Recent Advances in Computational Drug Discovery: From In Silico Screening to Multiscale De Novo Drug Design
A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Computational and Theoretical Chemistry".
Deadline for manuscript submissions: closed (31 January 2020) | Viewed by 53486
Special Issue Editor
Interests: multi-target drug discovery, chemoinformatics, QSAR-based approaches, virtual screening, multi-scale de novo drug design, machine learning.
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Special Issue Information
Dear Colleagues,
Diseases continue to plague modern societies, and over time, through the process known as drug discovery, a plethora of therapeutic options has been introduced to cure illnesses. Unfortunately, most of them remain as unresolved health issues. The experience accumulated demonstrates that the scientific community still faces several challenges in drug development. On one hand, it is well-established that the chemical space to be covered in the search for new drugs is vast, being formed by approximately 1060 small molecules. On the other hand, diseases are difficult to treat because of their multifactorial nature, which in many cases is related to phenomena such as drug resistance. Further, most of the current drugs are associated with a broad spectrum of side effects. Consequently, designing a new drug is increasingly expensive, complex, and time-consuming, taking 12–17 years with a cost of around US$3 billion.
Today, to accelerate and improve drug discovery, there is a pressing need to exploit and integrate the huge amounts of data coming from the domains of the chemical, biological, and biomedical sciences. In this context, in silico approaches have become an integral part of all the drug discovery projects, helping to rationalize the design of potent and versatile therapeutic agents.
In this Special Issue of Molecules, we are inviting the scientific community to submit original research contributions, short communications, or review articles that highlight the most recent advances in the applications of in silico approaches to all the areas involved in drug discovery.
Prof. Alejandro Speck-Planche
Guest Editor
Manuscript Submission Information
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Keywords
- Virtual screening
- De novo design
- Chemoinformatics
- Bioinformatics
- QSAR
- Big data and data mining
- Machine learning
- Network modeling
- Multiscale models
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