Protein structure prediction is one of the most significant technologies pursued by computational structural biology and theoretical chemistry. It has the aim of determining the three-dimensional structure of proteins from their amino acid sequences (an example of emergence). In more formal terms, this is expressed as the prediction of protein tertiary structure from primary structure. Given the usefulness of known protein structures in such valuable tasks as rational drug design this is a highly active field of research. Proteins are an important class of biological macromolecules present in all biological organisms, made up of such elements as carbon, hydrogen, nitrogen, oxygen and sulfur. ... Map of the human X chromosome (from the NCBI website). ... Theoretical chemistry is the use of reasoning to explain or predict chemical phenomena. ... A representation of the 3D structure of myoglobin, showing coloured alpha helices. ... Phenylalanine is one of the standard amino acids. ... A termite cathedral mound produced by a termite colony: a classic example of emergence in nature. ... In biochemistry, the tertiary structure of a protein is its overall shape. ... A protein primary structure is a chain of amino acids. ... Drug design is the approach of finding drugs by design, based on what the drug is targeting. ...

Every two years, the performance of current methods is assessed in the CASP experiment. CASP, which stands for Critical Assessment of Techniques for Protein Structure Prediction, is a community-wide experiment (though it is commonly referred to as a competition) for protein structure prediction taking place every two years. ...

Overview

The practical role of protein structure prediction is now more important than ever. Massive amounts of protein sequence data may be derived from modern large-scale DNA sequencing efforts such as the Human Genome Project. Despite community-wide efforts in structural genomics, the output of experimentally determined protein structures — typically by time-consuming and relatively expensive X-ray crystallography or NMR spectroscopy — is lagging far behind the output of protein sequences. The structure of part of a DNA double helix Deoxyribonucleic acid (DNA) is a nucleic acid that contains the genetic instructions for the development and function of living organisms. ... // The Human Genome Project (HGP) is a project to de-code (i. ... Structural genomics or structural bioinformatics refers to the analysis of macromolecular structure particularly proteins. ... X-ray crystallography, also known as single-crystal X-ray diffraction, is the oldest and most common crystallographic method for determining the structure of molecules. ... Pacific Northwest National Laboratorys high magnetic field (800 MHz) NMR spectrometer being loaded with a sample. ...

A number of factors exist that make protein structure prediction a very difficult task, including:

• The number of possible structures that proteins may possess is extremely large
• The physical basis of protein structural stability is not fully understood.
• The tertiary structure of a native protein may not be readily formed without the aid of trans-acting factors. For example, proteins known as chaperones are required for some proteins to properly fold; other proteins cannot fold properly without modifications such as glycosylation.
• A particular sequence may be able to assume multiple conformations depending on its environment, and the biologically active conformation may not be the most thermodynamically favorable.
• Direct simulation of protein folding via methods such as molecular dynamics is not tractable for both practical and theoretical reasons except in very small proteins, despite the efforts of distributed computing projects such as Folding@home.

Due to exponentially improving computer power, and new algorithms, much progress is being made to overcome these factors by the many research groups that are interested in the task. Prediction of structures for small proteins is now a perfectly realistic goal. A wide range of approaches are routinely applied for such predictions. These approaches may be classified into two broad classes; ab initio modelling and comparative modelling. Trans is a Latin noun or prefix, meaning across, beyond or on the opposite side [of] . It is the opposite of cis, which means on the same side [of]. In chemistry, a double bond (or ring) not subject to free rotation in which the greater radical on both ends is... In biology, chaperones are proteins whose function is to assist other proteins in achieving proper folding. ... Glycosylation is the process or result of addition of saccharides to proteins and lipids. ... Thermodynamics (from the Greek θερμη, therme, meaning heat and δυναμις, dunamis, meaning power) is a branch of physics that studies the effects of changes in temperature, pressure, and volume on physical systems at the macroscopic scale by analyzing the collective motion of their particles using statistics. ... Protein folding is the process by which a protein assumes its characteristic functional shape or tertiary structure, also known as the native state. ... Molecular dynamics (MD) is a form of computer simulation where atoms and molecules are allowed to interact for a period of time under known laws of physics. ... Folding@home (also known as FAH or F@H) is a distributed computing project designed to perform computationally intensive simulations of protein folding and other molecular dynamics simulations. ... Ab Initio Software Corporation was founded in the mid 1990s by the former CEO, Sheryl Handler, and several other former employees of Thinking Machines Corporation, after the bankruptcy of that company. ...

