Who checks the checkers? Four validation tools applied to eight atomic resolution structures. EU 3-D Validation Network

Learning Correlations between Internal Coordinates to Improve 3D Cartesian Coordinates for Proteins

We consider a generic representation problem of internal coordinates (bond lengths, valence angles, and dihedral angles) and their transformation to 3-dimensional Cartesian coordinates of a biomolecule. We show that the internal-to-Cartesian process relies on correctly predicting chemically subtle correlations among the internal coordinates themselves, and learning these correlations increases the fidelity of the Cartesian representation. We developed a machine learning algorithm, Int2Cart, to predict bond lengths and bond angles from backbone torsion angles and residue types of a protein, which allows reconstruction of protein structures better than using fixed bond lengths and bond angles or a static library method that relies on backbone torsion angles and residue types in a local environment. The method is able to be used for structure validation, as we show that the agreement between Int2Cart-predicted bond geometries and those from an AlphaFold 2 model can be used to estimate model quality. Additionally, by using Int2Cart to reconstruct an IDP ensemble, we are able to decrease the clash rate during modeling. The Int2Cart algorithm has been implemented as a publicly accessible python package at https://github.com/THGLab/int2cart.

When are two hydrogen bonds better than one? Accurate first-principles models explain the balance of hydrogen bond donors and acceptors found in proteins

Hydrogen bonds (HBs) play an essential role in the structure and catalytic action of enzymes, but a complete understanding of HBs in proteins challenges the resolution of modern structural (i.e., X-ray diffraction) techniques and mandates computationally demanding electronic structure methods from correlated wavefunction theory for predictive accuracy. Numerous amino acid sidechains contain functional groups (e.g., hydroxyls in Ser/Thr or Tyr and amides in Asn/Gln) that can act as either HB acceptors or donors (HBA/HBD) and even form simultaneous, ambifunctional HB interactions. To understand the relative energetic benefit of each interaction, we characterize the potential energy surfaces of representative model systems with accurate coupled cluster theory calculations. To reveal the relationship of these energetics to the balance of these interactions in proteins, we curate a set of 4000 HBs, of which >500 are ambifunctional HBs, in high-resolution protein structures. We show that our model systems accurately predict the favored HB structural properties. Differences are apparent in HBA/HBD preference for aromatic Tyr versus aliphatic Ser/Thr hydroxyls because Tyr forms significantly stronger O–H⋯O HBs than N–H⋯O HBs in contrast to comparable strengths of the two for Ser/Thr. Despite this residue-specific distinction, all models of residue pairs indicate an energetic benefit for simultaneous HBA and HBD interactions in an ambifunctional HB. Although the stabilization is less than the additive maximum due both to geometric constraints and many-body electronic effects, a wide range of ambifunctional HB geometries are more favorable than any single HB interaction.

Correlated wavefunction theory predicts and high-resolution crystal structure analysis confirms the important, stabilizing effect of simultaneous hydrogen bond donor and acceptor interactions in proteins.

Iris: Interactive all-in-one graphical validation of 3D protein model iterations

Iris validation is a Python package created to represent comprehensive per‐residue validation metrics for entire protein chains in a compact, readable and interactive view. These metrics can either be calculated by Iris, or by a third‐party program such as MolProbity. We show that those parts of a protein model requiring attention may generate ripples across the metrics on the diagram, immediately catching the modeler's attention. Iris can run as a standalone tool, or be plugged into existing structural biology software to display per‐chain model quality at a glance, with a particular emphasis on evaluating incremental changes resulting from the iterative nature of model building and refinement. Finally, the integration of Iris into the CCP4i2 graphical user interface is provided as a showcase of its pluggable design.

Unraveling the structural and chemical features of biological short hydrogen bonds

Short hydrogen bonds are ubiquitous in biological macromolecules and exhibit distinctive proton potential energy surfaces and proton sharing properties.

The three-dimensional architecture of biomolecules often creates specialized structural elements, notably short hydrogen bonds that have donor–acceptor separations below 2.7 Å. In this work, we statistically analyze 1663 high-resolution biomolecular structures from the Protein Data Bank and demonstrate that short hydrogen bonds are prevalent in proteins, protein–ligand complexes and nucleic acids. From these biological macromolecules, we characterize the preferred location, connectivity and amino acid composition in short hydrogen bonds and hydrogen bond networks, and assess their possible functional importance. Using electronic structure calculations, we further uncover how the interplay of the structural and chemical features determines the proton potential energy surfaces and proton sharing conditions in biological short hydrogen bonds.

