SWOTein: a structure-based approach to predict stability Strengths and Weaknesses of prOTEINs.

MOTIVATION: Although structured proteins adopt their lowest free energy conformation in physiological conditions, the individual residues are generally not in their lowest free energy conformation. Residues that are stability weaknesses are often involved in functional regions, whereas stability strengths ensure local structural stability. The detection of strengths and weaknesses provides key information to guide protein engineering experiments aiming to modulate folding and various functional processes. RESULTS: We developed the SWOTein predictor which identifies strong and weak residues in proteins on the basis of three types of statistical energy functions describing local interactions along the chain, hydrophobic forces and tertiary interactions. The large-scale analysis of the different types of strengths and weaknesses demonstrated their complementarity and the enhancement of the information they provide. Moreover, a good average correlation was observed between predicted and experimental strengths and weaknesses obtained from native hydrogen exchange data. SWOTein application to three test cases further showed its suitability to predict and interpret strong and weak residues in the context of folding, conformational changes and protein-protein binding. In summary, SWOTein is both fast and accurate and can be applied at small and large scale to analyze and modulate folding and molecular recognition processes. AVAILABILITY: The SWOTein webserver provides the list of predicted strengths and weaknesses and a protein structure visualization tool that facilitates the interpretation of the predictions. It is freely available for academic use at http://babylone.ulb.ac.be/SWOTein/.

2P2Idb: a structural database dedicated to orthosteric modulation of protein-protein interactions.

Protein-protein interactions are considered as one of the next generation of therapeutic targets. Specific tools thus need to be developed to tackle this challenging chemical space. In an effort to derive some common principles from recent successes, we have built 2P2Idb (freely accessible at http://2p2idb.cnrs-mrs.fr), a hand-curated structural database dedicated to protein-protein interactions with known orthosteric modulators. It includes all interactions for which both the protein-protein and protein-ligand complexes have been structurally characterized. A web server provides links to related sites of interest, binding affinity data, pre-calculated structural information about protein-protein interfaces and 3D interactive views through java applets. Comparison of interfaces in 2P2Idb to those of representative datasets of heterodimeric complexes has led to the identification of geometrical parameters and residue properties to assess the druggability of protein-protein complexes. A tool is proposed to calculate a series of biophysical and geometrical parameters that characterize protein-protein interfaces. A large range of descriptors are computed including, buried accessible surface area, gap volume, non-bonded contacts, hydrogen-bonds, atom and residue composition, number of segments and secondary structure contribution. All together the 2P2I database represents a structural source of information for scientists from academic institutions or pharmaceutical industries.

The Automated Crystallography Pipelines at the EMBL HTX Facility in Grenoble.

EMBL Grenoble operates the High Throughput Crystallization Laboratory (HTX Lab), a large-scale user facility offering high throughput crystallography services to users worldwide. The HTX lab has a strong focus in the development of new methods in macromolecular crystallography. Through the combination of a high throughput crystallization platform, the CrystalDirect technology for fully automated crystal mounting and cryocooling and the CRIMS software we have developed fully automated pipelines for macromolecular crystallography that can be remotely operated over the internet. These include a protein-to-structure pipeline for the determination of new structures, a pipeline for the rapid characterization of protein-ligand complexes in support of medicinal chemistry, and a large-scale, automated fragment screening pipeline enabling evaluation of libraries of over 1000 fragments. Here we describe how to access and use these resources.

Amplitude of pancreatic lipase lid opening in solution and identification of spin label conformational subensembles by combining continuous wave and pulsed EPR spectroscopy and molecular dynamics.

The opening of the lid that controls the access to the active site of human pancreatic lipase (HPL) was measured from the magnetic interaction between two spin labels grafted on this enzyme. One spin label was introduced at a rigid position in HPL where an accessible cysteine residue (C181) naturally occurs. A second spin label was covalently bound to the mobile lid after introducing a cysteine residue at position 249 by site-directed mutagenesis. Double electron-electron resonance (DEER) experiments allowed the estimation of a distance of 19 +/- 2 A between the spin labels when bilabeled HPL was alone in a frozen solution, i.e., with the lid in the closed conformation. A magnetic interaction was however detected by continuous wave EPR experiments, suggesting that a fraction of bilabeled HPL contained spin labels separated by a shorter distance. These results could be interpreted by the presence of two conformational subensembles for the spin label lateral chain at position 249 when the lid was closed. The existence of these conformational subensembles was revealed by molecular dynamics experiments and confirmed by the simulation of the EPR spectrum. When the lid opening was induced by the addition of bile salts and colipase, a larger distance of 43 +/- 2 A between the two spin labels was estimated from DEER experiments. The distances measured between the spin labels grafted at positions 181 and 249 were in good agreement with those estimated from the known X-ray structures of HPL in the closed and open conformations, but for the first time, the amplitude of the lid opening was measured in solution or in a frozen solution in the presence of amphiphiles.

Computational analysis of the amino acid interactions that promote or decrease protein solubility.

