1,720,975 research outputs found
In silico binding free energy predictability by using the linear interaction energy (LIE) method: Bromobenzimidazole CK2 inhibitors as a case study
No full textProtein kinase CK2 is essential for cell viability, and its control regards a broad series of cellular events such as gene expression, RNA, and protein synthesis. Evidence of its involvement in tumor development and viral replication indicates CK2 as a potential target of antineoplastic and antiviral drugs. In this study the Linear Interaction Energy (LIE) Method with the Surface Generalized Born (SGB) continuum solvation model was used to study several bromobenzimidazole CK2 inhibitors. This methodology, developed by Aqvist, finds a plausible compromise between accuracy and computational speed in evaluating binding free energy (DeltaGbind) values. In this study, two different free binding energy models, named "CK2scoreA" and "CK2scoreB", were developed using 22 inhibitors as the training set in a stepwise approach useful to appropriately select both the tautomeric form and the starting binding position of each inhibitor. Both models are statistically acceptable. Indeed, the better one is characterized by a correlation coefficient (r2) of 0.81, and the predictive accuracy was 0.65 kcal/mol. The corresponding validation, using an external test set of 16 analogs, showed a correlation coefficient (q2) of 0.68 and a prediction root-mean-square error of 0.78 kcal/mol. In this case, the LIE approach has been proved to be an efficient methodology to rationalize the difference of activity, the key interactions, and the different possible binding modes of this specific class of potent CK2 inhibitors
Designing a ligand for pharmaceutical purposes
No full textBackground: Drug approval applications to the FDA have shown a remarkably small increment compared with what was expected. In the last few years several efforts have been made to improve the results of rational drug design approaches and in particular to predict inhibitor-target structure and to evaluate the free energy of binding. Virtual database screening, combined with other computational methods, is one of the most promising methods to overcome this key issue. Objective: It is possible to understand how computational medicinal chemistry is changing, improving from its errors and moving towards becoming a more important tool for drug development. Methods: Some of the most recent modeling techniques have been presented and in particular the benefits of combining these techniques are highlighted. Results/conclusion: At present computational chemists can understand the peculiar problems associated with the study of biological systems and on this basis they can choose the right collection of complementary in silico approaches to solve the medicinal chemistry problem in a better manner
Protein Kinase CK2 Inhibitors: Emerging Anticancer Therapeutic Agents?
No full textProtein kinase CK2 is a ubiquitous, essential, and highly pleiotropic protein kinase whose abnormally high constitutive activity is suspected to underlie its pathogenic potential in neoplasia and other diseases. A number of structurally unrelated CK2 inhibitors, tested on a variety of cells derived from tumours, including lymphomas, leukaemias, multiple myeloma and prostate carcinoma, display a pro-apoptotic effect which is roughly proportional to their in vitro inhibitory potency. In the present review we summarize the most recent discovery of potent and selective CK2 inhibitors and their prospective as future anticancer agents
Transient abdominal motor block after a transversus abdominis plane block in an elderly patient
Full text linkHow Druggable Is Protein Kinase CK2?
No full textCK2 is a pleiotropic, ubiquitous, and constitutively active protein kinase (PK), with both cytosolic and nuclear localization in most mammalian cells. The holoenzyme is generally composed of two catalytic (alpha and/or alpha') and two regulatory (beta) subunits, but the free alpha/alpha' subunits are catalytically active by themselves and can be present in cells under some circumstances. CK2 catalyzes the phosphorylation of more than 300 substrates characterized by multiple acidic residues surrounding the phosphor-acceptor amino acid, and, consequently, it plays a key role in several physiological and pathological processes. But how can one kinase orchestrate all these tasks faithfully? How is it possible that one kinase can, despite all pleiotropic characteristics of PKs in general, be involved in so many different biochemical events? Is CK2 a druggable target? Several questions are still to be clearly answered, and this review is an occasion for a fruitful discussion
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Water network perturbation in ligand binding: Adenosine A2AAntagonists as a case study
No full textRecent efforts in the computational evaluation of the thermodynamic properties of water molecules have resulted in the development of promising new in silico methods to evaluate the role of water in ligand binding. These methods include WaterMap, SZMAP, GRID/CRY probe, and Grand Canonical Monte Carlo simulations. They allow the prediction of the position and relative free energy of the water molecule in the protein active site and the analysis of the perturbation of an explicit water network (WNP) as a consequence of ligand binding. We have for the first time extended these approaches toward the prediction of kinetics for small molecules and of relative free energy of binding with a focus on the perturbation of the water network and application to large diverse data sets. Our results support a qualitative correlation between the residence time of 12 related triazine adenosine A2A receptor antagonists and the number and position of high energy trapped solvent molecules. From a quantitative viewpoint, we successfully applied these computational techniques as an implicit solvent alternative, in linear combination with a molecular mechanics force field, to predict the relative ligand free energy of binding (WNP-MMSA). The applicability of this linear method, based on the thermodynamics additivity principle, did not extend to 375 diverse A2A receptor antagonists. However, a fast but effective method could be enabled by replacing the linear approach with a machine learning technique using probabilistic classification trees, which classified the binding affinity correctly for 90% of the ligands in the training set and 67% in the test set
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