Stereochemistry and Validation of Macromolecular Structures

Macromolecular structure is governed by the strict rules of stereochemistry. Several approaches to the validation of the correctness of the interpretation of crystallographic and NMR data that underlie the models deposited in the PDB are utilized in practice. The stereochemical rules applicable to macromolecular structures are discussed in this chapter. Practical, computer-based methods and tools of verification of how well the models adhere to those established structural principles to assure their quality are summarized.

On the reliability of peptide nonplanarity seen in ultra-high resolution crystal structures

Ultra-high resolution protein crystal structures have been considered as relatively reliable sources for defining details of protein geometry, such as the extent to which the peptide unit deviates from planarity. Chellapa and Rose (Proteins 2015; 83:1687) recently called this into question, reporting that for a dozen representative protein structures determined at ∼ 1 Å resolution, the diffraction data could be equally well fit with models restrained to have highly planar peptides, i.e. having a standard deviation of the ω torsion angles of only ∼ 1° instead of the typically observed value of ∼ 6°. Here, we document both conceptual and practical shortcomings of that study and show that the more tightly restrained models are demonstrably incorrect and do not fit the diffraction data equally well. We emphasize the importance of inspecting electron density maps when investigating the agreement between a model and its experimental data. Overall, this report reinforces that modern standard refinement protocols have been well-conceived and that ultra-high resolution protein crystal structures, when evaluated carefully and used with an awareness of their levels of coordinate uncertainty, are powerful sources of information for providing reliable information about the details of protein geometry.

New Biological Insights from Better Structure Models

Structure validation is a key component of all steps in the structure determination process, from structure building, refinement, deposition, and evaluation all the way to post-deposition optimisation of structures in the Protein Data Bank (PDB) by re-refinement and re-building. Today, many aspects of protein structures are understood better than 10years ago, and combined with improved software and more computing power, the automated PDB_REDO procedure can significantly improve about 85% of all X-ray structures ever deposited in the PDB. We review structure validation, structure improvement, and a series of validation resources and facilities that give access to improved PDB files and to reports on the quality of the original and the improved structures. Post-deposition optimisation generally leads to improved protein structures and a series of examples will illustrate how that, in turn, leads to improved or even novel biological insights.

Bond distances in polypeptide backbones depend on the local conformation

By combining quantum-mechanical analysis of small model peptides and statistical surveys of high-resolution protein structures, a systematic conformational dependence of bond lengths in polypeptide backbones has been unveiled which involves both the peptide bond (C—O and C—N) and those bonds centred on the Cα atom. All of these bond lengths indeed display a systematic variability in the ψ angle according to both calculations and surveys of protein structures. The overall agreement between the computed and the statistical data suggests that these trends are essentially driven by local effects. The dependence of Cα distances on ψ is governed by interactions between the σ system of the Cα moiety and the C—O π system of the peptide bond. Maximum and minimum values for each bond distance are found for conformations with the specific bond perpendicular and parallel to the adjacent CONH peptide plane, respectively. On the other hand, the variability of the C—O and C—N distances is related to the strength of the interactions between the lone pair of the N atom and the C—O π* system, which is modulated by the ψ angle. The C—O and C—N distances are related but their trends are not strictly connected to peptide-bond planarity, although a correlation amongst all of these parameters is expected on the basis of the classical resonance model.

CING: an integrated residue-based structure validation program suite

We present a suite of programs, named CING for Common Interface for NMR Structure Generation that provides for a residue-based, integrated validation of the structural NMR ensemble in conjunction with the experimental restraints and other input data. External validation programs and new internal validation routines compare the NMR-derived models with empirical data, measured chemical shifts, distance- and dihedral restraints and the results are visualized in a dynamic Web 2.0 report. A red-orange-green score is used for residues and restraints to direct the user to those critiques that warrant further investigation. Overall green scores below ~20 % accompanied by red scores over ~50 % are strongly indicative of poorly modelled structures. The publically accessible, secure iCing webserver ( https://nmr.le.ac.uk ) allows individual users to upload the NMR data and run a CING validation analysis.

Virtual screening and in vitro assay of potential drug like inhibitors from spices against Glutathione-S-Transferase of Meloidogyne incognita

Glutathione S-transferases (GSTs) enzymes are critical antioxidant and detoxification system responsible for long-term existence of nematodes in host species. Hence, 16 phytochemicals predicted and reported to have potential nematicidal activity have been docked to GST enzyme of Meloidogyne incognita to assess their binding affinity and inhibitory activity. In vitro effects of these phytochemicals from in silico results have been done for validation of docking studies and efficacy in GST inhibition of following compounds such as alpha- pinene, alpha- terpineol, beta- caryophyllene, capsaicin, cinnamic acid, citronellol, curcumin, eugenol, geraniol, isoeugenol, linalool, myristicin, neral, NVA (N-vanillylnonanamide), piperine, vanillin have been revealed. Nematode inhibition in vitro bioassay for selected compounds could conclude that maximum mortality was observed with highest concentrations of beta- caryophyllene (78%) followed by eugenol (61.6%), cinnamic acid (55%) and N-vanillylnonanamide (49%). These findings thus suggest that the above phytochemicals could be potentially developed as nematicidal molecules against M. incognita infections.

