Our research focuses on characterizing the molecular interactions that drive protein folding and association, and mediate compartmentalization in biological membranes. We develop and apply new optical tools based on ultrafast two-dimensional infrared (2D IR) spectroscopy. Our current research builds upon our expertise in ultrafast optics, non-linear spectroscopy and microscopy, molecular dynamics simulations, semiclassical models of vibrational spectra, and protein biophysics.
Water Dynamics in Biocondensates
Liquid-liquid phase separation (LLPS) is a critical phenomenon in biology, wherein specific biomolecules, primarily proteins and nucleic acids, demix from the surrounding milieu to form concentrated, droplet-like assemblies known as condensates. these condensates compartmentalize cellular space without a membrane, allowing the cell to dynamically regulate biological processes, including signal transduction, RNA metabolism, and stress response. Analogous to oil and water separation, these condensates are liquid-like. The specific interactions that lead to LLPS are not well understood, and specifically the role of water and hydrogen-bonding has not been well characterized within the complex condensate phase. We use a combination of ultrafast 2D IR spectroscopy and molecular dynamics simulations to study how water behaves within the condensate phase. Specifically, we probe the changes hydrogen-bond dynamics and disrupted hydrogen bond networks in the ultracrowded environment of the condensate.
Hydrogen-bond Dynamics in Complex Environments
Intracellular environments are highly crowded and heterogeneous containing proteins, lipids, and osmolytes, which are small organic molecules. In fact, as much as 30% of intracellular water molecules are part of the inner solvation shells of these molecules and exhibit slower hydrogen-bond dynamics. While the effects of crowding are not well understood, it is known that excluded-volumes can provide a certain degree of entropic stabilization of native protein structures. Ultrafast spectroscopy has provided an atomistic description of hydrogen-bond dynamics in bulk water, however probing the heterogeneous environments remains challenging. Our group is applying the 2D IR “toolkit” towards understanding ultrafast hydrogen-bond dynamics at the protein-water interface in crowded environments.
Further reading: Xiao You, and Carlos R. Baiz “Importance of Hydrogen-bonding in Crowded Environments: A Physical Chemistry Perspective“, Journal of Physical Chemistry A (2022) [PDF]
The Chemistry of Ice
We are investigating the effect of small molecules known as “cryoprotectants” which disrupt the H-bond donor/acceptor balance and can prevent intracellular ice formation. Such compounds are routinely added to cell cultures prior to low-temperature storage. The thermodynamic effects of cryoprotectants on the proteins and membranes are not well understood. Our group is investigating the specific mechanisms by which DMSO, a common cryoprotectant, disrupts the water-water interactions, and leads to protein denaturation.
Further reading: Euihyun Lee, and Carlos R. Baiz, “How cryoprotectants work: hydrogen-bonding in low-temperature vitrified solutions“, Chemical Science (2022) [PDF]
Heterogeneous Surfactant Interfaces
Surfactants are used daily in an extremely diverse array of applications, ranging from food and cosmetics to oil recovery and organic synthesis. However, current models of these molecules are extremely reductive and little is known about how interactions between surfactants and their solution environment gives rise to well-characterized bulk behaviors. This forces researchers to use trial-and-error methods to find the compound best-suited for a given application. Furthermore, highly heterogeneous blends of detergents are commonly used in industrial applications. We combine advanced spectroscopic techniques, molecular dynamics simulations, and synthetic labeling protocols to observe the surfactant environment as a function of solution composition and detergent heterogeneity to begin to understand the connection between molecular interactions and useful properties.
Further reading: Christopher P Baryiames, Paul Garrett, and Carlos R. Baiz, “Bursting the bubble: a molecular understanding of surfactant-water interfaces“, Journal of Chemical Physics (2021) [PDF]
Peptide Folding and Membrane Translocation
Three-dimensional protein structures are the end result of a complex, multi-step folding process. Spontaneous folding depends on a subtle enthalpic and entropic balance between contact formation, desolvation, and electrostatics. Lipid membranes add an extra layer of complexity as the environment changes significantly between the hydrophilic, solvent-exposed environment of the disordered peptide and the hydrophobic, membrane-embedded folded state. The figure shows possible pathways for the coupled folding-translocation of a small peptide into a lipid membrane. Our group uses a combination of pH-jump nonequilibrium two-dimensional infrared spectroscopy, isotope labeling of the peptide backbone, and molecular dynamics simulations to map protein-membrane interactions and track the folding pathways from the initial disordered state to the final folded structure.
