Mestrelab s Users Meeting. Santi Dominguez MBA CEO Dr Manuel Pérez Senior VP October 22 nd 2015

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1 Mestrelab s Users Meeting Santi Dominguez MBA CEO Dr Manuel Pérez Senior VP October 22 nd 2015

2 Layout Layout 13:00 13:10: Introduction 13:10 13:50: MestreNova(Mnova) NMR plugin: a wealth of functionality 13:50 14:20: Mnova Verification: predictions and understanding results 14:20 14:40: Coffee Break 14:20 14:50: MnovaSMA and qnmr: analysis and quantification of single and multiple compounds 14:50 15:20: MnovaDB: using databases to capture, share and create knowledge 15:20 15:40: Mnova MS plugin: main characteristics 16:00 17:00: Q&A

3 10 years of Mestrelab!!! From1st Dec2004 today From2 FTE to 30 FTE From 10 customers to 85,000 1/12/ /09/2015 Intro & What s New 3

4 The development team: Nikolay Larin(Head of Software Development) Isaac Iglesias (Developer) Felipe Seoane(Developer) Pablo Monje (Apps Chemist) Santi Fraga (Developer) Michael Goebel(Developer) Esther Vaz (QA PhD Chemist) Santi López (Developer) José Antonio García (Developer) Oleg Ovchinnikov (Developer) Agustin Barba (Developer) José Antonio García Pulido (Developer) The scientific team: Carlos Cobas Javier Sardina Mike Bernstein Manuel Perez Chen Peng Brian Marquez The business team: Santi Dominguez Chen Peng Cristina Geada Dani Fraga Olalla Lema Manuel Perez Enrique Sánchez Izabella Kroll The Team We are over> in thefamily! The scientific partners(collaborations and contractors) Modgraph Consultants Ltd Rashmi Mistry Jeff Seymour Mike Wainwright Wolfgang Robien Ray Abraham Erno Pretsch Portanova GmbH Pius Portmann USC Manuel Martin Pastor Origenis Michael Thormann ebyte Stan Sykora Nucleomatica Giuseppe Balacco Sierra Analytics David Stranz Scott Campbell George Maydwell Mspin Armando Navarro R4R Silvia Mari Intro & What s New 5

5 The customers Continued market expansion led by NMR 34 of top Worlduniversitieshavecampus licensesof Mnova(9 of top 10) Latest additions are Stanford, Oxford, Nottingham and Strasbourg Several pharmaceutical and chemical companies have gone for Company wide Mnova installations: Pfizer Novartis BASF LGChem Boehringer Ingelheim Leo Pharma Intro & What s New 6

6 The customers Japan Japanese market starting to grow Very important market, huge potential and high level of expertise Hand in hand with SystemPlus, who are our partners for supporting the Japanese market Thisisourfirsttripto Japan, buttherewillbe manymore Full training session in Spring 2016 Intro & What s New 6

7 Areas y Methodologies Manufacturing Development Research Mnova MS Databases SMA qnmr Verification and Prediction NMR: Functionality

8 What most of us want i

9 It is easy

10 Introduction The Trinity of NMR (or a combination of) Integra tion Chemic al Shift Coupli ng

11 Phasing, Baseline correction (and lies) Will influence: Integration Chemical Shift Need to: Learn to appreciate their impact Know your algorithms

12 Pre-Acquisiton Considerations O O Expansion of aromatic region d1 = 0 sec d1 = 1 sec d1 = 3 sec d1 = 10 sec OH 37 % error (on signal at 7.8 ppm) 29 % error (Standard 1H) 17 % error 3 % error (Proton_Quantitative )

13 Phasing Strategies No perfect automatic solution But. Play!

14 Phase correction: Let s look at some integrals ph0 +3

15 Baseline Correction Considerations Influence over quantitation Multiple Choices Smooth: Polynomial Methods Aggressive: Smoothers, Splines Manual: slower but more precise

16 Baseline correction Whittaker: Influence on integrals

17 Referencing: Absolute Referencing Influence over chemical shift Consistency IUPAC recommendation: unified scale Added benefit: Alignment across all experiments

