Computer-assisted drug design
Computer-assisted drug design uses computational chemistry to discover, enhance, or study drugs and related biologically active molecules. The most fundamental goal is to predict whether a given molecule will bind to a target and if so how strongly. Molecular mechanics or molecular dynamics are most often used to predict the conformation of the small molecule and to model conformational changes in the biological target that may occur when the small molecule binds to it. Semi-empirical, ab initio quantum chemistry methods, or density functional theory are often used to provide optimized parameters for the molecular mechanics calculations and also provide an estimate of the electronic properties (electrostatic potential, polarizability, etc.) of the drug candidate which will influence binding affinity.
Molecular mechanics methods may also be used to provide semi-quantitative prediction of the binding affinity. Alternatively knowledge based scoring function may be used to provide binding affinity estimates. These methods use linear regression, machine learning, neural nets or other statistical techniques to derive predictive binding affinity equations by fitting experimental affinities to computationally derived interaction energies between the small molecule and the target.
Ideally the computational method should be able to predict affinity before a compound is synthesized and hence in theory only one compound needs to be synthesized. The reality however is that present computational methods provide at best only qualitative accurate estimates of affinity. Therefore in practice it still takes several iterations of design, synthesis, and testing before an optimal molecule is discovered. On the other hand, computational methods have accelerated discovery by reducing the number of iterations required and in addition have often provided more novel small molecule structures.
Drug design with the help of computers may be used at any of the following stages of drug discovery:
- hit identification using virtual screening (structure- or ligand-based design)
- hit-to-lead optimization of affinity and selectivity (structure-based design, QSAR, etc.)
- lead optimization optimization of other pharmaceutical properties while maintaining affinity
Comparative table of packages covering the major aspects of molecular design
3D - Molecular Graphics, Mouse - drawing molecule by mouse, Poly - polymer building, DNA - Nucleic acid building, Pept - Peptide building, Cryst - crystal building, Solv - solvent addition, Q - partial charges, Dock - docking, Min - optimization, MM - Molecular mechanics, QM - Quantum mechanics. FF - Support for Force Field development.
| 3D | Mouse | Poly | DNA | Pept | Cryst | Solv | Q | Dock | Min | MM | QM | FF | Homepage | Comments | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AMBER | + | + | + | + | + | + | ambermd.org | Classical molecular modeling program | |||||||
| ArgusLab | + | + | + | + | + | + | + | + | Planaria Software | A molecular modeling, graphics, and drug design program | |||||
| Ascalaph Designer | + | + | + | + | + | + | + | + | + | + | + | + | Agile Molecule | common molecular modeling suite | |
| Avogadro (software) | + | + | + | + | + | + | + | + | OpenMolecules.net | Extensible, free, open source molecular editor | |||||
| BOSS | + | + | + | + | + | Yale University | OPLS inventor | ||||||||
| DOCK | + | + | + | + | University of California | DOCK algorithm | |||||||||
| Firefly (PC GAMESS) | + | + | + | + | Moscow State University | ab initio and DFT computational chemistry program | |||||||||
| Maestro | + | + | + | + | + | + | + | + | + | + | + | + | + | Schrodinger | A molecular modeling, visualization, and drug design program |
| Materials Studio | + | + | + | + | + | + | + | + | + | + | + | Accelrys | software environment | ||
| MedeA | + | + | + | + | + | + | Materials Design | software environment for inorganic materials science | |||||||
| MOE | + | + | + | + | + | + | + | + | + | + | + | + | + | Chemical Computing Group | Molecular Operating Environment |
| NAB | + | + | + | Rutgers University | molecular manipulation language for nucleic acids | ||||||||||
| PCMODEL | + | + | + | + | + | + | + | + | Serena Software | common molecular modeling tool | |||||
| STR3DI32 | + | + | + | + | + | + | + | + | + | + | + | Exorga Software | molecular modeling tool | ||
| TINKER | + | + | + | + | Washington University | tools for protein design | |||||||||
| VEGA | + | + | + | + | + | + | Università degli Studi di Milano | a bridge between most of the molecular software packages |
Wikipedia