Protein activity regulation by conformational entropy

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.

Role of Associated Water Dynamics on Protein Stability and Activity in Crowded Milieu

Macromolecular crowding bridges in vivo and in vitro studies by simulating cellular complexities such as high viscosity and limited space while maintaining the experimental feasibility. Over the last two decades, the impact of macromolecular crowding on protein stability and activity has been a significant topic of study and discussion, though still lacking a thorough mechanistic understanding. This article investigates the role of associated water dynamics on protein stability and activity within crowded environments, using bromelain and Ficoll-70 as the model systems. Traditional crowding theory primarily attributes protein stability to entropic effects (excluded volume) and enthalpic interactions. However, our recent findings suggest that water structure modulation plays a crucial role in a crowded environment. In this report, we strengthen the conclusion of our previous study, i.e., rigid-associated water stabilizes proteins via entropy and destabilizes them via enthalpy, while flexible water has the opposite effect. In the process, we addressed previous shortcomings with a systematic concentration-dependent study using a single-domain protein and component analysis of solvation dynamics. More importantly, we analyze bromelain's hydrolytic activity using the Michaelis-Menten model to understand kinetic parameters like maximum velocity (Vmax) achieved by the system and the Michaelis-Menten coefficient (KM). Results indicate that microviscosity (not the bulk viscosity) controls the enzyme-substrate (ES) complex formation, where an increase in the microviscosity makes the ES complex formation less favorable. On the other hand, flexible associated water dynamics were found to favor the rate of product formation significantly from the ES complex, while rigid associated water hinders it. This study improves our understanding of protein stability and activity in crowded environments, highlighting the critical role of associated water dynamics.

AAontology: An ontology of amino acid scales for interpretable machine learning

Amino acid scales are crucial for protein prediction tasks, many of them being curated in the AAindex database. Despite various clustering attempts to organize them and to better understand their relationships, these approaches lack the fine-grained classification necessary for satisfactory interpretability in many protein prediction problems. To address this issue, we developed AAontology-a two-level classification for 586 amino acid scales (mainly from AAindex) together with an in-depth analysis of their relations-using bag-of-word-based classification, clustering, and manual refinement over multiple iterations. AAontology organizes physicochemical scales into 8 categories and 67 subcategories, enhancing the interpretability of scale-based machine learning methods in protein bioinformatics. Thereby it enables researchers to gain a deeper biological insight. We anticipate that AAontology will be a building block to link amino acid properties with protein function and dysfunctions as well as aid informed decision-making in mutation analysis or protein drug design.

Entropy drives the ligand recognition in G-protein-coupled receptor subtypes

Achieving ligand subtype selectivity within highly homologous subtypes of G-protein-coupled receptor (GPCR) is critical yet challenging for GPCR drug discovery, primarily due to the unclear mechanism underlying ligand subtype selectivity, which hampers the rational design of subtype-selective ligands. Herein, we disclose an unusual molecular mechanism of entropy-driven ligand recognition in cannabinoid (CB) receptor subtypes, revealed through atomic-level molecular dynamics simulations, cryoelectron microscopy structure, and mutagenesis experiments. This mechanism is attributed to the distinct conformational dynamics of the receptor's orthosteric pocket, leading to variations in ligand binding entropy and consequently, differential binding affinities, which culminate in specific ligand recognition. We experimentally validated this mechanism and leveraged it to design ligands with enhanced or ablated subtype selectivity. One such ligand demonstrated favorable pharmacokinetic properties and significant efficacy in rodent inflammatory analgesic models. More importantly, it is precisely due to the high subtype selectivity obtained based on this mechanism that this ligand does not show addictive properties in animal models. Our findings elucidate the unconventional role of entropy in CB receptor subtype selectivity and suggest a strategy for rational design of ligands to achieve entropy-driven subtype selectivity for many pharmaceutically important GPCRs.

Glycosylation and charge distribution orchestrates the conformational ensembles of a biotechnologically promissory phytase in different pHs - a computational study

Phytases [myo-inositol(1,2,3,4,5,6) hexakisphosphate phosphohydrolases] are phytate-specific phosphatases not present in monogastric animals. Nevertheless, they are an essential supplement to feeding such animals and for human special diets. It is crucial, hence, the biotechnological use of phytases with intrinsic stability and activity at the acid pHs from gastric environments. Here we use Metadynamics (METADY) simulations to probe the conformational space of the Aspergillus nidulans phytase and the differential effects of pH and glycosylation in this same space. The results suggest that strategic combinations of pH and glycosylation affect the stability of native-like conformations and alternate these structures from a metastable to a stable profile. Furthermore, the protein segments previously reported as more thermosensitive in phytases from this family present a pivotal role in the conformational changes at different conditions, especially H2, H5-7, L8, L10, L12, and L17. Also, the glycosylations and the pH-dependent charge balance modulate the mobility and interactions at these same regions, with consequences for the surface solvation and active site exposition. Finally, although the glycosylations have stabilized the native structure and improved the substrate docking at all the studied pHs, the data suggest a higher phytate receptivity at catalytic poses for the unglycosylated structure at pH 6.5 and the glycosylated one at pH 4.5. This behavior agrees with the exact change in optimum pH reported for this enzyme, expressed on low or high glycosylating systems. We hope the results and insights presented here will be helpful in future approaches for rational engineering of technologically promising phytases and intelligent planning of their heterologous expression systems and conditions for use.Communicated by Ramaswamy H. Sarma.

Cyclization of ubiquitin chains reinforces their recognition by ZNF216

Lys48-linked ubiquitin chains, regulating proteasomal protein degradation, are known to include cyclized forms. This cyclization hinders recognition by many downstream proteins by occluding the Ile44-centered patch. In contrast, the A20-like Znf domain of ZNF216 (a ubiquitin-binding protein, A20 Znf) is expected to bind to cyclic ubiquitin chains via constitutively solvent-exposed surfaces. However, the underlying interaction mechanism remains unclear. Here, our ITC and NMR experiments collectively showed that cyclization did not interfere with and even slightly enhance the molecular recognition of diubiquitin by A20 Znf. This effect is explained by the cyclization-induced repression of conformational dynamics in diubiquitin and an enlarged molecular interface in the complex. Thus, these results suggest that cyclic ubiquitin chains can be involved in regulation of ZNF216-dependent proteasomal protein degradation.

