ProSAT2--Protein Structure Annotation Server.

ProSAT2 is a server to facilitate interactive visualization of sequence-based, residue-specific annotations mapped onto 3D protein structures. As the successor of ProSAT (Protein Structure Annotation Tool), it includes its features for visualizing SwissProt and PROSITE functional annotations. Currently, the ProSAT2 server can perform automated mapping of information on variants and mutations from the UniProt KnowledgeBase and the BRENDA enzyme information system onto protein structures. It also accepts and maps user-prepared annotations. By means of an annotation selector, the user can interactively select and group residue-based information according to criteria such as whether a mutation affects enzyme activity. The visualization of the protein structures is based on the WebMol Java molecular viewer and permits simultaneous highlighting of annotated residues and viewing of the corresponding descriptive texts. ProSAT2 is available at http://projects.villa-bosch.de/mcm/database/prosat2/.

Computational approaches to structural and functional analysis of plastocyanin and other blue copper proteins.

Computational techniques are becoming increasingly important in structural and functional biology, in particular as tools to aid the interpretation of experimental results and the design of new systems. This review reports on recent studies employing a variety of computational approaches to unravel the microscopic details of the structure-function relationships in plastocyanin and other proteins belonging to the blue copper superfamily. Aspects covered include protein recognition, electron transfer and protein-solvent interaction properties of the blue copper protein family. The relevance of integrating diverse computational approaches to address the analysis of a complex protein system, such as a cupredoxin metalloprotein, is emphasized.

Electrostatic analysis and Brownian dynamics simulation of the association of plastocyanin and cytochrome f.

The oxidation of cytochrome f by the soluble cupredoxin plastocyanin is a central reaction in the photosynthetic electron transfer chain of all oxygenic organisms. Here, two different computational approaches are used to gain new insights into the role of molecular recognition and protein-protein association processes in this redox reaction. First, a comparative analysis of the computed molecular electrostatic potentials of seven single and multiple point mutants of spinach plastocyanin (D42N, E43K, E43N, E43Q/D44N, E59K/E60Q, E59K/E60Q/E43N, Q88E) and the wt protein was carried out. The experimentally determined relative rates (k(2)) for the set of plastocyanin mutants are found to correlate well (r(2) = 0.90 - 0.97) with the computed measure of the similarity of the plastocyanin electrostatic potentials. Second, the effects on the plastocyanin/cytochrome f association rate of these mutations in the plastocyanin "eastern site" were evaluated by simulating the association of the wild type and mutant plastocyanins with cytochrome f by Brownian dynamics. Good agreement between the computed and experimental relative rates (k(2)) (r(2) = 0.89 - 0.92) was achieved for the plastocyanin mutants. The results obtained by applying both computational techniques provide support for the fundamental role of the acidic residues at the plastocyanin eastern site in the association with cytochrome f and in the overall electron-transfer process.

Protein-protein association: investigation of factors influencing association rates by brownian dynamics simulations.

The rate of protein-protein association limits the response time due to protein-protein interactions. The bimolecular association rate may be diffusion-controlled or influenced, and in such cases, Brownian dynamics simulations of protein-protein diffusional association may be used to compute association rates. Here, we report Brownian dynamics simulations of the diffusional association of five different protein-protein pairs: barnase and barstar, acetylcholinesterase and fasciculin-2, cytochrome c peroxidase and cytochrome c, the HyHEL-5 antibody and hen egg lysozyme (HEL), and the HyHEL-10 antibody and HEL. The same protocol was used to compute the diffusional association rates for all the protein pairs in order to assess, by comparison to experimentally measured rates, whether the association of these proteins can be explained solely on the basis of diffusional encounter. The simulation protocol is similar to those previously derived for simulation of the association of barnase and barstar, and of acetylcholinesterase and fasciculin-2; these produced results in excellent agreement with experimental data for these protein pairs, with changes in association rate due to mutations reproduced within the limits of expected computational and modeling errors. Here, we find that for all protein pairs, the effects of mutations can be well reproduced by the simulations, even though the degree of the electrostatic translational and orientational steering varies widely between the cases. However, the absolute values of association rates for the acetylcholinesterase: fasciculin-2 and HyHEL-10 antibody: HEL pairs are overestimated. Comparison of bound and unbound protein structures shows that this may be due to gating resulting from protein flexibility in some of the proteins. This may lower the association rates compared to their bimolecular diffusional encounter rates.

