar 

  40. Havranek JJ, Harbury PB (2003) Automated design of specificity in molecular recognition. Nat Struct Biol 10(1):45–52. doi:10.1038/nsb877

    Article  CAS  PubMed  Google Scholar 

  41. Calhoun JR, Kono H, Lahr S, Wang W, DeGrado WF, Saven JG (2003) Computational design and characterization of a monomeric helical dinuclear metalloprotein. J Mol Biol 334(5):1101–1115

    Article  CAS  PubMed  Google Scholar 

  42. Calhoun JR, Liu W, Spiegel K, Dal Peraro M, Klein ML, Valentine KG, Wand AJ, DeGrado WF (2008) Solution NMR structure of a designed metalloprotein and complementary molecular dynamics refinement. Structure 16(2):210–215. doi:10.1016/j.str.2007.11.011

    Article  CAS  PubMed  Google Scholar 

  43. Kuhlman B, Dantas G, Ireton GC, Varani G, Stoddard BL, Baker D (2003) Design of a novel globular protein fold with atomic-level accuracy. Science 302(5649):1364–1368. doi:10.1126/science.1089427

    Article  CAS  PubMed  Google Scholar 

  44. Kraemer-Pecore CM, Lecomte JT, Desjarlais JR (2003) A de novo redesign of the WW domain. Protein Sci 12(10):2194–2205. doi:10.1110/ps.03190903

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Dantas G, Kuhlman B, Callender D, Wong M, Baker D (2003) A large scale test of computational protein design: folding and stability of nine completely redesigned globular proteins. J Mol Biol 332(2):449–460

    Article  CAS  PubMed  Google Scholar 

  46. Dantas G, Corrent C, Reichow SL, Havranek JJ, Eletr ZM, Isern NG, Kuhlman B, Varani G, Merritt EA, Baker D (2007) High-resolution structural and thermodynamic analysis of extreme stabilization of human procarboxypeptidase by computational protein design. J Mol Biol 366(4):1209–1221. doi:10.1016/j.jmb.2006.11.080

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Di Costanzo L, Wade H, Geremia S, Randaccio L, Pavone V, DeGrado WF, Lombardi A (2001) Toward the de novo design of a catalytically active helix bundle: a substrate-accessible carboxylate-bridged dinuclear metal center. J Am Chem Soc 123(51):12749–12757

    Article  PubMed  CAS  Google Scholar 

  48. Kaplan J, DeGrado WF (2004) De novo design of catalytic proteins. Proc Natl Acad Sci U S A 101(32):11566–11570. doi:10.1073/pnas.0404387101

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Kortemme T, Joachimiak LA, Bullock AN, Schuler AD, Stoddard BL, Baker D (2004) Computational redesign of protein-protein interaction specificity. Nat Struct Mol Biol 11(4):371–379. doi:10.1038/nsmb749

    Article  CAS  PubMed  Google Scholar 

  50. Joachimiak LA, Kortemme T, Stoddard BL, Baker D (2006) Computational design of a new hydrogen bond network and at least a 300-fold specificity switch at a protein-protein interface. J Mol Biol 361(1):195–208. doi:10.1016/j.jmb.2006.05.022

    Article  CAS  PubMed  Google Scholar 

  51. Slovic AM, Kono H, Lear JD, Saven JG, DeGrado WF (2004) Computational design of water-soluble analogues of the potassium channel KcsA. Proc Natl Acad Sci U S A 101(7):1828–1833. doi:10.1073/pnas.0306417101

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Korkegian A, Black ME, Baker D, Stoddard BL (2005) Computational thermostabilization of an enzyme. Science 308(5723):857–860. doi:10.1126/science.1107387

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Bolon DN, Grant RA, Baker TA, Sauer RT (2005) Specificity versus stability in computational protein design. Proc Natl Acad Sci U S A 102(36):12724–12729. doi:10.1073/pnas.0506124102

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Nanda V, Rosenblatt MM, Osyczka A, Kono H, Getahun Z, Dutton PL, Saven JG, Degrado WF (2005) De novo design of a redox-active minimal rubredoxin mimic. J Am Chem Soc 127(16):5804–5805. doi:10.1021/ja050553f

    Article  CAS  PubMed  Google Scholar 

  55. Cochran FV, Wu SP, Wang W, Nanda V, Saven JG, Therien MJ, DeGrado WF (2005) Computational de novo design and characterization of a four-helix bundle protein that selectively binds a nonbiological cofactor. J Am Chem Soc 127(5):1346–1347. doi:10.1021/ja044129a

    Article  CAS  PubMed  Google Scholar 

  56. Swift J, Wehbi WA, Kelly BD, Stowell XF, Saven JG, Dmochowski IJ (2006) Design of functional ferritin-like proteins with hydrophobic cavities. J Am Chem Soc 128(20):6611–6619. doi:10.1021/ja057069x

    Article  CAS  PubMed  Google Scholar 

  57. van der Sloot AM, Tur V, Szegezdi E, Mullally MM, Cool RH, Samali A, Serrano L, Quax WJ (2006) Designed tumor necrosis factor-related apoptosis-inducing ligand variants initiating apoptosis exclusively via the DR5 receptor. Proc Natl Acad Sci U S A 103(23):8634–8639. doi:10.1073/pnas.0510187103