18 Absolute Referencing in Mnova For all nuclei: Manage References:

19 Peak Picking Different Approaches Standard Global Spectral Deconvolution Effect over: Chemical Shift Coupling

20 Standard Peak Picking Simple algorithm: Look for peak maxima Good enough for certain cases But. Peak overlap Insufficient peak resolution Not accurate coupling constants

21 GSD Intro Multiplication of the FID by a resolution-enhancement function But: poorer SNR and peak shape distortions

22 GSD Intro Resolution Booster Original Integral part of GSD

23 Why GSD (overlap) Overlap

24 Why GSD (Auto-classification of peaks)

25 Why GSD - Couplings

26 But why?! Because we can reconstruct the data

27 To the report! Now that some of you are scared Creation of reporting templates, including: Exact look and feel All the analysis operations (phase and baseline correction, peak picking, autoclassification, reports of multiplets and parameters )

29 Tracking Data COSY TOCSY NOESY HSQC HMBC 1 H- 15 N HMBC

30 Tracking assignments Correlations Assignment Tables

31 Data Analysis T1 calculation

32 Reaction Monitoring by NMR

33 Verification and Prediction Areas y Methodologies Manufacturing Development Research Mnova MS Databases SMA qnmr Verification and Prediction NMR: Functionality

34 Verification and Prediction Approaches 1 H NMR Increments (Prof Erno Prest) Conformers (Prof Ray Abraham) Access through:

35 Verification and Prediction Approaches 13 C NMR HOSE Code Wolfgang Robien Neural Networks Wolfgang Robien

36 1 H NMR Prediction Increments Similar (but different to HOSE) Uses substructures Very accurate Easy to anonymize Over 10,000 structurally different molecules in the DB Data organised into multiple databases

37 1 H NMR Prediction Conformers Semi empirical approach Takes into consideration the 3D structure of the compound Thousands of compounds used to create the models Effective when dealing with flexible systems Visualise the conformers that contribute to the predictions

38 13 C Prediction 13 C HOSE Concept of Shells : how similar are the substructures as we go further away from the Carbon atom predicted: 5 shells: perfectly represented 1 shell: not represented Over compounds in the prediction database Constantly updated

39 13 C Prediction 13 C Neural Networks Fall-back approach More accurate than any other when no representative data can be found in the database

40 Method Selection Best Approach and Error Estimation Algorithm to decide which model produces the best predictions Errors calculated following considerable atom by atom type analysis

41 Solvents Solvents For 1 H NMR three solvents are considered by default: CDCl 3 DMSO D 2 O For 13 C NMR the solvent is automatically detected and the predictions are produced from relevant data.

42 Error interpretation Error Interpretation It is possible for any given prediction to display the estimated errors of the prediction graphically or in a table format:

43 Results Result Overview The inclusion of user data has a marked effect: Total refers to the effect over the entire of the dataset, Partial only for those atom that showed a change Total Partial Total Partial 13C 13C 1H 1H Improvement %

44 Structural Determination Need workflows to Track information across multiple Record these effectively But need the killer experiment

45 Verification What is verification Is my Structure compatible with my data?

46 Verification What is Mnova Verify? Candidate Structures(one or several) Spectra 1H or/& 13C or/& HSQC or/& LC/GC/MS NMRPrediction (1H, 13C, 19F, 31P, 17º, 19N, 29Si) -CHARGE - Increments -HOSE -CSEARCH MS Prediction -m/z value - Isotopic cluster pattern -MSMS NMR Analysis - Autoprocess - GSD Enhance resolution Quantitate overlapped peaks - Autoedit Mark solvent lines Identify impurities Label labiles MS Analysis -Autoprocess - Integration/Peak Pick - Clustering Comparison Test 1 Global metrics Test 2 Nuclide count Test 3 Predicted multiplets Test 4 Js and assignme nts Test 5 HSQC XCOR Test 6 Isotope cluster distance Test 7 MSMS Peaks Scoring System(Scores and Significances) a novel scoring system able to apply fuzzy logic to combining many tests of different reliability in each specific case

