Binding energy analysis and molecular dynamic simulation studies of the designed orally active, non-toxic GABARAP modulators

Abstract

Epilepsy is a severe neurological disorder that occurs when the communication between the neurons is disturbed. Gamma-amino butyric acid-associated protein (GABARAP) plays a key role in balancing Gamma-aminobutyric acid-A (GABA(A)) receptor functions of inhibiting the neurotransmission and controlling the seizure. In this study, we introduce the derivatives of the selected anti-epileptic drugs, namely Felbamate and Clobazam, by substituting different hydrophilic and hydrophobic groups at the specified positions. Molecular docking studies between the derivatives and GABARAP were carried out using PyRx software. The interacting residues were identified from LigPlot⁺. Drug-likeness, drug-related properties, and toxic endpoints of each derivative were analyzed using the SwissADME, Osiris property explorer, and ProTox-II servers. After analyzing the binding energy, drug-properties, and toxicity, the best five derivatives of Felbamate and Clobazam were selected. Molecular Dynamic simulation studies involving the target-ligand interaction were carried out for 100 nanoseconds using GROMACS 2018. The root mean square deviation, root mean square fluctuation, radius of gyration, Solvent accessible area, Energy plots and trajectories of the ten GABARAP complexes of the derivatives, and two GABARAP complexes of parent drugs were compared and critically analyzed. Among the five Felbamate derivatives, F7 formed the most stable complex with GABARAP. Among the five Clobazam derivatives, C27, C33 and C32 showed stable GABARAP interaction. In light of the above systematic computational analysis, we propose F7, C27, C33, and C32 as the potential anti-epileptic drug candidates for developing novel therapeutics. The substitution of hydrophobic groups at para position on benzene ring has promoted strong binding to GABARAP.

Communicated by Ramaswamy H. Sarma

KEYWORDS:

• GABARAP
• GABA(A)
• molecular docking
• drug-likeness molecular dynamic simulation
• trajectories

Acknowledgments

ARB acknowledges the support of Management, Sir Syed College for the ‘Sahayog’ Project funds. The authors are thankful to the Department of Chemistry, Sir Syed College, Taliparamba-670141, Kannur, Kerala, for all the support. The authors acknowledge the support of DST, FIST, and Ajit Balakrishnan (CEO, Rediff.com) foundation. The authors acknowledge the Supercomputing facility ‘PARAM Shakti’ at the IIT Kharagpur established under National Supercomputing Mission (NSM), Government of India

Disclosure statement

No potential conflict of interest was reported by the authors.

Ethics

This work is purely computational. No studies involving animals and humans are done in this work, by any of the authors.

Author contributions

All authors have approved the final version of the manuscript.

Additional information

Funding

ARB acknowledges the support of Management, Sir Syed College for the ‘Sahayog’ Project funds.