Binding Analysis Using Accelerated Molecular Dynamics Simulations and Future Perspectives

Applications of Molecular Dynamics Simulations in Drug Discovery

In the current drug development process, molecular dynamics (MD) simulations have proven to be very useful. This chapter provides an overview of the current applications of MD simulations in drug discovery, from detecting protein druggable sites and validating drug docking outcomes to exploring protein conformations and investigating the influence of mutations on its structure and functions. In addition, this chapter emphasizes various strategies to improve the conformational sampling efficiency in molecular dynamics simulations. With a growing computer power and developments in the production of force fields and MD techniques, the importance of MD simulations in helping the drug development process is projected to rise significantly in the future.

Molecular Dynamics as a Tool for Virtual Ligand Screening

Rational drug design is essential for new drugs to emerge, especially when the structure of a target protein or nucleic acid is known. To that purpose, high-throughput virtual ligand screening campaigns aim at discovering computationally new binding molecules or fragments to modulate particular biomolecular interactions or biological activities, related to a disease process. The structure-based virtual ligand screening process primarily relies on docking methods which allow predicting the binding of a molecule to a biological target structure with a correct conformation and the best possible affinity. The docking method itself is not sufficient as it suffers from several and crucial limitations (lack of full protein flexibility information, no solvation and ion effects, poor scoring functions, and unreliable molecular affinity estimation).At the interface of computer techniques and drug discovery, molecular dynamics (MD) allows introducing protein flexibility before or after a docking protocol, refining the structure of protein-drug complexes in the presence of water, ions, and even in membrane-like environments, describing more precisely the temporal evolution of the biological complex and ranking these complexes with more accurate binding energy calculations. In this chapter, we describe the up-to-date MD, which plays the role of supporting tools in the virtual ligand screening (VS) process.Without a doubt, using docking in combination with MD is an attractive approach in structure-based drug discovery protocols nowadays. It has proved its efficiency through many examples in the literature and is a powerful method to significantly reduce the amount of required wet experimentations (Tarcsay et al, J Chem Inf Model 53:2990-2999, 2013; Barakat et al, PLoS One 7:e51329, 2012; De Vivo et al, J Med Chem 59:4035-4061, 2016; Durrant, McCammon, BMC Biol 9:71-79, 2011; Galeazzi, Curr Comput Aided Drug Des 5:225-240, 2009; Hospital et al, Adv Appl Bioinforma Chem 8:37-47, 2015; Jiang et al, Molecules 20:12769-12786, 2015; Kundu et al, J Mol Graph Model 61:160-174, 2015; Mirza et al, J Mol Graph Model 66:99-107, 2016; Moroy et al, Future Med Chem 7:2317-2331, 2015; Naresh et al, J Mol Graph Model 61:272-280, 2015; Nichols et al, J Chem Inf Model 51:1439-1446, 2011; Nichols et al, Methods Mol Biol 819:93-103, 2012; Okimoto et al, PLoS Comput Biol 5:e1000528, 2009; Rodriguez-Bussey et al, Biopolymers 105:35-42, 2016; Sliwoski et al, Pharmacol Rev 66:334-395, 2014).

Ligand Gaussian Accelerated Molecular Dynamics 2 (LiGaMD2): Improved Calculations of Ligand Binding Thermodynamics and Kinetics with Closed Protein Pocket

Ligand binding thermodynamics and kinetics are critical parameters for drug design. However, it has proven challenging to efficiently predict ligand binding thermodynamics and kinetics from molecular simulations due to limited simulation timescales. Protein dynamics, especially in the ligand binding pocket, often plays an important role in ligand binding. Based on our previously developed Ligand Gaussian accelerated molecular dynamics (LiGaMD), here we present LiGaMD2 in which a selective boost potential was applied to both the ligand and protein residues in the binding pocket to improve sampling of ligand binding and dissociation. To validate the performance of LiGaMD2, the T4 lysozyme (T4L) mutants with open and closed pockets bound by different ligands were chosen as model systems. LiGaMD2 could efficiently capture repetitive ligand dissociation and binding within microsecond simulations of all T4L systems. The obtained ligand binding kinetic rates and free energies agreed well with available experimental values and previous modeling results. Therefore, LiGaMD2 provides an improved approach to sample opening of closed protein pockets for ligand dissociation and binding, thereby allowing for efficient calculations of ligand binding thermodynamics and kinetics.