47 Applications Structure Verification Foundation: GSD Auto classification of peaks Assignment Classification

48 Verification Reporting and result visualization Meaningful feedback for chemists on verification results Assignments on molecule Percentage or score result NMR Purity

49 Reporting and result visualization Meaningful feedback for chemists on verification results Results explained Reasons for specific verification scores

part of the verification workflow generate extra value for

50 Integration with concentration calculation Quantification and Verification We can now run concentration and purity calculations as part of the verification workflow generate extra value for verification users and get more information out of your data with quantification for free

51 Reporting and result visualization Latest Developments in Mnova Verify Meaningful feedback for chemists on verification results Acquisition issues which may affect verification or quantification accuracy

52 Latest Developments in Mnova Verify Ranking between possible reaction outcomes Confidence for chemists on the outcome of their reactions

53 Latest Developments in Mnova Verify Ranking between possible reaction outcomes Meaningful feedback for chemists on verification results

54 Automation in Verify Automation - Batch There is now a batch verification plugin available, which allows users to verify any number of samples in automation

55 Automation - Listener Latest Developments in Mnova Verify Verification can now be run as a listener launched by the arrival of new data in a specifically preselected location

56 Latest Developments in Mnova Verify Automation Verification listener

57 Result visualisation Multiple verification review Verification viewer allows the fast review of any number of verification analysis Results for specific well Detailed Results for specific well Wellplate Concentration information

58 Integration with MyData / Spectral DB Databasing of Verify results Storage in Spectral DB integrated as part of the verification workflow

59 Reporting and result visualization Latest Developments in Mnova Verify Integration of verification with layout templates for automated report generation including reporting results

60 Verification and Prediction Areas y Methodologies Manufacturing Development Research Mnova MS Databases SMA qnmr Verification and Prediction NMR: Functionality

61 Methodologies Internal Reference External reference Artificial Signal Conversion Factor 2D Methods Relative Response Factors

62 qnmr qnmr: General aspects of data processing Sample preparation, shimming, temperature stability Interpulse delay Signal-to-noise-ratio (SNR)(guideline: 150) Number of data points/peak Apodisation Phase correction Baseline correction Integration method Integration regions Blind regions

63 qnmr Basics of qnmr spectroscopy Fundamental relationship of qnmr: the signal intensity in the NMR spectrum is directly proportional to the number of nuclei responsible for that particular resonance (1) so I I X X = N K X S N X where K S is the spectrometer constant and remains the same for all the resonances in a NMR spectrum Relative quantitation method The easiest method where the molar ratio between two compounds (M x /M y ) can be calculated M M X X ( 2) = Y I N X N I Y Y Absolute quantitation method and Purity By determining the absolute concentration of an analyte it is possible to derive its purity: I. If all the impurities (or other components) present in the NMR spectrum can be measured quantitatively, then the assay is just a difference from the 100% value II. Otherwise purity of a compound X is derived by the comparison with a standard according to the formula: I N MW X STD X ( 3) PX = ISTD NX MWSTD W W STD P STD where, I, N, M, W and P are integral area, number of nuclei, molar mass, gravimetric weight and purity of analyte (X) and standard (STD), respectively 63

64 Potency Potency (Purity) Purity/Potency

65 Concentration Determination Concentration Response factor calculation

66 qnmr Setup: load Spectrum, Compound Library and General Settings W-qNMR directory Open in Mnova 66

67 Adding DMSO2 as a reference to the table of compounds qnmr Finally: Save Compound Library 67

68 qnmr Check that Nuclides are correct 68

69 qnmr Preparing to Calculate Do this after Multiplets Ananlysis using Sum integration! 69

70 qnmr Expected result 70

71 qnmr Save experiment dialogue Check Analysis with replicates if >1 spectrum of a sample 71

72 qnmr Running an experiment 72

73 Verification and Prediction Areas y Methodologies Manufacturing Development Research Mnova MS Databases SMA qnmr Verification and Prediction NMR: Functionality

