Allostery at a Protein-Protein Interface Harboring an Intermolecular Motional Network.

Motional properties of proteins govern recognition, catalysis, and regulation. The dynamics of tightly interacting residues can form intramolecular dynamic networks, dependencies fine-tuned by evolution to optimize a plethora of functional aspects. The constructive interaction of residues from different proteins to assemble intermolecular dynamic networks is a similarly likely case but has escaped thorough experimental assessment due to interfering association/dissociation dynamics. Here, we use fast-MAS solid-state 15N R1ρ NMR relaxation dispersion aided by molecular-dynamics simulations to mechanistically assess the hierarchy of individual µs timescale motions arising from a crystal-crystal contact, in the absence of translational motion. In contrast to the monomer, where particular mutations entail isolated perturbations, specific intermolecular interactions couple the motional properties between distant residues in the same protein. The mechanistic insights obtained from this conceptual work may improve our understanding on how intramolecular allostery can be tuned by intermolecular interactions via assembly of dynamic networks from previously isolated elements.

Molecular basis of the interactions between the disordered Neh4 and Neh5 domains of Nrf2 and CBP/p300 in oxidative stress response.

Nuclear factor erythroid 2-related factor 2 (Nrf2) is a major transcription factor that functions in maintaining redox homeostasis in cells. It mediates the transcription of cytoprotective genes in response to environmental and endogenous stresses to prevent oxidative damage. Thus, Nrf2 plays a significant role in chemoprevention. However, aberrant activation of Nrf2 has been shown to protect cancer cells from apoptosis and contribute to their chemoresistance. The interaction between Nrf2 and CBP is critical for the gene transcription activation. CBP and its homologue p300 interact with two transactivation domains in Nrf2, Neh4, and Neh5 domains through their TAZ1 and TAZ2 domains. To date, the molecular basis of this crucial interaction is not known, hindering a more detailed understanding of the regulation of Nrf2. To close this knowledge gap, we have used a set of biophysical experiments to dissect the Nrf2-CBP/p300 interactions. Structural properties of Neh4 and Neh5 and their binding with the TAZ1 and TAZ2 domains of CBP/p300 were characterized. Our results show that the Neh4 and Neh5 domains of Nrf2 are intrinsically disordered, and they both can bind the TAZ1 and TAZ2 domains of CBP/p300 with micromolar affinities. The findings provide molecular insight into the regulation of Nrf2 by CBP/p300 through multi-domain interactions.

The structural biology and dynamics of malate dehydrogenases.

Malate dehydrogenase (MDH) enzymes catalyze the reversible oxidoreduction of malate to oxaloacetate using NAD(P) as a cofactor. This reaction is vital for metabolism and the exchange of reducing equivalents between cellular compartments. There are more than 100 structures of MDH in the Protein Data Bank, representing species from archaea, bacteria, and eukaryotes. This conserved family of enzymes shares a common nucleotide-binding domain, substrate-binding domain, and subunits associate to form a dimeric or a tetrameric enzyme. Despite the variety of crystallization conditions and ligands in the experimental structures, the conformation and configuration of MDH are similar. The quaternary structure and active site dynamics account for most conformational differences in the experimental MDH structures. Oligomerization appears essential for activity despite each subunit having a structurally independent active site. There are two dynamic regions within the active site that influence substrate binding and possibly catalysis, with one of these regions adjoining the subunit interface. In this review, we introduce the reader to the general structural framework of MDH highlighting the conservation of certain features and pointing out unique differences that regulate MDH enzyme activity.

Differential conformational dynamics in two type-A RNA-binding domains drive the double-stranded RNA recognition and binding.

Trans-activation response (TAR) RNA-binding protein (TRBP) has emerged as a key player in the RNA interference pathway, wherein it binds to different pre-microRNAs (miRNAs) and small interfering RNAs (siRNAs), each varying in sequence and/or structure. We hypothesize that TRBP displays dynamic adaptability to accommodate heterogeneity in target RNA structures. Thus, it is crucial to ascertain the role of intrinsic and RNA-induced protein dynamics in RNA recognition and binding. We have previously elucidated the role of intrinsic and RNA-induced conformational exchange in the double-stranded RNA-binding domain 1 (dsRBD1) of TRBP in shape-dependent RNA recognition. The current study delves into the intrinsic and RNA-induced conformational dynamics of the TRBP-dsRBD2 and then compares it with the dsRBD1 study carried out previously. Remarkably, the two domains exhibit differential binding affinity to a 12-bp dsRNA owing to the presence of critical residues and structural plasticity. Furthermore, we report that dsRBD2 depicts constrained conformational plasticity when compared to dsRBD1. Although, in the presence of RNA, dsRBD2 undergoes induced conformational exchange within the designated RNA-binding regions and other residues, the amplitude of the motions remains modest when compared to those observed in dsRBD1. We propose a dynamics-driven model of the two tandem domains of TRBP, substantiating their contributions to the versatility of dsRNA recognition and binding.

