Gán đồng bộ và chính xác tự động các tần số protein cho NMR trạng thái rắn

Journal of Biomolecular NMR - Tập 59 - Trang 119-134 - 2014
Jakob Toudahl Nielsen1, Natalia Kulminskaya1, Morten Bjerring1, Niels Chr. Nielsen1
1Center for Insoluble Protein Structures (inSPIN), Interdisciplinary Nanoscience Center (iNANO), Department of Chemistry, Aarhus University, Aarhus C, Denmark

Tóm tắt

Quá trình gán đồng bộ đại diện cho một nút thắt thời gian tiêu tốn và có nguy cơ sai sót trong các nghiên cứu cấu trúc của protein bằng NMR trạng thái rắn (ssNMR). Phần mềm tự động hóa quá trình này do đó đang được quan tâm cao. Các quy trình được phát triển trong vài thập kỷ qua cho NMR ở trạng thái dung dịch không thể áp dụng trực tiếp cho ssNMR do chất lượng dữ liệu vốn dĩ thấp hơn gây ra bởi độ nhạy thấp hơn và các đường phổ rộng hơn, dẫn đến chồng chéo giữa các đỉnh. Gần đây, những nỗ lực đầu tiên hướng tới các quy trình đặc biệt dành cho ssNMR đã được thực hiện (Schmidt et al. trong J Biomol NMR 56(3):243–254, 2013). Tại đây, chúng tôi trình bày một phương pháp tự động mạnh mẽ, có thể gán chính xác các tần số protein bằng cách sử dụng danh sách đỉnh từ một tập hợp nhỏ các thí nghiệm ssNMR 2D và 3D đơn giản, có thể áp dụng trong các trường hợp có độ nhạy thấp. Phương pháp này được chứng minh trên ba sinh chất sinh học được đánh dấu đồng nhất với 13C, 15N với những thách thức khác nhau trong việc gán. Cụ thể, đối với miền gán kết immunoglobulin B1 của protein G do liên cầu khuẩn, việc gán tự động cho thấy độ chính xác 100% cho các tần số xương sống và 91,8% khi bao gồm tất cả các carbon chuỗi bên. Nó được chứng minh, bằng cách sử dụng quy trình tạo ra quang phổ nhân tạo với chiều rộng đường tăng dần, rằng phương pháp của chúng tôi, GAMES_ASSIGN có thể xử lý một lượng lớn các đỉnh chồng chéo trong việc gán. Tác động của việc bao gồm các thí nghiệm ssNMR khác nhau cũng được đánh giá.

Từ khóa

#NMR trạng thái rắn #gán đồng bộ protein #tự động hóa #độ chính xác #quang phổ nhân tạo

