Identifying and Visualizing Macromolecular Flexibility in Structural Biology

Proactive vaccination using multiviral Quartet Nanocages to elicit broad anti-coronavirus responses

Defending against future pandemics requires vaccine platforms that protect across a range of related pathogens. Nanoscale patterning can be used to address this issue. Here, we produce quartets of linked receptor-binding domains (RBDs) from a panel of SARS-like betacoronaviruses, coupled to a computationally designed nanocage through SpyTag/SpyCatcher links. These Quartet Nanocages, possessing a branched morphology, induce a high level of neutralizing antibodies against several different coronaviruses, including against viruses not represented in the vaccine. Equivalent antibody responses are raised to RBDs close to the nanocage or at the tips of the nanoparticle's branches. In animals primed with SARS-CoV-2 Spike, boost immunizations with Quartet Nanocages increase the strength and breadth of an otherwise narrow immune response. A Quartet Nanocage including the Omicron XBB.1.5 'Kraken' RBD induced antibodies with binding to a broad range of sarbecoviruses, as well as neutralizing activity against this variant of concern. Quartet nanocages are a nanomedicine approach with potential to confer heterotypic protection against emergent zoonotic pathogens and facilitate proactive pandemic protection.

Biochemical and in silico structural characterization of a cold-active arginase from the psychrophilic yeast, Glaciozyma antarctica PI12

Glaciozyma antarctica PI12 is a psychrophilic yeast isolated from Antarctica. In this work, we describe the heterologous production, biochemical properties and in silico structure analysis of an arginase from this yeast (GaArg). GaArg is a metalloenzyme that catalyses the hydrolysis of L-arginine to L-ornithine and urea. The cDNA of GaArg was reversed transcribed, cloned, expressed and purified as a recombinant protein in Escherichia coli. The purified protein was active against L-arginine as its substrate in a reaction at 20 °C, pH 9. At 10-35 °C and pH 7-9, the catalytic activity of the protein was still present around 50%. Mn2+, Ni2+, Co2+ and K+ were able to enhance the enzyme activity more than two-fold, while GaArg is most sensitive to SDS, EDTA and DTT. The predicted structure model of GaArg showed a very similar overall fold with other known arginases. GaArg possesses predominantly smaller and uncharged amino acids, fewer salt bridges, hydrogen bonds and hydrophobic interactions compared to the other counterparts. GaArg is the first reported arginase that is cold-active, facilitated by unique structural characteristics for its adaptation of catalytic functions at low-temperature environments. The structure and function of cold-active GaArg provide insights into the potentiality of new applications in various biotechnology and pharmaceutical industries.

A robust normalized local filter to estimate compositional heterogeneity directly from cryo-EM maps

Cryo electron microscopy (cryo-EM) is used by biological research to visualize biomolecular complexes in 3D, but the heterogeneity of cryo-EM reconstructions is not easily estimated. Current processing paradigms nevertheless exert great effort to reduce flexibility and heterogeneity to improve the quality of the reconstruction. Clustering algorithms are typically employed to identify populations of data with reduced variability, but lack assessment of remaining heterogeneity. Here we develope a fast and simple algorithm based on spatial filtering to estimate the heterogeneity of a reconstruction. In the absence of flexibility, this estimate approximates macromolecular component occupancy. We show that our implementation can derive reasonable input parameters, that composition heterogeneity can be estimated based on contrast loss, and that the reconstruction can be modified accordingly to emulate altered constituent occupancy. This stands to benefit conventionally employed maximum-likelihood classification methods, whereas we here limit considerations to cryo-EM map interpretation, quantification, and particle-image signal subtraction.

Modeling protein-nucleic acid complexes with extremely large conformational changes using Flex-LZerD

Proteins and nucleic acids are key components in many processes in living cells, and interactions between proteins and nucleic acids are often crucial pathway components. In many cases, large flexibility of proteins as they interact with nucleic acids is key to their function. To understand the mechanisms of these processes, it is necessary to consider the 3D atomic structures of such protein-nucleic acid complexes. When such structures are not yet experimentally determined, protein docking can be used to computationally generate useful structure models. However, such docking has long had the limitation that the consideration of flexibility is usually limited to small movements or to small structures. We previously developed a method of flexible protein docking which could model ordered proteins which undergo large-scale conformational changes, which we also showed was compatible with nucleic acids. Here, we elaborate on the ability of that pipeline, Flex-LZerD, to model specifically interactions between proteins and nucleic acids, and demonstrate that Flex-LZerD can model more interactions and types of conformational change than previously shown.