Peptide bond distortions from planarity: new insights from quantum mechanical calculations and peptide/protein crystal structures

By combining quantum-mechanical analysis and statistical survey of peptide/protein structure databases we here report a thorough investigation of the conformational dependence of the geometry of peptide bond, the basic element of protein structures. Different peptide model systems have been studied by an integrated quantum mechanical approach, employing DFT, MP2 and CCSD(T) calculations, both in aqueous solution and in the gas phase. Also in absence of inter-residue interactions, small distortions from the planarity are more a rule than an exception, and they are mainly determined by the backbone ψ dihedral angle. These indications are fully corroborated by a statistical survey of accurate protein/peptide structures. Orbital analysis shows that orbital interactions between the σ system of C(α) substituents and the π system of the amide bond are crucial for the modulation of peptide bond distortions. Our study thus indicates that, although long-range inter-molecular interactions can obviously affect the peptide planarity, their influence is statistically averaged. Therefore, the variability of peptide bond geometry in proteins is remarkably reproduced by extremely simplified systems since local factors are the main driving force of these observed trends. The implications of the present findings for protein structure determination, validation and prediction are also discussed.

On the complexity of Engh and Huber refinement restraints: the angle τ as example

The angle τ (backbone N—C^α—C) is the most contested Engh and Huber refinement target parameter. It is shown that this parameter is ‘correct’ as a PDB-wide average, but can be improved by taking into account residue types, secondary structures and many other aspects of our knowledge of the biophysical relations between residue type and protein structure.

The Engh and Huber parameters for bond lengths and bond angles have been used uncontested in macromolecular structure refinement from 1991 until very recently, despite critical discussion of their ubiquitous validity by many authors. An extensive analysis of the backbone angle τ (N—C^α—C) illustrates that the Engh and Huber parameters can indeed be improved and a recent study [Tronrud et al. (2010 ▶), Acta Cryst. D66, 834–842] confirms these ideas. However, the present study of τ shows that improving the Engh and Huber parameters will be considerably more complex than simply making the parameters a function of the backbone ϕ, ψ angles. Many other aspects, such as the cooperativity of hydrogen bonds, the bending of secondary-structure elements and a series of biophysical aspects of the 20 amino-acid types, will also need to be taken into account. Different sets of Engh and Huber parameters will be needed for conceptually different refinement programs.

Proteins do not have strong spines after all

In this issue of Structure, Berkholz et al. show that the detailed backbone geometry of proteins depends on the local conformation and suggest how this information can be practically used in modeling and refining protein structures.

X-ray crystal structure of GarR-tartronate semialdehyde reductase from Salmonella typhimurium

Tartronate semialdehyde reductases (TSRs), also known as 2-hydroxy-3-oxopropionate reductases, catalyze the reduction of tartronate semialdehyde using NAD as cofactor in the final stage of D-glycerate biosynthesis. These enzymes belong to family of structurally and mechanically related beta-hydroxyacid dehydrogenases which differ in substrate specificity and catalyze reactions in specific metabolic pathways. Here, we present the crystal structure of GarR a TSR from Salmonella typhimurium determined by the single-wavelength anomalous diffraction method and refined to 1.65 A resolution. The active site of the enzyme contains L-tartrate which most likely mimics a position of a glycerate which is a product of the enzyme reaction. The analysis of the TSR structure shows also a putative NADPH binding site in the enzyme.

Protein crystallography for non-crystallographers, or how to get the best (but not more) from published macromolecular structures

The number of macromolecular structures deposited in the Protein Data Bank now exceeds 45,000, with the vast majority determined using crystallographic methods. Thousands of studies describing such structures have been published in the scientific literature, and 14 Nobel prizes in chemistry or medicine have been awarded to protein crystallographers. As important as these structures are for understanding the processes that take place in living organisms and also for practical applications such as drug design, many non-crystallographers still have problems with critical evaluation of the structural literature data. This review attempts to provide a brief outline of technical aspects of crystallography and to explain the meaning of some parameters that should be evaluated by users of macromolecular structures in order to interpret, but not over-interpret, the information present in the coordinate files and in their description. A discussion of the extent of the information that can be gleaned from the coordinates of structures solved at different resolution, as well as problems and pitfalls encountered in structure determination and interpretation are also covered.

