Editing Protein (section)

==Methods of study==

{{Main|Protein methods}}

Methods commonly used to study protein structure and function include [[immunohistochemistry]], [[site-directed mutagenesis]], [[X-ray crystallography]], [[nuclear magnetic resonance]] and [[mass spectrometry]]. The activities and structures of proteins may be examined ''[[in vitro]],'' ''[[in vivo]], and [[in silico]]''. '''''In vitro''''' studies of purified proteins in controlled environments are useful for learning how a protein carries out its function:<ref>{{Citation |title=Experimental Animal and In Vitro Study Designs |vauthors=((National Research Council (US) Subcommittee on Reproductive and Developmental Toxicity)) |date=2001 |work=Evaluating Chemical and Other Agent Exposures for Reproductive and Developmental Toxicity |url=https://www.ncbi.nlm.nih.gov/books/NBK222201/ |access-date=2024-12-23 |publisher=National Academies Press}}</ref> for example, [[enzyme kinetics]] studies explore the [[reaction mechanism|chemical mechanism]] of an enzyme's catalytic activity and its relative affinity for various possible substrate molecules.<ref>{{Cite journal |last1=Ricard |first1=Jacques |last2=Cornish-Bowden |first2=Athel |date=July 1987 |title=Co-operative and allosteric enzymes: 20 years on |url=https://onlinelibrary.wiley.com/doi/10.1111/j.1432-1033.1987.tb13510.x |journal=European Journal of Biochemistry |volume=166 |issue=2 |pages=255–272 |doi=10.1111/j.1432-1033.1987.tb13510.x|pmid=3301336 }}</ref> By contrast, '''''in vivo''''' experiments can provide information about the physiological role of a protein in the context of a [[Cell biology|cell]] or even a whole [[organism]], and can often provide more information about protein behavior in different contexts.<ref>{{Cite journal |last1=Lipinski |first1=Christopher |last2=Hopkins |first2=Andrew |date=December 2004 |title=Navigating chemical space for biology and medicine |url=https://www.nature.com/articles/nature03193 |journal=Nature |volume=432 |issue=7019 |pages=855–861 |doi=10.1038/nature03193|pmid=15602551 |bibcode=2004Natur.432..855L }}</ref> '''''In silico''''' studies use computational methods to study proteins.<ref>{{Cite journal |last1=Danchin |first1=A. |last2=Médigue |first2=C. |last3=Gascuel |first3=O. |last4=Soldano |first4=H. |last5=Hénaut |first5=A. |date=1991 |title=From data banks to data bases |url=https://linkinghub.elsevier.com/retrieve/pii/092325089190073J |journal=Research in Microbiology |volume=142 |issue=7–8 |pages=913–916 |doi=10.1016/0923-2508(91)90073-J|pmid=1784830 }}</ref>

===Protein purification===

{{Main|Protein purification}}

Proteins may be [[protein purification|purified]] from other cellular components using a variety of techniques such as [[ultracentrifugation]], [[Precipitation (chemistry)|precipitation]], [[electrophoresis]], and [[chromatography]];<ref name = "Murray_2006" />{{rp|21–24}} the advent of [[genetic engineering]] has made possible a number of methods to facilitate purification.<ref name=Terpe2003/>

To perform ''[[in vitro]]'' analysis, a protein must be purified away from other cellular components. This process usually begins with [[cytolysis|cell lysis]], in which a cell's membrane is disrupted and its internal contents released into a solution known as a [[crude lysate]]. The resulting mixture can be purified using [[ultracentrifugation]], which fractionates the various cellular components into fractions containing soluble proteins; membrane [[lipid]]s and proteins; cellular [[organelle]]s, and [[nucleic acid]]s. [[Precipitation (chemistry)|Precipitation]] by a method known as [[salting out]] can concentrate the proteins from this lysate. Various types of [[chromatography]] are then used to isolate the protein or proteins of interest based on properties such as molecular weight, net charge and binding affinity.<ref name = "Murray_2006" />{{rp|21–24}} The level of purification can be monitored using various types of [[gel electrophoresis]] if the desired protein's molecular weight and [[isoelectric point]] are known, by [[spectroscopy]] if the protein has distinguishable spectroscopic features, or by [[enzyme assay]]s if the protein has enzymatic activity. Additionally, proteins can be isolated according to their charge using [[electrofocusing]].<ref name=Hey2008/>

