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Protein secondary structure is the local spatial conformation of the polypeptide backbone excluding the side chains. The two most common secondary structural elements are alpha helices and beta sheets, though beta turns and omega loops occur as well. Secondary structure elements typically spontaneously form as an intermediate before the protein folds into its three dimensional tertiary structure.
Protein tertiary structure is the three-dimensional shape of a protein. The tertiary structure will have a single polypeptide chain "backbone" with one or more protein secondary structures, the protein domains. Amino acid side chains and the backbone may interact and bond in a number of ways. The interactions and bonds of side chains within a particular protein determine its tertiary structure. The protein tertiary structure is defined by its atomic coordinates. These coordinates may refer either to a protein domain or to the entire tertiary structure. A number of these structures may bind to each other, forming a quaternary structure.
Protein folding is the physical process by which a protein, after synthesis by a ribosome as a linear chain of amino acids, changes from an unstable random coil into a more ordered three-dimensional structure. This structure permits the protein to become biologically functional.
Protein structure prediction is the inference of the three-dimensional structure of a protein from its amino acid sequence—that is, the prediction of its secondary and tertiary structure from primary structure. Structure prediction is different from the inverse problem of protein design. Protein structure prediction is one of the most important goals pursued by computational biology; it is important in medicine and biotechnology.
Structural bioinformatics is the branch of bioinformatics that is related to the analysis and prediction of the three-dimensional structure of biological macromolecules such as proteins, RNA, and DNA. It deals with generalizations about macromolecular 3D structures such as comparisons of overall folds and local motifs, principles of molecular folding, evolution, binding interactions, and structure/function relationships, working both from experimentally solved structures and from computational models. The term structural has the same meaning as in structural biology, and structural bioinformatics can be seen as a part of computational structural biology. The main objective of structural bioinformatics is the creation of new methods of analysing and manipulating biological macromolecular data in order to solve problems in biology and generate new knowledge.
Protein structure is the three-dimensional arrangement of atoms in an amino acid-chain molecule. Proteins are polymers – specifically polypeptides – formed from sequences of amino acids, which are the monomers of the polymer. A single amino acid monomer may also be called a residue, which indicates a repeating unit of a polymer. Proteins form by amino acids undergoing condensation reactions, in which the amino acids lose one water molecule per reaction in order to attach to one another with a peptide bond. By convention, a chain under 30 amino acids is often identified as a peptide, rather than a protein. To be able to perform their biological function, proteins fold into one or more specific spatial conformations driven by a number of non-covalent interactions, such as hydrogen bonding, ionic interactions, Van der Waals forces, and hydrophobic packing. To understand the functions of proteins at a molecular level, it is often necessary to determine their three-dimensional structure. This is the topic of the scientific field of structural biology, which employs techniques such as X-ray crystallography, NMR spectroscopy, cryo-electron microscopy (cryo-EM) and dual polarisation interferometry, to determine the structure of proteins.
Lattice proteins are highly simplified models of protein-like heteropolymer chains on lattice conformational space which are used to investigate protein folding. Simplification in lattice proteins is twofold: each whole residue is modeled as a single "bead" or "point" of a finite set of types, and each residue is restricted to be placed on vertices of a lattice. To guarantee the connectivity of the protein chain, adjacent residues on the backbone must be placed on adjacent vertices of the lattice. Steric constraints are expressed by imposing that no more than one residue can be placed on the same lattice vertex.
Macromolecular docking is the computational modelling of the quaternary structure of complexes formed by two or more interacting biological macromolecules. Protein–protein complexes are the most commonly attempted targets of such modelling, followed by protein–nucleic acid complexes.
In molecular biology, an intrinsically disordered protein (IDP) is a protein that lacks a fixed or ordered three-dimensional structure, typically in the absence of its macromolecular interaction partners, such as other proteins or RNA. IDPs range from fully unstructured to partially structured and include random coil, molten globule-like aggregates, or flexible linkers in large multi-domain proteins. They are sometimes considered as a separate class of proteins along with globular, fibrous and membrane proteins.
Michael Levitt, is a South African-born biophysicist and a professor of structural biology at Stanford University, a position he has held since 1987. Levitt received the 2013 Nobel Prize in Chemistry, together with Martin Karplus and Arieh Warshel, for "the development of multiscale models for complex chemical systems". In 2018, Levitt was a founding co-editor of the Annual Review of Biomedical Data Science.
