Electrostatic contributions to protein stability and folding energy

Screening of natural epigenetic modifiers for managing glycemic memory and diabetic nephropathy

Short hyperglycaemic episodes trigger metabolic memory (MM) in which managing hyperglycaemia alone is not enough to tackle the progression of Diabetic nephropathy on the epigenetic axis. We used a structural similarity search approach to identify phytochemicals similar to natural epigenetic modifiers and docked with SIRT1 protein and did ADME studies. We found that UMB was 84.3% similar to esculetin. Upon docking, we found that UMB had a binding energy of -9.2 kcal/mol while the standard ligand had -11.8 kcal/mol. ADME showed UMB to be a good lead. 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay showed it to be a good antioxidant with IC50 of 107 µg/mL and MTT stands for 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) showed that it does not promote cell death. Oxidative biomarkers in vitro showed UMB was able to ameliorate glycemic memory induced by high glucose. Western blot revealed decreased histone acetylation under hyperglycaemic conditions and upon treatment with UMB along with DR, its levels increased. This led us to check our hypothesis of whether concomitant diet reversal (DR) together with UMB can alleviate high-fat diet-induced metabolic memory and diabetic nephropathy (DN) in SD rats. UMB was able to decrease blood glucose, lipid, renal, and liver profile concluding UMB was able to ameliorate DN and MM by increasing the histone acetylation level.

Structure and Mutations of SARS-CoV-2 Spike Protein: A Focused Overview

The spike protein (S-protein) of SARS-CoV-2, the protein that enables the virus to infect human cells, is the basis for many vaccines and a hotspot of concerning virus evolution. Here, we discuss the outstanding progress in structural characterization of the S-protein and how these structures facilitate analysis of virus function and evolution. We emphasize the differences in reported structures and that analysis of structure-function relationships is sensitive to the structure used. We show that the average residue solvent exposure in nearly complete structures is a good descriptor of open vs closed conformation states. Because of structural heterogeneity of functionally important surface-exposed residues, we recommend using averages of a group of high-quality protein structures rather than a single structure before reaching conclusions on specific structure-function relationships. To illustrate these points, we analyze some significant chemical tendencies of prominent S-protein mutations in the context of the available structures. In the discussion of new variants, we emphasize the selectivity of binding to ACE2 vs prominent antibodies rather than simply the antibody escape or ACE2 affinity separately. We note that larger chemical changes, in particular increased electrostatic charge or side-chain volume of exposed surface residues, are recurring in mutations of concern, plausibly related to adaptation to the negative surface potential of human ACE2. We also find indications that the fixated mutations of the S-protein in the main variants are less destabilizing than would be expected on average, possibly pointing toward a selection pressure on the S-protein. The richness of available structures for all of these situations provides an enormously valuable basis for future research into these structure-function relationships.

α1 Subunit Histidine 55 at the Interface between Extracellular and Transmembrane Domains Affects Preactivation and Desensitization of the GABAA Receptor

The GABA_A receptor is a member of the Cys-loop family and plays a crucial role in the adult mammalian brain inhibition. Although the static structure of this receptor is emerging, the molecular mechanisms underlying its conformational transitions remain elusive. It is known that in the Cys-loop receptors, the interface between extracellular and transmembrane domains plays a key role in transmitting the “activation wave” down to the channel gate in the pore. It has been previously reported that histidine 55 (H55), located centrally at the interfacial β1−β2 loop of the α₁ subunit, is important in the receptor activation, but it is unknown which specific gating steps it is affecting. In the present study, we addressed this issue by taking advantage of the state-of-the-art macroscopic and single-channel recordings together with extensive modeling. Considering that H55 is known to affect the local electrostatic landscape and because it is neighbored by two negatively charged aspartates, a well conserved feature in the α subunits, we considered substitution with negative (E) and positive (K) residues. We found that these mutations markedly affected the receptor gating, altering primarily preactivation and desensitization transitions. Importantly, opposite effects were observed for these two mutations strongly suggesting involvement of electrostatic interactions. Single-channel recordings suggested also a minor effect on opening/closing transitions which did not depend on the electric charge of the substituting amino acid. Altogether, we demonstrate that H55 mutations affect primarily preactivation and desensitization most likely by influencing local electrostatic interactions at the receptor interface.