A parameterized two-domain thermodynamic model explains diverse mutational effects on protein allostery

New experimental findings continue to challenge our understanding of protein allostery. Recent deep mutational scanning study showed that allosteric hotspots in the tetracycline repressor (TetR) and its homologous transcriptional factors are broadly distributed rather than spanning well-defined structural pathways as often assumed. Moreover, hotspot mutation-induced allostery loss was rescued by distributed additional mutations in a degenerate fashion. Here, we develop a two-domain thermodynamic model for TetR, which readily rationalizes these intriguing observations. The model accurately captures the in vivo activities of various mutants with changes in physically transparent parameters, allowing the data-based quantification of mutational effects using statistical inference. Our analysis reveals the intrinsic connection of intra- and inter-domain properties for allosteric regulation and illustrate epistatic interactions that are consistent with structural features of the protein. The insights gained from this study into the nature of two-domain allostery are expected to have broader implications for other multi-domain allosteric proteins.

Fast collective motions of backbone in transmembrane α helices are critical to water transfer of aquaporin

Fast collective motions are widely present in biomolecules, but their functional relevance remains unclear. Herein, we reveal that fast collective motions of backbone are critical to the water transfer of aquaporin Z (AqpZ) by using solid-state nuclear magnetic resonance (ssNMR) spectroscopy and molecular dynamics (MD) simulations. A total of 212 residue site-specific dipolar order parameters and 158 15N spin relaxation rates of the backbone are measured by combining the 13C- and 1H-detected multidimensional ssNMR spectra. Analysis of these experimental data by theoretic models suggests that the small-amplitude (~10°) collective motions of the transmembrane α helices on the nanosecond-to-microsecond timescales are dominant for the dynamics of AqpZ. The MD simulations demonstrate that these collective motions are critical to the water transfer efficiency of AqpZ by facilitating the opening of the channel and accelerating the water-residue hydrogen bonds renewing in the selectivity filter region.

Lowering Entropic Barriers in Triplex DNA Switches Facilitating Biomedical Applications at Physiological pH

Triplex DNA switches are attractive allosteric tools for engineering smart nanodevices, but their poor triplex-forming capacity at physiological conditions limited the practical applications. To address this challenge, we proposed a low-entropy barrier design to facilitate triplex formation by introducing a hairpin duplex linker into the triplex motif, and the resulting triplex switch was termed as CTNSds. Compared to the conventional clamp-like triplex switch, CTNSds increased the triplex-forming ratio from 30 % to 91 % at pH 7.4 and stabilized the triple-helix structure in FBS and cell lysate. CTNSds was also less sensitive to free-energy disturbances, such as lengthening linkers or mismatches in the triple-helix stem. The CTNSds design was utilized to reversibly isolate CTCs from whole blood, achieving high capture efficiencies (>86 %) at pH 7.4 and release efficiencies (>80 %) at pH 8.0. Our approach broadens the potential applications of DNA switches-based switchable nanodevices, showing great promise in biosensing and biomedicine.

The immune checkpoint receptor LAG3: Structure, function, and target for cancer immunotherapy

Lymphocyte activation gene 3 protein (LAG3) is an immune checkpoint receptor that is highly upregulated on exhausted T cells in the tumor microenvironment. LAG3 transmits inhibitory signals to T cells upon binding to MHC class II and other ligands, rendering T cells dysfunctional. Consequently, LAG3 is a major target for cancer immunotherapy with many anti-LAG3 monoclonal antibodies (mAbs) that block LAG3 inhibitory activity in clinical trials. In this review, we examine the molecular basis for LAG3 function in light of recently determined crystal and cryoEM structures of this inhibitory receptor. We review what is known about LAG3 interactions with MHC class II, its canonical ligand, and the newly discovered ligands FGL1 and the T cell receptor (TCR)-CD3 complex, including current controversies over the relative importance of these ligands. We then address the development and mechanisms of action of anti-LAG3 mAbs in clinical trials for cancer immunotherapy. We discuss new strategies to therapeutically target LAG3 using mAbs that not only block the LAG3-MHC class II interaction, but also LAG3 interactions with FGL1 or TCR-CD3, or that disrupt LAG3 dimerization. Finally, we assess the possibility of developing mAbs that enhance, rather than block, LAG3 inhibitory activity as treatments for autoimmune diseases.

Sorting drug conformers in enzyme active sites: the XTB way

In the present study, we have used the MEI196 set of interaction energies to investigate low-cost computational chemistry approaches for the calculation of binding between a molecule and its environment. Density functional theory (DFT) methods, when used with the vDZP basis set, yield good agreement with the reference energies. On the other hand, semi-empirical methods are less accurate as expected. By examining different groups of systems within MEI196 that contain species of a similar nature, we find that chemical similarity leads to cancellation of errors in the calculation of relative binding energies. Importantly, the semi-empirical method GFN1-xTB (XTB1) yields reasonable results for this purpose. We have thus further assessed the performance of XTB1 for calculating relative energies of docking poses of substrates in enzyme active sites represented by cluster models or within the ONIOM protocol. The results support the observations on error cancellation. This paves the way for the use of XTB1 in parts of large-scale virtual screening workflows to accelerate the drug discovery process.

Nanotoxicity of two-dimensional nanomaterials on human skin and the structural evolution of keratin protein

Two-dimensional (2D) materials have been increasingly widely used in biomedical and cosmetical products nowadays, yet their safe usage in human body and environment necessitates a comprehensive understanding of their nanotoxicity. In this work, the effect of pristine graphene and graphene oxide (GO) on the adsorption and conformational changes of skin keratin using molecular dynamics simulations. It is found that skin keratin can be absorbed through various noncovalent driving forces, such as van der Waals (vdW) and electrostatics. In the case of GO, the oxygen-containing groups prevent tighter contact between skin keratin and the graphene basal plane through steric effects and electrostatic repulsion. On the other hand, electrostatic attraction and hydrogen bonding enhance their binding affinity to positively charged residues such as lysine and arginine. The secondary structure of skin keratin is better preserved in GO system, suggesting that GO has good biocompatibility. The charged groups on GO surface perform as the hydrogen bond acceptors, which is like to the natural receptors of keratin in this physiological environment. This work contributes to a better knowledge of the nanotoxicity of cutting-edge 2D materials on human health, thereby advancing their potential biological applications.

A parametrized two-domain thermodynamic model explains diverse mutational effects on protein allostery

New experimental findings continue to challenge our understanding of protein allostery. Recent deep mutational scanning study showed that allosteric hotspots in the tetracycline repressor (TetR) and its homologous transcriptional factors are broadly distributed rather than spanning well-defined structural pathways as often assumed. Moreover, hotspot mutation-induced allostery loss was rescued by distributed additional mutations in a degenerate fashion. Here, we develop a two-domain thermodynamic model for TetR, which readily rationalizes these intriguing observations. The model accurately captures the in vivo activities of various mutants with changes in physically transparent parameters, allowing the data-based quantification of mutational effects using statistical inference. Our analysis reveals the intrinsic connection of intra- and inter-domain properties for allosteric regulation and illustrate epistatic interactions that are consistent with structural features of the protein. The insights gained from this study into the nature of two-domain allostery are expected to have broader implications for other multidomain allosteric proteins.

