Docking, virtual high throughput screening and in silico fragment-based drug design.

ABSTRACT The drug discovery process has been profoundly changed recently by the adoption of computational methods helping the design of new drug candidates more rapidly and at lower costs. In silico drug design consists of a collection of tools helping to make rational decisions at the different steps of the drug discovery process, such as the identification of a biomolecular target of therapeutical interest, the selection or the design of new lead compounds and their modification to obtain better affinities, as well as pharmacokinetic and pharmacodynamic properties. Among the different tools available, a particular emphasis is placed in this review on molecular docking, virtual high throughput screening and fragment-based ligand design.

iLOGP: A Simple, Robust, and Efficient Description of n-Octanol/Water Partition Coefficient for Drug Design Using the GB/SA Approach.

The n-octanol/water partition coefficient (log Po/w) is a key physicochemical parameter for drug discovery, design, and development. Here, we present a physics-based approach that shows a strong linear correlation between the computed solvation free energy in implicit solvents and the experimental log Po/w on a cleansed data set of more than 17,500 molecules. After internal validation by five-fold cross-validation and data randomization, the predictive power of the most interesting multiple linear model, based on two GB/SA parameters solely, was tested on two different external sets of molecules. On the Martel druglike test set, the predictive power of the best model (N = 706, r = 0.64, MAE = 1.18, and RMSE = 1.40) is similar to six well-established empirical methods. On the 17-drug test set, our model outperformed all compared empirical methodologies (N = 17, r = 0.94, MAE = 0.38, and RMSE = 0.52). The physical basis of our original GB/SA approach together with its predictive capacity, computational efficiency (1 to 2 s per molecule), and tridimensional molecular graphics capability lay the foundations for a promising predictor, the implicit log P method (iLOGP), to complement the portfolio of drug design tools developed and provided by the SIB Swiss Institute of Bioinformatics.

MALDI-TOF MS-based drug susceptibility testing of pathogens: The example of Candida albicans and fluconazole.

MALDI-TOF MS can be used for the identification of microorganism species. We have extended its application to a novel assay of Candida albicans susceptibility to fluconazole, based on monitoring modifications of the proteome of yeast cells grown in the presence of varying drug concentrations. The method was accurate, and reliable, and showed full agreement with the Clinical Laboratory Standards Institute's reference method. This proof-of-concept demonstration highlights the potential for this approach to test other pathogens.

A new poly(ortho ester)-based drug delivery system as an adjunct treatment in filtering surgery.

PURPOSE: Pharmacologic modulation of wound healing after glaucoma filtering surgery remains a major clinical challenge in ophthalmology. Poly(ortho ester) (POE) is a bioerodible and biocompatible viscous polymer potentially useful as a sustained drug delivery system that allows the frequency of intraocular injections to be reduced. The purpose of this study was to determine the efficacy of POE containing a precise amount of 5-fluorouracil (5-FU) in an experimental model of filtering surgery in the rabbit. METHODS: Trabeculectomy was performed in pigmented rabbit eyes. An ointmentlike formulation of POE containing 1% wt/wt 5-FU was injected subconjunctivally at the site of surgery, during the procedure. Intraocular pressure (IOP), bleb persistence, and ocular inflammatory reaction were monitored until postoperative day 30. Quantitative analysis of 5-FU was performed in the anterior chamber. Histologic analysis was used to assess the appearance of the filtering fistula and the polymer's biocompatibility. RESULTS: The decrease in IOP from baseline and the persistence of the filtering bleb were significantly more marked in the 5-FU-treated eyes during postoperative days 9 through 28. Corneal toxicity triggered by 5-FU was significantly lower in the group that received 5-FU in POE compared with a 5-FU tamponade. Histopathologic evaluation showed that POE was well tolerated, and no fibrosis occurred in eyes treated with POE containing 5-FU. CONCLUSIONS: In this rabbit model of trabeculectomy, the formulation based on POE and containing a precise amount of 5-FU reduced IOP and prolonged bleb persistence in a way similar to the conventional method of a 5-FU tamponade, while significantly reducing 5-FU toxicity.

Structure-Based, Rational Design of T Cell Receptors.