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Ashworth J, Havranek JJ, Duarte CM, Sussman D, Monnat RJ Jr, Stoddard BL, Baker D (2006) Computational redesign of endonuclease DNA binding and cleavage specificity. Nature 441(7093):656–659. doi:10.1038/nature04818

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Lazar GA, Dang W, Karki S, Vafa O, Peng JS, Hyun L, Chan C, Chung HS, Eivazi A, Yoder SC, Vielmetter J, Carmichael DF, Hayes RJ, Dahiyat BI (2006) Engineered antibody Fc variants with enhanced effector function. Proc Natl Acad Sci U S A 103(11):4005–4010. doi:10.1073/pnas.0508123103

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Huang PS, Love JJ, Mayo SL (2007) A de novo designed protein protein interface. Protein Sci 16(12):2770–2774. doi:10.1110/ps.073125207

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Yin H, Slusky JS, Berger BW, Walters RS, Vilaire G, Litvinov RI, Lear JD, Caputo GA, Bennett JS, DeGrado WF (2007) Computational design of peptides that target transmembrane helices. Science 315(5820):1817–1822. doi:10.1126/science.1136782

    Article  CAS  PubMed  Google Scholar 

  62. Hu X, Wang H, Ke H, Kuhlman B (2007) High-resolution design of a protein loop. Proc Natl Acad Sci U S A 104(45):17668–17673. doi:10.1073/pnas.0707977104

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Liu S, Liu S, Zhu X, Liang H, Cao A, Chang Z, Lai L (2007) Nonnatural protein-protein interaction-pair design by key residues grafting. Proc Natl Acad Sci U S A 104(13):5330–5335. doi:10.1073/pnas.0606198104

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Shah PS, Hom GK, Ross SA, Lassila JK, Crowhurst KA, Mayo SL (2007) Full-sequence computational design and solution structure of a thermostable protein variant. J Mol Biol 372(1):1–6. doi:10.1016/j.jmb.2007.06.032

    Article  CAS  PubMed  Google Scholar 

  65. Bender GM, Lehmann A, Zou H, Cheng H, Fry HC, Engel D, Therien MJ, Blasie JK, Roder H, Saven JG, DeGrado WF (2007) De novo design of a single-chain diphenylporphyrin metalloprotein. J Am Chem Soc 129(35):10732–10740. doi:10.1021/ja071199j

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Lippow SM, Wittrup KD, Tidor B (2007) Computational design of antibody-affinity improvement beyond in vivo maturation. Nat Biotechnol 25(10):1171–1176. doi:10.1038/nbt1336

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Potapov V, Reichmann D, Abramovich R, Filchtinski D, Zohar N, Ben Halevy D, Edelman M, Sobolev V, Schreiber G (2008) Computational redesign of a protein-protein interface for high affinity and binding specificity using modular architecture and naturally occurring template fragments. J Mol Biol 384(1):109–119. doi:10.1016/j.jmb.2008.08.078

    Article  CAS  PubMed  Google Scholar 

  68. Butts CA, Swift J, Kang SG, Di Costanzo L, Christianson DW, Saven JG, Dmochowski IJ (2008) Directing noble metal ion chemistry within a designed ferritin protein. Biochemistry 47(48):12729–12739. doi:10.1021/bi8016735

    Article  CAS  PubMed  Google Scholar 

  69. Reynolds KA, Hanes MS, Thomson JM, Antczak AJ, Berger JM, Bonomo RA, Kirsch JF, Handel TM (2008) Computational redesign of the SHV-1 beta-lactamase/beta-lactamase inhibitor protein interface. J Mol Biol 382(5):1265–1275. doi:10.1016/j.jmb.2008.05.051

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. McAllister KA, Zou H, Cochran FV, Bender GM, Senes A, Fry HC, Nanda V, Keenan PA, Lear JD, Saven JG, Therien MJ, Blasie JK, DeGrado WF (2008) Using alpha-helical coiled-coils to design nanostructured metalloporphyrin arrays. J Am Chem Soc 130(36):11921–11927. doi:10.1021/ja800697g

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Jiang L, Althoff EA, Clemente FR, Doyle L, Rothlisberger D, Zanghellini A, Gallaher JL, Betker JL, Tanaka F, Barbas CF 3rd, Hilvert D, Houk KN, Stoddard BL, Baker D (2008) De novo computational design of retro-aldol enzymes. Science 319(5868):1387–1391. doi:10.1126/science.1152692

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Rothlisberger D, Khersonsky O, Wollacott AM, Jiang L, DeChancie J, Betker J, Gallaher JL, Althoff EA, Zanghellini A, Dym O, Albeck S, Houk KN, Tawfik DS, Baker D (2008) Kemp elimination catalysts by computational enzyme design. Nature 453(7192):190–195. doi:10.1038/nature06879

    Article  PubMed  CAS  Google Scholar 

  73. Murphy PM, Bolduc JM, Gallaher JL, Stoddard BL, Baker D (2009) Alteration of enzyme specificity by computational loop remodeling and design. Proc Natl Acad Sci U S A 106(23):9215–9220. doi:10.1073/pnas.0811070106

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Yosef E, Politi R, Choi MH, Shifman JM (2009) Computational design of calmodulin mutants with up to 900-fold increase in binding specificity. J Mol Biol 385(5):1470–1480. doi:10.1016/j.jmb.2008.09.053

