How optimal are the binding energetics of barnase and barstar?

Characterization of the mechanism of bile salt hydrolase substrate specificity by experimental and computational analyses

Bile salt hydrolases (BSHs) are currently being investigated as target enzymes for metabolic regulators in humans and as growth promoters in farm animals. Understanding structural features underlying substrate specificity is necessary for inhibitor design. Here, we used a multidisciplinary workflow including mass spectrometry, mutagenesis, molecular dynamic simulations, machine learning, and crystallography to demonstrate substrate specificity in Lactobacillus salivarius BSH, the most abundant enzyme in human and farm animal intestines. We show the preference of substrates with a taurine head and a dehydroxylated sterol ring for hydrolysis. A regression model that correlates the relative rates of hydrolysis of various substrates in various enzyme mutants with the residue-substrate interaction energies guided the identification of structural determinants of substrate binding and specificity. In addition, we found T208 from another BSH protomer regulating the hydrolysis. The designed workflow can be used for fast and comprehensive characterization of enzymes with a broad range of substrates.

Electrochemical sensor based on molecularly imprinted polymer cryogel and multiwalled carbon nanotubes for direct insulin detection

Insulin is the polypeptide hormone that regulates blood glucose levels. It is used as an indicator of both types of diabetes. An electrochemical insulin sensor was developed using a gold electrode modified with carboxylated multiwalled carbon nanotubes (f-MWCNTs) and molecularly imprinted polymer (MIP) cryogel. The MIP provided specific recognition sites for insulin, while the macropores of the cryogel promoted the mass transfer of insulin to the recognition sites. The f-MWCNTs increased the effective surface area and conductivity of the sensor and also reduced the potential required to oxidize insulin. Insulin oxidation was directly measured in a flow system using square wave voltammetry. This MIP cryogel/f-MWCNTs sensor provided a linear range of 0.050-1.40 pM with a very low limit of detection (LOD) of 33 fM. The sensor exhibited high selectivity and long-term stability over 10 weeks of dry storage at room temperature. The results of insulin determination in human serum using the sensor compared well with the results of the Elecsys insulin assay. The developed MIP sensor offers a promising alternative for the diagnosis and treatment of diabetes.

The Intrinsic Radius as a Key Parameter in the Generalized Born Model to Adjust Protein-Protein Electrostatic Interaction

The generalized Born (GB) model is an extension of the continuum dielectric theory of Born solvation energy and is a powerful method for accelerating the molecular dynamic (MD) simulations of charged biological molecules in water. While the effective dielectric constant of water that varies as a function of the separation distance between solute molecules is incorporated into the GB model, adjustment of the parameters is indispensable for accurate calculation of the Coulomb (electrostatic) energy. One of the key parameters is the lower limit of the spatial integral of the energy density of the electric field around a charged atom, known as the intrinsic radius ρ. Although ad hoc adjustment of ρ has been conducted to improve the Coulombic (ionic) bond stability, the physical mechanism by which ρ affects the Coulomb energy remains unclear. Via energetic analysis of three differently sized systems, here, we clarify that the Coulomb bond stability increases with increasing ρ and that the increased stability is caused by the interaction energy term, not by the self-energy (desolvation energy) term, as was supposed previously. Our results suggest that the use of larger values for the intrinsic radii of hydrogen and oxygen atoms, together with the use of a relatively small value for the spatial integration cutoff in the GB model, can better reproduce the Coulombic attraction between protein molecules.

Exploring new strategies for grafting binding peptides onto protein loops using a consensus-designed tetratricopeptide repeat scaffold

Peptide display approaches, in which peptide epitopes of known binding activities are grafted onto stable protein scaffolds, have been developed to constrain the peptide in its bioactive conformation and to enhance its stability. However, peptide grafting can be a lengthy process requiring extensive computational modeling and/or optimisation by directed evolution techniques. In this study, we show that ultra-stable consensus-designed tetratricopeptide repeat (CTPR) proteins are amenable to the grafting of peptides that bind the Kelch-like ECH-associated protein 1 (Keap1) onto the loop between adjacent repeats. We explore simple strategies to optimize the grafting process and show that modest improvements in Keap1-binding affinity can be obtained by changing the composition of the linker sequence flanking either side of the binding peptide.

Structural Perspective on Revealing and Altering Molecular Functions of Genetic Variants Linked with Diseases

Structural information of biological macromolecules is crucial and necessary to deliver predictions about the effects of mutations-whether polymorphic or deleterious (i.e., disease causing), wherein, thermodynamic parameters, namely, folding and binding free energies potentially serve as effective biomarkers. It may be emphasized that the effect of a mutation depends on various factors, including the type of protein (globular, membrane or intrinsically disordered protein) and the structural context in which it occurs. Such information may positively aid drug-design. Furthermore, due to the intrinsic plasticity of proteins, even mutations involving radical change of the structural and physico⁻chemical properties of the amino acids (native vs. mutant) can still have minimal effects on protein thermodynamics. However, if a mutation causes significant perturbation by either folding or binding free energies, it is quite likely to be deleterious. Mitigating such effects is a promising alternative to the traditional approaches of designing inhibitors. This can be done by structure-based in silico screening of small molecules for which binding to the dysfunctional protein restores its wild type thermodynamics. In this review we emphasize the effects of mutations on two important biophysical properties, stability and binding affinity, and how structures can be used for structure-based drug design to mitigate the effects of disease-causing variants on the above biophysical properties.

