EADock: docking of small molecules into protein active sites with a multiobjective evolutionary optimization.

In recent years, protein-ligand docking has become a powerful tool for drug development. Although several approaches suitable for high throughput screening are available, there is a need for methods able to identify binding modes with high accuracy. This accuracy is essential to reliably compute the binding free energy of the ligand. Such methods are needed when the binding mode of lead compounds is not determined experimentally but is needed for structure-based lead optimization. We present here a new docking software, called EADock, that aims at this goal. It uses an hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 A around the center of mass of the ligand position in the crystal structure, and on the contrary to other benchmarks, our algorithm was fed with optimized ligand positions up to 10 A root mean square deviation (RMSD) from the crystal structure, excluding the latter. This validation illustrates the efficiency of our sampling strategy, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures could be explained by the presence of crystal contacts in the experimental structure. Finally, the ability of EADock to accurately predict binding modes on a real application was illustrated by the successful docking of the RGD cyclic pentapeptide on the alphaVbeta3 integrin, starting far away from the binding pocket.

Chemodiversity and molecular plasticity: recognition processes as explored by property spaces.

In the last few years, a need to account for molecular flexibility in drug-design methodologies has emerged, even if the dynamic behavior of molecular properties is seldom made explicit. For a flexible molecule, it is indeed possible to compute different values for a given conformation-dependent property and the ensemble of such values defines a property space that can be used to describe its molecular variability; a most representative case is the lipophilicity space. In this review, a number of applications of lipophilicity space and other property spaces are presented, showing that this concept can be fruitfully exploited: to investigate the constraints exerted by media of different levels of structural organization, to examine processes of molecular recognition and binding at an atomic level, to derive informative descriptors to be included in quantitative structure--activity relationships and to analyze protein simulations extracting the relevant information. Much molecular information is neglected in the descriptors used by medicinal chemists, while the concept of property space can fill this gap by accounting for the often-disregarded dynamic behavior of both small ligands and biomacromolecules. Property space also introduces some innovative concepts such as molecular sensitivity and plasticity, which appear best suited to explore the ability of a molecule to adapt itself to the environment variously modulating its property and conformational profiles. Globally, such concepts can enhance our understanding of biological phenomena providing fruitful descriptors in drug-design and pharmaceutical sciences.

Uncovering the genetic basis of adaptive change: on the intersection of landscape genomics and theoretical population genetics

A workshop recently held at the Ecole Polytechnique Federale de Lausanne (EPFL, Switzerland) was dedicated to understanding the genetic basis of adaptive change, taking stock of the different approaches developed in theoretical population genetics and landscape genomics and bringing together knowledge accumulated in both research fields. Indeed, an important challenge in theoretical population genetics is to incorporate effects of demographic history and population structure. But important design problems (e.g. focus on populations as units, focus on hard selective sweeps, no hypothesis-based framework in the design of the statistical tests) reduce their capability of detecting adaptive genetic variation. In parallel, landscape genomics offers a solution to several of these problems and provides a number of advantages (e.g. fast computation, landscape heterogeneity integration). But the approach makes several implicit assumptions that should be carefully considered (e.g. selection has had enough time to create a functional relationship between the allele distribution and the environmental variable, or this functional relationship is assumed to be constant). To address the respective strengths and weaknesses mentioned above, the workshop brought together a panel of experts from both disciplines to present their work and discuss the relevance of combining these approaches, possibly resulting in a joint software solution in the future.

Reinvention of chemotherapy: drug conjugates and nanoparticles.

PURPOSE OF REVIEW: Recent advances in nanotechnology have addressed some of the issues related to lack of selectivity and nonspecific toxicities associated with conventional chemotherapy. Nanoparticles are therapeutic carriers that can be fine tuned for specific application and for passive or active tumor targeting. RECENT FINDINGS: Although the nanoparticle field is rapidly expanding, there are to date only six nanoparticle-based drug delivery platforms and two antibody-drug conjugates that are clinically approved for cancer therapy. Here, we review the clinical data of liposomal anthracyclines, nanoparticle formulations of paclitaxel and trastuzumab emtansine. We then briefly comment on efficacy and safety issues of nanoparticles, as well as on the next-generation nanoparticles for cancer therapy. SUMMARY: The emerging development of cancer nanotechnology offers the opportunity of reinvestigating the potential of cytotoxic agents, improving tumor targeting and drug delivery, leading to better safety profile and antitumor activity. Adding specificity to nanoparticles may allow personalization of cancer therapy using chemotherapy.

