Protein stability, flexibility and function

FLEXc: protein flexibility prediction using context-based statistics, predicted structural features, and sequence information

Background

The fluctuation of atoms around their average positions in protein structures provides important information regarding protein dynamics. This flexibility of protein structures is associated with various biological processes. Predicting flexibility of residues from protein sequences is significant for analyzing the dynamic properties of proteins which will be helpful in predicting their functions.

Results

In this paper, an approach of improving the accuracy of protein flexibility prediction is introduced. A neural network method for predicting flexibility in 3 states is implemented. The method incorporates sequence and evolutionary information, context-based scores, predicted secondary structures and solvent accessibility, and amino acid properties. Context-based statistical scores are derived, using the mean-field potentials approach, for describing the different preferences of protein residues in flexibility states taking into consideration their amino acid context.

The 7-fold cross validated accuracy reached 61 % when context-based scores and predicted structural states are incorporated in the training process of the flexibility predictor.

Conclusions

Incorporating context-based statistical scores with predicted structural states are important features to improve the performance of predicting protein flexibility, as shown by our computational results. Our prediction method is implemented as web service called “FLEXc” and available online at: http://hpcr.cs.odu.edu/flexc.

Bridging Enzymatic Structure Function via Mechanics: A Coarse-Grain Approach

Flexibility is a central aspect of protein function, and ligand binding in enzymes involves a wide range of structural changes, ranging from large-scale domain movements to small loop or side-chain rearrangements. In order to understand how the mechanical properties of enzymes, and the mechanical variations that are induced by ligand binding, relate to enzymatic activity, we carried out coarse-grain Brownian dynamics simulations on a set of enzymes whose structures in the unbound and ligand-bound forms are available in the Protein Data Bank. Our results show that enzymes are remarkably heterogeneous objects from a mechanical point of view and that the local rigidity of individual residues is tightly connected to their part in the protein's overall structure and function. The systematic comparison of the rigidity of enzymes in their unbound and bound forms highlights the fact that small conformational changes can induce large mechanical effects, leading to either more or less flexibility depending on the enzyme's architecture and the location of its ligand-biding site. These mechanical variations target a limited number of specific residues that occupy key locations for enzymatic activity, and our approach thus offers a mean to detect perturbation-sensitive sites in enzymes, where the addition or removal of a few interactions will lead to important changes in the proteins internal dynamics.

Computational investigation of dynamical transitions in Trp-cage miniprotein powders

We investigate computationally the dynamical transitions in Trp-cage miniprotein powders, at three levels of hydration: 0.04, 0.26 and 0.4 g water/g protein. We identify two distinct temperatures where transitions in protein dynamics occur. Thermal motions are harmonic and independent of hydration level below T_low ≈ 160 K, above which all powders exhibit harmonic behavior but with a different and enhanced temperature dependence. The second onset, which is often referred to as the protein dynamical transition, occurs at a higher temperature T_D that decreases as the hydration level increases, and at the lowest hydration level investigated here (0.04 g/g) is absent in the temperature range we studied in this work (T ≤ 300 K). Protein motions become anharmonic at T_D, and their amplitude increases with hydration level. Upon heating above T_D, hydrophilic residues experience a pronounced enhancement in the amplitude of their characteristic motions in hydrated powders, whereas it is the hydrophobic residues that experience the more pronounced enhancement in the least hydrated system. The dynamical transition in Trp-cage is a collective phenomenon, with every residue experiencing a transition to anharmonic behavior at the same temperature.

Fast, cheap and out of control--Insights into thermodynamic and informatic constraints on natural protein sequences from de novo protein design

The accumulated results of thirty years of rational and computational de novo protein design have taught us important lessons about the stability, information content, and evolution of natural proteins. First, de novo protein design has complicated the assertion that biological function is equivalent to biological structure - demonstrating the capacity to abstract active sites from natural contexts and paste them into non-native topologies without loss of function. The structure-function relationship has thus been revealed to be either a generality or strictly true only in a local sense. Second, the simplification to "maquette" topologies carried out by rational protein design also has demonstrated that even sophisticated functions such as conformational switching, cooperative ligand binding, and light-activated electron transfer can be achieved with low-information design approaches. This is because for simple topologies the functional footprint in sequence space is enormous and easily exceeds the number of structures which could have possibly existed in the history of life on Earth. Finally, the pervasiveness of extraordinary stability in designed proteins challenges accepted models for the "marginal stability" of natural proteins, suggesting that there must be a selection pressure against highly stable proteins. This can be explained using recent theories which relate non-equilibrium thermodynamics and self-replication. This article is part of a Special Issue entitled Biodesign for Bioenergetics--The design and engineering of electronc transfer cofactors, proteins and protein networks, edited by Ronald L. Koder and J.L. Ross Anderson.