Double and triple thermodynamic mutant cycles reveal the basis for specific MsbA-lipid interactions

Structural and functional studies of the ATP-binding cassette transporter MsbA have revealed two distinct lipopolysaccharide (LPS) binding sites: one located in the central cavity and the other at a membrane-facing, exterior site. Although these binding sites are known to be important for MsbA function, the thermodynamic basis for these specific MsbA-LPS interactions is not well understood. Here, we use native mass spectrometry to determine the thermodynamics of MsbA interacting with the LPS-precursor 3-deoxy-D-manno-oct-2-ulosonic acid (Kdo)2-lipid A (KDL). The binding of KDL is solely driven by entropy, despite the transporter adopting an inward-facing conformation or trapped in an outward-facing conformation with adenosine 5'-diphosphate and vanadate. An extension of the mutant cycle approach is employed to probe basic residues that interact with KDL. We find the molecular recognition of KDL is driven by a positive coupling entropy (as large as -100 kJ/mol at 298 K) that outweighs unfavorable coupling enthalpy. These findings indicate that alterations in solvent reorganization and conformational entropy can contribute significantly to the free energy of protein-lipid association. The results presented herein showcase the advantage of native MS to obtain thermodynamic insight into protein-lipid interactions that would otherwise be intractable using traditional approaches, and this enabling technology will be instrumental in the life sciences and drug discovery.

All over or overall - Do we understand allostery?

Allostery is probably the most important concept in the regulation of cellular processes. Models to explain allostery are plenty. Each sheds light on different aspects but their entirety conveys an ambiguous feeling of comprehension and disappointment. Here, I discuss the most popular allostery models, their roots, similarities, and limitations. All of them are thermodynamic models. Naturally this bears a certain degree of redundancy, which forms the center of this review. After sixty years, many questions remain unanswered, mainly because our human longing for causality as base for understanding is not satisfied by thermodynamics alone. A description of allostery in terms of pathways, i.e., as a temporal chain of events, has been-, and still is-, a missing piece of the puzzle.

Double and triple thermodynamic mutant cycles reveal the basis for specific MsbA-lipid interactions

Structural and functional studies of the ATP-binding cassette transporter MsbA have revealed two distinct lipopolysaccharide (LPS) binding sites: one located in the central cavity and the other at a membrane-facing, exterior site. Although these binding sites are known to be important for MsbA function, the thermodynamic basis for these specific MsbA-LPS interactions is not well understood. Here, we use native mass spectrometry to determine the thermodynamics of MsbA interacting with the LPS-precursor 3-deoxy-D-manno-oct-2-ulosonic acid (Kdo)2-lipid A (KDL). The binding of KDL is solely driven by entropy, despite the transporter adopting an inward-facing conformation or trapped in an outward-facing conformation with adenosine 5'-diphosphate and vanadate. An extension of the mutant cycle approach is employed to probe basic residues that interact with KDL. We find the molecular recognition of KDL is driven by a positive coupling entropy (as large as -100 kJ/mol at 298K) that outweighs unfavorable coupling enthalpy. These findings indicate that alterations in solvent reorganization and conformational entropy can contribute significantly to the free energy of protein-lipid association. The results presented herein showcase the advantage of native MS to obtain thermodynamic insight into protein-lipid interactions that would otherwise be intractable using traditional approaches, and this enabling technology will be instrumental in the life sciences and drug discovery.

Allosteric modulation of SHP2: Quest from known to unknown

Src homology-2 domain-containing protein tyrosine phosphatase-2 (SHP2) is a key regulatory factor in the cell cycle and its activating mutations play an important role in the development of various cancers, making it an important target for antitumor drugs. Due to the highly conserved amino acid sequence and positively charged nature of the active site of SHP2, it is difficult to discover inhibitors with high affinity for the catalytic site of SHP2 and sufficient cell permeability, making it considered an "undruggable" target. However, the discovery of allosteric regulation mechanisms provides new opportunities for transforming undruggable targets into druggable ones. Given the limitations of orthosteric inhibitors, SHP2 allosteric inhibitors have become a more selective and safer research direction. In this review, we elucidate the oncogenic mechanism of SHP2 and summarize the discovery methods of SHP2 allosteric inhibitors, providing new strategies for the design and improvement of SHP2 allosteric inhibitors.

Influence of metal binding on the conformational landscape of neurofilament peptides

In order to understand the preferred modes of chelation in metal-binding peptides, quantum mechanical calculations can be used to compute energies, resulting in a hierarchy of binding affinities. These calculations often produce increasing stabilization energies the higher the coordination of the complex. However, as the coordination of a metal increases, the conformational freedom of the polypeptide chain is inevitably reduced, resulting in an entropic penalty. Estimating the magnitude of this penalty from the many different degrees of freedom of biomolecular systems is very challenging, and as a result this contribution to the free energy is often ignored. Here we explore this problem focusing on a family of phosphorylated neuropeptides that bind to aluminum. We find that there is a general negative correlation between both stabilization energy and entropy. Our results suggest that a subtle interplay between enthalpic and entropic forces will determine the population of the most favourable species. Additionally, we discuss the requirements for a possible "Metal Ion Hypothesis" based on our findings.

Kinetic and thermodynamic allostery in the Ras protein family

Allostery, the transfer of information between distant parts of a macromolecule, is a fundamental feature of protein function and regulation. However, allosteric mechanisms are usually not explained by protein structure, requiring information on correlated fluctuations uniquely accessible to molecular simulation. Existing work to extract allosteric pathways from molecular dynamics simulations has focused on thermodynamic correlations. Here, we show how kinetic correlations encode complementary information essential to explain observed variations in allosteric regulation. We applied kinetic and thermodynamic correlation analysis on atomistic simulations of H, K, and NRas isoforms in the apo, GTP, and GDP-bound states of Ras protein, with and without complexing to its downstream effector, Raf. We show that switch I and switch II are the primary components of thermodynamic and kinetic allosteric networks, consistent with the key roles of these two motifs. These networks connect the switches to an allosteric loop recently discovered from a crystal structure of HRas. This allosteric loop is inactive in KRas, but is coupled to the hydrolysis arm switch II in NRas and HRas. We find that the mechanism in the latter two isoforms are thermodynamic and kinetic, respectively. Binding of Raf-RBD further activates thermodynamic allostery in HRas and KRas but has limited effect on NRas. These results indicate that kinetic and thermodynamic correlations are both needed to explain protein function and allostery. These two distinct channels of allosteric regulation, and their combinatorial variability, may explain how subtle mutational differences can lead to diverse regulatory profiles among enzymatic proteins.