4B.05: Plasma Lasma copeptin is associated with insulin resistance in a Swiss population-based study

OBJECTIVE: Previous studies suggest that arginine vasopressin may have a role in metabolic syndrome (MetS) and diabetes by altering liver glycogenolysis, insulin, and glucagon secretion and pituitary ACTH release. We tested whether plasma copeptin, the stable C-terminal fragment of arginine vasopressin prohormone, was associated with insulin resistance and MetS in a Swiss population-based study. DESIGN AND METHOD: We analyzed data from the population-based Swiss Kidney Project on Genes in Hypertension. Copeptin was assessed by an immunoluminometric assay. Insulin resistance was derived from the HOMA model and calculated as follows: (FPI x FPG)/22.5, where FPI is fasting plasma insulin concentration (mU/L) and FPG fasting plasma glucose (mmol/L). Subjects were classified as having the MetS according to the National Cholesterol Education Program Adult Treatment Panel III criteria. Mixed multivariate linear regression models were built to explore the association of insulin resistance with copeptin. In addition, multivariate logistic regression models were built to explore the association between MetS and copeptin. In the two analyses, adjustment was done for age, gender, center, tobacco and alcohol consumption, socioeconomic status, physical activity, intake of fruits and vegetables and 24 h urine flow rate. Copeptin was log-transformed for the analyses. RESULTS: Among the 1,089 subjects included in this analysis, 47% were male. Mean (SD) age and body mass index were 47.4 (17.6) years 25.0 (4.5) kg/m2. The prevalence of MetS was 10.5%. HOMA-IR was higher in men (median 1.3, IQR 0.7-2.1) than in women (median 1.0, IQR 0.5-1.6,P < 0.0001). Plasma copeptin was higher in men (median 5.2, IQR 3.7-7.8 pmol/L) than in women (median 3.0, IQR 2.2-4.3 pmol/L), P < 0.0001. HOMA-IR was positively associated with log-copeptin after full adjustment (β (95% CI) 0.19 (0.09-0.29), P < 0.001). MetS was not associated with copeptin after full adjustment (P = 0.92). CONCLUSIONS: Insulin resistance, but not MetS, was associated with higher copeptin levels. Further studies should examine whether modifying pharmacologically the arginine vasopressin system might improve insulin resistance, thereby providing insight into the causal nature of this association.

Toward on-the-fly quantum mechanical/molecular mechanical (QM/MM) docking: development and benchmark of a scoring function.

We address the challenges of treating polarization and covalent interactions in docking by developing a hybrid quantum mechanical/molecular mechanical (QM/MM) scoring function based on the semiempirical self-consistent charge density functional tight-binding (SCC-DFTB) method and the CHARMM force field. To benchmark this scoring function within the EADock DSS docking algorithm, we created a publicly available dataset of high-quality X-ray structures of zinc metalloproteins ( http://www.molecular-modelling.ch/resources.php ). For zinc-bound ligands (226 complexes), the QM/MM scoring yielded a substantially improved success rate compared to the classical scoring function (77.0% vs 61.5%), while, for allosteric ligands (55 complexes), the success rate remained constant (49.1%). The QM/MM scoring significantly improved the detection of correct zinc-binding geometries and improved the docking success rate by more than 20% for several important drug targets. The performance of both the classical and the QM/MM scoring functions compare favorably to the performance of AutoDock4, AutoDock4Zn, and AutoDock Vina.

Native-like, long synthetic peptides as components of sub-unit vaccines: practical and theoretical considerations for their use in humans.

Vaccines have been used as a successful tool in medicine by way of controlling many major diseases. In spite of this, vaccines today represent only a handful of all infectious diseases. Therefore, there is a pressing demand for improvements of existing vaccines with particular reference to higher efficacy and undisputed safety profiles. To this effect, as an alternative to available vaccine technologies, there has been a drive to develop vaccine candidate polypeptides by chemical synthesis. In our laboratory, we have recently developed a technology to manufacture long synthetic peptides of up to 130 residues, which are correctly folded and biologically active. This paper discusses the advantages of the molecularly defined, long synthetic peptide approach in the context of vaccine design, development and use in human vaccination.