Water determines the intramolecular dynamics of proteins. En example of bovine serum albumin.

In this work, the terahertz time-domain spectroscopy method analyzed solutions of bovine serum albumin (BSA) in two high concentrations (50 and 334 mg/mL) at three pH values (2.5, 6.5, 8.5) and the same solvents without protein, at 25°C. The spectra of dry BSA were also recorded. For the first time, a method for determining the complex dielectric permittivity of protein molecules in aqueous solutions, without the dielectric contribution of the aqueous phase, is proposed. It is shown that the dielectric permittivity of dissolved and dry BSA (lyophilized, in the native conformation) differ significantly in the terahertz frequency range. These differences are small near 70 cm-1, but they increase greatly with decreasing frequency. It was found that the dielectric losses of protein molecules in solution are close to the dielectric losses of the aqueous environment, which in this frequency range are determined by intermolecular relaxation processes of water. Since dielectric losses are directly related to molecular dynamics, this fact shows that the intramolecular dynamics of the protein completely adjusts to the intermolecular dynamics of the aqueous environment. It also indicates that the native conformation does not determine all the fundamental characteristics of a protein molecule, in particular, it does not determine the dynamics of the protein, which significantly depends on the water environment.

Computational exploration of protein structure dynamics and RNA structural consequences of PKD1 missense variants: implications in ADPKD pathogenesis.

We analyzed the impact of nine previously identified missense PKD1 variants from our studies, including c.6928G > A p.G2310R, c.8809G > A p.E2937K, c.2899 T > C p.W967R, c.6284A > G p.D2095G, c.6644G > A p.R2215Q, c.7810G > A p.D2604N, c.11249G > C p.R3750P, c.1001C > T p.T334M, and c.3101A > G p.N1034S on RNA structures and PC1 protein structure dynamics utilizing computational tools. RNA structure analysis was done using short RNA snippets of 41 nucleotides with the variant position at the 21st nucleotide, ensuring 20 bases on both sides. The secondary structures of these RNA snippets were predicted using RNAstructure. Structural changes of the mutants compared to the wild type were analyzed using the MutaRNA webserver. Molecular dynamics (MD) simulation of PC1 wild-type and mutant protein regions were performed using GROMACS 2018 (GROMOS96 54a7 force field). Findings revealed that five variants including c.8809G > A (p.E2937K), c.11249G > C (p.R3750P), c.3101A > G (p.N1034S), c.6928G > A (p.G2310R), c.6644G > A (p.R2215Q) exhibited major alterations in RNA structures and thereby their interactions with other proteins or RNAs affecting protein structure dynamics. While certain variants have minimal impact on RNA conformations, their observed alterations in MD simulations indicate impact on protein structure dynamics highlighting the importance of evaluating the functional consequences of genetic variants by considering both RNA and protein levels. The study also emphasizes that each missense variant exerts a unique impact on RNA stability, and protein structure dynamics, potentially contributing to the heterogeneous clinical manifestations and progression observed in Autosomal Dominant Polycystic Kidney Disease (ADPKD) patients offering a novel perspective in this direction. Thus, the utility of studying the structure dynamics through computational tools can help in prioritizing the variants for their functional implications, understanding the molecular mechanisms underlying variability in ADPKD presentation and developing targeted therapeutic interventions. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-024-04057-9.

Field-domain rapid-scan EPR at 240GHz for studies of protein functional dynamics at room temperature.