Blue copper proteins: a comparative analysis of their molecular interaction properties.

Blue copper proteins are type-I copper-containing redox proteins whose role is to shuttle electrons from an electron donor to an electron acceptor in bacteria and plants. A large amount of experimental data is available on blue copper proteins; however, their functional characterization is hindered by the complexity of redox processes in biological systems. We describe here the application of a semiquantitative method based on a comparative analysis of molecular interaction fields to gain insights into the recognition properties of blue copper proteins. Molecular electrostatic and hydrophobic potentials were computed and compared for a set of 33 experimentally-determined structures of proteins from seven blue copper subfamilies, and the results were quantified by means of similarity indices. The analysis provides a classification of the blue copper proteins and shows that (I) comparison of the molecular electrostatic potentials provides useful information complementary to that highlighted by sequence analysis; (2) similarities in recognition properties can be detected for proteins belonging to different subfamilies, such as amicyanins and pseudoazurins, that may be isofunctional proteins; (3) dissimilarities in interaction properties, consistent with experimentally different binding specificities, may be observed between proteins belonging to the same subfamily, such as cyanobacterial and eukaryotic plastocyanins; (4) proteins with low sequence identity, such as azurins and pseudoazurins, can have sufficient similarity to bind to similar electron donors and acceptors while having different binding specificity profiles.

Classification of protein sequences by homology modeling and quantitative analysis of electrostatic similarity.

Protein electrostatics plays a key role in ligand binding and protein-protein interactions. Therefore, similarities or dissimilarities in electrostatic potentials can be used as indicators of similarities or dissimilarities in protein function. We here describe a method to compare the electrostatic properties within protein families objectively and quantitatively. Three-dimensional structures are built from database sequences by comparative modeling. Molecular potentials are then computed for these with a continuum solvation model by finite difference solution of the Poisson-Boltzmann equation or analytically as a multipole expansion that permits rapid comparison of very large datasets. This approach is applied to 104 members of the Pleckstrin homology (PH) domain family. The deviation of the potentials of the homology models from those of the corresponding experimental structures is comparable to the variation of the potential in an ensemble of structures from nuclear magnetic resonance data or between snapshots from a molecular dynamics simulation. For this dataset, the results for analysis of the full electrostatic potential and the analysis using only monopole and dipole terms are very similar. The electrostatic properties of the PH domains are generally conserved despite the extreme sequence divergence in this family. Notable exceptions from this conservation are seen for PH domains linked to a Db1 homology (DH) domain and in proteins with internal PH domain repeats.

On the protein-protein diffusional encounter complex.

When two proteins diffuse together to form a bound complex, an intermediate is formed at the end-point of diffusional association which is called the encounter complex. Its characteristics are important in determining association rates, yet its structure cannot be directly observed experimentally. Here, we address the problem of how to construct the ensemble of three-dimensional structures which constitute the protein-protein diffusional encounter complex using available experimental data describing the dependence of protein association rates on mutation and on solvent ionic strength and viscosity. The magnitude of the association rates is fitted well using a variety of definitions of encounter complexes in which the two proteins are located at up to about 17 A root-mean-squared distance from their relative arrangement in the bound complex. Analysis of the ionic strength dependence of bimolecular association rates shows that this is determined to a greater extent by the (protein charge) - (salt ion) separation distance than by the protein-protein charge separation distance. Consequently, ionic strength dependence of association rates provides little information about the geometry of the encounter complex. On the other hand, experimental data on electrostatic rate enhancement, mutation and viscosity dependence suggest a model of the encounter complex in which the two proteins form a subset of the contacts present in the bound complex and are significantly desolvated.

Computer simulation of protein-protein association kinetics: acetylcholinesterase-fasciculin.