Ubiquilin-mediated Small Molecule Inhibition of Mammalian Target of Rapamycin Complex 1 (mTORC1) Signaling

Mammalian target of rapamycin complex 1 (mTORC1) is a master regulator of cellular metabolism, growth, and proliferation. mTORC1 has been implicated in many diseases such as cancer, diabetes, and neurodegeneration, and is a target to prolong lifespan. Here we report a small molecule inhibitor (Cbz-B3A) of mTORC1 signaling. Cbz-B3A inhibits the phosphorylation of eIF4E-binding protein 1 (4EBP1) and blocks 68% of translation. In contrast, rapamycin preferentially inhibits the phosphorylation of p70(S6k) and blocks 35% of translation. Cbz-B3A does not appear to bind directly to mTORC1, but instead binds to ubiquilins 1, 2, and 4. Knockdown of ubiquilin 2, but not ubiquilins 1 and 4, decreases the phosphorylation of 4EBP1, suggesting that ubiquilin 2 activates mTORC1. The knockdown of ubiquilins 2 and 4 decreases the effect of Cbz-B3A on 4EBP1 phosphorylation. Cbz-B3A slows cellular growth of some human leukemia cell lines, but is not cytotoxic. Thus Cbz-B3A exemplifies a novel strategy to inhibit mTORC1 signaling that might be exploited for treating many human diseases. We propose that Cbz-B3A reveals a previously unappreciated regulatory pathway coordinating cytosolic protein quality control and mTORC1 signaling.

SK. Structural exploration of acid sphingomyelinase at different physiological pH through molecular dynamics and docking studies

Acid sphingomyelinase (ASM) hydrolysis the sphingomyelin at physiological pH 5.0 and subsequently leads to ceramide production.

Structural and dynamic evolution of the amphipathic N-terminus diversifies enzyme thermostability in the glycoside hydrolase family 12

The N-terminus diversifies enzyme thermostability in the GH12 family, which was investigated by MD simulations, and provides potential applications in protein engineering.

Secreted Acb1 Contributes to the Yeast-to-Hypha Transition in Cryptococcus neoformans

Adaptation to stress by eukaryotic pathogens is often accompanied by a transition in cellular morphology. The human fungal pathogen Cryptococcus neoformans is known to switch between the yeast and the filamentous form in response to amoebic predation or during mating. As in the classic dimorphic fungal pathogens, the morphotype is associated with the ability of cryptococci to infect various hosts. Many cryptococcal factors and environmental stimuli, including pheromones (small peptides) and nutrient limitation, are known to induce the yeast-to-hypha transition. We recently discovered that secreted matricellular proteins could also act as intercellular signals to promote the yeast-to-hypha transition. Here we show that the secreted acyl coenzyme A (acyl-CoA)-binding protein Acb1 plays an important role in enhancing this morphotype transition. Acb1 does not possess a signal peptide. Its extracellular secretion and, consequently, its function in filamentation are dependent on an unconventional GRASP (Golgi reassembly stacking protein)-dependent secretion pathway. Surprisingly, intracellular recruitment of Acb1 to the secretory vesicles is independent of Grasp. In addition to Acb1, Grasp possibly controls the secretion of other cargos, because the graspΔ mutant, but not the acb1Δ mutant, is defective in capsule production and macrophage phagocytosis. Nonetheless, Acb1 is likely the major or the sole effector of Grasp in terms of filamentation. Furthermore, we found that the key residue of Acb1 for acyl binding, Y80, is critical for the proper subcellular localization and secretion of Acb1 and for cryptococcal morphogenesis.

Interacting mechanism of ID3 HLH domain towards E2A/E12 transcription factor - An Insight through molecular dynamics and docking approach

Inhibitor of DNA binding protein 3 (ID3) has long been characterized as an oncogene that implicates its functional role through its Helix-Loop-Helix (HLH) domain upon protein-protein interaction. An insight into the dimerization brought by this domain helps in identifying the key residues that favor the mechanism behind it. Molecular dynamics (MD) simulations were performed for the HLH proteins ID3 and Transcription factor E2-alpha (E2A/E12) and their ensemble complex (ID3-E2A/E12) to gather information about the HLH domain region and its role in the interaction process. Further evaluation of the results by Principal Component Analysis (PCA) and Free Energy Landscape (FEL) helped in revealing residues of E2A/E12: Lys570, Ala595, Val598, and Ile599 and ID3: Glu53, Gln63, and Gln66 buried in their HLH motifs imparting key roles in dimerization process. Furthermore the T-pad analysis results helped in identifying the key fluctuations and conformational transitions using the intrinsic properties of the residues present in the domain region of the proteins thus specifying their crucial role towards molecular recognition. The study provides an insight into the interacting mechanism of the ID3-E2A/E12 complex and maps the structural transitions arising in the essential conformational space indicating the key structural changes within the helical regions of the motif. It thereby describes how the internal dynamics of the proteins might regulate their intrinsic structural features and its subsequent functionality.

