Computational Modeling of antiepilepsy Perampanel: From Conformational Analysis to SERS Spectra

Computational Modeling of antiepilepsy Perampanel: From Conformational Analysis to SERS Spectra C. Picarelli1, N.S. Villa1,2, A. Lucotti1, M. Tommasini1, G. Raffaini1 1Dipartimento di Chimica, Materiali e Ingegneria Chimica “G. Natta”, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, Italy 2SYENSQO Eco-Efficient Products and Processes Laboratory (E2P2L), 3966 Jindu Rd. Xinzhuang Industrial Zone, Shanghai, 201108, China email: [email protected] Perampanel (PER) is an antiepileptic drug that requires strict dosage control due to potential side effects[1]. Alongside conventional Therapeutic Drug Monitoring (TDM), Raman and SERS spectroscopy have emerged as promising non-invasive techniques for detecting Perampanel in biological fluids[2][3]. However, a comprehensive theoretical model describing the molecular structure and vibrational features of Perampanel is lacking. In this work, we systematically explored the Potential Energy Surface (PES) of Perampanel using DFT methods (B3LYP/6-31G(d,p)). We identified its stable conformers, including one corresponding to the known receptor-bound structure [4]. For these conformers, we computed theoretical Raman and SERS spectra — the latter considering protonated species, in accordance with the acidic environment adopted in SERS experiments [5]. The good comparison of the simulated spectra vs. their experimental counterparts allows assigning the strongest features observed in Raman/SERS [5]. Furthermore, we analyzed MM/MD simulations in the gas phase via fast Fourier transform (FFT) to investigate molecular flexibility and mobility and reveal periodic internal motions. In particular, the FFT analysis of MD trajectories enabled the characterization of low-frequency torsional modes[6][7]. Finally, we investigated Perampanel adsorption and mobility on Au(100) and Au(111) surfaces, and we simulated the SERS spectra of adsorbed conformers, supporting the interpretation of experimental spectra and advancing Perampanel detection strategies. [1] T. Hanada, Expert opinion on drug discovery, vol. 9, no. 4, pp. 449–458, 2014. [2] J.-S. Kang and M.-H. Lee, The Korean Journal of internal medicine, vol. 24, no. 1, pp. 1–10, 2009. [3] D.-Y. Kim, J. Moon, Y.-W. Shin, et al., Epilepsia, vol. 61, no. 6, pp. 1120–1128, May 2020. [4] M.V. Yelshanskaya, A.K. Singh, J.M. Sampson, C. Narangoda, M. Kurnikova, and A.I. Sobolevsky, Neuron, vol. 91, no. 6, pp. 1305–1315, Sep. 2016. [5] N.S. Villa, C. Picarelli, F. Iacoe, C.G. Zanchi, P.M. Ossi, A. Lucotti, M. Tommasini, Molecules 2023, 28, 5968. [6] G. Raffaini, and F. Ganazzoli, Macromolecular Symposia. Vol. 411. No. 1. 2023. [7] G. Raffaini, Macromolecular Symposia, Vol. 404. No. 1. 2022.