The Inclusion of Water Molecules in Residue Interaction Networks Identifies Additional Central Residues

The relevance of water molecules for the recognition and the interaction of biomolecules is widely appreciated. In this paper we address the role that water molecules associated to protein complexes play for the functional relevance of residues by considering their residue interaction networks (RINs). These are commonly defined on the basis of the amino acid composition of the proteins themselves, disregarding the solvation state of the protein. We determine properties of the RINs of two protein complexes, colicin E2/Im2 and barnase/barstar, with and without associated water molecules, using a previously developed methodology and its associated application RINspector. We find that the inclusion of water molecules in RINs leads to an increase in the number of central residues which adds a novel mechanism to the relevance of water molecules for protein function.

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.

Plum Fruit Development Occurs via Gibberellin-Sensitive and -Insensitive DELLA Repressors

Fruit growth depends on highly coordinated hormonal activities. The phytohormone gibberellin (GA) promotes growth by triggering degradation of the growth-repressing DELLA proteins; however, the extent to which such proteins contribute to GA-mediated fruit development remains to be clarified. Three new plum genes encoding DELLA proteins, PslGAI, PslRGL and PslRGA were isolated and functionally characterized. Analysis of expression profile during fruit development suggested that PslDELLA are transcriptionally regulated during flower and fruit ontogeny with potential positive regulation by GA and ethylene, depending on organ and developmental stage. PslGAI and PslRGL deduced proteins contain all domains present in typical DELLA proteins. However, PslRGA exhibited a degenerated DELLA domain and subsequently lacks in GID1–DELLA interaction property. PslDELLA–overexpression in WT Arabidopsis caused dramatic disruption in overall growth including root length, stem elongation, plant architecture, flower structure, fertility, and considerable retardation in development due to dramatic distortion in GA-metabolic pathway. GA treatment enhanced PslGAI/PslRGL interaction with PslGID1 receptors, causing protein destabilization and relief of growth-restraining effect. By contrast, PslRGA protein was not degraded by GA due to its inability to interact with PslGID1. Relative to other PslDELLA–mutants, PslRGA–plants displayed stronger constitutive repressive growth that was irreversible by GA application. The present results describe additional complexities in GA-signalling during plum fruit development, which may be particularly important to optimize successful reproductive growth.

Structural basis for the development of SARS 3CL protease inhibitors from a peptide mimic to an aza-decaline scaffold

Design of inhibitors against severe acute respiratory syndrome (SARS) chymotrypsin-like protease (3CL(pro) ) is a potentially important approach to fight against SARS. We have developed several synthetic inhibitors by structure-based drug design. In this report, we reveal two crystal structures of SARS 3CL(pro) complexed with two new inhibitors based on our previous work. These structures combined with six crystal structures complexed with a series of related ligands reported by us are collectively analyzed. To these eight complexes, the structural basis for inhibitor binding was analyzed by the COMBINE method, which is a chemometrical analysis optimized for the protein-ligand complex. The analysis revealed that the first two latent variables gave a cumulative contribution ratio of r(2)  = 0.971. Interestingly, scores using the second latent variables for each complex were strongly correlated with root mean square deviations (RMSDs) of side-chain heavy atoms of Met(49) from those of the intact crystal structure of SARS-3CL(pro) (r = 0.77) enlarging the S2 pocket. The substantial contribution of this side chain (∼10%) for the explanation of pIC50 s was dependent on stereochemistry and the chemical structure of the ligand adapted to the S2 pocket of the protease. Thus, starting from a substrate mimic inhibitor, a design for a central scaffold for a low molecular weight inhibitor was evaluated to develop a further potent inhibitor. © 2015 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 106: 391-403, 2016.

Molecular docking as a popular tool in drug design, an in silico travel

New molecular modeling approaches, driven by rapidly improving computational platforms, have allowed many success stories for the use of computer-assisted drug design in the discovery of new mechanism-or structure-based drugs. In this overview, we highlight three aspects of the use of molecular docking. First, we discuss the combination of molecular and quantum mechanics to investigate an unusual enzymatic mechanism of a flavoprotein. Second, we present recent advances in anti-infectious agents' synthesis driven by structural insights. At the end, we focus on larger biological complexes made by protein-protein interactions and discuss their relevance in drug design. This review provides information on how these large systems, even in the presence of the solvent, can be investigated with the outlook of drug discovery.

Electrosynthesis and binding properties of molecularly imprinted poly-o-phenylenediamine for selective recognition and direct electrochemical detection of myoglobin

Electrosynthesis of molecularly imprinted polymer (MIP) templated with myoglobin (Mb) and the reference non-imprinted polymer (NIP) was examined with o-phenylenediamine (o-PD) as a monomer. Mass-sensitive quartz crystal microbalance with dissipation monitoring supplied by an electrochemical module (EQCM-D) was applied to characterize and optimize MIP/NIP electrosynthesis. Mb rebinding was detected by direct electrocatalytic reduction of Mb by square wave voltammetry (SWV) or differential pulse voltammetry (DPV). The results obtained showed high specificity of polymeric antibodies to template Mb, with an imprinting factor determined as a ratio Imax(MIP)/Imax(NIP) of 2-4. The prepared MIP sensor is characterized by an apparent dissociation constant of (3.3±0.5)×10(-9)M and has a broad range of working concentrations of 1nM-1μМ, with the detection limit of 0.5nM (9ng/ml). Mb rebinding was examined in Mb-free diluted human serum spiked with Mb as well as in plasma samples of patients with acute myocardial infarction (AMI) and in control plasma of healthy donors in order to demonstrate the potential medical application of developed MIP sensors.