Molecular-scale features that govern the effects of O-glycosylation on a carbohydrate-binding module

Protein glycosylation is a ubiquitous post-translational modification in all kingdoms of life. Despite its importance in molecular and cellular biology, the molecular-level ramifications of O-glycosylation on biomolecular structure and function remain elusive. Here, we took a small model glycoprotein and changed the glycan structure and size, amino acid residues near the glycosylation site, and glycosidic linkage while monitoring any corresponding changes to physical stability and cellulose binding affinity. The results of this study reveal the collective importance of all the studied features in controlling the most pronounced effects of O-glycosylation in this system. Going forward, this study suggests the possibility of designing proteins with multiple improved properties by simultaneously varying the structures of O-glycans and amino acids local to the glycosylation site.

Effects of Non-Natural Amino Acid Incorporation into the Enzyme Core Region on Enzyme Structure and Function

Techniques to incorporate non-natural amino acids (NNAAs) have enabled biosynthesis of proteins containing new building blocks with unique structures, chemistry, and reactivity that are not found in natural amino acids. It is crucial to understand how incorporation of NNAAs affects protein function because NNAA incorporation may perturb critical function of a target protein. This study investigates how the site-specific incorporation of NNAAs affects catalytic properties of an enzyme. A NNAA with a hydrophobic and bulky sidechain, 3-(2-naphthyl)-alanine (2Nal), was site-specifically incorporated at six different positions in the hydrophobic core of a model enzyme, murine dihydrofolate reductase (mDHFR). The mDHFR variants with a greater change in van der Waals volume upon 2Nal incorporation exhibited a greater reduction in the catalytic efficiency. Similarly, the steric incompatibility calculated using RosettaDesign, a protein stability calculation program, correlated with the changes in the catalytic efficiency.

Bridging scales through multiscale modeling: a case study on protein kinase A

The goal of multiscale modeling in biology is to use structurally based physico-chemical models to integrate across temporal and spatial scales of biology and thereby improve mechanistic understanding of, for example, how a single mutation can alter organism-scale phenotypes. This approach may also inform therapeutic strategies or identify candidate drug targets that might otherwise have been overlooked. However, in many cases, it remains unclear how best to synthesize information obtained from various scales and analysis approaches, such as atomistic molecular models, Markov state models (MSM), subcellular network models, and whole cell models. In this paper, we use protein kinase A (PKA) activation as a case study to explore how computational methods that model different physical scales can complement each other and integrate into an improved multiscale representation of the biological mechanisms. Using measured crystal structures, we show how molecular dynamics (MD) simulations coupled with atomic-scale MSMs can provide conformations for Brownian dynamics (BD) simulations to feed transitional states and kinetic parameters into protein-scale MSMs. We discuss how milestoning can give reaction probabilities and forward-rate constants of cAMP association events by seamlessly integrating MD and BD simulation scales. These rate constants coupled with MSMs provide a robust representation of the free energy landscape, enabling access to kinetic, and thermodynamic parameters unavailable from current experimental data. These approaches have helped to illuminate the cooperative nature of PKA activation in response to distinct cAMP binding events. Collectively, this approach exemplifies a general strategy for multiscale model development that is applicable to a wide range of biological problems.

Characterization of the global stabilizing substitution A77V and its role in the evolution of CTX-M β-lactamases

The widespread use of oxyimino-cephalosporin antibiotics drives the evolution of the CTX-M family of β-lactamases that hydrolyze these drugs and confer antibiotic resistance. Clinically isolated CTX-M enzymes carrying the P167S or D240G active site-associated adaptive mutation have a broadened substrate profile that includes the oxyimino-cephalosporin antibiotic ceftazidime. The D240G substitution is known to reduce the stability of CTX-M-14 β-lactamase, and the P167S substitution is shown here to also destabilize the enzyme. Proteins are marginally stable entities, and second-site mutations that stabilize the enzyme can offset a loss in stability caused by mutations that enhance enzyme activity. Therefore, the evolution of antibiotic resistance enzymes can be dependent on the acquisition of stabilizing mutations. The A77V substitution is present in CTX-M extended-spectrum β-lactamases (ESBLs) from a number of clinical isolates, suggesting that it may be important in the evolution of antibiotic resistance in this family of β-lactamases. In this study, the effects of the A77V substitution in the CTX-M-14 model enzyme were characterized with regard to the kinetic parameters for antibiotic hydrolysis as well as enzyme expression levels in vivo and protein stability in vitro. The A77V substitution has little effect on the kinetics of oxyimino-cephalosporin hydrolysis, but it stabilizes the CTX-M enzyme and compensates for the loss of stability resulting from the P167S and D240G mutations. The acquisition of global stabilizing mutations, such as A77V, is an important feature in β-lactamase evolution and a common mechanism in protein evolution.