We present field-domain rapid-scan (RS) electron paramagnetic resonance (EPR) at 8.6T and 240GHz. To enable this technique, we upgraded a home-built EPR spectrometer with an FPGA-enabled digitizer and real-time processing software. The software leverages the Hilbert transform to recover the in-phase (I) and quadrature (Q) channels, and therefore the raw absorptive and dispersive signals, χ' and χ'', from their combined magnitude (I2+Q2). Averaging a magnitude is simpler than real-time coherent averaging and has the added benefit of permitting long-timescale signal averaging (up to at least 2.5×106 scans) because it eliminates the effects of source-receiver phase drift. Our rapid-scan (RS) EPR provides a signal-to-noise ratio that is approximately twice that of continuous wave (CW) EPR under the same experimental conditions, after scaling by the square root of acquisition time. We apply our RS EPR as an extension of the recently reported time-resolved Gd-Gd EPR (TiGGER) [Maity et al., 2023], which is able to monitor inter-residue distance changes during the photocycle of a photoresponsive protein through changes in the Gd-Gd dipolar couplings. RS, opposed to CW, returns field-swept spectra as a function of time with 10ms time resolution, and thus, adds a second dimension to the static field transients recorded by TiGGER. We were able to use RS TiGGER to track time-dependent and temperature-dependent kinetics of AsLOV2, a light-activated phototropin domain found in oats. The results presented here combine the benefits of RS EPR with the improved spectral resolution and sensitivity of Gd chelates at high magnetic fields. In the future, field-domain RS EPR at high magnetic fields may enable studies of other real-time kinetic processes with time resolutions that are otherwise difficult to access in the solution state.

Riemannian geometry for efficient analysis of protein dynamics data.

An increasingly common viewpoint is that protein dynamics datasets reside in a nonlinear subspace of low conformational energy. Ideal data analysis tools should therefore account for such nonlinear geometry. The Riemannian geometry setting can be suitable for a variety of reasons. First, it comes with a rich mathematical structure to account for a wide range of geometries that can be modeled after an energy landscape. Second, many standard data analysis tools developed for data in Euclidean space can be generalized to Riemannian manifolds. In the context of protein dynamics, a conceptual challenge comes from the lack of guidelines for constructing a smooth Riemannian structure based on an energy landscape. In addition, computational feasibility in computing geodesics and related mappings poses a major challenge. This work considers these challenges. The first part of the paper develops a local approximation technique for computing geodesics and related mappings on Riemannian manifolds in a computationally feasible manner. The second part constructs a smooth manifold and a Riemannian structure that is based on an energy landscape for protein conformations. The resulting Riemannian geometry is tested on several data analysis tasks relevant for protein dynamics data. In particular, the geodesics with given start- and end-points approximately recover corresponding molecular dynamics trajectories for proteins that undergo relatively ordered transitions with medium-sized deformations. The Riemannian protein geometry also gives physically realistic summary statistics and retrieves the underlying dimension even for large-sized deformations within seconds on a laptop.

Quantifying Protein Dynamics by Kymograph Analysis.

Time-lapse imaging of the subcellular localization and dynamic behavior of proteins is critical to understand their biological functions in cells. With the advent of various methodologies and computational tools, the precise tracking and quantification of protein spatiotemporal dynamics have become feasible. Kymograph analysis, in particular, has been extensively adopted for the quantitative assessment of proteins, vesicles, and organelle movements. However, conventional kymograph analysis, which is based on a single linear trajectory, may not comprehensively capture the complexity of proteins that alter their course during intracellular transport and activity. In this chapter, we introduced an advanced protocol for whole-cell kymograph analysis that allows for three-dimensional (3D) tracking of protein dynamics. This method was validated through the analysis of tip-focused endocytosis and exocytosis processes in growing tobacco pollen tubes by employing both the advanced whole-cell and classical kymograph methods. In addition, we enhanced this method by integrating pseudo-colored kymographs that enables the direct visualization of changes in protein fluorescence intensity with fluorescence recovery after photobleaching to advance our understanding of protein localization and dynamics. This comprehensive method offers a novel insight into the intricate dynamics of protein activity within the cellular context.

Visualization, Quantification, and Statistical Evaluation of Dynamics for DNA-Binding Proteins in Bacteria by Single-Molecule Tracking.

All DNA-binding proteins in vivo exist as a population of freely diffusing molecules and of DNA-bound molecules. The molecules bound to DNA can be split into specifically/tightly and nonspecifically bound proteins. Single-molecule tracking (SMT) is a method allowing to visualize protein dynamics in living cells, revealing their behavior in terms of mode of motion, diffusion coefficient/speed, change of dwell times, and unveiling preferred subcellular sites of dwelling. Bleaching-type SMT or fluorescent protein-tagged SMT involves rapid laser-induced bleaching of most fluorophore-labeled molecules. The remaining single fluorescent proteins are then continuously tracked. The trajectories of several fluorescent molecules per cell for a population of cells are analyzed and combined to permit a robust analysis of average behavior of single molecules in live cells, including analyses of protein dynamics in mutant cells or cells exposed to changes in environmental conditions.In this chapter, we describe the preparation of Bacillus subtilis cells, the recording of movies of those cells expressing a monomeric variant of a yellow fluorescent protein (mNeonGreen) fused to a protein of choice, and the subsequent curation of the movie data including the statistical analysis of the protein dynamics. We present a short overview of the analysis program SMTracker 2.0, highlighting its ability to analyze SMT data by non-expert scientists.

