Development of Bacterial Display Peptides for use in 

Biosensing Applications

by Dimitra N. Stratis-Cullum, Joshua M. Kogot, Michael S. Sellers, 

Margaret M. Hurley, Deborah A. Sarkes Joseph M. Pennington, 

Irene Val-Addo, Bryn L. Adams, Candice R. Warner, James P. Carney, 

Rebecca L. Brown, and Paul M. Pellegrino

ARL-RP-0404 September 2012

A reprint from SPIE Proceedings, 23 April 2012

Approved for public release; distribution unlimited.
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Destroy this report when it is no longer needed. Do not return it to the originator.
Army Research Laboratory 

Adelphi, MD 20783-1197 

ARL-RP-0404 September 2012 

Development of Bacterial Display Peptides for use in 

Biosensing Applications 

Dimitra N. Stratis-Cullum, Joshua M. Kogot, Michael S. Sellers, 

Margaret M. Hurley, Deborah A. Sarkes, Joseph M. Pennington, 

Irene Val-Addo, Bryn L. Adams, Paul M. Pellegrino 

Sensors and Electron Devices Directorate, ARL 

Candice R. Warner, James P. Carney, Rebecca L. Brown 

U.S. Army Edgewood Chemical Biological Center 

A reprint from SPIE Proceedings, 23 April 2012

Approved for public release; distribution unlimited. 
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Development of Bacterial Display Peptides for use in Biosensing Applications

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Dimitra N. Stratis-Cullum, Joshua M. Kogot, Michael S. Sellers, Margaret M. 

Hurley, Deborah A. Sarkes Joseph M. Pennington, Irene Val-Addo, Bryn L. 

Adams, Candice R. Warner, James P. Carney, Rebecca L. Brown, and Paul M. 

Pellegrino

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13. SUPPLEMENTARY NOTES

14. ABSTRACT

Recent advances in synthetic library engineering continue to show promise for the rapid production of reagent technology in 

response to biological threats. A synthetic library of peptide mutants built off a bacterial host offers a convenient means to link 

the peptide sequence, (i.e., identity of individual library members) with the desired molecular recognition traits, but also allows 

for a relatively simple protocol, amenable to automation. An improved understanding of the mechanisms of recognition and 

control of synthetic reagent isolation and evolution remain critical to success. In this paper, we describe our approach to 

development of peptide affinity reagents based on peptide bacterial display technology with improved control of binding 

interactions for stringent evolution of reagent candidates, and tailored performance capabilities. There are four key elements to 

the peptide affinity reagent program including: (1) the diverse bacterial library technology, (2) advanced reagent screening 

amenable to laboratory automation and control, (3) iterative characterization and feedback on both affinity and specificity of the 

molecular interactions, and (3) integrated multiscale computational prescreening of candidate peptide ligands including in silico 

prediction of improved binding performance. Specific results on peptides binders to Protective Antigen (PA) protein of Bacillus 

anthracis and Staphylococcal Enterotoxin B (SEB) will be presented. Recent highlights of on cell vs. off-cell affinity behavior 

and correlation of the results with advanced docking simulations on the protein-peptide system(s) are included. The potential of 

this technology and approach to enable rapid development of a new affinity reagent with unprecedented speed (less than one 

week) would allow for rapid response to new and constantly emerging threats.

15. SUBJECT TERMS

peptide, synthetic reagent, affinity reagent, bacterial display, multi-scale modeling, docking, protective

antigen, SEB, biosensing

16. SECURITY CLASSIFICATION OF: 

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OF ABSTRACT

UU

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OF PAGES

14

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Dimitra N. Stratis-Cullum

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UNCLASSIFIED

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UNCLASSIFIED

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(301) 394-0794

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Prescribed by ANSI Std. Z39.18 
Development of bacterial display peptides for use in biosensing 

applications 

Dimitra N. Stratis-Cullum*a, Joshua M. Kogota, Michael S. Sellersa, Margaret M. Hurleya, Deborah 

