3D-Lab: a collaborative web-based platform for molecular modeling.

AIM: The use of 3D information has shown impact in numerous applications in drug design. However, it is often under-utilized and traditionally limited to specialists. We want to change that, and present an approach making 3D information and molecular modeling accessible and easy-to-use 'for the people'. METHODOLOGY/RESULTS: A user-friendly and collaborative web-based platform (3D-Lab) for 3D modeling, including a blazingly fast virtual screening capability, was developed. 3D-Lab provides an interface to automatic molecular modeling, like conformer generation, ligand alignments, molecular dockings and simple quantum chemistry protocols. 3D-Lab is designed to be modular, and to facilitate sharing of 3D-information to promote interactions between drug designers. Recent enhancements to our open-source virtual reality tool Molecular Rift are described. CONCLUSION: The integrated drug-design platform allows drug designers to instantaneously access 3D information and readily apply advanced and automated 3D molecular modeling tasks, with the aim to improve decision-making in drug design projects.

Creating novel activated factor XI inhibitors through fragment based lead generation and structure aided drug design.

Activated factor XI (FXIa) inhibitors are anticipated to combine anticoagulant and profibrinolytic effects with a low bleeding risk. This motivated a structure aided fragment based lead generation campaign to create novel FXIa inhibitor leads. A virtual screen, based on docking experiments, was performed to generate a FXIa targeted fragment library for an NMR screen that resulted in the identification of fragments binding in the FXIa S1 binding pocket. The neutral 6-chloro-3,4-dihydro-1H-quinolin-2-one and the weakly basic quinolin-2-amine structures are novel FXIa P1 fragments. The expansion of these fragments towards the FXIa prime side binding sites was aided by solving the X-ray structures of reported FXIa inhibitors that we found to bind in the S1-S1'-S2' FXIa binding pockets. Combining the X-ray structure information from the identified S1 binding 6-chloro-3,4-dihydro-1H-quinolin-2-one fragment and the S1-S1'-S2' binding reference compounds enabled structure guided linking and expansion work to achieve one of the most potent and selective FXIa inhibitors reported to date, compound 13, with a FXIa IC50 of 1.0 nM. The hydrophilicity and large polar surface area of the potent S1-S1'-S2' binding FXIa inhibitors compromised permeability. Initial work to expand the 6-chloro-3,4-dihydro-1H-quinolin-2-one fragment towards the prime side to yield molecules with less hydrophilicity shows promise to afford potent, selective and orally bioavailable compounds.

Beyond the scope of free-Wilson analysis. 2: Can distance encoded R-group fingerprints provide interpretable nonlinear models?

In a recent study, we presented a novel quantitative-structure-activity-relationship (QSAR) approach, combining R-group signatures and nonlinear support-vector-machines (SVM), to build interpretable local models for congeneric compound sets. Here, we outline further refinements in the fingerprint scheme for the purpose of analyzing and visualizing structure-activity relationships (SAR). The concept of distance encoded R-group signature descriptors is introduced, and we explore the influence of different signature encoding schemes on both interpretability and predictive power of the SVM models using ten public data sets. The R-group and atomic gradients provide a way to interpret SVM models and enable detailed analysis of structure-activity relationships within substituent groups. We discuss applications of the method and show how it can be used to analyze nonadditive SAR and provide intuitive and powerful SAR visualizations.

Beyond the scope of Free-Wilson analysis: building interpretable QSAR models with machine learning algorithms.

A novel methodology was developed to build Free-Wilson like local QSAR models by combining R-group signatures and the SVM algorithm. Unlike Free-Wilson analysis this method is able to make predictions for compounds with R-groups not present in a training set. Eleven public data sets were chosen as test cases for comparing the performance of our new method with several other traditional modeling strategies, including Free-Wilson analysis. Our results show that the R-group signature SVM models achieve better prediction accuracy compared with Free-Wilson analysis in general. Moreover, the predictions of R-group signature models are also comparable to the models using ECFP6 fingerprints and signatures for the whole compound. Most importantly, R-group contributions to the SVM model can be obtained by calculating the gradient for R-group signatures. For most of the studied data sets, a significant correlation with that of a corresponding Free-Wilson analysis is shown. These results suggest that the R-group contribution can be used to interpret bioactivity data and highlight that the R-group signature based SVM modeling method is as interpretable as Free-Wilson analysis. Hence the signature SVM model can be a useful modeling tool for any drug discovery project.