Characterizing the combined effects of cytochrome P450 missense variation within star allele definitions

Background: Cytochrome P450 (CYP) genetic variation largely impacts drug response. However, many CYP star alleles (haplotypes) lack functional annotation, impeding our understanding of drug metabolism mechanisms. We aimed to investigate the impact of missense variant combinations on CYP protein structures. Methods: Normal mode analysis was conducted on 261 missense variants within 91 CYP haplotypes. CYP2D6*2 and CYP2D6*17 were prioritized for molecular dynamics simulation. Results: Normal mode analysis and molecular dynamics highlight the effects of known CYP missense variants on protein stability and conformational dynamics. Missense variants within haplotypes may have intermodulating effects on protein structure and function. Conclusion: This study highlights the utility of multiscale modeling in interpreting CYP missense variants and particularly their combinations within various star alleles.

Multiviral Quartet Nanocages Elicit Broad Anti-Coronavirus Responses for Proactive Vaccinology

Defending against future pandemics may require vaccine platforms that protect across a range of related pathogens. The presentation of multiple receptor-binding domains (RBDs) from evolutionarily-related viruses on a nanoparticle scaffold elicits a strong antibody response to conserved regions. Here we produce quartets of tandemly-linked RBDs from SARS-like betacoronaviruses coupled to the mi3 nanocage through a SpyTag/SpyCatcher spontaneous reaction. These Quartet Nanocages induce a high level of neutralizing antibodies against several different coronaviruses, including against viruses not represented on the vaccine. In animals primed with SARS-CoV-2 Spike, boost immunizations with Quartet Nanocages increased the strength and breadth of an otherwise narrow immune response. Quartet Nanocages are a strategy with potential to confer heterotypic protection against emergent zoonotic coronavirus pathogens and facilitate proactive pandemic protection.

Modeling of Protein Complexes

The recent advances in structural biology, combined with continuously increasing computational capabilities and development of advanced softwares, have drastically simplified the workflow for protein homology modeling. Modeling of individual proteins is nowadays quick and straightforward for a large variety of protein targets, thanks to guided pipelines relying on advanced computational tools and user-friendly interfaces, which have extended and promoted the use of modeling also to scientists not focusing on molecular structures of proteins. Nevertheless, construction of models of multi-protein complexes remains quite challenging for the non-experts, often due to the usage of specific procedures depending on the system under investigation and the need for experimental validation approaches to strengthen the generated output.In this chapter, we provide a brief overview of the approaches enabling generation of multi-protein complex models starting from homology models of individual protein components. Using real-life examples, we include two examples to guide the reader in the generation of homomeric and heteromeric protein models.

Domain-Based Protein Docking with Extremely Large Conformational Changes

Proteins are key components in many processes in living cells, and physical interactions with other proteins and nucleic acids often form key parts of their functions. In many cases, large flexibility of proteins as they interact is key to their function. To understand the mechanisms of these processes, it is necessary to consider the 3D structures of such protein complexes. When such structures are not yet experimentally determined, protein docking has long been present to computationally generate useful structure models. However, protein docking has long had the limitation that the consideration of flexibility is usually limited to very small movements or very small structures. Methods have been developed which handle minor flexibility via normal mode or other structure sampling, but new methods are required to model ordered proteins which undergo large-scale conformational changes to elucidate their function at the molecular level. Here, we present Flex-LZerD, a framework for docking such complexes. Via partial assembly multidomain docking and an iterative normal mode analysis admitting curvilinear motions, we demonstrate the ability to model the assembly of a variety of protein-protein and protein-nucleic acid complexes.

Modeling of protein conformational changes with Rosetta guided by limited experimental data

Conformational changes are an essential component of functional cycles of many proteins, but their characterization often requires an integrative structural biology approach. Here, we introduce and benchmark ConfChangeMover (CCM), a new method built into the widely used macromolecular modeling suite Rosetta that is tailored to model conformational changes in proteins using sparse experimental data. CCM can rotate and translate secondary structural elements and modify their backbone dihedral angles in regions of interest. We benchmarked CCM on soluble and membrane proteins with simulated Cα-Cα distance restraints and sparse experimental double electron-electron resonance (DEER) restraints, respectively. In both benchmarks, CCM outperformed state-of-the-art Rosetta methods, showing that it can model a diverse array of conformational changes. In addition, the Rosetta framework allows a wide variety of experimental data to be integrated with CCM, thus extending its capability beyond DEER restraints. This method will contribute to the biophysical characterization of protein dynamics.