A. Sarkesa, Joseph M. Penningtona, Irene Val-Addoa, Bryn L. Adamsa, Candice R. Warnerb, James 

P. Carneyb, Rebecca L. Brownb, and Paul M. Pellegrinoa

aU.S. Army Research Laboratory, bU.S. Army Edgewood Chemical Biological Center 

ABSTRACT 

Recent advances in synthetic library engineering continue to show promise for the rapid production of reagent 

technology in response to biological threats. A synthetic library of peptide mutants built off a bacterial host offers a 

convenient means to link the peptide sequence, (i.e., identity of individual library members) with the desired molecular 

recognition traits, but also allows for a relatively simple protocol, amenable to automation. An improved understanding 

of the mechanisms of recognition and control of synthetic reagent isolation and evolution remain critical to success. In 

this paper, we describe our approach to development of peptide affinity reagents based on peptide bacterial display 

technology with improved control of binding interactions for stringent evolution of reagent candidates, and tailored 

performance capabilities. There are four key elements to the peptide affinity reagent program including: (1) the diverse 

bacterial library technology, (2) advanced reagent screening amenable to laboratory automation and control, (3) iterative 

characterization and feedback on both affinity and specificity of the molecular interactions, and (3) integrated multiscale computational prescreening of candidate peptide ligands including in silico prediction of improved binding 

performance. Specific results on peptides binders to Protective Antigen (PA) protein of Bacillus anthracis and 

Staphylococcal Enterotoxin B (SEB) will be presented. Recent highlights of on cell vs. off-cell affinity behavior and 

correlation of the results with advanced docking simulations on the protein-peptide system(s) are included. The potential 

of this technology and approach to enable rapid development of a new affinity reagent with unprecedented speed (less 

than one week) would allow for rapid response to new and constantly emerging threats. 

 

Keywords: peptide, synthetic reagent, affinity reagent, bacterial display, multi-scale modeling, docking, protective 

antigen, SEB, biosensing

1. INTRODUCTION 

The challenge in hazard detection (whether chemical or biological in nature) is detection of trace concentrations of 

materials in a complex background plagued with interferences. The Army and broader sensing community are in need of 

technologies that can offer robust, rapid, and reliable detection. The “heart” of any biosensor technology is the 

bioreceptor element (i.e. affinity reagent), as it is responsible for the specific recognition of the target threat of interest. 

The current state-of-the-art in element technology (i.e., antibody bioreceptors) is fraught with difficulties including: poor 

mass production capabilities, reagent stability, and large overall production costs. Moreover, the rate at which the DoD 

requires reagents for new and emerging threats far exceeds the rate at which they can currently be produced. Antibodies 

usually require several weeks-to-months to isolate from living hosts whereas recent advances have demonstrated that 

synthetic routes can be employed using various synthetic recognition element technologies (e.g., bacterial display and 

phage display) to produce bioreceptors in as little as a few days to a couple weeks (see Figure 1).1-3 

Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XIII, edited by Augustus Way Fountain III,

Proc. of SPIE Vol. 8358, 83580A · © 2012 SPIE · CCC code: 0277-786X/12/$18 · doi: 10.1117/12.919782

Proc. of SPIE Vol. 8358 83580A-1

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Figure 1. Comparison of time needed to develop new reagents using antibody and synthetic protein regent 

technologies. 

The mechanisms for specific binding f r o m a s y n t h e t i c r e c o g n i t i o n e l e m e n t ( S R E ) r e c e p t o r are 

similar to antibody-antigen interactions but unlike antibodies, peptide reagents can be rapidly developed through 

b i o - e n g i n e e r e d library screening t o o l k i t s and mass-produced through standard synthesis techniques. Another

potential advantage of peptide-based sensing includes a greater stability that would allow for wide-spread field use, a 

shortcoming of current antibody technology. Several variations of peptide development technologies including yeast, 

phage, and bacterial display are currently being used to isolate SREs. However, with bacterial peptide display 

technology, the extremely fast replication rate of bacteria is exploited and biological components (e.g., modified proteins) 

on an E. coli cell surface are harnessed to produce the peptide library of binders. It is with this speed of bacterial growth 

rates, combined with improved computational techniques to characterize and tailor peptide affinity and specificity, that 

bacterial peptide display technology has emerged as a means to rapidly isolate high affinity protein binders (within 1 

week). This is critical for combating newly emerging biological weapons of mass destruction (WMD) that have no 

readily available or specific antibody bioreceptor. 

