Molecular Modeling Strategies of Cancer Multidrug Resistance

Gozde Yalcin-Ozkat1

  • 1Recep Tayyip Erdogan University, Faculty of Engineering and Architecture, Bioengineering Department, 53100, Rize, Turkey; Max Planck Institute for Dynamics of Complex Technical Systems, Molecular Simulations and Design Group, Sandtorstrasse 1, 39106, Magdeburg, Germany.

Insights

Computational methods accelerate the development of new anticancer drugs by investigating multidrug resistance (MDR) efflux transporters. This review focuses on molecular modeling techniques and in silico tools used between 2019-2021 to combat cancer MDR.

Area of Science:

  • Oncology
  • Computational Chemistry
  • Pharmacology

Background:

  • Multidrug resistance (MDR) remains a significant obstacle in cancer therapy.
  • ATP-binding cassette (ABC) transporters are key mediators of MDR.
  • Developing novel therapeutic agents to overcome MDR is crucial.

Purpose of the Study:

  • To review computational drug development studies focused on MDR efflux transporters, specifically ABC superfamily proteins.
  • To summarize molecular modeling methods and in silico tools applied between 2019-2021.
  • To provide a guide for researchers in computational drug discovery for cancer MDR.

Main Methods:

  • Literature review of computational studies on MDR reversal.
  • Analysis of molecular modeling techniques: homology modeling, quantum mechanics, molecular docking, molecular dynamics, and QSAR.
  • Investigation of in silico ADME/Tox and drug repurposing studies.
  • Evaluation of licensed applications and free web servers for in silico studies.

Main Results:

  • Molecular modeling significantly accelerates the identification and development of novel anticancer drugs targeting ABC transporters.
  • Homology modeling is vital for efflux transporters lacking experimental 3D structures.
  • QSAR and in silico ADME/Tox studies aid in predicting drug efficacy and safety.

Conclusions:

  • Computational approaches, including molecular modeling and in silico tools, are indispensable for overcoming cancer multidrug resistance.
  • This review highlights recent advancements and resources for researchers in the field.
  • Further application of these methods can lead to more effective cancer therapies.

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