TITAN: Two-dimensional lineshape analysis Chris Waudby - PowerPoint PPT Presentation

TITAN: Two-dimensional lineshape analysis Chris Waudby Christodoulou Group c.waudby@ucl.ac.uk Andres Ramos Lisa Cabrita John Christodoulou

Inhibition of fatty acid synthesis for treatment of tularemia OH Cl O Cl Cl OH O Cl OH O OH O 2 OH O Inhibition of Francisella tularensis enoyl reductase (interaction of inhibitors with E–NAD + complex) 5 Lu, H. et al. ACS Chem. Biol. 4 , 221–231 (2009) Copeland, R. A. Nat Rev Drug Discov 15 , 87–95 (2016)

Inhibition of fatty acid synthesis for treatment of tularemia a 100 OH Cl O 80 Cl Cl OH O Survival (%) 60 Cl OH 40 O 20 OH O 0 2 0 0.5 1.0 1.5 2.0 2.5 3.0 OH K i (nM) O In vivo . Lu et al. 5 the relationship between the residence time of a series of Fabl enoyl‑reductase inhibitors and in vivo Lu, H. et al. ACS Chem. Biol. 4 , 221–231 (2009) Copeland, R. A. Nat Rev Drug Discov 15 , 87–95 (2016) activity. The plots presented here show the percent survival of mice 10 days after they were infected Francisella tularensis and then treated with the inhibitors. Correlation of percent ). Correlation of percent survival with inhibitor residence time. Figure is adapted with permission from , Wiley.

Inhibition of fatty acid synthesis for treatment of tularemia b 100 OH Cl Kinetics of ligand binding are O crucial to in vivo activity 80 Cl Cl OH O Survival (%) 60 Cl OH 40 O 20 OH O 0 2 3.0 0 20 40 60 80 100 120 140 160 OH Residence time (minutes) O In vivo . Lu et al. 5 the relationship between the residence time of a series of Fabl enoyl‑reductase inhibitors and in vivo Lu, H. et al. ACS Chem. Biol. 4 , 221–231 (2009) Copeland, R. A. Nat Rev Drug Discov 15 , 87–95 (2016) activity. The plots presented here show the percent survival of mice 10 days after they were infected Francisella tularensis and then treated with the inhibitors. Correlation of percent ). Correlation of percent survival with inhibitor residence time. Figure is adapted with permission from , Wiley.

Molecular mechanism of imatinib (Gleevec) Mechanism of binding 
 is central to activity Agafonov, R. V., Wilson, C., Otten, R., Buosi, V. & Kern, D. Nat. Struct. Mol. Biol. 21 , 848–853 (2014) Wilson, C. et al. Science 347 , 882–886 (2015)

Rates of reactions and spectroscopic timescales UV NMR ∆ν ∆ν UV frequency difference ∆ν ~ 10 14 Hz k ex ≪ ∆ν NMR frequency difference ∆ν ~ 100 Hz k ex ≫ ∆ν http://casegroup.rutgers.edu/lnotes/NMR_lecture_dynamics.pdf

NMR lineshapes vs exchange rates slow exchange 3 s –1 A ⌦ B 100% A 100% B frequency difference 200 s –1

NMR lineshapes vs exchange rates slow-intermediate exchange 30 s –1 A ⌦ B 100% A 100% B frequency difference 200 s –1

NMR lineshapes vs exchange rates fast-intermediate exchange 300 s –1 A ⌦ B 100% A 100% B frequency difference 200 s –1

NMR lineshapes vs exchange rates fast exchange 3000 s –1 A ⌦ B 100% A 100% B frequency difference 200 s –1

NMR lineshapes vs exchange rates magnetic field strength http://casegroup.rutgers.edu/lnotes/NMR_lecture_dynamics.pdf

NMR titrations are information rich molecular weight structure (linewidths) (chemical shifts) ∆ν ~ 10 – 10,000 s –1 binding => measure exchange on ‡ kinetics free energy timescales of µs – s P thermodynamics ( ∆ G = RT ln K d ) PL

NMR lineshape analysis Bloch-McConnell spin system parameters ligand concentration equations chemical shifts linewidths (relaxation rates) binding model parameters K d , k off … chemical shift P + L ⌦ PL 1 k ex = k o ff + k on [L] true fraction bound fraction bound chemical shift 0 0 50 100 150 ligand concentration / µM

NMR lineshape analysis Bloch-McConnell spin system parameters ligand concentration equations chemical shifts linewidths (relaxation rates) binding model parameters K d , k off … chemical shift

NMR lineshape analysis example: ultrafast folding (10 µs timescale) of villin headpiece Wang, M. et al. J. Am. Chem. Soc . 125 , 6032–6033 (2003)

From 1D to 2D… 8.5 8.0 7.5 7.0 108 108 15N chemical shift / ppm 110 110 112 112 114 114 116 116 8.5 8.0 7.5 7.0 1H chemical shift / ppm

Lineshape analysis of 1D cross-sections O'Connor, C. & Kovrigin, E. L. Biochemistry 51, 9638–9646 (2012)

Why isn’t lineshape analysis more common? • Apathy – ‘Good enough’ to assume fast/slow exchange and analyse chemical shift/intensity changes? • No! This risks systematic errors and ignores the richness of titration datasets • Complexity of analysis? • Software needs to be easy to use!

