Aritro Sinha Roy

Intrinsically disordered proteins (IDPs) underlie essential cellular functions and drive neurodegenerative diseases through mutation-induced structural changes, yet their conformational heterogeneity often evades crystallography and cryo-EM. Electron spin resonance (ESR) pulsed dipolar spectroscopy (PDS), which determines distance distributions between a pair of spin-labeled residues in a protein, can provide complementary and meaningful information related to conformational heterogeneity in IDPs. Double quantum coherence (DQC) is an important ESR PDS technique, capable of measuring a wide range of distances (∼10 to at least 80 Å), and is a single-frequency technique with a small background that can be easily removed. This makes DQC an ideal candidate to probe IDPs. We present a complete theoretical framework for DQC data analysis, incorporating pseudosecular dipolar coupling and finite pulse effects, enabling rapid and accurate reconstruction of complex distance distributions in doubly nitroxide-labeled IDPs. We validate the method on rigid biradicals with known interspin distances. The application to a tau protein fragment (jR2R3) reveals distinct end-to-end distance distributions for the wild-type vs the disease-associated P301L mutant. The results expose differences in their conformational distributions, which likely govern their divergent aggregation propensities. This advance also establishes DQC ESR as a powerful, accessible tool for probing disorders in biomolecular systems.

Green hydrogen is increasingly acknowledged as a pivotal facilitator for the transition to a sustainable and renewable energy paradigm, presenting a clean alternative to conventional fossil fuels.

A uniquely positioned pendant amine-mediated molecular Cu-complex-driven rapid electrocatalytic H ₂ production reaction in water.

Double electron electron resonance (DEER) spectroscopy is an important technique to measure distance distributions P(r) for studying protein structures and protein-protein interactions. DEER data analysis can at times become challenging due to the lack of a detailed analytical signal expression or numerical methods with rapid computation time. We have derived an analytical expression κ_FULL, which includes both the pseudo-secular dipolar coupling (PSDC) and the finite pulse effects, especially important for shorter distances. Analyses of experiments by κ_FULL yield accurate and consistent P(r) values for three DEER nitroxide-rulers with distances (r_AVG) in the range of 15 to 32 Å, while the current standard analysis produces erroneous results for r_AVG < 20 Å. Computation times for deriving P(r) vary between 1 min and 4 min, which is usually much shorter than previous methods that include pseudo-secular and other effects. The expression can be applied to all types of DEER spin probes with little or no modifications.

Electron spin resonance pulsed dipolar spectroscopy (PDS) has become popular in protein 3D structure analysis. PDS studies yield distance distributions between a pair or multiple pairs of spin probes attached to protein molecules, which can be used directly in structural studies or as constraints in theoretical predictions. Double-quantum coherence (DQC) is a highly sensitive and accurate PDS technique to study protein structures in the solid state and under physiologically relevant conditions. In this work, we have derived analytical expressions for the DQC signal for a system with N-dipolar coupled spin-1/2 particles in the solid state. The expressions are integrated over the relevant spatial parameters to obtain closed form DQC signal expressions. These expressions contain the concentration-dependent “instantaneous diffusion” and the background signal. For micromolar and lower concentrations, these effects are negligible. An approximate analysis is provided for cases of finite pulses. The expressions obtained in this work should improve the analysis of DQC experimental data significantly, and the analytical approach could be extended easily to a wide range of magnetic resonance phenomena.

Site-directed spin labeling has enabled protein structure determination using electron spin resonance pulsed dipolar spectroscopy (PDS). Small details in a distance distribution can be key to understanding important protein structure–function relationships. A major challenge has been to differentiate unimodal and overlapped multimodal distance distributions. They often yield similar distributions and dipolar signals. Current model-free distance reconstruction techniques, such as Srivastava-Freed singular value decomposition and Tikhonov regularization, can suppress these small features in uncertainty and/or error bounds, despite being present. In this work, we demonstrate that continuous wavelet transform (CWT) can distinguish PDS signals from unimodal and multimodal distance distributions. We show that periodicity in CWT representation reflects unimodal distributions, which is masked for multimodal cases. This work is meant as a precursor to a cross-validation technique, which could indicate the modality of the distance distribution.

Two-dimensional electron spin resonance (2D ESR) spectroscopy is a unique experimental technique for probing protein structure and dynamics, including processes that occur at the microsecond time scale. While it provides significant resolution enhancement over the one-dimensional experimental setup, spectral broadening and noise make extraction of spectral information highly challenging. Traditionally, two-dimensional Fourier transform (2D FT) is applied for the analysis of 2D ESR signals, although its efficiency is limited to stationary signals. In addition, it often fails to resolve overlapping peaks in 2D ESR. In this work, we propose a time-frequency analysis of 2D time-domain signals, which identifies all frequency peaks by decoupling a signal into its distinct constituent components via projection on the time-frequency plane. The method utilizes 2D undecimated discrete wavelet transform (2D UDWT) as an intermediate step in the analysis, followed by signal reconstruction and 2D FT. We have applied the method to a simulated 2D double quantum coherence (DQC) signal for validation and a set of experimental 2D ESR signals, demonstrating its efficiency in resolving overlapping peaks in the frequency domain, while displaying frequency evolution with time in case of non-stationary data.

The accurate analysis of continuous-wave electron spin resonance (cw ESR) spectra of biological or organic free-radicals and paramagnetic metal complexes is key to understanding their structure–function relationships and electrochemical properties. The current methods of analysis based on simulations often fail to extract the spectral information accurately. In addition, such analyses are highly sensitive to spectral resolution and artifacts, users’ defined input parameters and spectral complexity. We introduce a simulation-independent spectral analysis approach that enables broader application of ESR. We use a wavelet packet transform-based method for extracting g values and hyperfine (A) constants directly from cw ESR spectra. We show that our method overcomes the challenges associated with simulation-based methods for analyzing poorly/partially resolved and unresolved spectra, which is common in most cases. The accuracy and consistency of the method are demonstrated on a series of experimental spectra of organic radicals and copper–nitrogen complexes. We showed that for a two-component system, the method identifies their individual spectral features even at a relative concentration of 5% for the minor component.

Accurate analysis of continuous-wave electron spin resonance (cw ESR) spectra of biological or organic free-radicals and paramagnetic metal complexes is key to understand their structure-function relationships and electrochemical properties. Current method of analysis based on simulations often fail to extract the spectral information accurately. In addition, such analyses are highly sensitive to spectral resolution and artifacts, users’ defined input parameters and spectral complexity. We introduce a simulation-independent spectral analysis approach that enables broader application of ESR. We use a wavelet packet transform-based method for extracting g values and hyperfine (A) constants directly from cw ESR spectra. We show that our method overcomes the challenges associated with simulation-based methods for analyzing poorly / partially resolved and unresolved spectra, which is a common in most cases. The accuracy and consistency of the method are demonstrated on a series of experimental spectra of organic radicals and copper-nitrogen complexes. We showed that for a two-component system, the method identifies their individual spectral features even at a relative concentration of 5% for the minor component.