Modulation of the thermostability and substrate specificity of Candida rugosa lipase1 by altering the acyl-binding residue Gly414 at the α-helix-connecting bend

Candida rugosa Lipase1 (LIP1) is widely used in industrial applications. Optimizing its catalytic performance is still a challenging goal for protein engineers. Mutagenesis of key residues in the active site of the enzyme may provide an effective strategy for enhancing stability and altering substrate specificity. In this study, multiple sequence alignment and structural analysis revealed that the acyl-binding residue, Gly414, of LIP1, which is located at a bend connecting α-helixes, was the non-conserved residue in five other isoenzymes. Using saturation mutagenesis, four mutants with improved stability (G414A, G414M, G414H and G414W) were obtained. Compared to the wild type, the best mutant (G414W) exhibited a remarkable 6.5-fold enhancement in half-life at 60 °C and a 14 °C higher T50(15). Its optimum temperature was increased by 15 °C. Simultaneously, G414W displayed a shift in substrate preference from medium-chain to short-chain pNP-ester. Modeling analysis showed that the multiple interactions formed by hydrophobic clusters and hydrogen bonds in the acyl-binding tunnel might lead to the observed thermostability improvement. Additionally, the bulky tryptophan substitution formed a strong steric hindrance to the accommodation of long-chain substrates in the tunnel. These results indicate that the key acyl-binding residues at the α-helix-connecting bend could mediate enzyme stability and catalytic substrate spectra.

Contingency and entrenchment in protein evolution under purifying selection

The phenotypic effect of an allele at one genetic site may depend on alleles at other sites, a phenomenon known as epistasis. Epistasis can profoundly influence the process of evolution in populations and shape the patterns of protein divergence across species. Whereas epistasis between adaptive substitutions has been studied extensively, relatively little is known about epistasis under purifying selection. Here we use computational models of thermodynamic stability in a ligand-binding protein to explore the structure of epistasis in simulations of protein sequence evolution. Even though the predicted effects on stability of random mutations are almost completely additive, the mutations that fix under purifying selection are enriched for epistasis. In particular, the mutations that fix are contingent on previous substitutions: Although nearly neutral at their time of fixation, these mutations would be deleterious in the absence of preceding substitutions. Conversely, substitutions under purifying selection are subsequently entrenched by epistasis with later substitutions: They become increasingly deleterious to revert over time. Our results imply that, even under purifying selection, protein sequence evolution is often contingent on history and so it cannot be predicted by the phenotypic effects of mutations assayed in the ancestral background.

Information flow and protein dynamics: the interplay between nuclear magnetic resonance spectroscopy and molecular dynamics simulations

Proteins participate in information pathways in cells, both as links in the chain of signals, and as the ultimate effectors. Upon ligand binding, proteins undergo conformation and motion changes, which can be sensed by the following link in the chain of information. Nuclear magnetic resonance (NMR) spectroscopy and molecular dynamics (MD) simulations represent powerful tools for examining the time-dependent function of biological molecules. The recent advances in NMR and the availability of faster computers have opened the door to more detailed analyses of structure, dynamics, and interactions. Here we briefly describe the recent applications that allow NMR spectroscopy and MD simulations to offer unique insight into the basic motions that underlie information transfer within and between cells.

Advanced protein formulations

It is well recognized that protein product development is far more challenging than that for small-molecule drugs. The major challenges include inherent sensitivity to different types of stresses during the drug product manufacturing process, high rate of physical and chemical degradation during long-term storage, and enhanced aggregation and/or viscosity at high protein concentrations. In the past decade, many novel formulation concepts and technologies have been or are being developed to address these product development challenges for proteins. These concepts and technologies include use of uncommon/combination of formulation stabilizers, conjugation or fusion with potential stabilizers, site-specific mutagenesis, and preparation of nontraditional types of dosage forms-semiaqueous solutions, nonfreeze-dried solid formulations, suspensions, and other emerging concepts. No one technology appears to be mature, ideal, and/or adequate to address all the challenges. These gaps will likely remain in the foreseeable future and need significant efforts for ultimate resolution.

Water-mediated interactions between trimethylamine-N-oxide and urea

The osmoprotectant trimethylamine-N-oxide (TMAO) interacts with the protein denaturant urea via the hydrogen-bonded water network.