The folding funnel hypothesis is a specific version of the energy landscape theory of protein folding, which assumes that a protein's native state corresponds to its free energy minimum under the solution conditions usually encountered in cells. Although energy landscapes may be "rough", with many non-native local minima in which partially folded proteins can become trapped, the folding funnel hypothesis assumes that the native state is a deep free energy minimum with steep walls, corresponding to a single well-defined tertiary structure. The term was introduced by Ken A. Dill in a 1987 article discussing the stabilities of globular proteins.
Hydrophobic collapse is a proposed process for the production of the 3-D conformation adopted by polypeptides and other molecules in polar solvents. The theory states that the nascent polypeptide forms initial secondary structure creating localized regions of predominantly hydrophobic residues. The polypeptide interacts with water, thus placing thermodynamic pressures on these regions which then aggregate or "collapse" into a tertiary conformation with a hydrophobic core. Incidentally, polar residues interact favourably with water, thus the solvent-facing surface of the peptide is usually composed of predominantly hydrophilic regions.
Molecular biophysics is a rapidly evolving interdisciplinary area of research that combines concepts in physics, chemistry, engineering, mathematics and biology. It seeks to understand biomolecular systems and explain biological function in terms of molecular structure, structural organization, and dynamic behaviour at various levels of complexity. This discipline covers topics such as the measurement of molecular forces, molecular associations, allosteric interactions, Brownian motion, and cable theory. Additional areas of study can be found on Outline of Biophysics. The discipline has required development of specialized equipment and procedures capable of imaging and manipulating minute living structures, as well as novel experimental approaches.
David Baker is an American biochemist and computational biologist who has pioneered methods to predict and design the three-dimensional structures of proteins. He is the Henrietta and Aubrey Davis Endowed Professor in Biochemistry and an adjunct professor of genome sciences, bioengineering, chemical engineering, computer science, and physics at the University of Washington. He serves as the director of the Rosetta Commons, a consortium of labs and researchers that develop biomolecular structure prediction and design software. The problem of protein structure prediction to which Baker has contributed significantly has now been largely solved by DeepMind using artificial intelligence. Baker is a Howard Hughes Medical Institute investigator and a member of the United States National Academy of Sciences. He is also the director of the University of Washington's Institute for Protein Design.
Helix–coil transition models are formalized techniques in statistical mechanics developed to describe conformations of linear polymers in solution. The models are usually but not exclusively applied to polypeptides as a measure of the relative fraction of the molecule in an alpha helix conformation versus turn or random coil. The main attraction in investigating alpha helix formation is that one encounters many of the features of protein folding but in their simplest version. Most of the helix–coil models contain parameters for the likelihood of helix nucleation from a coil region, and helix propagation along the sequence once nucleated; because polypeptides are directional and have distinct N-terminal and C-terminal ends, propagation parameters may differ in each direction.
In computational biology, de novo protein structure prediction refers to an algorithmic process by which protein tertiary structure is predicted from its amino acid primary sequence. The problem itself has occupied leading scientists for decades while still remaining unsolved. According to Science, the problem remains one of the top 125 outstanding issues in modern science. At present, some of the most successful methods have a reasonable probability of predicting the folds of small, single-domain proteins within 1.5 angstroms over the entire structure.
In molecular biology, a protein domain is a region of a protein's polypeptide chain that is self-stabilizing and that folds independently from the rest. Each domain forms a compact folded three-dimensional structure. Many proteins consist of several domains, and a domain may appear in a variety of different proteins. Molecular evolution uses domains as building blocks and these may be recombined in different arrangements to create proteins with different functions. In general, domains vary in length from between about 50 amino acids up to 250 amino acids in length. The shortest domains, such as zinc fingers, are stabilized by metal ions or disulfide bridges. Domains often form functional units, such as the calcium-binding EF hand domain of calmodulin. Because they are independently stable, domains can be "swapped" by genetic engineering between one protein and another to make chimeric proteins.
