Drug discovery is an eternal challenge for the biomedical sciences

Background: Numerous sequencing techniques have been progressed since the 1960s with the rapid development of molecular biology studies focusing on DNA and RNA. Methods: a great number of articles, book chapters, websites are reviewed, and the studies covering NGS history, technology and applications to cancer therapy are included in the present article. Results: High throughput next-generation sequencing (NGS) technologies offer many advantages over classical Sanger sequencing with decreasing cost per base and increasing sequencing efficiency. NGS technologies are combined with bioinformatics software to sequence genomes to be used in diagnostics, transcriptomics, epidemiologic and clinical trials in biomedical sciences. The NGS technology has also been successfully used in drug discovery for the treatment of different cancer types. Conclusion: This review focuses on current and potential applications of NGS in various stages of drug discovery process, from target identification through to personalized medicine.

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The QSAR Paradigm in Fragment-Based Drug Discovery: From the Virtual Generation of Target Inhibitors to Multi-Scale Modeling

Mini-Reviews in Medicinal Chemistry ◽

10.2174/1389557520666200204123156 ◽

2020 ◽

Vol 20 (14) ◽

pp. 1357-1374 ◽

Cited By ~ 1

Author(s):

Valeria V. Kleandrova ◽

Alejandro Speck-Planche

Keyword(s):

Drug Discovery ◽

Structural Information ◽

Biological Data ◽

Heterogeneous Databases ◽

Biomedical Sciences ◽

Multi Scale ◽

Scale Modeling ◽

Multi Scale Modeling

Fragment-Based Drug Design (FBDD) has established itself as a promising approach in modern drug discovery, accelerating and improving lead optimization, while playing a crucial role in diminishing the high attrition rates at all stages in the drug development process. On the other hand, FBDD has benefited from the application of computational methodologies, where the models derived from the Quantitative Structure-Activity Relationships (QSAR) have become consolidated tools. This mini-review focuses on the evolution and main applications of the QSAR paradigm in the context of FBDD in the last five years. This report places particular emphasis on the QSAR models derived from fragment-based topological approaches to extract physicochemical and/or structural information, allowing to design potentially novel mono- or multi-target inhibitors from relatively large and heterogeneous databases. Here, we also discuss the need to apply multi-scale modeling, to exemplify how different datasets based on target inhibition can be simultaneously integrated and predicted together with other relevant endpoints such as the biological activity against non-biomolecular targets, as well as in vitro and in vivo toxicity and pharmacokinetic properties. In this context, seminal papers are briefly analyzed. As huge amounts of data continue to accumulate in the domains of the chemical, biological and biomedical sciences, it has become clear that drug discovery must be viewed as a multi-scale optimization process. An ideal multi-scale approach should integrate diverse chemical and biological data and also serve as a knowledge generator, enabling the design of potentially optimal chemicals that may become therapeutic agents.

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Pharmaceutical patent landscape for cancer immunotherapy: an interview with Gilles Berger

Pharmaceutical Patent Analyst ◽

10.4155/ppa-2019-0021 ◽

2019 ◽

Vol 8 (5) ◽

pp. 163-164

Author(s):

Gilles Berger

Keyword(s):

Drug Discovery ◽

Halogen Bonding ◽

Theoretical Chemistry ◽

Biomedical Sciences ◽

Research Fellow ◽

Track Record ◽

Research Associate ◽

Patent Landscape ◽

Hands On ◽

The Us

Dr Gilles Berger is a chemist and pharmacist with broad interest in organic and theoretical chemistry, drug discovery and design, biomedical sciences and oncology. He has worked as a Research Fellow in Brussels, Paris, Montreal and at MIT in Boston, where he has gathered hands-on experience at the interface of drug design, nanotechnologies, biology and human disease. He has been involved in project management and mentoring and has in depth experience in collaborative and multi-disciplinary projects, with a proven track record of publications in various fields, in collaboration with research groups from all around Europe, Canada and the US. In recent years, he has developed as a translational scientist, allowing the use of his complementary multi-disciplinary skills toward the advancement of fundamental projects, such as organocatalysis, theoretical chemistry or halogen bonding; as well as in applications like drug discovery, as evidenced by his numerous publications aimed at developing novel anticancer medicines and other agents. He is currently a Research Fellow of the Harvard Medical School, a Research Associate at MIT and a Fellow of the Belgian Science Foundation.

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