    Article  CAS  PubMed  Google Scholar 

  75. Grigoryan G, Reinke AW, Keating AE (2009) Design of protein-interaction specificity gives selective bZIP-binding peptides. Nature 458(7240):859–864. doi:10.1038/nature07885

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Thyme SB, Jarjour J, Takeuchi R, Havranek JJ, Ashworth J, Scharenberg AM, Stoddard BL, Baker D (2009) Exploitation of binding energy for catalysis and design. Nature 461(7268):1300–1304. doi:10.1038/nature08508

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Chen CY, Georgiev I, Anderson AC, Donald BR (2009) Computational structure-based redesign of enzyme activity. Proc Natl Acad Sci U S A 106(10):3764–3769. doi:10.1073/pnas.0900266106

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Fry HC, Lehmann A, Saven JG, DeGrado WF, Therien MJ (2010) Computational design and elaboration of a de novo heterotetrameric alpha-helical protein that selectively binds an emissive abiological (porphinato)zinc chromophore. J Am Chem Soc 132(11):3997–4005. doi:10.1021/ja907407m

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Ashworth J, Taylor GK, Havranek JJ, Quadri SA, Stoddard BL, Baker D (2010) Computational reprogramming of homing endonuclease specificity at multiple adjacent base pairs. Nucleic Acids Res 38(16):5601–5608. doi:10.1093/nar/gkq283

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Chica RA, Moore MM, Allen BD, Mayo SL (2010) Generation of longer emission wavelength red fluorescent proteins using computationally designed libraries. Proc Natl Acad Sci U S A 107(47):20257–20262. doi:10.1073/pnas.1013910107

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Korendovych IV, Senes A, Kim YH, Lear JD, Fry HC, Therien MJ, Blasie JK, Walker FA, Degrado WF (2010) De novo design and molecular assembly of a transmembrane diporphyrin-binding protein complex. J Am Chem Soc 132(44):15516–15518. doi:10.1021/ja107487b

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Jha RK, Leaver-Fay A, Yin S, Wu Y, Butterfoss GL, Szyperski T, Dokholyan NV, Kuhlman B (2010) Computational design of a PAK1 binding protein. J Mol Biol 400(2):257–270. doi:10.1016/j.jmb.2010.05.006

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Allen BD, Nisthal A, Mayo SL (2010) Experimental library screening demonstrates the successful application of computational protein design to large structural ensembles. Proc Natl Acad Sci U S A 107(46):19838–19843. doi:10.1073/pnas.1012985107

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Frey KM, Georgiev I, Donald BR, Anderson AC (2010) Predicting resistance mutations using protein design algorithms. Proc Natl Acad Sci U S A 107(31):13707–13712. doi:10.1073/pnas.1002162107

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Grigoryan G, Kim YH, Acharya R, Axelrod K, Jain RM, Willis L, Drndic M, Kikkawa JM, DeGrado WF (2011) Computational design of virus-like protein assemblies on carbon nanotube surfaces. Science 332(6033):1071–1076. doi:10.1126/science.1198841

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Fleishman SJ, Whitehead TA, Ekiert DC, Dreyfus C, Corn JE, Strauch EM, Wilson IA, Baker D (2011) Computational design of proteins targeting the conserved stem region of influenza hemagglutinin. Science 332(6031):816–821. doi:10.1126/science.1202617

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Karanicolas J, Corn JE, Chen I, Joachimiak LA, Dym O, Peck SH, Albeck S, Unger T, Hu W, Liu G, Delbecq S, Montelione GT, Spiegel CP, Liu DR, Baker D (2011) A de novo protein binding pair by computational design and directed evolution. Mol Cell 42(2):250–260. doi:10.1016/j.molcel.2011.03.010

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Stranges PB, Machius M, Miley MJ, Tripathy A, Kuhlman B (2011) Computational design of a symmetric homodimer using beta-strand assembly. Proc Natl Acad Sci U S A 108(51):20562–20567. doi:10.1073/pnas.1115124108

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Correia BE, Ban YE, Friend DJ, Ellingson K, Xu H, Boni E, Bradley-Hewitt T, Bruhn-Johannsen JF, Stamatatos L, Strong RK, Schief WR (2011) Computational protein design using flexible backbone remodeling and resurfacing: case studies in structure-based antigen design. J Mol Biol 405(1):284–297. doi:10.1016/j.jmb.2010.09.061

    Article  CAS  PubMed  Google Scholar 

  90. Diaz JE, Lin CS, Kunishiro K, Feld BK, Avrantinis SK, Bronson J, Greaves J, Saven JG, Weiss GA (2011) Computational design and selections for an engineered, thermostable terpene synthase. Protein Sci 20(9):1597–1606. doi:10.1002/pro.691

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Xu F, Zahid S, Silva T, Nanda V (2011) Computational design of a collagen A:B:C-type heterotrimer. J Am Chem Soc 133(39):15260–15263. doi:10.1021/ja205597g

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Korendovych IV, Kulp DW, Wu Y, Cheng H, Roder H, DeGrado WF (2011) Design of a switchable eliminase. Proc Natl Acad Sci U S A 108(17):6823–6827. doi:10.1073/pnas.1018191108

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Merski M, Shoichet BK (2012) Engineering a model protein cavity to catalyze the Kemp elimination. Proc Natl Acad Sci U S A 109(40):16179–16183. doi:10.1073/pnas.1208076109