A dry lab is a laboratory where the nature of the experiments does not involve significant risk. This is in contrast to a wet lab where it is necessary to handle various types of chemicals and biological hazards. An example of a dry lab is one where computational or applied mathematical analyses are done on a computer-generated model to simulate a phenomenon in the physical realm. Examples of such phenomena include a molecule changing quantum states, the event horizon of a black hole or anything that otherwise might be impossible or too dangerous to observe under normal laboratory conditions. This term may also refer to a lab that uses primarily electronic equipment, for example, a robotics lab. A dry lab can also refer to a laboratory space for the storage of dry materials.
Edward Nikolayevich Trifonov is a Russian-born Israeli molecular biophysicist and a founder of Israeli bioinformatics. In his research, he specializes in the recognition of weak signal patterns in biological sequences and is known for his unorthodox scientific methods.
Ruth Nussinov is an Israeli-American biologist born in Rehovot who works as a Professor in the Department of Human Genetics, School of Medicine at Tel Aviv University and is the Senior Principal Scientist and Principal Investigator at the National Cancer Institute, National Institutes of Health. Nussinov is also the Editor in Chief of the Current Opinion in Structural Biology and formerly of the journal PLOS Computational Biology.
References
- ↑ Nelson, David L.; Cox, Michael M.; Lehninger, Albert L. (2017). "Polypeptides Fold Rapidly by a Stepwise Process". Lehninger principles of biochemistry (7th ed.). New York, NY : Houndmills, Basingstoke: W.H. Freeman and Company ; Macmillan Higher Education. ISBN 978-1-4641-2611-6. OCLC 986827885.
- ↑ Levinthal, Cyrus (1969). "How to Fold Graciously". Mossbauer Spectroscopy in Biological Systems: Proceedings of a Meeting Held at Allerton House, Monticello, Illinois: 22–24. Archived from the original on 2010-10-07.
- ↑ Levinthal, Cyrus (1968). "Are there pathways for protein folding?" (PDF). Journal de Chimie Physique et de Physico-Chimie Biologique. 65: 44–45. Bibcode:1968JCP....65...44L. doi:10.1051/jcp/1968650044. Archived from the original (PDF) on 2009-09-02.
- ↑ Zwanzig R, Szabo A, Bagchi B (1992-01-01). "Levinthal's paradox". Proc Natl Acad Sci USA. 89 (1): 20–22. Bibcode:1992PNAS...89...20Z. doi: 10.1073/pnas.89.1.20 . PMC 48166 . PMID 1729690.
- ↑ Rooman, Marianne Rooman; Yves Dehouck; Jean Marc Kwasigroch; Christophe Biot; Dimitri Gilis (2002). "What is paradoxical about Levinthal Paradox?" (PDF). Journal of Biomolecular Structure and Dynamics. 20 (3): 327–329. doi:10.1080/07391102.2002.10506850. PMID 12437370. S2CID 6839744.[ permanent dead link ]
- ↑ Dill K; H.S. Chan (1997). "From Levinthal to pathways to funnels". Nat. Struct. Biol. 4 (1): 10–19. doi:10.1038/nsb0197-10. PMID 8989315. S2CID 11557990.
- ↑ Durup, Jean (1998). "On "Levinthal paradox" and the theory of protein folding". Journal of Molecular Structure. 424 (1–2): 157–169. doi:10.1016/S0166-1280(97)00238-8.
- ↑ s˘Ali, Andrej; Shakhnovich, Eugene; Karplus, Martin (1994). "How does a protein fold?" (PDF). Nature. 369 (6477): 248–251. Bibcode:1994Natur.369..248S. doi:10.1038/369248a0. PMID 7710478. S2CID 4281915.[ permanent dead link ]
- ↑ Karplus, Martin (1997). "The Levinthal paradox: yesterday and today". Folding & Design. 2 (4): S69–S75. doi: 10.1016/S1359-0278(97)00067-9 . PMID 9269572.
- ↑ Hunter, Philip (2006). "Into the fold". EMBO Rep. 7 (3): 249–252. doi:10.1038/sj.embor.7400655. PMC 1456894 . PMID 16607393.
- ↑ Berezovsky, Igor N.; Trifonov, Edward N. (2002). "Loop fold structure of proteins: Resolution of Levinthal's paradox" (PDF). Journal of Biomolecular Structure & Dynamics. 20 (1): 5–6. doi:10.1080/07391102.2002.10506817. ISSN 0739-1102. PMID 12144347. S2CID 33174198. Archived from the original (PDF) on 2005-02-12.