Further reading: Jennifer C. Flanagan, and Carlos R. Baiz, “Site-specific peptide probes detect buried water in a lipid membrane“, Biophysical Journal, 116, 9, 1692-1700 (2019).[PDF]
Biophysics of Lipid Membranes
Biological membranes are highly heterogeneous, containing thousands of lipid species and crowded by hundreds of different proteins. However, to date most biophysical studies are carried out on model bilayers containing a single lipid species. The interplay between interfacial environments, lipid-lipid interactions, local water structure and dynamics is not understood, particularly, for multi-component membranes. Our group uses 2D IR spectroscopy, isotope labels on the lipid ester carbonyls, and molecular dynamics simulations (in collaboration with Prof. Eric Senning and Prof. Ron Elber) to investigate the local water dynamics (H-bond lifetimes) in heterogeneous membranes. Our experiments are aimed at measuring how membrane composition affects interfacial water environments. Initial studies on this project have shown that ions can significantly slow down the interfacial water dynamics.
Further reading: Xiaobing Chen, Ziareena A. Al-Mualem, Carlos R. Baiz, “Lipid Landscapes: Vibrational Spectroscopy for Decoding Membrane Complexity“, Submitted (2023). [ChemRXiv]
Biological Ion-binding – Critical Minerals
Rare-earth elements are ubiquitous in many applications including electronics and renewable energy technologies. The ions are difficult to separate due to their similar chemical properties. Proteins have shown great promise due to their ability to specifically bind certain lanthanides. We are exploring the potential of small peptide sequences that have the ability to chelate ions with high affinity and specificity. We investigate the relation between sequence, structure, binding configuration, across different ions in the lanthanide series. This is achieved by preforming 2D IR measurements on the carboxylate groups that make up the binding residues.
Further reading: Stephanie Liu, Emily R. Featherston, Joseph A. Cotruvo, Jr., and Carlos R. Baiz, “Lanthanide-dependent coordination interactions in lanmodulin: a 2D IR and molecular dynamics simulations study“, Physical Chemistry Chemical Physics, (2021) [PDF]
Hydrogen Bonding at Electrode Interfaces
Electrochemical reactions for hydrogen gas production will play a pivotal role in the transition towards renewable energies. Specifically the hydrogen-evolution reaction (HER), HER effectively produces hydrogen gas—a form of energy that can be stored providing a buffer for intermittent sources such as solar and wind and increasing the reliability of renewable energy. Improving the efficiency of HER, however, is quite challenging as water acts as both a reactant and solvent. Controlling the hydrogen-bond networks at the electrode interface is a promising route to reduce losses. Our group investigates local hydrogen bond networks in water and organic cosolvents, such as DMSO, at the electrode interface using surface-enhanced IR absorption spectroscopy (SEIRAS) a technique that provides very high surface sensitivity using thin metal films to enhance IR signals at the interface. IR spectroscopy can then be used to probe the vibrational modes, and hence the environments, of the molecules located within ~100 nm of an electrode interface across a wide range of applied potentials.
Further reading: Ziareena A. Al-Mualem,† , Keegan A. Lorenz-Ochoa,†, Lei Pan, Hang Ren, Carlos R. Baiz, “DMSO Cosolvent Mixtures Modulate Hydrogen Bonding at a Gold Electrode Interface“ [ChemRXiv]
Generative AI for Science and Education
Generative AI has emerged as a powerful tool in both chemistry research and education, paving the way for innovative approaches to complex problems that cannot be solved using traditional methods. In the realm of research, especially in areas like molecular dynamics simulations and IR spectroscopy, generative AI can be used to optimize data acquisition, and analysis. For example, we have developed an algorithm that can denoise 2D IR spectra using constrained Generative Adversarial Neural Networks (cGANNs) which can speed up data acquisition by an order of magnitude. We aim to continue following the latest developments in AI and exploring creative uses of AI for scientific applications. In terms of education, we explore uses of AI throughout the scientific process, including data analysis and manuscript writing.
