Exploring the Binding Pattern of Geraniol with Acetylcholinesterase through In Silico Docking, Molecular Dynamics Simulation, and In Vitro Enzyme Inhibition Kinetics Studies

Acetylcholinesterase (AChE) inhibition is a key element in enhancing cholinergic transmission and subsequently relieving major symptoms of several neurological and neuromuscular disorders. Here, the inhibitory potential of geraniol and its mechanism of inhibition against AChE were elucidated in vitro and validated via an in silico study. Our in vitro enzyme inhibition kinetics results show that at increasing concentrations of geraniol and substrate, Vmax did not change significantly, but Km increased, which indicates that geraniol is a competitive inhibitor against AChE with an IC50 value 98.06 ± 3.92 µM. All the parameters of the ADME study revealed that geraniol is an acceptable drug candidate. A docking study showed that the binding energy of geraniol (−5.6 kcal mol−1) was lower than that of acetylcholine (−4.1 kcal mol−1) with AChE, which exhibited around a 12.58-fold higher binding affinity of geraniol. Furthermore, molecular dynamics simulation revealed that the RMSD of AChE alone or in complex with geraniol fluctuated within acceptable limits throughout the simulation. The mean RMSF value of the complex ensures that the overall conformation of the protein remains conserved. The average values of Rg, MolSA, SASA, and PSA of the complex were 3.16 Å, 204.78, 9.13, and 51.58 Å2, respectively. We found that the total SSE of AChE in the complex was 38.84% (α-helix: 26.57% and β-sheets: 12.27%) and remained consistent throughout the simulation. These findings suggest that geraniol remained inside the binding cavity of AChE in a stable conformation. Further in vivo investigation is required to fully characterize the pharmacokinetic properties, optimization of dose administration, and efficacy of this plant-based natural compound.

A Quantitative Study of Sr2+ Impact on Barite Crystallization and Inhibition Kinetics

Scale inhibitors have been widely used for barite scale control. Our group has developed several barite crystallization and inhibition models to predict the crystallization and inhibition kinetics of pure barite with different inhibitors and calculate the minimum inhibitor concentration (MIC) required. However, instead of pure barite scale formation, the incorporation of Sr2+ can be frequently found in the oilfield, because of the coexistence of Ba2+ and Sr2+ in the produced water, which can influence the kinetics of crystallization and inhibition significantly. As a result, the MIC predicted could be off significantly. Therefore, in this study, the effect of Sr2+ on barite crystallization and inhibition kinetics is quantitatively investigated to evaluate the accuracy of MIC values under various conditions. The induction time of barite with different concentrations of Sr2+ was measured by laser apparatus without or with different concentrations of scale inhibitor diethylenetriamine penta(methylene phosphonic acid) (DTPMP) at the conditions: barite saturation index (SI) from 1.5 to 1.8; temperature (T) from 40 to 70 ℃; and [Sr2+]/[Ba2+] molar ratios from 0 to 15, all with celestite SI < 0. The results show that the induction time of the barite increases with [Sr2+]/[Ba2+] ratio at a fixed barite SI, T and DTPMP dosage. That means the MIC will be overestimated if it is calculated by previous semiempirical pure barite crystallization and inhibition models, without considering the presence of Sr2+. Based on the experimental results, the novel quantitative barite crystallization and inhibition models that include the influence of Sr2+ were developed for the first time as follows: Barite crystallization model with the influence of Sr2+: l o g 10 t 0 B a S O 4 , S r = ( 1.523 − 10.88 S I − 895.67 T ( K ) + 5477 S I × T ( K ) + 0.829 × [ C a 2 + ] ) + ( 0.823 S I + 85.44 T ( K ) − 0.667 ) × ( [ Sr 2 + ] [ B a 2 + ] ) Barite inhibition model including the influence of Sr2+ l o g 10 ( t i n h B a s o 4 , S r t 0 B a S O 4 , S r ) = b B a S O 4 , S r × C i n h l o g 10 b B a S O 4 , S r = ( − 2.187 − 1.411 × S I + 1329.29 T ( K ) + 0.153 × p H ) + ( 0.0983 × S I − 74.66 T ( K ) + 0.099 ) × ( [ Sr 2 + ] [ B a 2 + ] ) These novel models are in good agreement with the experimental data. They are used to predict the induction time and MIC more accurately at these common Ba2+ and Sr2+ coexisting scenarios. The observations and new models proposed in this study will significantly improve the barite scale management when Ba2+ and Sr2+ coexist in the oilfield.