Affiliations 

  • 1 Advanced Medical & Dental Institute (AMDI), Universiti Sains Malaysia, Bertam, 13200, Kepala Batas, Penang, Malaysia
  • 2 Department of Mechanical Engineering, Columbia University, New York, NY, 10027, United States
  • 3 School of Medicine, Deakin University, Pigdons Road, Waurn Ponds, Victoria, 3216, Australia
  • 4 Advanced Medical & Dental Institute (AMDI), Universiti Sains Malaysia, Bertam, 13200, Kepala Batas, Penang, Malaysia. Electronic address: tangth@usm.my
  • 5 Advanced Medical & Dental Institute (AMDI), Universiti Sains Malaysia, Bertam, 13200, Kepala Batas, Penang, Malaysia; Department of Mechanical Engineering, Columbia University, New York, NY, 10027, United States. Electronic address: citartan@usm.my
Anal Biochem, 2020 07 01;600:113742.
PMID: 32315616 DOI: 10.1016/j.ab.2020.113742

Abstract

The performance of aptamers as versatile tools in numerous analytical applications is critically dependent on their high target binding specificity and selectivity. However, only the technical or methodological aspects of measuring aptamer-target binding affinities are focused, ignoring the equally important mathematical components that play pivotal roles in affinity measurements. In this study, we aim to provide a comprehensive review regarding the utilization of different mathematical models and equations, along with a detailed description of the computational steps involved in mathematically deriving the binding affinity of aptamers against their specific target molecules. Mathematical models ranging from one-site binding to multiple aptameric binding site-based models are explained in detail. Models applied in several different approaches of affinity measurements such as thermodynamics and kinetic analysis, including cooperativity and competitive-assay based mathematical models have been elaborately discussed. Mathematical models incorporating factors that could potentially affect affinity measurements are also further scrutinized.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.