Leveraging intrinsic flexibility to engineer enhanced enzyme catalytic activity

Dynamic motions of enzymes occurring on a broad range of timescales play a pivotal role in all steps of the reaction pathway, including substrate binding, catalysis, and product release. However, it is unknown whether structural information related to conformational flexibility can be exploited for the directed evolution of enzymes with higher catalytic activity. Here, we show that mutagenesis of residues exclusively located at flexible regions distal to the active site of Homo sapiens kynureninase (HsKYNase) resulted in the isolation of a variant (BF-HsKYNase) in which the rate of the chemical step toward kynurenine was increased by 45-fold. Mechanistic pre–steady-state kinetic analysis of the wild type and the evolved enzyme shed light on the underlying effects of distal mutations (>10 Å from the active site) on the rate-limiting step of the catalytic cycle. Hydrogen-deuterium exchange coupled to mass spectrometry and molecular dynamics simulations revealed that the amino acid substitutions in BF-HsKYNase allosterically affect the flexibility of the pyridoxal-5′-phosphate (PLP) binding pocket, thereby impacting the rate of chemistry, presumably by altering the conformational ensemble and sampling states more favorable to the catalyzed reaction.

Engineering of the Recombinant Expression and PEGylation Efficiency of the Therapeutic Enzyme Human Thymidine Phosphorylase

Human thymidine phosphorylase (HsTP) is an enzyme with important implications in the field of rare metabolic diseases. Defective mutations of HsTP lead to mitochondrial neurogastrointestinal encephalomyopathy (MNGIE), a disease with a high unmet medical need that is associated with severe neurological and gastrointestinal complications. Current efforts focus on the development of an enzyme replacement therapy (ERT) using the Escherichia coli ortholog (EcTP). However, bacterial enzymes are counter-indicated for human therapeutic applications because they are recognized as foreign by the human immune system, thereby eliciting adverse immune responses and raising significant safety and efficacy risks. Thus, it is critical to utilize the HsTP enzyme as starting scaffold for pre-clinical drug development, thus de-risking the safety concerns associated with the use of bacterial enzymes. However, HsTP expresses very poorly in E. coli, whereas its PEGylation, a crucial chemical modification for achieving long serum persistence of therapeutic enzymes, is highly inefficient and negatively affects its catalytic activity. Here we focused on the engineering of the recombinant expression profile of HsTP in E. coli cells, as well as on the optimization of its PEGylation efficiency aiming at the development of an alternative therapeutic approach for MNGIE. We show that phylogenetic and structural analysis of proteins can provide important insights for the rational design of N’-terminus-truncation constructs which exhibit significantly improved recombinant expression levels. In addition, we developed and implemented a criteria-driven rational surface engineering strategy for the substitution of arginine-to-lysine and lysine-to-arginine residues to achieve more efficient, homogeneous and reproducible PEGylation without negatively affecting the enzymatic catalytic activity upon PEGylation. Collectively, our proposed strategies provide an effective way to optimize enzyme PEGylation and E. coli recombinant expression and are likely applicable for other proteins and enzymes.

Wavelet invariants for statistically robust multi-reference alignment

We propose a nonlinear, wavelet-based signal representation that is translation invariant and robust to both additive noise and random dilations. Motivated by the multi-reference alignment problem and generalizations thereof, we analyze the statistical properties of this representation given a large number of independent corruptions of a target signal. We prove the nonlinear wavelet-based representation uniquely defines the power spectrum but allows for an unbiasing procedure that cannot be directly applied to the power spectrum. After unbiasing the representation to remove the effects of the additive noise and random dilations, we recover an approximation of the power spectrum by solving a convex optimization problem, and thus reduce to a phase retrieval problem. Extensive numerical experiments demonstrate the statistical robustness of this approximation procedure.