Protein electrostatics: From computational and structural analysis to discovery of functional fingerprints and biotechnological design

Computationally driven engineering of proteins aims to allow them to withstand an extended range of conditions and to mediate modified or novel functions. Therefore, it is crucial to the biotechnological industry, to biomedicine and to afford new challenges in environmental sciences, such as biocatalysis for green chemistry and bioremediation. In order to achieve these goals, it is important to clarify molecular mechanisms underlying proteins stability and modulating their interactions. So far, much attention has been given to hydrophobic and polar packing interactions and stability of the protein core. In contrast, the role of electrostatics and, in particular, of surface interactions has received less attention. However, electrostatics plays a pivotal role along the whole life cycle of a protein, since early folding steps to maturation, and it is involved in the regulation of protein localization and interactions with other cellular or artificial molecules. Short- and long-range electrostatic interactions, together with other forces, provide essential guidance cues in molecular and macromolecular assembly. We report here on methods for computing protein electrostatics and for individual or comparative analysis able to sort proteins by electrostatic similarity. Then, we provide examples of electrostatic analysis and fingerprints in natural protein evolution and in biotechnological design, in fields as diverse as biocatalysis, antibody and nanobody engineering, drug design and delivery, molecular virology, nanotechnology and regenerative medicine.

Electrostatic control of calcineurin's intrinsically-disordered regulatory domain binding to calmodulin

Calcineurin (CaN) is a serine/threonine phosphatase that regulates a variety of physiological and pathophysiological processes in mammalian tissue. The calcineurin (CaN) regulatory domain (RD) is responsible for regulating the enzyme's phosphatase activity, and is believed to be highly-disordered when inhibiting CaN, but undergoes a disorder-to-order transition upon diffusion-limited binding with the regulatory protein calmodulin (CaM). The prevalence of polar and charged amino acids in the regulatory domain (RD) suggests electrostatic interactions are involved in mediating calmodulin (CaM) binding, yet the lack of atomistic-resolution data for the bound complex has stymied efforts to probe how the RD sequence controls its conformational ensemble and long-range attractions contribute to target protein binding. In the present study, we investigated via computational modeling the extent to which electrostatics and structural disorder facilitate CaM/CaN association kinetics. Specifically, we examined several RD constructs that contain the CaM binding region (CAMBR) to characterize the roles of electrostatics versus conformational diversity in controlling diffusion-limited association rates, via microsecond-scale molecular dynamics (MD) and Brownian dynamic (BD) simulations. Our results indicate that the RD amino acid composition and sequence length influence both the dynamic availability of conformations amenable to CaM binding, as well as long-range electrostatic interactions to steer association. These findings provide intriguing insight into the interplay between conformational diversity and electrostatically-driven protein-protein association involving CaN, which are likely to extend to wide-ranging diffusion-limited processes regulated by intrinsically-disordered proteins.

Long-Range Modulations of Electric Fields in Proteins

Electrostatic interactions are essential for controlling the protein structure and function. Whereas so far experimental and theoretical efforts focused on the effect of local electrostatics, this work aims at elucidating the long-range modulation of electric fields in proteins upon binding to charged surfaces. The study is based on cytochrome c (Cytc) variants carrying nitrile reporters for the vibrational Stark effect that are incorporated into the protein via genetic engineering and chemical modification. The Cytc variants were thoroughly characterized with respect to possible structural perturbations due to labeling. For the proteins in solution, the relative hydrogen bond occupancy and the calculated electric fields, both obtained from molecular dynamics (MD) simulations, and the experimental nitrile stretching frequencies were used to develop a relationship for separating hydrogen-bonding and non-hydrogen-bonding electric field effects. This relationship provides an excellent description for the stable Cytc variants in solution. For the proteins bound to Au electrodes coated with charged self-assembled monolayers (SAMs), the underlying MD simulations can only account for the electric field changes Δ E_ads due to the formation of the electrostatic SAM-Cytc complexes but not for the additional contribution, Δ E_int, representing the consequences of the potential drops over the electrode/SAM/protein interfaces. Both Δ E_ads and Δ E_int, determined at distances between 20 and 30 Å with respect to the SAM surface, are comparable in magnitude to the non-hydrogen-bonding electric field in the unbound protein. This long-range modulation of the internal electric field may be of functional relevance for proteins in complexes with partner proteins (Δ E_ads) and attached to membranes (Δ E_ads + Δ E_int).

Electrostatic Interactions in Protein Structure, Folding, Binding, and Condensation

Charged and polar groups, through forming ion pairs, hydrogen bonds, and other less specific electrostatic interactions, impart important properties to proteins. Modulation of the charges on the amino acids, e.g., by pH and by phosphorylation and dephosphorylation, have significant effects such as protein denaturation and switch-like response of signal transduction networks. This review aims to present a unifying theme among the various effects of protein charges and polar groups. Simple models will be used to illustrate basic ideas about electrostatic interactions in proteins, and these ideas in turn will be used to elucidate the roles of electrostatic interactions in protein structure, folding, binding, condensation, and related biological functions. In particular, we will examine how charged side chains are spatially distributed in various types of proteins and how electrostatic interactions affect thermodynamic and kinetic properties of proteins. Our hope is to capture both important historical developments and recent experimental and theoretical advances in quantifying electrostatic contributions of proteins.