Composite multi-parameter ranking of real and virtual compounds for design of MC4R agonists: renaissance of the Free-Wilson methodology.

Drug design is a multi-parameter task present in the analysis of experimental data for synthesized compounds and in the prediction of new compounds with desired properties. This article describes the implementation of a binned scoring and composite ranking scheme for 11 experimental parameters that were identified as key drivers in the MC4R project. The composite ranking scheme was implemented in an AstraZeneca tool for analysis of project data, thereby providing an immediate re-ranking as new experimental data was added. The automated ranking also highlighted compounds overlooked by the project team. The successful implementation of a composite ranking on experimental data led to the development of an equivalent virtual score, which was based on Free-Wilson models of the parameters from the experimental ranking. The individual Free-Wilson models showed good to high predictive power with a correlation coefficient between 0.45 and 0.97 based on the external test set. The virtual ranking adds value to the selection of compounds for synthesis but error propagation must be controlled. The experimental ranking approach adds significant value, is parameter independent and can be tuned and applied to any drug discovery project.

SARConnect: A Tool to Interrogate the Connectivity Between Proteins, Chemical Structures and Activity Data.

The access and use of large-scale structure-activity relationships (SAR) is increasing as the range of targets and availability of bioactive compound-to-protein mappings expands. However, effective exploitation requires merging and normalisation of activity data, mappings to target classifications as well as visual display of chemical structure relationships. This work describes the development of the application "SARConnect" to address these issues. We discuss options for delivery and analysis of large-scale SAR data together with a set of use-cases to illustrate the design choices and utility. The main activity sources of ChEMBL,1 GOSTAR2 and AstraZeneca's internal system IBIS, had already been integrated in Chemistry Connect.3 For target relationships we selected human UniProtKB/Swiss-Prot4 as our primary source of a heuristic target classification. Similarly, to explore chemical relationships we combined several methods for framework and scaffold analysis into a unified, hierarchical classification where ease of navigation was the primary goal. An application was built on TIBCO Spotfire to retrieve data for visual display. Consequently, users can explore relationships between target, activity and structure across internal, external and commercial sources that encompass approximately 3 million compounds, 2000 human proteins and 10 million activity values. Examples showing the utility of the application are given.

Binding affinities of factor Xa inhibitors estimated by thermodynamic integration and MM/GBSA.

We present free energy estimates of nine 3-amidinobenzyl-1H-indole-2-carboxamide inhibitors of factor Xa. Using alchemical thermodynamic integration (TI) calculations, we estimate the difference in binding free energies with high accuracy and precision, except for mutations involving one of the amidinobenzyl rings. Crystal studies show that the inhibitors may bind in two distinct conformations, and using TI, we show that the two conformations give a similar binding affinity. Furthermore, we show that we can reduce the computational demand, while still retaining a high accuracy and precision, by using fewer integration points and shorter protein-ligand simulations. Finally, we have compared the TI results to those obtained with the simpler MM/GBSA method (molecular-mechanics with generalized Born surface-area solvation). MM/GBSA gives better results for the mutations that involve a change of net charge, but if a precision similar to that of the TI method is required, the MM/GBSA method is actually slightly more expensive. Thus, we have shown that TI could be a valuable tool in drug design.

Investigation of the relationship between topology and selectivity for druglike molecules.