Computer simulations were performed to investigate the role of electrostatic interactions in promoting fast association of acetylcholinesterase with its peptidic inhibitor, the neurotoxin fasciculin. The encounter of the two macromolecules was simulated with the technique of Brownian dynamics (BD), using atomically detailed structures, and association rate constants were calculated for the wild-type and a number of mutant proteins. In a first set of simulations, the ordering of the experimental rate constants for the mutant proteins was correctly reproduced, although the absolute values of the rate constants were overestimated by a factor of around 30. Rigorous calculations of the full electrostatic interaction energy between the two proteins indicate that this overestimation of association rates results at least in part from approximations made in the description of interaction energetics in the BD simulations. In particular, the initial BD simulations neglect the unfavourable electrostatic desolvation effects that result from the exclusion of high dielectric solvent that accompanies the approach of the two low dielectric proteins. This electrostatic desolvation component is so large that the overall contribution of electrostatics to the binding energy of the complex is unlikely to be strongly favourable. Nevertheless, electrostatic interactions are still responsible for increased association rates, because even if they are unfavourable in the fully formed complex, they are still favourable at intermediate protein-protein separation distances. It therefore appears possible for electrostatic interactions to promote the kinetics of binding even if they do not make a strongly favourable contribution to the thermodynamics of binding. When an approximate description of these electrostatic desolvation effects is included in a second set of BD simulations, the relative ordering of the mutant proteins is again correctly reproduced, but now association rate constants that are much closer in magnitude to the experimental values are obtained. Inclusion of electrostatic desolvation effects also improves reproduction of the experimental ionic strength dependence of the wild-type association rate.

Species dependence of enzyme-substrate encounter rates for triose phosphate isomerases.

Triose phosphate isomerase (TIM) is a diffusion-controlled enzyme whose rate is limited by the diffusional encounter of the negatively charged substrate glyceraldehyde 3-phosphate (GAP) with the homodimeric enzyme's active sites. Translational and orientational steering of GAP toward the active sites by the electrostatic field of chicken muscle TIM has been observed in previous Brownian dynamics (BD) simulations. Here we report simulations of the association of GAP with TIMs from four species with net charges at pH 7 varying from -12e to +12e. Computed second-order rate constants are in good agreement with experimental data. The BD simulations and computation of average Boltzmann factors of substrate-protein interaction energies show that the protein electrostatic potential enhances the rates for all the enzymes. There is much less variation in the computed rates than might be expected on the basis of the net charges. Comparison of the electrostatic potentials by means of similarity indices shows that this is due to conservation of the local electrostatic potentials around the active sites which are the primary determinants of electrostatic steering of the substrate.

Electrostatic steering and ionic tethering in enzyme-ligand binding: insights from simulations.

To bind at an enzyme's active site, a ligand must diffuse or be transported to the enzyme's surface, and, if the binding site is buried, the ligand must diffuse through the protein to reach it. Although the driving force for ligand binding is often ascribed to the hydrophobic effect, electrostatic interactions also influence the binding process of both charged and nonpolar ligands. First, electrostatic steering of charged substrates into enzyme active sites is discussed. This is of particular relevance for diffusion-influenced enzymes. By comparing the results of Brownian dynamics simulations and electrostatic potential similarity analysis for triose-phosphate isomerases, superoxide dismutases, and beta-lactamases from different species, we identify the conserved features responsible for the electrostatic substrate-steering fields. The conserved potentials are localized at the active sites and are the primary determinants of the bimolecular association rates. Then we focus on a more subtle effect, which we will refer to as "ionic tethering." We explore, by means of molecular and Brownian dynamics simulations and electrostatic continuum calculations, how salt links can act as tethers between structural elements of an enzyme that undergo conformational change upon substrate binding, and thereby regulate or modulate substrate binding. This is illustrated for the lipase and cytochrome P450 enzymes. Ionic tethering can provide a control mechanism for substrate binding that is sensitive to the electrostatic properties of the enzyme's surroundings even when the substrate is nonpolar.

Brownian dynamics simulation of protein-protein diffusional encounter.

