47 research outputs found
Exploring the Anti-Hypoxaemia Effect of Hydromethylthionine : A Prospective Study of Phase 3 Clinical Trial Participants
Funding Information: This work was funded by TauRx Therapeutics Ltd., Singapore.Peer reviewedPublisher PD
Exploring Protein-Protein Interactions as Drug Targets for Anti-cancer Therapy with In Silico Workflows
We describe a computational protocol to aid the design of small molecule and peptide drugs that target protein-protein interactions, particularly for anti-cancer therapy. To achieve this goal, we explore multiple strategies, including finding binding hot spots, incorporating chemical similarity and bioactivity data, and sampling similar binding sites from homologous protein complexes. We demonstrate how to combine existing interdisciplinary resources with examples of semi-automated workflows. Finally, we discuss several major problems, including the occurrence of drug-resistant mutations, drug promiscuity, and the design of dual-effect inhibitors.Fil: Goncearenco, Alexander. National Institutes of Health; Estados UnidosFil: Li, Minghui. Soochow University; China. National Institutes of Health; Estados UnidosFil: Simonetti, Franco Lucio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Shoemaker, Benjamin A. National Institutes of Health; Estados UnidosFil: Panchenko, Anna R. National Institutes of Health; Estados Unido
Prediction of cyclin-dependent kinase 2 inhibitor potency using the fragment molecular orbital method
Stable Mutated tau441 Transfected SH-SY5Y Cells as Screening Tool for Alzheimer’s Disease Drug Candidates
The role of hyperphosphorylation of the microtubule-associated protein tau in the pathological processes of several neurodegenerative diseases is becoming better understood. Consequently, development of new compounds capable of preventing tau hyperphosphorylation is an increasingly hot topic. For this reason, dependable in vitro and in vivo models that reflect tau hyperphosphorylation in human diseases are needed. In this study, we generated and validated an in vitro model appropriate to test potential curative and preventive compound effects on tau phosphorylation. For this purpose, a stably transfected SH-SY5Y cell line was constructed over-expressing mutant human tau441 (SH-SY5Y-TMHT441). Analyses of expression levels and tau phosphorylation status in untreated cells confirmed relevance to human diseases. Subsequently, the effect of different established kinase inhibitors on tau phosphorylation (e.g., residues Thr231, Thr181, and Ser396) was examined. It was shown with several methods including immunosorbent assays and mass spectrometry that the phosphorylation pattern of tau in SH-SY5Y-TMHT441 cells can be reliably modulated by these compounds, specifically targeting JNK, GSK-3, CDK1/5, and CK1. These four protein kinases are known to be involved in in vivo tau phosphorylation and are therefore authentic indicators for the suitability of this new cell culture model for tauopathies
Computational Methods Used in Hit-to-Lead and Lead Optimization Stages of Structure-Based Drug Discovery
GPCR modeling approaches are widely used in the hit-to-lead (H2L) and lead optimization (LO) stages of drug discovery. The aims of these modeling approaches are to predict the 3D structures of the receptor-ligand complexes, to explore the key interactions between the receptor and the ligand and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this book chapter, we present a brief survey of key computational approaches integrated with hierarchical GPCR modeling protocol (HGMP) used in hit-to-lead (H2L) and in lead optimization (LO) stages of structure-based drug discovery (SBDD). We outline the differences in modeling strategies used in H2L and LO of SBDD and illustrate how these tools have been applied in three drug discovery projects