T1-weighted MRI as a substitute to CT for refocusing planning in MR-guided focused ultrasound.

Precise focusing is essential for transcranial MRI-guided focused ultrasound (TcMRgFUS) to minimize collateral damage to non-diseased tissues and to achieve temperatures capable of inducing coagulative necrosis at acceptable power deposition levels. CT is usually used for this refocusing but requires a separate study (CT) ahead of the TcMRgFUS procedure. The goal of this study was to determine whether MRI using an appropriate sequence would be a viable alternative to CT for planning ultrasound refocusing in TcMRgFUS. We tested three MRI pulse sequences (3D T1 weighted 3D volume interpolated breath hold examination (VIBE), proton density weighted 3D sampling perfection with applications optimized contrasts using different flip angle evolution and 3D true fast imaging with steady state precision T2-weighted imaging) on patients who have already had a CT scan performed. We made detailed measurements of the calvarial structure based on the MRI data and compared those so-called 'virtual CT' to detailed measurements of the calvarial structure based on the CT data, used as a reference standard. We then loaded both standard and virtual CT in a TcMRgFUS device and compared the calculated phase correction values, as well as the temperature elevation in a phantom. A series of Bland-Altman measurement agreement analyses showed T1 3D VIBE as the optimal MRI sequence, with respect to minimizing the measurement discrepancy between the MRI derived total skull thickness measurement and the CT derived total skull thickness measurement (mean measurement discrepancy: 0.025; 95% CL (-0.22-0.27); p = 0.825). The T1-weighted sequence was also optimal in estimating skull CT density and skull layer thickness. The mean difference between the phase shifts calculated with the standard CT and the virtual CT reconstructed from the T1 dataset was 0.08 ± 1.2 rad on patients and 0.1 ± 0.9 rad on phantom. Compared to the real CT, the MR-based correction showed a 1 °C drop on the maximum temperature elevation in the phantom (7% relative drop). Without any correction, the maximum temperature was down 6 °C (43% relative drop). We have developed an approach that allows for a reconstruction of a virtual CT dataset from MRI to perform phase correction in TcMRgFUS.

Structural prediction of peptides bound to MHC class I.

An ab initio structure prediction approach adapted to the peptide-major histocompatibility complex (MHC) class I system is presented. Based on structure comparisons of a large set of peptide-MHC class I complexes, a molecular dynamics protocol is proposed using simulated annealing (SA) cycles to sample the conformational space of the peptide in its fixed MHC environment. A set of 14 peptide-human leukocyte antigen (HLA) A0201 and 27 peptide-non-HLA A0201 complexes for which X-ray structures are available is used to test the accuracy of the prediction method. For each complex, 1000 peptide conformers are obtained from the SA sampling. A graph theory clustering algorithm based on heavy atom root-mean-square deviation (RMSD) values is applied to the sampled conformers. The clusters are ranked using cluster size, mean effective or conformational free energies, with solvation free energies computed using Generalized Born MV 2 (GB-MV2) and Poisson-Boltzmann (PB) continuum models. The final conformation is chosen as the center of the best-ranked cluster. With conformational free energies, the overall prediction success is 83% using a 1.00 Angstroms crystal RMSD criterion for main-chain atoms, and 76% using a 1.50 Angstroms RMSD criterion for heavy atoms. The prediction success is even higher for the set of 14 peptide-HLA A0201 complexes: 100% of the peptides have main-chain RMSD values &lt; or =1.00 Angstroms and 93% of the peptides have heavy atom RMSD values &lt; or =1.50 Angstroms. This structure prediction method can be applied to complexes of natural or modified antigenic peptides in their MHC environment with the aim to perform rational structure-based optimizations of tumor vaccines.

SwissSidechain: a molecular and structural database of non-natural sidechains.