Decoding the dual recognition mechanism of the glucocorticoid receptor for DNA and RNA: sequence versus shape

Transcription factors (TFs) regulate eukaryotic transcription through selective DNA-binding, can also specifically interact with RNA, which may present another layer of transcriptional control. The mechanisms of the TFs-DNA recognition are often well-characterised, while the details of TFs-RNA complexation are less understood. Here we investigate the dual recognition mechanism of the glucocorticoid receptor (GR), which interacts with similar affinities with consensus DNA and diverse RNA hairpin motifs but discriminates against uniform dsRNA. Using atomic molecular dynamics simulations, we demonstrate that the GR binding to nucleic acids requires a wide and shallow groove pocket. The protein effectively moulds its binding site within DNA major groove, which enables base-specific interactions. Contrary, the GR binding has little effect on the grooves geometry of RNA systems, most notably in uniform dsRNA. Instead, a hairpin motif in RNA yields a wide and shallow major groove pocket, allowing the protein to anchor itself through nonspecific electrostatic contacts with RNA backbone. Addition of a bulge increases RNA hairpin flexibility, which leads to a greater number of GR-RNA contacts and, thus, higher affinity. Thus, the combination of structural motifs defines the GR-RNA selective binding: a recognition mechanism, which may be shared by other zinc finger TFs.

Mixed, nonclassical behavior in a classic allosteric protein

Allostery is a major driver of biological processes requiring coordination. Thus, it is one of the most fundamental and remarkable phenomena in nature, and there is motivation to understand and manipulate it to a multitude of ends. Today, it is often described in terms of two phenomenological models proposed more than a half-century ago involving only T(tense) or R(relaxed) conformations. Here, methyl-based NMR provides extensive detail on a dynamic T to R switch in the classical dimeric allosteric protein, yeast chorismate mutase (CM), that occurs in the absence of substrate, but only with the activator bound. Switching of individual subunits is uncoupled based on direct observation of mixed TR states in the dimer. This unique finding excludes both classic models and solves the paradox of a coexisting hyperbolic binding curve and highly skewed substrate-free T-R equilibrium. Surprisingly, structures of the activator-bound and effector-free forms of CM appear the same by NMR, providing another example of the need to account for dynamic ensembles. The apo enzyme, which has a sigmoidal activity profile, is shown to switch, not to R, but to a related high-energy state. Thus, the conformational repertoire of CM does not just change as a matter of degree depending on the allosteric input, be it effector and/or substrate. Rather, the allosteric model appears to completely change in different contexts, which is only consistent with modern ensemble-based frameworks.

Hydrogen-Atom Tunneling in a Homochiral Environment

The role-exchanging concerted torsional motion of two hydrogen atoms in the homochiral dimer of trans-1,2-cyclohexanediol was characterized through a combination of broadband rotational spectroscopy and theoretical modeling. The results reveal that the concerted tunneling motion of the hydrogen atoms leads to the inversion of the sign of the dipole moment components along the a and b principal axes, due to the interchange motion that cooperatively breaks and reforms one intermolecular hydrogen bond. This motion is also coupled with two acceptor switching motions. The energy difference between the two ground vibrational states arising from this tunneling motion was determined to be 29.003(2) MHz. The corresponding wavefunctions suggest that the two hydrogen atoms are evenly delocalized on two equivalent potential wells, which differs from the heterochiral case where the hydrogen atoms are confined in separate wells, as the permutation-inversion symmetry breaks down. This intriguing contrast in hydrogen-atom behavior between homochiral and heterochiral environments could further illuminate our understanding of the role of chirality in intermolecular interactions and dynamics.

Heterogeneity in M. tuberculosis β-lactamase inhibition by Sulbactam

For decades, researchers have elucidated essential enzymatic functions on the atomic length scale by tracing atomic positions in real-time. Our work builds on possibilities unleashed by mix-and-inject serial crystallography (MISC) at X-ray free electron laser facilities. In this approach, enzymatic reactions are triggered by mixing substrate or ligand solutions with enzyme microcrystals. Here, we report in atomic detail (between 2.2 and 2.7 Å resolution) by room-temperature, time-resolved crystallography with millisecond time-resolution (with timepoints between 3 ms and 700 ms) how the Mycobacterium tuberculosis enzyme BlaC is inhibited by sulbactam (SUB). Our results reveal ligand binding heterogeneity, ligand gating, cooperativity, induced fit, and conformational selection all from the same set of MISC data, detailing how SUB approaches the catalytic clefts and binds to the enzyme noncovalently before reacting to a trans-enamine. This was made possible in part by the application of singular value decomposition to the MISC data using a program that remains functional even if unit cell parameters change up to 3 Å during the reaction.

NMR Shows Why a Small Chemical Change Almost Abolishes the Antimicrobial Activity of Glycocin F

Glycocin F (GccF), a ribosomally synthesized, post-translationally modified peptide secreted by Lactobacillus plantarum KW30, rapidly inhibits the growth of susceptible bacteria at nanomolar concentrations. Previous studies have highlighted structural features important for its activity and have shown the absolute requirement for the Ser18 O-linked GlcNAc on the eight-residue loop linking the two short helices of the (C-X6-C)2 structure. Here, we show that an ostensibly very small chemical modification to Ser18, the substitution of the Cα proton with a methyl group, reduces the antimicrobial activity of GccF 1000-fold (IC50 1.5 μM cf. 1.5 nM). A comparison of the GccFα-methylSer18 NMR structure (PDB 8DFZ) with that of the native protein (PDB 2KUY) showed a marked difference in the orientation and mobility of the loop, as well as a markedly different positioning of the GlcNAc, suggesting that loop conformation, dynamics, and glycan presentation play an important role in the interaction of GccF with as yet unknown but essential physiological target molecules.

