Resolving overlapped signals with automated FitNMR analytical peak modeling

Heat-induced structural and chemical changes to a computationally designed miniprotein

The de novo design of miniprotein inhibitors has recently emerged as a new technology to create proteins that bind with high affinity to specific therapeutic targets. Their size, ease of expression, and apparent high stability makes them excellent candidates for a new class of protein drugs. However, beyond circular dichroism melts and hydrogen/deuterium exchange experiments, little is known about their dynamics, especially at the elevated temperatures they seemingly tolerate quite well. To address that and gain insight for future designs, we have focused on identifying unintended and previously overlooked heat-induced structural and chemical changes in a particularly stable model miniprotein, EHEE_rd2_0005. Nuclear magnetic resonance (NMR) studies suggest the presence of dynamics on multiple time and temperature scales. Transiently elevating the temperature results in spontaneous chemical deamidation visible in the NMR spectra, which we validate using both capillary electrophoresis and mass spectrometry (MS) experiments. High temperatures also result in greatly accelerated intrinsic rates of hydrogen exchange and signal loss in NMR heteronuclear single quantum coherence spectra from local unfolding. These losses are in excellent agreement with both room temperature hydrogen exchange experiments and hydrogen bond disruption in replica exchange molecular dynamics simulations. Our analysis reveals important principles for future miniprotein designs and the potential for high stability to result in long-lived alternate conformational states.

Effects of Xylanase A double mutation on substrate specificity and structural dynamics

While protein activity is traditionally studied with a major focus on the active site, the activity of enzymes has been hypothesized to be linked to the flexibility of adjacent regions, warranting more exploration into how the dynamics in these regions affects catalytic turnover. One such enzyme is Xylanase A (XylA), which cleaves hemicellulose xylan polymers by hydrolysis at internal β-1,4-xylosidic linkages. It contains a "thumb" region whose flexibility has been suggested to affect the activity. The double mutation D11F/R122D was previously found to affect activity and potentially bias the thumb region to a more open conformation. We find that the D11F/R122D double mutation shows substrate-dependent effects, increasing activity on the non-native substrate ONPX2 but decreasing activity on its native xylan substrate. To characterize how the double mutant causes these kinetics changes, nuclear magnetic resonance (NMR) and molecular dynamics (MD) simulations were used to probe structural and flexibility changes. NMR chemical shift perturbations revealed structural changes in the double mutant relative to the wild-type, specifically in the thumb and fingers regions. Increased slow-timescale dynamics in the fingers region was observed as intermediate-exchange line broadening. Lipari-Szabo order parameters show negligible changes in flexibility in the thumb region in the presence of the double mutation. To help understand if there is increased energetic accessibility to the open state upon mutation, alchemical free energy simulations were employed that indicated thumb opening is more favorable in the double mutant. These studies aid in further characterizing how flexibility in adjacent regions affects the function of XylA.

REDEN: Interactive multi-fitting decomposition-based NMR peak picking assistant

We present a new program REDEN (Residual Decomposition of NMR peaks) designed to perform identification of peaks in NMR spectra. This integrated, cross-platform, open-source software visually assists with explicit peak picking through decomposition of NMR peaks on the frequency domain data. It provides a distinctive interactive workflow with iPick due to its integration with the POKY suite, providing users with a seamless and efficient experience. The decomposition of peaks operates in a chosen region of an NMR spectrum by multi-fitting simulated peaks with four lineshape fitting options as support, Gaussian, Lorentzian, a fast/optimized Lorentzian, and Pseudo-Voigt. Furthermore, REDEN provides a way to fine-tune for the users in two operating modes (Basic and Advanced). REDEN is pre-built in the POKY suite, which is available from https://poky.clas.ucdenver.edu.