For natural proteins, a series of purification steps may be necessary to obtain protein sufficiently pure for laboratory applications. To simplify this process, [[genetic engineering]] is often used to add chemical features to proteins that make them easier to purify without affecting their structure or activity. Here, a "tag" consisting of a specific amino acid sequence, often a series of [[histidine]] residues (a "[[His-tag]]"), is attached to one terminus of the protein. As a result, when the lysate is passed over a chromatography column containing [[nickel]], the histidine residues ligate the nickel and attach to the column while the untagged components of the lysate pass unimpeded. A number of tags have been developed to help researchers purify specific proteins from complex mixtures.<ref name=Terpe2003/>

===Cellular localization===

[[File:Localisations02eng.jpg|thumb|right|upright=1.35|Proteins in various [[cellular compartment]]s and structures tagged with [[green fluorescent protein]] (here, white)]]

The study of proteins ''in vivo'' is often concerned with the synthesis and localization of the protein within the cell. Although many intracellular proteins are synthesized in the [[cytoplasm]] and membrane-bound or secreted proteins in the [[endoplasmic reticulum]], the specifics of how proteins are [[protein targeting|targeted]] to specific organelles or cellular structures is often unclear. A useful technique for assessing cellular localization uses genetic engineering to express in a cell a [[fusion protein]] or [[chimera (protein)|chimera]] consisting of the natural protein of interest linked to a "[[reporter gene|reporter]]" such as [[green fluorescent protein]] (GFP).<ref name=Stepanenko2008/> The fused protein's position within the cell can then be cleanly and efficiently visualized using [[microscopy]].<ref name=Yuste2005/>

Other methods for elucidating the cellular location of proteins requires the use of known compartmental markers for regions such as the ER, the Golgi, lysosomes or vacuoles, mitochondria, chloroplasts, plasma membrane, etc. With the use of fluorescently tagged versions of these markers or of antibodies to known markers, it becomes much simpler to identify the localization of a protein of interest. For example, [[indirect immunofluorescence]] will allow for fluorescence colocalization and demonstration of location. Fluorescent dyes are used to label cellular compartments for a similar purpose.<ref name=Margolin2000/>

Other possibilities exist, as well. For example, [[immunohistochemistry]] usually uses an antibody to one or more proteins of interest that are conjugated to enzymes yielding either luminescent or chromogenic signals that can be compared between samples, allowing for localization information.<ref>{{Cite web |last=Hrycaj |first=Steven |date=17 October 2023 |title=Immunohistochemistry: Origins, Tips, and a Look to the Future |url=https://www.the-scientist.com/immunohistochemistry-origins-tips-and-a-look-to-the-future-71439 |access-date=2024-12-22 |website=The Scientist Magazine}}</ref> Another applicable technique is cofractionation in sucrose (or other material) gradients using [[isopycnic centrifugation]].<ref name=Walker2000/> While this technique does not prove colocalization of a compartment of known density and the protein of interest, it indicates an increased likelihood.<ref name=Walker2000/>

Finally, the gold-standard method of cellular localization is [[immunoelectron microscopy]]. This technique uses an antibody to the protein of interest, along with classical electron microscopy techniques. The sample is prepared for normal electron microscopic examination, and then treated with an antibody to the protein of interest that is conjugated to an extremely electro-dense material, usually gold. This allows for the localization of both ultrastructural details as well as the protein of interest.<ref name=Mayhew2008/>

Through another genetic engineering application known as [[site-directed mutagenesis]], researchers can alter the protein sequence and hence its structure, cellular localization, and susceptibility to regulation. This technique even allows the incorporation of unnatural amino acids into proteins, using modified tRNAs,<ref name=Hohsaka2002/> and may allow the rational [[protein design|design]] of new proteins with novel properties.<ref name=Cedrone2000/>

