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Structure-based discovery of novel ROCK2 inhibitors using integrated virtual screening, molecular dynamics,

Shradheya R R Gupta1, Rashmi Rameshwari1, Indrakant K Singh2,3,4

  • 1Department of Biotechnology, School of Engineering and Technology (SET), Manav Rachna International Institute of Research and Studies (MRIIRS), Faridabad, Haryana 121004 India.

In Silico Pharmacology
|August 19, 2026
PubMed

Insights

This study identifies novel Rho-associated kinase 2 (ROCK2) inhibitors using computational methods. Two lead compounds, ASN52 and Selles74, show strong binding potential for breast cancer therapy.

Area of Science:

  • Biochemistry and Structural Biology
  • Computational Chemistry
  • Cancer Therapeutics

Background:

  • Breast cancer metastasis is a major cause of mortality.
  • Rho-associated kinase 2 (ROCK2) is crucial in cancer progression and cytoskeletal dynamics.
  • ROCK2 is a promising therapeutic target for breast cancer treatment.

Purpose of the Study:

  • To identify novel inhibitors of Rho-associated kinase 2 (ROCK2) using a structure-based computational approach.
  • To characterize the binding interactions and affinities of potential ROCK2 inhibitors.
  • To provide a computational basis for developing ROCK2-targeted cancer therapies.

Main Methods:

  • Virtual screening of over 1.5 million compounds against ROCK2.
  • Molecular mechanics/Generalized Born surface area (MM/GBSA) rescoring and molecular dynamics (MD) simulations.
  • Principal component analysis (PCA), free energy landscape mapping, and well-tempered metadynamics simulations.
  • Absolute Binding Free Energy Perturbation (ABFEP) calculations to estimate binding affinities.

Main Results:

  • Two lead compounds, ASN52 and Selles74, with synthetically accessible heterocyclic cores were identified.
  • Both compounds demonstrated stable interactions within the ROCK2 active site.
  • ASN52 showed a highly favorable binding conformation with a significant energetic minimum.
  • ABFEP calculations yielded binding free energies of -6.7 ± 1.27 kcal/mol for ASN52 and -6.15 ± 1.78 kcal/mol for Selles74.

Conclusions:

  • The study successfully identified potent ROCK2 inhibitors through a structure-based computational strategy.
  • ASN52 and Selles74 represent promising candidates for further preclinical development as breast cancer therapeutics.
  • The computational methodology is applicable to the discovery of various kinase inhibitors for cancer and other diseases.
Keywords:
ABFEPBreast cancerDynamic simulationInhibitorMetadynamicsROCK2

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