Fast coarse-grained model for RNA titration

A new numerical scheme for RNA (ribonucleic acid) titration based on the Debye-Hückel framework for the salt description is proposed in an effort to reduce the computational costs for further applications to study protein-RNA systems. By means of different sets of Monte Carlo simulations, we demonstrated that this new scheme is able to correctly reproduce the experimental titration behavior and salt pK_a shifts. In comparison with other theoretical approaches, similar or even better outcomes are achieved at much lower computational costs. The model was tested on the lead-dependent ribozyme, the branch-point helix, and the domain 5 from Azotobacter vinelandii Intron 5.

An expanded genetic code for probing the role of electrostatics in enzyme catalysis by vibrational Stark spectroscopy

BACKGROUND

To find experimental validation for electrostatic interactions essential for catalytic reactions represents a challenge due to practical limitations in assessing electric fields within protein structures.

SCOPE OF REVIEW

This review examines the applications of non-canonical amino acids (ncAAs) as genetically encoded probes for studying the role of electrostatic interactions in enzyme catalysis.

MAJOR CONCLUSIONS

ncAAs constitute sensitive spectroscopic probes to detect local electric fields by exploiting the vibrational Stark effect (VSE) and thus have the potential to map the protein electrostatics.

GENERAL SIGNIFICANCE

Mapping the electrostatics in proteins will improve our understanding of natural catalytic processes and, in beyond, will be helpful for biocatalyst engineering. This article is part of a Special Issue entitled "Biochemistry of Synthetic Biology - Recent Developments" Guest Editor: Dr. Ilka Heinemann and Dr. Patrick O'Donoghue.

Refining the treatment of membrane proteins by coarse-grained models

Obtaining a quantitative description of the membrane proteins stability is crucial for understanding many biological processes. However the advance in this direction has remained a major challenge for both experimental studies and molecular modeling. One of the possible directions is the use of coarse-grained models but such models must be carefully calibrated and validated. Here we use a recent progress in benchmark studies on the energetics of amino acid residue and peptide membrane insertion and membrane protein stability in refining our previously developed coarse-grained model (Vicatos et al., Proteins 2014;82:1168). Our refined model parameters were fitted and/or tested to reproduce water/membrane partitioning energetics of amino acid side chains and a couple of model peptides. This new model provides a reasonable agreement with experiment for absolute folding free energies of several β-barrel membrane proteins as well as effects of point mutations on a relative stability for one of those proteins, OmpLA. The consideration and ranking of different rotameric states for a mutated residue was found to be essential to achieve satisfactory agreement with the reference data.

Two misfolding routes for the prion protein around pH 4.5

Using molecular dynamics simulations, we show that the prion protein (PrP) exhibits a dual behavior, with two possible transition routes, upon protonation of H187 around pH 4.5, which mimics specific conditions encountered in endosomes. Our results suggest a picture in which the protonated imidazole ring of H187 experiences an electrostatic repulsion with the nearby guanidinium group of R136, to which the system responds by pushing either H187 or R136 sidechains away from their native cavities. The regions to which H187 and R136 are linked, namely the C-terminal part of H2 and the loop connecting S1 to H1, respectively, are affected in a different manner depending on which pathway is taken. Specific in vivo or in vitro conditions, such as the presence of molecular chaperones or a particular experimental setup, may favor one transition pathway over the other, which can result in very different [Formula: see text] monomers. This has some possible connections with the observation of various fibril morphologies and the outcome of prion strains. In addition, the finding that the interaction of H187 with R136 is a weak point in mammalian PrP is supported by the absence of the [Formula: see text] residue pair in non-mammalian species that are known to be resistant to prion diseases.

Correlated electrostatic mutations provide a reservoir of stability in HIV protease

HIV protease, an aspartyl protease crucial to the life cycle of HIV, is the target of many drug development programs. Though many protease inhibitors are on the market, protease eventually evades these drugs by mutating at a rapid pace and building drug resistance. The drug resistance mutations, called primary mutations, are often destabilizing to the enzyme and this loss of stability has to be compensated for. Using a coarse-grained biophysical energy model together with statistical inference methods, we observe that accessory mutations of charged residues increase protein stability, playing a key role in compensating for destabilizing primary drug resistance mutations. Increased stability is intimately related to correlations between electrostatic mutations – uncorrelated mutations would strongly destabilize the enzyme. Additionally, statistical modeling indicates that the network of correlated electrostatic mutations has a simple topology and has evolved to minimize frustrated interactions. The model's statistical coupling parameters reflect this lack of frustration and strongly distinguish like-charge electrostatic interactions from unlike-charge interactions for of the most significantly correlated double mutants. Finally, we demonstrate that our model has considerable predictive power and can be used to predict complex mutation patterns, that have not yet been observed due to finite sample size effects, and which are likely to exist within the larger patient population whose virus has not yet been sequenced.