74 SMA Mnova capabilities for mixtures analysis Unsupervised methods Targeted analysis(=quantitation of defined substances) qnmr Simple Mixtures Analysis(SMA) 74 74

75 SMA is useful for Drug substances for release (CoA) Compound "Purity" determinations Quantitate the components of biological fluids, fermentation broths Wines and beverages Oligo-/polysaccharide hydrolysis sugar analysis Petroleum analysis PUFAs Metabolomics Other Low-field, high-field, 1D, 2D data 75

76 SMA You can design an SMA experiment to: Search for a multiplet or integrate a spectral region Use of GSD in areas of peak overlap Peak pattern recognition SMA will automatically determine these areas for each spectrum Specify an equationthat converts that area into meaningful quantification If necessary, use an internal quantitation standard / 76

77 SMA basics Other data Quantitation of C 1 Equation for SMA I1 I2 I3 77

78 SMA basics Equations Automatic and manual Measurement Equation SMA equation Mole ratio (I1*NNR1)/(IR1*NN1) Concentration Purity Ref: RC * (NN1/I1) Compound: CCF * (I1/NN1) (I1*NNR1*RW*MW) /(IR1*NN1*SW*MWR) Statistics,e.g. average )/2 0.5*(C_A+ C_B) 78

79 SMA basics Further flexibility in equation usage Factorise partly hidden, or semi-saturated signals 1D or 2D Specify the NMR experiment for a sample mix and match Use a previous result in a later equation 79

80 Extending targeted analysis Multiple spectral information for a sample Extends the scope of targeted analysis 80

81 Extending targeted analysis Helping to deal with overlap AI AI t = AI* 2 AI AI t = AI-AI 81 81

SMA workflow for complex mixtures The SMA analysis workflow: analyse-alert-refinereanalyse Search for multiplets Alert the user to possible

82 SMA workflow for complex mixtures The SMA analysis workflow: analyse-alert-refinereanalyse Search for multiplets Alert the user to possible false peak identification (J, relative integral, etc.) or review each region Allow the user to manually fix a problem Reanalyse Reporting 82

83 SMA worked example Example: concentrations of Aspirin C components Acetyl salicylic acid Salicylic acid Ascorbic acid Citric acid Acetic acid 83

84 Verification and Prediction Areas y Methodologies Manufacturing Development Research Mnova MS Databases SMA qnmr Verification and Prediction NMR: Functionality

85 Verification and Prediction Areas y Methodologies Manufacturing Development Research Mnova MS Databases SMA qnmr Verification and Prediction NMR: Functionality

86 LC/MS data formats Mnova MS can open Formats supported Vendor Windows Mac Linux Agilent ChemStation, MassHunter, Ion Trap ChemStation ChemStation Bruker 1 XMass, Compass XMass XMass Waters MassLynx MassLynx MassLynx Thermo Scientific Xcalibur, Exactive, Q-Exactive JEOL MSQ 1000, FastFlight AB SCIEX Analyst Shimadzu 2 LabSolutions mzdata, mzxml mzdata, mzxml mzdata, mzxml mzdata, mzxml NetCDF ANDI-MS NetCDF ANDI-MS

87 To open your LC/MS data Opening data Choose File Page Setup Orientation and change the page orientation to portrait, if you prefer Choose File Opento open any file in the folder containing the raw data, or drag/dropthe folder from Windows Explorer to Mnova Mnovaautomatically converts your data and does peak picking TIC Drag & drop Mass spectrum (at highest TIC)

88 To browse the mass spectra Browsing Data Click to switch to crosshair cursor, and click on the TIC to display the mass spectrum at that retention time, or click-and-drag to display co-added spectra Click to change to appending mode if you want to display multiple mass spectra Choose the Spectrum Selection Mode to display mass spectra conveniently: Manual mode: You click to display a single MS, or click-and-drag to co-add multiple MS Peak mode: You click on a peak to display the co-added MS within the peak range Peak (Background subtraction) mode: You click on a peak to display the co-added MS within the peak range with the background subtracted

89 To browse the UV traces MS browser Click to show the MS Browser dialog Highlight the Total UV Absorbance under Traces, and click to display it Repeat the above step to display the other traces if any