Adoptive cell transfer using engineered T cells is emerging as a promising treatment for metastatic melanoma. Such an approach allows one to introduce T cell receptor (TCR) modifications that, while maintaining the specificity for the targeted antigen, can enhance the binding and kinetic parameters for the interaction with peptides (p) bound to major histocompatibility complexes (MHC). Using the well-characterized 2C TCR/SIYR/H-2K(b) structure as a model system, we demonstrated that a binding free energy decomposition based on the MM-GBSA approach provides a detailed and reliable description of the TCR/pMHC interactions at the structural and thermodynamic levels. Starting from this result, we developed a new structure-based approach, to rationally design new TCR sequences, and applied it to the BC1 TCR targeting the HLA-A2 restricted NY-ESO-1157-165 cancer-testis epitope. Fifty-four percent of the designed sequence replacements exhibited improved pMHC binding as compared to the native TCR, with up to 150-fold increase in affinity, while preserving specificity. Genetically engineered CD8(+) T cells expressing these modified TCRs showed an improved functional activity compared to those expressing BC1 TCR. We measured maximum levels of activities for TCRs within the upper limit of natural affinity, K D = ∼1 - 5 μM. Beyond the affinity threshold at K D < 1 μM we observed an attenuation in cellular function, in line with the "half-life" model of T cell activation. Our computer-aided protein-engineering approach requires the 3D-structure of the TCR-pMHC complex of interest, which can be obtained from X-ray crystallography. We have also developed a homology modeling-based approach, TCRep 3D, to obtain accurate structural models of any TCR-pMHC complexes when experimental data is not available. Since the accuracy of the models depends on the prediction of the TCR orientation over pMHC, we have complemented the approach with a simplified rigid method to predict this orientation and successfully assessed it using all non-redundant TCR-pMHC crystal structures available. These methods potentially extend the use of our TCR engineering method to entire TCR repertoires for which no X-ray structure is available. We have also performed a steered molecular dynamics study of the unbinding of the TCR-pMHC complex to get a better understanding of how TCRs interact with pMHCs. This entire rational TCR design pipeline is now being used to produce rationally optimized TCRs for adoptive cell therapies of stage IV melanoma.

X-ray structures of Sap1 and Sap5: structural comparison of the secreted aspartic proteinases from Candida albicans.

Proteolytic activity is an important virulence factor for Candida albicans (C. albicans). It is attributed to the family of the secreted aspartic proteinases (Saps) from C. albicans with a minimum of 10 members. Saps show controlled expression and regulation for the individual stages of the infection process. Distinct isoenzymes can be responsible for adherence and tissue damage of local infections, while others cause systemic diseases. Earlier, only the structures of Sap2 and Sap3 were known. In our research, we have now succeeded in solving the X-ray crystal structures of the apoenzyme of Sap1 and Sap5 in complex with pepstatin A at 2.05 and 2.5 A resolution, respectively. With the structure of Sap1, we have completed the set of structures of isoenzyme subgroup Sap1-3. Of subgroup Sap4-6, the structure of the enzyme Sap5 is the first structure that has been described up to now. This facilitates comparison of structural details as well as inhibitor binding modes among the different subgroup members. Structural analysis reveals a highly conserved overall secondary structure of Sap1-3 and Sap5. However, Sap5 clearly differs from Sap1-3 by its electrostatic overall charge as well as through structural conformation of its entrance to the active site cleft. Design of inhibitors specific for Sap5 should concentrate on the S4 and S3 pockets, which significantly differ from Sap1-3 in size and electrostatic charge. Both Sap1 and Sap5 seem to play a major part in superficial Candida infections. Determination of the isoenzymes' structures can contribute to the development of new Sap-specific inhibitors for the treatment of superficial infections with a structure-based drug design program.

Rational design of indoleamine 2,3-dioxygenase inhibitors.

Indoleamine 2,3-dioxygenase (IDO) is an important therapeutic target for the treatment of diseases such as cancer that involve pathological immune escape. We have used the evolutionary docking algorithm EADock to design new inhibitors of this enzyme. First, we investigated the modes of binding of all known IDO inhibitors. On the basis of the observed docked conformations, we developed a pharmacophore model, which was then used to devise new compounds to be tested for IDO inhibition. We also used a fragment-based approach to design and to optimize small organic molecule inhibitors. Both approaches yielded several new low-molecular weight inhibitor scaffolds, the most active being of nanomolar potency in an enzymatic assay. Cellular assays confirmed the potential biological relevance of four different scaffolds.

EADock : design of a new molecular docking algorithm and some of its applications

3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a 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 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, 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 in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.

Synthesis and characterization of a new class of anti-angiogenic agents based on ruthenium clusters.