The solubility of globular proteins is a basic biophysical property that is usually a prerequisite for their functioning. In this study, we probed the solubility of globular proteins with the help of the statistical potential formalism, in view of objectifying the connection of solubility with structural and energetic properties and of the solubility-dependence of specific amino acid interactions. We started by setting up two independent datasets containing either soluble or aggregation-prone proteins with known structures. From these two datasets, we computed solubility-dependent distance potentials that are by construction biased towards the solubility of the proteins from which they are derived. Their analysis showed the clear preference of amino acid interactions such as Lys-containing salt bridges and aliphatic interactions to promote protein solubility, whereas others such as aromatic, His-π, cation-π, amino-π and anion-π interactions rather tend to reduce it. These results indicate that interactions involving delocalized π-electrons favor aggregation, unlike those involving no (or few) dispersion forces. Furthermore, using our potentials derived from either highly or weakly soluble proteins to compute protein folding free energies, we found that the difference between these two energies correlates better with solubility than other properties analyzed before such as protein length, isoelectric point and aliphatic index. This is, to the best of our knowledge, the first comprehensive in silico study of the impact of residue-residue interactions on protein solubility properties.The results of this analysis provide new insights that will facilitate future rational protein design applications aimed at modulating the solubility of targeted proteins.

Predicting protein thermal stability changes upon point mutations using statistical potentials: Introducing HoTMuSiC.

The accurate prediction of the impact of an amino acid substitution on the thermal stability of a protein is a central issue in protein science, and is of key relevance for the rational optimization of various bioprocesses that use enzymes in unusual conditions. Here we present one of the first computational tools to predict the change in melting temperature ΔTm upon point mutations, given the protein structure and, when available, the melting temperature Tm of the wild-type protein. The key ingredients of our model structure are standard and temperature-dependent statistical potentials, which are combined with the help of an artificial neural network. The model structure was chosen on the basis of a detailed thermodynamic analysis of the system. The parameters of the model were identified on a set of more than 1,600 mutations with experimentally measured ΔTm. The performance of our method was tested using a strict 5-fold cross-validation procedure, and was found to be significantly superior to that of competing methods. We obtained a root mean square deviation between predicted and experimental ΔTm values of 4.2 °C that reduces to 2.9 °C when ten percent outliers are removed. A webserver-based tool is freely available for non-commercial use at soft.dezyme.com.

2P2I HUNTER: a tool for filtering orthosteric protein-protein interaction modulators via a dedicated support vector machine.

Over the last 10 years, protein-protein interactions (PPIs) have shown increasing potential as new therapeutic targets. As a consequence, PPIs are today the most screened target class in high-throughput screening (HTS). The development of broad chemical libraries dedicated to these particular targets is essential; however, the chemical space associated with this 'high-hanging fruit' is still under debate. Here, we analyse the properties of 40 non-redundant small molecules present in the 2P2I database (http://2p2idb.cnrs-mrs.fr/) to define a general profile of orthosteric inhibitors and propose an original protocol to filter general screening libraries using a support vector machine (SVM) with 11 standard Dragon molecular descriptors. The filtering protocol has been validated using external datasets from PubChem BioAssay and results from in-house screening campaigns. This external blind validation demonstrated the ability of the SVM model to reduce the size of the filtered chemical library by eliminating up to 96% of the compounds as well as enhancing the proportion of active compounds by up to a factor of 8. We believe that the resulting chemical space identified in this paper will provide the scientific community with a concrete support to search for PPI inhibitors during HTS campaigns.

Chemical and structural lessons from recent successes in protein-protein interaction inhibition (2P2I).

Worldwide research efforts have driven recent pharmaceutical successes, and consequently, the emerging role of Protein-Protein Interactions (PPIs) as drug targets has finally been widely embraced by the scientific community. Inhibitors of these Protein-Protein Interactions (2P2Is or i-PPIs) are likely to represent the next generation of highly innovative drugs that will reach the market over the next decade. This review describes up-to-date knowledge on this particular chemical space, with a specific emphasis on a subset of this ensemble. We also address current structural knowledge regarding both protein-protein and protein-inhibitor complexes, that is, the 2P2I database. Finally, ligand efficiency analyses permit us to relate potency to size and polarity and to discuss the need to co-develop nanoparticle drug delivery systems.

Atomic analysis of protein-protein interfaces with known inhibitors: the 2P2I database.

BACKGROUND: In the last decade, the inhibition of protein-protein interactions (PPIs) has emerged from both academic and private research as a new way to modulate the activity of proteins. Inhibitors of these original interactions are certainly the next generation of highly innovative drugs that will reach the market in the next decade. However, in silico design of such compounds still remains challenging. METHODOLOGY/PRINCIPAL FINDINGS: Here we describe this particular PPI chemical space through the presentation of 2P2I(DB), a hand-curated database dedicated to the structure of PPIs with known inhibitors. We have analyzed protein/protein and protein/inhibitor interfaces in terms of geometrical parameters, atom and residue properties, buried accessible surface area and other biophysical parameters. The interfaces found in 2P2I(DB) were then compared to those of representative datasets of heterodimeric complexes. We propose a new classification of PPIs with known inhibitors into two classes depending on the number of segments present at the interface and corresponding to either a single secondary structure element or to a more globular interacting domain. 2P2I(DB) complexes share global shape properties with standard transient heterodimer complexes, but their accessible surface areas are significantly smaller. No major conformational changes are seen between the different states of the proteins. The interfaces are more hydrophobic than general PPI's interfaces, with less charged residues and more non-polar atoms. Finally, fifty percent of the complexes in the 2P2I(DB) dataset possess more hydrogen bonds than typical protein-protein complexes. Potential areas of study for the future are proposed, which include a new classification system consisting of specific families and the identification of PPI targets with high druggability potential based on key descriptors of the interaction. CONCLUSIONS: 2P2I database stores structural information about PPIs with known inhibitors and provides a useful tool for biologists to assess the potential druggability of their interfaces. The database can be accessed at http://2p2idb.cnrs-mrs.fr.