Predicting 13Calpha chemical shifts for validation of protein structures

The (13)C(alpha) chemical shifts for 16,299 residues from 213 conformations of four proteins (experimentally determined by X-ray crystallography and Nuclear Magnetic Resonance methods) were computed by using a combination of approaches that includes, but is not limited to, the use of density functional theory. Initially, a validation test of this methodology was carried out by a detailed examination of the correlation between computed and observed (13)C(alpha) chemical shifts of 10,564 (of the 16,299) residues from 139 conformations of the human protein ubiquitin. The results of this validation test on ubiquitin show agreement with conclusions derived from computation of the chemical shifts at the ab initio Hartree-Fock level. Further, application of this methodology to 5,735 residues from 74 conformations of the three remaining proteins that differ in their number of amino acid residues, sequence and three-dimensional structure, together with a new scoring function, namely the conformationally averaged root-mean-square-deviation, enables us to: (a) offer a criterion for an accurate assessment of the quality of NMR-derived protein conformations; (b) examine whether X-ray or NMR-solved structures are better representations of the observed (13)C(alpha) chemical shifts in solution; (c) provide evidence indicating that the proposed methodology is more accurate than automated predictors for validation of protein structures; (d) shed light as to whether the agreement between computed and observed (13)C(alpha) chemical shifts is influenced by the identity of an amino acid residue or its location in the sequence; and (e) provide evidence confirming the presence of dynamics for proteins in solution, and hence showing that an ensemble of conformations is a better representation of the structure in solution than any single conformation.

TAP score: torsion angle propensity normalization applied to local protein structure evaluation

BACKGROUND

Experimentally determined protein structures may contain errors and require validation. Conformational criteria based on the Ramachandran plot are mainly used to distinguish between distorted and adequately refined models. While the readily available criteria are sufficient to detect totally wrong structures, establishing the more subtle differences between plausible structures remains more challenging.

RESULTS

A new criterion, called TAP score, measuring local sequence to structure fitness based on torsion angle propensities normalized against the global minimum and maximum is introduced. It is shown to be more accurate than previous methods at estimating the validity of a protein model in terms of commonly used experimental quality parameters on two test sets representing the full PDB database and a subset of obsolete PDB structures. Highly selective TAP thresholds are derived to recognize over 90% of the top experimental structures in the absence of experimental information. Both a web server and an executable version of the TAP score are available at http://protein.cribi.unipd.it/tap/.

CONCLUSION

A novel procedure for energy normalization (TAP) has significantly improved the possibility to recognize the best experimental structures. It will allow the user to more reliably isolate problematic structures in the context of automated experimental structure determination.

CRYBA4, a novel human cataract gene, is also involved in microphthalmia

Genetic analysis of a large Indian family with an autosomal dominant cataract phenotype allowed us to identify a novel cataract gene, CRYBA4. After a genomewide screen, linkage analysis identified a maximum LOD score of 3.20 (recombination fraction [theta] 0.001) with marker D22S1167 of the beta -crystallin gene cluster on chromosome 22. To date, CRYBA4 was the only gene in this cluster not associated with either human or murine cataracts. A pathogenic mutation was identified in exon 4 that segregated with the disease status. The c.317T-->C sequence change is predicted to replace the highly conserved hydrophobic amino acid phenylalanine94 with the hydrophilic amino acid serine. Modeling suggests that this substitution would significantly reduce the intrinsic stability of the crystalline monomer, which would impair its ability to form the association modes critical for lens transparency. Considering that CRYBA4 associates with CRYBB2 and that the latter protein has been implicated in microphthalmia, mutational analysis of CRYBA4 was performed in 32 patients affected with microphthalmia (small eye). We identified a c.242T-->C (Leu69Pro) sequence change in exon 4 in one patient, which is predicted here to disrupt the beta -sheet structure in CRYBA4. Protein folding would consequently be impaired, most probably leading to a structure with reduced stability in the mutant. This is the first report linking mutations in CRYBA4 to cataractogenesis and microphthalmia.

The flexibility in the proline ring couples to the protein backbone

In proteins, the proline ring exists predominantly in two discrete states. However, there is also a small but significant amount of flexibility in the proline ring of high-resolution protein structures. We have found that this side-chain flexibility is coupled to the backbone conformation. To study this coupling, we have developed a model that is simply based on geometric and steric factors and not on energetics. We show that the coupling between phi and chi1 torsions in the proline ring can be described by an analytic equation that was developed by Bricard in 1897, and we describe a computer algorithm that implements the equation. The model predicts the observed coupling very well. The strain in the C(gamma)-C(delta)-N angle appears to be the principal barrier between the UP and DOWN pucker. This strain is relaxed to allow the proline ring to flatten in the rare PLANAR conformation.

