Proteomics/Proteomics and Drug Discovery/Software Tools

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Helpful Links, Resources, and Software

These tools and databases are examples of the publicly available resources available to drug discovery teams. Private databases often contain the contents of publicly available ones as well.

Protein, Proteomics, and Drug Discovery Resources

Databases

Applications

Print/Web Resources

Virtual Drug and Target Libraries

Free Libraries

Pay-per-use Libraries

Docking and Scoring Tools

The search space in a docking problem consists of all possible conformations (the relative positions of atoms in the 3D structure of a molecule, independent of the coordinate system) and configurations /orientations (the positions of atoms of a molecule after undergoing a rotation and translation in a coordinate system of the protein paired with the ligand). With present computing resources, it would be impossible to exhaustively explore the search space for all possible poses (a pose is the name given to the configuration of the conformation of a molecule in a coordinate system). Needless to say, every docking simulation is a trade-off between accuracy and speed and a good docking tool is expected to maintain a reasonably good balance between the two. The success of a docking program can be said to depend on depend on two components: the scoring function and the search algorithm.

There are many competitive docking tools available from various sources, ranging from expensive and feature-rich corporate suites to simple yet powerful applications developed by academic/ research institutes.

DOCK

DOCK was developed by the team led by Irwin Kuntz at the University of California, San Francisco (http://dock.compbio.ucsf.edu/). The most recent version, DOCK 6; is written in C++ and is functionally separated into independent components, thereby conferring program flexibility. The Kuntz lab provides source code for all programs and they are available free of charge for academic institutions, however industrial organizations are charged a licensing fee. Following are some of the applications cited by the authors for DOCK:

The main DOCK executable is run command line from a standard unix shell and windows users need to run it using a Linux-like environment like Cygwin. DOCK uses an “incremental construction” docking algorithm, which essentially means that the ligands are initially ‘fragmented’:

The active site of the protein is identified by the program sphgen, which also generates the sphere centers filling the site. Scoring grids are generated by the program grid. The program DOCK then matches the spheres to the ligand atoms and uses the scoring grids to evaluate ligand orientations and finally minimizes the energy based scores. A comprehensive tutorial for DOCK 6 and the docking process in general can be found here: http://www2.umdnj.edu/~kholodvl/tut/DOCK60_intro_linux.pdf

GLIDE

Glide is a commercial product marketed as “A complete solution for ligand-receptor docking” by Schrödinger (http://www.schrodinger.com/). Some of the highlights of the tool include:

Glide uses a “Stochastic Search” docking algorithm. The algorithm approximates a complete systematic search over ligand positions, orientations, and conformations in the receptor site. The energy minimization stage utilizes the Monte Carlo simulation algorithm.

The enhanced features and easy-to-use interface of Glide, however comes at a cost that is both financial and computational.

Yucca

Yucca is a very recent and new algorithm specifically for small molecule docking, developed by Vicky Choi at the Department of Computer Science, Virginia Tech. The algorithm (still under active development), is based on an efficient heuristic for local search and has been used in conjunction with the conformer generator OMEGA (Optimized Molecular Ensemble Generation Application) to generate a set of low-energy conformers. Yucca utilizes a “multiconformer” algorithm. The conformers obtained from OMEGA are then rigidly docked and the configurations are coarsely sampled. Each configuration is then improved locally to a local minimum.

Comparative evaluation of Yucca with the other existing algorithms seems to prove it to be a competitive tool, however it is still being developed and tweaked to add and improve features. Among the improvements being made are: the tool’s own conformer generator, a better scoring function, flexible receptor docking and virtual screening.


Other available software tools include:

The Binding Affinity Prediction of Protein-Ligand server is a tool which can be used to calculate the binding energy of a non-metallo protein-ligand complex.

AutoDOCK, like DOCK, attempts to determine the orientation of a compound in a drug target. AutoDOCK, being a docking and scoring package, also contains scoring functions. AutoDOCK has also been applied to the problem of protein-protein docking .

A newer system that claims to use novel docking algorithms.

FleXX is another widely used docking program, known for its speed compared to many other applications.

Molecular docking server is an internet service that calculates the site, geometry and energy of small molecules interacting with proteins.

ZLAB is free academically but requires a paid license through Accelrys commercially. It is a two-stage docking system with ZLAB performing initial FT calculations and RLAB optimizing the highest scoring hits.

See the Wikipedia Molecular docking site for links to additional softwares.

Although there are currently, many applications that simulate intermolecular interactions, there is still much room for improvement. Newer applications and algorithms are being developed constantly and the struggle for the perfect balance between accuracy and speed remains one of the critical factors. For instance, Glide, in spite of being among the best performers in terms of accuracy and ease of use, loses out heavily on computational time. Institutionally designed packages such as DOCK and AutoDock also have strengths as they are constantly worked on and updated. Most such academic software, however are command-line based and pose a steep learning curve for most users. Various other problems such as flexible receptor docking (which is, at this point enormously computationally expensive) are still areas of active research.

References

Choi, Vicky. “Yucca: An Efficient Algorithm for Small-Molecule Docking." Chemistry & Biodiversity 2 (2005): 1517-1524.

Flower, Darren. "Molecular Informatics: Sharpening Drug Design’s Cutting Edge". N.p.: Royal Society of Chemistry, 2002.

Kellenberger, E, et al. “Comparative Evaluation of Eight Docking Tools for Docking and Virtual Screening Accuracy.” Proteins 57.2 (2004): 225-242.

Kuntz, Irwin, et al. “DOCK 6.0 Users Manual.” The Official UCSF DOCK Web-site. July 2006. 12 Nov. 2006 http://dock.compbio.ucsf.edu/DOCK_6/dock6_manual.htm>.

Perun, Thomas J, and C L Propst. "Computer Aided Drug Design". N.p.: Marcel Dekker, Inc, 1989.

Schrödinger. “Glide 4.0 User Manual.” Biowulf. Apr. 2006. Schrödinger. 12 Nov. 2006.


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