In Figure 2, we show there are four key research areas that we bring together for the development of peptide SREs for 

affinity reagent discovery including: (1) the diverse bacterial library technology, (2) advanced reagent screening 

amenable to laboratory automation and control, (3) iterative characterization and feedback on both affinity and 

specificity of the molecular interactions, and (3) integrated multi-scale computational prescreening of candidate peptide 

ligands including in silico prediction of improved binding performance. 

To engineer a “library” of peptide binding elements, a small section of protein from the surface of a biological system 

(e.g., bacterium, virus, etc.) is manipulated to present a randomized sequence of amino acids (the building blocks of 

proteins). Previous work by the Daugherty lab, details the development and early screening results with the eCPX 

platform4). Briefly, this peptide library employs an E. coli bacterial display platform, generated from the extracellular 

loop of OmpX outer-membrane protein. The randomized portion of the library is a 15-mer, yielding a greater than 1010 

member library. The bacterial display library utilized throughout these studies is an enhanced form, termed eCPX. The 

OmpX outer membrane protein has been engineered into a circularly permuted scaffold to allow both C-terminal and Nterminal display of proteins. 

The large diversity of sequences (1010 members for bacterial display presented by this library) is then exposed to a target 

of interest and stringency controls, in an alternating fashion. This procedure is sometimes referred to as “bio-panning,” 

“library screening,” or “sorting” and is conducted to isolate a small subset of peptide sequences that demonstrate 

extremely high binding affinity and specificity. Sorting, or screening of peptide libraries for suitable reagent candidates 

is typically performed by a combination of several rounds of manual MACS for pre-enrichment and several rounds of 

FACS. Although effective, the approach is quite labor intensive, and most importantly the performance characteristics of 

the resulting reagents are highly operator dependent. Furthermore, the cost of an instrument equipped with fluorescence 

< 1 week

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1 month

several 

months

0 50 100

Bacterial Display

Phage Display

Yeast Display

Polycolonal Sera

Hybridoma

Time to develop reagent (Days)

Reagent Production

Method

Proc. of SPIE Vol. 8358 83580A-2

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Structural and Binder er1&mancSludies Peptide Affinity Reagent Development

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activated cell (FACS) sorting and isolation is often prohibitively expensive (~$350-500K) for many laboratories. 

Consequently the ability to automate the process on an inexpensive platform is highly desired. 

Figure 2. Schematic diagram showing the four main areas of research which enable rapid, high-performance 

synthetic recognition element development. 

The key performance metrics to SRE isolation include the purity of separation (ability to perform a pure separation of 

the binding reagents from background), rare-cell recovery (ability to isolate extremely low cell count populations from 

the sea of 1010 binder library cells), and throughput (ability to sort several mL of library solution in minutes for high 

throughput isolation). We recently published on our work showing rare-cell recovery and reagent studies using the 

second generation Micro Magnetic Sorter (MMS), which consists of a semi-automated magnetic separation system 

consisting of a disposable microfluidic cartridge. SRE reagent screening with the MMS approach was found to cause an 

increase in reproducibility and control over the biopanning with consistent results through cross-laboratory study.1 

Characterization of binder performance is a critical component of SRE development as it allows for isolation of high 

affinity peptides for the target of interest but more importantly specific reagents, which is directly linked to the degree to 

which the sensor, ultimately using this reagent will false alarm. On-cell characterization is typically performed using 

flow cytometry analysis. Off-cell characterization is significantly more challenging due to the small size of the peptides 

where chemical modification can significantly alter the function and performance and solubility of the synthetic peptide 

is sometimes problematic. Recently, we published a custom method5 developed to address these challenges by 

incorporating a fusion tag which binds to polystyrene. The polystyrene fusion tag provides an overall better solubility 

profile and a means by which to incorporate the peptide as a reagent into a standard enzyme-linked immunosorbent 

assay format. Although more expensive and less standard, off-cell characterization can also be performed label-free 

through other custom methods, such as surface Plasmon resonance spectroscopy (SPR). 

