Treatment Of Multifactorial Diseases Research Articles

A Computational Approach for the Discovery of Novel DNA Methyltransferase Inhibitors.

Nowadays, the explosion of knowledge in the field of epigenetics has revealed new pathways toward the treatment of multifactorial diseases, rendering the key players of the epigenetic machinery the focus of today's pharmaceutical landscape. Among epigenetic enzymes, DNA methyltransferases (DNMTs) are first studied as inhibition targets for cancer treatment. The increasing clinical interest in DNMTs has led to advanced experimental and computational strategies in the search for novel DNMT inhibitors. Considering the importance of epigenetic targets as a novel and promising pharmaceutical trend, the present study attempted to discover novel inhibitors of natural origin against DNMTs using a combination of structure and ligand-based computational approaches. Particularly, a pharmacophore-based virtual screening was performed, followed by molecular docking and molecular dynamics simulations in order to establish an accurate and robust selection methodology. Our screening protocol prioritized five natural-derived compounds, derivatives of coumarins, flavones, chalcones, benzoic acids, and phenazine, bearing completely diverse chemical scaffolds from FDA-approved "Epi-drugs". Their total DNMT inhibitory activity was evaluated, revealing promising results for the derived hits with an inhibitory activity ranging within 30-45% at 100 µM of the tested compounds.

Structure and biological property studies of the fluorinated sulfonic esters derived from 2-hydroxy-4-(hydroxy/methoxy)acetophenone as inhibitors of biochemical targets linked to type 2 diabetes mellitus

Small molecule multi-target drugs substituted with fluorine atom/s or fluorine-containing group/s continue to attract considerable interest in medicinal chemistry due to their advantages in the treatment of multifactorial diseases. In this study, fluorine-containing alkyl and benzenesulfonyl chloride building blocks were reacted with 2,4-dihydroxyacetophenone 1a or 2-hydroxy-4-methoxyacetophenone 1b to afford the corresponding sulfonic ester derivatives 2a–f and 2g–j, respectively. Detailed crystallographic characterization was performed on a representative compound from each series. The compounds were evaluated through enzymatic assays in vitro for potential to inhibit biochemical targets linked to type 2 diabetes mellitus. Compound 1a and its 4-(4-fluorophenyl)sulfonyl derivative 2d exhibited strong and significant inhibitory effect in vitro against α-glucosidase (IC50 = 0.97 ± 0.02 μM and 0.81 ± 0.07 μM, respectively) and α-amylase (IC50 = 6.89 ± 0.04 μM and 4.87 ± 0.02 μM, respectively) compared to acarbose (IC50 = 8.60 ± 0.20 μM and 1.96 ± 0.03 μM, respectively). The presence of a 4-fluorophenylsulfonyl moiety resulted in moderate inhibitory activity for 2d (IC50 = 27.05 ± 0.01 μM) against protein tyrosine phosphatase 1 beta (PTP1B) compared to the PTP1B inhibitor, suramin (IC50 = 4.63 ± 0.003 μM). The test compounds exhibited strong to moderate nitric oxide radical scavenging activity in vitro against ascorbic acid (IC50 = 5.53 ± 0.03 μM) with IC50 values in the range 0.05–19.30 μM. Compounds 1a and 2d did not inhibit superoxide dismutase (SOD) activity. Molecular docking revealed the involvement of hydrophobic, hydrophilic and electrostatic interactions with amino acid residues in the active site of the test enzymes.

Non-parametric synergy modeling of chemical compounds with Gaussian processes

BackgroundUnderstanding the synergetic and antagonistic effects of combinations of drugs and toxins is vital for many applications, including treatment of multifactorial diseases and ecotoxicological monitoring. Synergy is usually assessed by comparing the response of drug combinations to a predicted non-interactive response from reference (null) models. Possible choices of null models are Loewe additivity, Bliss independence and the recently rediscovered Hand model. A different approach is taken by the MuSyC model, which directly fits a generalization of the Hill model to the data. All of these models, however, fit the dose–response relationship with a parametric model.ResultsWe propose the Hand-GP model, a non-parametric model based on the combination of the Hand model with Gaussian processes. We introduce a new logarithmic squared exponential kernel for the Gaussian process which captures the logarithmic dependence of response on dose. From the monotherapeutic response and the Hand principle, we construct a null reference response and synergy is assessed from the difference between this null reference and the Gaussian process fitted response. Statistical significance of the difference is assessed from the confidence intervals of the Gaussian process fits. We evaluate performance of our model on a simulated data set from Greco, two simulated data sets of our own design and two benchmark data sets from Chou and Talalay. We compare the Hand-GP model to standard synergy models and show that our model performs better on these data sets. We also compare our model to the MuSyC model as an example of a recent method on these five data sets and on two-drug combination screens: Mott et al. anti-malarial screen and O’Neil et al. anti-cancer screen. We identify cases in which the HandGP model is preferred and cases in which the MuSyC model is preferred.ConclusionThe Hand-GP model is a flexible model to capture synergy. Its non-parametric and probabilistic nature allows it to model a wide variety of response patterns.

Interactomics and personalized pharmacotherapy – present and looking to the future

The review highlights the advances in natural science that form the basis of the concept of personalized and precision medicine (PPM). The provisions of PPM (prediction, prevention, personalization) have been disclosed and modern molecular genetic tools have been shown, which are used in leading scientific and practical biomedical centers to improve the quality of treatment of patients with multifactorial diseases (MFD). The main principles of molecular genetic biomarking of MFDs, as well as gene technologies (CRISPR, non-coding RNA, etc.) used in medical practice and at the stage of clinical trials were highlighted. Particular attention has been paid to molecular genetic methods of targeted therapy for cancer, including antitumor vaccines. Scientific developments in the field of prediction and preventive treatment of MFD have been considered - precision healing technologies of tomorrow. The main provisions of interactomics as an interdisciplinary field of natural science have been highlighted, as well as the applied aspects of this section of fundamental science for the development of diagnostic and treatment-and-prophylactic technologies of a new generation.