===Proteomics===

{{Main|Proteomics}}

The total complement of proteins present at a time in a cell or cell type is known as its [[proteome]], and the study of such large-scale data sets defines the field of [[proteomics]], named by analogy to the related field of [[genomics]]. Key experimental techniques in proteomics include [[Two-dimensional gel electrophoresis|2D electrophoresis]],<ref name=Gorg2008/> which allows the separation of many proteins, [[mass spectrometry]],<ref name=Conrotto2008/> which allows rapid high-throughput identification of proteins and sequencing of peptides (most often after [[in-gel digestion]]), [[protein microarray]]s, which allow the detection of the relative levels of the various proteins present in a cell, and [[two-hybrid screening]], which allows the systematic exploration of [[protein–protein interaction]]s.<ref name=Koegl2007/> The total complement of biologically possible such interactions is known as the [[interactome]].<ref name=Plewczynski2009/> A systematic attempt to determine the structures of proteins representing every possible fold is known as [[structural genomics]].<ref name=Zhang2003/>

===Structure determination===

Discovering the tertiary structure of a protein, or the quaternary structure of its complexes, can provide important clues about how the protein performs its function and how it can be affected, i.e. in [[Drug design#Structure-based|drug design]]. As proteins are [[Diffraction-limited system|too small to be seen]] under a [[Optical microscope|light microscope]], other methods have to be employed to determine their structure. Common experimental methods include [[X-ray crystallography]] and [[protein NMR|NMR spectroscopy]], both of which can produce structural information at [[atom]]ic resolution. However, NMR experiments are able to provide information from which a subset of distances between pairs of atoms can be estimated, and the final possible conformations for a protein are determined by solving a [[distance geometry]] problem. [[Dual polarisation interferometry]] is a quantitative analytical method for measuring the overall [[protein conformation]] and [[conformational change]]s due to interactions or other stimulus. [[Circular dichroism]] is another laboratory technique for determining internal β-sheet / α-helical composition of proteins. [[Cryoelectron microscopy]] is used to produce lower-resolution structural information about very large protein complexes, including assembled [[virus]]es;<ref name = "Brandon_1999" />{{rp|340–41}} a variant known as [[electron crystallography]] can produce high-resolution information in some cases, especially for two-dimensional crystals of membrane proteins.<ref name=Gonen2005/> Solved structures are usually deposited in the [[Protein Data Bank]] (PDB), a freely available resource from which structural data about thousands of proteins can be obtained in the form of [[Cartesian coordinates]] for each atom in the protein.<ref name=Standley2008/>

Many more gene sequences are known than protein structures. Further, the set of solved structures is biased toward proteins that can be easily subjected to the conditions required in [[X-ray crystallography]], one of the major structure determination methods. In particular, globular proteins are comparatively easy to [[crystallize]] in preparation for X-ray crystallography. Membrane proteins and large protein complexes, by contrast, are difficult to crystallize and are underrepresented in the PDB.<ref name=Walian2004/> [[Structural genomics]] initiatives have attempted to remedy these deficiencies by systematically solving representative structures of major fold classes. [[Protein structure prediction]] methods attempt to provide a means of generating a plausible structure for proteins whose structures have not been experimentally determined.<ref name=Sleator2012/>

===Structure prediction===

[[File:225 Peptide Bond-01.jpg|thumb|right|upright=1.6|Constituent amino-acids can be analyzed to predict secondary, tertiary and quaternary protein structure, in this case hemoglobin containing [[heme]] units]]

{{Main|Protein structure prediction|List of protein structure prediction software}}

Complementary to the field of structural genomics, ''protein structure prediction'' develops efficient [[mathematical model]]s of proteins to computationally predict the molecular formations in theory, instead of detecting structures with laboratory observation.<ref name=Zhang2008/> The most successful type of structure prediction, known as [[homology modeling]], relies on the existence of a "template" structure with sequence similarity to the protein being modeled; structural genomics' goal is to provide sufficient representation in solved structures to model most of those that remain.<ref name=Xiang2006/> Although producing accurate models remains a challenge when only distantly related template structures are available, it has been suggested that [[sequence alignment]] is the bottleneck in this process, as quite accurate models can be produced if a "perfect" sequence alignment is known.<ref name=Zhang2005/> Many structure prediction methods have served to inform the emerging field of [[protein engineering]], in which novel protein folds have already been designed.<ref name=Kuhlman2003/> Many proteins (in eukaryotes ~33%) contain large unstructured but biologically functional segments and can be classified as [[intrinsically disordered proteins]]. Predicting and analysing protein disorder is an important part of protein structure characterisation.<ref>{{cite journal | vauthors = Ward JJ, Sodhi JS, McGuffin LJ, Buxton BF, Jones DT | title = Prediction and functional analysis of native disorder in proteins from the three kingdoms of life | journal = Journal of Molecular Biology | volume = 337 | issue = 3 | pages = 635–645 | date = March 2004 | pmid = 15019783 | doi = 10.1016/j.jmb.2004.02.002 | citeseerx = 10.1.1.120.5605 }}</ref>