Discrete structural features among interface residue-level classes

BACKGROUND

Protein-protein interaction (PPI) is essential for molecular functions in biological cells. Investigation on protein interfaces of known complexes is an important step towards deciphering the driving forces of PPIs. Each PPI complex is specific, sensitive and selective to binding. Therefore, we have estimated the relative difference in percentage of polar residues between surface and the interface for each complex in a non-redundant heterodimer dataset of 278 complexes to understand the predominant forces driving binding.

RESULTS

Our analysis showed ~60% of protein complexes with surface polarity greater than interface polarity (designated as class A). However, a considerable number of complexes (~40%) have interface polarity greater than surface polarity, (designated as class B), with a significantly different p-value of 1.66E-45 from class A. Comprehensive analyses of protein complexes show that interface features such as interface area, interface polarity abundance, solvation free energy gain upon interface formation, binding energy and the percentage of interface charged residue abundance distinguish among class A and class B complexes, while electrostatic visualization maps also help differentiate interface classes among complexes.

CONCLUSIONS

Class A complexes are classical with abundant non-polar interactions at the interface; however class B complexes have abundant polar interactions at the interface, similar to protein surface characteristics. Five physicochemical interface features analyzed from the protein heterodimer dataset are discriminatory among the interface residue-level classes. These novel observations find application in developing residue-level models for protein-protein binding prediction, protein-protein docking studies and interface inhibitor design as drugs.

Enhanced Anti-Tumor (Anti-Proliferation) Activity of Recombinant Human Interleukin-29 (IL-29) Mutants Using Site-Directed Mutagenesis Method

Interferon (IFN)-λ, also known as IL-28A, IL-28B, or IL-29, is a new type III IFN, which shares many functional characteristics with type I IFN (α/β). Currently, IFN-α is used in the treatment of certain forms of cancer with severe adverse effects. Some researches had stated that IFN-λs induced a similar but restricted growth inhibition of tumor cells relative to IFN-α; moreover, mutations of IFN-λs could strongly impact its biological properties. In this study, three hIL-29 mutants (K33R, R35K, and K33R/R35K) were generated by site-directed mutagenesis and efficiently expressed in Pichia pastoris GS115, which have considerable abilities to inhibit the growth of BEL-7402, HCT-8, and SGC-7901 tumor cells in vitro. The results showed that these mutants (K33R, R35K, and K33R/R35K) exhibited a significantly enhanced anti-proliferation activity against these tumor cells, compared with native hIL-29 in vitro. Further assay in vitro indicated that superior to K33R and R35K, K33R/R35K had a significant increase in anti-tumor activity compared with IFN-α2b, which suggested that the K33R/R35K could make improvement for the effectiveness of native hIL-29 in clinic and could be used as a potentially powerful candidate for cancer immunotherapy.

Development of a Model Protein Interaction Pair as a Benchmarking Tool for the Quantitative Analysis of 2-Site Protein-Protein Interactions

A significant challenge in the molecular interaction field is to accurately determine the stoichiometry and stepwise binding affinity constants for macromolecules having >1 binding site. The mission of the Molecular Interactions Research Group (MIRG) of the Association of Biomolecular Resource Facilities (ABRF) is to show how biophysical technologies are used to quantitatively characterize molecular interactions, and to educate the ABRF members and scientific community on the utility and limitations of core technologies [such as biosensor, microcalorimetry, or analytic ultracentrifugation (AUC)]. In the present work, the MIRG has developed a robust model protein interaction pair consisting of a bivalent variant of the Bacillus amyloliquefaciens extracellular RNase barnase and a variant of its natural monovalent intracellular inhibitor protein barstar. It is demonstrated that this system can serve as a benchmarking tool for the quantitative analysis of 2-site protein-protein interactions. The protein interaction pair enables determination of precise binding constants for the barstar protein binding to 2 distinct sites on the bivalent barnase binding partner (termed binase), where the 2 binding sites were engineered to possess affinities that differed by 2 orders of magnitude. Multiple MIRG laboratories characterized the interaction using isothermal titration calorimetry (ITC), AUC, and surface plasmon resonance (SPR) methods to evaluate the feasibility of the system as a benchmarking model. Although general agreement was seen for the binding constants measured using solution-based ITC and AUC approaches, weaker affinity was seen for surface-based method SPR, with protein immobilization likely affecting affinity. An analysis of the results from multiple MIRG laboratories suggests that the bivalent barnase-barstar system is a suitable model for benchmarking new approaches for the quantitative characterization of complex biomolecular interactions.