Further reading: Ziareena A. Al-Mualem, and Carlos R. Baiz, “Generative Adversarial Neural Networks for Denoising Coherent Multidimensional Spectra“, Journal of Physical Chemistry A (2022) [PDF]
Eman A Alasadi, and Carlos R. Baiz, “Generative AI in Education and Research: Opportunities, Concerns, and Solutions“, Journal of Chemical Education (2023) [PDF]
Ultrafast 2D IR spectroscopy
Two-dimensional infrared spectroscopy is an ultrafast optical technique that reveals molecular structure and fast dynamics by using a sequence of femtosecond (10-15 s) laser pulses to measure frequency correlations between (and within) vibrational modes in a sample. In brief, a pair of pulses excites specific vibrational modes in the sample, then, following a short waiting time, a third laser pulse measures the response of the sample. Analogous to 2D NMR, a 2D IR spectrum is, in essence, a two-dimensional excitation-detection frequency correlation map. Cross peaks are observed when two vibrational modes are able to exchange vibrational energy, for instance, two normal modes involving the same atoms, or molecules able to chemically interconvert within the timescales measurement, such as two rapidly-interconverting molecular conformations. The degree of diagonal elongation (frequency correlation) is a direct measure of the frequency fluctuations of a vibrational mode, which in turn reports on the environment around a molecule. In general, the diagonal and off-diagonal lineshapes and peak intensities provide a detailed, bond-specific, view of molecular structure and dynamics.
Protein structure is reflected on the backbone C=O stretching vibrations, known as amide I modes. The periodic arrangement of residues along a protein backbone, gives rise to characteristic vibrational modes which appear in specific regions of the IR spectrum, but the broad, often featureless, peaks that arise from structural disorder and solvent exposure complicate the interpretation of traditional FTIR spectra. Two-dimensional infrared spectroscopy spreads the spectral information onto two frequency axes, thus providing an additional degree of structural characterization of the protein ensemble. In addition, the excitation-waiting-detection sequence of interactions serves to map the fast hydrogen-bonding dynamics of the backbone. Our group develops new optical implementations of 2D IR spectroscopy.
Futher reading: Ziareena A. Al-Mualem, Xiaobing Chen, Joseph C. Shirley, Cong Xu, Carlos R. Baiz “BoxCARS 2D IR Spectroscopy with Pulse Shaping“, Optics Express (2023) [ChemRxiv]
Computational modeling of IR spectra
Vibrational frequencies are particularly sensitive to the environment of a molecule, but lineshapes are often broad and difficult to interpret. Computational models are useful in helping us interpret the measured spectra (frequencies, linewidths, timescales). We develop models that produce accurate results at little computational expense. Particularly, semiclassical models take the advantage of the sensitivity of vibrational frequencies to the electrostatic environment. Our group is currently extending these models to understand how the spectra of lipids report on the overall structure and hydrogen-bonding environment, specifically the degree of hydration inside lipid bilayers.
Futher reading: Carlos R. Baiz, Bartosz Blasiak, Jens Bredenbeck, Minhaeng Cho* (corresponding author), Jun-Ho Choi, Steven A. Corcelli, Arend G. Dijkstra, Chi-Jui Feng, Sean Garrett-Roe, Nien-Hui Ge, Magnus W. Hanson-Heine, Jonathan D. Hirst, Thomas la Cour Jansen, Kijeong Kwac, Kevin J. Kubarych, Casey H. Londergan, Hiroaki Maekawa, Mike Reppert, Shinji Saito, Santunu Roy, James L. Skinner, Gerhard Stock, John E. Straub, Megan C. Thielges, Keisuke Tominaga, Andrei Tokmakoff, Hajime Torii, Lu Wang, Lauren J. Webb, and Martin T. Zanni, Vibrational Frequency Map, Vibrational Spectroscopy, and Intermolecular Interaction, Chemical Reviews (2020) [PDF]