Editing Protein design (section)

==Applications and examples of designed proteins==

===Enzyme design===

The design of new [[enzyme]]s is a use of protein design with huge bioengineering and biomedical applications. In general, designing a protein structure can be different from designing an enzyme, because the design of enzymes must consider many states involved in the [[enzyme catalysis|catalytic mechanism]]. However protein design is a prerequisite of ''de novo'' enzyme design because, at the very least, the design of catalysts requires a scaffold in which the catalytic mechanism can be inserted.<ref name="baker10">{{cite journal|last=Baker|first=D|title=An exciting but challenging road ahead for computational enzyme design.|journal=Protein Science|date=October 2010|volume=19|issue=10|pages=1817–9|pmid=20717908|doi=10.1002/pro.481|pmc=2998717}}</ref>

Great progress in ''de novo'' enzyme design, and redesign, was made in the first decade of the 21st century. In three major studies, David Baker and coworkers ''de novo'' designed enzymes for the retro-[[aldol reaction]],<ref name="jiang08">{{cite journal |doi=10.1126/science.1152692 |title=De Novo Computational Design of Retro-Aldol Enzymes |year=2008 |last1=Jiang |first1=Lin |last2=Althoff |first2=Eric A. |last3=Clemente |first3=Fernando R. |last4=Doyle |first4=Lindsey |last5=Rothlisberger |first5=Daniela |last6=Zanghellini |first6=Alexandre |last7=Gallaher |first7=Jasmine L. |last8=Betker |first8=Jamie L. |last9=Tanaka |first9=Fujie |journal=Science |volume=319 |pages=1387–91 |pmid=18323453 |issue=5868|bibcode= 2008Sci...319.1387J |pmc=3431203}}</ref> a Kemp-elimination reaction,<ref name="roth08">{{cite journal |doi=10.1038/nature06879 |title=Kemp elimination catalysts by computational enzyme design |year=2008 |last1=Röthlisberger |first1=Daniela |last2=Khersonsky |first2=Olga |last3=Wollacott |first3=Andrew M. |last4=Jiang |first4=Lin |last5=Dechancie |first5=Jason |last6=Betker |first6=Jamie |last7=Gallaher |first7=Jasmine L. |last8=Althoff |first8=Eric A. |last9=Zanghellini |first9=Alexandre |journal=Nature |volume=453 |pages=190–5 |pmid=18354394 |issue=7192|bibcode= 2008Natur.453..190R|doi-access=free }}</ref> and for the [[Diels-Alder reaction]].<ref>{{cite journal|last=Siegel|first=JB|author2=Zanghellini, A; Lovick, HM; Kiss, G; Lambert, AR; St Clair, JL; Gallaher, JL; Hilvert, D; Gelb, MH; Stoddard, BL; Houk, KN; Michael, FE; Baker, D|title=Computational design of an enzyme catalyst for a stereoselective bimolecular Diels-Alder reaction.|journal=Science|date=July 16, 2010|volume=329|issue=5989|pages=309–13|pmid=20647463|bibcode= 2010Sci...329..309S |doi= 10.1126/science.1190239|pmc=3241958}}</ref> Furthermore, Stephen Mayo and coworkers developed an iterative method to design the most efficient known enzyme for the Kemp-elimination reaction.<ref>{{cite journal|last=Privett|first=HK|author2=Kiss, G |author3=Lee, TM |author4=Blomberg, R |author5=Chica, RA |author6=Thomas, LM |author7=Hilvert, D |author8=Houk, KN |author9= Mayo, SL |title=Iterative approach to computational enzyme design.|journal=Proceedings of the National Academy of Sciences of the United States of America|date=March 6, 2012|volume=109|issue=10|pages=3790–5|pmid=22357762|bibcode= 2012PNAS..109.3790P |doi= 10.1073/pnas.1118082108 |pmc=3309769|doi-access=free}}</ref> Also, in the laboratory of [[Bruce Donald]], computational protein design was used to switch the specificity of one of the [[protein domain]]s of the [[nonribosomal peptide|nonribosomal peptide synthetase]] that produces [[Gramicidin S]], from its natural substrate [[Phenylalanine|phe]]nylalanine to other noncognate substrates including charged amino acids; the redesigned enzymes had activities close to those of the wild-type.<ref name="chen09">{{cite journal|last=Chen|first=CY|author2=Georgiev, I |author3=Anderson, AC |author4= Donald, BR |title=Computational structure-based redesign of enzyme activity.|journal=Proceedings of the National Academy of Sciences of the United States of America|date=March 10, 2009|volume=106|issue=10|pages=3764–9|pmid=19228942|bibcode= 2009PNAS..106.3764C |doi= 10.1073/pnas.0900266106 |pmc=2645347|doi-access=free}}</ref>