Potential Use of Tea Tree Oil as a Disinfectant Agent against Coronaviruses: A Combined Experimental and Simulation Study

The COVID-19 pandemic has highlighted the relevance of proper disinfection procedures and renewed interest in developing novel disinfectant materials as a preventive strategy to limit SARS-CoV-2 contamination. Given its widely known antibacterial, antifungal, and antiviral properties, Melaleuca alternifolia essential oil, also named Tea tree oil (TTO), is recognized as a potential effective and safe natural disinfectant agent. In particular, the proposed antiviral activity of TTO involves the inhibition of viral entry and fusion, interfering with the structural dynamics of the membrane and with the protein envelope components. In this study, for the first time, we demonstrated the virucidal effects of TTO against the feline coronavirus (FCoVII) and the human coronavirus OC43 (HCoV-OC43), both used as surrogate models for SARS-CoV-2. Then, to atomistically uncover the possible effects exerted by TTO compounds on the outer surface of the SARS-CoV-2 virion, we performed Gaussian accelerated Molecular Dynamics simulations of a SARS-CoV-2 envelope portion, including a complete model of the Spike glycoprotein in the absence or presence of the three main TTO compounds (terpinen-4-ol, γ-terpinene, and 1,8-cineole). The obtained results allowed us to hypothesize the mechanism of action of TTO and its possible use as an anti-coronavirus disinfectant agent.

ADP-Induced Conformational Transition of Human Adenylate Kinase 1 Is Triggered by Suppressing Internal Motion of α3α4 and α7α8 Fragments on the ps-ns Timescale

Human adenylate kinase 1 (hAK1) plays a vital role in the energetic and metabolic regulation of cell life, and impaired functions of hAK1 are closely associated with many diseases. In the presence of Mg²⁺ ions, hAK1 in vivo can catalyze two ADP molecules into one ATP and one AMP molecule, activating the downstream AMP signaling. The ADP-binding also initiates AK1 transition from an open conformation to a closed conformation. However, how substrate binding triggers the conformational transition of hAK1 is still unclear, and the underlying molecular mechanisms remain elusive. Herein, we determined the solution structure of apo-hAK1 and its key residues for catalyzing ADP, and characterized backbone dynamics characteristics of apo-hAK1 and hAK1-Mg²⁺-ADP complex (holo-hAK1) using NMR relaxation experiments. We found that ADP was primarily bound to a cavity surrounded by the LID, NMP, and CORE domains of hAK1, and identified several critical residues for hAK1 catalyzing ADP including G16, G18, G20, G22, T39, G40, R44, V67, D93, G94, D140, and D141. Furthermore, we found that apo-hAK1 adopts an open conformation with significant ps-ns internal mobility, and Mg²⁺-ADP binding triggered conformational transition of hAK1 by suppressing the ps-ns internal motions of α₃α₄ in the NMP domain and α₇α₈ in the LID domain. Both α₃α₄ and α₇α₈ fragments became more rigid so as to fix the substrate, while the catalyzing center of hAK1 experiences promoted µs-ms conformational exchange, potentially facilitating catalysis reaction and conformational transition. Our results provide the structural basis of hAK1 catalyzing ADP into ATP and AMP, and disclose the driving force that triggers the conformational transition of hAK1, which will deepen understanding of the molecular mechanisms of hAK1 functions.

Molecular Simulations and Drug Discovery of Adenosine Receptors

G protein-coupled receptors (GPCRs) represent the largest family of human membrane proteins. Four subtypes of adenosine receptors (ARs), the A1AR, A2AAR, A2BAR and A3AR, each with a unique pharmacological profile and distribution within the tissues in the human body, mediate many physiological functions and serve as critical drug targets for treating numerous human diseases including cancer, neuropathic pain, cardiac ischemia, stroke and diabetes. The A1AR and A3AR preferentially couple to the Gi/o proteins, while the A2AAR and A2BAR prefer coupling to the Gs proteins. Adenosine receptors were the first subclass of GPCRs that had experimental structures determined in complex with distinct G proteins. Here, we will review recent studies in molecular simulations and computer-aided drug discovery of the adenosine receptors and also highlight their future research opportunities.