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2. MATERIALS AND METHODS

2.1 MMS Disposable Microfluidic Card:

The Micro-Magnetic Sorter (MMS) is an automated magnetic separation system consisting of a disposable microfluidic 

cartridge and a companion instrument (Figure 3). The disposable cartridges are made of injection-molded polypropylene 

(Pinnacle Polymers PP 5135C). The 200 μm deep fluidic channels are defined by two injected parts, which are laserwelded (California Lasers, Simi Valley, CA) and a portion is heat staked with a hydrophobic membrane for bubble 

removal (Pall Co, Ann Arbor, MI). The trapping region was designed to accommodate up to 1 x 109 of 1 μm trapped 

magnetic beads and process up to 1 x 1011 bacterial cells. Female luer fittings on the top of the cartridge allow for a leakproof interface between the cartridge and disposable syringes (Becton Dickinson, San José, CA). The luer fittings on the 

cartridge are designed to hold a reservoir array, for pneumatically driven applications as well as the injector inputs. 

There are a total of four luer ports required for two sample injectors (1 or 5 mL volume), one running/wash buffer 

injector (up to 10 mL) and one elution buffer injector (up to 3 mL volume). Strategically designed micro-channels allow 

for full automation of magnetic separation on the cartridge. To accomplish this, five pneumatically actuated pinch valves 

are located on the underside of the cartridge, which allow for the redirection of flow. These valve membranes require a 

force of ~15 lb/in2 to seal and are robust enough to be actuated multiple times. 

2.2 MMS Instrumentation 

The instrument utilizes a cRIO controller with LabVIEW script (National Instruments, Austin, TX) outfitted with 

standard digital and analog in/out modules for control of the internal components. Flow rates within the cartridge are 

controlled by four stepper motors (Figure 7c) and controller boards (Haydon and Anaheim Automation, respectively), 

which physically push on the injectors (Figure 7d). These motors are fitted with micro-switches (Panasonic ECG, 

Secaucus, NJ) that allow for the automatic calculation of input volume. Valves on the cartridge are actuated using 

pneumatically controlled air cylinders (SMC Corp, Noblesville, IN) and a DC diaphragm pump (Thomas provided by 

Nor Cal Controls, San Jose, CA). There are seventy custom neodymium-iron boron magnets, which are positioncontrolled by another Haydon stepper motor. The magnets are distributed equally among top and bottom portions of a 

magnetic rack, which sandwich the disposable cartridge. A single motor, in conjunction with a spring, allows for both 

horizontal and vertical movement of magnets. This facilitates horizontal movement required for trapping and elution, 

and vertical movement capable of agitating the sample within the cartridge. Software control is provided using a 

LabVIEW interface. Push button applications have been created for bacterial library sorting. Advanced users can 

generate custom sorting routines, which allow full access to all the operation parameters with minimal training. Direct 

control of flow rates, wash stringencies, and positive/negative selection criteria enables the end user to specify the 

magnetic bead and protocol of choice, and optimize it for applications beyond bacterial library sorting (i.e. cell culture, 

flow cytometry, toxicology studies, etc.). 

2.3 Sorting Procedures and Sample Preparation 

Figure 4 shows a general schematic of the library sorting scheme. A bacterial display library (Cytomx Therapeutics; San 

Francisco, CA: eCPX library) which contains approximately 3 × 1010 members was screened for clones that display PA 

binding peptides The random library is first grown in 500 mL LB media containing 25 μg/mL chloramphenicol (LBCm25) to an OD600nm of approximately 0.6 (Eppendorf Biophotometer; Eppendorf, Hamburg, Germany). At this point in 

exponential growth phase the cells were induced by the addition of arabinose to a final concentration of 0.04% (w/v); the 

enhanced circularly permuted OmpX (eCPX) gene expressing the library peptides is under the control of an arabinose 

inducible promoter (Rice, 2008). The cells were shaken at 37 °C for an additional 45 mins, after which the OD600nm was 

again measured and, using the assumption that an OD600nm of 1.0 relates to a bacterial concentration of 1 x 109 cfu/mL, 

approximately 2 x 1011 cells were pelleted by centrifugation at 3000g for 20 mins. 