New Insights into the Cooperativity and Dynamics of Dimeric Enzymes

A survey of protein databases indicates that the majority of enzymes exist in oligomeric forms, with about half of those found in the UniProt database being homodimeric. Understanding why many enzymes are in their dimeric form is imperative. Recent developments in experimental and computational techniques have allowed for a deeper comprehension of the cooperative interactions between the subunits of dimeric enzymes. This review aims to succinctly summarize these recent advancements by providing an overview of experimental and theoretical methods, as well as an understanding of cooperativity in substrate binding and the molecular mechanisms of cooperative catalysis within homodimeric enzymes. Focus is set upon the beneficial effects of dimerization and cooperative catalysis. These advancements not only provide essential case studies and theoretical support for comprehending dimeric enzyme catalysis but also serve as a foundation for designing highly efficient catalysts, such as dimeric organic catalysts. Moreover, these developments have significant implications for drug design, as exemplified by Paxlovid, which was designed for the homodimeric main protease of SARS-CoV-2.

Using Implicit-Solvent Potentials to Extract Water Contributions to Enthalpy-Entropy Compensation in Biomolecular Associations

Biomolecular assembly typically exhibits enthalpy-entropy compensation (EEC) behavior whose molecular origin remains a long-standing puzzle. While water restructuring is believed to play an important role in EEC, its contribution to the entropy and enthalpy changes, and how these changes relate to EEC, remains poorly understood. Here, we show that water reorganization entropy/enthalpy can be obtained by exploiting the temperature dependence in effective, implicit-solvent potentials. We find that the different temperature dependencies in the hydrophobic interaction, rooted in water reorganization, result in substantial variations in the entropy/enthalpy change, which are responsible for EEC. For lower-critical-solution-temperature association, water reorganization entropy dominates the free-energy change at the expense of enthalpy; for upper-critical-solution-temperature association, water reorganization enthalpy drives the process at the cost of entropy. Other effects, such as electrostatic interaction and conformation change of the macromolecules, contribute much less to the variations in entropy/enthalpy.

The Conformational Transitions and Dynamics of Burkholderia cepacia Lipase Regulated by Water-Oil Interfaces

Structural dynamics and conformational transitions are crucial for the activities of enzymes. As one of the most widely used industrial biocatalysts, lipase could be activated by the water-oil interfaces. The interface activations were believed to be dominated by the close-to-open transitions of the lid subdomains. However, the detailed mechanism and the roles of structure transitions are still under debate. In this study, the dynamic structures and conformational transitions of Burkholderia cepacia lipase (LipA) were investigated by combining all-atom molecular dynamics simulations, enhanced sampling simulation, and spectrophotometric assay experiments. The conformational transitions between the lid-open and lid-closed states of LipA in aqueous solution are directly observed by the computational simulation methods. The interactions between the hydrophobic residues on the two lid-subdomains are the driven forces for the LipA closing. Meanwhile, the hydrophobic environment provided by the oil interfaces would separate the interactions between the lid-subdomains and promote the structure opening of LipA. Moreover, our studies demonstrate the opening of the lids structure is insufficient to initiate the interfacial activation, providing explanations for the inability of interfacial activation of many lipases with lid structures.

Fitting Force Field Parameters to NMR Relaxation Data

We present an approach to optimize force field parameters using time-dependent data from NMR relaxation experiments. To do so, we scan parameters in the dihedral angle potential energy terms describing the rotation of the methyl groups in proteins and compare NMR relaxation rates calculated from molecular dynamics simulations with the modified force fields to deuterium relaxation measurements of T4 lysozyme. We find that a small modification of C^γ methyl groups improves the agreement with experiments both for the protein used to optimize the force field and when validating using simulations of CI2 and ubiquitin. We also show that these improvements enable a more effective a posteriori reweighting of the MD trajectories. The resulting force field thus enables more direct comparison between simulations and side-chain NMR relaxation data and makes it possible to construct ensembles that better represent the dynamics of proteins in solution.

Mapping N- to C-terminal allosteric coupling through disruption of a putative CD74 activation site in D-dopachrome tautomerase

The macrophage migration inhibitory factor (MIF) protein family consists of MIF and D-dopachrome tautomerase (also known as MIF-2). These homologs share 34% sequence identity while maintaining nearly indistinguishable tertiary and quaternary structure, which is likely a major contributor to their overlapping functions, including the binding and activation of the cluster of differentiation 74 (CD74) receptor to mediate inflammation. Previously, we investigated a novel allosteric site, Tyr99, that modulated N-terminal catalytic activity in MIF through a "pathway" of dynamically coupled residues. In a comparative study, we revealed an analogous allosteric pathway in MIF-2 despite its unique primary sequence. Disruptions of the MIF and MIF-2 N termini also diminished CD74 activation at the C terminus, though the receptor activation site is not fully defined in MIF-2. In this study, we use site-directed mutagenesis, NMR spectroscopy, molecular simulations, in vitro and in vivo biochemistry to explore the putative CD74 activation region of MIF-2 based on homology to MIF. We also confirm its reciprocal structural coupling to the MIF-2 allosteric site and N-terminal enzymatic site. Thus, we provide further insight into the CD74 activation site of MIF-2 and its allosteric coupling for immunoregulation.

Theoretical investigation of functional responses of bio-molecular assembly networks

Cooperative protein-protein and protein-DNA interactions form programmable complex assemblies, often performing non-linear gene regulatory operations involved in signal transductions and cell fate determination. The apparent structure of those complex assemblies is very similar, but their functional response strongly depends on the topology of the protein-DNA interaction networks. Here, we demonstrate how the coordinated self-assembly creates gene regulatory network motifs that corroborate the existence of a precise functional response at the molecular level using thermodynamic and dynamic analyses. Our theoretical and Monte Carlo simulations show that a complex network of interactions can form a decision-making loop, such as feedback and feed-forward circuits, only by a few molecular mechanisms. We characterize each possible network of interactions by systematic variations of free energy parameters associated with the binding among biomolecules and DNA looping. We also find that the higher-order networks exhibit alternative steady states from the stochastic dynamics of each network. We capture this signature by calculating stochastic potentials and attributing their multi-stability features. We validate our findings against the Gal promoter system in yeast cells. Overall, we show that the network topology is vital in phenotype diversity in regulatory circuits.

Extrinsic stabilization of antiviral ACE2-Fc fusion proteins targeting SARS-CoV-2

The angiotensin-converting enzyme 2 (ACE2) is a viral receptor used by sarbecoviruses to infect cells. Fusion proteins comprising extracellular ACE2 domains and the Fc part of immunoglobulins exhibit high virus neutralization efficiency, but the structure and stability of these molecules are poorly understood. We show that although the hinge between the ACE2 and the IgG4-Fc is highly flexible, the conformational dynamics of the two ACE2 domains is restricted by their association. Interestingly, the conformational stability of the ACE2 moiety is much lower than that of the Fc part. We found that chemical compounds binding to ACE2, such as DX600 and MLN4760, can be used to strongly increase the thermal stability of the ACE2 by different mechanisms. Together, our findings reveal a general concept for stabilizing the labile receptor segments of therapeutic antiviral fusion proteins by chemical compounds.