There is a strong interest in drug discovery and development to advance the understanding of pharmacological promiscuity. Improved understanding of how a molecular structure is related to promiscuity could help to reduce the attrition of compounds in the drug discovery process. For this purpose, a descriptor is introduced that describes the structural complexity of a compound based on the size of its molecular framework (MF) in relation to its overall size. It is defined as the fraction of the size of the molecular framework versus the size of the whole molecule (f(MF)). It is demonstrated that promiscuity correlates with f(MF) for large f(MF) values. The observed correlation is not due to lipophilicity. To provide further explanation of this observation, it was found that the number of terminal ring systems in a compound is correlated with promiscuity. The analysis presented here might help medicinal chemists to improve the selectivity for compounds in drug discovery projects.

From natural products to achiral drug prototypes: potent thrombin inhibitors based on P2/P3 dihydropyrid-2-one core motifs.

A series of dihydropyrid-2-ones was synthesized and tested for inhibitory activity against serine protease enzymes. Moderate to low nanomolar inhibitory activities were obtained against thrombin and excellent selectivity against trypsin was observed.

Design, synthesis, and thrombin-inhibitory activity of pyridin-2-ones as P2/P3 core motifs.

Guided by available X-ray crystal structure data on the serine protease thrombin, a series of pyridin-2-one derivatives were designed and synthesized having diverse functionality at the P(1) and P(3) sites. Potent in vitro activity against thrombin, with excellent selectivity over trypsin was found for selected analogues.

Ligand affinities predicted with the MM/PBSA method: dependence on the simulation method and the force field.

The free energy of binding between avidin and seven biotin analogues has been calculated with the molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) method. We have studied how the force field and the method to generate geometries affect the calculated binding free energies. Four different force fields were compared, but we saw no significant difference in the results. However, mixing the force fields used for the geometry generation and energy calculations is not recommended. In the molecular dynamics simulations, explicit water molecules must be used, but the size of the simulated system and the boundary conditions are less important. In fact, nonperiodic simulations with a fixed protein outside a relatively small simulated system (18 A) seem to be a proper approach. The mean absolute error was 9-19 kJ/mol, with a standard error of 5-15 kJ/mol, which arises mainly from the entropy term.

Appendectomy versus antibiotic treatment in acute appendicitis. a prospective multicenter randomized controlled trial.

BACKGROUND: Appendectomy has been the treatment for acute appendicitis for over 120 years. Antibiotic treatment has occasionally been used in small uncontrolled studies, instead of operation, but this alternative has never before been tried in a multicenter randomized trial. PATIENTS AND METHODS: Male patients, 18-50 years of age, admitted to six different hospitals in Sweden between 1996 and 1999 were enrolled in the study. No women were enrolled by decision of the local ethics committee. If appendectomy was planned, patients were asked to participate, and those who agreed were randomized either to surgery or to antibiotic therapy. Patients randomized to surgery were operated on with open surgery or laparoscopically. Those randomized to antibiotic therapy were treated intravenously for 2 days, followed by oral treatment for 10 days. If symptoms did not resolve within 24 hours, an appendectomy was performed. Participants were monitored at the end of 1 week, 6 weeks, and 1 year. RESULTS: During the study period 252 men participated, 124 in the surgery group and 128 in the antibiotic group. The frequency of appendicitis was 97% in the surgery group and 5% had a perforated appendix. The complication rate was 14% in the surgery group. In the antibiotic group 86% improved without surgery; 18 patients were operated on within 24 hours, and the diagnosis of acute appendicitis was confirmed in all but one patient, and he was suffering from terminal ileitis. There were seven patients (5%) with a perforated appendix in this group. The rate of recurrence of symptoms of appendicitis among the 111 patients treated with antibiotics was 14% during the 1-year follow-up. CONCLUSIONS: Acute non-perforated appendicitis can be treated successfully with antibiotics. However, there is a risk of recurrence in cases of acute appendicitis, and this risk should be compared with the risk of complications after appendectomy.

Phenolic P2/P3 core motif as thrombin inhibitors--design, synthesis, and X-ray co-crystal structure.

