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Nanomechanics of Drug-target Interactions and Antibacterial Resistance Detection
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Modelling proteins' hidden conformations to predict antibiotic resistance.

Kathryn M Hart1, Chris M W Ho1, Supratik Dutta2

  • 1Department of Biochemistry &Molecular Biophysics, Washington University School of Medicine, 660 South Euclid Avenue, St Louis, Missouri 63110, USA.

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|October 7, 2016
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TEM β-lactamase, an enzyme conferring antibiotic resistance, evolves new drug activities. This study uses Markov state models to reveal hidden protein shapes, improving drug specificity prediction and guiding the design of new antibiotic resistance drugs.

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Area of Science:

  • Biochemistry
  • Structural Biology
  • Computational Biology

Background:

  • TEM β-lactamase is a key enzyme in bacterial antibiotic resistance.
  • Its rapid evolution of activity against new antibiotics poses a significant challenge.
  • Existing crystal structures do not fully explain functional changes in TEM β-lactamase.

Purpose of the Study:

  • To identify hidden protein conformations of TEM β-lactamase using Markov state models (MSMs).
  • To explore the role of these conformations in determining enzyme specificity.
  • To develop a novel computational technique for predicting enzyme specificity.

Main Methods:

  • Application of Markov state models (MSMs) to identify hidden protein conformations.
  • Integration of MSMs with drug-design tools to create Boltzmann docking.
  • Experimental validation using rapid mass spectrometric footprinting.
  • Design and testing of novel enzyme variants.

Main Results:

  • MSMs identified hidden states correlating with cefotaxime activity.
  • Experimental data confirmed that increased cefotaxime activity correlates with reduced Ω-loop flexibility.
  • Designed variants stabilizing specific hidden states showed predictable activity against cefotaxime in vitro and in vivo.

Conclusions:

  • Hidden protein conformations play a crucial role in TEM β-lactamase specificity.
  • Boltzmann docking, integrating MSMs, enhances prediction of enzyme specificity by accounting for conformational heterogeneity.
  • This framework offers a promising approach for drug and protein design, particularly in combating antibiotic resistance.