Computer-aided drug design (CADD) is a modern computational technique used in the drug discovery process. CADD includes computational chemistry, molecular modeling, molecular design and rational drug design. CADD techniques are gaining popularity and appreciation in both academic circles as well as in pharmaceutical industries. It has revolutionized the drug discovery process with greater speed and accuracy.
Figure 1 An overview of CADD drug designing/design pipeline. (Vartika Tomar, et al. 2019)
- Screen large databases of molecules and identify potential drug candidates.
- Quickly and efficiently identify promising compounds for further investigation.
CD ComputaBio can screen small molecule library against the target using virtual screening protocol to identify hits/leads.
- Build 3D models of drug molecules and predict their properties, such as binding affinity, solubility, and toxicity.
- Optimize drug candidates and improve their chances of success.
- Predict how a drug molecule will interact with its target protein.
- Design more effective drugs that bind to the target protein with high affinity.
Lead Optimization
- Optimize the leads by designing better molecules for synthesis and testing.
- Modify existing drug molecules and optimize their properties, such as improving their potency, reducing toxicity, or increasing their selectivity for a particular target protein.
ADME/Tox Prediction
- Predict a drug molecule's absorption, distribution, metabolism, and excretion (ADME) properties, as well as its potential toxicity, using in silico techniques.
- Design safer and more effective drugs.
CADD comprises a broad range of theoretical and computational approaches that are part of modern drug discovery. Such methods have emerged and evolved along with experimental approaches used in drug design. Due to the advanced technology in chem-informatics, bioinformatics, proteomics, genomics, and structural information, CADD tools have paved the way in innovating novel drugs have accelerated the process of developing new drugs and cost-effectively conducting the research and development.
Available Software Packages
- Schrödinger Suite is one of the most widely used software in CADD. It offers a range of tools for molecular modeling, virtual screening, and lead optimization. Some of its popular modules include Maestro, Glide, LigPrep, and Prime.
- AutoDock is a popular software for docking studies, which predicts the binding orientation and affinity of a ligand to a protein. It uses a variety of search algorithms to explore the conformational space of the ligand and protein.
- OpenEye Suite is a comprehensive software package for molecular modeling, virtual screening, and cheminformatics. It includes a range of tools for ligand design, shape and electrostatic similarity analysis, and molecular dynamics simulation.
- MOE (Molecular Operating Environment) is a software package that provides a range of tools for molecular modeling, visualization, and analysis. It offers several modules for ligand-based and structure-based drug design, including docking, pharmacophore modeling, and QSAR.
- CHARMM (Chemistry at Harvard Macromolecular Mechanics) is a widely used molecular simulation software that provides tools for molecular dynamics simulation, energy minimization, and free energy calculations. It is particularly useful for simulating large biomolecules such as proteins and nucleic acids.
* For Research Use Only.