Amino acids form the building blocks of all proteins. Naturally occurring amino acids are restricted to a few tens of sidechains, even when considering post-translational modifications and rare amino acids such as selenocysteine and pyrrolysine. However, the potential chemical diversity of amino acid sidechains is nearly infinite. Exploiting this diversity by using non-natural sidechains to expand the building blocks of proteins and peptides has recently found widespread applications in biochemistry, protein engineering and drug design. Despite these applications, there is currently no unified online bioinformatics resource for non-natural sidechains. With the SwissSidechain database (http://www.swisssidechain.ch), we offer a central and curated platform about non-natural sidechains for researchers in biochemistry, medicinal chemistry, protein engineering and molecular modeling. SwissSidechain provides biophysical, structural and molecular data for hundreds of commercially available non-natural amino acid sidechains, both in l- and d-configurations. The database can be easily browsed by sidechain names, families or physico-chemical properties. We also provide plugins to seamlessly insert non-natural sidechains into peptides and proteins using molecular visualization software, as well as topologies and parameters compatible with molecular mechanics software.

Functional analysis of the post-transcriptional regulator RsmA reveals a novel RNA-binding site.

The RsmA family of RNA-binding proteins are global post-transcriptional regulators that mediate extensive changes in gene expression in bacteria. They bind to, and affect the translation rate of target mRNAs, a function that is further modulated by one or more, small, untranslated competitive regulatory RNAs. To gain new insights into the nature of this protein/RNA interaction, we used X-ray crystallography to solve the structure of the Yersinia enterocolitica RsmA homologue. RsmA consists of a dimeric beta barrel from which two alpha helices are projected. From structure-based alignments of the RsmA protein family from diverse bacteria, we identified key amino acid residues likely to be involved in RNA-binding. Site-specific mutagenesis revealed that arginine at position 44, located at the N terminus of the alpha helix is essential for biological activity in vivo and RNA-binding in vitro. Mutation of this site affects swarming motility, exoenzyme and secondary metabolite production in the human pathogen Pseudomonas aeruginosa, carbon metabolism in Escherichia coli, and hydrogen cyanide production in the plant beneficial strain Pseudomonas fluorescens CHA0. R44A mutants are also unable to interact with the small untranslated RNA, RsmZ. Thus, although possessing a motif similar to the KH domain of some eukaryotic RNA-binding proteins, RsmA differs substantially and incorporates a novel class of RNA-binding site.

Fifteen years SIB Swiss Institute of Bioinformatics: life science databases, tools and support.

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) was created in 1998 as an institution to foster excellence in bioinformatics. It is renowned worldwide for its databases and software tools, such as UniProtKB/Swiss-Prot, PROSITE, SWISS-MODEL, STRING, etc, that are all accessible on ExPASy.org, SIB's Bioinformatics Resource Portal. This article provides an overview of the scientific and training resources SIB has consistently been offering to the life science community for more than 15 years.

Electron cryo-microscopy reveals mechanism of action of propranolol on artificial membranes.

The pharmacological activity of several amphiphilic drugs is often related to their ability to interact with biological membranes. Propranolol is an efficient multidrug resistance (MDR) modulator; it is a nonselective beta-blocker and is thought to reduce hypertension by decreasing the cardiac frequency and thus blood pressure. It is used in drug delivery studies in order to treat systemic hypertension. We are interested in the interaction of propranolol with artificial membranes, as liposomes of controllable size are used as biocompatible and protective structures to encapsulate labile molecules, such as proteins, nucleic acids or drugs, for pharmaceutical, cosmetic or chemical applications. We present here a study of the interaction of propranolol, a cationic surfactant, with pure egg phosphatidylcholine (EPC) vesicles. The gradual transition from liposome to micelle of EPC vesicles in the presence of propranolol was monitored by time-resolved electron cryo-microscopy (cryo-EM) under different experimental conditions. The liposome-drug interaction was studied with varying drug/lipid (D/L) ratios and different stages were captured by direct thin-film vitrification. The time-series cryo-EM data clearly illustrate the mechanism of action of propranolol on the liposome structure: the drug disrupts the lipid bilayer by perturbing the local organization of the phospholipids. This is followed by the formation of thread-like micelles, also called worm-like micelles (WLM), and ends with the formation of spherical (globular) micelles. The overall reaction is slow, with the process taking almost two hours to be completed. The effect of a monovalent salt was also investigated by repeating the lipid-surfactant interaction experiments in the presence of KCl as an additive to the lipid/drug suspension. When KCl was added in the presence of propranolol the overall reaction was the same but with slower kinetics, suggesting that this monovalent salt affects the general lipid-to-micelle transition by stabilizing the membrane, presumably by binding to the carbonyl chains of the phosphatidylcholine.