Effects of p47 C Terminus Phosphorylations on Binding Interactions with p40 and p67

The neutrophil NADPH oxidase produces superoxide anions in response to infection. This reaction is activated by association of cytosolic factors, p47phox and p67phox, and a small G protein Rac with the membranous flavocytochrome b558. Another cytosolic factor, p40phox, is associated to the complex and is reported to play regulatory roles. Initiation of the NADPH oxidase activation cascade has been reported as consecutive to phosphorylation on serines 359/370 and 379 of the p47phox C terminus. These serines surround a polyproline motif that can interact with the Src homology 3 (SH3) module of p40phox (SH3p40) or the C-terminal SH3 of p67phox (C-SH3p67). The latter one presents a higher affinity in the resting state for p47phox. A change in SH3 binding preference following phosphorylation has been postulated earlier. Here we report the crystal structures of SH3p40 alone or in complex with a 12-residue proline-rich region of p47phox at 1.46 angstrom resolution. Using intrinsic tryptophan fluorescence measurements, we compared the affinity of the strict polyproline motif and the whole C terminus peptide with both SH3p40 and C-SH3p67. These data reveal that SH3p40 can interact with a consensus polyproline motif but also with a noncanonical motif of the p47phox C terminus. The electrostatic surfaces of both SH3 are very different, and therefore the binding preference for C-SH3p67 can be attributed to the polyproline motif recognition and particularly to the Arg-368p47 binding mode. The noncanonical motif contributes equally to interaction with both SH3. The influence of serine phosphorylation on residues 359/370 and 379 on the affinity for both SH3 domains has been checked. We conclude that contrarily to previous suggestions, phosphorylation of Ser-359/370 does not modify the SH3 binding affinity for both SH3, whereas phosphorylation of Ser-379 has a destabilizing effect on both interactions. Other mechanisms than a phosphorylation induced switch between the two SH3 must therefore take place for NADPH oxidase activation cascade to start.

Molecular models of protein targets from Mycobacterium tuberculosis

Structural characterization of enzymes that belong to microbial metabolic pathways is very important for structure-based drug design since some of these proteins may be present in the bacterial genome, but absent in humans. Thus, metabolic pathways became potential targets for drug design. The motivation of this work is the fact that Mycobacterium tuberculosis is the cause of the deaths of millions of people in the world, so that the structural characterization of protein targets to propose new drugs has become essential. DBMODELING is a relational database, created to highlight the importance of methods of molecular modeling applied to the Mycobacterium tuberculosis genome with the aim of proposing protein-ligand docking analysis. There are currently more than 300 models for proteins from Mycobacterium tuberculosis genome in the database. The database contains a detailed description of the reaction catalyzed by each enzyme and their atomic coordinates. Information about structures, a tool for animated gif image, a table with a specification of the metabolic pathway, modeled protein, inputs used in modeling, and analysis methods used in this project are available in the database for download. The search tool can be used for researchers to find specific pathways or enzymes.

Parmodel: a web server for automated comparative modeling of proteins

Parmodel is a web server for automated comparative modeling and evaluation of protein structures. The aim of this tool is to help inexperienced users to perform modeling, assessment, visualization, and optimization of protein models as well as crystallographers to evaluate structures solved experimentally. It is subdivided in four modules: Parmodel Modeling, Parmodel Assessment, Parmodel Visualization, and Parmodel Optimization. The main module is the Parmodel Modeling that allows the building of several models for a same protein in a reduced time, through the distribution of modeling processes on a Beowulf cluster. Parmodel automates and integrates the main softwares used in comparative modeling as MODELLER, Whatcheck, Procheck, Raster3D, Molscript, and Gromacs. This web server is freely accessible at .

Homology model of the structure of influenza B virus HA1

Influenza B virus is one of two types of influenza virus that cause substantial morbidity and mortality in humans, the other being influenza A virus. The inability to provide lasting protection to humans against influenza B virus infection is due, in part, to antigenic drift of the viral surface glycoprotein, haemagglutinin (HA). Studies of the antigenicity of the HA of influenza B virus have been hampered by lack of knowledge of its structure. To address this gap, two possible models have been inferred for this structure, based on two known structures of the homologous HA of the influenza A virus (subtypes H3 and H9). Statistical, structural and functional analyses of these models suggested that they matched important details of experimental observations and did not differ from each other in any substantive way. These models were used to investigate two HA sites at which viral variants appeared to carry a selective advantage. It was found that each of these sites coevolved with nearby sites to compensate for either size or charge changes.