Other Related Techniques

With the advances in computational resources, there is an increasing urge among the computational researchers to make the in silico approaches fast, convenient, reproducible, acceptable, and sensible ones. Along with the typical two-dimensional (2D) and three-dimensional (3D) quantitative structure–activity relationship (QSAR) methods, approaches like pharmacophore, structure-based docking studies, and combinations of ligand- and structure-based approaches like comparative residue interaction analysis (CoRIA) and comparative binding energy analysis (COMBINE) have gained a significant popularity in the computational drug design process. A pharmacophore can be developed either in a ligand-based method, by superposing a set of active molecules and extracting common chemical features which are vital for their bioactivity; or in a structure-based manner, by probing probable interaction points between the macromolecular target and ligands. The interaction of protein and ligand molecules with each other is one of the interesting studies in modern molecular biology and molecular recognition. This interaction can well be explained with the conceptof a docking study to show how a molecule can bind to another molecule to exert the bioactivity. Docking and pharmacophore are non-QSAR approaches in in silico drug design that can support the QSAR findings. Approaches like CoRIA and COMBINE can use information generated from the ligand–receptor complexes to extract the critical clue concerning the types of significant interaction at the level of both the receptor and the ligand. Employing the abovementioned ligand- and structure-based methodologies and chemical libraries, virtual screening (VS) emerged as an important tool in the quest to develop novel drug compounds. VS serves as an efficient computational tool that integrates structural data with lead optimization as a cost-effective approach to drug discovery.

Energy landscape of all-atom protein-protein interactions revealed by multiscale enhanced sampling

Protein-protein interactions are regulated by a subtle balance of complicated atomic interactions and solvation at the interface. To understand such an elusive phenomenon, it is necessary to thoroughly survey the large configurational space from the stable complex structure to the dissociated states using the all-atom model in explicit solvent and to delineate the energy landscape of protein-protein interactions. In this study, we carried out a multiscale enhanced sampling (MSES) simulation of the formation of a barnase-barstar complex, which is a protein complex characterized by an extraordinary tight and fast binding, to determine the energy landscape of atomistic protein-protein interactions. The MSES adopts a multicopy and multiscale scheme to enable for the enhanced sampling of the all-atom model of large proteins including explicit solvent. During the 100-ns MSES simulation of the barnase-barstar system, we observed the association-dissociation processes of the atomistic protein complex in solution several times, which contained not only the native complex structure but also fully non-native configurations. The sampled distributions suggest that a large variety of non-native states went downhill to the stable complex structure, like a fast folding on a funnel-like potential. This funnel landscape is attributed to dominant configurations in the early stage of the association process characterized by near-native orientations, which will accelerate the native inter-molecular interactions. These configurations are guided mostly by the shape complementarity between barnase and barstar, and lead to the fast formation of the final complex structure along the downhill energy landscape.

Dynamic nature of the protein-protein interactions is an important element of cellular processes such as metabolic reactions and signal transduction, but its atomistic details are still unclear. Computational survey using molecular dynamics simulation is a straightforward method to elucidate these atomistic protein-protein interaction processes. However, a sufficient configurational sampling of the large system containing the atomistic protein complex model and explicit solvent remains a great challenge due to the long timescale involved. Here, we demonstrate that the multiscale enhanced sampling (MSES) successfully captured the atomistic details of the association/dissociation processes of a barnase-barstar complex covering the sampled space from the native complex structure to fully non-native configurations. The landscape derived from the simulation indicates that the association process is funnel-like downhill, analogously to the funnel landscape of fast-folding proteins. The funnel was found to be originated from near-native orientations guided by the shape complementarity between barnase and barstar, accelerating the formation of native inter-molecular interactions to complete the final complex structure.

Biophysical highlights from 54 years of macromolecular crystallography

The United Nations has declared 2014 the International Year of Crystallography, and in commemoration, this review features a selection of 54 notable macromolecular crystal structures that have illuminated the field of biophysics in the 54 years since the first excitement of the myoglobin and hemoglobin structures in 1960. Chronological by publication of the earliest solved structure, each illustrated entry briefly describes key concepts or methods new at the time and key later work leveraged by knowledge of the three-dimensional atomic structure.

Inducible resistance to maize streak virus

Maize streak virus (MSV), which causes maize streak disease (MSD), is the major viral pathogenic constraint on maize production in Africa. Type member of the Mastrevirus genus in the family Geminiviridae, MSV has a 2.7 kb, single-stranded circular DNA genome encoding a coat protein, movement protein, and the two replication-associated proteins Rep and RepA. While we have previously developed MSV-resistant transgenic maize lines constitutively expressing "dominant negative mutant" versions of the MSV Rep, the only transgenes we could use were those that caused no developmental defects during the regeneration of plants in tissue culture. A better transgene expression system would be an inducible one, where resistance-conferring transgenes are expressed only in MSV-infected cells. However, most known inducible transgene expression systems are hampered by background or "leaky" expression in the absence of the inducer. Here we describe an adaptation of the recently developed INPACT system to express MSV-derived resistance genes in cell culture. Split gene cassette constructs (SGCs) were developed containing three different transgenes in combination with three different promoter sequences. In each SGC, the transgene was split such that it would be translatable only in the presence of an infecting MSV's replication associated protein. We used a quantitative real-time PCR assay to show that one of these SGCs (pSPLITrepIII-Rb-Ubi) inducibly inhibits MSV replication as efficiently as does a constitutively expressed transgene that has previously proven effective in protecting transgenic maize from MSV. In addition, in our cell-culture based assay pSPLITrepIII-Rb-Ubi inhibited replication of diverse MSV strains, and even, albeit to a lesser extent, of a different mastrevirus species. The application of this new technology to MSV resistance in maize could allow a better, more acceptable product.