HIV is incurable because its enzymes evolve rapidly by developing resistance mutations to retroviral inhibitors. Most of these mutations work synergistically, but the biophysical basis behind their cooperation is not well understood. Our work addresses these important issues by bridging the gap between the statistical modeling of HIV protease subtype B sequences with the energetics of mutations involving charged amino acids by showing that electrostatic stability is intimately related to correlations. Moreover, we demonstrate that our statistical model has considerable predictive power and can be used to predict complex mutation patterns that have not yet been observed due to the finite sizes of the current sequence databases. In other words, as the database size increases, our model has the ability to predict the identities of the high probability mutations patterns, which are more likely to be observed. Knowing which currently unobserved mutations are more likely to be observed can be very advantageous in combating the disease.

Reactions of dipolar bio-molecules in nano-capsules--example of folding-unfolding process

The confinement of chemical reactions in nano-capsules can lead to a dramatic effect on the equilibrium constant of these latter. Indeed, capillary effects due to the curvature and surface energy of nano-capsules can alter in a noticeable way the evolution of reactions occurring within. Nano-encapsulation of bio-materials has attracted lately wide interest from the scientific community because of the great potential of its applications in biomedical areas and targeted therapies. The present paper focuses one's attention on alterations of conformation mechanisms due to extremely confining and interacting solvated dipolar macromolecules at their isoelectric point. As a specific example studied here, the folding-unfolding reaction of proteins (particularly RNase A and creatine kinase CK) is drastically changed when encapsulated in solid inorganic hollow nano-capsules. The effects demonstrated in this work can be extended to a wide variety of nano-encapsulation situations. The design and sizing of nano-capsules can even make use of the effects shown in the present study to achieve better and more effective encapsulation.

The linear interaction energy method for the prediction of protein stability changes upon mutation

The coupling of protein energetics and sequence changes is a critical aspect of computational protein design, as well as for the understanding of protein evolution, human disease, and drug resistance. To study the molecular basis for this coupling, computational tools must be sufficiently accurate and computationally inexpensive enough to handle large amounts of sequence data. We have developed a computational approach based on the linear interaction energy (LIE) approximation to predict the changes in the free-energy of the native state induced by a single mutation. This approach was applied to a set of 822 mutations in 10 proteins which resulted in an average unsigned error of 0.82 kcal/mol and a correlation coefficient of 0.72 between the calculated and experimental ΔΔG values. The method is able to accurately identify destabilizing hot spot mutations; however, it has difficulty in distinguishing between stabilizing and destabilizing mutations because of the distribution of stability changes for the set of mutations used to parameterize the model. In addition, the model also performs quite well in initial tests on a small set of double mutations. On the basis of these promising results, we can begin to examine the relationship between protein stability and fitness, correlated mutations, and drug resistance.

Methyl groups of trimethylamine N-oxide orient away from hydrophobic interfaces

The molecular orientation of trimethylamine N-oxide (TMAO), a powerful protein stabilizer, was explored at aqueous/hydrophobic interfaces using vibrational sum frequency spectroscopy (VSFS). The systems studied included the octadecyltrichlorosilane (OTS)/water interface, which represents an aqueous solution in direct contact with a hydrophobic medium. Surprisingly, the measurements revealed that the methyl groups of TMAO pointed into the aqueous phase and away from the OTS. This orientation may arise from the more hydrophilic nature of methyl groups attached to a strongly electron-withdrawing atom such as a quaternary nitrogen. Additional studies were performed at the air/water interface. This interface showed a high degree of TMAO alignment, but the dangling OH from water was present even at 5 M TAMO. Moreover, the addition of this osmolyte modestly increased the surface tension of the interface. This meant that this species was somewhat depleted at the interface compared to the bulk solution. These findings may have implications for the stabilizing effect of TMAO on proteins. Specifically, the strong hydration required for the methyl groups as well as the oxide moiety should be responsible for the osmolyte's depletion from hydrophobic/aqueous interfaces. Such depletion effects should help stabilize proteins in their folded and native conformations on entropic grounds, although orientational effects may play an additional role.

Nonlocal continuum electrostatic theory predicts surprisingly small energetic penalties for charge burial in proteins