Discovery and Quantitative Dissection of Cytokinesis Mechanisms Using Dictyostelium discoideum.

The social amoeba Dictyostelium discoideum is a versatile model for understanding many different cellular processes involving cell motility including chemotaxis, phagocytosis, and cytokinesis. Cytokinesis, in particular, is a model cell-shaped change process in which a cell separates into two daughter cells. D. discoideum has been used extensively to identify players in cytokinesis and understand how they comprise the mechanosensory and biochemical pathways of cytokinesis. In this chapter, we describe how we use cDNA library complementation with D. discoideum to discover potential regulators of cytokinesis. Once identified, these regulators are further analyzed through live cell imaging, immunofluorescence imaging, fluorescence correlation and cross-correlation spectroscopy, micropipette aspiration, and fluorescence recovery after photobleaching. Collectively, these methods aid in detailing the mechanisms and signaling pathways that comprise cell division.

Probing conformational dynamics of DNA binding by CO-sensing transcription factor, CooA.

The transcription factor CooA is a CRP/FNR (cAMP receptor protein/ fumarate and nitrate reductase) superfamily protein that uses heme to sense carbon monoxide (CO). Allosteric activation of CooA in response to CO binding is currently described as a series of discrete structural changes, without much consideration for the potential role of protein dynamics in the process of DNA binding. This work uses site-directed spin-label electron paramagnetic resonance spectroscopy (SDSL-EPR) to probe slow timescale (µs-ms) conformational dynamics of CooA with a redox-stable nitroxide spin label, and IR spectroscopy to probe the environment at the CO-bound heme. A series of cysteine substitution variants were created to selectively label CooA in key functional regions, the heme-binding domain, the 4/5-loop, the hinge region, and the DNA binding domain. The EPR spectra of labeled CooA variants are compared across three functional states: Fe(III) "locked off", Fe(II)-CO "on", and Fe(II)-CO bound to DNA. We observe changes in the multicomponent EPR spectra at each location; most notably in the hinge region and DNA binding domain, broadening the description of the CooA allosteric mechanism to include the role of protein dynamics in DNA binding. DNA-dependent changes in IR vibrational frequency and band broadening further suggest that there is conformational heterogeneity in the active WT protein and that DNA binding alters the environment of the heme-bound CO.

Real-Time Measurement of a Weak Interaction of a Transcription Factor Motif with a Protein Hub at Single-Molecule Precision.

Transcription factors often interact with other protein cofactors, regulating gene expression. Direct detection of these brief events using existing technologies remains challenging due to their transient nature. In addition, intrinsically disordered domains, intranuclear location, and lack of cofactor-dependent active sites of transcription factors further complicate the quantitative analysis of these critical processes. Here, we create a genetically encoded label-free sensor to identify the interaction between a motif of the MYC transcription factor, a primary cancer driver, and WDR5, a chromatin-associated protein hub. Using an engineered nanopore equipped with this motif, WDR5 is probed through reversible captures and releases in a one-by-one and time-resolved fashion. Our single-molecule kinetic measurements indicate a weak-affinity interaction arising from a relatively slow complex association and a fast dissociation of WDR5 from the tethered motif. Further, we validate this subtle interaction by determinations in an ensemble using single nanodisc-wrapped nanopores immobilized on a biolayer interferometry sensor. This study also provides the proof-of-concept for a sensor that reveals unique recognition signatures of different protein binding sites. Our foundational work may be further developed to produce sensing elements for analytical proteomics and cancer nanomedicine.

NMR Dynamic View of the Destabilization of WW4 Domain by Chaotropic GdmCl and NaSCN.

