title: New approach to develop ultra-high inhibitory drug using the power function of the stoichiometry of the targeted nanomachine or biocomplex.
abstract: OBJECTIVE
  To find methods for potent drug development by targeting to biocomplex with high copy number.
  
  
  METHODS
  Phi29 DNA packaging motor components with different stoichiometries were used as model to assay virion assembly with Yang Hui's Triangle [Formula: see text], where Z = stoichiometry, M = drugged subunits per biocomplex, p and q are the fraction of drugged and undrugged subunits in the population.
  
  
  RESULTS
  Inhibition efficiency follows a power function. When number of drugged subunits to block the function of the complex K = 1, the uninhibited biocomplex equals q(z), demonstrating the multiplicative effect of stoichiometry on inhibition with stoichiometry 1000 > 6 > 1. Complete inhibition of virus replication was found when Z = 6.
  
  
  CONCLUSIONS
  Drug inhibition potency depends on the stoichiometry of the targeted components of the biocomplex or nanomachine. The inhibition effect follows a power function of the stoichiometry of the target biocomplex.
authors.affiliation: Department of Pharmaceutical Sciences, Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA.
authors.forename: Dan
authors.initials: D
authors.lastname: Shu
authors.affiliation: Department of Pharmaceutical Sciences, Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA.
authors.forename: Fengmei
authors.initials: F
authors.lastname: Pi
authors.affiliation: Department of Biostatistics & Nanobiotechnology Center, University of Kentucky, Lexington, KY 40536, USA.
authors.forename: Chi
authors.initials: C
authors.lastname: Wang
authors.affiliation: Department of Surgery, University of Michigan Health System, Ann Arbor, MI 48109, USA.
authors.forename: Peng
authors.initials: P
authors.lastname: Zhang
authors.affiliation: Department of Pharmaceutical Sciences, Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA.
authors.forename: Peixuan
authors.initials: P
authors.lastname: Guo
mesh_terms: D000251:Adenosine Triphosphatases / Q000037:antagonists & inhibitors*; D000465:Algorithms; D003198:Computer Simulation; D042003:DNA Packaging; D004279:DNA, Viral / Q000737:chemistry*; D015195:Drug Design; D008956:Models, Chemical; D020409:Molecular Motor Proteins / Q000737:chemistry; D053758:Nanoparticles / Q000737:chemistry*; D011485:Protein Binding; D017434:Protein Structure, Tertiary; D019065:Virus Assembly
chemical_list: D004279:DNA, Viral; D020409:Molecular Motor Proteins; D000251:Adenosine Triphosphatases
keywords: binomial distribution; bionanotechnology; drug target; hexameric ATPase; nanobiotechnology; nanomotor; phi29 viral assembly