Identifying the origin of local flexibility in a carbohydrate polymer

The monomer sequence dictates the structure and properties of natural polymers. Such a structure–property relationship is well known for polypeptides and polynucleotides but not for polysaccharides, the most abundant biopolymers on Earth. Here, we establish the structure–property relationship for a polysaccharide at the atomic level by determining molecular flexibility of carbohydrate chains with defined sequences. The chain flexibility can be engineered one linkage at a time by chemical substitution and conformation change, highlighting how the primary and secondary structures of a carbohydrate dictate its flexibility—a critical observable in the de novo design of carbohydrate materials. Our approach can be extended to establish the structure–property relationship at the atomic level of any molecule that can be electrosprayed.

Correlating the structures and properties of a polymer to its monomer sequence is key to understanding how its higher hierarchy structures are formed and how its macroscopic material properties emerge. Carbohydrate polymers, such as cellulose and chitin, are the most abundant materials found in nature whose structures and properties have been characterized only at the submicrometer level. Here, by imaging single-cellulose chains at the nanoscale, we determine the structure and local flexibility of cellulose as a function of its sequence (primary structure) and conformation (secondary structure). Changing the primary structure by chemical substitutions and geometrical variations in the secondary structure allow the chain flexibility to be engineered at the single-linkage level. Tuning local flexibility opens opportunities for the bottom-up design of carbohydrate materials.

Tethering-facilitated DNA 'opening' and complementary roles of β-hairpin motifs in the Rad4/XPC DNA damage sensor protein

XPC/Rad4 initiates eukaryotic nucleotide excision repair on structurally diverse helix-destabilizing/distorting DNA lesions by selectively 'opening' these sites while rapidly diffusing along undamaged DNA. Previous structural studies showed that Rad4, when tethered to DNA, could also open undamaged DNA, suggesting a 'kinetic gating' mechanism whereby lesion discrimination relied on efficient opening versus diffusion. However, solution studies in support of such a mechanism were lacking and how 'opening' is brought about remained unclear. Here, we present crystal structures and fluorescence-based conformational analyses on tethered complexes, showing that Rad4 can indeed 'open' undamaged DNA in solution and that such 'opening' can largely occur without one or the other of the β-hairpin motifs in the BHD2 or BHD3 domains. Notably, the Rad4-bound 'open' DNA adopts multiple conformations in solution notwithstanding the DNA's original structure or the β-hairpins. Molecular dynamics simulations reveal compensatory roles of the β-hairpins, which may render robustness in dealing with and opening diverse lesions. Our study showcases how fluorescence-based studies can be used to obtain information complementary to ensemble structural studies. The tethering-facilitated DNA 'opening' of undamaged sites and the dynamic nature of 'open' DNA may shed light on how the protein functions within and beyond nucleotide excision repair in cells.

Probing the Structural Dynamics of the Plasmodium falciparum Tunneling-Fold Enzyme 6-Pyruvoyl Tetrahydropterin Synthase to Reveal Allosteric Drug Targeting Sites

The de novo folate synthesis pathway is a well-established drug target in the treatment of many infectious diseases. Antimalarial antifolate drugs have proven to be effective against malaria, however, rapid drug resistance has emerged on the two primary targeted enzymes: dihydrofolate reductase and dihydroptoreate synthase. The need to identify alternative antifolate drugs and novel metabolic targets is of imminent importance. The 6-pyruvol tetrahydropterin synthase (PTPS) enzyme belongs to the tunneling fold protein superfamily which is characterized by a distinct central tunnel/cavity. The enzyme catalyzes the second reaction step of the parasite’s de novo folate synthesis pathway and is responsible for the conversion of 7,8-dihydroneopterin to 6-pyruvoyl-tetrahydropterin. In this study, we examine the structural dynamics of Plasmodium falciparum PTPS using the anisotropic network model, to elucidate the collective motions that drive the function of the enzyme and identify potential sites for allosteric modulation of its binding properties. Based on our modal analysis, we identified key sites in the N-terminal domains and central helices which control the accessibility to the active site. Notably, the N-terminal domains were shown to regulate the open-to-closed transition of the tunnel, via a distinctive wringing motion that deformed the core of the protein. We, further, combined the dynamic analysis with motif discovery which revealed highly conserved motifs that are unique to the Plasmodium species and are located in the N-terminal domains and central helices. This provides essential structural information for the efficient design of drugs such as allosteric modulators that would have high specificity and low toxicity as they do not target the PTPS active site that is highly conserved in humans.

