About this Research Topic
Over the last few decades, computer-aided drug design (CADD) has developed as an influential technique playing a crucial role in the development of new drug molecules that are capable of modulating protein functions in pathogenesis-related pathways.
Below, we briefly introduce several current topics in CADD addressing some of the most recent methods and efficient approaches:
A) For starting a CADD project, complete information on the 3D crystal structure of the drug target is required. Structure-based drug design (de novo ligand design, docking) and ligand-based drug design (pharmacophore modeling, Quantitative structure-activity relationships (QSAR), CoMFA) are the two methods generally used in computer-aided drug design.
B) Virtual screening has been established as a powerful strategy that is based on fast automated docking methods or similarity-based screening.
C) Molecular modeling systems are important and essential tools for building, visualizing, analyzing, and storing models of complex molecular structures.
D) Molecular dynamics simulation has become one of the most powerful tools to explore the flexibility of both small molecules and proteins and changes in their conformation in a short period of time.
Computer-based methods can contribute to the discovery of new lead compounds to be evaluated, to the selection of best candidates, and to avoid the chemical synthesis and screening of many irrelevant compounds. These methods create many benefits such as cost-saving, time to market improvement, in-sight knowledge of drug receptor interactions, and speed up of drug discovery and development. The progression of drug design and drug development is very challenging, expensive and time consuming, but has been accelerated thanks to the improvement of computational tools and methods.
The drug discovery process is complex and designing an effective and commercially viable drug requires interdisciplinary work. For this reason, Computer Aided Drug Design (CADD) Centre works with collaboration between structure biologists, biophysicists, and computational scientists to find new therapeutic agents. The design and development of any medicine takes many years: it begins when scientists learn about a biological target (e.g., a receptor, enzyme, protein, gene, etc.) that is involved in a biological process thought to be dysfunctional in patients with a disease, followed by the determination of specific target receptor, and finally by the determination of active compound from the mass of compounds. Linking and cross-validating studies, whether undertaken within the same research laboratory or across centers, is an essential element to a successful medicine development program. The concurrent evaluation of measures associated with drug mechanism/hypothesis can open new venues of research as well as close them and advance our knowledge of the targets for intervention. Therefore, the role of multiscale biomolecular simulations in identifying drug binding sites on the target macromolecule and elucidating drug action mechanisms is extremely significant.
In addition, development of both computer hardware, software, and algorithms is needed to benefit much from various computational methods which greatly reduce the time and cost of drug development.
In the collection, we focus on the publication of papers that take Computer-assisted approaches such as:
- Structure-Based Drug Design
- Virtual Screening
- Combining Docking and Molecular Dynamics Simulations
- Pharmacophore Modeling
- Statistical Methods (quantum chemistry calculation and 3D-Quantitative structure-activity relationships (QSAR) methods)
- Ligand-binding pocket prediction
- Pharmacokinetics/pharmacodynamics (PK/PD) prediction
- Physical property prediction
- Homology modeling to identify novel bioactive compounds.
Below, we briefly introduce several current topics in CADD addressing some of the most recent methods and efficient approaches:
A) For starting a CADD project, complete information on the 3D crystal structure of the drug target is required. Structure-based drug design (de novo ligand design, docking) and ligand-based drug design (pharmacophore modeling, Quantitative structure-activity relationships (QSAR), CoMFA) are the two methods generally used in computer-aided drug design.
B) Virtual screening has been established as a powerful strategy that is based on fast automated docking methods or similarity-based screening.
C) Molecular modeling systems are important and essential tools for building, visualizing, analyzing, and storing models of complex molecular structures.
D) Molecular dynamics simulation has become one of the most powerful tools to explore the flexibility of both small molecules and proteins and changes in their conformation in a short period of time.
Computer-based methods can contribute to the discovery of new lead compounds to be evaluated, to the selection of best candidates, and to avoid the chemical synthesis and screening of many irrelevant compounds. These methods create many benefits such as cost-saving, time to market improvement, in-sight knowledge of drug receptor interactions, and speed up of drug discovery and development. The progression of drug design and drug development is very challenging, expensive and time consuming, but has been accelerated thanks to the improvement of computational tools and methods.
The drug discovery process is complex and designing an effective and commercially viable drug requires interdisciplinary work. For this reason, Computer Aided Drug Design (CADD) Centre works with collaboration between structure biologists, biophysicists, and computational scientists to find new therapeutic agents. The design and development of any medicine takes many years: it begins when scientists learn about a biological target (e.g., a receptor, enzyme, protein, gene, etc.) that is involved in a biological process thought to be dysfunctional in patients with a disease, followed by the determination of specific target receptor, and finally by the determination of active compound from the mass of compounds. Linking and cross-validating studies, whether undertaken within the same research laboratory or across centers, is an essential element to a successful medicine development program. The concurrent evaluation of measures associated with drug mechanism/hypothesis can open new venues of research as well as close them and advance our knowledge of the targets for intervention. Therefore, the role of multiscale biomolecular simulations in identifying drug binding sites on the target macromolecule and elucidating drug action mechanisms is extremely significant.
In addition, development of both computer hardware, software, and algorithms is needed to benefit much from various computational methods which greatly reduce the time and cost of drug development.
In the collection, we focus on the publication of papers that take Computer-assisted approaches such as:
- Structure-Based Drug Design
- Virtual Screening
- Combining Docking and Molecular Dynamics Simulations
- Pharmacophore Modeling
- Statistical Methods (quantum chemistry calculation and 3D-Quantitative structure-activity relationships (QSAR) methods)
- Ligand-binding pocket prediction
- Pharmacokinetics/pharmacodynamics (PK/PD) prediction
- Physical property prediction
- Homology modeling to identify novel bioactive compounds.
Keywords: Drug design, Molecular dynamics simulation, Virtual screening, Molecular modeling, QSAR, Pharmacophore modeling
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