Barriers to resolution in 1H NMR of rotating solids

The role of 1H solid-state NMR in structure elucidation of solids is becoming more preponderant, particularly as faster magic-angle spinning rates (MAS) become available which improve 1H detected assignment strategies. However, current 1H spectral resolution is still relatively poor, with linewidths of typically a few hundred Hz, even at the fastest rates available today. Here we detail and assess the factors limiting proton linewidths and line shapes in MAS experiments with five different samples, exemplifying the different sources of broadening that affect the residual linewidth. We disentangle the different contributions through one- and two-dimensional experiments: by using dilution to identify the contribution of ABMS; by using extensive deuteration to identify the dipolar contributions; and by using variable MAS rates to determine the ratio between homogeneous and inhomogeneous components. We find that the overall widths and the nature of the different contributions to the linewidths can vary very considerably. While we find that faster spinning always yields narrower lines and longer coherence lifetimes, we also find that for some resonances the dipolar contribution is no longer dominant at 100 kHz MAS. When the inhomogeneous sources of broadening, such as ABMS and chemical shift disorder, are dominant, two-dimensional 1H-1H correlation experiments yield better resolution for assignment. Particularly the extraction of the antidiagonal of a 2D peak will remove any correlated inhomogeneous broadening, giving substantially narrower 1H linewidths.

DEEP Picker1D and Voigt Fitter1D: a versatile tool set for the automated quantitative spectral deconvolution of complex 1D-NMR spectra

The quantitative deconvolution of 1D-NMR spectra into individual resonances or peaks is a key step in many modern NMR workflows as it critically affects downstream analysis and interpretation. Depending on the complexity of the NMR spectrum, spectral deconvolution can be a notable challenge. Based on the recent deep neural network DEEP Picker and Voigt Fitter for 2D NMR spectral deconvolution, we present here an accurate, fully automated solution for 1D-NMR spectral analysis, including peak picking, fitting, and reconstruction. The method is demonstrated for complex 1D solution NMR spectra showing excellent performance also for spectral regions with multiple strong overlaps and a large dynamic range whose analysis is challenging for current computational methods. The new tool will help streamline 1D-NMR spectral analysis for a wide range of applications and expand their reach toward ever more complex molecular systems and their mixtures.

COLMARq: A Web Server for 2D NMR Peak Picking and Quantitative Comparative Analysis of Cohorts of Metabolomics Samples

Highly quantitative metabolomics studies of complex biological mixtures are facilitated by the resolution enhancement afforded by 2D NMR spectra such as 2D ¹³C-¹H HSQC spectra. Here, we describe a new public web server, COLMARq, for the semi-automated analysis of sets of 2D HSQC spectra of cohorts of samples. The workflow of COLMARq includes automated peak picking using the deep neural network DEEP Picker, quantitative cross-peak volume extraction by numerical fitting using Voigt Fitter, the matching of corresponding cross-peaks across cohorts of spectra, peak volume normalization between different spectra, database query for metabolite identification, and basic univariate and multivariate statistical analyses of the results. COLMARq allows the analysis of cross-peaks that belong to both known and unknown metabolites. After a user has uploaded cohorts of 2D ¹³C-¹H HSQC and optionally 2D ¹H-¹H TOCSY spectra in their preferred format, all subsequent steps on the web server can be performed fully automatically, allowing manual editing if needed and the sessions can be saved for later use. The accuracy, versatility, and interactive nature of COLMARq enables quantitative metabolomics analysis, including biomarker identification, of a broad range of complex biological mixtures as is illustrated for cohorts of samples from bacterial cultures of Pseudomonas aeruginosa in both its biofilm and planktonic states.

Non-Uniform Sampling in NMR Spectroscopy and the Preservation of Spectral Knowledge in the Time and Frequency Domains

The increased sensitivity under weighted non-uniform sampling (NUS) is demonstrated and quantified using Monte Carlo simulations of nuclear magnetic resonance (NMR) time- and frequency-domain signals. The concept of spectral knowledge is introduced and shown to be superior to the frequency-domain signal-to-noise ratio for assessing the quality of NMR data. Two methods for rigorously preserving spectral knowledge and the time-domain NUS knowledge enhancement upon transformation to the frequency domain are demonstrated, both theoretically and numerically. The first, non-uniform weighted sampling using consistent root-mean-square noise, is applicable to data sampled on the Nyquist grid, whereas the second, the block Fourier transform using consistent root-mean-square noise, can be used to transform time-domain data acquired with arbitrary, off-grid NUS.