Computer-assisted design of organic synthesis

The computer programs to design synthetic pathways of organic compounds have been utilized throughout the world since the first system was reported by Corey in 1969, and the LHASA was reported in1972 to become the predominant system. Many programs have been reported mainly in the United States and Europe, and groups of corporations, especially chemical companies, have been trying to improve programs and increase the efficiency of research. In Japan, unfortunately, no concrete movement in this area has been seen. Of course, it goes without saying that these kinds of programs are effective for efficient research, but the remarkable aspect is that these can present unexpected data to the researchers to stimulate them to develop new ideas

Characterization of the Hemagglutinin Cleaving Transmembrane Serine Proteases Matriptase and TMPRSS2

Influenza is one of the commonest infectious diseases affecting millions of people every year including 290,000 – 650,000 heavy casualties. Influenza viruses undergo constant genetic changes and every 10 – 50 years new influenza virus strains emerge that potentially cause a severe pandemic. In this modern interconnected world, experts believe the next influenza pandemic will be a “devastating global health event with far-reaching consequences” [1]. Novel effective anti-influenza drugs are in need. One strategy of influenza research is to focus on host-specific proteases that are essential for virus activation and spread. Trypsin-like serine proteases are crucial for influenza activation by mediating the cleavage of the viral surface glycoprotein HA and hence promoting the fusion potential of the virus. Therefore, their inhibition provides a promising therapeutic approach. The present work focused on the characterization of two relevant HA cleaving type-II transmembrane serine proteases matriptase and TMPRSS2. Chapter 3 and chapter 4 of this thesis engaged with the recombinant production of matriptase (chapter 3) in order to obtain a pure functional enzyme of high quality for a SAR study with novel monobasic (hence potentially bioavailable) matriptase inhibitors of the 3-amidinophenylalanine type (chapter 4). Adequate amounts of high-quality matriptase enzymes were isolated using a new expression system and in total 5 matriptase crystals were available at the end of this thesis for structural analysis. The matriptase inhibitor design in this thesis focused on matriptase-affine compounds with a fair selectivity profile against the blood coagulation enzymes thrombin and fXa. In total, 18 new monobasic and potentially bioavailable, as well as four new dibasic compounds of the 3-amidinophenylalanine types were tested. Based on the last published crystal structure of this inhibitor type in complex with matriptase from 2006 (PDB code 2GV6) docking was used as a structure-based virtual screening method for lead optimization of the compounds N-terminus. Selected compounds were suggested to interact with the carbonyl side chain of Gln175 of matriptase to achieve a higher affinity of matriptase compared to fXa. The 4-tert-butylureido-piperidine could be identified as suitable C-terminus in combination with 3-fluoro-4-hydroxymethyl biphenylsulphonyl N-terminally in order to obtain excellent selectivity over thrombin. The binding mode of this compound (compound 55) was crystallographically determined in complex with matriptase as well as trypsin. Trypsin proved as a suitable alternative to matriptase for detailed binding mode analysis of the compounds N-terminus. However, different preferences were detected for the C-terminus. Dibasic compounds showed higher matriptase affinity and selectivity in comparison with the monobasic analogues. However, the tested monobasic compounds were still decent matriptase inhibitors that are additionally suitable for cell culture and animal studies in their benzamidine prodrug forms, which are well established from related inhibitors of thrombin. In addition, selected monobasic as well as dibasic compounds demonstrated strong suppression of the replication of certain H9N2 influenza viruses in a matriptase-expressing MDCK II cell model. These matriptase inhibitors could be potential lead structures for the development of new drugs against H9 strains for influenza. TMPRSS2 is widely discussed for its role in influenza activation. With a TMPRSS2 dependancy of HA-activation of certain subtypes, the characterization of this protease is an important prerequisite for being available as a target for influenza drug design. However, only little is known about the physiological function of TMPRSS2 and no experimental structure data are available at the moment to enable a structure-based drug development. Therefore, chapter 5 of this thesis focused on the characterization of TMPRSS2 in order to develop a strategy for the isolation of proteolytically active TMPRSS2 from cell culture. Even though, no functional TMPRSS2 could be recovered at the end of this work some new structural characteristics of TMPRSS2 were identified as crucial for functionality insight the cell. In general, TMPRSS2 without the cytosolic part, the transmembrane domain and the LDLRA domain is able to undergo autocatalytically activation if an artificial signal peptide was added N-terminal to enable entry into the endoplasmic reticulum. The presence of the cysteine-rich SRCR domain and the presence of the disulfide chain that connects the SPD and the stem region after activation cleavage have been identified as crucial for activity. N-terminal truncation of TMPRSS2 did not result in obvious dislocation within the cell: as the full-length positive control truncated TMPRSS2 was exclusively found in cell compartments surrounding the nucleus in immunofluorescence experiments. However, a reduced proteolytic cleavage activity towards H3-HA in co-expression experiments has been observed and might be a result of dislocation, since truncated TMPRSS2 is not bound to the biomembrane anymore. In addition, TMPRSS2 has been identified as a potential substrate of matriptase in vitro, which suggests possible participation in several zymogen cascades