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Cui T, Mowrey D, Bondarenko V, Tillman T, Ma D, Landrum E, Perez-Aguilar JM, He J, Wang W, Saven JG, Eckenhoff RG, Tang P, Xu Y (2012) NMR structure and dynamics of a designed water-soluble transmembrane domain of nicotinic acetylcholine receptor. Biochim Biophys Acta 1818(3):617–626. doi:10.1016/j.bbamem.2011.11.021

    Article  CAS  PubMed  Google Scholar 

  95. Khare SD, Kipnis Y, Greisen P Jr, Takeuchi R, Ashani Y, Goldsmith M, Song Y, Gallaher JL, Silman I, Leader H, Sussman JL, Stoddard BL, Tawfik DS, Baker D (2012) Computational redesign of a mononuclear zinc metalloenzyme for organophosphate hydrolysis. Nat Chem Biol 8(3):294–300. doi:10.1038/nchembio.777

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Azoitei ML, Ban YE, Julien JP, Bryson S, Schroeter A, Kalyuzhniy O, Porter JR, Adachi Y, Baker D, Pai EF, Schief WR (2012) Computational design of high-affinity epitope scaffolds by backbone grafting of a linear epitope. J Mol Biol 415(1):175–192. doi:10.1016/j.jmb.2011.10.003

    Article  CAS  PubMed  Google Scholar 

  97. Kapp GT, Liu S, Stein A, Wong DT, Remenyi A, Yeh BJ, Fraser JS, Taunton J, Lim WA, Kortemme T (2012) Control of protein signaling using a computationally designed GTPase/GEF orthogonal pair. Proc Natl Acad Sci U S A 109(14):5277–5282. doi:10.1073/pnas.1114487109

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Koga N, Tatsumi-Koga R, Liu G, Xiao R, Acton TB, Montelione GT, Baker D (2012) Principles for designing ideal protein structures. Nature 491(7423):222–227. doi:10.1038/nature11600

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Fallas JA, Hartgerink JD (2012) Computational design of self-assembling register-specific collagen heterotrimers. Nat Commun 3:1087. doi:10.1038/ncomms2084

    Article  PubMed  CAS  Google Scholar 

  100. Privett HK, Kiss G, Lee TM, Blomberg R, Chica RA, Thomas LM, Hilvert D, Houk KN, Mayo SL (2012) Iterative approach to computational enzyme design. Proc Natl Acad Sci U S A 109(10):3790–3795. doi:10.1073/pnas.1118082108

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Blomberg R, Kries H, Pinkas DM, Mittl PR, Grutter MG, Privett HK, Mayo SL, Hilvert D (2013) Precision is essential for efficient catalysis in an evolved Kemp eliminase. Nature 503(7476):418–421. doi:10.1038/nature12623

    Article  CAS  PubMed  Google Scholar 

  102. Grzyb J, Xu F, Nanda V, Luczkowska R, Reijerse E, Lubitz W, Noy D (2012) Empirical and computational design of iron-sulfur cluster proteins. Biochim Biophys Acta 1817(8):1256–1262. doi:10.1016/j.bbabio.2012.02.001

    Article  CAS  PubMed  Google Scholar 

  103. Lanci CJ, MacDermaid CM, Kang SG, Acharya R, North B, Yang X, Qiu XJ, DeGrado WF, Saven JG (2012) Computational design of a protein crystal. Proc Natl Acad Sci U S A 109(19):7304–7309. doi:10.1073/pnas.1112595109

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Reig AJ, Pires MM, Snyder RA, Wu Y, Jo H, Kulp DW, Butch SE, Calhoun JR, Szyperski T, Solomon EI, DeGrado WF (2012) Alteration of the oxygen-dependent reactivity of de novo Due Ferri proteins. Nat Chem 4(11):900–906. doi:10.1038/nchem.1454

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Dagliyan O, Shirvanyants D, Karginov AV, Ding F, Fee L, Chandrasekaran SN, Freisinger CM, Smolen GA, Huttenlocher A, Hahn KM, Dokholyan NV (2013) Rational design of a ligand-controlled protein conformational switch. Proc Natl Acad Sci U S A 110(17):6800–6804. doi:10.1073/pnas.1218319110

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Fry HC, Lehmann A, Sinks LE, Asselberghs I, Tronin A, Krishnan V, Blasie JK, Clays K, DeGrado WF, Saven JG, Therien MJ (2013) Computational de novo design and characterization of a protein that selectively binds a highly hyperpolarizable abiological chromophore. J Am Chem Soc 135(37):13914–13926. doi:10.1021/ja4067404

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Perez-Aguilar JM, Xi J, Matsunaga F, Cui X, Selling B, Saven JG, Liu R (2013) A computationally designed water-soluble variant of a G-protein-coupled receptor: the human mu opioid receptor. PLoS One 8(6), e66009. doi:10.1371/journal.pone.0066009

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Lerner MB, Matsunaga F, Han GH, Hong SJ, Xi J, Crook A, Perez-Aguilar JM, Park YW, Saven JG, Liu R, Johnson AT (2014) Scalable production of highly sensitive nanosensors based on graphene functionalized with a designed G protein-coupled receptor. Nano Lett 14(5):2709–2714. doi:10.1021/nl5006349