The PDZ2 Domain of Syntenin at Ultra-high Resolution: Bridging the Gap Between Macromolecular and Small Molecule Crystallography

The crystal structure of the second PDZ domain of the scaffolding protein syntenin was solved using data extending to 0.73 A resolution. The crystallographic model, including the hydrogen atoms and the anisotropic displacement parameters, was refined to a conventional R-factor of 7.5% and Rfree of 8.7%, making it the most precise crystallographic model of a protein molecule to date. The model reveals discrete disorder in several places in the molecule, and significant plasticity of the peptide bond, with some omega angles deviating by nearly 20 degrees from planarity. Most hydrogen atoms are easily identifiable in the electron density and weak hydrogen bonds of the C-H...O type are clearly visible between the beta-strands. The study sets a new standard for high-resolution protein crystallography.

The major conformational IgE-binding epitopes of hevein (Hev b6.02) are identified by a novel chimera-based allergen epitope mapping strategy

A novel approach to localize and reconstruct conformational IgE-binding epitope regions of hevein (Hev b6.02), a major natural rubber latex allergen, is described. An antimicrobial protein (AMP) from the amaranth Amaranthus caudatus was used as an immunologically non-IgE-binding adaptor molecule to which terminal or central parts of hevein were fused. Hevein and AMP share a structurally identical core region but have different N-terminal and C-terminal regions. Only 1 of 16 hevein-allergic patients showed weak IgE binding to purified native or recombinant AMP. Chimeric AMP with the hevein N terminus was recognized by IgE from 14 (88%) patients, and chimeric AMP with the hevein C terminus was recognized by IgE from 6 (38%) patients. In contrast, chimeric AMP containing the hevein core region was recognized by IgE from only two patients. When both the N-terminal and C-terminal regions of hevein were fused with the AMP core, IgE from all 16 patients bound to the chimera. This chimera was also able to significantly inhibit (>70%) IgE binding to the native hevein. On the contrary, linear synthetic peptides corresponding to hevein regions in the AMP chimeras showed no significant IgE binding capacity in either enzyme-linked immunosorbent assay or inhibition enzyme-linked immunosorbent assay. These results suggest that the IgE binding ability of hevein is essentially determined by its N-terminal and C-terminal regions and that major IgE-binding epitopes of hevein are conformational. The chimera-based epitope mapping strategy described here provides a valuable tool for defining structural epitopes and creating specific reagents for allergen immunotherapy.

Molecular modelling and site-directed mutagenesis of human GALR1 galanin receptor defines determinants of receptor subtype specificity

Human galanin is a 30 amino acid neuropeptide that elicits a range of biological activities by interaction with G protein-coupled receptors. We have generated a model of the human GALR1 galanin receptor subtype (hGALR1) based on the alpha carbon maps of frog rhodopsin and investigated the significance of potential contact residues suggested by the model using site-directed mutagenesis. Mutation of Phe186 within the second extracellular loop to Ala resulted in a 6-fold decrease in affinity for galanin, representing a change in free energy consistent with hydrophobic interaction. Our model suggests interaction between Phe186 of hGALR1 and Ala7 or Leu11 of galanin. Receptor subtype specificity was investigated by replacement of residues in hGALR1 with the corresponding residues in hGALR2 and use of the hGALR2-specific ligands hGalanin(2-30) and [D-Trp2]hGalanin(1-30). The His267Ile mutant receptor exhibited a pharmacological profile corresponding to that of hGALR1, suggesting that His267 is not involved in a receptor-ligand interaction. The mutation Phe115Ala resulted in a decreased binding affinity for hGalanin and for hGALR2-specific analogues, indicating Phe115 to be of structural importance to the ligand binding pocket of hGALR1 but not involved in direct ligand interaction. Analysis of Glu271Trp suggested that Glu271 of hGALR1 interacts with the N-terminus of galanin and that the Trp residue in the corresponding position in hGALR2 is involved in receptor subtype specificity of binding. Our model supports previous reports of Phe282 of hGALR1 interacting with Trp2 of galanin and His264 of hGALR1 interacting with Tyr9 of galanin.