Prototypical thrombin inhibitors were synthesized based on a trisubstituted phenol as a core motif. A naphthylsulfonamide analogue showed excellent antithrombin activity. An X-ray co-crystal structure showed the expected interactions.

Synthesis and SAR of thrombin inhibitors incorporating a novel 4-amino-morpholinone sscaffold: analysis of X-ray crystal structure of enzyme inhibitor complex.

A 4-amino-2-carboxymethyl-3-morpholinone structural motif derived from malic acid has been used to mimic d-Phe-Pro in the thrombin inhibiting tripeptide d-Phe-Pro-Arg. The arginine in D-Phe-Pro-Arg was replaced by the more rigid P1 truncated p-amidinobenzylamine (Pab). These new thrombin inhibitors were used to probe the inhibitor binding site of alpha-thrombin. The best candidate in this series of thrombin inhibitors exhibits an in vitro IC50 of 0.130 microM. Interestingly, the stereochemistry of the 4-amino-2-carboxymethyl-3-morpholinone motif is reversed for the most active compounds compared to that of a previously reported 2-carboxymethyl-3-morpholinone series. The X-ray crystal structure of the lead inhibitor cocrystallized with alpha-thrombin is discussed.

Synthesis of novel thrombin inhibitors. Use of ring-closing metathesis reactions for synthesis of P2 cyclopentene- and cyclohexenedicarboxylic acid derivatives.

The thrombin inhibitory tripeptide d-Phe-Pro-Arg has been mimicked using either cyclopentenedicarboxylic derivatives or a cyclohexenedicarboxylic derivative as surrogate for the P2 proline. In the P3 position, tertiary amides were optimized as d-Phe P3 replacements. The P1 arginine was, in all compounds, substituted with the more rigid and biocompatible 4-aminomethylbenzamidine. One of the novel inhibitors was cocrystallized with alpha-thrombin and subjected to X-ray analysis. From analysis of the X-ray crystal structure, new ligands were designed leading to significantly improved binding affinity, the lead candidate exhibiting an in vitro IC(50) of 49 nM.

Targeting thrombin and factor VIIa: design, synthesis, and inhibitory activity of functionally relevant indolizidinones.

Guided by molecular modeling, docking experiments, and available X-ray crystal structure data on the serine protease Factor VIIa and thrombin, a series of indolizidinone derivatives was designed and synthesized having diverse functionality at the P1, P2, and P3 sites.

Novel morpholinone-based D-Phe-Pro-Arg mimics as potential thrombin inhibitors: design, synthesis, and X-ray crystal structure of an enzyme inhibitor complex.

A morpholinone structural motif derived from D(+)- and L(-)-malic acid has been used as a mimic of D-Phe-Pro in the thrombin inhibiting tripeptide D-Phe-Pro-Arg. In place of Arg the more rigid P1 truncated p-amidinobenzylamine (Pab) or 2-amino-5-aminomethyl-3-methyl-pyridine have been utilized. The synthetic strategy developed readily delivers these novel thrombin inhibitors used to probe the alpha-thrombin inhibitor binding site. The best candidate in this series of thrombin inhibitors exhibits an in vitro IC(50) of 720 nM. The X-ray crystal structure of this candidate co-crystallized with alpha-thrombin is discussed.

Synthesis of potential thrombin inhibitors. Incorporation of tartaric acid templates as P2 proline mimetics.

With the objective to prepare novel non-peptidic thrombin inhibitors, bioisosteres of the inhibitory tripeptide D-Phe-Pro-Arg chain have been examined. Thus, the P1 Arg was replaced with p-amidinobenzylamine, an elongated homologue of the same and with 2,5-dichloro benzylamine. The P2-P3, D-Phe-Pro, was replaced with a novel tartaric acid template coupled to a series of readily available, mainly lipophilic, amines. Some of these compounds exhibit promising thrombin inhibition activity in vitro, IC(50 ) approximately 5.9 microM.