Pharmacophore-based screening and identification of novel human ligase I inhibitors with potential anticancer activity

Human DNA ligases are enzymes that are indispensable for DNA replication and repair processes. Among the three human ligases, ligase I is attributed to the ligation of thousands of Okazaki fragments that are formed during lagging strand synthesis during DNA replication. Blocking ligation therefore can lead to the accumulation of thousands of single strands and subsequently double strand breaks in the DNA, which is lethal for the cells. The reports of the high expression level of ligase I protein in several cancer cells (versus the low ligase expression level and the low rate of division of most normal cells in the adult body) support the belief that ligase I inhibitors can target cancer cells specifically with minimum side effects to normal cells. Recent publications showing exciting data for a ligase IV inhibitor exhibiting antitumor activity in mouse models also strengthens the argument for ligases as valid antitumor targets. Keeping this in view, we performed a pharmacophore-based screening for potential ligase inhibitors in the Maybridge small molecule library and procured some of the top-ranking compounds for enzyme-based and cell-based in vitro screening. We report here the identification of novel ligase I inhibitors with potential anticancer activity against a colon cancer cell line.

Characterization of gibberellin-signalling elements during plum fruit ontogeny defines the essentiality of gibberellin in fruit development

Fruit growth is a coordinated, complex interaction of cell division, differentiation and expansion. Gibberellin (GA) involvement in the reproductive events is an important aspect of GA effects. Perennial fruit-trees such as plum (Prunus salicina L.) have distinct features that are economically important and provide opportunities to dissect specific GA mechanisms. Currently, very little is known on the molecular mechanism(s) mediating GA effects on fruit development. Determination of bioactive GA content during plum fruit ontogeny revealed that GA1 and GA4 are critical for fruit growth and development. Further, characterization of several genes involved in GA-signalling showed that their transcriptional regulation are generally GA-dependent, confirming their involvement in GA-signalling. Based on these results, a model is presented elucidating how the potential association between GA and other hormones may contribute to fruit development. PslGID1 proteins structure, Y2H and BiFC assays indicated that plum GA-receptors can form a complex with AtDELLA-repressors in a GA-dependent manner. Moreover, phenotypical-, molecular- and GA-analyses of various Arabidopsis backgrounds ectopically expressing PslGID1 sequences provide evidence on their role as active GA-signalling components that mediate GA-responsiveness. Our findings support the critical contribution of GA alone or in association with other hormones in mediating plum fruit growth and development.

The role of tyrosine sulfation in the dimerization of the CXCR4:SDF-1 complex

Oligomerization of G protein-coupled receptors is a recognized mode of regulation of receptor activities, with alternate oligomeric states resulting in different signaling functions. The CXCR4 chemokine receptor is a G protein-coupled receptor that is post-translationally modified by tyrosine sulfation at three sites on its N-terminus (Y7, Y12, Y21), leading to enhanced affinity for its ligand, stromal cell derived factor (SDF-1, also called CXCL12). The complex has been implicated in cancer metastasis and is a therapeutic target in cancer treatment. Using molecular dynamics simulation of NMR-derived structures of the CXCR4 N-terminus in complex with SDF-1, and calculations of electrostatic binding energies for these complexes, we address the role of tyrosine sulfation in this complex. Our results show that sulfation stabilizes the dimeric state of the CXCR4:SDF-1 complex through hydrogen bonding across the dimer interface, conformational changes in residues at the dimer interface, and an enhancement in electrostatic binding energies associated with dimerization. These findings suggest a mechanism through which post-translational modifications such as tyrosine sulfation might regulate downstream function through modulation of the oligomeric state of the modified system.

Efficient determination of protein-protein standard binding free energies from first principles

Characterizing protein-protein association quantitatively has been a longstanding challenge for computer simulations. Here, a theoretical framework is put forth that addresses this challenge on the basis of detailed all-atom molecular dynamics simulations with explicit solvent. The proposed methodology relies upon independent potential of mean force (PMF) free-energy calculations carried out sequentially, wherein the biological objects are restrained in the conformation, position and orientation of the bound state, using adequately chosen biasing potentials. These restraints systematically narrow down the configurational entropy available to the system and effectively guarantee that the relevant network of interactions is properly sampled as the two proteins reversibly associate. Decomposition of the binding process into consecutive, well-delineated stages, for both the protein complex and the individual, unbound partners, offers a rigorous definition of the standard state, from which the absolute binding free energy can be determined. The method is applied to the difficult case of the extracellular ribonuclease barnase binding to its intracellular inhibitor barstar. The calculated binding free energy is -21.0 ± 1.4 kcal/mol, which compares well with the experimental value of -19.0 ± 0.2 kcal/mol. The relatively small statistical error reflects the precision and convergence afforded by the PMF-based simulation methodology. In addition to providing an accurate reproduction of the standard binding free energy, the proposed strategy offers a detailed picture of the protein-protein interface, illuminating the thermodynamic forces that underlie reversible association. The application of the present formal framework to barnase:barstar binding provides a foundation for tackling nearly any protein-protein complex.