2.4 PA-binder enrichment 

The SA-binder depleted library was centrifuged at 3000 g for 20 mins, resuspended in 1mL phosphate buffered saline 

with 0.5% bovin serum albumin (PBSB) buffer containing 600 nM biotinylated protective antigen, PA, (List Biological 

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Laboratories, Inc; Campbell, CA), and incubated at 4 oC for 45 mins. Cells were centrifuged as above and re-suspended 

in 1 mL PBSB buffer with 1 x 109 pre-washed magnetic beads. After 45 mins at 4 oC with rotation, the cell-beads 

suspension was loaded into an MMS cartridge (or separated by manual MACS using the same methods as SA binder 

depletion). Bacterial cells bound to PA were trapped on cartridge, and then eluted into a collection vessel. A second 

round of sorting was performed following the same protocol as the first; however, the assay parameters were adjusted to 

account for the smaller starting population and to increase the selection pressure in the second round, therefore 1 x 108

cells in 50 μL of 300 nM PA and 1 x 108 magnetic beads were used. Cells were incubated static on ice for all labeling 

steps. Also, 1 μM biotin was added in the washing buffer to compete with any remaining streptavidin binders (peptides 

which bind to streptavidin typically have a much lower affinity than biotin). In the third round of MMS sorting, cells 

were labeled with 150 nM biotinylated PA, and then labeled with 1 x 106 magnetic beads in 50 μL of PBSB. After each 

round of magnetic separation, the bead-bound enriched library was added to LB-Cm25 media supplemented with 0.2% 

glucose to inhibit expression of the eCPX gene and therefore prevent growth bias. The cultures were then grown 

overnight at 37 oC with shaking. 

2.5 Flow Cytometry Analysis of Binder Enrichment 

To quantify the library enrichment of potential PA binders, flow cytometry analysis (BD FACSAria; BD Biosciences, 

Franklin Lakes, NJ) was performed using biotinylated PA (EZ-Link Sulfo-NHS biotinylation kit; Thermo Scientific, 

Rockford, IL) labeled with alternating fluorescent secondary labels: streptavidin, R-phycoerythrin conjugate (SAPE; 

Invitrogen, Carlsbad, CA), and Neutravidin, R-phycoerythrin conjugate (NAPE; Invitrogen, Carlsbad, CA). Following 

each round of PA selection, the arabinose induced cell population was incubated with 100 nM biotin-PA solution for 45 

mins. The sample was centrifuged at 3000 x g for 10 mins to remove unbound biotin-PA and was resuspended in a 25 

L solution of PBSB with secondary label concentration of 5 g/mL and incubated for 45 mins at 4 oC. The sample was 

centrifuged and resuspended in 1 mL ice-cold BD FACSFlow (BD Biosciences, Franlin Lakes, NJ) sheath immediately 

prior to flow cytometry. Cells labeled with SAPE exhibit increased red fluorescence and are easily distinguishable by 

flow cytometry. 

3. RESULTS AND DISCUSSION

Previously, we demonstrated the effectiveness eCPX technology for bacterial library sorting and the capability of 

automating the selection using the micromagnetic sorter (MMS) platform1. Advantages to this approach include 

reproducible reagent isololation in a disposable cartridge format to avoid exposure to potentially harmful threat materials 

under investigation. For a typical 1 mL sample volume, MMS requires only 5 mins of user interaction, while manual 

selection requires more than 20 mins. With reagent sorting, there are three key parameters that are critical to evaluate 

with the first being throughput, i.e. how many cells can be sorted per second. The MMS platform achieves high 

throughput screening since it is capable of screening a bacterial library containing 3 × 1010 members in 15 mins. With 

regard to gross throughput per hour, MMS is able to process 5 × 1012 cells/hr (50 mL/hr at a cell concentration of 1 x 

1011 cells/mL), which is four orders of magnitude higher than that achieved using state-of-art FACS instrumentation or a 

previously reported dielectrophoretic cell sorter.1 In this work, we compare peptide reagent candidates produced by the 

MMS sorter platform for targeting PA from Bacillus anthracis, and enterotoxin B from Staphylococcus aureus (SEB) in 

terms of binding affinity and specificity with specific focus on streptavidin cross-reactivity. We also show initial results 

on multi-scale docking simulations using the ARL XPairIt program developed in-house.

