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Medicinal Chemistry

University of Valencia

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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:

  1. hit identification using virtual screening (structure- or ligand-based design)
  2. hit-to-lead optimization of affinity and selectivity (structure-based design, QSAR, etc.)
  3. 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

 

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