===In silico simulation of dynamical processes===

A more complex computational problem is the prediction of intermolecular interactions, such as in [[docking (molecular)|molecular docking]],<ref name=Ritchie2008/> [[protein folding]], [[protein–protein interaction]] and chemical reactivity. Mathematical models to simulate these dynamical processes involve [[molecular mechanics]], in particular, [[molecular dynamics]]. In this regard, ''[[in silico]]'' simulations discovered the folding of small α-helical [[protein domain]]s such as the [[villin]] headpiece,<ref name=Zagrovic2002/> the [[HIV]] accessory protein<ref name=Herges2005/> and hybrid methods combining standard molecular dynamics with [[quantum mechanics|quantum mechanical]] mathematics have explored the electronic states of [[rhodopsin]]s.<ref name=Hoffman2006/>

Beyond classical molecular dynamics, [[quantum dynamics]] methods allow the simulation of proteins in atomistic detail with an accurate description of quantum mechanical effects. Examples include the multi-layer [[multi-configuration time-dependent Hartree ]] method and the [[hierarchical equations of motion]] approach, which have been applied to plant cryptochromes<ref name= Gatti2018/> and bacteria light-harvesting complexes,<ref name= Schulten2012/> respectively. Both quantum and classical mechanical simulations of biological-scale systems are extremely computationally demanding, so [[distributed computing]] initiatives such as the [[Folding@home]] project facilitate the [[molecular modeling on GPU|molecular modeling]] by exploiting advances in [[Graphics processing unit|GPU]] parallel processing and [[Monte Carlo method|Monte Carlo]] techniques.<ref name=Scheraga2007/><ref name="Zheng Javidpour 2020">{{cite journal |last1=Zheng |first1=Size |last2=Javidpour |first2=Leili |last3=Sahimi |first3=Muhammad |last4=Shing |first4=Katherine S. |last5=Nakano |first5=Aiichiro |title=sDMD: An open source program for discontinuous molecular dynamics simulation of protein folding and aggregation |journal=Computer Physics Communications |volume=247 |date=2020 |doi=10.1016/j.cpc.2019.106873 |page=106873|bibcode=2020CoPhC.24706873Z }}</ref>

===Chemical analysis===
{{See also|Protein (nutrient)#Testing in foods}}
The total nitrogen content of organic matter is mainly formed by the amino groups in proteins. The Total Kjeldahl Nitrogen ([[TKN]]) is a measure of nitrogen widely used in the analysis of (waste) water, soil, food, feed and organic matter in general. As the name suggests, the [[Kjeldahl method]] is applied. More sensitive methods are available.<ref>{{cite journal | vauthors = Muñoz-Huerta RF, Guevara-Gonzalez RG, Contreras-Medina LM, Torres-Pacheco I, Prado-Olivarez J, Ocampo-Velazquez RV | title = A review of methods for sensing the nitrogen status in plants: advantages, disadvantages and recent advances | journal = Sensors | volume = 13 | issue = 8 | pages = 10823–10843 | date = August 2013 | pmid = 23959242 | pmc = 3812630 | doi = 10.3390/s130810823 | doi-access = free | bibcode = 2013Senso..1310823M }}</ref><ref>{{cite journal | vauthors = Martin PD, Malley DF, Manning G, Fuller L |title=Determination of soil organic carbon and nitrogen at the field level using near-infrared spectroscopy |journal=Canadian Journal of Soil Science |date=November 2002 |volume=82 |issue=4 |pages=413–422 |doi=10.4141/S01-054 |bibcode=2002CaJSS..82..413M }}</ref>