Engineering the Active Site Lid Dynamics to Improve the Catalytic Efficiency of Yeast Cytosine Deaminase

Conformational dynamics is important for enzyme catalysis. However, engineering dynamics to achieve a higher catalytic efficiency is still challenging. In this work, we develop a new strategy to improve the activity of yeast cytosine deaminase (yCD) by engineering its conformational dynamics. Specifically, we increase the dynamics of the yCD C-terminal helix, an active site lid that controls the product release. The C-terminal is extended by a dynamical single α-helix (SAH), which improves the product release rate by up to ~8-fold, and the overall catalytic rate kcat by up to ~2-fold. It is also shown that the kcat increase is due to the favorable activation entropy change. The NMR H/D exchange data indicate that the conformational dynamics of the transition state analog complex increases as the helix is extended, elucidating the origin of the enhanced catalytic entropy. This study highlights a novel dynamics engineering strategy that can accelerate the overall catalysis through the entropy-driven mechanism.

cAMP Activation of the cAMP Receptor Protein, a Model Bacterial Transcription Factor

The active and inactive structures of the Escherichia coli cAMP receptor protein (CRP), a model bacterial transcription factor, are compared to generate a paradigm in the cAMP-induced activation of CRP. The resulting paradigm is shown to be consistent with numerous biochemical studies of CRP and CRP*, a group of CRP mutants displaying cAMP-free activity. The cAMP affinity of CRP is dictated by two factors: (i) the effectiveness of the cAMP pocket and (ii) the protein equilibrium of apo-CRP. How these two factors interplay in determining the cAMP affinity and cAMP specificity of CRP and CRP* mutants are discussed. Both the current understanding and knowledge gaps of CRP-DNA interactions are also described. This review ends with a list of several important CRP issues that need to be addressed in the future.

Deep mining of the protein energy landscape

For over half a century, it has been known that protein molecules naturally undergo extensive structural fluctuations, and that these internal motions are intimately related to their functional properties. The energy landscape view has provided a powerful framework for describing the various physical states that proteins visit during their lifetimes. This Perspective focuses on the commonly neglected and often disparaged axis of the protein energy landscape: entropy. Initially seen largely as a barrier to functionally relevant states of protein molecules, it has recently become clear that proteins retain considerable conformational entropy in the "native" state, and that this entropy can and often does contribute significantly to the free energy of fundamental protein properties, processes, and functions. NMR spectroscopy, molecular dynamics simulations, and emerging crystallographic views have matured in parallel to illuminate dynamic disorder of the "ground state" of proteins and their importance in not only transiting between biologically interesting structures but also greatly influencing their stability, cooperativity, and contribution to critical properties such as allostery.

Data-driven design of orthogonal protein-protein interactions

Engineering protein-protein interactions to generate new functions presents a challenge with great potential for many applications, ranging from therapeutics to synthetic biology. To avoid unwanted cross-talk with preexisting protein interaction networks in a cell, the specificity and selectivity of newly engineered proteins must be controlled. Here, we developed a computational strategy that mimics gene duplication and the divergence of preexisting interacting protein pairs to design new interactions. We used the bacterial PhoQ-PhoP two-component system as a model system to demonstrate the feasibility of this strategy and validated the approach with known experimental results. The designed protein pairs are predicted to exclusively interact with each other and to be insulated from potential cross-talk with their native partners. Thus, our approach enables exploration of uncharted regions of the protein sequence space and the design of new interacting protein pairs.

Computer-Aided Discovery of Potent Broad-Spectrum Vaccine Adjuvants

Adjuvants stimulate the immune system to vigorously respond to a vaccine. While current adjuvants such as aluminum salts and oil-in-water emulsions have been used for decades, they do not generate broad and long-lasting responses in many vaccines. Consequently, more potent adjuvants are needed. Here, using computer-aided molecule design and machine learning, we discovered 2 new, broad-spectrum adjuvants that can boost vaccine responses. Our library containing 46 toll-like receptor (TLR)-targeting agonist ligands were assembled on Au nanoparticles. Comprehensive in vitro, ex vivo and in vivo studies showed both leads promoted dendritic cell activation via multiple TLRs and enhanced antigen presentation to T cells. When used together with tumor-specific antigens to immunize mice against B16-OVA melanoma and 4T1-PD1 breast cancer, both adjuvants unleashed strong immune responses that suppressed tumor growth and lung metastases. Our results show computer-aided design and screening can rapidly uncover potent adjuvants for tackling waning immunity in current vaccines.

mRNA interactions with disordered regions control protein activity

The cytoplasm is compartmentalized into different translation environments. mRNAs use their 3'UTRs to localize to distinct cytoplasmic compartments, including TIS granules (TGs). Many transcription factors, including MYC, are translated in TGs. It was shown that translation of proteins in TGs enables the formation of protein complexes that cannot be established when these proteins are translated in the cytosol, but the mechanism is poorly understood. Here we show that MYC protein complexes that involve binding to the intrinsically disordered region (IDR) of MYC are only formed when MYC is translated in TGs. TG-dependent protein complexes require TG-enriched mRNAs for assembly. These mRNAs bind to a new and widespread RNA-binding domain in neutral or negatively charged IDRs in several transcription factors, including MYC. RNA-IDR interaction changes the conformational ensemble of the IDR, enabling the formation of MYC protein complexes that act in the nucleus and control functions that cannot be accomplished by cytosolically-translated MYC. We propose that certain mRNAs have IDR chaperone activity as they control IDR conformations. In addition to post-translational modifications, we found a novel mode of protein activity regulation. Since RNA-IDR interactions are prevalent, we suggest that mRNA-dependent control of protein functional states is widespread.

Perspective on the potential of tandem-ion mobility /mass spectrometry methods for structural proteomics applications

Cellular processes are usually carried out collectively by the entirety of all proteins present in a biological cell, i.e. the proteome. Mass spectrometry-based methods have proven particularly successful in identifying and quantifying the constituent proteins of proteomes, including different molecular forms of a protein. Nevertheless, protein sequences alone do not reveal the function or dysfunction of the identified proteins. A straightforward way to assign function or dysfunction to proteins is characterization of their structures and dynamics. However, a method capable to characterize detailed structures of proteins and protein complexes in a large-scale, systematic manner within the context of cellular processes does not yet exist. Here, we discuss the potential of tandem-ion mobility / mass spectrometry (tandem-IM/MS) methods to provide such ability. We highlight the capability of these methods using two case studies on the protein systems ubiquitin and avidin using the tandem-TIMS/MS technology developed in our laboratory and discuss these results in the context of other developments in the broader field of tandem-IM/MS.