The importance of both affinity and specificity characterization is illustrated in Figure 3. In Figure 3a and d, flow 

cytometry analysis shows the negative control population. In figures 3b and 3e, a positive response to PA is clearly 

evident for both peptide reagent candidates. In figures 3c and f, the cross-reactivity with streptavidin is compared, and 

SM545 was found to have significantly more cross-reactivity with the PA target. In all cases the binding population is 

indicated in red and the overall percentage of the population determined as binding to the target or interferent is given. It 

is clear that there is very little binding to the cell or library scaffold itself, designated as the negative control panels 3a) 

and 3d) for the DS-28 and SM545 binders, respectively. It is clear upon examination of panels 5b and 5e, that both DS28 and SM545 exhibit marked binding to the protective antigen target, with the SM545 binder exhibiting superior 

performance (95.4 % binding). Negative sorting is performed during the selection process to remove potentially crossreactivity with the bead chemistry used for reagent isolation. However, it is necessary to evaluate the degree of crossreactivity for any isolated reagent to have practical relevance. Figure 5 c and f show the cross-reactivity to streptavidin 

Proc. of SPIE Vol. 8358 83580A-5

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I

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for the clones DS-28 and SM545, respectively. From these data it is clear that both clones exhibit cross-reactivity to 

streptavidin and in the case of DS-28, the binding population to streptavidin is even greater than that to the target. The 

binding to the target PA over the streptavidin is significantly greater, however, for the SM545 clone at 95.4% (PA) and 

24% (Streptavidin). 

Figure 3: Flow cytometry analysis of two peptide reagent candidates designated DS-28 (a, b, c) and SM545, 

designated d, e, f. The binding to the cell scaffold alone is illustrated in a) for DS-28 and d) for SM545. The 

binding to the PA target is illustrated in b and c and c) and f) represents the fraction which binds to streptavidin. 

In all panels, the binding population is indicated in red.

Through a streptavidin pre-sort, we are able to cleanse the binder population of significant streptavidin binding and have 

adopted this streptavidin depletion coupled with in silico optimization of binding affinity subsequent to selection as a 

general strategy for development of both specific and high affinity peptide reagent candidates. An example of the 

improved specificity for PA is shown in Figure 4, upon comparison of the FACS characterization of clone DS23 

produced from the pre-sorted library binding to PA (4a) and Streptavidin (4b). The percent of the population binding was 

calculated to be 68.8% and 1.6% for PA and Streptavidin, a marked improvement in specificity. 

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p5

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Figure 4: Flow cytometry analysis of the DS-23 anti-PA reagent candidate produced after a streptavidin presorting . Panel (4a) shows 68.8% binding to PA, and panel (4b) shows minimal cross-reactivity to streptavidin

(1.6%). In all panels, the binding population is indicated in red.

Recent results routinely demonstrate peptide SREs with excellent specificity determined by evaluating relative binding 

to a cross-reactivity panel using flow cytometry and SPR analysis and we are currently extending reagent development 

to several toxin threats including Staphylococcal enterotoxin B (SEB). SEB is a 29-kDa superantigen and is one of the 

seven enterotoxins of Staphyloccocus aureus and is one of the most well understood and well studied staph 

enterotoxins.5 Detection of the staphyloccocal enterotoxins in food is critical since food poisoning is often caused by 

enteric exposure of these enterotoxins, resulting in emesis and diarrhea12. In Figure 5(a), flow cytometry 

characterization of an isolated clone (peptide reagent candidate) shows a high binding affinity (Kd ~15 nm). The 

outstanding specificity that uniquely characterizes our SRE methodology is clearly evident upon comparison of relative 

binding to the SEB target and example protein from the cross-reactivity panel in Figure 5 (b) and (c), respectively. 

Figure 5: SEB toxin synthetic reagent performance characterization including a) Peptide binding study to 150 

nM SEB showing ~15 nm Kd binding affinity, Inset: representation of SEB protein toxin (b) FACS analysis of 

peptide shows 99.7% binding of the reagent population to the target (orange), compared to the control (blue), 

and (c) FACS analysis shows minimal cross-reactivity (<1%) of the population to an equivalent concentration 

of protective antigen

Over the past year we have expanded our experimental success to include development of an integrative and iterative 

modeling capability to rapidly predict smart peptide binders for a target protein. Through the ARL developed XpairIt 

toolkit we have advanced the state-of-the-art in docking simulations incorporating a range of simulation methods to 

enable a more accurate assessment of protein-peptide interactions, ultimately providing predictive capability. The current 

computational suite combines a python-based application programming interface developed in-house, combined with 

state-of-the-art external software (VMDTM, NAMDTM,& PyRosettaTM). 

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Figure 6: Atomistic level elucidation of binding mode enables a priori design of improved binders in future 

development rounds.