Molecular basis for interaction between Icap1 alpha PTB domain and beta 1 integrin

Icap1 alpha is a 200-amino acid protein that binds to the COOH-terminal 13 amino acids ((786)AVTTVVNPKYEGK(798)) of the integrin beta(1) subunit. Alanine scanning mutagenesis of this region revealed that Val(787), Val(790), and (792)NPKY(795) are critical for Icap1 alpha binding. The NPXY motif is a known binding substrate for phosphotyrosine binding (PTB) domain proteins. The sequences of Icap1 alpha, residues 58--200, and the beta(1) integrin, residues 786-797, were aligned to the available PTB-peptide structures to generate a high quality structural model. Site-directed mutagenesis showed that Leu(135), Ile(138), and Ile(139) of Icap1 alpha, residues predicted by the model to be in close proximity to (792)NPKY(795), and Leu(82) and Tyr(144), residues expected to form a hydrophobic pocket near Val(787), are required for the Icap1 alpha-beta(1) integrin interaction. These findings indicate that Icap1 alpha is a PTB domain protein, which recognizes the NPXY motif of beta(1) integrin. Furthermore, our date suggest that an interaction between Val(787) and the hydrophobic pocket created by Leu(82) and Tyr(144) of Icap1 alpha forms the basis for the specificity of Icap1 alpha for the beta(1) integrin subunit.

Functional characterization of an anti-estradiol antibody by site-directed mutagenesis and molecular modelling: modulation of binding properties and prominent role of the V(L) domain in estradiol recognition

The high-affinity monoclonal anti-estradiol antibody 9D3 presents a specificity defect towards estradiol-3-sulphate and 3-glucuronide conjugates incompatible with use in direct immunoassays. The corresponding single-chain variable fragment (scFv), cloned and produced in E. coli, exhibited a 10-fold lower affinity for estradiol (K(a)=1.2 x 10(9) M (-1)) and a slightly increased specificity defect for the 3-position. Site-directed mutagenesis revealed critical residues involved in estradiol recognition and produced mutants exhibiting up to a 3-fold increase of the binding affinity for estradiol and up to a 2-fold decrease of the cross-reactivity with estradiol-3-sulphate. A comparative model of the antibody 9D3-estradiol complex was built in which the estradiol D-ring is buried into the binding pocket while the 3-, 6- and 7-positions are solvent exposed, agreeing with the lack of specificity for these three positions. Two potential alternative orientations of the A-ring, one close to CDR H3 and L2 loops, and the other one close to CDR H2 and L3 loops, have been considered for the docking of estradiol, none of which could be unambiguously privileged taking into account data from cross-reactivity measurements, photolabelling and mutagenesis studies. For both orientations, estradiol is stabilized by hydrogen bonding of the 17beta-OH group with TyrL36, His89 and GlnH35 in the first case, or TyrL36, only, in the second case and by van der Waals contacts from TyrL91 with alpha- or beta-face of estradiol, respectively, and from ValH95 and GlyH97 with the opposite face. To elucidate the molecular basis of antibody 9D3 specificity, as compared with that of another anti-estradiol antibody 15H11, single variable domains (V(H) and V(L)) and scFv hybrids have been constructed. The binding activity of V(L)9D3 as well as the specificity of the V(L)9D3/V(H)15H11 hybrid, both similar to antibody 9D3, revealed a prominent role of V(L) in estradiol recognition. These findings establish premises for antibody engineering to reduce cross-reactivity, especially with estradiol-3-conjugates.

The interrelationships of side-chain and main-chain conformations in proteins

The accurate determination of a large number of protein structures by X-ray crystallography makes it possible to conduct a reliable statistical analysis of the distribution of the main-chain and side-chain conformational angles, how these are dependent on residue type, adjacent residue in the sequence, secondary structure, residue-residue interactions and location at the polypeptide chain termini. The interrelationship between the main-chain (phi, psi) and side-chain (chi 1) torsion angles leads to a classification of amino acid residues that simplify the folding alphabet considerably and can be a guide to the design of new proteins or mutational studies. Analyses of residues occurring with disallowed main-chain conformation or with multiple conformations shed some light on why some residues are less favoured in thermophiles.

Comparative protein structure modeling of genes and genomes

Comparative modeling predicts the three-dimensional structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. The number of protein sequences that can be modeled and the accuracy of the predictions are increasing steadily because of the growth in the number of known protein structures and because of the improvements in the modeling software. Further advances are necessary in recognizing weak sequence-structure similarities, aligning sequences with structures, modeling of rigid body shifts, distortions, loops and side chains, as well as detecting errors in a model. Despite these problems, it is currently possible to model with useful accuracy significant parts of approximately one third of all known protein sequences. The use of individual comparative models in biology is already rewarding and increasingly widespread. A major new challenge for comparative modeling is the integration of it with the torrents of data from genome sequencing projects as well as from functional and structural genomics. In particular, there is a need to develop an automated, rapid, robust, sensitive, and accurate comparative modeling pipeline applicable to whole genomes. Such large-scale modeling is likely to encourage new kinds of applications for the many resulting models, based on their large number and completeness at the level of the family, organism, or functional network.

