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Protein Structure Prediction

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Book cover Biomedical Applications of Biophysics

Part of the book series: Handbook of Modern Biophysics ((HBBT,volume 3))

Abstract

The molecular basis of life rests on the activity of large biomolecules, mostly nucleic acids(DNA and RNA), carbohydrates, lipids, and proteins. While each of these molecules has itsrole, there is something special about proteins, as they are the lead performers of cellular functions.This was dramatized by Jacques Monod, who stated that “C’est à ce niveau d’ organisation chimique que gît, s’il y en a un, le secret de la vie,” i.e., that it is at this level of organization that lies the secret of life, if there is one [1]. To understand how these molecules function we first need to know their shapes; consequently, structural molecular biology has emerged as a new line of experimental research focused on revealing the structure of these biomolecules. This branch of biology has recently experienced a major uplift through the development of highthroughput structural studies, the structural genomics projects, aimed atdeveloping a comprehensive view of the protein structure universe. All these initiatives are expected to help us unravel the connections between the sequence, structure, and function of a protein. Experimental data at a molecular level are scarce, however; this has led to the development of many modeling initiatives to shed light on these connections. Probably the most famous is the study of the protein-folding problem — the “holy grail” for the structural biology community. Its elusive goal is to predict the detailed three-dimensional structure of a protein from its sequence as well as to decipher the sequence of events the protein goes through to reach its folded state. This chapter is dedicated to the first part of this task, namely the protein structure prediction problem. We structure prediction problem benefit from two different approaches to science, which differ in the importance they give to experimental data.

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Authors and Affiliations

  1. Department of Computer Science and Genome Center, University of California, Davis, One Shields Avenue, Davis, 95616, USA

    Patrice Koehl

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  1. Patrice Koehl
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  1. Department of Biochemistry and Molecular Medicine, University of California Davis, One Shields Avenue, Davis, CA, 95616, USA

    Thomas Jue Ph.D.

1.1 Electronic Supplementary material

Figure 1.1.

Amino acids: the building blocks of proteins. (A) Each amino acid has a mainchain (N, Cα, C, and O) on which is attached a sidechain schematically represented as R. The mainchain can itself be partitioned into three groups: the amino group, the central Cα group, and the carboxyl group. Note that even though the amino group and the carboxyl group are charged at neutral pH, the amino acid is neutral: we say that it is a zwitterion. (B) Amino acids in proteins are attached through planar peptide bonds, connecting atom C of the current residue to atom N of the following residue. Please visit http://extras.springer.com/ to view a high-resolution full-color version of this illustration. (PDF 2,785 KB)

Figure 1.2.

The three most common arrangements of secondary structure elements (SSE) found in proteins. (A) The regular α–helix is a right–handed helix, in which all residues adopt similar conformations. The α–helix is characterized by hydrogen bonds between the oxygen O of residue i, and the polar backbone hydrogen HN (bound to N) of residue i + 4. Note that all C=O and N–HN bonds are parallel to the main axis of the helix. (B) An anti-parallel β–sheet. Two strands (stretches of extended backbone segments) are running in an anti-parallel geometry. The atoms HN and O of residue i in the first strand hydrogen bond with the atoms O and HN of residue j in the opposite strand, respectively, while residues i + 1 and j + 1 face outward. (C) A parallel β–sheet. The two strands are parallel, and the atoms HN and O of residue i in the first strand hydrogen bond with the O of residue j and the HN of residue j + 2, respectively. The same alternating pattern of residues involved in hydrogen bonds with the opposite strand, and facing outward is observed in parallel and anti-parallel β–sheets. A strand can therefore be involved in two different sheets. For simplicity, sidechains and non-polar hydrogens are ignored. Figure drawn using Pymol (http://www.pymol.org). Please visit http://extras.springer.com/ to view a high-resolution full-color version of this illustration. (PDF 2,783 KB)

Figure 1.3.

The three main types of proteins. (A) Collagen is the main protein of connective tissues in animals and the most abundant protein in mammals, making up close to 30% of their body protein content. It is a fiber protein, with each fiber made up of three polypeptide strands possessing the conformation of left-handed helices. These three left-handed helices are twisted together into a right-handed coiled coil, a cooperative quaternary structure stabilized by numerous hydrogen bonds. (B) Bacteriorhodopsin is a mainly α–protein, containing seven helices, that crosses the membrane of a cell (a few lipids of the membrane are shown as a space-filling diagram in green). It serves as an ion pump, and is found in bacteria that can survive in high salt concentrations. (C) TIM is a globular protein that belongs to the α–β class. The protein chain alternates between β and α secondary structure type, giving rise to a barrel β–sheet in the center surrounded by a large ring of α-helix on the outside. This structure, first seen in the triose phosphate isomerase of chicken, has been observed in many unrelated proteins since then. Figure drawn using Pymol (http://www.pymol.org). Please visit http://extras.springer.com/ to view a high-resolution full-color version of this illustration. (PDF 2,792 KB)

Figure 1.7.

A self-consistent mean field (SCMF) approach to the problem of predicting sidechain conformation. (A) The multicopy approach. Let us assume that residue i in the protein of interest is a phenylalanine, and that this phenylalanine can adopt three possible conformations. A systematic enumeration of all possible sidechain conformations in the protein would require that all three conformations of phenylalanine i be considered. If the protein contains 100 residues, each with three possible conformations, the size of the corresponding conformational space is 3100, a number out of reach of modern computers. As an alternative, we construct a chimera molecule, where sidechains are represented as an ensemble of discrete conformation: phenylalanine i is now represented with 3 conformations, each with a weight P(i,j), such that the sum of the weights is 1. (B,C) The mean field. The chimera molecule considered contains all conformations of all sidechains in the proteins. The energy of conformation k for residue i includes the internal energy for conformation k, the energy of interaction of conformation k for i with the backbone, and all interactions with all conformations of the remaining sidechains of the protein, each weighted with their probabilities. (D) Updating the probabilities. The initial probabilities are chosen to be uniform. Using the equations given in (C) we get the energies of all conformations of all residues in the chimera protein. These energies are then used to update the probabilities of these conformations. We have shown that updating the probabilities using a Boltzmann law is equivalent to minimizing the total free energy of the chimera molecule [97]. The new probabilities are then used to compute new energies; this procedure is repeated until we reach convergence (“self-consistency”), i.e., when the probabilities and energies do not change anymore. For each residue, we choose the conformation with the resolution full-color version of this illustration. highest converged probability as its predicted conformation. Please visit http://extras.springer.com/ to view a high resolution full-color version of this illustration. (PDF 2,802 KB)

Figure 1.8.

Lattice model of a protein structure. The figure depicts an example of a compact selfavoiding structure of a protein chain of 27 “residues” on a regular cubic lattice. This structure contains 28 contacts between non-sequential residues (shown as dashed line). The total energy of this conformation is the sum of the energies over these contacts. Please visit http://extras.springer.com/ to view a high resolution full-color version of this illustration. (PDF 2,789 KB)

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Koehl, P. (2010). Protein Structure Prediction. In: Jue, T. (eds) Biomedical Applications of Biophysics. Handbook of Modern Biophysics, vol 3. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60327-233-9_1

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