Light-coupled cryo-plunger for time-resolved cryo-EM

Proteins are dynamic molecules that can undergo rapid conformational rearrangements in response to stimuli. These structural changes are often critical to protein function, and thus elucidating time-dependent conformational landscapes has been a long-standing goal of structural biology. To harness the power of single particle cryo-EM methods to enable 'time-resolved' structure determination, we have developed a light-coupled cryo-plunger that pairs flash-photolysis of caged ligands with rapid sample vitrification. The 'flash-plunger' consists of a high-power ultraviolet LED coupled with focusing optics and a motorized linear actuator, enabling the user to immobilize protein targets in vitreous ice within a programmable time window - as short as tens of milliseconds - after stimulus delivery. The flash-plunger is a simple, inexpensive and flexible tool to explore short-lived conformational states previously unobtainable by conventional sample preparation methods.

Discriminating changes in protein structure using tyrosine conjugation

Chemical modification of proteins has been crucial in engineering protein-based therapies, targeted biopharmaceutics, molecular probes, and biomaterials. Here, we explore the use of a conjugation-based approach to sense alternative conformational states in proteins. Tyrosine has both hydrophobic and hydrophilic qualities, thus allowing it to be positioned at protein surfaces, or binding interfaces, or to be buried within a protein. Tyrosine can be conjugated with 4-phenyl-3H-1,2,4-triazole-3,5(4H)-dione (PTAD). We hypothesized that individual protein conformations could be distinguished by labeling tyrosine residues in the protein with PTAD. We conjugated tyrosine residues in a well-folded protein, bovine serum albumin (BSA), and quantified labeled tyrosine with liquid chromatography with tandem mass spectrometry. We applied this approach to alternative conformations of BSA produced in the presence of urea. The amount of PTAD labeling was found to relate to the depth of each tyrosine relative to the protein surface. This study demonstrates a new use of tyrosine conjugation using PTAD as an analytic tool able to distinguish the conformational states of a protein.

Insight into the Structural Features of TSPO: Implications for Drug Development

The translocator protein (TSPO), an 18-kDa transmembrane protein primarily found in the outer mitochondrial membrane, is evolutionarily conserved and widely distributed across species. In mammals, TSPO has been described as a key member of a multiprotein complex involved in many putative functions and, over the years, several classes of ligand have been developed to modulate these functions. In this review, we consider the currently available atomic structures of mouse and bacterial TSPO and propose a rationale for the development of new ligands for the protein. We provide a review of TSPO monomeric and oligomeric states and their conformational flexibility, together with ligand-binding site and interaction mechanisms. These data are expected to help considerably the development of high-affinity ligands for TSPO-based therapies or diagnostics.

Dissecting the Extracellular Complexity of Neuromuscular Junction Organizers

Synapse formation is a very elaborate process dependent upon accurate coordination of pre and post-synaptic specialization, requiring multiple steps and a variety of receptors and signaling molecules. Due to its relative structural simplicity and the ease in manipulation and observation, the neuromuscular synapse or neuromuscular junction (NMJ)-the connection between motor neurons and skeletal muscle-represents the archetype junction system for studying synapse formation and conservation. This junction is essential for survival, as it controls our ability to move and breath. NMJ formation requires coordinated interactions between motor neurons and muscle fibers, which ultimately result in the formation of a highly specialized post-synaptic architecture and a highly differentiated nerve terminal. Furthermore, to ensure a fast and reliable synaptic transmission following neurotransmitter release, ligand-gated channels (acetylcholine receptors, AChRs) are clustered on the post-synaptic muscle cell at high concentrations in sites opposite the presynaptic active zone, supporting a direct role for nerves in the organization of the post-synaptic membrane architecture. This organized clustering process, essential for NMJ formation and for life, relies on key signaling molecules and receptors and is regulated by soluble extracellular molecules localized within the synaptic cleft. Notably, several mutations as well as auto-antibodies against components of these signaling complexes have been related to neuromuscular disorders. The recent years have witnessed strong progress in the understanding of molecular identities, architectures, and functions of NMJ macromolecules. Among these, prominent roles have been proposed for neural variants of the proteoglycan agrin, its receptor at NMJs composed of the lipoprotein receptor-related protein 4 (LRP4) and the muscle-specific kinase (MuSK), as well as the regulatory soluble synapse-specific protease Neurotrypsin. In this review we summarize the current state of the art regarding molecular structures and (agrin-dependent) canonical, as well as (agrin-independent) non-canonical, MuSK signaling mechanisms that underscore the formation of neuromuscular junctions, with the aim of providing a broad perspective to further stimulate molecular, cellular and tissue biology investigations on this fundamental intercellular contact.