We study the energetics of burying charges, ion pairs, and ionizable groups in a simple protein model using nonlocal continuum electrostatics. Our primary finding is that the nonlocal response leads to markedly reduced solvent screening, comparable to the use of application-specific protein dielectric constants. Employing the same parameters as used in other nonlocal studies, we find that for a sphere of radius 13.4 Å containing a single +1e charge, the nonlocal solvation free energy varies less than 18 kcal/mol as the charge moves from the surface to the center, whereas the difference in the local Poisson model is ∼35 kcal/mol. Because an ion pair (salt bridge) generates a comparatively more rapidly varying Coulomb potential, energetics for salt bridges are even more significantly reduced in the nonlocal model. By varying the central parameter in nonlocal theory, which is an effective length scale associated with correlations between solvent molecules, nonlocal-model energetics can be varied from the standard local results to essentially zero; however, the existence of the reduction in charge-burial penalties is quite robust to variations in the protein dielectric constant and the correlation length. Finally, as a simple exploratory test of the implications of nonlocal response, we calculate glutamate pK(a) shifts and find that using standard protein parameters (ε(protein) = 2-4), nonlocal results match local-model predictions with much higher dielectric constants. Nonlocality may, therefore, be one factor in resolving discrepancies between measured protein dielectric constants and the model parameters often used to match titration experiments. Nonlocal models may hold significant promise to deepen our understanding of macromolecular electrostatics without substantially increasing computational complexity.

Simulating electrostatic energies in proteins: perspectives and some recent studies of pKas, redox, and other crucial functional properties

Electrostatic energies provide what is arguably the most effective tool for structure-function correlation of biological molecules. Here, we provide an overview of the current state-of-the-art simulations of electrostatic energies in macromolecules, emphasizing the microscopic perspective but also relating it to macroscopic approaches. We comment on the convergence issue and other problems of the microscopic models and the ways of keeping the microscopic physics while moving to semi-macroscopic directions. We discuss the nature of the protein dielectric "constants" reiterating our long-standing point that the dielectric "constants" in semi-macroscopic models depend on the definition and the specific treatment. The advances and the challenges in the field are illustrated considering different functional properties including pK(a)'s, redox potentials, ion and proton channels, enzyme catalysis, ligand binding, and protein stability. We emphasize the microscopic overcharging approach for studying pK(a) 's of internal groups in proteins and give a demonstration of power of this approach. We also emphasize recent advances in coarse grained models with a physically based electrostatic treatment and provide some examples including further directions in treating voltage activated ion channels.

Coarse grained model for exploring voltage dependent ion channels

The relationship between the membrane voltage and the gating of voltage activated ion channels and other systems have been a problem of great current interest. Unfortunately, reliable molecular simulations of external voltage effects present a major challenge, since meaningful converging microscopic simulations are not yet available and macroscopic treatments involve major uncertainties in terms of the dielectric used and other key features. This work extends our coarse grained (CG) model to simulations of membrane/protein systems under external potential. Special attention is devoted to a consistent modeling of the effect of external potential due to the electrodes, emphasizing semimacroscopic description of the electrolytes in the solution regions between the membranes and the electrodes, as well as the coupling between the combined potential from the electrodes plus the electrolytes and the protein ionized groups. We also provide a clear connection to microscopic treatment of the electrolytes and thus can explore possible conceptual problems that are hard to resolve by other current approaches. For example, we obtain a clear description of the charge distribution in the entire electrolyte system, including near the electrodes in membrane/electrodes systems (where continuum models do not seem to provide the relevant results). Furthermore, the present treatment provides an insight on the distribution of the electrolyte charges before and after equilibration across the membrane, and thus on the nature of the gating charge. The different aspects of the model have been carefully validated by considering problems ranging for the simple Debye-Huckel, and the Gouy-Chapman models to the evaluation of the electrolyte distribution between two electrodes, as well as the effect of extending the simulation system by periodic replicas. Overall the clear connection to microscopic descriptions combined with the power of the CG modeling seems to offer a powerful tool for exploring the balance between the protein conformational energy and the interaction with the external potential in voltage activated channels. To illustrate these features we present a preliminary study of the gating charge in the voltage activated Kv1.2 channel, using the actual change in the electrolyte charge distribution rather than the conventional macroscopic estimate. We also discuss other special features of the model, which include the ability to capture the effect of changes in the protonation states of the protein residues during the close to open voltage induced transition. This article is part of a Special Issue entitled: Membrane protein structure and function.

Electrostatics in proteins and protein-ligand complexes

Accurate computational methods for predicting electrostatic energies are of major importance for our understanding of protein energetics in general for computer-aided drug design as well as for the design of novel biocatalysts and protein therapeutics. Electrostatic energies are of particular importance in such applications as virtual screening, drug design and protein-protein docking due to the high charge density of protein ligands and small-molecule drugs, and the frequent protonation state changes observed when drugs bind to their protein targets. Therefore, the development of a reliable and fast algorithm for the evaluation of electrostatic free energies, as an important contributor to the overall protein energy function, has been the focus for many scientists over the past three decades. In this review we describe the current state-of-the-art in modeling electrostatic effects in proteins and protein-ligand complexes. We focus mainly on the merits and drawbacks of the continuum methodology, and speculate on future directions in refining algorithms for calculating electrostatic energies in proteins using experimental data.