Tài liệu tham khảo

Alexandrescu AT (2001) An NMR-based quenched hydrogen exchange investigation of model amyloid fibrils formed by cold shock protein A. Pac Symp Biocomput 6:67–78 Altieri AS, Byrd RA (2004) Automation of NMR structure determination of proteins. Curr Opin Struct Biol 14(5):547–553 Atreya HS, Sahu SC, Chary KVR, Govil G (2000) A tracked approach for automated NMR assignments in proteins (TATAPRO). J Biomol NMR 17(2):125–136 Baran MC, Huang YJ, Moseley HNB, Montelione GT (2004) Automated analysis of protein NMR assignments and structures. Chem Rev 104(8):3541–3555 Bartels C, Billeter M, Guntert P, Wuthrich K (1996) Automated sequence-specific NMR assignment of homologous proteins using the program GARANT. J Biomol NMR 7(3):207–213 Bartels C, Guntert P, Billeter M, Wuthrich K (1997) GARANT—a general algorithm for resonance assignment of multidimensional nuclear magnetic resonance spectra. J Comput Chem 18(1):139–149 Bouvignies G, Meier S, Grzesiek S, Blackledge M (2006) Ultrahigh-resolution backbone structure of perdeuterated protein GB1 using residual dipolar couplings from two alignment media. Angew Chem Int Ed 45(48):8166–8169 Cela E (1998) The quadratic assignment problem. Theory and Algorithms. Kluwer Academic Publishers, Dordrecht Chevelkov V, Rehbein K, Diehl A, Reif B (2006) Ultrahigh resolution in proton solid-state NMR spectroscopy at high levels of deuteration. Angew Chem Int Ed 45(23):3878–3881 Coeytaux K, Poupon A (2005) Prediction of unfolded segments in a protein sequence based on amino acid composition. Bioinformatics 21(9):1891–1900 Coggins BE, Zhou P (2003) PACES: protein sequential assignment by computer-assisted exhaustive search. J Biomol NMR 26(2):93–111 Crippen GM, Rousaki A, Revington M, Zhang YB, Zuiderweg ERP (2010) SAGA: rapid automatic mainchain NMR assignment for large proteins. J Biomol NMR 46(4):281–298 Eghbalnia HR, Bahrami A, Wang LY, Assadi A, Markley JL (2005) Probabilistic identification of spin systems and their assignments including coil-helix inference as output (PISTACHIO). J Biomol NMR 32(3):219–233 Fiaux J, Bertelsen EB, Horwich AL, Wuthrich K (2002) NMR analysis of a 900 K GroEL-GroES complex. Nature 418(6894):207–211 Franks WT, Zhou DH, Wylie BJ, Money BG, Graesser DT, Frericks HL, Sahota G, Rienstra CM (2005) Magic-angle spinning solid-state NMR spectroscopy of the beta 1 immunoglobulin binding domain of protein G (GB1): N-15 and C-13 chemical shift assignments and conformational analysis. J Am Chem Soc 127(35):12291–12305 Frigaard NU, Li H, Martinsson P, Das SK, Frank HA, Aartsma TJ, Bryant DA (2005) Isolation and characterization of carotenosomes from a bacteriochlorophyll c-less mutant of Chlorobium tepidum. Photosynth Res 86(1–2):101–111 Gallagher T, Alexander P, Bryan P, Gilliland GL (1994) 2 crystal-structures of the B1 immunoglobulin-binding domain of streptococcal protein-G and comparison with nmr. Biochemistry 33(15):4721–4729 Gath J, Habenstein B, Bousset L, Melki R, Meier BH, Boeckmann A (2012) Solid-state NMR sequential assignments of alpha-synuclein. Biomol NMR Assigm 6(1):51–55 Griswold IJ, Dahlquist FW (2002) Bigger is better: megadalton protein NMR in solution. Nat Struct Biol 9(8):567–568 Guerry P, Herrmann T (2011) Advances in automated NMR protein structure determination. Quart Rev Biophys 44(3):257–309 Habenstein B, Wasmer C, Bousset L, Sourigues Y, Schuetz A, Loquet A, Meier BH, Melki R, Boeckmann A (2011) Extensive de novo solid-state NMR assignments of the 33 kDa C-terminal domain of the Ure2 prion. J Biomol NMR 51(3):235–243 He B, Wang KJ, Liu YL, Xue B, Uversky VN, Dunker AK (2009) Predicting intrinsic disorder in proteins: an overview. Cell Res 19(8):929–949 Hitchens TK, Lukin JA, Zhan YP, McCallum SA, Rule GS (2003) MONTE: an automated Monte Carlo based approach to nuclear magnetic resonance assignment of proteins. J Biomol NMR 25(1):1–9 Holland GP, Cherry BR, Jenkins JE, Yarger JL (2010) Proton-detected heteronuclear single quantum correlation NMR spectroscopy in rigid solids with ultra-fast MAS. J Magn Reson 202(1):64–71 Hu K-N, Qiang W, Tycko R (2011) A general Monte Carlo/simulated annealing algorithm for resonance assignment in NMR of uniformly labeled biopolymers. J Biomol NMR 50(3):267–276 Igumenova TI, McDermott AE, Zilm KW, Martin RW, Paulson EK, Wand AJ (2004) Assignments of carbon NMR resonances for microcrystalline ubiquitin. J Am Chem Soc 126(21):6720–6727 Jung YS, Zweckstetter M (2004) Mars—robust automatic backbone assignment of proteins. J Biomol NMR 30(1):11–23 Kim S, Szyperski T (2003) GFT NMR, a new approach to rapidly obtain precise high-dimensional NMR spectral information. J Am Chem Soc 125(5):1385–1393 Konermann L, Pan JX, Liu YH (2011) Hydrogen exchange mass spectrometry for studying protein structure and dynamics. Chem Soc Rev 40(3):1224–1234 Kulminskaya NV, Pedersen