Hydrodynamic effects on the relative rotational velocity of associating proteins

Hydrodynamic steering effects on the barnase-barstar association were studied through the analysis of the relative rotational velocity of the proteins. We considered the two proteins approaching each other in response to their electrostatic attraction and employed a method that accounts for the long-range and many-body character of the hydrodynamic interactions, as well as the complicated shapes of the proteins. Hydrodynamic steering effects were clearly seen when attractive forces were applied to the geometric centers of the proteins (resulting in zero torques) and the attraction acted along the line that connects centers of geometry of proteins in their crystallographic complex. When we rotated barstar relative to barnase around this line by an angle in the range from -90° to 60°, the rotational velocity arising solely from hydrodynamic interactions restored the orientation of the proteins in the crystal structure. However, because, in reality, both electrostatic forces and torques act on the proteins and these forces and torques depend on the protein-protein distance and the relative orientation of the binding partners, we also investigated more realistic situations employing continuum electrostatics calculations based on atomistic protein models. Overall, we conclude that hydrodynamic interactions aid barnase and barstar in assuming a proper relative orientation upon complex formation.

Comparative binding energy COMBINE analysis for understanding the binding determinants of type II dehydroquinase inhibitors

Herein we report comparative binding energy (COMBINE) analyses to derive quantitative structure-activity relationship (QSAR) models that help rationalize the determinants of binding affinity for inhibitors of type II dehydroquinase (DHQ2), the third enzyme of the shikimic acid pathway. Independent COMBINE models were derived for Helicobacter pylori and Mycobacterium tuberculosis DHQ2, which is an essential enzyme in both these pathogenic bacteria that has no counterpart in human cells. These studies quantify the importance of the hydrogen bonding interactions between the ligands and the water molecule involved in the DHQ2 reaction mechanism. They also highlight important differences in the ligand interactions with the interface pocket close to the active site that could provide guides for future inhibitor design.

Identification of the catalytic Mg²⁺ ion in the hepatitis delta virus ribozyme

The hepatitis delta virus ribozyme catalyzes an RNA cleavage reaction using a catalytic nucleobase and a divalent metal ion. The catalytic base, C75, serves as a general acid and has a pK(a) shifted toward neutrality. Less is known about the role of metal ions in the mechanism. A recent crystal structure of the precleavage ribozyme identified a Mg²⁺ ion that interacts through its partial hydration sphere with the G25·U20 reverse wobble. In addition, this Mg²⁺ ion is in position to directly coordinate the nucleophile, the 2'-hydroxyl of U(-1), suggesting it can serve as a Lewis acid to facilitate deprotonation of the 2'-hydroxyl. To test the role of the active site Mg²⁺ ion, we replaced the G25·U20 reverse wobble with an isosteric A25·C20 reverse wobble. This change was found to significantly reduce the negative potential at the active site, as supported by electrostatics calculations, suggesting that active site Mg²⁺ binding could be adversely affected by the mutation. The kinetic analysis and molecular dynamics of the A25·C20 double mutant suggest that this variant stably folds into an active structure. However, pH-rate profiles of the double mutant in the presence of Mg²⁺ are inverted relative to the profiles for the wild-type ribozyme, suggesting that the A25·C20 double mutant has lost the active site metal ion. Overall, these studies support a model in which the partially hydrated Mg²⁺ positioned at the G25·U20 reverse wobble is catalytic and could serve as a Lewis acid, a Brønsted base, or both to facilitate deprotonation of the nucleophile.

Modeling Protein-Protein Recognition in Solution Using the Coarse-Grained Force Field SCORPION

We present here the SCORPION-Solvated COaRse-grained Protein interactION-force field, a physics-based simplified coarse-grained (CG) force field. It combines our previous CG protein model and a novel particle-based water model which makes it suitable for Molecular Dynamics (MD) simulations of protein association processes. The protein model in SCORPION represents each amino acid with one to three beads, for which electrostatic and van der Waals effective interactions are fitted separately to reproduce those of the all-atom AMBER force field. The protein internal flexibility is accounted for by an elastic network model (ENM). We now include in SCORPION a new Polarizable Coarse-Grained Solvent (PCGS) model, which is computationally efficient, consistent with the protein CG representation, and yields accurate electrostatic free energies of proteins. SCORPION is used here for the first time to perform hundreds-of-nanoseconds-long MD simulations of protein/protein recognition in water, here the case of the barnase/barstar complex. These MD simulations showed that, for five of a total of seven simulations starting from several initial conformations, and after a time going from 1 to 500 ns, the proteins bind in a conformation very close to the native bound structure and remain stable in this conformation for the rest of the simulation. An energetic analysis of these MD show that this recognition is driven both by van der Waals and electrostatic interactions between proteins. SCORPION appears therefore as a useful tool to study protein-protein recognition in a solvated environment.

Brownian dynamics study of the association between the 70S ribosome and elongation factor G

Protein synthesis on the ribosome involves a number of external protein factors that bind at its functional sites. One key factor is the elongation factor G (EF-G) that facilitates the translocation of transfer RNAs between their binding sites, as well as advancement of the messenger RNA by one codon. The details of the EF-G/ribosome diffusional encounter and EF-G association pathway still remain unanswered. Here, we applied Brownian dynamics methodology to study bimolecular association in the bacterial EF-G/70S ribosome system. We estimated the EF-G association rate constants at 150 and 300 mM monovalent ionic strengths and obtained reasonable agreement with kinetic experiments. We have also elucidated the details of EF-G/ribosome association paths and found that positioning of the L11 protein of the large ribosomal subunit is likely crucial for EF-G entry to its binding site.

