Dávid Bajusz

Bio: Dávid Bajusz is an academic researcher from Hungarian Academy of Sciences. The author has contributed to research in topics: Virtual screening & Medicine. The author has an hindex of 15, co-authored 45 publications receiving 1194 citations. Previous affiliations of Dávid Bajusz include University of Debrecen.

Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations?

Abstract: Cheminformaticians are equipped with a very rich toolbox when carrying out molecular similarity calculations. A large number of molecular representations exist, and there are several methods (similarity and distance metrics) to quantify the similarity of molecular representations. In this work, eight well-known similarity/distance metrics are compared on a large dataset of molecular fingerprints with sum of ranking differences (SRD) and ANOVA analysis. The effects of molecular size, selection methods and data pretreatment methods on the outcome of the comparison are also assessed. A supplier database ( https://mcule.com/ ) was used as the source of compounds for the similarity calculations in this study. A large number of datasets, each consisting of one hundred compounds, were compiled, molecular fingerprints were generated and similarity values between a randomly chosen reference compound and the rest were calculated for each dataset. Similarity metrics were compared based on their ranking of the compounds within one experiment (one dataset) using sum of ranking differences (SRD), while the results of the entire set of experiments were summarized on box and whisker plots. Finally, the effects of various factors (data pretreatment, molecule size, selection method) were evaluated with analysis of variance (ANOVA). This study complements previous efforts to examine and rank various metrics for molecular similarity calculations. Here, however, an entirely general approach was taken to neglect any a priori knowledge on the compounds involved, as well as any bias introduced by examining only one or a few specific scenarios. The Tanimoto index, Dice index, Cosine coefficient and Soergel distance were identified to be the best (and in some sense equivalent) metrics for similarity calculations, i.e. these metrics could produce the rankings closest to the composite (average) ranking of the eight metrics. The similarity metrics derived from Euclidean and Manhattan distances are not recommended on their own, although their variability and diversity from other similarity metrics might be advantageous in certain cases (e.g. for data fusion). Conclusions are also drawn regarding the effects of molecule size, selection method and data pretreatment on the ranking behavior of the studied metrics.

One- versus two-electron oxidation with peroxomonosulfate ion: reactions with iron(II), vanadium(IV), halide ions, and photoreaction with cerium(III).

Abstract: The kinetics of the redox reactions of the peroxomonosulfate ion (HSO(5)(-)) with iron(II), vanadium(IV), cerium(III), chloride, bromide, and iodide ions were studied. Cerium(III) is only oxidized upon illumination by UV light and cerium(IV) is produced in a photoreaction with a quantum yield of 0.33 +/- 0.03. Iron(II) and vanadium(IV) are most probably oxidized through one-electron transfer producing sulfate ion radicals as intermediates. The halide ions are oxidized in a formally two-electron process, which most likely includes oxygen-atom transfer. Comparison with literature data suggests that the activation entropies might be used as indicators distinguishing between heterolytic and homolytic cleavage of the peroxo bond in the redox reactions of HSO(5)(-).

Pharmacologic inhibition of STAT5 in acute myeloid leukemia

Abstract: The transcription factor STAT5 is an essential downstream mediator of many tyrosine kinases (TKs), particularly in hematopoietic cancers. STAT5 is activated by FLT3-ITD, which is a constitutively active TK driving the pathogenesis of acute myeloid leukemia (AML). Since STAT5 is a critical mediator of diverse malignant properties of AML cells, direct targeting of STAT5 is of significant clinical value. Here, we describe the development and preclinical evaluation of a novel, potent STAT5 SH2 domain inhibitor, AC-4-130, which can efficiently block pathological levels of STAT5 activity in AML. AC-4-130 directly binds to STAT5 and disrupts STAT5 activation, dimerization, nuclear translocation, and STAT5-dependent gene transcription. Notably, AC-4-130 substantially impaired the proliferation and clonogenic growth of human AML cell lines and primary FLT3-ITD+ AML patient cells in vitro and in vivo. Furthermore, AC-4-130 synergistically increased the cytotoxicity of the JAK1/2 inhibitor Ruxolitinib and the p300/pCAF inhibitor Garcinol. Overall, the synergistic effects of AC-4-130 with TK inhibitors (TKIs) as well as emerging treatment strategies provide new therapeutic opportunities for leukemia and potentially other cancers.