90 Adding a chromatogram To extract a UV trace at selected wavenumber Highlight the DAD in the MS Browser Click to display it In the New Chromatogram dialog, choose Wavelength, and enter a wave length and a tolerance to display the extracted UV trace

91 To display a UV spectrum at selected retention time If available, highlight the DAD Trace in the MS Browser and click to display it Click for Crosshair cursor, press and hold Alt key, click on the DAD trace to display the UV spectrum at that retention time. DAD In crosshair cursor mode, click on the PDA curve to display the UV spectrum at that retention time UV spectrum

92 To edit and report peak integration results Peaks are automatically integrated when you open a chromatogram Use the Peak Detection tool menu to re-detect peaks, add, delete or clear peaks Hover your cursor on the wedges, click and drag the green boxes to change the range of a peak Or press Shift, click and drag the green boxes to change the baseline of a peak Choose View Tables Mass Peaksto display or report the Mass Peaks Table SHIFT+ Drag

93 To display extracted ion chromatogram from an m/zvalue Click (or choose Mass Analysis New Mass Chromatogram Manually) In the New Chromatogram dialog, enter the m/z value that you are interested in, and a suitable Tolerance Press OK to display the EIC TIC EIC at /-0.25 Da

94 To display extracted ion chromatogram for an MS peak TIC First display the MS trace and zoom into the molecular ion peak that you are interested. Next select Click (or choose Mass Analysis New Mass Chromatogram Graphically), clickand-drag around the peak to define a mass range An EIC will be displayed within the mass range MS at 3.08 min EIC at Da

95 To confirm proposed structures using Molecule Match Molecular Match TIC Import one or several structures by copy/pasting from ChemDraw, Isis/Draw or ChemSketch, or by opening.mol or.sdf files. Click (or choose Mass Analysis Molecule Match Calculate). In the Molecule Match Table, click on a molecule to see the matching results Matched Isotope Cluster Chromat. Matched Isotope Cluster Mol Match Results

96 Molecular Match You can choose Mass Analysis Molecule Match Settings to change the settings for Molecule Match. The default settings are for low-resolution MS. Change Tolerance to 5-10 ppm if you are using high-resolution MS. Edit the Adducts or Losses and other parameters if you want. Click to run the Molecule Match again To confirm proposed structures using Molecule Match (2) Tip: Click the + buttons to add a new adduct. Enter + for a radical cation. Highlight one and click the x button to remove it. Click Restore to reset to the default or previously saved settings.

97 To confirm proposed MF using Molecule Match Molecular Match If you don t have a structure but only a MF, choose the Calculate From Molecular Formula tool Enter one or more molecular formulas The results are displayed in Molecule Match Table

98 To predict isotope clusters from a mol. formula High Resolution data Choose Mass Analysis Spectrum Prediction Predict Enter one or more molecular formulae to predict the isotope clusters with all predefined adducts and losses Click on TIC to display a mass spec (or a range of co-added mass spec), and highlight a row in the Mass Prediction Table. Mnovadisplays the predicted isotope cluster with matched peaks in the experimental peaks, if any Choose an adduct/loss Click on TIC to choose a mass spec Predicted (blue) and matched experimental peaks (red)

99 To enumerate elemental compositions Elemental composition Zoom into the molecular ion peak of a MS trace Click or choose Mass Analysis Elemental Composition Calculate. Click on the molecule ion peak. An Elemental Composition Table is displayed Click on a row to see the match of observed and predicted isotope peaks Choose Mass Analysis Elemental Composition Settings to change the settings if necessary. Then click on the ion peak to recalculate. Possible Elemental Compositions Match of observed and predicted isotope peaks

100 Acknowledgements Mestrelab Team Questions?

Mnova Software Tools for Fragment-Based Drug Discovery

Mnova Software Tools for Fragment-Based Drug Discovery Chen Peng, PhD, VP of Business Development, US & China Mestrelab Research SL San Diego, CA chen.peng@mestrelab.com 858.736.4563 Agenda Brief intro