Problem #1: Peak overlap

Problem #2: Normalisation 1D pulse-acquire: 1 H no delay between pulse and acquisition => signal proportional to concentration 2D HSQC: signals decay during pulse program execution

Problem #2: Normalisation Raw intensities 7.7 7.6 7.5 7.4 7.3 Normalised peak volumes 7.7 7.6 7.5 7.4 7.3 1H chemical shift / ppm

Problem #2: Normalisation Raw intensities Spectra with measurement noise 7.7 7.6 7.5 7.4 7.3 7.7 7.6 7.5 7.4 7.3 Normalised peak volumes Normalised peak volumes 7.7 7.6 7.5 7.4 7.3 7.7 7.6 7.5 7.4 7.3 1H chemical shift / ppm 1H chemical shift / ppm

Problem #3: Differential relaxation 1D pulse-acquire: 1 H no delay between pulse and acquisition => signal proportional to concentration 2D HSQC: signals decay during pulse program execution

Problem #4: Multiple quantum evolution Δδ H = 0.1 ppm Δδ N = 0 ppm HMQC appears ligand concentration [P] 0 = 100 µM to have more 700 MHz 0 eq 0.25 eq 0.5 eq 0.75 eq 1 eq binding than HSQC 116 116 116 116 116 HMQC in HSQC 2 s – 1 117 117 117 117 117 7.6 7.5 7.6 7.5 7.6 7.5 7.6 7.5 7.6 7.5 dissociation rate 116 116 116 116 116 1 H chemical shift / ppm 2 0 s – 1 117 117 117 117 117 7.6 7.5 7.6 7.5 7.6 7.5 7.6 7.5 7.6 7.5 7.7 7.6 7.5 7.4 1 H chemical shift / ppm 116 116 116 116 116 1 2 0 0 s – 117 117 117 117 117 7.6 7.5 7.6 7.5 7.6 7.5 7.6 7.5 7.6 7.5 116 116 116 116 116 – 1 2 0 0 0 s 117 117 117 117 117 7.6 7.5 7.6 7.5 7.6 7.5 7.6 7.5 7.6 7.5 1 H chemical shift / ppm

Existing methods – at best – analyse 2D data using 1D theory… There must be a better way!

Two-dimensional lineshape analysis 114 114 15 N chemical shift / ppm spin system parameters QM chemical shifts 115 115 linewidths (relaxation rates) binding model parameters 116 116 K d , k off … 117 117 8 7.5 7 1 H chemical shift / ppm

Two-dimensional lineshape analysis 114 114 15 N chemical shift / ppm spin system parameters QM chemical shifts 115 115 linewidths (relaxation rates) binding model parameters 116 116 K d , k off … 117 117 8 7.5 7 1 H chemical shift / ppm

Two-dimensional lineshape analysis pulse program +experimental settings +processing parameters 114 114 15 N chemical shift / ppm spin system parameters QM chemical shifts 115 115 linewidths (relaxation rates) binding model parameters 116 116 K d , k off … 117 117 8 7.5 7 1 H chemical shift / ppm

How many parameters can we expect to extract from a spectrum? Evolution of isolated IS spin system (without chemical exchange): Pulse programs / degrees of freedom Helgstrand, M., Härd, T. & Allard, P. J. Biomol. NMR 18 , 49–63 (2000) 16 free parameters!

Two-dimensional lineshape analysis Helgstrand, M., Härd, T. & Allard, P. J. Biomol. NMR 18 , 49–63 (2000) Helgstrand, M. & Allard, P. J. Biomol. NMR 30 , 71–80 (2004)

Two-dimensional lineshape analysis ✓ No normalisation required between spectra ✓ Accounts for differential relaxation and MQ evolution during pulse sequence 15 N chemical shift / ppm 120 ✓ Can avoid regions of peak 
 overlap or fit overlapping 
 120.5 signals simultaneously 121 121.5 122 8.7 8.6 8.5 8.4 1 H chemical shift / ppm

Example: FIR / Nbox interaction GT rich FUSE ssDNA FBP RRM1 RRM2 FIR Nbox

Lineshape analysis: FIR / FBP Nbox observed fit reported: K d = 14 ± 8 µM fit: K d = 22.7 ± 0.5 µM k off = 2700 ±100 s –1 observed fit RRM1 RRM2 FIR Nbox

Lineshape analysis: FIR / FBP3 Nbox RRM1 fit: reported: K d = 283 ± 2 µM K d = 280 ± 36 µM RRM2 k off = 15000 ± 300 s –1 FIR Nbox3 observed fit