Interface matters: the stiffness route to stability of a thermophilic tetrameric malate dehydrogenase

In this work we investigate by computational means the behavior of two orthologous bacterial proteins, a mesophilic and a thermophilic tetrameric malate dehydrogenase (MalDH), at different temperatures. Namely, we quantify how protein mechanical rigidity at different length- and time-scales correlates to protein thermophilicity as commonly believed. In particular by using a clustering analysis strategy to explore the conformational space of the folded proteins, we show that at ambient conditions and at the molecular length-scale the thermophilic variant is indeed more rigid that the mesophilic one. This rigidification is the result of more efficient inter-domain interactions, the strength of which is further quantified via ad hoc free energy calculations. When considered isolated, the thermophilic domain is indeed more flexible than the respective mesophilic one. Upon oligomerization, the induced stiffening of the thermophilic protein propagates from the interface to the active site where the loop, controlling the access to the catalytic pocket, anchors down via an extended network of ion-pairs. On the contrary in the mesophilic tetramer the loop is highly mobile. Simulations at high temperature, could not re-activate the mobility of the loop in the thermophile. This finding opens questions on the similarities of the binding processes for these two homologues at their optimal working temperature and suggests for the thermophilic variant a possible cooperative role of cofactor/substrate.

γS-crystallin proteins from the Antarctic nototheniid toothfish: a model system for investigating differential resistance to chemical and thermal denaturation

The γS1- and γS2-crystallins, structural eye lens proteins from the Antarctic toothfish (Dissostichus mawsoni), are homologues of the human lens protein γS-crystallin. Although γS1 has the higher thermal stability of the two, it is more susceptible to chemical denaturation by urea. The lower thermodynamic stability of both toothfish crystallins relative to human γS-crystallin is consistent with the current picture of how proteins from organisms endemic to perennially cold environments have achieved low-temperature functionality via greater structural flexibility. In some respects, the sequences of γS1- and γS2-crystallin are typical of psychrophilic proteins; however, their amino acid compositions also reflect their selection for a high refractive index increment. Like their counterparts in the human lens and those of mesophilic fish, both toothfish crystallins are relatively enriched in aromatic residues and methionine and exiguous in aliphatic residues. The sometimes contradictory requirements of selection for cold tolerance and high refractive index make the toothfish crystallins an excellent model system for further investigation of the biophysical properties of structural proteins.

Introducing a salt bridge into the lipase of Stenotrophomonas maltophilia results in a very large increase in thermal stability

High thermostability of enzymes is a prerequisite for their biotechnological applications. An organic solvent-tolerant and cold-active lipase, from the Stenotrophomonas maltophilia, was unstable above 40 °C in previous studies. To increase the enzyme stability, possible hydrogen-bond networks were simulated by the introduction of a salt bridge in a highly flexible region of the protein. Compared with the wild-type lipase, a mutant lipase (G165D and F73R) showed a >900-fold improvement in half-life at 50 °C, with the optimal activity-temperature increasing from 35 to 90 °C. Therefore, the hydrogen-bond strategy is a powerful approach for improving enzyme stability through the introduction of a salt bridge.

Virtual screening on an α-helix to β-strand switchable region of the FGFR2 extracellular domain revealed positive and negative modulators

The secondary structure of some protein segments may vary between α-helix and β-strand. To predict these switchable segments, we have developed an algorithm, Switch-P, based solely on the protein sequence. This algorithm was used on the extracellular parts of FGF receptors. For FGFR2, it predicted that β4 and β5 strands of the third Ig-like domain were highly switchable. These two strands possess a high number of somatic mutations associated with cancer. Analysis of PDB structures of FGF receptors confirmed the switchability prediction for β5. We thus evaluated if compound-driven α-helix/β-strand switching of β5 could modulate FGFR2 signaling. We performed the virtual screening of a library containing 1.4 million of chemical compounds with two models of the third Ig-like domain of FGFR2 showing different secondary structures for β5, and we selected 32 compounds. Experimental testing using proliferation assays with FGF7-stimulated SNU-16 cells and a FGFR2-dependent Erk1/2 phosphorylation assay with FGFR2-transfected L6 cells, revealed activators and inhibitors of FGFR2. Our method for the identification of switchable proteinic regions, associated with our virtual screening approach, provides an opportunity to discover new generation of drugs with under-explored mechanism of action.

Specificity and affinity quantification of flexible recognition from underlying energy landscape topography

Flexibility in biomolecular recognition is essential and critical for many cellular activities. Flexible recognition often leads to moderate affinity but high specificity, in contradiction with the conventional wisdom that high affinity and high specificity are coupled. Furthermore, quantitative understanding of the role of flexibility in biomolecular recognition is still challenging. Here, we meet the challenge by quantifying the intrinsic biomolecular recognition energy landscapes with and without flexibility through the underlying density of states. We quantified the thermodynamic intrinsic specificity by the topography of the intrinsic binding energy landscape and the kinetic specificity by association rate. We found that the thermodynamic and kinetic specificity are strongly correlated. Furthermore, we found that flexibility decreases binding affinity on one hand, but increases binding specificity on the other hand, and the decreasing or increasing proportion of affinity and specificity are strongly correlated with the degree of flexibility. This shows more (less) flexibility leads to weaker (stronger) coupling between affinity and specificity. Our work provides a theoretical foundation and quantitative explanation of the previous qualitative studies on the relationship among flexibility, affinity and specificity. In addition, we found that the folding energy landscapes are more funneled with binding, indicating that binding helps folding during the recognition. Finally, we demonstrated that the whole binding-folding energy landscapes can be integrated by the rigid binding and isolated folding energy landscapes under weak flexibility. Our results provide a novel way to quantify the affinity and specificity in flexible biomolecular recognition.

