Jonas Boström

Assessing the performance of OMEGA with respect to retrieving bioactive conformations

OMEGA is a rule-based program which rapidly generates conformational ensembles of small molecules. We have varied the parameters which control the nature of the ensembles generated by OMEGA in a statistical fashion (D-optimal) with the aim of increasing the probability of generating bioactive conformations. Thirty-six drug-like ligands from different ligand-protein complexes determined by high-resolution (< or =2.0A) X-ray crystallography have been analyzed. Statistically significant models (Q(2)> or =0.75) confirm that one can increase the performance of OMEGA by modifying the parameters. Twenty-eight of the bioactive conformations were retrieved when using a low-energy cut-off (5 kcal/mol), a low RMSD value (0.6A) for duplicate removal, and a maximum of 1000 output conformations. All of those that were not retrieved had eight or more rotatable bonds. The duplicate removal parameter was found to have the largest impact on retrieval of bioactive conformations, and the maximum number of conformations also affected the results considerably. The input conformation was found to influence the results largely because certain bond angles can prevent the bioactive conformation from being generated as a low-energy conformation. Pre-optimizing the input structures with MMFF94s improved the results significantly. We also investigated the performance of OMEGA in connection with database searching. The shape-matching program Rapid Overlay of Chemical Structures (ROCS) was used as search tool. Two multi-conformational databases were built from the MDDR database plus the 36 compounds; one large (maximum 1000 conformations/mol) and one small (maximum 100 conformations/mol). Both databases provided satisfactory results in terms of retrieval. ROCS was able to rank 35 out of 36 X-ray structures among the top 500 hits from the large database.

Oxadiazoles in medicinal chemistry.

Oxadiazoles are five-membered heteroaromatic rings containing two carbons, two nitrogens, and one oxygen atom, and they exist in different regioisomeric forms. Oxadiazoles are frequently occurring motifs in druglike molecules, and they are often used with the intention of being bioisosteric replacements for ester and amide functionalities. The current study presents a systematic comparison of 1,2,4- and 1,3,4-oxadiazole matched pairs in the AstraZeneca compound collection. In virtually all cases, the 1,3,4-oxadiazole isomer shows an order of magnitude lower lipophilicity (log D), as compared to its isomeric partner. Significant differences are also observed with respect to metabolic stability, hERG inhibition, and aqueous solubility, favoring the 1,3,4-oxadiazole isomers. The difference in profile between the 1,2,4 and 1,3,4 regioisomers can be rationalized by their intrinsically different charge distributions (e.g., dipole moments). To facilitate the use of these heteroaromatic rings, novel synthetic routes for ready access of a broad spectrum of 1,3,4-oxadiazoles, under mild conditions, are described.

Analysis of Past and Present Synthetic Methodologies on Medicinal Chemistry: Where Have All the New Reactions Gone?

An analysis of chemical reactions used in current medicinal chemistry (2014), three decades ago (1984), and in natural product total synthesis has been conducted. The analysis revealed that of the current most frequently used synthetic reactions, none were discovered within the past 20 years and only two in the 1980s and 1990s (Suzuki-Miyaura and Buchwald-Hartwig). This suggests an inherent high bar of impact for new synthetic reactions in drug discovery. The most frequently used reactions were amide bond formation, Suzuki-Miyaura coupling, and SNAr reactions, most likely due to commercial availability of reagents, high chemoselectivity, and a pressure on delivery. We show that these practices result in overpopulation of certain types of molecular shapes to the exclusion of others using simple PMI plots. We hope that these results will help catalyze improvements in integration of new synthetic methodologies as well as new library design.

Computational chemistry-driven decision making in lead generation

Novel starting points for drug discovery projects are generally found either by screening large collections of compounds or smaller more-focused libraries. Ideally, hundreds or even thousands of actives are initially found, and these need to be reduced to a handful of promising lead series. In several sequential steps, many actives are dropped and only some are followed up. Computational chemistry tools are used in this context to predict properties, cluster hits, design focused libraries and search for close analogues to explore the potential of hit series. At the end of hit-to-lead, the project must commit to one, or preferably a few, lead series that will be refined during lead optimization and hopefully produce a drug candidate. Striving for the best possible decision is crucial because choosing the wrong series is a costly one-way street.

Using matched molecular series as a predictive tool to optimize biological activity.