Ab initio protein modelling

Ab initio- or de novo- protein modelling methods seek to build three-dimensional protein models "from scratch", i.e., based on physical principles rather than (directly) on previously solved structures. There are many possible procedures that either attempt to mimic protein folding or apply some stochastic method to search possible solutions (i.e., global optimization of a suitable energy function). These procedures tend to require vast computational resources, and have thus only been carried out for tiny proteins. To attempt to predict protein structure de novo for larger proteins, we will need better algorithms and larger computational resources like those afforded by either powerful supercomputers (such as Blue Gene or MDGRAPE-3) or distributed computing (such as Folding@home, the Human Proteome Folding Project and Rosetta@Home). Although these computational barriers are vast, the potential benefits of structural genomics (by predicted or experimental methods) make ab initio structure prediction an active research field. In general usage, de novo is a Latin expression meaning afresh, anew, beginning again. In Banking, a de novo bank is defined as a state member bank that has been in operation for five years or less. ... Protein folding is the process by which a protein assumes its characteristic functional shape or tertiary structure, also known as the native state. ... Stochastic, from the Greek stochos or goal, means of, relating to, or characterized by conjecture; conjectural; random. ... Global optimization is a branch of applied mathematics and numerical analysis that deals with the optimization of a function or a set of functions to some criteria. ... A BlueGene/L cabinet Blue Gene is a computer architecture project designed to produce several next-generation supercomputers, designed to reach operating speeds in the petaflops range, and currently reaching sustained speeds over 360 teraflops. ... MDGrape 3 is a high peformance computer processor being developed by RIKEN in Japan. ... Folding@home (also known as FAH or F@H) is a distributed computing project designed to perform computationally intensive simulations of protein folding and other molecular dynamics simulations. ... The World Community Grid is an effort to create the worlds largest public computing grid to tackle projects that benefit humanity. ... Rosetta@home (website) is a distributed computing project, run by the Baker Laboratory at the University of Washington, aiming to solve the protein structure prediction problem. ...

Comparative protein modelling

Comparative protein modelling uses previously solved structures as starting points, or templates. This is effective because it appears that although the number of actual proteins is vast, there is a limited set of tertiary structural motifs to which most proteins belong. It has been suggested that there are only around 2000 distinct protein folds in nature, though there are many millions of different proteins. In biochemistry, the tertiary structure of a protein is its overall shape. ... It has been suggested that Supersecondary structure be merged into this article or section. ...

These methods may also be split into two groups:

• Homology modelling is based on the reasonable assumption that two homologous proteins will share very similar structures. Because a protein's fold is more evolutionarily conserved than its amino acid sequence, a target sequence can be modeled with reasonable accuracy on a very distantly related template, provided that the relationship between target and template can be discerned through sequence alignment. It has been suggested that the primary bottleneck in comparative modelling arises from difficulties in alignment rather than from errors in structure prediction given a known-good alignment.^[1] Unsurprisingly, homology modelling is most accurate when the target and template have similar sequences.

• Protein threading^[2] scans the amino acid sequence of an unknown structure against a database of solved structures. In each case, a scoring function is used to assess the compatibility of the sequence to the structure, thus yielding possible three-dimensional models. This type of method is also known as 3D-1D fold recognition due to its compatibility analysis between three-dimensional structures and linear protein sequences. This method has also given rise to methods performing an inverse folding search by evaluating the compatibility of a given structure with a large database of sequences, thus predicting which sequences have the potential to produce a given fold.

Protein structure prediction is one of the most significant tasks tackled in computational structural biology. ... In biology, homology is any similarity between structures that is due to their shared ancestry. ... In bioinformatics, a sequence alignment is a way of arranging the primary sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences. ... Protein structure prediction is one of the most significant tasks tackled in computational structural biology. ...

Side chain geometry prediction

Even structure prediction methods that are reasonably accurate for the peptide backbone often get the orientation and packing of the amino acid side chains wrong. Methods that specifically address the problem of predicting side chain geometry include dead-end elimination and the self-consistent mean field method. Both discretize the continuously varying dihedral angles that determine a side chain's orientation relative to the backbone into a set of rotamers with fixed dihedral angles. The methods then attempt to identify the set of rotamers that minimize the model's overall energy. Rotamers are the side chain conformations with low energy. Such methods are most useful for analyzing the protein's hydrophobic core, where side chains are more closely packed; they have more difficulty addressing the looser constraints and higher flexibility of surface residues.^[3] The term Side chain can have different meanings depending on the context: In chemistry and biochemistry a side chain is a part of a molecule attached to a core structure. ... The dead-end elimination algorithm (DEE) is a method for minimizing a function over a discrete set of independent variables. ... The self-consistent mean field (SCMF) method is an adaptation of mean field theory used in protein structure prediction to determine the optimal amino acid side chain packing given a fixed protein backbone. ... In Aerospace engineering, the dihedral is the angle that the two wings make with each other. ... In chemistry, a chemical conformation is the spatial arrangement of atoms in a molecule. ... In chemistry, hydrophobic or lipophilic species, or hydrophobes, tend to be electrically neutral and nonpolar, and thus prefer other neutral and nonpolar solvents or molecular environments. ...