Flexibility in biomolecular recognition is crucial for the function. Flexibility often leads to moderate binding affinity but high binding specificity, challenging the conventional wisdom that high specificity is guaranteed by high affinity. Currently, understanding of the relationship between affinity and specificity in flexible biomolecular recognition is still obscure, even in a qualitative way. By exploring the intrinsic biomolecular recognition energy landscapes, we provided a novel way to quantify the thermodynamic intrinsic specificity by energy landscape topography and kinetic specificity by association rate. We show quantitatively that flexibility decreases binding affinity while increases binding specificity, and the relative changes in affinity and specificity are strongly correlated with the degree of flexibility. Our results show that more (less) flexibility leads to weaker (stronger) coupling between affinity and specificity. Importantly, we demonstrated that flexibility modulates affinity and specificity through the underlying energy landscape. Our study establishes the quantitative relationship among flexibility, affinity and specificity, bridging the gap between theory and experiments.

Peptidoglycan remodeling by the coordinated action of multispecific enzymes

The peptidoglycan (PG) cell wall constitutes the main defense barrier of bacteria against environmental insults and acts as communication interface. The biochemistry of this macromolecule has been well characterized throughout the years but recent discoveries have unveiled its chemical plasticity under environmental stresses. Non-canonical D-amino acids (NCDAA) are produced and released to the extracellular media by diverse bacteria. Such molecules govern cell wall adaptation to challenging environments through their incorporation into the polymer, a widespread capability among bacteria that reveals the inherent catalytic plasticity of the enzymes involved in the cell wall metabolism. Here, we analyze the recent structural and biochemical characterization of Bsr, a new family of broad spectrum racemases able to generate a wide range of NCDAA. We also discuss the necessity of a coordinated action of PG multispecific enzymes to generate adequate levels of modification in the murein sacculus. Finally, we also highlight how this catalytic plasticity of NCDAA-incorporating enzymes has allowed the development of new revolutionary methodologies for the study of PG modes of growth and in vivo dynamics.

Physicochemical and functional characterization of vaccine antigens and adjuvants

As novel vaccine antigens and adjuvants are being tested in humans, understanding of critical quality attributes essential for eliciting optimal vaccine response and vaccine antigen-adjuvant interactions is pivotal for vaccine safety and eliciting 'protective' immune responses. Therefore, the efforts to better characterize and evaluate vaccine antigen and antigen-adjuvant drug products need to begin very early during the discovery and development phase. In this review, we discuss the importance of characterization of physicochemical and functional properties in vaccine antigen, adjuvant and the final antigen-adjuvant drug product and emphasize the greater need for more extensive understanding of vaccine antigen-adjuvant interactions. We highlight the key parameters and quality attributes that are critical to measure during preclinical and clinical testing of the vaccine and discuss in some detail the technologies, and their limitations, used in analyzing the key physicochemical and functional attributes of vaccine antigen and antigen-adjuvant drug product.

Thermodynamic stability contributes to immunoglobulin specificity

Antigen-binding specificity of immunoglobulins is important for their function in immune defense. However, immune repertoires contain a considerable fraction of immunoglobulins with promiscuous binding behavior, the physicochemical basis of which is not well understood. Evolution of immunoglobulin specificity occurs through iterative processes of mutation and selection, referred to as affinity maturation. Recent studies reveal that some somatic mutations could compromise the thermodynamic stability of the variable regions of immunoglobulins. By integrating this observation with the wealth of data on the evolution of novel enzyme activities, we propose that antibody specificity is linked to the thermodynamic stability of the antigen-binding regions, which provides a quantitative distinction between highly specific and promiscuous antibodies.

Toward in silico biomolecular manipulation through static modes: atomic scale characterization of HIV-1 protease flexibility

Probing biomolecular flexibility with atomic-scale resolution is a challenging task in current computational biology for fundamental understanding and prediction of biomolecular interactions and associated functions. This paper makes use of the static mode method to study HIV-1 protease considered as a model system to investigate the full biomolecular flexibility at the atomic scale, the screening of active site biomechanical properties, the blind prediction of allosteric sites, and the design of multisite strategies to target deformations of interest. Relying on this single calculation run of static modes, we demonstrate that in silico predictive design of an infinite set of complex excitation fields is reachable, thanks to the storage of the static modes in a data bank that can be used to mimic single or multiatom contact and efficiently anticipate conformational changes arising from external stimuli. All along this article, we compare our results to data previously published and propose a guideline for efficient, predictive, and custom in silico experiments.