Effect of the ordered interfacial water layer in protein complex formation: A nonlocal electrostatic approach

Using a nonlocal electrostatic approach that incorporates the short-range structure of the contacting media, we evaluated the electrostatic contribution to the energy of the complex formation of two model proteins. In this study, we have demonstrated that the existence of an ordered interfacial water layer at the protein-solvent interface reduces the charging energy of the proteins in the aqueous solvent, and consequently increases the electrostatic contribution to the protein binding (change in free energy upon the complex formation of two proteins). This is in contrast with the finding of the continuum electrostatic model, which suggests that electrostatic interactions are not strong enough to compensate for the unfavorable desolvation effects.

Tracking single proteins in live cells using single-chain antibody fragment-fluorescent quantum dot affinity pair

Quantum dots (QDs) are extremely bright fluorescent imaging probes that are particularly useful for tracking individual molecules in living cells. Here, we show how a two-component system composed of a high-affinity single-chain fragment antibody and its cognate hapten (fluorescein) can be utilized for tracking individual proteins in various cell types. The single-chain fragment antibody against fluorescein is genetically appended to the protein of interest, while the hapten fluorescein is attached to the end of the peptide that is used to coat the QDs. We describe (i) the method used to functionalize QDs with fluorescein peptides; (ii) the method used to control the stoichiometry of the hapten on the surface of the QD; and (iii) the technical details necessary to observe single molecules in living cells.

Fast predictions of thermodynamics and kinetics of protein-protein recognition from structures: from molecular design to systems biology

The increasing call for an overall picture of the interactions between the components of a biological system that give rise to the observed function is often summarized by the expression systems biology. Both the interpretative and predictive capabilities of holistic models of biochemical systems, however, depend to a large extent on the level of physico-chemical knowledge of the individual molecular interactions making up the network. This review is focused on the structure-based quantitative characterization of protein-protein interactions, ubiquitous in any biochemical pathway. Recently developed, fast and effective computational methods are reviewed, which allow the assessment of kinetic and thermodynamic features of the association-dissociation processes of protein complexes, both in water soluble and membrane environments. The performance and the accuracy of fast and semi-empirical structure-based methods have reached comparable levels with respect to the classical and more elegant molecular simulations. Nevertheless, the broad accessibility and lower computational cost provide the former methods with the advantageous possibility to perform systems-level analyses including extensive in silico mutagenesis screenings and large-scale structural predictions of multiprotein complexes.

Progress in ab initio QM/MM free-energy simulations of electrostatic energies in proteins: accelerated QM/MM studies of pKa, redox reactions and solvation free energies

Hybrid quantum mechanical/molecular mechanical (QM/MM) approaches have been used to provide a general scheme for chemical reactions in proteins. However, such approaches still present a major challenge to computational chemists, not only because of the need for very large computer time in order to evaluate the QM energy but also because of the need for proper computational sampling. This review focuses on the sampling issue in QM/MM evaluations of electrostatic energies in proteins. We chose this example since electrostatic energies play a major role in controlling the function of proteins and are key to the structure-function correlation of biological molecules. Thus, the correct treatment of electrostatics is essential for the accurate simulation of biological systems. Although we will be presenting different types of QM/MM calculations of electrostatic energies (and related properties) here, our focus will be on pKa calculations. This reflects the fact that pKa's of ionizable groups in proteins provide one of the most direct benchmarks for the accuracy of electrostatic models of macromolecules. While pKa calculations by semimacroscopic models have given reasonable results in many cases, existing attempts to perform pKa calculations using QM/MM-FEP have led to discrepancies between calculated and experimental values. In this work, we accelerate our QM/MM calculations using an updated mean charge distribution and a classical reference potential. We examine both a surface residue (Asp3) of the bovine pancreatic trypsin inhibitor and a residue buried in a hydrophobic pocket (Lys102) of the T4-lysozyme mutant. We demonstrate that, by using this approach, we are able to reproduce the relevant side chain pKa's with an accuracy of 3 kcal/mol. This is well within the 7 kcal/mol energy difference observed in studies of enzymatic catalysis, and is thus sufficient accuracy to determine the main contributions to the catalytic energies of enzymes. We also provide an overall perspective of the potential of QM/MM calculations in general evaluations of electrostatic free energies, pointing out that our approach should provide a very powerful and accurate tool to predict the electrostatics of not only solution but also enzymatic reactions, as well as the solvation free energies of even larger systems, such as nucleic acid bases incorporated into DNA.

Accurate solution of multi-region continuum biomolecule electrostatic problems using the linearized Poisson-Boltzmann equation with curved boundary elements