MO, Bjerring M, Underhaug J, Miller M, Frigaard N-U, Nielsen JT, Nielsen NC (2012) In situ solid-state NMR spectroscopy of protein in heterogeneous membranes: the baseplate antenna complex of Chlorobaculum tepidum. Angew Chem Int Ed 51(28):6891–6895 Kupce E, Freeman R (2003) Fast multi-dimensional NMR of proteins. J Biomol NMR 25(4):349–354 Leutner M, Gschwind RM, Liermann J, Schwarz C, Gemmecker G, Kessler H (1998) Automated backbone assignment of labeled proteins using the threshold accepting algorithm. J Biomol NMR 11(1):31–43 Lukin JA, Gove AP, Talukdar SN, Ho C (1997) Automated probabilistic method for assigning backbone resonances of (C-13, N-15)-labeled proteins. J Biomol NMR 9(2):151–166 Malmodin D, Papavoine CHM, Billeter M (2003) Fully automated sequence-specific resonance assignments of heteronuclear protein spectra. J Biomol NMR 27(1):69–79 Moseley HNB, Montelione GT (1999) Automated analysis of NMR assignments and structures for proteins. Curr Opin Struct Biol 9(5):635–642 Moseley HNB, Monleon D, Montelione GT (2001) Automatic determination of protein backbone resonance assignments from triple resonance nuclear magnetic resonance data. Nucl Magn Reson Biol Macromol Pt B 339:91–108 Moseley HNB, Sperling LJ, Rienstra CM (2010) Automated protein resonance assignments of magic angle spinning solid-state NMR spectra of beta 1 immunoglobulin binding domain of protein G (GB1). J Biomol NMR 48(3):123–128 Nagarajan V, Sviridenko M (2009) On the maximum quadratic assignment problem. Math Oper Res 34(4):859–868 Nielsen JT, Nielsen NC (2014) VirtualSpectrum, a tool for simulating realistic peak list for multi-dimensional NMR spectra. Submitted Nielsen JT, Eghbalnia HR, Nielsen NC (2012) Chemical shift prediction for protein structure calculation and quality assessment using an optimally parameterized force field. Progr Nuc Magn Reson Spectrosc 60:1–28 Pedersen MØ, Underhaug J, Dittmer J, Miller M, Nielsen NC (2008) The three-dimensional structure of CsmA: a small antenna protein from the green sulfur bacterium Chlorobium tepidum. FEBS Lett 582(19):2869–2874 Rovnyak D, Frueh DP, Sastry M, Sun ZYJ, Stern AS, Hoch JC, Wagner G (2004) Accelerated acquisition of high resolution triple-resonance spectra using non-uniform sampling and maximum entropy reconstruction. J Magn Reson 170(1):15–21 Schmidt E, Guntert P (2012) A new algorithm for reliable and general NMR resonance assignment. J Am Chem Soc 134(30):12817–12829 Schmidt E, Gath J, Habenstein B, Ravotti F, Szekely K, Huber M, Buchner L, Boeckmann A, Meier BH, Guentert P (2013) Automated solid-state NMR resonance assignment of protein microcrystals and amyloids. J Biomol NMR 56(3):243–254 Schmucki R, Yokoyama S, Guentert P (2009) Automated assignment of NMR chemical shifts using peak-particle dynamics simulation with the DYNASSIGN algorithm. J Biomol NMR 43(2):97–109 Tang KS, Man KF, Kwong S, He Q (1996) Genetic algorithms and their applications. IEEE Signal Process Mag 13(6):22–37 Tycko R, Hu K-N (2010) A Monte Carlo/simulated annealing algorithm for sequential resonance assignment in solid state NMR of uniformly labeled proteins with magic-angle spinning. J Magn Reson 205(2):304–314 Ulrich EL, Akutsu H, Doreleijers JF, Harano Y, Ioannidis YE, Lin J, Livny M, Mading S, Maziuk D, Miller Z, Nakatani E, Schulte CF, Tolmie DE, Wenger RK, Yao HY, Markley JL (2008) BioMagResBank. Nucl Acids Res 36:D402–D408 Vijaykumar S, Bugg CE, Cook WJ (1987) Structure of ubiquitin refined at 1.8 A resolution. J Mol Biol 194(3):531–544 Vilar M, Wang L, Riek R (2012) Structural Studies of Amyloids by Quenched Hydrogen-Deuterium Exchange by NMR. In: Sigurdsson EM, Calero M, Gasset M (eds) Amyloid Proteins: Methods and Protocols, 2ed. 849. Methods Mol Biol 1:pp 185–198 Xu Y, Zheng Y, Fan J-S, Yang D (2006) A new strategy for structure determination of large proteins in solution without deuteration. Nat Methods 3(11):931–937 Yao J, Dyson HJ, Wright PE (1997) Chemical shift dispersion and secondary structure prediction in unfolded and partly folded proteins. FEBS Lett 419(2–3):285–289 Zech SG, Wand AJ, McDermott AE (2005) Protein structure determination by high-resolution solid-state NMR spectroscopy: application to microcrystalline ubiquitin. J Am Chem Soc 127(24):8618–8626 Zhang HY, Neal S, Wishart DS (2003) RefDB: a database of uniformly referenced protein chemical shifts. J Biom NMR 25(3):173–195 Zhou DHH, Nieuwkoop AJ, Berthold DA, Comellas G, Sperling LJ, Tang M, Shah GJ, Brea EJ, Lemkau LR, Rienstra CM (2012) Solid-state NMR analysis of membrane proteins and protein aggregates by proton detected spectroscopy. J Biomol NMR 54:291 Zimmerman DE, Kulikowski CA, Huang YP, Feng WQ, Tashiro M, Shimotakahara S, Chien CY, Powers R, Montelione GT (1997) Automated analysis of protein NMR assignments using methods from artificial intelligence. J Mol Biol 269(4):592–610