=== Semi-rational design ===
Semi-rational design is a purposeful modification method based on a certain understanding of the sequence, structure, and catalytic mechanism of enzymes. This method is between irrational design and rational design. It uses known information and means to perform evolutionary modification on the specific functions of the target enzyme. The characteristic of semi-rational design is that it does not rely solely on random mutation and screening, but combines the concept of directed evolution. It creates a library of random mutants with diverse sequences through [[mutagenesis]], [[Mutagenesis (molecular biology technique)|error-prone RCR]], [[Recombinant DNA|DNA recombination]], and [[Saturation mutagenesis|site-saturation mutagenesis]]. At the same time, it uses the understanding of enzymes and design principles to purposefully screen out mutants with desired characteristics.

The methodology of semi-rational design emphasizes the in-depth understanding of enzymes and the control of the evolutionary process. It allows researchers to use known information to guide the evolutionary process, thereby improving efficiency and success rate. This method plays an important role in protein function modification because it can combine the advantages of irrational design and rational design, and can explore unknown space and use known knowledge for targeted modification.

Semi-rational design has a wide range of applications, including but not limited to enzyme optimization, modification of drug targets, evolution of biocatalysts, etc. Through this method, researchers can more effectively improve the functional properties of proteins to meet specific biotechnology or medical needs. Although this method has high requirements for information and technology and is relatively difficult to implement, with the development of computing technology and bioinformatics, the application prospects of semi-rational design in protein engineering are becoming more and more broad.<ref>{{Cite book |last=Korendovych |first=Ivan V. |title=Protein Engineering |date=2018 |chapter=Rational and Semirational Protein Design |series=Methods in Molecular Biology (Clifton, N.J.) |volume=1685 |pages=15–23 |doi=10.1007/978-1-4939-7366-8_2 |issn=1064-3745 |pmc=5912912 |pmid=29086301|isbn=978-1-4939-7364-4 }}</ref>

===Design for affinity===

[[Protein–protein interaction]]s are involved in most biotic processes. Many of the hardest-to-treat diseases, such as [[Alzheimer]]'s, many forms of [[cancer]] (e.g., [[TP53]]), and human immunodeficiency virus ([[HIV]]) infection involve protein–protein interactions. Thus, to treat such diseases, it is desirable to design protein or protein-like therapeutics that bind one of the partners of the interaction and, thus, disrupt the disease-causing interaction. This requires designing protein-therapeutics for ''affinity'' toward its partner.

Protein–protein interactions can be designed using protein design algorithms because the principles that rule protein stability also rule protein–protein binding. Protein–protein interaction design, however, presents challenges not commonly present in protein design. One of the most important challenges is that, in general, the interfaces between proteins are more polar than protein cores, and binding involves a tradeoff between desolvation and hydrogen bond formation.<ref name="kuhlman2009">{{cite journal|last=Karanicolas|first=J|author2=Kuhlman, B |title=Computational design of affinity and specificity at protein–protein interfaces.|journal=Current Opinion in Structural Biology|date=August 2009|volume=19|issue=4|pages=458–63|pmid=19646858|doi=10.1016/j.sbi.2009.07.005|pmc=2882636}}</ref> To overcome this challenge, Bruce Tidor and coworkers developed a method to improve the affinity of antibodies by focusing on electrostatic contributions. They found that, for the antibodies designed in the study, reducing the desolvation costs of the residues in the interface increased the affinity of the binding pair.<ref name=kuhlman2009 /><ref>{{cite journal|last=Shoichet|first=BK|title=No free energy lunch.|journal=Nature Biotechnology|date=October 2007|volume=25|issue=10|pages=1109–10|pmid=17921992|doi=10.1038/nbt1007-1109|s2cid=5527226}}</ref><ref>{{cite journal|last=Lippow|first=SM|author2=Wittrup, KD |author3=Tidor, B |title=Computational design of antibody-affinity improvement beyond in vivo maturation.|journal=Nature Biotechnology|date=October 2007|volume=25|issue=10|pages=1171–6|pmid=17891135|doi=10.1038/nbt1336|pmc=2803018}}</ref>

====Scoring binding predictions====

Protein design energy functions must be adapted to score binding predictions because binding involves a trade-off between the lowest-[[Thermodynamic free energy|energy]] conformations of the free proteins (<var>E<sub>P</sub></var> and <var>E<sub>L</sub></var>) and the lowest-energy conformation of the bound complex (<var>E<sub>PL</sub></var>):

: <math>\Delta_G = E_{PL} - E_P - E_L </math>.

The K* algorithm approximates the binding constant of the algorithm by including conformational entropy into the free energy calculation. The K* algorithm considers only the lowest-energy conformations of the free and bound complexes (denoted by the sets <var>P</var>, <var>L</var>, and <var>PL</var>) to approximate the partition functions of each complex:<ref name=donald10 />

: <math>K^* = \frac{\sum\limits_{x\in PL} e^{-E(x)/RT}}{\sum\limits_{x\in P} e^{-E(x)/RT}\sum\limits_{x\in L} e^{-E(x)/RT}}</math>

===Design for specificity ===

The design of protein–protein interactions must be highly specific because proteins can interact with a large number of proteins; successful design requires selective binders. Thus, protein design algorithms must be able to distinguish between on-target (or ''positive design'') and off-target binding (or ''negative design'').<ref name="richardson1989"/><ref name=kuhlman2009 /> One of the most prominent examples of design for specificity is the design of specific [[bZIP domain|bZIP]]-binding peptides by Amy Keating and coworkers for 19 out of the 20 bZIP families; 8 of these peptides were specific for their intended partner over competing peptides.<ref name="kuhlman2009" /><ref name="schreiber11">{{cite journal|last=Schreiber|first=G|author2=Keating, AE |title=Protein binding specificity versus promiscuity.|journal=Current Opinion in Structural Biology|date=February 2011|volume=21|issue=1|pages=50–61|pmid=21071205|doi=10.1016/j.sbi.2010.10.002|pmc=3053118}}</ref><ref>{{cite journal|last=Grigoryan|first=G|author2=Reinke, AW |author3=Keating, AE |title=Design of protein-interaction specificity gives selective bZIP-binding peptides.|journal=Nature|date=April 16, 2009|volume=458|issue=7240|pages=859–64|pmid=19370028|bibcode= 2009Natur.458..859G |doi= 10.1038/nature07885 |pmc=2748673}}</ref> Further, positive and negative design was also used by Anderson and coworkers to predict mutations in the active site of a drug target that conferred resistance to a new drug; positive design was used to maintain wild-type activity, while negative design was used to disrupt binding of the drug.<ref name="frey10">{{cite journal|last=Frey|first=KM|author2=Georgiev, I |author3=Donald, BR |author4= Anderson, AC |title=Predicting resistance mutations using protein design algorithms.|journal=Proceedings of the National Academy of Sciences of the United States of America|date=August 3, 2010|volume=107|issue=31|pages=13707–12|pmid=20643959|bibcode= 2010PNAS..10713707F |doi= 10.1073/pnas.1002162107 |pmc=2922245|doi-access=free}}</ref> Recent computational redesign by Costas Maranas and coworkers was also capable of experimentally switching the [[cofactor (biochemistry)|cofactor]] specificity of ''Candida boidinii'' xylose reductase from [[Nicotinamide adenine dinucleotide phosphate|NADPH]] to [[Nicotinamide adenine dinucleotide|NADH]].<ref name="khoury">{{cite journal |title=Computational design of Candida boidinii xylose reductase for altered cofactor specificity |journal=Protein Science |volume=18 |issue=10 |pages=2125–38 |date=October 2009 |doi=10.1002/pro.227 |pmc=2786976 |pmid=19693930 |last1=Khoury |first1=GA |last2=Fazelinia |first2=H |last3=Chin |first3=JW |last4=Pantazes |first4=RJ |last5=Cirino |first5=PC |last6=Maranas |first6=CD}}</ref>

===Protein resurfacing===

Protein resurfacing consists of designing a protein's surface while preserving the overall fold, core, and boundary regions of the protein intact. Protein resurfacing is especially useful to alter the binding of a protein to other proteins. One of the most important applications of protein resurfacing was the design of the RSC3 probe to select broadly neutralizing HIV antibodies at the NIH Vaccine Research Center. First, residues outside of the binding interface between the gp120 HIV envelope protein and the formerly discovered b12-antibody were selected to be designed. Then, the sequence spaced was selected based on evolutionary information, solubility, similarity with the wild-type, and other considerations. Then the RosettaDesign software was used to find optimal sequences in the selected sequence space. RSC3 was later used to discover the broadly neutralizing antibody VRC01 in the serum of a long-term HIV-infected non-progressor individual.<ref>{{cite journal|last=Burton|first=DR|author2=Weiss, RA |title=AIDS/HIV. A boost for HIV vaccine design.|journal=Science|date=August 13, 2010|volume=329|issue=5993|pages=770–3|pmid=20705840|bibcode= 2010Sci...329..770B |doi= 10.1126/science.1194693|s2cid=206528638}}</ref>

===Design of globular proteins===

[[Globular protein]]s are proteins that contain a hydrophobic core and a hydrophilic surface. Globular proteins often assume a stable structure, unlike [[fibrous protein]]s, which have multiple conformations. The three-dimensional structure of globular proteins is typically easier to determine through [[X-ray crystallography]] and [[nuclear magnetic resonance]] than both fibrous proteins and [[membrane protein]]s, which makes globular proteins more attractive for protein design than the other types of proteins. Most successful protein designs have involved globular proteins. Both [[#Sequence space|RSD-1]], and [[#Target structure|Top7]] were ''de novo'' designs of globular proteins. Five more protein structures were designed, synthesized, and verified in 2012 by the Baker group. These new proteins serve no biotic function, but the structures are intended to act as building-blocks that can be expanded to incorporate functional active sites. The structures were found computationally by using new heuristics based on analyzing the connecting loops between parts of the sequence that specify secondary structures.<ref>{{cite news |title=Proteins made to order |author=Jessica Marshall |url=http://www.nature.com/news/proteins-made-to-order-1.11767 |newspaper=Nature News |date=November 7, 2012 |access-date=November 17, 2012}}</ref>

===Design of membrane proteins===
Several transmembrane proteins have been successfully designed,<ref>[https://opm.phar.umich.edu/superfamilies/478 Designed transmembrane alpha-hairpin proteins] in [[OPM database]]</ref> along with many other membrane-associated peptides and proteins.<ref>[https://opm.phar.umich.edu/species/213 Designed membrane-associated peptides and proteins] in [[OPM database]]</ref> Recently, Costas Maranas and his coworkers developed an automated tool<ref>{{Cite journal|last1=Chowdhury|first1=Ratul|last2=Kumar|first2=Manish|last3=Maranas|first3=Costas D.|last4=Golbeck|first4=John H.|last5=Baker|first5=Carol|last6=Prabhakar|first6=Jeevan|last7=Grisewood|first7=Matthew|last8=Decker|first8=Karl|last9=Shankla|first9=Manish|date=2018-09-10|title=PoreDesigner for tuning solute selectivity in a robust and highly permeable outer membrane pore|journal=Nature Communications|language=en|volume=9|issue=1|pages=3661|doi=10.1038/s41467-018-06097-1|issn=2041-1723|pmc=6131167|pmid=30202038|bibcode=2018NatCo...9.3661C}}</ref> to redesign the pore size of Outer Membrane Porin Type-F (OmpF) from ''E.coli'' to any desired sub-nm size and assembled them in membranes to perform precise angstrom scale separation.

===Other applications ===

One of the most desirable uses for protein design is for [[biosensor]]s, proteins that will sense the presence of specific compounds. Some attempts in the design of biosensors include sensors for unnatural molecules including [[TNT]].<ref>{{cite journal |last1=Looger |first1=Loren L. |last2=Dwyer |first2=Mary A. |last3=Smith |first3=James J. |last4=Hellinga |first4=Homme W. |name-list-style=amp |year=2003 |title=Computational design of receptor and sensor proteins with novel functions |journal=[[Nature (journal)|Nature]] |pmid=12736688 |volume=423 |issue=6936 |pages=185–190 |doi=10.1038/nature01556 |bibcode= 2003Natur.423..185L|s2cid=4387641 }}</ref> More recently, Kuhlman and coworkers designed a biosensor of the [[p21 activated kinase|PAK1]].<ref>{{cite journal|last=Jha|first=RK|author2=Wu, YI |author3=Zawistowski, JS |author4=MacNevin, C |author5=Hahn, KM |author6= Kuhlman, B |title=Redesign of the PAK1 autoinhibitory domain for enhanced stability and affinity in biosensor applications.|journal=Journal of Molecular Biology|date=October 21, 2011|volume=413|issue=2|pages=513–22|pmid=21888918|doi=10.1016/j.jmb.2011.08.022 |pmc=3202338}}</ref>

In a sense, protein design is a subset of [[circuit design|battery design]].{{Explain|date=April 2022}}