GdmCl and NaSCN are two strong chaotropic salts commonly used in protein folding and stability studies, but their microscopic mechanisms remain enigmatic. Here, by CD and NMR, we investigated their effects on conformations, stability, binding and backbone dynamics on ps-ns and µs-ms time scales of a 39-residue but well-folded WW4 domain at salt concentrations ≤200 mM. Up to 200 mM, both denaturants did not alter the tertiary packing of WW4, but GdmCl exerted more severe destabilization than NaSCN. Intriguingly, GdmCl had only weak binding to amide protons, while NaSCN showed extensive binding to both hydrophobic side chains and amide protons. Neither denaturant significantly affected the overall ps-ns backbone dynamics, but they distinctively altered µs-ms backbone dynamics. This study unveils that GdmCl and NaSCN destabilize a protein before the global unfolding occurs with differential binding properties and µs-ms backbone dynamics, implying the absence of a simple correlation between thermodynamic stability and backbone dynamics of WW4 at both ps-ns and µs-ms time scales.

Investigating how HIV-1 antiretrovirals differentially behave as substrates and inhibitors of P-glycoprotein via molecular dynamics simulations.

HIV-1 can rapidly infect the brain upon initial infection, establishing latent reservoirs that induce neuronal damage and/or death, resulting in HIV-Associated Neurocognitive Disorder. Though anti-HIV-1 antiretrovirals (ARVs) suppress viral load, the blood-brain barrier limits drug access to the brain, largely because of highly expressed efflux proteins like P-glycoprotein (P-gp). While no FDA-approved P-gp inhibitor currently exists, HIV-1 protease inhibitors show promise as partial P-gp inhibitors, potentially enhancing drug delivery to the brain. Herein, we employed docking and molecular dynamics simulations to elucidate key differences in P-gp's interactions with several antiretrovirals, including protease inhibitors, with known inhibitory or substrate-like behaviors towards P-gp. Our results led us to hypothesize new mechanistic details of small-molecule efflux by and inhibition of P-gp, where the "Lower Pocket" in P-gp's transmembrane domain serves as the primary initial site for small-molecule binding. Subsequently, this pocket merges with the more traditionally studied drug binding site-the "Upper Pocket"-thus funneling small-molecule drugs, such as ARVs, towards the Upper Pocket for efflux. Furthermore, our results reinforce the understanding that both binding energetics and changes in protein dynamics are crucial in discerning small molecules as non-substrates, substrates, or inhibitors of P-gp. Our findings indicate that interactions between P-gp and inhibitory ARVs induce bridging of transmembrane domain helices, impeding P-gp conformational changes and contributing to the inhibitory behavior of these ARVs. Overall, insights gained in this study could serve to guide the design of future P-gp-targeting therapeutics for a wide range of pathological conditions and diseases, including HIV-1.

Martini 3 Coarse-Grained Model for the Cofactors Involved in Photosynthesis.

As a critical step in advancing the simulation of photosynthetic complexes, we present the Martini 3 coarse-grained (CG) models of key cofactors associated with light harvesting (LHCII) proteins and the photosystem II (PSII) core complex. Our work focuses on the parametrization of beta-carotene, plastoquinone/quinol, violaxanthin, lutein, neoxanthin, chlorophyll A, chlorophyll B, and heme. We derived the CG parameters to match the all-atom reference simulations, while structural and thermodynamic properties of the cofactors were compared to experimental values when available. To further assess the reliability of the parameterization, we tested the behavior of these cofactors within their physiological environments, specifically in a lipid bilayer and bound to photosynthetic complexes. The results demonstrate that our CG models maintain the essential features required for realistic simulations. This work lays the groundwork for detailed simulations of the PSII-LHCII super-complex, providing a robust parameter set for future studies.

Raman Spectroscopy Reveals Photobiomodulation-Induced α-Helix to ß-Sheet Transition in Tubulins: Potential Implications for Alzheimer's and Other Neurodegenerative Diseases.

