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ICEP: Indiana Cheminformatics Education Portal
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2D chemical database searching systems
3D visualization, alignment, docking and scoring
Characterizing 2D structures with descriptors and fingerprints
Chemical structures on the web and in the scholarly literature
Cluster Analysis and Diversity Analysis
Data mining of chemical & biological information
MOOCs and Learning Materials Relevant to Cheminformatics
Quantitative Structure-Activity Relationships (QSAR) and Predictive Models
Representation and characterization of 3D structures
Representation of 2D structures on computer
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3D visualization, alignment, docking and scoring
We have already discussed ways of representing and characterizing 3D structures, including conformer generation, energy minimization and 3D pharmacophore and similarity searching. In this section, we will look molecular visualization, and then how 3D structures can be used in a variety of computational fashions either separately from or in conjunction with a protein target structure.
Visualization of 3D structures and proteins
The simplest and most common way to visualize a 3D structure is with the CPK ball and stick model:
Interestingly, molecular visualization was introduced very early (1960's and 70's) and until high quality graphics became commoditized in the 1990's, was one of the main applications of high-end graphics workstations. As a comparison, here are a molecular image taken from an Evans & Sutherland workstation running Sybyl, and the current version of Microsoft Windows, both taken in 1988 (Windows 2.0 image taken from www.guidebookgallery.org):
There are plenty of programs available for visualizing and rotating and translating molecules in this fashion (and with a variety of other bells and whistles). Most of them are free. Some work in web browsers; some are standalone; some produce images. Most work with proteins as well as small molecules. A few notable ones are
There are plenty of tutorials available, particularly using JMol. Here are some:
on installing and basic use of JMol
Introduction to JMOL
Introduction to JMOL scripting
from California Lutheran
Some great work on advanced molecular visualization has been done at the
Scripps Molecular Graphics Laboratory
Molecular superposition involves aligning two or more molecules in 3D (either to each other or to a single rigid reference molecule) so they optimally overlay in some fashion. Alignment is done by rotating and translating the molecules, and by flexing and rotating bonds to create different conformers. Superimposition can be a prerequisite to 3D similarity searching, pharmacophore detection, and 3D QSAR.
Superposition is an example of optimization, and thus can use one of a variety of methods, from simple hill climbing to genetic algorithms, simulated annealing and monte-carlo. Example commercial packages are
and Accelrys Discovery Studio
. Other methods have been used for alignment, for example shape-based overlay (see OpenEye
) or field-based overlay.
3D QSAR can be done simply by using 3D descriptors instead of 2D. However, there are a variety of other ways of doing QSAR in 3D. One well known one is
(Comparative Molecular Field Analysis). CoMFA uses fields to optimize overlay of multiple structures based on features related to binding (electrostatics, sterics, hydrophobics), finds commonality in the overlaid fields, then correlates these areas of commonality with activity. It requires that structures be already aligned, and can be used predictively or for visualization. For more information, see the
. A nice example of its use with D2 agonists is in
another NetSci article
Molecular docking involves attempting to predict how compounds ("ligands") might bind to the active sites of protein targets (usually to predict inhibition activity). Most of them rotate and translate molecules in an active site, flexing rotatable bonds, until some function relating to binding is minimized. This
often is made of some combination of hydrogen bonding, electrostatic interactions, shape, and hydrophobic interactions. The final value of the scoring function is generally taken as a measure of the success of the docking. Whilst docking algorithms have proven quite good at replicating binding orientations of compounds in active sites (testes using RMSD from bound ligands in crystal structures), the relationship of the final value of the scoring function to binding affinity is much less clear. Some of the more popular docking programs are:
Molecular Modeling Tools
There are a variety of molecular modeling tools available that can do superposition, 3D QSAR, docking, and/or quantum calculations. Here are a few:
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