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Procko E, Hedman R, Hamilton K, Seetharaman J, Fleishman SJ, Su M, Aramini J, Kornhaber G, Hunt JF, Tong L, Montelione GT, Baker D (2013) Computational design of a protein-based enzyme inhibitor. J Mol Biol 425(18):3563–3575. doi:10.1016/j.jmb.2013.06.035

    Article  CAS  PubMed  Google Scholar 

  110. Tinberg CE, Khare SD, Dou J, Doyle L, Nelson JW, Schena A, Jankowski W, Kalodimos CG, Johnsson K, Stoddard BL, Baker D (2013) Computational design of ligand-binding proteins with high affinity and selectivity. Nature 501(7466):212–216. doi:10.1038/nature12443

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Strauch EM, Fleishman SJ, Baker D (2014) Computational design of a pH-sensitive IgG binding protein. Proc Natl Acad Sci U S A 111(2):675–680. doi:10.1073/pnas.1313605111

    Article  CAS  PubMed  Google Scholar 

  112. Xiong P, Wang M, Zhou X, Zhang T, Zhang J, Chen Q, Liu H (2014) Protein design with a comprehensive statistical energy function and boosted by experimental selection for foldability. Nat Commun 5:5330. doi:10.1038/ncomms6330

    Article  CAS  PubMed  Google Scholar 

  113. Huang PS, Oberdorfer G, Xu C, Pei XY, Nannenga BL, Rogers JM, DiMaio F, Gonen T, Luisi B, Baker D (2014) High thermodynamic stability of parametrically designed helical bundles. Science 346(6208):481–485. doi:10.1126/science.1257481

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Thomson AR, Wood CW, Burton AJ, Bartlett GJ, Sessions RB, Brady RL, Woolfson DN (2014) Computational design of water-soluble alpha-helical barrels. Science 346(6208):485–488. doi:10.1126/science.1257452

    Article  CAS  PubMed  Google Scholar 

  115. Negron C, Keating AE (2014) A set of computationally designed orthogonal antiparallel homodimers that expands the synthetic coiled-coil toolkit. J Am Chem Soc 136(47):16544–16556. doi:10.1021/ja507847t

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Correia BE, Bates JT, Loomis RJ, Baneyx G, Carrico C, Jardine JG, Rupert P, Correnti C, Kalyuzhniy O, Vittal V, Connell MJ, Stevens E, Schroeter A, Chen M, Macpherson S, Serra AM, Adachi Y, Holmes MA, Li Y, Klevit RE, Graham BS, Wyatt RT, Baker D, Strong RK, Crowe JE Jr, Johnson PR, Schief WR (2014) Proof of principle for epitope-focused vaccine design. Nature 507(7491):201–206. doi:10.1038/nature12966

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Joh NH, Wang T, Bhate MP, Acharya R, Wu Y, Grabe M, Hong M, Grigoryan G, DeGrado WF (2014) De novo design of a transmembrane Zn(2)(+)-transporting four-helix bundle. Science 346(6216):1520–1524. doi:10.1126/science.1261172

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. King C, Garza EN, Mazor R, Linehan JL, Pastan I, Pepper M, Baker D (2014) Removing T-cell epitopes with computational protein design. Proc Natl Acad Sci U S A 111(23):8577–8582. doi:10.1073/pnas.1321126111

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Voet AR, Noguchi H, Addy C, Simoncini D, Terada D, Unzai S, Park SY, Zhang KY, Tame JR (2014) Computational design of a self-assembling symmetrical beta-propeller protein. Proc Natl Acad Sci U S A 111(42):15102–15107. doi:10.1073/pnas.1412768111

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Ramisch S, Weininger U, Martinsson J, Akke M, Andre I (2014) Computational design of a leucine-rich repeat protein with a predefined geometry. Proc Natl Acad Sci U S A 111(50):17875–17880. doi:10.1073/pnas.1413638111

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  121. Samish I, MacDermaid CM, Perez-Aguilar JM, Saven JG (2011) Theoretical and computational protein design. Annu Rev Phys Chem 62:129–149. doi:10.1146/annurev-physchem-032210-103509

    Article  CAS  PubMed  Google Scholar 

  122. Pantazes RJ, Grisewood MJ, Maranas CD (2011) Recent advances in computational protein design. Curr Opin Struct Biol 21(4):467–472. doi:10.1016/j.sbi.2011.04.005

    Article  CAS  PubMed  Google Scholar 

  123. O’Neil KT, DeGrado WF (1985) A predicted structure of calmodulin suggests an electrostatic basis for its function. Proc Natl Acad Sci U S A 82(15):4954–4958

    Article  PubMed  PubMed Central  Google Scholar 

  124. Weiner SJ, Kollman PA, Case DA, Singh UC, Ghio C, Alagona G, Profeta S, Weiner P (1984) A new force field for molecular mechanical simulation of nucleic acids and proteins. J Am Chem Soc 106(3):765–784

    Article  CAS  Google Scholar 

  125. Hellinga HW, Richards FM (1991) Construction of new ligand binding sites in proteins of known structure. I. Computer-aided modeling of sites with pre-defined geometry. J Mol Biol 222(3):763–785

    Article  CAS  PubMed  Google Scholar 

  126. Ponder JW, Richards FM (1987) Tertiary templates for proteins. Use of packing criteria in the enumeration of allowed sequences for different structural classes. J Mol Biol 193(4):775–791