Figure 6 shows a peptide docked to protective antigen using the XPairIt simulator. The XPairIt Simulator (Version 2) 

was used to perform a blind test to predict and analyze the structure of a peptide synthetic reagent with the Anthrax PA 

bound complex. The simulation results highlight binding on domain 2 of the PA protein a priori, which were found to 

concur with experiment (data not shown). Simulation of the peptide-PA system was carried out with no knowledge of 

peptide secondary structure or binding location, a task notoriously difficult for other docking software. Figure 3 shows 

an example of the docked peptide with protective antigen after simulation. With the molecular dynamics and custom 

sampling methodology contained in XPairIt, the bound complex displayed an average interface energy increase of more 

than two-fold, and the frequency of hydrogen bonding increased by 26-fold when compared to standard Rosetta docking. 

The final XPairit simulator under development will include additional quantum mechanics, coarse graining and 

improved treatment of electrostatics. This is the first freeware, HPC-ready, extensible, biologically oriented multiscale 

modeling toolkit. The code is suitable for study of peptide-protein and protein-protein interactions and extensible to a 

variety of DoD applications (medical and non-medical).

4. CONCLUSION

To conclude, we highlight in this paper our approach to synthetic peptide reagent production based on bacterial display 

technology. We use a combination of semi-automated sorting and extensive characterization of relative binding affinity 

and specificity to isolate clones (i.e., peptide reagent candidates) with tailored binding performance. Biopanning,

fundamentally is an affinity driven selection process. It is not surprising that peptide reagent candidates, and synthetic 

reagent candidates developed by similar methods such as phage display, are often characterized as high affinity binders, 

but are not very specific. In particular, “over-sorting” the library to yield only the highest binder affinity candidates is 

likely to yield these results. We have initiated the development of a multi-scale simulation toolkit capable of a priori 

docking simulations to enable in-silico screening of binder candidates, and ultimately predictions of new binder 

candidates with improved performance through in silico mutations. This coupled with discovery methodologies which 

favor specificity should ultimately allow development and evolution of reagents which satisfy stringent affinity and 

specificity performance requirements. 

5. ACKNOWLEDGEMENTS

This project receives support from the Defense Threat Reduction Agency Joint Science and Technology Office for 

Chemical and Biological Defense (Grant no. BRCALL08-Per3-P-2-0028). Research is also supported in part by 

appointments to the U.S. Army Research Laboratory Postdoctoral Fellowship Program administered by the Oak Ridge 

Associated Universities through a contract with the U.S. Army Research Laboratory. NAMD was developed by the 

Theoretical and Computational Biophysics Group in the Beckman Institute for Advanced Science and Technology at the 

University of Illinois at Urbana-Champaign. Images were generated using VMD.

Proc. of SPIE Vol. 8358 83580A-8

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6. REFERENCES 

[1] J. M. Kogot, Y. Zhang, S. J. Moore et al., “Screening of Peptide Libraries against Protective Antigen of 

Bacillus anthracis in a Disposable Microfluidic Cartridge,” Plos One, 6(11), (2011).B. Alberts, A. Johnson, J. 

Lewis et al., [Molecular Biology of the Cell] Garland Science, Taylor & Francis Group, LLC, New 

York(2008). 

[2] D. Stratis-Cullum, J. Kogot, D. Sarkes et al., [Bacterial Display Peptides for Use in Biosensing Applications] 

Intech, (2011). 

[3] L. J. Sooter, D. N. Stratis-Cullum, et al., [Hand Held Biowarfare Assays: Rapid Biowarfare Detection Using the 

Combined Attributes of Microfluidic in vitro Selections and Immunochromatographic Assays] ACS Pub.(2008). 

[4] J. J. Rice, and P. S. Daugherty, “Directed evolution of a biterminal bacterial display scaffold enhances the 

display of diverse peptides,” Protein Eng Des Sel, 21(7), 435-42 (2008). 

[5] J. M. Kogot, D. A. Sarkes, I. Val-Addo et al., “Increased affinity and solubility of peptides used for direct 

peptide ELISA on polystyrene surfaces through fusion with a polystyrene-binding peptide tag,” Biotechniques,

52(2), 95-102. 

[6] R. G. Ulrich, S. Sidell, T. J. Taylor et al., [Staphylococcal Enterotoxin B and Related Pyrogenic Toxins] Office 

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