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Tools for Validation of NMR-Structures

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Tools for Validation of NMR-Structures Motivation Tools for Validation of Analysis of ~400 NMR structures NMR structures are NMR-Structures generally not very good 90% ~25 % of recently deposited 75% structures is seriously flawed Geerten W. Vuister 50% average ~ Structural quality can often 25% be improved by: Department of Biochemistry, University of Leicester 10% • Proper computational procedures Geerten W. Vuister http://proteins.dyndns.org/Validation • Validation of input data Protein Biophysics, IMM, Radboud University Nijmegen • Validation of results http://proteins.dyndns.org Nabuurs et al. PLoS Comp. Biol. 2, e9, 2006 NMR Structure Validation EMBO course, Basel, July 2013 1 2 Structural quality Structural quality 1Q7X human PDZ2-AS 1OZI mouse PDZ2-AS Statistics over first 10 deposited structures hPDZ2 mPDZ2 Number of NOE restraints 1648 1354 Number of torsion angle restraints 80 76 RMSD all backbone atoms (Å) 0.24 2.56 RMSD all heavy atoms (Å) 0.86 3.00 PROCHECK Most favoured 59% 79% PROCHECK Additionally allowed 27% 16% PROCHECK Generously allowed / Disallowed 14% 5% WHAT IF Ramachandran plot Z-score -6.7 -3.7 WHAT IF Packing quality Z-score -3.7 -1.2 RMS Z-scores output of WHATIF WHAT IF Rotamer normality Z-score -6.5 -1.8 WHAT IF Backbone normality Z-score -8.6 -3.8 Backbone RDC R-factor 69% 40% NMR Structure Validation EMBO course, Basel, July 2013 NMR Structure Validation EMBO course, Basel, July 2013 3 4 Maybe the wrong ensemble was deposited? Structural quality ‣ Unfortunately it looks like this was not the DR1885 apo copper-bound case. ‣ The images used in the publication also contain the errors. ‣ Furthermore, the structural observations described in the paper are in agreement with the incorrect structure… [JMB, 2003, 334:143-155 ] RMS Z-scores output of WHATIF 1X7L (replaced by 2JQA) 1X9L NMR Structure Validation EMBO course, Basel, July 2013 NMR Structure Validation EMBO course, Basel, July 2013 5 6 Structural quality Structural quality DR1885 Restraint s How did such errors pass unnoticed? RMS Z-scores output of WHATIF [PNAS, 2005, 102 (11) 3994-3999 ] NMR Structure Validation EMBO course, Basel, July 2013 NMR Structure Validation EMBO course, Basel, July 2013 7 8 Background reading wwPDB NMR-VTF Concepts and Tools for Task: to formulate general accepted routines and Progress in Nuclear Magnetic Resonance Spectroscopy 45 (2004) 315–337 NMR Restraint Analysis www.elsevier.com/locate/pnmrs procedures for the validation of NMR derived and Validation Validation of protein structures derived by NMR spectroscopy 1 1 1 2 a a a a b,* biomolecular structures SANDER B. NABUURS, CHRIS A.E.M. SPRONK, GERT VRIEND, GEERTEN W. VUISTER Chris A.E.M. Spronk , Sander B. Nabuurs , Elmar Krieger , Gert Vriend , Geerten W. Vuister 1 Center for Molecular and Biomolecular Informatics,University of Nijmegen,Toernooiveld 1, aCentre for Molecular and Biomolecular Informatics, IMM, Radboud University Nijmegen, Toernooiveld 1, 6525 ED Nijmegen, The Netherlands 6525 ED Nijmegen,The Netherlands bDepartment of Biophysical Chemistry, IMM, Radboud University Nijmegen, Toernooiveld 1, 6525 ED Nijmegen, The Netherlands 2 Department of Biophysical Chemistry,University of Nijmegen,Toernooiveld 1, 6525 ED Nijmegen,The Netherlands Received 15 July 2004 Contents ABSTRACT: The quality of NMR-derived biomolecular structure models can be assessed 1. Introduction .................................................................................... 316 by validation on the level of structural characteristics as well as the NMR data used to derive the structure models. Here, an overview is given of the common methods to validate 2. NMR structure determination ........................................................................ 317 Phase 1. Tasks to be implemented by PDB using experimental NMR data. These methods provide measures of quality and goodness of fit of 2.1. Structure calculation procedures .................................................................. 317 the structure to the data. A detailed discussion is given of newly developed methods to 2.2. Structure selection ............................................................................ 317 assess the information contained in experimental NMR restraints, which provide powerful 3. Validation of experimental data ...................................................................... 318 tools for validation and error analysis in NMR structure determination. © 2004 Wiley 3.1. Fit of structures to experimental restraints .......................................................... 319 largely existing software Periodicals, Inc. Concepts Magn Reson Part A 22A: 90–105, 2004 3.1.1. Restraint violations ..................................................................... 