Pre- and post-docking sampling of conformational changes using ClustENM and HADDOCK for protein-protein and protein-DNA systems

Incorporating the dynamic nature of biomolecules in the modeling of their complexes is a challenge, especially when the extent and direction of the conformational changes taking place upon binding is unknown. Estimating whether the binding of a biomolecule to its partner(s) occurs in a conformational state accessible to its unbound form (“conformational selection”) and/or the binding process induces conformational changes (“induced‐fit”) is another challenge. We propose here a method combining conformational sampling using ClustENM—an elastic network‐based modeling procedure—with docking using HADDOCK, in a framework that incorporates conformational selection and induced‐fit effects upon binding. The extent of the applied deformation is estimated from its energetical costs, inspired from mechanical tensile testing on materials. We applied our pre‐ and post‐docking sampling of conformational changes to the flexible multidomain protein‐protein docking benchmark and a subset of the protein‐DNA docking benchmark. Our ClustENM‐HADDOCK approach produced acceptable to medium quality models in 7/11 and 5/6 cases for the protein‐protein and protein‐DNA complexes, respectively. The conformational selection (sampling prior to docking) has the highest impact on the quality of the docked models for the protein‐protein complexes. The induced‐fit stage of the pipeline (post‐sampling), however, improved the quality of the final models for the protein‐DNA complexes. Compared to previously described strategies to handle conformational changes, ClustENM‐HADDOCK performs better than two‐body docking in protein‐protein cases but worse than a flexible multidomain docking approach. However, it does show a better or similar performance compared to previous protein‐DNA docking approaches, which makes it a suitable alternative.

Challenges and advances in atomistic simulations of potassium and sodium ion channel gating and permeation

Ion channels are implicated in many essential physiological events such as electrical signal propagation and cellular communication. The advent of K⁺ and Na⁺ ion channel structure determination has facilitated numerous investigations of molecular determinants of their behaviour. At the same time, rapid development of computer hardware and molecular simulation methodologies has made computational studies of large biological molecules in all-atom representation tractable. The concurrent evolution of experimental structural biology with biomolecular computer modelling has yielded mechanistic details of fundamental processes unavailable through experiments alone, such as ion conduction and ion channel gating. This review is a short survey of the atomistic computational investigations of K⁺ and Na⁺ ion channels, focusing on KcsA and several voltage-gated channels from the K_V and Na_V families, which have garnered many successes and engendered several long-standing controversies regarding the nature of their structure-function relationship. We review the latest advancements and challenges facing the field of molecular modelling and simulation regarding the structural and energetic determinants of ion channel function and their agreement with experimental observations.

Biomechanical defects and rescue of cardiomyocytes expressing pathologic nuclear lamins

Aims

Given the clinical impact of LMNA cardiomyopathies, understanding lamin function will fulfill a clinical need and will lead to advancement in the treatment of heart failure. A multidisciplinary approach combining cell biology, atomic force microscopy (AFM), and molecular modeling was used to analyse the biomechanical properties of human lamin A/C gene (LMNA) mutations (E161K, D192G, N195K) using an in vitro neonatal rat ventricular myocyte model.

Methods and results

The severity of biomechanical defects due to the three LMNA mutations correlated with the severity of the clinical phenotype. AFM and molecular modeling identified distinctive biomechanical and structural changes, with increasing severity from E161K to N195K and D192G, respectively. Additionally, the biomechanical defects were rescued with a p38 MAPK inhibitor.

Conclusions

AFM and molecular modeling were able to quantify distinct biomechanical and structural defects in LMNA mutations E161K, D192G, and N195K and correlate the defects with clinical phenotypic severity. Improvements in cellular biomechanical phenotype was demonstrated and may represent a mechanism of action for p38 MAPK inhibition therapy that is now being used in human clinical trials to treat laminopathies.