    Article  CAS  PubMed  Google Scholar 

  127. Bryson JW, Betz SF, Lu HS, Suich DJ, Zhou HX, O’Neil KT, DeGrado WF (1995) Protein design: a hierarchic approach. Science 270(5238):935–941

    Article  CAS  PubMed  Google Scholar 

  128. Raha K, Wollacott AM, Italia MJ, Desjarlais JR (2000) Prediction of amino acid sequence from structure. Protein Sci 9(6):1106–1119. doi:10.1110/ps.9.6.1106

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Desmet J, De Maeyer M, Hazes B, Lasters I (1992) The dead-end elimination theorem and its use in protein side-chain positioning. Nature 356(6369):539–542

    Article  CAS  PubMed  Google Scholar 

  130. Samish I (2009) Search and sampling in structural bioinformatics. In: Bourne P, Gu J (eds) Structural bioinformatics. Wiley, Hoboken, NJ, pp 207–236

    Google Scholar 

  131. Dunbrack RL Jr, Karplus M (1993) Backbone-dependent rotamer library for proteins. Application to side-chain prediction. J Mol Biol 230(2):543–574. doi:10.1006/jmbi.1993.1170

    Article  CAS  PubMed  Google Scholar 

  132. Tuffery P, Etchebest C, Hazout S, Lavery R (1991) A new approach to the rapid determination of protein side chain conformations. J Biomol Struct Dyn 8(6):1267–1289. doi:10.1080/07391102.1991.10507882

    Article  CAS  PubMed  Google Scholar 

  133. Bowers PM, Strauss CE, Baker D (2000) De novo protein structure determination using sparse NMR data. J Biomol NMR 18(4):311–318

    Article  CAS  PubMed  Google Scholar 

  134. Kuhlman B, Baker D (2000) Native protein sequences are close to optimal for their structures. Proc Natl Acad Sci U S A 97(19):10383–10388

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Fisinger S, Serrano L, Lacroix E (2001) Computational estimation of specific side chain interaction energies in alpha helices. Protein Sci 10(4):809–818. doi:10.1110/ps.34901

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  136. Kortemme T, Ramirez-Alvarado M, Serrano L (1998) Design of a 20-amino acid, three-stranded beta-sheet protein. Science 281(5374):253–256

    Article  CAS  PubMed  Google Scholar 

  137. Debler EW, Ito S, Seebeck FP, Heine A, Hilvert D, Wilson IA (2005) Structural origins of efficient proton abstraction from carbon by a catalytic antibody. Proc Natl Acad Sci U S A 102(14):4984–4989. doi:10.1073/pnas.0409207102

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Khersonsky O, Rothlisberger D, Wollacott AM, Murphy P, Dym O, Albeck S, Kiss G, Houk KN, Baker D, Tawfik DS (2011) Optimization of the in-silico-designed kemp eliminase KE70 by computational design and directed evolution. J Mol Biol 407(3):391–412. doi:10.1016/j.jmb.2011.01.041

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  139. Khersonsky O, Rothlisberger D, Dym O, Albeck S, Jackson CJ, Baker D, Tawfik DS (2010) Evolutionary optimization of computationally designed enzymes: Kemp eliminases of the KE07 series. J Mol Biol 396(4):1025–1042. doi:10.1016/j.jmb.2009.12.031

    Article  CAS  PubMed  Google Scholar 

  140. Khersonsky O, Kiss G, Rothlisberger D, Dym O, Albeck S, Houk KN, Baker D, Tawfik DS (2012) Bridging the gaps in design methodologies by evolutionary optimization of the stability and proficiency of designed Kemp eliminase KE59. Proc Natl Acad Sci U S A 109(26):10358–10363. doi:10.1073/pnas.1121063109

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Dahiyat BI, Mayo SL (1996) Protein design automation. Protein Sci 5(5):895–903. doi:10.1002/pro.5560050511

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  142. Kortemme T, Baker D (2002) A simple physical model for binding energy hot spots in protein-protein complexes. Proc Natl Acad Sci U S A 99(22):14116–14121. doi:10.1073/pnas.202485799

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  143. Kono H, Saven JG (2001) Statistical theory for protein combinatorial libraries. Packing interactions, backbone flexibility, and the sequence variability of a main-chain structure. J Mol Biol 306(3):607–628. doi:10.1006/jmbi.2000.4422

    Article  CAS  PubMed  Google Scholar 

  144. Lombardi A, Summa CM, Geremia S, Randaccio L, Pavone V, DeGrado WF (2000) Retrostructural analysis of metalloproteins: application to the design of a minimal model for diiron proteins. Proc Natl Acad Sci U S A 97(12):6298–6305

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  145. Dunbrack RL Jr, Cohen FE (1997) Bayesian statistical analysis of protein side-chain rotamer preferences. Protein Sci 6(8):1661–1681. doi:10.1002/pro.5560060807

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  146. Fu X, Kono H, Saven JG (2003) Probabilistic approach to the design of symmetric protein quaternary structures. Protein Eng 16(12):971–977. doi:10.1093/protein/gzg132

    Article  CAS  PubMed  Google Scholar 

  147. Zhang SQ, Kulp DW, Schramm CA, Mravic M, Samish I, DeGrado WF (2015) The membrane- and soluble-protein helix-helix interactome: similar geometry via different interactions. Structure 23(3):527–541. doi:10.1016/j.str.2015.01.009