We present a boundary-element method (BEM) implementation for accurately solving problems in biomolecular electrostatics using the linearized Poisson-Boltzmann equation. Motivating this implementation is the desire to create a solver capable of precisely describing the geometries and topologies prevalent in continuum models of biological molecules. This implementation is enabled by the synthesis of four technologies developed or implemented specifically for this work. First, molecular and accessible surfaces used to describe dielectric and ion-exclusion boundaries were discretized with curved boundary elements that faithfully reproduce molecular geometries. Second, we avoided explicitly forming the dense BEM matrices and instead solved the linear systems with a preconditioned iterative method (GMRES), using a matrix compression algorithm (FFTSVD) to accelerate matrix-vector multiplication. Third, robust numerical integration methods were employed to accurately evaluate singular and near-singular integrals over the curved boundary elements. Fourth, we present a general boundary-integral approach capable of modeling an arbitrary number of embedded homogeneous dielectric regions with differing dielectric constants, possible salt treatment, and point charges. A comparison of the presented BEM implementation and standard finite-difference techniques demonstrates that for certain classes of electrostatic calculations, such as determining absolute electrostatic solvation and rigid-binding free energies, the improved convergence properties of the BEM approach can have a significant impact on computed energetics. We also demonstrate that the improved accuracy offered by the curved-element BEM is important when more sophisticated techniques, such as nonrigid-binding models, are used to compute the relative electrostatic effects of molecular modifications. In addition, we show that electrostatic calculations requiring multiple solves using the same molecular geometry, such as charge optimization or component analysis, can be computed to high accuracy using the presented BEM approach, in compute times comparable to traditional finite-difference methods.

Volume-based solvation models out-perform area-based models in combined studies of wild-type and mutated protein-protein interfaces

BACKGROUND

Empirical binding models have previously been investigated for the energetics of protein complexation (DeltaG models) and for the influence of mutations on complexation (i.e. differences between wild-type and mutant complexes, DeltaDeltaG models). We construct binding models to directly compare these processes, which have generally been studied separately.

RESULTS

Although reasonable fit models were found for both DeltaG and DeltaDeltaG cases, they differ substantially. In a dataset curated for the absence of mainchain rearrangement upon binding, non-polar area burial is a major determinant of DeltaG models. However this DeltaG model does not fit well to the data for binding differences upon mutation. Burial of non-polar area is weighted down in fitting of DeltaDeltaG models. These calculations were made with no repacking of sidechains upon complexation, and only minimal packing upon mutation. We investigated the consequences of more extensive packing changes with a modified mean-field packing scheme. Rather than emphasising solvent exposure with relatively extended sidechains, rotamers are selected that exhibit maximal packing with protein. This provides solvent accessible areas for proteins that are much closer to those of experimental structures than the more extended sidechain regime. The new packing scheme increases changes in non-polar burial for mutants compared to wild-type proteins, but does not substantially improve agreement between DeltaG and DeltaDeltaG binding models.

CONCLUSION

We conclude that solvent accessible area, based on modelled mutant structures, is a poor correlate for DeltaDeltaG upon mutation. A simple volume-based, rather than solvent accessibility-based, model is constructed for DeltaG and DeltaDeltaG systems. This shows a more consistent behaviour. We discuss the efficacy of volume, as opposed to area, approaches to describe the energetic consequences of mutations at interfaces. This knowledge can be used to develop simple computational screens for binding in comparative modelled interfaces.

Crystal structural analysis of protein-protein interactions drastically destabilized by a single mutation

The complex of barnase (bn) and barstar (bs), which has been widely studied as a model for quantitative analysis of protein-protein interactions, is significantly destabilized by a single mutation, namely, bs Asp39 --> Ala, which corresponds to a change of 7.7 kcal x mol(-1) in the free energy of binding. However, there has been no structural information available to explain such a drastic destabilization. In the present study, we determined the structure of the mutant complex at 1.58 A resolution by X-ray crystallography. The complex was similar to the wild-type complex in terms of overall and interface structures; however, the hydrogen bond network mediated by water molecules at the interface was significantly different. Several water molecules filled the cavity created by the mutation and consequently caused rearrangement of the hydrated water molecules at the interface. The water molecules were redistributed into a channel-like structure that penetrated into the complex. Furthermore, molecular dynamics simulations showed that the mutation increased the mobility of water molecules at the interface. Since such a drastic change in hydration was not observed in other mutant complexes of bn and bs, the significant destabilization of the interaction may be due to this channel-like structure of hydrated water molecules.

Electrostatic rate enhancement and transient complex of protein-protein association

The association of two proteins is bounded by the rate at which they, via diffusion, find each other while in appropriate relative orientations. Orientational constraints restrict this rate to approximately 10(5)-10(6) M(-1) s(-1). Proteins with higher association rates generally have complementary electrostatic surfaces; proteins with lower association rates generally are slowed down by conformational changes upon complex formation. Previous studies (Zhou, Biophys J 1997;73:2441-2445) have shown that electrostatic enhancement of the diffusion-limited association rate can be accurately modeled by $k_{\bf D}$ = $k_{D}0\ {exp} ( - \langle U_{el} \rangle;{\star}/k_{B} T),$ where k(D) and k(D0) are the rates in the presence and absence of electrostatic interactions, respectively, U(el) is the average electrostatic interaction energy in a "transient-complex" ensemble, and k(B)T is the thermal energy. The transient-complex ensemble separates the bound state from the unbound state. Predictions of the transient-complex theory on four protein complexes were found to agree well with the experiment when the electrostatic interaction energy was calculated with the linearized Poisson-Boltzmann (PB) equation (Alsallaq and Zhou, Structure 2007;15:215-224). Here we show that the agreement is further improved when the nonlinear PB equation is used. These predictions are obtained with the dielectric boundary defined as the protein van der Waals surface. When the dielectric boundary is instead specified as the molecular surface, electrostatic interactions in the transient complex become repulsive and are thus predicted to retard association. Together these results demonstrate that the transient-complex theory is predictive of electrostatic rate enhancement and can help parameterize PB calculations.