Kinetics and thermodynamics of membrane protein folding

Understanding protein folding has been one of the great challenges in biochemistry and molecular biophysics. Over the past 50 years, many thermodynamic and kinetic studies have been performed addressing the stability of globular proteins. In comparison, advances in the membrane protein folding field lag far behind. Although membrane proteins constitute about a third of the proteins encoded in known genomes, stability studies on membrane proteins have been impaired due to experimental limitations. Furthermore, no systematic experimental strategies are available for folding these biomolecules in vitro. Common denaturing agents such as chaotropes usually do not work on helical membrane proteins, and ionic detergents have been successful denaturants only in few cases. Refolding a membrane protein seems to be a craftsman work, which is relatively straightforward for transmembrane β-barrel proteins but challenging for α-helical membrane proteins. Additional complexities emerge in multidomain membrane proteins, data interpretation being one of the most critical. In this review, we will describe some recent efforts in understanding the folding mechanism of membrane proteins that have been reversibly refolded allowing both thermodynamic and kinetic analysis. This information will be discussed in the context of current paradigms in the protein folding field.

The molecular basis of conformational instability of the ecdysone receptor DNA binding domain studied by in silico and in vitro experiments

The heterodimer of the ecdysone receptor (EcR) and ultraspiracle (Usp), members of the nuclear receptors superfamily, regulates gene expression associated with molting and metamorphosis in insects. The DNA binding domains (DBDs) of the Usp and EcR play an important role in their DNA-dependent heterodimerization. Analysis of the crystal structure of the UspDBD/EcRDBD heterocomplex from Drosophila melanogaster on the hsp27 gene response element, suggested an appreciable similarity between both DBDs. However, the chemical denaturation experiments showed a categorically lower stability for the EcRDBD in contrast to the UspDBD. The aim of our study was an elucidation of the molecular basis of this intriguing instability. Toward this end, we mapped the EcRDBD amino acid sequence positions which have an impact on the stability of the EcRDBD. The computational protein design and in vitro analyses of the EcRDBD mutants indicate that non-conserved residues within the α-helix 2, forming the EcRDBD hydrophobic core, represent a specific structural element that contributes to instability. In particular, the L58 appears to be a key residue which differentiates the hydrophobic cores of UspDBD and EcRDBD and is the main reason for the low stability of the EcRDBD. Our results might serve as a benchmark for further studies of the intricate nature of the EcR molecule.

Binding patterns and structure-affinity relationships of food azo dyes with lysozyme: a multitechnique approach

Food dyes serve to beguile consumers: they are often used to imitate the presence of healthful, colorful food produce such as fruits and vegetables. But considering the hurtful impact of these chemicals on the human body, it is time to thoroughly uncover the toxicity of these food dyes at the molecular level. In the present contribution, we have examined the molecular reactions of protein lysozyme with model food azo compound Color Index (C.I.) Acid Red 2 and its analogues C.I. Acid Orange 52, Solvent Yellow 2, and the core structure of azobenzene using a combination of biophysical methods at physiological conditions. Fluorescence, circular dichroism (CD), time-resolved fluorescence, UV-vis absorption as well as computer-aided molecular modeling were used to analyze food dye affinity, binding mode, energy transfer, and the effects of food dye complexation on lysozyme stability and conformation. Fluorescence emission spectra indicate complex formation at 10(-5) M dye concentration, and this corroborates time-resolved fluorescence results showing the diminution in the tryptophan (Trp) fluorescence mainly via a static type (KSV = 1.505 × 10(4) M(-1)) and Förster energy transfer. Structural analysis displayed the participation of several amino acid residues in food dye protein adducts, with hydrogen bonds, π-π and cation-π interactions, but the conformation of lysozyme was unchanged in the process, as derived from fluorescence emission, far-UV CD, and synchronous fluorescence spectra. The overall affinity of food dye is 10(4) M(-1) and there exists only one kind of binding domain in protein for food dye. These data are consistent with hydrophobic probe 8-anilino-1-naphthalenesulfonic acid (ANS) displacement, and molecular modeling manifesting the food dye binding patch was near to Trp-62 and Trp-63 residues of lysozyme. On the basis of the computational analyses, we determine that the type of substituent on the azobenzene structure has a powerful influence on the toxicity of food dyes. Results from this work testify that model protein, though an indirect method, provides a more comprehensive profile of the essence of toxicity evaluation of food dyes.