Protein association events are ubiquitous in biological systems. Some protein associations and subsequent responses are diffusion controlled in vivo. Hence, it is important to be able to compute bimolecular diffusional association rates for proteins. The Brownian dynamics simulation methodology may be used to simulate protein-protein encounter, compute association rates, and examine their dependence on protein mutation and the nature of the physical environment (e.g., as a function of ionic strength or viscosity). Here, the theory for Brownian dynamics simulations is described, and important methodological aspects, particularly pertaining to the correct modeling of electrostatic forces and definition of encounter complex formation, are highlighted. To illustrate application of the method, simulations of the diffusional encounter of the extracellular ribonuclease, barnase, and its intracellular inhibitor, barstar, are described. This shows how experimental rates for a series of mutants and the dependence of rates on ionic strength can be reproduced well by Brownian dynamics simulations. Potential future uses of the Brownian dynamics method for investigating protein-protein association are discussed.

Classification of auxin plant hormones by interaction property similarity indices.

Although auxins were the first type of plant hormone to be identified, little is known about the molecular mechanism of this important class of plant hormones. We present a classification of a set of about 50 compounds with measured auxin activities, according to their interaction properties. Four classes of compounds were defined: strongly active, weakly active with weak antiauxin behaviour, inactive and inhibitory. All compounds were modeled in two low-energy conformations, 'P' and 'T', so as to obtain the best match to the 'planar' and 'tilted' conformations, respectively, of indole 3-acetic acid. Each set of conformers was superimposed separately using several different alignment schemes. Molecular interaction energy fields were computed for each molecule with five different chemical probes and then compared by computing similarity indices. Similarity analysis showed that the classes are on average distinguishable, with better differentiation achieved for the T conformers than the P conformers. This indicates that the T conformation might be the active one. Further, a screening was developed which could distinguish compounds with auxin activity from inactive compounds and most antiauxins using the T conformers. The classifications rationalize ambiguities in activity data found in the literature and should be of value in predicting the activities of new plant growth substances and herbicides.

Simulation of the diffusional association of barnase and barstar.

The rate of protein association places an upper limit on the response time due to protein interactions, which, under certain circumstances, can be diffusion-controlled. Simulations of model proteins show that diffusion-limited association rates are approximately 10(6)-10(7) M-1 s-1 in the absence of long-range forces (Northrup, S. H., and H. P. Erickson. 1992. Kinetics of protein-protein association explained by Brownian dynamics computer simulations. Proc. Natl. Acad. Sci. U.S.A. 89:3338-3342). The measured association rates of barnase and barstar are 10(8)-10(9) M-1 s-1 at 50 mM ionic strength, and depend on ionic strength (Schreiber, G., and A. R. Fersht. 1996. Rapid, electrostatically assisted association of proteins. Nat. Struct. Biol. 3:427-431), implying that their association is electrostatically facilitated. We report Brownian dynamics simulations of the diffusional association of barnase and barstar to compute association rates and their dependence on ionic strength and protein mutation. Crucial to the ability to reproduce experimental rates is the definition of encounter complex formation at the endpoint of diffusional motion. Simple definitions, such as a required root mean square (RMS) distance to the fully bound position, fail to explain the large influence of some mutations on association rates. Good agreement with experiments could be obtained if satisfaction of two intermolecular residue contacts was required for encounter complex formation. In the encounter complexes, barstar tends to be shifted from its position in the bound complex toward the guanine-binding loop on barnase.

Analytically defined surfaces to analyze molecular interaction properties.

Molecular surfaces are widely used for characterizing molecules and displaying and quantifying their interaction properties. Here we consider molecular surfaces defined as isocontours of a function (a sum of exponential functions centered on each atom) that approximately represents electron density. The smoothness is advantageous for surface mapping of molecular properties (e.g., electrostatic potential). By varying parameters, these surfaces can be constructed to represent the van der Waals or solvent-accessible surface of a molecular with any accuracy. We describe numerical algorithms to operate on the analytically defined surfaces. Two applications are considered: (1) We define and locate extremal points of molecular properties on the surfaces. The extremal points provide a compact representation of a property on a surface, obviating the necessity to compute values of the property on an array of surface points as is usually done; (2) a molecular surface patch or interface is projected onto a flat surface (by introducing curvilinear coordinates) with approximate conservation of area for analysis purposes. Applications to studies of protein-protein interactions are described.