Protein computational tools

Sotriffer C, Klebe G. 2002. Identification and mapping of smaU-molecule binding sites in proteins computational tools for structure-based drug design. Farmaco 57(3) 243-251. 

In computational chemistry it can be very useful to have a generic model that you can apply to any situation. Even if less accurate, such a computational tool is very useful for comparing results between molecules and certainly lowers the level of pain in using a model from one that almost always fails. The MM+ force field is meant to apply to general organic chemistry more than the other force fields of HyperChem, which really focus on proteins and nucleic acids. HyperChem includes a default scheme such that when MM+ fails to find a force constant (more generally, force field parameter), HyperChem substitutes a default value. This occurs universally with the periodic table so all conceivable molecules will allow computations. Whether or not the results of such a calculation are realistic can only be determined by close examination of the default parameters and the particular molecular situation. ... 

The overall scope of this book is the implementation and application of available theoretical and computational methods toward understanding the structure, dynamics, and function of biological molecules, namely proteins, nucleic acids, carbohydrates, and membranes. The large number of computational tools already available in computational chemistry preclude covering all topics, as Schleyer et al. are doing in The Encyclopedia of Computational Chemistry [23]. Instead, we have attempted to create a book that covers currently available theoretical methods applicable to biomolecular research along with the appropriate computational applications. We have designed it to focus on the area of biomolecular computations with emphasis on the special requirements associated with the treatment of macromolecules. 

Ivanciuc, O., Schein, C.H. and Braun, W., SDAP Database and computational tools for allergenic proteins. Nucleic Acids Res., 31, 359, 2003. 

Knowledge of the pKa value is crucial for analyzing both lipophilicity and solubility of ionizable compounds, as discussed above. Ionization equilibria also affect several toxicokinetic parameters, such as intestinal absorption, membrane permeability, protein binding, and metabolic transformations. Therefore, much research has been invested in developing both experimental and computational tools for pKa determination. Experimentally, two high-throughput methods exist spectral gradient analysis and capillary electrophoresis. However, the most definitive methods are still... 

The application of the primary databases and structural analytical tools will be introduced using a protein from a future experiment. In Experiment 4, you will extract, purify, and characterize a-lactalbumin from bovine milk. To prepare for this activity, here you will learn about the structure of a related protein, a-lactalbumin from humans. We will search databases to find and view its primary and secondary structure and also determine if there are other proteins with a similar amino acid sequence and structure. After completion of these exercises, you will be able to apply these computer tools to proteins of your own choice. 

A number of useful computational tools have been developed for predicting the identity of unknown proteins based on the physical and chemical properties of amino acids and vice versa. Many of these tools are available through the Expert Protein Analysis System (ExPASy) at http //www.expasy.ch (Appel et al., 1994) and other servers. 

Bryson CJ, fones TD, Baker MP (2010) Prediction of immunogenicity of therapeutic proteins validity of computational tools. BioDrugs 24 1-8... 

Considering the generally poor ability of prediction methods, including those that are based on GAs, to provide accurate predictions based on sequence alone, the next studies [51-53] explored the possibility of including experimental data in the prediction scheme. In Ref. [51], distance constraints derived from NMR experiments were used to calculate the three-dimensional structure of proteins with the help of a GA for structure refinement. In this case, of course, the method is not a prediction scheme, but rather is used as a computational tool, like distance geometry algorithms, to identify a structure or structures which are compatible with the distance constraints. 

Improbability of docked binding mode. Fast docking tools cannot produce reasonable solutions for all compounds. Often even some high-scoring compounds are found to be docked to the outer surface of the protein. Computational filters help to detect such situations. 

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