Inference of structure ensembles of flexible biomolecules from sparse, averaged data

We present the theoretical foundations of a general principle to infer structure ensembles of flexible biomolecules from spatially and temporally averaged data obtained in biophysical experiments. The central idea is to compute the Kullback-Leibler optimal modification of a given prior distribution with respect to the experimental data and its uncertainty. This principle generalizes the successful inferential structure determination method and recently proposed maximum entropy methods. Tractability of the protocol is demonstrated through the analysis of simulated nuclear magnetic resonance spectroscopy data of a small peptide.

Engineering proteins for thermostability through rigidifying flexible sites

Engineering proteins for thermostability is an exciting and challenging field since it is critical for broadening the industrial use of recombinant proteins. Thermostability of proteins arises from the simultaneous effect of several forces such as hydrophobic interactions, disulfide bonds, salt bridges and hydrogen bonds. All of these interactions lead to decreased flexibility of polypeptide chain. Structural studies of mesophilic and thermophilic proteins showed that the latter need more rigid structures to compensate for increased thermal fluctuations. Hence flexibility can be an indicator to pinpoint weak spots for enhancing thermostability of enzymes. A strategy has been proven effective in enhancing proteins' thermostability with two steps: predict flexible sites of proteins firstly and then rigidify these sites. We refer to this approach as rigidify flexible sites (RFS) and give an overview of such a method through summarizing the methods to predict flexibility of a protein, the methods to rigidify residues with high flexibility and successful cases regarding enhancing thermostability of proteins using RFS.

Differential binding of RhoA, RhoB, and RhoC to protein kinase C-related kinase (PRK) isoforms PRK1, PRK2, and PRK3: PRKs have the highest affinity for RhoB

Protein kinase C-related kinases (PRKs) are members of the protein kinase C superfamily of serine-threonine kinases and can be activated by binding to members of the Rho family of GTPases via a Rho-binding motif known as an HR1 domain. Three tandem HR1 domains reside at the N-terminus of the PRKs. We have assessed the ability of the HR1a and HR1b domains from the three PRK isoforms (PRK1, PRK2, and PRK3) to interact with the three Rho isoforms (RhoA, RhoB, and RhoC). The affinities of RhoA and RhoC for a construct encompassing both PRK1 HR1 domains were similar to those for the HR1a domain alone, suggesting that these interactions are mediated solely by the HR1a domain. The affinities of RhoB for both the PRK1 HR1a domain and the HR1ab didomain were higher than those of RhoA or RhoC. RhoB also bound more tightly to the didomain than to the HR1a domain alone, implicating the HR1b domain in the interaction. As compared with PRK1 HR1 domains, PRK2 and PRK3 domains bind less well to all Rho isoforms. Uniquely, however, the PRK3 domains display a specificity for RhoB that requires both the C-terminus of RhoB and the PRK3 HR1b domain. The thermal stability of the HR1a and HR1b domains was also investigated. The PRK2 HR1a domain was found to be the most thermally stable, while PRK2 HR1b, PRK3 HR1a, and PRK3 HR1b domains all exhibited lower melting temperatures, similar to that of the PRK1 HR1a domain. The lower thermal stability of the PRK2 and PRK3 HR1b domains may impart greater flexibility, driving their ability to interact with Rho isoforms.

Simplicity within the complexity: bilateral impact of DMSO on the functional and unfolding patterns of α-chymotrypsin

New understanding of the fundamental links between protein stability, conformational flexibility and function, can be gained through synergic studies on their catalytic and folding/unfolding properties under the influence of stabilizing/destabilizing additives. We explored an impact of dimethyl sulfoxide (DMSO), the moderate effector of multilateral action, on the kinetic (functional) and thermodynamic (thermal unfolding) patterns of a hydrolytic enzyme, α-chymotrypsin (α-CT), over a wide range of additive concentrations, 0-70% (v/v). Both the calorimetric and kinetic data exhibited rich behavior pointing to the complex interplay of global/local stability (and flexibility) patterns. The complex action of DMSO is explained through the negative and positive preferential solvation motifs that prevail for the extreme opposite, native-like and unfolded states, respectively, implying essential stabilization of compact domains by enhancement of interfacial water networks and destabilization of a flexible active site by direct binding of DMSO to the unoccupied specific positions intended for elongated polypeptide substrates.

Computer-Aided Protein Directed Evolution: a Review of Web Servers, Databases and other Computational Tools for Protein Engineering

The combination of computational and directed evolution methods has proven a winning strategy for protein engineering. We refer to this approach as computer-aided protein directed evolution (CAPDE) and the review summarizes the recent developments in this rapidly growing field. We will restrict ourselves to overview the availability, usability and limitations of web servers, databases and other computational tools proposed in the last five years. The goal of this review is to provide concise information about currently available computational resources to assist the design of directed evolution based protein engineering experiment.