Explicit Water Models Affect the Specific Solvation and Dynamics of Unfolded Peptides While the Conformational Behavior and Flexibility of Folded Peptides Remain Intact

Conventional molecular dynamics simulations on 50 ns to 1 μs time scales were used to study the effects of explicit solvent models on the conformational behavior and solvation of two oligopeptide solutes: α-helical EK-peptide (14 amino acids) and a β-hairpin chignolin (10 amino acids). The widely used AMBER force fields (ff99, ff99SB, and ff03) were combined with four of the most commonly used explicit solvent models (TIP3P, TIP4P, TIP5P, and SPC/E). Significant differences in the specific solvation of chignolin among the studied water models were identified. Chignolin was highly solvated in TIP5P, whereas reduced specific solvation was found in the TIP4P, SPC/E, and TIP3P models for kinetic, thermodynamic, and both kinetic and thermodynamic reasons, respectively. The differences in specific solvation did not influence the dynamics of structured parts of the folded peptide. However, substantial differences between TIP5P and the other models were observed in the dynamics of unfolded chignolin, stability of salt bridges, and specific solvation of the backbone carbonyls of EK-peptide. Thus, we conclude that the choice of water model may affect the dynamics of flexible parts of proteins that are solvent-exposed. On the other hand, all water models should perform similarly for well-structured folded protein regions. The merits of the TIP3P model include its high and overestimated mobility, which accelerates simulation processes and thus effectively increases sampling.

On the energetics of translocon-assisted insertion of charged transmembrane helices into membranes

The understanding of the mechanism of insertion of transmembrane (TM) helixes through the translocon presents a major open challenge. Although the experimental information about the partition of the inserted helices between the membrane and the solution contains crucial information about this process, it is not clear how to extract this information. In particular, it is not clear how to rationalize the small apparent insertion energy, ΔG(app), of an ionized residue in the center of a TM helix. Here we explore the nature of the insertion energies, asking what should be the value of these parameters if their measurements represent equilibrium conditions. This is done using a coarse-grained model with advanced electrostatic treatment. Estimating the energetics of ionized arginine of a TM helix in the presence of neighboring helixes or the translocon provides a rationale for the observed ΔG(app) of ionized residues. It is concluded that the apparent insertion free energy of TM with charged residues reflects probably more than just the free energy of moving the isolate single helix from water into the membrane. The present approach should be effective not only in exploring the mechanism of the operation of the translocon but also for studies of other membrane proteins.

Putative one-pot prebiotic polypeptides with ribonucleolytic activity

KIA7, a peptide with a highly restricted set of amino acids (Lys, Ile, Ala, Gly and Tyr), adopts a specifically folded structure. Some amino acids, including Lys, Ile, Ala, Gly and His, form under the same putative prebiotic conditions, whereas different conditions are needed for producing Tyr, Phe and Trp. Herein, we report the 3D structure and conformational stability of the peptide KIA7H, which is composed of only Lys, Ile, Ala, Gly and His. When the imidazole group is neutral, this 20-mer peptide adopts a four-helix bundle with a specifically packed hydrophobic core. Therefore, one-pot prebiotic proteins with well-defined structures might have arisen early in chemical evolution. The Trp variant, KIA7W, was also studied. It adopts a 3D structure similar to that of KIA7H and its previously studied Tyr and Phe variants, but is remarkably more stable. When tested for ribonucleolytic activity, KIA7H, KIA7W and even short, unstructured peptides rich in His and Lys, in combination with Mg(++), Mn(++) or Ni(++) (but not Cu(++), Zn(++) or EDTA) specifically cleave the single-stranded region in an RNA stem-loop. This suggests that prebiotic peptide-divalent cation complexes with ribonucleolytic activity might have co-inhabited the RNA world.

Multiscale simulations of protein landscapes: using coarse-grained models as reference potentials to full explicit models

Evaluating the free-energy landscape of proteins and the corresponding functional aspects presents a major challenge for computer simulation approaches. This challenge is due to the complexity of the landscape and the enormous computer time needed for converging simulations. The use of simplified coarse-grained (CG) folding models offers an effective way of sampling the landscape but such a treatment, however, may not give the correct description of the effect of the actual protein residues. A general way around this problem that has been put forward in our early work (Fan et al., Theor Chem Acc 1999;103:77-80) uses the CG model as a reference potential for free-energy calculations of different properties of the explicit model. This method is refined and extended here, focusing on improving the electrostatic treatment and on demonstrating key applications. These applications include: evaluation of changes of folding energy upon mutations, calculations of transition-states binding free energies (which are crucial for rational enzyme design), evaluations of catalytic landscape, and evaluations of the time-dependent responses to pH changes. Furthermore, the general potential of our approach in overcoming major challenges in studies of structure function correlation in proteins is discussed.