Engineering of a T7 Bacteriophage Endolysin Variant with Enhanced Amidase Activity

The therapeutic use of bacteriophage-encoded endolysins as enzybiotics has increased significantly in recent years due to the emergence of antibiotic resistant bacteria. Phage endolysins lyse the bacteria by targeting their cell wall. Various engineering strategies are commonly used to modulate or enhance the utility of therapeutic enzymes. This study employed a structure-guided mutagenesis approach to engineer a T7 bacteriophage endolysin (T7L) with enhanced amidase activity and lysis potency via replacement of a noncatalytic gating residue (His 37). Two H37 variants (H37A and H37K) were designed and characterized comprehensively using integrated biophysical and biochemical techniques to provide mechanistic insights into their structure-stability-dynamics-activity paradigms. Among the studied proteins, cell lysis data suggested that the obtained H37A variant exhibits amidase activity (∼35%) enhanced compared to that of wild-type T7 endolysin (T7L-WT). In contrast to this, the H37K variant is highly unstable, prone to aggregation, and less active. Comparison of the structure and dynamics of the H37A variant to those of T7L-WT evidenced that the alteration at the site of H37 resulted in long-range structural perturbations, attenuated the conformational heterogeneity, and quenched the microsecond to millisecond time scale motions. Stability analysis confirmed the altered stability of H37A compared to that of its WT counterpart. All of the obtained results established that the H37A variant enhances the lysis activity by regulating the stability-activity trade-off. This study provided deeper atomic level insights into the structure-function relationships of endolysin proteins, thus aiding researchers in the rational design of engineered endolysins with enhanced therapeutic properties.

Heterogeneity in the M. tuberculosis β-Lactamase Inhibition by Sulbactam

For decades, researchers have been determined to elucidate essential enzymatic functions on the atomic lengths scale by tracing atomic positions in real time. Our work builds on new possibilities unleashed by mix-and-inject serial crystallography (MISC) 1-5 at X-ray free electron laser facilities. In this approach, enzymatic reactions are triggered by mixing substrate or ligand solutions with enzyme microcrystals 6 . Here, we report in atomic detail and with millisecond time-resolution how the Mycobacterium tuberculosis enzyme BlaC is inhibited by sulbactam (SUB). Our results reveal ligand binding heterogeneity, ligand gating 7-9 , cooperativity, induced fit 10,11 and conformational selection 11-13 all from the same set of MISC data, detailing how SUB approaches the catalytic clefts and binds to the enzyme non-covalently before reacting to a trans- enamine. This was made possible in part by the application of the singular value decomposition 14 to the MISC data using a newly developed program that remains functional even if unit cell parameters change during the reaction.

Locating dynamic contributions to allostery via determining rates of vibrational energy transfer

Determining rates of energy transfer across non-covalent contacts for different states of a protein can provide information about dynamic and associated entropy changes during transitions between states. We investigate the relationship between rates of energy transfer across polar and nonpolar contacts and contact dynamics for the β₂-adrenergic receptor, a rhodopsin-like G-protein coupled receptor, in an antagonist-bound inactive state and agonist-bound active state. From structures sampled during molecular dynamics (MD) simulations, we find the active state to have, on average, a lower packing density, corresponding to generally more flexibility and greater entropy than the inactive state. Energy exchange networks (EENs) are computed for the inactive and active states from the results of the MD simulations. From the EENs, changes in the rates of energy transfer across polar and nonpolar contacts are found for contacts that remain largely intact during activation. Change in dynamics of the contact, and entropy associated with the dynamics, can be estimated from the change in rates of energy transfer across the contacts. Measurement of change in the rates of energy transfer before and after the transition between states thereby provides information about dynamic contributions to activation and allostery.

Disruption of electrostatic contacts in the HNH nuclease from a thermophilic Cas9 rewires allosteric motions and enhances high-temperature DNA cleavage

Allosteric signaling within multidomain proteins is a driver of communication between spatially distant functional sites. Understanding the mechanism of allosteric coupling in large multidomain proteins is the most promising route to achieving spatial and temporal control of the system. The recent explosion of CRISPR-Cas9 applications in molecular biology and medicine has created a need to understand how the atomic level protein dynamics of Cas9, which are the driving force of its allosteric crosstalk, influence its biophysical characteristics. In this study, we used a synergistic approach of nuclear magnetic resonance (NMR) and computation to pinpoint an allosteric hotspot in the HNH domain of the thermostable GeoCas9. We show that mutation of K597 to alanine disrupts a salt-bridge network, which in turn alters the structure, the timescale of allosteric motions, and the thermostability of the GeoHNH domain. This homologous lysine-to-alanine mutation in the extensively studied mesophilic S. pyogenes Cas9 similarly alters the dynamics of the SpHNH domain. We have previously demonstrated that the alteration of allostery via mutations is a source for the specificity enhancement of SpCas9 (eSpCas9). Hence, this may also be true in GeoCas9.

General Theory of Specific Binding: Insights from a Genetic-Mechano-Chemical Protein Model

Proteins need to selectively interact with specific targets among a multitude of similar molecules in the cell. However, despite a firm physical understanding of binding interactions, we lack a general theory of how proteins evolve high specificity. Here, we present such a model that combines chemistry, mechanics, and genetics and explains how their interplay governs the evolution of specific protein-ligand interactions. The model shows that there are many routes to achieving molecular discrimination-by varying degrees of flexibility and shape/chemistry complementarity-but the key ingredient is precision. Harder discrimination tasks require more collective and precise coaction of structure, forces, and movements. Proteins can achieve this through correlated mutations extending far from a binding site, which fine-tune the localized interaction with the ligand. Thus, the solution of more complicated tasks is enabled by increasing the protein size, and proteins become more evolvable and robust when they are larger than the bare minimum required for discrimination. The model makes testable, specific predictions about the role of flexibility and shape mismatch in discrimination, and how evolution can independently tune affinity and specificity. Thus, the proposed theory of specific binding addresses the natural question of "why are proteins so big?". A possible answer is that molecular discrimination is often a hard task best performed by adding more layers to the protein.