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  148. Smith MD, Zanghellini A, Grabs-Rothlisberger D (2014) Computational design of novel enzymes without cofactors. Methods Mol Biol 1216:197–210. doi:10.1007/978-1-4939-1486-9_10

    Article  PubMed  Google Scholar 

  149. Zanghellini A, Jiang L, Wollacott AM, Cheng G, Meiler J, Althoff EA, Rothlisberger D, Baker D (2006) New algorithms and an in silico benchmark for computational enzyme design. Protein Sci 15(12):2785–2794. doi:10.1110/ps.062353106

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  150. Richter F, Leaver-Fay A, Khare SD, Bjelic S, Baker D (2011) De novo enzyme design using Rosetta3. PLoS One 6(5), e19230. doi:10.1371/journal.pone.0019230

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  151. Frushicheva MP, Cao J, Chu ZT, Warshel A (2010) Exploring challenges in rational enzyme design by simulating the catalysis in artificial kemp eliminase. Proc Natl Acad Sci U S A 107(39):16869–16874. doi:10.1073/pnas.1010381107

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  152. Georgiev I, Lilien RH, Donald BR (2008) The minimized dead-end elimination criterion and its application to protein redesign in a hybrid scoring and search algorithm for computing partition functions over molecular ensembles. J Comput Chem 29(10):1527–1542. doi:10.1002/jcc.20909

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  153. Schneidman-Duhovny D, Inbar Y, Polak V, Shatsky M, Halperin I, Benyamini H, Barzilai A, Dror O, Haspel N, Nussinov R, Wolfson HJ (2003) Taking geometry to its edge: fast unbound rigid (and hinge-bent) docking. Proteins 52(1):107–112. doi:10.1002/prot.10397

    Article  CAS  PubMed  Google Scholar 

  154. Fiser A, Do RK, Sali A (2000) Modeling of loops in protein structures. Protein Sci 9(9):1753–1773. doi:10.1110/ps.9.9.1753

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  155. Ofek G, Guenaga FJ, Schief WR, Skinner J, Baker D, Wyatt R, Kwong PD (2010) Elicitation of structure-specific antibodies by epitope scaffolds. Proc Natl Acad Sci U S A 107(42):17880–17887. doi:10.1073/pnas.1004728107

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  156. Canutescu AA, Dunbrack RL Jr (2003) Cyclic coordinate descent: a robotics algorithm for protein loop closure. Protein Sci 12(5):963–972. doi:10.1110/ps.0242703

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  157. Smith CA, Kortemme T (2011) Predicting the tolerated sequences for proteins and protein interfaces using RosettaBackrub flexible backbone design. PLoS One 6(7), e20451. doi:10.1371/journal.pone.0020451

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  158. Mandell DJ, Coutsias EA, Kortemme T (2009) Sub-angstrom accuracy in protein loop reconstruction by robotics-inspired conformational sampling. Nat Methods 6(8):551–552. doi:10.1038/nmeth0809-551

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  159. Roy A, Kucukural A, Zhang Y (2010) I-TASSER: a unified platform for automated protein structure and function prediction. Nat Protoc 5(4):725–738. doi:10.1038/nprot.2010.5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  160. Summa CM, Levitt M, Degrado WF (2005) An atomic environment potential for use in protein structure prediction. J Mol Biol 352(4):986–1001. doi:10.1016/j.jmb.2005.07.054

    Article  CAS  PubMed  Google Scholar 

  161. Antonkine ML, Maes EM, Czernuszewicz RS, Breitenstein C, Bill E, Falzone CJ, Balasubramanian R, Lubner C, Bryant DA, Golbeck JH (2007) Chemical rescue of a site-modified ligand to a [4Fe-4S] cluster in PsaC, a bacterial-like dicluster ferredoxin bound to Photosystem I. Biochim Biophys Acta 1767(6):712–724. doi:10.1016/j.bbabio.2007.02.003

    Article  CAS  PubMed  Google Scholar 

  162. Kulp DW, Subramaniam S, Donald JE, Hannigan BT, Mueller BK, Grigoryan G, Senes A (2012) Structural informatics, modeling, and design with an open-source Molecular Software Library (MSL). J Comput Chem 33(20):1645–1661. doi:10.1002/jcc.22968

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  163. Yang Y, Zhou Y (2008) Ab initio folding of terminal segments with secondary structures reveals the fine difference between two closely related all-atom statistical energy functions. Protein Sci 17(7):1212–1219. doi:10.1110/ps.033480.107

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  164. Schramm CA, Hannigan BT, Donald JE, Keasar C, Saven JG, Degrado WF, Samish I (2012) Knowledge-based potential for positioning membrane-associated structures and assessing residue-specific energetic contributions. Structure 20(5):924–935. doi:10.1016/j.str.2012.03.016

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  165. Grigoryan G (2013) Absolute free energies of biomolecules from unperturbed ensembles. J Comput Chem 34(31):2726–2741. doi:10.1002/jcc.23448

    Article  CAS  PubMed  Google Scholar 

  166. Dwyer MA, Looger LL, Hellinga HW (2008) Retraction. Science 319(5863):569. doi:10.1126/science.319.5863.569b

    Article  CAS  PubMed  Google Scholar 

  167. Dwyer MA, Looger LL, Hellinga HW (2004) Computational design of a biologically active enzyme. Science 304(5679):1967–1971. doi:10.1126/science.1098432