Effective approach for calculations of absolute stability of proteins using focused dielectric constants

The ability to predict the absolute stability of proteins based on their corresponding sequence and structure is a problem of great fundamental and practical importance. In this work, we report an extensive, refinement and validation of our recent approach (Roca et al., FEBS Lett 2007;581:2065-2071) for predicting absolute values of protein stability DeltaG(fold). This approach employs the semimacroscopic protein dipole Langevin dipole method in its linear response approximation version (PDLD/S-LRA) while using the best fitted values of the dielectric constants epsilon'(p) and epsilon'(eff) for the self energy and charge-charge interactions, respectively. The method is validated on a diverse set of 45 proteins. It is found that the best fitted values of both dielectric constants are around 40. However, the self energy of internal residues and the charge-charge interactions of Lys have to be treated with care, using a somewhat lower values of epsilon'(p) and epsilon'(eff). The predictions of DeltaG(fold) reported here, have an average error of only 1.8 kcal/mole compared to the observed values, making our method very promising for estimating protein stability. It also provides valuable insight into the complex electrostatic phenomena taking place in folded proteins.

Protein ionizable groups: pK values and their contribution to protein stability and solubility

The structure, stability, solubility, and function of proteins depend on their net charge and on the ionization state of the individual residues. Consequently, biochemists are interested in the pK values of the ionizable groups in proteins and how these pK values depend on their environment. We review what has been learned about pK values of ionizable groups in proteins from experimental studies and discuss the important contributions they make to protein stability and solubility.

Toward accurate screening in computer-aided enzyme design

The ability to design effective enzymes is one of the most fundamental challenges in biotechnology and in some respects in biochemistry. In fact, such ability would be one of the most convincing manifestations of a full understanding of the origin of enzyme catalysis. In this work, we explore the reliability of different simulation approaches, in terms of their ability to rank different possible active site constructs. This validation is done by comparing the ability of different approaches to evaluate the catalytic contributions of various residues in chorismate mutase. It is demonstrated that the empirical valence bond (EVB) model can serve as a practical yet accurate tool in the final stages of computer-aided enzyme design (CAED). Other approaches for fast screening are also examined and found to be less accurate and mainly useful for qualitative screening of ionized residues. It is pointed out that accurate ranking of different options for enzyme design cannot be accomplished by approaches that cannot capture the electrostatic preorganization effect. This is in particular true with regard to current design approaches that use gas phase or small cluster calculations and then estimate the interaction between the enzyme and the transition state (TS) model rather than the TS binding free energy or the relevant activation free energy. The ability of the EVB model to provide a tool for quantitative ranking in the final stage of CAED may help in progressing toward the design of enzymes whose catalytic power is closer to that of native enzymes than to that of the current generation of designer enzymes.

Analysis of electrostatic contributions to the selectivity of interactions between RING-finger domains and ubiquitin-conjugating enzymes

The zinc-coordinated protein motifs known as RING-finger domains, present on a class of ubiquitin ligases (E3's), recruit ubiquitin-conjugating enzymes (E2s), tethering them to substrate proteins for covalent modification with ubiquitin. Each RING-finger domain can recruit different E2s, and these interactions are frequently selective, in that certain RING-finger domains associate preferentially with certain E2s. This selectivity acquires particular biological relevance when the recruited E2s exert specialized functions. We have explored the determinants that specify the presence or absence of experimentally detectable interaction between two RING-finger domains, those on RNF11 and RNF103, and two E2s, UBC13, a specialized E2 that catalyzes ubiquitin chain elongation through Lys63 of ubiquitin, and UbcH7, which mediates polyubiquitylation through Lys48. Through the iterative use of computational predictive tools and experimental validations, we have found that these interactions and their selectivity are partly governed by the combinations of electrostatic interactions linking specific residues of the contact interfaces. Our analysis also predicts that the main determinants of selectivity of these interactions reside on the RING-finger domains, rather than on the E2s. The application of some of these rules of interaction selectivity has permitted us to experimentally manipulate the selectivity of interaction of the RING-finger domain-E2 pairs under study.

On the electrostatic component of protein-protein binding free energy

Calculations of electrostatic properties of protein-protein complexes are usually done within framework of a model with a certain set of parameters. In this paper we present a comprehensive statistical analysis of the sensitivity of the electrostatic component of binding free energy (DeltaDeltaGel) with respect with different force fields (Charmm, Amber, and OPLS), different values of the internal dielectric constant, and different presentations of molecular surface (different values of the probe radius). The study was done using the largest so far set of entries comprising 260 hetero and 2148 homo protein-protein complexes extracted from a previously developed database of protein complexes (ProtCom). To test the sensitivity of the energy calculations with respect to the structural details, all structures were energy minimized with corresponding force field, and the energies were recalculated. The results indicate that the absolute value of the electrostatic component of the binding free energy (DeltaDeltaGel) is very sensitive to the force field parameters, the minimization procedure, the values of the internal dielectric constant, and the probe radius. Nevertheless our results indicate that certain trends in DeltaDeltaGel behavior are much less sensitive to the calculation parameters. For instance, the fraction of the homo-complexes, for which the electrostatics was found to oppose binding, is 80% regardless of the force fields and parameters used. For the hetero-complexes, however, the percentage of the cases for which electrostatics opposed binding varied from 43% to 85%, depending on the protocol and parameters employed. A significant correlation was found between the effects caused by raising the internal dielectric constant and decreasing the probe radius. Correlations were also found among the results obtained with different force fields. However, despite of the correlations found, the absolute DeltaDeltaGel calculated with different force field parameters could differ more than tens of kcal/mol in some cases. Set of rules of obtaining confident predictions of absolute DeltaDeltaGel and DeltaDeltaGel sign are provided in the conclusion section.PACS codes: 87.15.A-, 87.15. km.

