Application of In Silico Techniques in Drug Design
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Biophysics".
Deadline for manuscript submissions: closed (20 April 2022) | Viewed by 77409
Special Issue Editor
Interests: cheminformatics; computational chemistry; computer-aided drug design; machine learning; molecular docking; molecular dynamics simulations; pharmacophore modeling; predictive modeling; QSAR; structure and ligand-based pharmacophore modeling
Special Issue Information
Dear Colleagues,
At present, in silico techniques play an important role in the drug discovery process. Various computational methods are used to identify novel and potent drug candidates as well as promising targets in various diseases. Applying in silico techniques such as high-throughput virtual screening, pharmacophore screening, molecular docking, and predictive models will help to identify potent drug candidates from large databases. Predictive models using machine learning, 3D-QSAR, combination of QSAR and molecular dynamics simulations, etc. will help to predict the activity of chemicals and suggest modifying the chemical probe to enhance the chemical activity. Understanding the 3D structure of the protein and its interactions with small molecules or macromolecules is important to identify novel chemicals as a drug. Molecular docking and molecular dynamics simulation play a major role in structure-based drug design approaches. If the 3D structure of the protein is unknown, homology modeling will be employed to build 3D structures based on its amino acid sequences. Quantum and molecular mechanism can be employed to understand the mechanism of the protein–ligand complex or macromolecule complexes, which helps to give a better understanding of the biological pathways and mechanisms. All these in silico techniques will help researchers in various fields to reduce the time and cost as well as the number of animals tested in in vivo studies.
The main feature of this Special Issue is to share, in open-source format, significant works using in silico methods in drug design that can help to design or identify a novel and potent candidate drug as well as to understand the mechanism of various proteins involved in various diseases. In this Special Issue, we welcome manuscripts from researchers using any in silico techniques in original research papers, short communications, and reviews.
Dr. Sugunadevi Sakkiah
Guest Editor
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Keywords
- computational chemistry
- computer-aided drug design
- drug designing
- drug discovery
- drug repurposing
- flexible docking
- homology modeling
- molecular docking
- molecular dynamics simulation
- molecular modeling
- predictive models using machine learning or deep learning or AI
- QSAR
- structure and ligand-based pharmacophore model
- virtual screening
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