    Article  CAS  PubMed  Google Scholar 

  168. Allert M, Dwyer MA, Hellinga HW (2007) Local encoding of computationally designed enzyme activity. J Mol Biol 366(3):945–953. doi:10.1016/j.jmb.2006.12.002

    Article  CAS  PubMed  Google Scholar 

  169. (2008) Negative results. Nature 453(7193):258. doi:10.1038/453258b

  170. Hayden EC (2009) Key protein-design papers challenged. Nature 461(7266):859. doi:10.1038/461859a

    Article  CAS  PubMed  Google Scholar 

  171. Looger LL, Dwyer MA, Smith JJ, Hellinga HW (2003) Computational design of receptor and sensor proteins with novel functions. Nature 423(6936):185–190. doi:10.1038/nature01556

    Article  CAS  PubMed  Google Scholar 

  172. Allert M, Rizk SS, Looger LL, Hellinga HW (2004) Computational design of receptors for an organophosphate surrogate of the nerve agent soman. Proc Natl Acad Sci U S A 101(21):7907–7912. doi:10.1073/pnas.0401309101

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  173. Hellinga HW (2008) In the wake of two retractions, a request for investigation. Nature 454(7203):397. doi:10.1038/454397b

    Article  CAS  PubMed  Google Scholar 

  174. Altamirano MM, Blackburn JM, Aguayo C, Fersht AR (2002) Retraction. Directed evolution of new catalytic activity using the alpha/beta-barrel scaffold. Nature 417(6887):468. doi:10.1038/417468a

    Article  CAS  PubMed  Google Scholar 

  175. Altamirano MM, Blackburn JM, Aguayo C, Fersht AR (2000) Directed evolution of new catalytic activity using the alpha/beta-barrel scaffold. Nature 403(6770):617–622. doi:10.1038/35001001

    Article  CAS  PubMed  Google Scholar 

  176. Feldmeier K, Hocker B (2013) Computational protein design of ligand binding and catalysis. Curr Opin Chem Biol 17(6):929–933

    Article  CAS  PubMed  Google Scholar 

  177. Wijma HJ, Janssen DB (2013) Computational design gains momentum in enzyme catalysis engineering. FEBS J 280(13):2948–2960. doi:10.1111/febs.12324

    Article  CAS  PubMed  Google Scholar 

  178. Khare SD, Fleishman SJ (2013) Emerging themes in the computational design of novel enzymes and protein-protein interfaces. FEBS Lett 587(8):1147–1154. doi:10.1016/j.febslet.2012.12.009

    Article  CAS  PubMed  Google Scholar 

  179. Davey JA, Chica RA (2012) Multistate approaches in computational protein design. Protein Sci 21(9):1241–1252. doi:10.1002/pro.2128

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  180. Tiwari MK, Singh R, Singh RK, Kim IW, Lee JK (2012) Computational approaches for rational design of proteins with novel functionalities. Comput Struct Biotechnol J 2, e201209002. doi:10.5936/csbj.201209002

    Article  PubMed  PubMed Central  Google Scholar 

  181. Senes A (2011) Computational design of membrane proteins. Curr Opin Struct Biol 21(4):460–466. doi:10.1016/j.sbi.2011.06.004

    Article  CAS  PubMed  Google Scholar 

  182. Verschueren E, Vanhee P, van der Sloot AM, Serrano L, Rousseau F, Schymkowitz J (2011) Protein design with fragment databases. Curr Opin Struct Biol 21(4):452–459. doi:10.1016/j.sbi.2011.05.002

    Article  CAS  PubMed  Google Scholar 

  183. Samish I, Bourne PE, Najmanovich RJ (2015) Achievements and challenges in structural bioinformatics and computational biophysics. Bioinformatics 31(1):146–150. doi:10.1093/bioinformatics/btu769

    Article  CAS  PubMed  Google Scholar 

  184. Rosenberg M, Goldblum A (2006) Computational protein design: a novel path to future protein drugs. Curr Pharm Des 12(31):3973–3997

    Article  CAS  PubMed  Google Scholar 

  185. Desjarlais JR, Lazar GA (2003) Negative design for improved therapeutic proteins. Trends Biotechnol 21(10):425–427. doi:10.1016/S0167-7799(03)00205-1

    Article  CAS  PubMed  Google Scholar 

  186. Moult J, Pedersen JT, Judson R, Fidelis K (1995) A large-scale experiment to assess protein structure prediction methods. Proteins 23(3):ii–v. doi:10.1002/prot.340230303

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, Israel

    Ilan Samish

  2. Department of Biotechnology Engineering, Ort Braude College of Engineering, Karmiel, Israel

    Ilan Samish

Authors
  1. Ilan Samish
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ilan Samish .

Editor information

Editors and Affiliations

  1. Department of Plants and Environmental Sciences, Weizmann Institute of Science, Rehovot, Israel

    Ilan Samish

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Science+Business Media New York

About this protocol

Cite this protocol

Samish, I. (2017). Achievements and Challenges in Computational Protein Design. In: Samish, I. (eds) Computational Protein Design. Methods in Molecular Biology, vol 1529. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6637-0_2

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-6637-0_2

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-6635-6

  • Online ISBN: 978-1-4939-6637-0

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation