Peptide Vs. Protein Arrays: Crucial Pros and Cons to Consider

Bio­molecule arrays have been trans­form­ing bio­med­ic­al research for dec­ades. At engine, we’re the proud suc­cessors of RZPD, a pion­eer insti­tu­tion in the field of pro­tein arrays. Today, spe­cial­ized arrays have evolved from the crude early ver­sions to empower ground­break­ing dis­cov­er­ies. This art­icle will dis­cuss the dif­fer­ence between pep­tide and pro­tein arrays – and how engine arrays can sup­port your own innov­at­ive research.

In Short

Microar­rays are a fant­ast­ic tool for bio­mark­er dis­cov­ery, and they come in mul­tiple shapes and sizes. Pep­tide arrays con­tain short­er amino acid sequences, help­ing you eval­u­ate pro­tein-pro­tein inter­ac­tions with amaz­ing accur­acy. Pro­tein arrays, on the oth­er hand, offer a more hol­ist­ic view, free of hypo­thes­is bias. At engine, we make high-through­put arrays with a range of bio­molecules, from full-length pro­tein to neoanti­gens and frameshift pro­tein. This ver­sat­il­ity is already sup­port­ing life-chan­ging research into con­di­tions like Hunt­ing­ton’s dis­ease or Sys­tem­ic Lupus Eryth­em­atosus.

Peptide Arrays

Pep­tide arrays are selec­tions of dis­tinct pep­tide sequences attached to sol­id sup­port like a glass slide or a mem­brane. They are an invalu­able, high-through­put tool to study pro­tein-pro­tein inter­ac­tions (Breitling et al., 2009). Key applic­a­tions include enzyme pro­fil­ing and immune mon­it­or­ing.


Using immob­il­ized pep­tides over pro­tein microar­rays comes with mul­tiple bene­fits for spe­cif­ic research areas:

  • Pep­tide arrays allow you to pin­point spe­cif­ic anti­body bind­ing sites, which is why epi­tope map­ping has been one of the chief use cases for these chips.
  • Since fold­ing does­n’t play a sig­ni­fic­ant role in pep­tide arrays, you are less likely to miss “hid­den” epi­topes.
  • Known pep­tides are not your only option – pep­tide microar­rays can also include bioin­form­at­ic­ally designed “neoanti­gens.” This allows you to study truly nov­el anti­gens without lim­it­ing your research to inter­ac­tions between already invest­ig­ated pro­teins and pep­tides.

Pep­tide arrays also come with tech­nic­al advant­ages.

Using chem­ic­al syn­thes­is (rather than pro­tein from nat­ive or recom­bin­ant sources) elim­in­ates host con­tam­in­a­tion and gives you free­dom for struc­tur­al modi­fic­a­tions. 

With pep­tide arrays, the sequence of each bio­molecule is unam­bigu­ous. This allows for a highly spe­cif­ic and accur­ate study of pro­tein inter­ac­tion domains, which medi­ate essen­tial sig­nal­ing path­ways and reg­u­lat­ory sys­tems (Katz et al., 2011; Pawson et al., 2002). Finally, it’s much easi­er to syn­thes­ize the pep­tide you iden­ti­fied, e.g., for ELISA pro­duc­tion.


While pep­tide arrays can be a fant­ast­ic tool for epi­tope map­ping or enzyme pro­fil­ing, they’re not without down­sides.

Take fold­ing, for example. While pep­tide arrays won’t miss hid­den epi­topes, what if fold­ing is rel­ev­ant to the study? Sol­id-phase coup­ling, linkers, and spacers can change the struc­ture dis­played dur­ing the assay. Non-nat­ive epi­topes can also arise – e.g., through bind­ing to these same spacers, linkers, or inser­ted groups.

In devel­op­ing clin­ic­ally rel­ev­ant research, it is essen­tial to assess inter­ac­tions closely related to physiolo­gic­al and patho­physiolo­gic­al func­tions. You want to get as close to how things work in vivo as pos­sible. Unfor­tu­nately, pep­tides may devi­ate from their nat­ive form due to tech­nic­ally neces­sary changes – for instance, modi­fy­ing residues to improve sta­bil­ity.  

Pep­tides don’t exist sep­ar­ate from their bio­lo­gic­al sys­tems. Inside the body, they mainly form dur­ing degrad­a­tion pro­cesses, many of which we don’t under­stand com­pletely. To accur­ately map the pep­tides com­ing out, you need to mim­ic degrad­a­tion in its entirety. How­ever, we’re far from com­pre­hens­ive know­ledge about all degrad­a­tion pro­cesses. Thus, using pep­tides, as accur­ate as they may be, you might still miss out on cru­cial inter­ac­tions.

Lastly, con­sider what it takes to map a nat­ive pro­tein. Pep­tides are tiny com­pared to the entire bio­molecule. You would need a large num­ber of pep­tide vari­ants for pre­cise test­ing, which means a high­er time and fin­an­cial invest­ment.

Protein Arrays

A pro­tein array is a col­lec­tion of pro­teins immob­il­ized on a sol­id sur­face (Cut­ler, 2003). Pro­tein chips have wide applic­a­tion in bio­mark­er dis­cov­ery, anti­body pro­fil­ing, treat­ment devel­op­ment, and a range of pro­tein func­tion stud­ies, estab­lish­ing them­selves as one of the essen­tial pro­teo­m­ics tech­niques of the 21st cen­tury.


Choos­ing pro­tein over pep­tides means you’re run­ning the exper­i­ment with the nat­ive, non-frag­men­ted form of the bio­molecule. This increases bind­ing oppor­tun­it­ies, allow­ing you to dis­cov­er more real-life anti­gens than pos­sible with pep­tides. It also makes it pos­sible to map out a cross-sec­tion of the pro­teo­me effi­ciently and real­ist­ic­ally.

Now, let’s con­sider fold­ing.

Even pro­tein arrays, which are much closer to in vivo molecules, are rarely nat­ively fol­ded. To pro­duce microar­rays, the pro­tein is pur­i­fied and pro­cessed, which will affect its struc­ture. How­ever, array incub­a­tion still hap­pens in nat­ive con­di­tions, allow­ing the pro­tein to fold back at least par­tially.

Cur­rently, you can’t buy a truly nat­ively struc­tured pro­tein. This means that even if you dis­covered an anti­body that reacts with the 100% nat­ive pro­tein (impossible due to the lack of arrays), devel­op­ing an effi­cient and afford­able in vitro dia­gnost­ic product is not real­ist­ic.

In short: while com­plete nat­ive fold­ing is not avail­able, pro­tein arrays give you the closest chip to in vivo pos­sible.

Fur­ther­more, pro­tein arrays can still con­tain pep­tides, frag­ments, and iso­forms of the bio­molecule. Neoanti­gens can also be intro­duced into the microar­rays, and it is pos­sible to par­tially modi­fy pro­tein after pro­du­cing the array (via enzymes). This sig­ni­fic­antly expands the use cases. You can study mul­tiple molecules at once, remove preselec­tion bias, and cov­er the het­ero­gen­eity of pro­tein expres­sion.

Even bet­ter, you can use pro­tein arrays to under­stand dis­eases where neoanti­gens and frameshift pep­tides play a sig­ni­fic­ant role in patho­physiology. Learn more about study­ing out-of-frame pep­tides and how it opens new fron­ti­ers in Huntington’s dis­ease research here (Dav­ies & Rubin­sztein, 2006).

And, although most pro­tein arrays are hypo­thes­is-bias-free, you can also use dis­ease and tis­sue-spe­cif­ic selec­tions. These can help you nar­row down your research, although you do have to be care­ful about preselec­tion par­ti­al­ity.


Pro­tein arrays are a unique oppor­tun­ity in pro­teo­m­ics, but def­in­itely not a meth­od without fault:

  • You can’t have a pro­tein array map of all pro­tein. Because hosts can­’t pro­duce all molecules with the cor­rect length, fold­ing, and modi­fic­a­tion, microar­rays are not a com­pre­hens­ive map of in vivo pro­tein. How­ever, if you’re using them for in vitro applic­a­tions, this isn’t a con­cern.
  • There can be repro­du­cib­il­ity chal­lenges. Some man­u­fac­tur­ers only give you the sequence and the host­name, mak­ing it dif­fi­cult to con­duct fol­low-up exper­i­ments. At engine, we give you the com­plete inform­a­tion, as well as the dir­ect clone, to avoid that issue.
  • Sequen­cing errors jeop­ard­ize accur­acy. In the worst-case scen­ario, the pro­tein has been syn­thes­ized based only on genes that have been cloned. Without a con­trol sequen­cing of the clones, this can lead to inac­cur­ate pro­tein pro­duc­tion. We avoid this by always sequen­cing our clones and run­ning reg­u­lar data­base updates, so you can trust engine to provide the cor­rect bio­molecules prom­ised.

Finally, host con­tam­in­a­tion can be an issue with pro­tein arrays, although its pre­val­ence var­ies depend­ing on the host.


Pro­tein arrays are an excel­lent top-down approach to bio­mark­er dis­cov­ery. You are test­ing for thou­sands of inter­ac­tions in a single run (with very little sample mater­i­al.) Since you’re not lim­ited by hypo­thes­is, pro­tein microar­rays open the door to ground­break­ing dis­cov­er­ies in dir­ec­tions that you would oth­er­wise over­look

How engine Supports Cutting-Edge Science

At engine, we’re proud to sup­port research that changes lives. Our pro­tein arrays have already helped over 100 pub­lic­a­tions, and here is why:

E. coli Host

By using E. coli clones, we avoid unwanted post-trans­la­tion­al modi­fic­a­tions — com­pare that to insect cells, which are notori­ous for glyc­osylat­ing products. E. coli is also a cost-effect­ive and effi­cient host, per­fect for ensur­ing accur­ate fol­low-up exper­i­ments. Since we have empty vec­tor spots, your invest­ig­a­tion is not com­prom­ised even if the host is detec­ted. Although we mit­ig­ate unex­pec­ted changes to the pro­tein, we can still modi­fy your array using enzymes to provide the exact molecule set you need.

Easy Follow-Up

Exper­i­ment rep­lic­a­tion is a corner­stone of qual­ity research. Since we give you com­plete inform­a­tion and access to the clones them­selves, fol­low-up exper­i­ments are more straight­for­ward and much more accur­ate.

Largest Neoantigen Library

We know that innov­a­tion often comes from the most unex­pec­ted sources. Thus, we don’t lim­it ourselves to known pro­teins. In fact, 41.8% of the spots in our hEXse­lect array are neoanti­gens and frameshift pep­tides, mak­ing it invalu­able when research­ing dis­eases like Huntington’s.

No Selection Bias

In con­di­tions where the cause-to-dis­ease path­way is com­plex and poorly under­stood, hypo­thes­is bias can ser­i­ously hinder dis­cov­ery. Our arrays include many human anti­gens, from full-length pro­tein to pep­tides, neoanti­gens, and frameshifts. You can test for 10,000 dif­fer­ent inter­ac­tions in a single run, sig­ni­fic­antly increas­ing your chance of dis­cov­ery.

Final Thoughts

Microar­rays have revo­lu­tion­ized the world of med­ic­al research by intro­du­cing a reli­able, high-through­put meth­od­o­logy. Dif­fer­ent arrays come with unique bene­fits and down­sides for spe­cif­ic exper­i­ments. At engine, we emphas­ize well-estab­lished, robust tech­no­logy for a hol­ist­ic view of your research prob­lem. Our com­pre­hens­ive microar­rays return pre­cise res­ults, help you avoid hypo­thes­is bias, and sup­port you through­out bio­mark­er study, val­id­a­tion, and fol­low-up exper­i­ments. How can we sup­port your next dis­cov­ery? Reach out today to learn more!

  • Breitling, F., Nes­ter­ov, A., Stadler, V., Fel­gen­hauer, T., & Bis­choff, F. R. (2009). High-dens­ity pep­tide arrays. Molecu­lar BioSys­tems, 5(3), 224.
  • Cut­ler, P. (2003). Pro­tein arrays: The cur­rent state-of-the-art. PROTEOMICS, 3(1), 3–18.
  • Dav­ies, J. E., & Rubin­sztein, D. C. (2006). Poly­alan­ine and poly­s­er­ine frameshift products in Huntington’s dis­ease. Journ­al of Med­ic­al Genet­ics, 43(11), 893–896.
  • Katz, C., Levy-Beladev, L., Rotem-Bam­ber­ger, S., Rito, T., Rüdi­ger, S. G. D., & Friedler, A. (2011). Study­ing protein–protein inter­ac­tions using pep­tide arrays. Chem­ic­al Soci­ety Reviews, 40(5), 2131.
  • Pawson, T., Raina, M., & Nash, P. (2002). Inter­ac­tion domains: from simple bind­ing events to com­plex cel­lu­lar beha­vi­or. FEBS Let­ters, 513(1), 2–10.–6

Email Us