1,721,406 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
Novel camptothecin derivatives as topoisomerase I inhibitors
No full textBACKGROUND:
Camptothecin (CPT), a pentacyclic alkaloid isolated by Wall et al. in 1958 from the Chinese tree Camptotheca acuminata, was reported to possess an interesting antitumor activity. Late in 1985, it was reported by Liu et al. that the cytotoxic activity of CPT was attributed to a novel mechanism of action involving the nuclear enzyme classified as type I DNA topoisomerase. Since the explanation of the unique mechanism of action, many derivatives have been synthesized and some of them are in various stages of preclinical and clinical development. Among them, two derivatives, topotecan and irinotecan, have successfully entered into the market and are used as topoisomerase I poisons in clinical practice.
OBJECTIVE:
The main focus of the present review is to describe the development of CPT derivatives over the years dividing them by decades according to the date of discovery and focusing attention on molecules that were published in patents.
RESULTS/CONCLUSION:
To summarize, > 150 patents have been deposited over the past 30 years. Structure-activity relationship studies suggest that substitutions at the 7-, 9- or 10-positions of most CPT derivatives enhance their antitumor activity, but at the 11- or 5-position usually lead to activity decrease
Supervised Molecular Dynamics (SuMD) as a Helpful Tool To Depict GPCR–Ligand Recognition Pathway in a Nanosecond Time Scale
No full textDesigning 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
Molecular modeling as a tool to investigate molecular recognition in P2Y receptors
No full textNucleotides are emerging as an ubiquitous family of extracellular signaling molecules. These effects are mediated through a specific class of plasma membrane receptors called P2 receptors that, according to the molecular structure, are further subdivided into two subfamilies: P2Y and P2X. Specifically, P2X-receptors are ligand-gated ion channels, whereas P2Y-receptors belong to the superfamily of G-protein-coupled receptors. In this review, we focus our attention to GPCRs molecular architecture, with the special emphasis on our work on the human P2Y(1) receptor. In fact, despite an enormous amount of research on the structure and function of these receptors, fundamental understanding of the molecular details of ligand/GPCR interactions remains very rudimentary. How agonist binding transforms a resting GPCR into its active form and the microscopic basis of binding site blockade by an antagonist are generally still unclear. In the absence of high-resolution structural knowledge of GPCRs, such questions only can be addressed by building models, which are tested through pharmacological and biochemical studies. In this review, we underline how different molecular modeling approaches can help the investigation of both receptor architecture and ligand/receptor molecular recognition
Mimicking Peptides... In Silico
No full textProtein-protein interactions (PPIs) play a central and crucial role in almost every cellular process. Understanding the structural basis of protein-protein interactions can lead to the development of new drugs for treatment of various diseases. With this purpose, peptide-based drug design (PBDD) has been extensively explored in the last few decades. Peptidomimetics are compounds which mimic the biological activity of peptides while offering the advantages of improving their pharmacokinetics profiles. In this review, we would like to summarize the state of the art of computational methods which have been recently introduced to design novel peptidomimetics involved in a therapeutically relevant protein-protein recognition processes
Role of the extracellular loops of G protein-coupled receptors in ligand recognition: a molecular modeling study of the human P2Y1 receptor
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