Advancing Peptide-Based Biorecognition Elements for Biosensors Using in-Silico Evolution

Xingqing Xiao, Zhifeng Kuang, Joseph M. Slocik, Sirimuvva Tadepalli, Michael Brothers, Steve Kim, Peter A. Mirau, Claire Butkus, Barry L. Farmer, Srikanth Singamaneni, Carol K. Hall, Rajesh R. Naik

Research output: Contribution to journalArticlepeer-review

37 Scopus citations


Sensors for human health and performance monitoring require biological recognition elements (BREs) at device interfaces for the detection of key molecular biomarkers that are measurable biological state indicators. BREs, including peptides, antibodies, and nucleic acids, bind to biomarkers in the vicinity of the sensor surface to create a signal proportional to the biomarker concentration. The discovery of BREs with the required sensitivity and selectivity to bind biomarkers at low concentrations remains a fundamental challenge. In this study, we describe an in-silico approach to evolve higher sensitivity peptide-based BREs for the detection of cardiac event marker protein troponin I (cTnI) from a previously identified BRE as the parental affinity peptide. The P2 affinity peptide, evolved using our in-silico method, was found to have â16-fold higher affinity compared to the parent BRE and â10 fM (0.23 pg/mL) limit of detection. The approach described here can be applied towards designing BREs for other biomarkers for human health monitoring.

Original languageEnglish
Pages (from-to)1024-1031
Number of pages8
JournalACS Sensors
Issue number5
StatePublished - May 25 2018


  • LSPR
  • biorecognition elements
  • biosensor
  • computational modeling
  • phage displayed peptides
  • troponin I


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