Carbohydrate-Based Host-Guest Complexation of Hydrophobic Antibiotics for the Enhancement of Antibacterial Activity

Host-guest complexation with various hydrophobic drugs has been used to enhance the solubility, permeability, and stability of guest drugs. Physical changes in hydrophobic drugs by complexation have been related to corresponding increases in the bioavailability of these drugs. Carbohydrates, including various derivatives of cyclodextrins, cyclosophoraoses, and some linear oligosaccharides, are generally used as host complexation agents in drug delivery systems. Many antibiotics with low bioavailability have some limitations to their clinical use due to their intrinsically poor aqueous solubility. Bioavailability enhancement is therefore an important step to achieve the desired concentration of antibiotics in the treatment of bacterial infections. Antibiotics encapsulated in a complexation-based drug delivery system will display improved antibacterial activity making it possible to reduce dosages and overcome the serious global problem of antibiotic resistance. Here, we review the present research trends in carbohydrate-based host-guest complexation of various hydrophobic antibiotics as an efficient delivery system to improve solubility, permeability, stability, and controlled release.

In Silico Studies of Small Molecule Interactions with Enzymes Reveal Aspects of Catalytic Function

Small molecules, such as solvent, substrate, and cofactor molecules, are key players in enzyme catalysis. Computational methods are powerful tools for exploring the dynamics and thermodynamics of these small molecules as they participate in or contribute to enzymatic processes. In-depth knowledge of how small molecule interactions and dynamics influence protein conformational dynamics and function is critical for progress in the field of enzyme catalysis. Although numerous computational studies have focused on enzyme-substrate complexes to gain insight into catalytic mechanisms, transition states and reaction rates, the dynamics of solvents, substrates, and cofactors are generally less well studied. Also, solvent dynamics within the biomolecular solvation layer play an important part in enzyme catalysis, but a full understanding of its role is hampered by its complexity. Moreover, passive substrate transport has been identified in certain enzymes, and the underlying principles of molecular recognition are an area of active investigation. Enzymes are highly dynamic entities that undergo different conformational changes, which range from side chain rearrangement of a residue to larger-scale conformational dynamics involving domains. These events may happen nearby or far away from the catalytic site, and may occur on different time scales, yet many are related to biological and catalytic function. Computational studies, primarily molecular dynamics (MD) simulations, provide atomistic-level insight and site-specific information on small molecule interactions, and their role in conformational pre-reorganization and dynamics in enzyme catalysis. The review is focused on MD simulation studies of small molecule interactions and dynamics to characterize and comprehend protein dynamics and function in catalyzed reactions. Experimental and theoretical methods available to complement and expand insight from MD simulations are discussed briefly.

Molecular modeling of biomolecules by paramagnetic NMR and computational hybrid methods

The 3D atomic structures of biomolecules and their complexes are key to our understanding of biomolecular function, recognition, and mechanism. However, it is often difficult to obtain structures, particularly for systems that are complex, dynamic, disordered, or exist in environments like cell membranes. In such cases sparse data from a variety of paramagnetic NMR experiments offers one possible source of structural information. These restraints can be incorporated in computer modeling algorithms that can accurately translate the sparse experimental data into full 3D atomic structures. In this review, we discuss various types of paramagnetic NMR/computational hybrid modeling techniques that can be applied to successful modeling of not only the atomic structure of proteins but also their interacting partners. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.

A mechanism for lipid binding to apoE and the role of intrinsically disordered regions coupled to domain-domain interactions

Relative to the apolipoprotein E (apoE) E3 allele of the APOE gene, apoE4 strongly increases the risk for the development of late-onset Alzheimer's disease. However, apoE4 differs from apoE3 by only a single amino acid at position 112, which is arginine in apoE4 and cysteine in apoE3. It remains unclear why apoE3 and apoE4 are functionally different. Described here is a proposal for understanding the functional differences between these two isoforms with respect to lipid binding. A mechanism is proposed that is based on the full-length monomeric structure of the protein, on hydrogen-deuterium exchange mass spectrometry data, and on the role of intrinsically disordered regions to control protein motions. It is proposed that lipid binds between the N-terminal and C-terminal domains and that separation of the two domains, along with the presence of intrinsically disordered regions, controls this process. The mechanism explains why apoE3 differs from apoE4 with respect to different lipid-binding specificities, why lipid increases the binding of apoE to its receptor, and why specific residues are conserved.