Levinthal's paradox is a thought experiment in the field of computational protein structure prediction; protein folding seeks a stable energy configuration. An algorithmic search through all possible conformations to identify the minimum energy configuration (the native state) would take an immense duration, however, in reality, protein folding happens very quickly, even in the case of the most complex structures, suggesting that the transitions are guided into a stable state through an uneven energy landscape. [1]
In 1969, Cyrus Levinthal noted that, because of the very large number of degrees of freedom in an unfolded polypeptide chain, the molecule has an astronomical number of possible conformations. An estimate of 10300 was made in one of his papers [2] (often incorrectly cited as the 1968 paper [3] ). For example, a polypeptide of 100 residues will have 99 peptide bonds, and therefore 198 different phi and psi bond angles. If each of these bond angles can be in one of three stable conformations, the protein may misfold into a maximum of 3198 different conformations (including any possible folding redundancy). Therefore, if a protein were to attain its correctly folded configuration by sequentially sampling all the possible conformations, it would require a time longer than the age of the universe to arrive at its correct native conformation. This is true even if conformations are sampled at rapid (nanosecond or picosecond) rates. The "paradox" is that most small proteins fold spontaneously on a millisecond or even microsecond time scale. The solution to this paradox has been established by computational approaches to protein structure prediction. [4]
Levinthal himself was aware that proteins fold spontaneously and on short timescales. He suggested that the paradox can be resolved if "protein folding is sped up and guided by the rapid formation of local interactions which then determine the further folding of the peptide; this suggests local amino acid sequences which form stable interactions and serve as nucleation points in the folding process". [5] Indeed, the protein folding intermediates and the partially folded transition states were experimentally detected, which explains the fast protein folding. This is also described as protein folding directed within funnel-like energy landscapes. [6] [7] [8] Some computational approaches to protein structure prediction have sought to identify and simulate the mechanism of protein folding. [9]
Levinthal also suggested that the native structure might have a higher energy, if the lowest energy was not kinetically accessible. An analogy is a rock tumbling down a hillside that lodges in a gully rather than reaching the base. [10]
According to Edward Trifonov and Igor Berezovsky, the proteins fold by subunits (modules) of the size of 25–30 amino acids. [11]
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.
Protein design is the rational design of new protein molecules to design novel activity, behavior, or purpose, and to advance basic understanding of protein function. Proteins can be designed from scratch or by making calculated variants of a known protein structure and its sequence. Rational protein design approaches make protein-sequence predictions that will fold to specific structures. These predicted sequences can then be validated experimentally through methods such as peptide synthesis, site-directed mutagenesis, or artificial gene synthesis.
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.
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.
Anfinsen's dogma, also known as the thermodynamic hypothesis, is a postulate in molecular biology. It states that, at least for a small globular protein in its standard physiological environment, the native structure is determined only by the protein's amino acid sequence. The dogma was championed by the Nobel Prize Laureate Christian B. Anfinsen from his research on the folding of ribonuclease A. The postulate amounts to saying that, at the environmental conditions at which folding occurs, the native structure is a unique, stable and kinetically accessible minimum of the free energy. In other words, there are three conditions for formation of a unique protein structure:
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.