Synthesis of 1,4-Disubstituted Mono and Bis-triazolocarbo-acyclonucleoside Analogues of 9-(4-Hydroxybutyl)guanine by Cu(I)-Catalyzed Click Azide-Alkyne Cycloaddition

A series of novel mono-1,2,3-triazole and bis-1,2,3-triazole acyclonucleoside analogues of 9-(4-hydroxybutyl)guanine was prepared via copper(I)-catalyzed 1,3-dipolar cycloaddition of N-9 propargylpurine, N-1-propargylpyrimidines/as-triazine with the azido-pseudo-sugar 4-azidobutylacetate under solvent-free microwave conditions, followed by treatment with K2CO3/MeOH, or NH3/MeOH. All compounds studied in this work were screened for their antiviral activities [against human rhinovirus (HRV) and hepatitis C virus (HCV)] and antibacterial activities against a series of Gram positive and negative bacteria

A rapid stability-indicating, fused-core HPLC method for simultaneous determination of β-artemether and lumefantrine in anti-malarial fixed dose combination products

Background: Artemisinin-based fixed dose combination (FDC) products are recommended by World Health Organization (WHO) as a first-line treatment. However, the current artemisinin FDC products, such as beta-artemether and lumefantrine, are inherently unstable and require controlled distribution and storage conditions, which are not always available in resource-limited settings. Moreover, quality control is hampered by lack of suitable analytical methods. Thus, there is a need for a rapid and simple, but stability-indicating method for the simultaneous assay of beta-artemether and lumefantrine FDC products. Methods: Three reversed-phase fused-core HPLC columns (Halo RP-Amide, Halo C18 and Halo Phenyl-hexyl), all thermostated at 30 degrees C, were evaluated. beta-artemether and lumefantrine (unstressed and stressed), and reference-related impurities were injected and chromatographic parameters were assessed. Optimal chromatographic parameters were obtained using Halo RP-Amide column and an isocratic mobile phase composed of acetonitrile and 1mM phosphate buffer pH 3.0 (52:48; V/V) at a flow of 1.0 ml/min and 3 mu l injection volume. Quantification was performed at 210 nm and 335 nm for beta-artemether and for lumefantrine, respectively. In-silico toxicological evaluation of the related impurities was made using Derek Nexus v2.0 (R). Results: Both beta-artemether and lumefantrine were separated from each other as well as from the specified and unspecified related impurities including degradants. A complete chromatographic run only took four minutes. Evaluation of the method, including a Plackett-Burman robustness verification within analytical QbD-principles, and real-life samples showed the method is suitable for quantitative assay purposes of both active pharmaceutical ingredients, with a mean recovery relative standard deviation (+/- RSD) of 99.7 % (+/- 0.7%) for beta-artemether and 99.7 % (+/- 0.6%) for lumefantrine. All identified beta-artemether-related impurities were predicted in Derek Nexus v2.0 (R) to have toxicity risks similar to beta-artemether active pharmaceutical ingredient (API) itself. Conclusions: A rapid, robust, precise and accurate stability-indicating, quantitative fused-core isocratic HPLC method was developed for simultaneous assay of beta-artemether and lumefantrine. This method can be applied in the routine regulatory quality control of FDC products. The in-silico toxicological investigation using Derek Nexus (R) indicated that the overall toxicity risk for beta-artemether-related impurities is comparable to that of beta-artemether API

Complex macrocycle exploration: parallel, heuristic, and constraint-based conformer generation using ForceGen.

ForceGen is a template-free, non-stochastic approach for 2D to 3D structure generation and conformational elaboration for small molecules, including both non-macrocycles and macrocycles. For conformational search of non-macrocycles, ForceGen is both faster and more accurate than the best of all tested methods on a very large, independently curated benchmark of 2859 PDB ligands. In this study, the primary results are on macrocycles, including results for 431 unique examples from four separate benchmarks. These include complex peptide and peptide-like cases that can form networks of internal hydrogen bonds. By making use of new physical movements ("flips" of near-linear sub-cycles and explicit formation of hydrogen bonds), ForceGen exhibited statistically significantly better performance for overall RMS deviation from experimental coordinates than all other approaches. The algorithmic approach offers natural parallelization across multiple computing-cores. On a modest multi-core workstation, for all but the most complex macrocycles, median wall-clock times were generally under a minute in fast search mode and under 2 min using thorough search. On the most complex cases (roughly cyclic decapeptides and larger) explicit exploration of likely hydrogen bonding networks yielded marked improvements, but with calculation times increasing to several minutes and in some cases to roughly an hour for fast search. In complex cases, utilization of NMR data to constrain conformational search produces accurate conformational ensembles representative of solution state macrocycle behavior. On macrocycles of typical complexity (up to 21 rotatable macrocyclic and exocyclic bonds), design-focused macrocycle optimization can be practically supported by computational chemistry at interactive time-scales, with conformational ensemble accuracy equaling what is seen with non-macrocyclic ligands. For more complex macrocycles, inclusion of sparse biophysical data is a helpful adjunct to computation

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment