Statistics for the analysis of molecular dynamics simulations: providing P values for agonist-dependent GPCR activation

Abstract

Molecular dynamics (MD) is the common computational technique for assessing efficacy of GPCR-bound ligands. Agonist efficacy measures the capability of the ligand-bound receptor of reaching the active state in comparison with the free receptor. In this respect, agonists, neutral antagonists and inverse agonists can be considered. A collection of MD simulations of both the ligand-bound and the free receptor are needed to provide reliable conclusions. Variability in the trajectories needs quantification and proper statistical tools for meaningful and non-subjective conclusions. Multiple-factor (time, ligand, lipid) ANOVA with repeated measurements on the time factor is proposed as a suitable statistical method for the analysis of agonist-dependent GPCR activation MD simulations. Inclusion of time factor in the ANOVA model is consistent with the time-dependent nature of MD. Ligand and lipid factors measure agonist and lipid influence on receptor activation. Previously reported MD simulations of adenosine A2a receptor (A2aR) are reanalyzed with this statistical method. TM6–TM3 and TM7–TM3 distances are selected as dependent variables in the ANOVA model. The ligand factor includes the presence or absence of adenosine whereas the lipid factor considers DOPC or DOPG lipids. Statistical analysis of MD simulations shows the efficacy of adenosine and the effect of the membrane lipid composition. Subsequent application of the statistical methodology to NECA A2aR agonist, with resulting P values in consistency with its pharmacological profile, suggests that the method is useful for ligand comparison and potentially for dynamic structure-based virtual screening.

Structural Assessment of Agonist Efficacy in the μ-Opioid Receptor: Morphine and Fentanyl Elicit Different Activation Patterns

“…The question arises which is the proper reference state for the system. Both the apo receptor and an antagonist-bound receptor may, in principle, be suitable for this purpose. We chose the latter condition because of the high stability of an antagonist-bound inactive receptor state, as well as the potential to deactivate an active receptor state to the inactive.…”

Molecular Mechanism of Methanol Inhibition in CALB-Catalyzed Alcoholysis: Analyzing Molecular Dynamics Simulations by a Markov State Model

“…The intensification of an enzyme-catalyzed reaction can be obtained by tuning a large number of parameters: feeding substrate at the optimal concentration, removal of product if the reaction is reversible or if product inhibition occurs, addition of co-solvents to increase substrate solubility and to prevent aggregation of the enzyme, using additives to improve thermal and solvent stability of the enzyme, increasing the temperature to improve catalytic activity, and enzyme engineering for improving activity, selectivity, and stability of the enzyme. MD simulation studies can support process design and optimization by exploring a physically meaningful subset of parameter space and by modeling the sensitivity of enzyme catalysis to reaction conditions. − For diluted systems, where substrate binding is dominated by the interaction between a single substrate molecule and the protein, free energy calculations by MD simulations and enhanced sampling techniques such as umbrella sampling methods provide reliable free energy profiles . The results can be transferred to finite bulk concentrations in the absence of any interference with the reaction mechanism. , However, at high substrate concentration, molecular crowding and substrate-induced conformational changes of the protein are expected, and substrate-interacting patches on the protein surface become saturated.…”

Theoretical causes of the Brazilian P.1 and P.2 lineages of the SARS-CoV-2 virus through molecular dynamics

“…This may be due mainly to the large sampling of data resulting from molecular dynamics, which tends to make statistically significant even very small variations. A similar approach is found in the literature that used ANOVA to study the impacts on the activation of the GPCR protein (Bruzzese, Dalton, & Giraldo, 2020). For this reason, we used the Student's t-test to confirm whether the differences in the conformational fluctuations of the P.2 strain are really significant.…”

“…This may be due mainly to the low sampling of data resulting from molecular dynamics, which tends to make statistically significant even very small variations. Despite of all, a statistical approach is found in the literature that used ANOVA to study the impacts on the activation of the GPCR protein (Bruzzese, Dalton, & Giraldo, 2020). It should be noted that the tests of statistical significance only make sense when running simulations at a time adequate to the studied problem.…”