New triruthenium-carbonyl clusters derivatized with glucose-modified bicyclophosphite ligands have been synthesized. These compounds were found to have cytostatic and cytotoxic activity and depending on the number of bicyclophosphite ligands, and could be tuned for either anti-cancer or specific anti-angiogenic activity. While some compounds had a broad cellular toxicity profile in several cell types others showed endothelial cell specific dose-dependent anti-proliferative and anti-migratory efficacy. A profound inhibition of angiogenesis was also observed in the in vivo chicken chorioallantoic membrane (CAM) model, and consequently, these new compounds have considerable potential in drug design, e.g. for the treatment of cancer.

SwissDock, a protein-small molecule docking web service based on EADock DSS.

Most life science processes involve, at the atomic scale, recognition between two molecules. The prediction of such interactions at the molecular level, by so-called docking software, is a non-trivial task. Docking programs have a wide range of applications ranging from protein engineering to drug design. This article presents SwissDock, a web server dedicated to the docking of small molecules on target proteins. It is based on the EADock DSS engine, combined with setup scripts for curating common problems and for preparing both the target protein and the ligand input files. An efficient Ajax/HTML interface was designed and implemented so that scientists can easily submit dockings and retrieve the predicted complexes. For automated docking tasks, a programmatic SOAP interface has been set up and template programs can be downloaded in Perl, Python and PHP. The web site also provides an access to a database of manually curated complexes, based on the Ligand Protein Database. A wiki and a forum are available to the community to promote interactions between users. The SwissDock web site is available online at http://www.swissdock.ch. We believe it constitutes a step toward generalizing the use of docking tools beyond the traditional molecular modeling community.

Tools in pharmacovigilance in psychiatry: therapeutic drug monitoring, pharmacogenetic tests and drug-drug interactions databases