A matched molecular series is the general form of a matched molecular pair and refers to a set of two or more molecules with the same scaffold but different R groups at the same position. We describe Matsy, a knowledge-based method that uses matched series to predict R groups likely to improve activity given an observed activity order for some R groups. We compare the Matsy predictions based on activity data from ChEMBLdb to the recommendations of the Topliss tree and carry out a large scale retrospective test to measure performance. We show that the basis for predictive success is preferred orders in matched series and that this preference is stronger for longer series. The Matsy algorithm allows medicinal chemists to integrate activity trends from diverse medicinal chemistry programs and apply them to problems of interest as a Topliss-like recommendation or as a hypothesis generator to aid compound design.

A novel series of piperazinyl-pyridine ureas as antagonists of the purinergic P2Y12 receptor

A novel series of P2Y(12) antagonists for development of drugs within the antiplatelet area is presented. The synthesis of the piperazinyl-pyridine urea derivatives and their structure-activity relationships (SAR) are described. Several compounds showed P2Y(12) antagonistic activities in the sub-micromolar range.

Synthesis, structure–property relationships and pharmacokinetic evaluation of ethyl 6-aminonicotinate sulfonylureas as antagonists of the P2Y12 receptor

The present paper describes the development of a new series of P2Y12 receptor antagonists based on our previously reported piperazinyl urea series 1 (IC50 binding affinity = 0.33 μM, aq solubility <0.1 μM, microsomal CLint (HLM) ≥300 μM/min/mg). By replacement of the urea functionality with a sulfonylurea group we observed increased affinity along with improved stability and solubility as exemplified by 47 (IC50 binding affinity = 0.042 μM, aq solubility = 90 μM, microsomal CLint (HLM) = 70 μM/min/mg). Further improvements in affinity and metabolic stability were achieved by replacing the central piperazine ring with a 3-aminoazetidine as exemplified by 3 (IC50 binding affinity = 0.0062 μM, aq solubility = 83 μM, microsomal CLint (HLM) = 28 μM/min/mg). The improved affinity observed in the in vitro binding assay also translated to the potency observed in the WPA aggregation assay (47: 19 nM and 3: 9.5 nM) and the observed in vitro ADME properties translates to the in vivo PK properties observed in rat. In addition, we found that the chemical stability of the sulfonylureas during prolonged storage in solution was related to the sulfonyl urea linker and depended on the type of solvent and the substitution pattern of the sulfonyl urea functionality.

Molecular Rift: Virtual Reality for Drug Designers

Recent advances in interaction design have created new ways to use computers. One example is the ability to create enhanced 3D environments that simulate physical presence in the real world--a virtual reality. This is relevant to drug discovery since molecular models are frequently used to obtain deeper understandings of, say, ligand-protein complexes. We have developed a tool (Molecular Rift), which creates a virtual reality environment steered with hand movements. Oculus Rift, a head-mounted display, is used to create the virtual settings. The program is controlled by gesture-recognition, using the gaming sensor MS Kinect v2, eliminating the need for standard input devices. The Open Babel toolkit was integrated to provide access to powerful cheminformatics functions. Molecular Rift was developed with a focus on usability, including iterative test-group evaluations. We conclude with reflections on virtual realitys future capabilities in chemistry and education. Molecular Rift is open source and can be downloaded from GitHub.

Potent Fibrinolysis Inhibitor Discovered by Shape and Electrostatic Complementarity to the Drug Tranexamic Acid

Protein-protein interfaces provide an important class of drug targets currently receiving increased attention. The typical design strategy to inhibit protein-protein interactions usually involves large molecules such as peptides and macrocycles. One exception is tranexamic acid (TXA), which, as a lysine mimetic, inhibits binding of plasminogen to fibrin. However, the daily dose of TXA is high due to its modest potency and pharmacokinetic properties. In this study, we report a computational approach, where the focus was on finding electrostatic potential similarities to TXA. Coupling this computational technique with a high-quality low-throughput screen identified 5-(4-piperidyl)-3-isoxazolol (4-PIOL) as a potent plasminogen binding inhibitor with the potential for the treatment of various bleeding disorders. Remarkably, 4-PIOL was found to be more than four times as potent as the drug TXA.

Novel thioamide derivatives as neutral CB1 receptor antagonists.

A novel class of cannabinoid-1 (CB1) receptor antagonists for the treatment of obesity is presented. The carboxamide linker in a set of 5,6-diaryl-pyrazine-2-amide derivatives was transformed into the corresponding thioamide, by using a one-pot synthesis. The structural series of thioamides not only showed retained CB1 potency (below 10nM), but also showed improved solubility. In addition, the neutral antagonist 2c significantly reduced body weight in cafeteria diet obese mice.