Multi-targeting drugs: past, present and future

The one disease - one target - one drug paradigm was an almost dominant principle in drug discovery from the 1960s to the 2000s. The stagnation and even decline in the productivity of drug innovation around the turn of the millennium and beyond, the realization of limitations of the one-target approach, especially in the treatment of multifactorial diseases, have drawn attention considerably to the one disease - multiple target - one drug multi-targeting drug concept. In this review, we outline old and new molecular design strategies and their practical implementation with own and other examples that also demonstrate unique therapeutic and diagnostic values and benefits of the multi-targeting approach. Finally, we point out that the full potential of the multi-targeting concept can emerge through data analytics and association methods (such as artificial intelligence) and system-based approach, preferably by linking it to quantitative systems pharmacology. This new systems pharmacology drug approach may also lead to novel breakthrough drugs, drug combinations and drug repositioning. Orv Hetil. 2020; 161(14): 523-531.

ChemInform Abstract: Multifunctional Compounds: Smart Molecules for Multifactorial Diseases

AbstractReview: 112 refs.

New perspectives for synergy research with the “omic”-technologies

Synergistic effects, understood as true overadditive effects, are often observed in experimental and clinical studies using phytopharmaceuticals. The introduction of the "omic"-technologies is now opening new perspectives in rationalizing these effects and making use of them in the development of a new generation of phytopharmaceuticals. This review describes possible mechanism of synergistic actions of herbal drugs by mono- and multitargeting and by the activation of signal cascades. It examines the possibilities of the standardization of single and multi component plant extracts and the prediction and assessment of the toxicity and safety of plant extracts with the support of the "omic"-technologies. It further discusses the use of phytopharmaceuticals in the context of an "individualized medicine". It makes proposals how to use the "omic"-technologies to rationalize and develop combination therapies of phytopharmaceuticals and synthetic drugs to minimize adverse reactions (ARs) or improve the therapeutic efficacy. Examples of clinical studies are given which explore already the potential of such co-medications. Modern medical therapy has acknowledged for quite some time the usefulness of combination therapies in the treatment of multifactorial diseases like cancer, cardiovascular or rheumatic diseases. The term "synergy" is rarely used in this context, the combinatory mechanisms of actions seldom completely understood and the potentially occurring adverse reactions feared. A systematic exploitation of synergy effects of phytomedical interventions alone or in combination with synthetic drugs should lead in a long term perspective to the discovery and development of more rational evidence-based interventions in the prevention and therapy of multifactorial diseases and should thereby enrich modern pharmacotherapy.

Heparin, Low Molecular Weight Heparin, and Derivatives in Thrombosis, Angiogenesis, and Inflammation: Emerging Links

The key reason behind the success of heparin in thrombosis and beyond is its polypharmacological sites of action for the prevention and treatment of multifactorial diseases that will only benefit slightly with single pharmacological mechanism-based agents. Thromboembolic disorders are driven by hypercoagulable, hyperactive platelet, proinflammatory, endothelial dysfunction, and proangiogenesis states. Heparin can effectively modulate all of those multifactorial components, as well as the interface among those components.

Pathogenesis of obesity and diabetes mellitus: insights provided by indirect calorimetry in humans.

Energy homeostasis is the balance between energy intake and energy expenditure. Assessment of energy intake is unreliable, especially in obese individuals. On the contrary it is possible to assess energy expenditure by means of different techniques. In this review, the contributions of indirect calorimetry to its assessment and to the comprehension of the pathogenic mechanisms of obesity and diabetes mellitus are discussed. Knowledge regarding energy expenditure and its components (basal metabolic rate, food-induced thermogenesis, expenditure related to physical activity), obtained in obese individuals by means of indirect calorimetry, is summarized. The effects of dietetic manipulation of the relative fractions of macronutrients (fat, carbohydrate and protein) and fiber intake on energy expenditure are described with implications regarding the pathogenesis of obesity. Besides environmental factors, energy expenditure is strongly influenced by inherited features. The application of indirect calorimetry to study recently discovered polymorphisms of genes strongly related to energy expenditure in humans is also summarized. The role of indirect calorimetry in the identification of the glucose metabolic pathways (oxidative and non-oxidative) affected in the insulin resistance syndrome is also described. Indirect calorimetry has been useful in realizing that the alterations typical of insulin resistance are reproducible in vivo in healthy humans, increasing the availability of free fatty acids. In fact, indirect calorimetry contributed to understanding the in vivo mechanisms of substrate competition, which was hypothesized more than forty years ago. In this field of application, the identification of simple (non-invasive and inexpensive) markers of insulin resistance is urgent for primary and secondary prevention of these diseases with high morbidity and mortality. The postabsorptive assessment of resting energy expenditure and macronutrient partitioning in fuel metabolism may be helpful and is discussed with advantages and limitations. The treatment of multifactorial diseases will probably require the use of poly-therapeutic interventions. In fact, drugs that act purely on one pathogenic factor of these diseases frequently fail. To better design strategic therapeutic approaches for each patient, to achieve significant long-term efficacy in the treatment of these diseases and to prevent their complications, indirect calorimetry has to be considered a landmark of quality control for nutritional support.