Consistency of QSAR models: Correct split of training and test sets, ranking of models and performance parameters

Abstract: Recent implementations of QSAR modelling software provide the user with numerous models and a wealth of information. In this work, we provide some guidance on how one should interpret the results of QSAR modelling, compare and assess the resulting models, and select the best and most consistent ones. Two QSAR datasets are applied as case studies for the comparison of model performance parameters and model selection methods. We demonstrate the capabilities of sum of ranking differences (SRD) in model selection and ranking, and identify the best performance indicators and models. While the exchange of the original training and (external) test sets does not affect the ranking of performance parameters, it provides improved models in certain cases (despite the lower number of molecules in the training set). Performance parameters for external validation are substantially separated from the other merits in SRD analyses, highlighting their value in data fusion.

Effect of Dataset Size and Train/Test Split Ratios in QSAR/QSPR Multiclass Classification.

Abstract: Applied datasets can vary from a few hundred to thousands of samples in typical quantitative structure-activity/property (QSAR/QSPR) relationships and classification. However, the size of the datasets and the train/test split ratios can greatly affect the outcome of the models, and thus the classification performance itself. We compared several combinations of dataset sizes and split ratios with five different machine learning algorithms to find the differences or similarities and to select the best parameter settings in nonbinary (multiclass) classification. It is also known that the models are ranked differently according to the performance merit(s) used. Here, 25 performance parameters were calculated for each model, then factorial ANOVA was applied to compare the results. The results clearly show the differences not just between the applied machine learning algorithms but also between the dataset sizes and to a lesser extent the train/test split ratios. The XGBoost algorithm could outperform the others, even in multiclass modeling. The performance parameters reacted differently to the change of the sample set size; some of them were much more sensitive to this factor than the others. Moreover, significant differences could be detected between train/test split ratios as well, exerting a great effect on the test validation of our models.

The Pharmacological Basis of Therapeutics

Abstract: The Pharmacological Basis of Therapeutics A Textbook of Pharmacology, Toxicology and Therapeutics for Physicians and Medical Students. By Prof. Louis Goodman and Prof. Alfred Gilman. Pp. xiii + 1383. (New York: The Macmillan Company, 1941.) 50s. net.

Persulfate-Based Advanced Oxidation: Critical Assessment of Opportunities and Roadblocks.

Abstract: Reports that promote persulfate-based advanced oxidation process (AOP) as a viable alternative to hydrogen peroxide-based processes have been rapidly accumulating in recent water treatment literature. Various strategies to activate peroxide bonds in persulfate precursors have been proposed and the capacity to degrade a wide range of organic pollutants has been demonstrated. Compared to traditional AOPs in which hydroxyl radical serves as the main oxidant, persulfate-based AOPs have been claimed to involve different in situ generated oxidants such as sulfate radical and singlet oxygen as well as nonradical oxidation pathways. However, there exist controversial observations and interpretations around some of these claims, challenging robust scientific progress of this technology toward practical use. This Critical Review comparatively examines the activation mechanisms of peroxymonosulfate and peroxydisulfate and the formation pathways of oxidizing species. Properties of the main oxidizing species are scrutinized and the role of singlet oxygen is debated. In addition, the impacts of water parameters and constituents such as pH, background organic matter, halide, phosphate, and carbonate on persulfate-driven chemistry are discussed. The opportunity for niche applications is also presented, emphasizing the need for parallel efforts to remove currently prevalent knowledge roadblocks.

Sulfate radicals induced from peroxymonosulfate by magnetic ferrospinel MFe2O4 (M = Co, Cu, Mn, and Zn) as heterogeneous catalysts in the water

Abstract: Magnetic ferrospinel MFe 2 O 4 (M = Co, Cu, Mn, and Zn) prepared in a sol–gel process was introduced as catalyst to generate powerful radicals from peroxymonosulfate (PMS) for refractory di-n-butyl phthalate (DBP) degradation in the water. Various catalysts were described and characterized, and the catalytic activities in PMS oxidation system were investigated. Most important of all, the mechanism of different catalysts in the catalytic PMS solution was illustrated. The results showed that the incorporation of CoFe 2 O 4 had the highest catalytic performance in PMS oxidation for DBP degradation. All catalysts presented favorable recycling and stability in the repeated batch experiment. The catalytic process showed a dependence on initial pH, and an uncharged surface of the catalyst was more profitable for sulfate radical generation. H 2 -TPR and CVs analysis indicated that the sequence of the catalyst's reducibility in PMS solution was CoFe 2 O 4 > CuFe 2 O 4 > MnFe 2 O 4 > ZnFe 2 O 4 , which had a close connection with the activity of metal ion in A site of the catalysts. The surface hydroxyl sites played an important role in the catalytic process, and its quantity determined the degradation of DBP. Moreover, the reactive species in PMS/MFe 2 O 4 system were identified as sulfate radical and hydroxyl radical. The promotion of these radical's reaction was due to the fact that a balance action in the process of M 2+ /M 3+ , O 2− /O 2 , occurred, and at the same time, PMS was catalyzed.