SUMMARYIn order to increase drug safety we must better understand how medication interacts with the body of our patients and this knowledge should be made easily available for the clinicians prescribing the medication. This thesis contributes to how the knowledge of some drug properties can increase and how to make information readily accessible for the medical professionals. Furthermore it investigates the use of Therapeutic drug monitoring, drug interaction databases and pharmacogenetic tests in pharmacovigilance.Two pharmacogenetic studies in the naturalistic setting of psychiatric in-patients clinics have been performed; one with the antidepressant mirtazapine, the other with the antipsychotic clozapine. Forty-five depressed patients have been treated with mirtazapine and were followed for 8 weeks. The therapeutic effect was as seen in other previous studies. Enantioselective analyses could confirm an influence of age, gender and smoking in the pharmacokinetics of mirtazapine; it showed a significant influence of the CYP2D6 genotype on the antidepressant effective S-enantiomer, and for the first time an influence of the CYP2B6 genotype on the plasma concentrations of the 8-OH metabolite was found. The CYP2B6*/*6 genotype was associated to better treatment response. A detailed hypothesis of the metabolic pathways of mirtazapine is proposed. In the second pharmacogenetic study, analyses of 75 schizophrenic patients treated with clozapine showed the influence of CYP450 and ABCB1 genotypes on its pharmacokinetics. For the first time we could demonstrate an in vivo effect of the CYP2C19 genotype and an influence of P-glycoprotein on the plasma concentrations of clozapine. Further we confirmed in vivo the prominent role of CYP1A2 in the metabolism of clozapine.Identifying risk factors for the occurrence of serious adverse drug reactions (SADR) would allow a more individualized and safer drug therapy. SADR are rare events and therefore difficult to study. We tested the feasibility of a nested matched case-control study to examine the influence of high drug plasma levels and CYP2D6 genotypes on the risk to experience an SADR. In our sample we compared 62 SADR cases with 82 controls; both groups were psychiatric patients from the in-patient clinic Königsfelden. Drug plasma levels of >120% of the upper recommended references could be identified as a risk factor with a statistically significant odds ratio of 3.5, a similar trend could be seen for CYP2D6 poor metaboliser. Although a matched case-control design seems a valid method, 100% matching is not easy to perform in a relative small cohort of one in-patient clinic. However, a nested case-control study is feasible.On the base of the experience gained in the AMSP+ study and the fact that we have today only sparse data indicating that routine drug plasma concentration monitoring and/or pharmacogenetic testing in psychiatry are justified to minimize the risk for ADR, we developed a test algorithm named "TDM plus" (TDM plus interaction checks plus pharmacogenetic testing).Pharmacovigilance programs such as the AMSP project (AMSP = Arzneimittelsicherheit in der Psychiatrie) survey psychiatric in-patients in order to collect SADR and to detect new safety signals. Case reports of such SADR are, although anecdotal, valuable to illustrate rare clinical events and sometimes confirm theoretical assumptions of e.g. drug interactions. Seven pharmacovigilance case reports are summarized in this thesis.To provide clinicians with meaningful information on the risk of drug combinations, during the course of this thesis the internet based drug interaction program mediQ.ch (in German) has been developed. Risk estimation is based on published clinical and pharmacological information of single drugs and alimentary products, including adverse drug reaction profiles. Information on risk factors such as renal and hepatic insufficiency and specific genotypes are given. More than 20'000 drug pairs have been described in detail. Over 2000 substances with their metabolic and transport pathways are included and all information is referenced with links to the published scientific literature or other information sources. Medical professionals of more than 100 hospitals and 300 individual practitioners do consult mediQ.ch regularly. Validations with comparisons to other drug interaction programs show good results.Finally, therapeutic drug monitoring, drug interaction programs and pharmacogenetic tests are helpful tools in pharmacovigilance and should, in absence of sufficient routine tests supporting data, be used as proposed in our TDM plus algorithm.RESUMEPour améliorer la sécurité d'emploi des médicaments il est important de mieux comprendre leurs interactions dans le corps des patients. Ensuite le clinicien qui prescrit une pharmacothérapie doit avoir un accès simple à ces informations. Entre autres, cette thèse contribue à mieux connaître les caractéristiques pharmacocinétiques de deux médicaments. Elle examine aussi l'utilisation de trois outils en pharmacovigilance : le monitorage thérapeutique des taux plasmatiques des médicaments (« therapeutic drug monitoring »), un programme informatisé d'estimation du risque de combinaisons médicamenteuses, et enfin des tests pharmacogénétiques.Deux études cliniques pharmacogénétiques ont été conduites dans le cadre habituel de clinique psychiatrique : l'une avec la mirtazapine (antidépresseur), l'autre avec la clozapine (antipsychotique). On a traité 45 patients dépressifs avec de la mirtazapine pendant 8 semaines. L'effet thérapeutique était semblable à celui des études précédentes. Nous avons confirmé l'influence de l'âge et du sexe sur la pharmacocinétique de la mirtazapine et la différence dans les concentrations plasmatiques entre fumeurs et non-fumeurs. Au moyen d'analyses énantiomères sélectives, nous avons pu montrer une influence significative du génotype CYP2D6 sur l'énantiomère S+, principalement responsable de l'effet antidépresseur. Pour la première fois, nous avons trouvé une influence du génotype CYP2B6 sur les taux plasmatiques de la 8-OH-mirtazapine. Par ailleurs, le génotype CYP2B6*6/*6 était associé à une meilleure réponse thérapeutique. Une hypothèse sur les voies métaboliques détaillées de la mirtazapine est proposée. Dans la deuxième étude, 75 patients schizophrènes traités avec de la clozapine ont été examinés pour étudier l'influence des génotypes des iso-enzymes CYP450 et de la protéine de transport ABCB1 sur la pharmacocinétique de cet antipsychotique. Pour la première fois, on a montré in vivo un effet des génotypes CYP2C19 et ABCB1 sur les taux plasmatiques de la clozapine. L'importance du CYP1A2 dans le métabolisme de la clozapine a été confirmée.L'identification de facteurs de risques dans la survenue d'effets secondaire graves permettrait une thérapie plus individualisée et plus sûre. Les effets secondaires graves sont rares. Dans une étude de faisabilité (« nested matched case-control design » = étude avec appariement) nous avons comparé des patients avec effets secondaires graves à des patients-contrôles prenant le même type de médicaments mais sans effets secondaires graves. Des taux plasmatiques supérieurs à 120% de la valeur de référence haute sont associés à un risque avec « odds ratio » significatif de 3.5. Une tendance similaire est apparue pour le génotype du CYP2D6. Le « nested matched case-control design » semble une méthode valide qui présente cependant une difficulté : trouver des patients-contrôles dans le cadre d'une seule clinique psychiatrique. Par contre la conduite d'une « nested case-control study » sans appariement est recommandable.Sur la base de notre expérience de l'étude AMSP+ et le fait que nous disposons que de peux de données justifiant des monitorings de taux plasmatiques et/ou de tests pharmacogénétiques de routine, nous avons développé un test algorithme nommé « TDMplus » (TDM + vérification d'interactions médicamenteuses + tests pharmacogénétique).Des programmes de pharmacovigilances comme celui de l'AMSP (Arzneimittelsicherheit in der Psychiatrie = pharmacovigilance en psychiatrie) collectent les effets secondaires graves chez les patients psychiatriques hospitalisés pour identifier des signaux d'alertes. La publication de certains de ces cas même anecdotiques est précieuse. Elle décrit des événements rares et quelques fois une hypothèse sur le potentiel d'une interaction médicamenteuse peut ainsi être confirmée. Sept publications de cas sont résumées ici.Dans le cadre de cette thèse, on a développé un programme informatisé sur internet (en allemand) - mediQ.ch - pour estimer le potentiel de risques d'une interaction médicamenteuse afin d'offrir en ligne ces informations utiles aux cliniciens. Les estimations de risques sont fondées sur des informations cliniques (y compris les profils d'effets secondaires) et pharmacologiques pour chaque médicament ou substance combinés. Le programme donne aussi des informations sur les facteurs de risques comme l'insuffisance rénale et hépatique et certains génotypes. Actuellement il décrit en détail les interactions potentielles de plus de 20'000 paires de médicaments, et celles de 2000 substances actives avec leurs voies de métabolisation et de transport. Chaque information mentionne sa source d'origine; un lien hypertexte permet d'y accéder. Le programme mediQ.ch est régulièrement consulté par les cliniciens de 100 hôpitaux et par 300 praticiens indépendants. Les premières validations et comparaisons avec d'autres programmes sur les interactions médicamenteuses montrent de bons résultats.En conclusion : le monitorage thérapeutique des médicaments, les programmes informatisés contenant l'information sur le potentiel d'interaction médicamenteuse et les tests pharmacogénétiques sont de précieux outils en pharmacovigilance. Nous proposons de les utiliser en respectant l'algorithme « TDM plus » que nous avons développé.

Expanding molecular modeling and design tools to non-natural sidechains.

Protein-protein interactions encode the wiring diagram of cellular signaling pathways and their deregulations underlie a variety of diseases, such as cancer. Inhibiting protein-protein interactions with peptide derivatives is a promising way to develop new biological and therapeutic tools. Here, we develop a general framework to computationally handle hundreds of non-natural amino acid sidechains and predict the effect of inserting them into peptides or proteins. We first generate all structural files (pdb and mol2), as well as parameters and topologies for standard molecular mechanics software (CHARMM and Gromacs). Accurate predictions of rotamer probabilities are provided using a novel combined knowledge and physics based strategy. Non-natural sidechains are useful to increase peptide ligand binding affinity. Our results obtained on non-natural mutants of a BCL9 peptide targeting beta-catenin show very good correlation between predicted and experimental binding free-energies, indicating that such predictions can be used to design new inhibitors. Data generated in this work, as well as PyMOL and UCSF Chimera plug-ins for user-friendly visualization of non-natural sidechains, are all available at http://www.swisssidechain.ch. Our results enable researchers to rapidly and efficiently work with hundreds of non-natural sidechains.

Practical considerations for improving the productivity of mass spectrometry-based proteomics.

Mass spectrometry (MS) is currently the most sensitive and selective analytical technique for routine peptide and protein structure analysis. Top-down proteomics is based on tandem mass spectrometry (MS/ MS) of intact proteins, where multiply charged precursor ions are fragmented in the gas phase, typically by electron transfer or electron capture dissociation, to yield sequence-specific fragment ions. This approach is primarily used for the study of protein isoforms, including localization of post-translational modifications and identification of splice variants. Bottom-up proteomics is utilized for routine high-throughput protein identification and quantitation from complex biological samples. The proteins are first enzymatically digested into small (usually less than ca. 3 kDa) peptides, these are identified by MS or MS/MS, usually employing collisional activation techniques. To overcome the limitations of these approaches while combining their benefits, middle-down proteomics has recently emerged. Here, the proteins are digested into long (3-15 kDa) peptides via restricted proteolysis followed by the MS/MS analysis of the obtained digest. With advancements of high-resolution MS and allied techniques, routine implementation of the middle-down approach has been made possible. Herein, we present the liquid chromatography (LC)-MS/MS-based experimental design of our middle-down proteomic workflow coupled with post-LC supercharging.