Molecular crowding effects on structure and stability of DNA

Living cells contain a variety of biomolecules including nucleic acids, proteins, polysaccharides, and metabolites as well as other soluble and insoluble components. These biomolecules occupy a significant fraction (20-40%) of the cellular volume. The total concentration of biomolecules reaches 400gL(-1), leading to a crowded intracellular environment referred to as molecular crowding. Therefore, an understanding of the effects of molecular crowding conditions on biomolecules is important to broad research fields such as biochemical, medical, and pharmaceutical sciences. In this review, we describe molecular conditions in the cytoplasm and nucleus, which are totally different from in vitro conditions, and then show the biochemical and biophysical consequences of molecular crowding. Finally, we discuss the effect of molecular crowding on the structure, stability, and function of nucleic acids and the significance of molecular crowding in biotechnology and nanotechnology.

On the relationship between thermal stability and catalytic power of enzymes

The possible relationship between the thermal stability and the catalytic power of enzymes is of great current interest. In particular, it has been suggested that thermophilic or hyperthermophilic (Tm) enzymes have lower catalytic power at a given temperature than the corresponding mesophilic (Ms) enzymes, because the thermophilic enzymes are less flexible (assuming that flexibility and catalysis are directly correlated). These suggestions presume that the reduced dynamics of the thermophilic enzymes is the reason for their reduced catalytic power. The present paper takes the specific case of dihydrofolate reductase (DHFR) and explores the validity of the above argument by simulation approaches. It is found that the Tm enzymes have restricted motions in the direction of the folding coordinate, but this is not relevant to the chemical process, since the motions along the reaction coordinate are perpendicular to the folding motions. Moreover, it is shown that the rate of the chemical reaction is determined by the activation barrier and the corresponding reorganization energy, rather than by dynamics or flexibility in the ground state. In fact, as far as flexibility is concerned, we conclude that the displacement along the reaction coordinate is larger in the Tm enzyme than in the Ms enzyme and that the general trend in enzyme catalysis is that the best catalyst involves less motion during the reaction than the less optimal catalyst. The relationship between thermal stability and catalysis appears to reflect the fact that to obtain small electrostatic reorganization energy it is necessary to invest some folding energy in the overall preorganization process. Thus, the optimized catalysts are less stable. This trend is clearly observed in the DHFR case.

A quantitative investigation of the chemical space surrounding amino acid alphabet formation

To date, explanations for the origin and emergence of the alphabet of amino acids encoded by the standard genetic code have been largely qualitative and speculative. Here, with the help of computational chemistry, we present the first quantitative exploration of nature's "choices" set against various models for plausible alternatives. Specifically, we consider the chemical space defined by three fundamental biophysical properties (size, charge, and hydrophobicity) to ask whether the amino acids that entered the genetic code exhibit a higher diversity than random samples of similar size drawn from several different definitions of amino acid possibility space. We found that in terms of the properties studied, the full, standard set of 20 biologically encoded amino acids is indeed significantly more diverse than an equivalently sized group drawn at random from the set of plausible, prebiotic alternatives (using the Murchison meteorite as a model for pre-biotic plausibility). However, when the set of possible amino acids is enlarged to include those that are produced by standard biosynthetic pathways (reflecting the widespread idea that many members of the standard alphabet were recruited in this way), then the genetically encoded amino acids can no longer be distinguished as more diverse than a random sample. Finally, if we turn to consider the overlap between biologically encoded amino acids and those that are prebiotically plausible, then we find that the biologically encoded subset are no more diverse as a group than would be expected from a random sample, unless the definition of "random sample" is adjusted to reflect possible prebiotic abundance (again, using the contents of the Murchison meteorite as our estimator). This final result is contingent on the accuracy of our computational estimates for amino acid properties, and prebiotic abundances, and an exploration of the likely effect of errors in our estimation reveals that our results should be treated with caution. We thus present this work as a first step in quantifying and thus testing various origin-of-life hypotheses regarding the origin and evolution of life's amino acid alphabet, and advocate the progress that would add valuable information in the future.