Dry Molten Globule-Like Intermediates in Protein Folding, Function, and Disease

The performance of a protein depends on its correct folding to the final functional native form. Hence, understanding the process of protein folding has remained an important field of research for the scientific community for the past five decades. Two important intermediate states, namely, wet molten globule (WMG) and dry molten globule (DMG), have emerged as critical milestones during protein folding-unfolding reactions. While much has been discussed about WMGs as a common unfolding intermediate, the evidence for DMGs has remained elusive owing to their near-native features, which makes them difficult to probe using global structural probes. This Review puts together the available literature and new evidence on DMGs to give a broader perspective on the universality of DMGs and discuss their significance in protein folding, function, and disease.

Global, in situ analysis of the structural proteome in individuals with Parkinson's disease to identify a new class of biomarker

Parkinson's disease (PD) is a prevalent neurodegenerative disease for which robust biomarkers are needed. Because protein structure reflects function, we tested whether global, in situ analysis of protein structural changes provides insight into PD pathophysiology and could inform a new concept of structural disease biomarkers. Using limited proteolysis-mass spectrometry (LiP-MS), we identified 76 structurally altered proteins in cerebrospinal fluid (CSF) of individuals with PD relative to healthy donors. These proteins were enriched in processes misregulated in PD, and some proteins also showed structural changes in PD brain samples. CSF protein structural information outperformed abundance information in discriminating between healthy participants and those with PD and improved the discriminatory performance of CSF measures of the hallmark PD protein α-synuclein. We also present the first analysis of inter-individual variability of a structural proteome in healthy individuals, identifying biophysical features of variable protein regions. Although independent validation is needed, our data suggest that global analyses of the human structural proteome will guide the development of novel structural biomarkers of disease and enable hypothesis generation about underlying disease processes.

Evaluation of the Influence of Biosurface Design on the Interaction between the Regulatory Peptide RS1-reg and ODC1 Reveals a Membrane-Dependent Affinity Increase

The regulatory solute carrier protein, family 1, member 1 (RS1) modulates via its N-terminal domain RS1-reg the activity of Na⁺ -d-glucose cotransporter 1 (SGLT1) and thereby the glucose uptake in the small intestine by blocking the release of SGLT1-containing vesicles at the trans-Golgi network (TGN). The antidiabetic activity of RS1 is mediated by ornithindecarboxylase 1 (ODC1), catalyzing the conversion of ornithine to putrescine. Putrescine can bind to a buddying protein complex for SGLT1-containing vesicles at the membrane of the TGN, triggering vesicle release. In this report, a first in-depth analysis of the important binding process between ODC1 and RS1-reg for regulating glucose uptake in the human organism is described by comparing results from the surface-based methods, "surface plasmon resonance" (SPR) and "surface acoustic wave" (SAW) with findings by isothermal titration calorimetry (ITC). In cases of SAW and SPR, three different assay surface setups are compared, resulting in small but significant differences in K_D values for different surfaces. Noteworthy, an affinity increase by the factor of about 100 for the interaction is detected and herewith described for the first time in the presence of biological membranes that may be relevant in vivo for the biological function of RS1 and future bespoken antidiabetic drug development.

Optimising Elastic Network Models for Protein Dynamics and Allostery: Spatial and Modal Cut-offs and Backbone Stiffness

The family of coarse-grained models for protein dynamics known as Elastic Network Models (ENMs) require careful choice of parameters to represent well experimental measurements or fully-atomistic simulations. The most basic ENM that represents each protein residue by a node at the position of its C-alpha atom, all connected by springs of equal stiffness, up to a cut-off in distance. Even at this level a choice is required of the optimum cut-off distance and the upper limit of elastic normal modes taken in any sum for physical properties, such as dynamic correlation or allosteric effects on binding. Additionally, backbone-enhanced ENM (BENM) may improve the model by allocating a higher stiffness to springs that connect along the protein backbone. This work reports on the effect of varying these three parameters (distance and mode cutoffs, backbone stiffness) on the dynamical structure of three proteins, Catabolite Activator Protein (CAP), Glutathione S-transferase (GST), and the SARS-CoV-2 Main Protease (M pro ). Our main results are: (1) balancing B-factor and dispersion-relation predictions, a near-universal optimal value of 8.5 Å is advisable for ENMs; (2) inhomogeneity in elasticity brings the first mode containing spatial structure not well-resolved by the ENM typically within the first 20; (3) the BENM only affects modes in the upper third of the distribution, and, additionally to the ENM, is only able to model the dispersion curve better in this vicinity; (4) BENM does not typically affect fluctuation-allostery, which also requires careful treatment of the effector binding to the host protein to capture.

Kinematic Vibrational Entropy Assessment and Analysis of SARS CoV-2 Main Protease

The three-dimensional conformations of a protein influence its function and select for the ligands it can interact with. The total free energy change during protein-ligand complex formation includes enthalphic and entropic components, which together report on the binding affinity and conformational states of the complex. However, determining the entropic contribution is computationally burdensome. Here, we apply kinematic flexibility analysis (KFA) to efficiently estimate vibrational frequencies from static protein and protein-ligand structures. The vibrational frequencies, in turn, determine the vibrational entropies of the structures and their complexes. Our estimates of the vibrational entropy change caused by ligand binding compare favorably to values obtained from a dynamic Normal Mode Analysis (NMA). Higher correlation factors can be achieved by increasing the distance cutoff in the potential energy model. Furthermore, we apply our new method to analyze the entropy changes of the SARS CoV-2 main protease when binding with different ligand inhibitors, which is relevant for the design of potential drugs.

Ligand binding remodels protein side-chain conformational heterogeneity

While protein conformational heterogeneity plays an important role in many aspects of biological function, including ligand binding, its impact has been difficult to quantify. Macromolecular X-ray diffraction is commonly interpreted with a static structure, but it can provide information on both the anharmonic and harmonic contributions to conformational heterogeneity. Here, through multiconformer modeling of time- and space-averaged electron density, we measure conformational heterogeneity of 743 stringently matched pairs of crystallographic datasets that reflect unbound/apo and ligand-bound/holo states. When comparing the conformational heterogeneity of side chains, we observe that when binding site residues become more rigid upon ligand binding, distant residues tend to become more flexible, especially in non-solvent-exposed regions. Among ligand properties, we observe increased protein flexibility as the number of hydrogen bonds decreases and relative hydrophobicity increases. Across a series of 13 inhibitor-bound structures of CDK2, we find that conformational heterogeneity is correlated with inhibitor features and identify how conformational changes propagate differences in conformational heterogeneity away from the binding site. Collectively, our findings agree with models emerging from nuclear magnetic resonance studies suggesting that residual side-chain entropy can modulate affinity and point to the need to integrate both static conformational changes and conformational heterogeneity in models of ligand binding.