Quality control in databanks for molecular biology

Using a scientific measurement without an estimate of its error is like lending money to a stranger. Given the explosion in nucleic acid and protein sequence and structural data, what risks are the scientific and medical communities running in using these databases. Is there an 'ombudsman' who speaks for the users of the data? CODATA, the Committee on Data for Science and Technology of the International Council of Scientific Unions was established to improve the quality, reliability, processing, management, and accessibility of data for science and technology. The CODATA Task Group on Biological Macromolecules has surveyed quality control procedures of archival databanks in molecular biology. Our role is 'to advise, to be consulted, and to warn.' This report describes the kinds and extents of errors that may appear in nucleic acid and protein databases, and presents an agenda for future work to improve the quality of these databases. The results of the survey appear on the webhttp://www.codata.org/codata/tgreports/ tg_reps.html.

Native protein sequences are close to optimal for their structures

How large is the volume of sequence space that is compatible with a given protein structure? Starting from random sequences, low free energy sequences were generated for 108 protein backbone structures by using a Monte Carlo optimization procedure and a free energy function based primarily on Lennard-Jones packing interactions and the Lazaridis-Karplus implicit solvation model. Remarkably, in the designed sequences 51% of the core residues and 27% of all residues were identical to the amino acids in the corresponding positions in the native sequences. The lowest free energy sequences obtained for ensembles of native-like backbone structures were also similar to the native sequence. Furthermore, both the individual residue frequencies and the covariances between pairs of positions observed in the very large SH3 domain family were recapitulated in core sequences designed for SH3 domain structures. Taken together, these results suggest that the volume of sequence space optimal for a protein structure is surprisingly restricted to a region around the native sequence.

Structural basis for isotype selectivity of the human retinoic acid nuclear receptor

The human retinoic acid receptor (hRAR) belongs to the family of nuclear receptors that regulate transcription in a ligand-dependent way. The isotypes RARalpha,beta and gamma are distinct pharmacological targets for retinoids that are involved in the treatment of various skin diseases and cancers, in particular breast cancer and acute promyelocytic leukemia. Therefore, synthetic retinoids have been developed aiming at isotype selectivity and reduced side-effects. We report the crystal structures of three complexes of the hRARgamma ligand-binding domain (LBD) bound to agonist retinoids that possess selectivity either for RARgamma (BMS184394) or for RARbeta/gamma (CD564), or that are potent for all RAR-isotypes (panagonist BMS181156). The high resolution data (1.3-1. 5 A) provide a description at the atomic level of the ligand pocket revealing the molecular determinants for the different degrees of ligand selectivity. The comparison of the complexes of the chemically closely related retinoids BMS184394 and CD564 shows that the side-chain of Met272 adopts different conformations depending on the presence of a hydrogen bond between its sulfur atom and the ligand. This accounts for their different isotype selectivity. On the other hand, the difference between the pan- and the RARbeta, gamma-selective agonist is probably due to a steric discrimination at the level of the 2-naphthoic acid moiety of CD564. Based on this study, we propose a model for a complex with the RARgamma-specific agonist CD666 that shows the possible applications for structure-based drug design of RAR isotype-selective retinoids.

Structural and functional studies with antibodies to the integrin beta 2 subunit. A model for the I-like domain

To establish a structure and function map of the beta2 integrin subunit, we mapped the epitopes of a panel of beta2 monoclonal antibodies including function-blocking, nonblocking, and activating antibodies using human/mouse beta2 subunit chimeras. Activating antibodies recognize the C-terminal half of the cysteine-rich region, residues 522-612. Antibodies that do not affect ligand binding map to residues 1-98 and residues 344-521. Monoclonal antibodies to epitopes within a predicted I-like domain (residues 104-341) strongly inhibit LFA-1-dependent adhesion. These function-blocking monoclonal antibodies were mapped to specific residues with human --> mouse knock-out or mouse --> human knock-in mutations. Combinatorial epitopes involving residues distant in the sequence provide support for a specific alignment between the beta-subunit and I domains that was used to construct a three-dimensional model. Antigenic residues 133, 332, and 339 are on the first and last predicted alpha-helices of the I-like domain, which are adjacent on its "front." Other antigenic residues in beta2 and in other integrin beta subunits are present on the front. No antigenic residues are present on the "back" of the domain, which is predicted to be in an interface with other domains, such as the alpha subunit beta-propeller domain. Most mutations in the beta2 subunit in leukocyte adhesion deficiency are predicted to be buried in the beta2 subunit I-like domain. Two long insertions are present relative to alpha-subunit I-domains. One is tied down to the back of the I-like domain by a disulfide bond. The other corresponds to the "specificity-determining loop" defined in beta1 and beta3 integrins and contains the antigenic residue Glu(175) in a disulfide-bonded loop located near the "top" of the domain.