Software

MODELLER is a popular software tool for producing homology models using methodology derived from NMR spectroscopy data processing. SwissModel provides an automated web server for basic homology modeling. A common software tool for protein threading is 3D-PSSM. The basic algorithm for threading is described in^[2] and is fairly straightforward to implement. Pacific Northwest National Laboratorys high magnetic field (800 MHz) NMR spectrometer being loaded with a sample. ...

TIP is a knowledgebase of STRUCTFAST^[4] models and precomputed similarity relationships between sequences, structures, and binding sites.

A very recent review of currently popular software for structure prediction can be found at.^[5] A partial list of web servers and available tools is maintained here.

Several distributed computing projects concerning protein structure prediction have also been implemented, such as the Folding@home, Rosetta@home, Human Proteome Folding Project, Predictor@home and TANPAKU. Distributed computing is a method of computer processing in which different parts of a program run simultaneously on two or more computers that are communicating with each other over a network. ... Folding@home (also known as FAH or F@H) is a distributed computing project designed to perform computationally intensive simulations of protein folding and other molecular dynamics simulations. ... Rosetta@home (website) is a distributed computing project, run by the Baker Laboratory at the University of Washington, aiming to solve the protein structure prediction problem. ... The World Community Grid is an effort to create the worlds largest public computing grid to tackle projects that benefit humanity. ... Predictor@home is a distributed computing project that uses BOINC and is run by the Scripps Research Institute to predict protein structure from protein sequence in the context of the 6th biannual CASP, or Critical Assessment of Techniques for Protein Structure Prediction. ... A BOINC distributed computing project TANPAKU is a distributed computing project aimed at attacking the protein structure prediction problem. ...

Protein-protein complexes

In the case of complexes of two or more proteins, where the structures of the proteins are known or can be predicted with high accuracy, protein-protein docking methods can be used to predict the structure of the complex. Information of the effect of mutations at specific sites on the affinity of the complex helps to understand the complex structure and to guide docking methods. A protein complex is a group of two or more associated proteins formed by protein-protein interaction that is stable over time. ... Protein-protein docking is the determination of the molecular structure of complexes formed by two or more proteins without the need for experimental measurement. ...

See also

• Protein structure prediction software
• Protein-protein interaction prediction

This list of protein structure prediction software summarizes commonly used software tools in protein structure prediction, including homology modeling, protein threading, ab initio methods, and secondary structure prediction. ... This article is being considered for deletion in accordance with Wikipedias deletion policy. ...

References

1. ^ Zhang Y and Skolnick J (2005). "The protein structure prediction problem could be solved using the current PDB library". Proc Natl Acad Sci USA 102 (4): 1029-1034. Entrez PubMed 15653774. 
2. ^ ^{a b} Bowie JU, Luthy R, Eisenberg D (1991). "A method to identify protein sequences that fold into a known three-dimensional structure". Science 253 (5016): 164-170. Entrez PubMed 1853201. 
3. ^ Voigt CA, Gordon DB, Mayo SL (2000). "Trading accuracy for speed: A quantitative comparison of search algorithms in protein sequence design". J Mol Biol 299 (3): 789-803. Entrez PubMed 10835284. 
4. ^ Debe DA, Danzer JF, Goddard WA, Poleksic A (2006). "STRUCTFAST: Protein sequence remote homology detection and alignment using novel dynamic programming and profile-profile scoring". Proteins 64: 960-967. Entrez PubMed 16786595. 
5. ^ Nayeem A, Sitkoff D, Krystek S Jr (2006). "A comparative study of available software for high-accuracy homology modeling: From sequence alignments to structural models". Protein Sci 15: 808-824. Entrez PubMed 16600967. 

The Entrez logo The Entrez Global Query Cross-Database Search System allows access to databases at the National Center for Biotechnology Information (NCBI) website. ... The Entrez logo The Entrez Global Query Cross-Database Search System allows access to databases at the National Center for Biotechnology Information (NCBI) website. ... The Entrez logo The Entrez Global Query Cross-Database Search System allows access to databases at the National Center for Biotechnology Information (NCBI) website. ... The Entrez logo The Entrez Global Query Cross-Database Search System allows access to databases at the National Center for Biotechnology Information (NCBI) website. ... The Entrez logo The Entrez Global Query Cross-Database Search System allows access to databases at the National Center for Biotechnology Information (NCBI) website. ...

Further reading

• Bonneau R, Baliga NS, Deutsch EW, Shannon P, Hood L (2004). "Comprehensive de novo structure prediction in a systems-biology context for the archaea Halobacterium sp. NRC-1". Genome Biology, 5(8):R52-68.