319 3.1.2. RMS deviations and energies of restraints ..................................................... 320 KEY WORDS: structure validation; experimental restraints; restraint validation; structure 3.1.3. NMR R-factors and cross-validation ......................................................... 320 refinement 3.1.4. Independent validation and Q-factors ........................................................ 321 3.2. Information content in experimental restraints ....................................................... 321 Phase 2. Tasks for which software / methods are 3.2.1. Number of restraints, completeness and redundancy ............................................. 321 3.2.2. Quantitative evaluation of experimentalRecommendations NMR restraints ........................................... of the wwPDB 322 !"#$%&'%(&)#$*#+$$,-#*$'#+.&#%/,(0/+($"#$*#1'$+&("#234#-+'56+5'&-the spectroscopic data directly, geometric confor-# INTRODUCTION 4. Precision and accuracy of NMR structure ensembles ....................................................... 323 mational restraints are derived from these data, !"#"$%&'()*+,-.$/"0"$1234,.5.$6"7"8"$0*9:+';<=>.$?"1"$@2+*A*'B*+(C$D$E"$!&)FG9G(>$ 4.1. Precision versus accuracy ...................................................................... 323 The result of a biomolecular structure determina- which are subsequently used to calculate the struc- NMR Validation Task Force available, but which need more assessment before ,H9'I*+(')J$2K$L*';*()*+.$@*MG+)F*9)$2K$N'2;4*F'()+J.$8;422A$2K$N'2A23';GA$8;'*9;*(.$0*9+J$#*AA;2F*$N&'A:'93tures (1). Derivation of.$LG9;G()*+$/2G:.$L*';*()*+.$LO,$P0Q.$H such structural restraints R"$ 5. Validation of geometric quality ...................................................................... 325 tion5 by solution nuclear magnetic resonance (NMR) $H9'I*+(')J$2K$SGFT+':3*.$@*MG+)F*9)$2K$N'2;4*F'()+J.$UV$W*99'($S2&+)$/2G:.$SGFT+':3*.$SN5$,!E.$Hfrom NMR spectraR is"$$ complicated because spectral 5.1. Z-scores and RMS Z-scores ..................................................................... 325 spectroscopy>6+2)*'9$@G)G$NG9<$'9$O&+2M*.$O7NL is typicallyXO&+2M*G9$N'2'9K2+FG)';($Y9()')&)*.$#*AA;2F*$W+&()$!*92F*$SGFM&(.$0'9=)29.$SGF a family of structural T+':3*$SN,V$,8@.$HR"$ 5.2. Bonded geometry ............................................................................ 326 modelsC$/G:T2&:$H9'I*+(')J$7*:';GA$S*9)+*.$QS7L8.$S7NY.$!**+)$!+22)*MA*'9$Z&':$5[ describing the accessible molecular confor- overlap,X5U.$[\5\$!E spin$Q'BF*3*9.$W4*$Q*)4*+AG9:(" diffusion, local dynamics,$ and inter- - 5.2.1. Bond lengths and angles .................................................................. 326 mations.W2$]42F$;2++*(M29:*9;*$(42&A:$T*$G::+*((*:" This family, or ensemble,$ of structure converting conformations have to be taken into defining standard validation conventions for PDB 5.2.2. Chirality and tetrahedral geometry .......................................................... 327 $ account. The traditional manual assignment of 1 2,3 4 5 models should agree as a whole with the experi- 5.2.3. SideGaetano chain planarity T. Montelione....................................................................., Michael Nilges , Ad Bax , Peter Güntert 327, N'2F2A*;&AG+$ ()+&;)&+*($ G)$ G)2F';$ +*(2A&)'29$ M+*(*9)$ G$ IGA&GTA*$NMR resonances +*(2&+;*$ K2+$ and )4*$ conversion &9:*+()G9:'93$ of NMR 2K$ T'2A23J"$ peaks Q7/$ mental NMR data used in the procedure, as well as 5.2.4. Side chain rotamers ..................................................................... 328 (M*;)+2(;2MJ$G;;2&9)($K2+$,,^$2K$GAA$()+&;)&+*($'9$)4*$6@N$+*M2(')2+J"$Y9$+*(M29(*$)2$(*+'2&($M+2TA*F($]')4$)4*$G;;&+G;J$ other additional data. Typically, rather than using into structural restraints is an extremely time-con- 5.2.5. Backbone conformation .................................................................. 331 2K$(2F*$2K$)4*$Q7/X:*+'I*:$()+&;)&+*($G9:$'9$2+:*+$)2$KG;'A')G)*$M+2M*+$G9GAJ('($2K$)4*$*=M*+'F*9)GA$F2:*A(.$G$9&FT*+$2K$ 6 7 8 suming process, even for experienced spectrosco- 5.3. Non-bondedT interactionsorsten .......................................................................Herrmann , Jane S. Richardson , Charles Schwieters , 331 M+23+GF$(&')*($G+*$GIG'AGTA*"$#*$:'(;&(($ 9'9*$2K$)4*(*$)22A($'9$)4'($+*I'*]_$6/`S0OSRXQ7/.$68%8.$!L7X/78@.$SYQ!.$ Received 2 March 2004; revised 13 April 2004; ac- pists. Further, manual interpretation of NMR data is 5.3.1. Inter-atomic bumps ..................................................................... 331 Phase 3. Tasks requiring further research over the 72AM+2T')J.$ %'IGA:'.$ /*(6+2=.$ Q7/$ ;29()+G'9)($ G9GAJa*+$ G9:$prone bF*G9"$ to human #*$ *IGA&G)*$ error and,)4*(*$ possibly, M+23+GF($ manipulation. K2+$ )4*'+$ GT'A')J$ )2$ cepted 13 April 2004 5.3.2. Hydrogen
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