In small clinical studies, the application of transcranial photobiomodulation (PBM), which typically delivers low-intensity near-infrared (NIR) to treat the brain, has led to some remarkable results in the treatment of dementia and several neurodegenerative diseases. However, despite the extensive literature detailing the mechanisms of action underlying PBM outcomes, the specific mechanisms affecting neurodegenerative diseases are not entirely clear. While large clinical trials are warranted to validate these findings, evidence of the mechanisms can explain and thus provide credible support for PBM as a potential treatment for these diseases. Tubulin and its polymerized state of microtubules have been known to play important roles in the pathology of Alzheimer's and other neurodegenerative diseases. Thus, we investigated the effects of PBM on these cellular structures in the quest for insights into the underlying therapeutic mechanisms. In this study, we employed a Raman spectroscopic analysis of the amide I band of polymerized samples of tubulin exposed to pulsed low-intensity NIR radiation (810 nm, 10 Hz, 22.5 J/cm2 dose). Peaks in the Raman fingerprint region (300-1900 cm-1)-in particular, in the amide I band (1600-1700 cm-1)-were used to quantify the percentage of protein secondary structures. Under this band, hidden signals of C=O stretching, belonging to different structures, are superimposed, producing a complex signal as a result. An accurate decomposition of the amide I band is therefore required for the reliable analysis of the conformation of proteins, which we achieved through a straightforward method employing a Voigt profile. This approach was validated through secondary structure analyses of unexposed control samples, for which comparisons with other values available in the literature could be conducted. Subsequently, using this validated method, we present novel findings of statistically significant alterations in the secondary structures of polymerized NIR-exposed tubulin, characterized by a notable decrease in α-helix content and a concurrent increase in ß-sheets compared to the control samples. This PBM-induced α-helix to ß-sheet transition connects to reduced microtubule stability and the introduction of dynamism to allow for the remodeling and, consequently, refreshing of microtubule structures. This newly discovered mechanism could have implications for reducing the risks associated with brain aging, including neurodegenerative diseases like Alzheimer's disease, through the introduction of an intervention following this transition.

Automated multiconformer model building for X-ray crystallography and cryo-EM.

In their folded state, biomolecules exchange between multiple conformational states that are crucial for their function. Traditional structural biology methods, such as X-ray crystallography and cryogenic electron microscopy (cryo-EM), produce density maps that are ensemble averages, reflecting molecules in various conformations. Yet, most models derived from these maps explicitly represent only a single conformation, overlooking the complexity of biomolecular structures. To accurately reflect the diversity of biomolecular forms, there is a pressing need to shift toward modeling structural ensembles that mirror the experimental data. However, the challenge of distinguishing signal from noise complicates manual efforts to create these models. In response, we introduce the latest enhancements to qFit, an automated computational strategy designed to incorporate protein conformational heterogeneity into models built into density maps. These algorithmic improvements in qFit are substantiated by superior Rfree and geometry metrics across a wide range of proteins. Importantly, unlike more complex multicopy ensemble models, the multiconformer models produced by qFit can be manually modified in most major model building software (e.g., Coot) and fit can be further improved by refinement using standard pipelines (e.g., Phenix, Refmac, Buster). By reducing the barrier of creating multiconformer models, qFit can foster the development of new hypotheses about the relationship between macromolecular conformational dynamics and function.

Transient Structural Properties of the Rho GDP-Dissociation Inhibitor.

Rho GTPases, master spatial regulators of a wide range of cellular processes, are orchestrated by complex formation with guanine nucleotide dissociation inhibitors (RhoGDIs). These have been thought to possess an unstructured N-terminus that inhibits nucleotide exchange of their client upon binding/folding. Via NMR analyses, molecular dynamics simulations, and biochemical assays, we reveal instead pertinent structural properties transiently maintained both, in the presence and absence of the client, imposed onto the terminus context-specifically by modulating interactions with the surface of the folded C-terminal domain. These observations revise the long-standing textbook picture of the GTPases' mechanism of membrane extraction. Rather than by a disorder-to-order transition upon binding of an inhibitory peptide, the intricate and highly selective extraction process of RhoGTPases is orchestrated via a dynamic ensemble bearing preformed transient structural properties, suitably modulated by the specific surrounding along the multi-step process.

Theory vs. experiment: The rise of the dynamic view of proteins.

Over the past century, the scientific conception of the protein has evolved significantly. This paper focuses on the most recent stage of this evolution, namely, the origin of the dynamic view of proteins and the challenge it posed to the static view of classical molecular biology. Philosophers and scientists have offered two hypotheses to explain the origin of the dynamic view and its slow reception by structural biologists. Some have argued that the shift from the static to the dynamic view was a Kuhnian revolution, driven by the accumulation of dynamic anomalies, while others have argued that the shift was caused by new empirical findings made possible by technological advances. I analyze this scientific episode and ultimately reject both of these empiricist accounts. I argue that focusing primarily on technological advances and empirical discoveries overlooks the important role of theory in driving this scientific change. I show how the application of general thermodynamic principles to proteins gave rise to the dynamic view, and a commitment to these principles then led early adopters to seek out the empirical examples of protein dynamics, which would eventually convince their peers. My analysis of this historical case shows that empiricist accounts of modern scientific progress-at least those that aim to explain developments in the molecular life sciences-need to be tempered in order to capture the interplay between theory and experiment.