Evaluation of the Key Structural Features of Various Butyrylcholinesterase Inhibitors Using Simple Molecular Descriptors

Abstract

In this study, we developed several QSAR models based on simple descriptors (such as topological and constitutional) to estimate butyrylcholinesterase (BChE) inhibition potency, pKi (or pIC50), of a set of 297 (289 after exclusion of outliers) structurally different compounds. The models were similar to the best model that we obtained previously for acetylcholinesterase AChE and were based on the valence molecular connectivity indices of second and third order (2χv and 3χv), the number of aliphatic hydroxyl groups (nOH), AlogP Ghose–Crippen octanol–water partition coeff. (logP), and O-060–atom-centred fragments (Al-O-Ar, Ar-O-Ar, R..O..R and R-O-C=X). The best models with two and three descriptors yielded r = 0.787 and S.E. = 0.89, and r = 0.827 and S.E. = 0.81, respectively. We also correlated nine scoring functions, calculated for 20 ligands whose complexes with BChE we found in the Protein Data Bank as crystal structures to pKi (or pIC50). The best correlations yielded PLP1 and PLP2 (Piecewise Linear Pairwise potential functions) with r = 0.619 and 0.689, respectively. Correlation with certain simple topological and constitutional descriptors yielded better results, e.g., 3χv (r = 0.730), on the same set of compounds (N = 20).

Evaluation of Anticholinesterase Activity of the Fungicides Mefentrifluconazole and Pyraclostrobin

“…The scores derived from the scoring functions for each ligand were correlated to its inhibition constant. The average score value for set of 20 BChE ligands was 59 ± 12 kcal/mol [ 39 ].…”

“…The predictive power of the model with only three simple descriptors was tested and confirmed on 165 compounds in total. Moreover, the QSAR regression model for BChE developed on a set of 297 compounds also with three simple descriptors, different from those for the AChE model, showed the same level of predictive power [ 39 ]. The approach of multi-target drug development (MTDD) is based on the idea that compounds interacting with more than one biological target cause the balance of wanted activities to maximize efficacy and safety.…”

“…The final fungicide poses were ranked by scores derived by scoring functions CDOCKER Energy and CDOCKER Interaction Energy. Details about ligand docking using the CDOCKER protocol and subsequent scoring of generated ligand poses by CHARMm energy were described previously [ 39 , 53 ].…”

New Heterostilbene and Triazole Oximes as Potential CNS-Active and Cholinesterase-Targeted Therapeutics

“…The protocol based on a CHARMm force field generated 20 binding poses for each ligand, and scoring functions CDOCKER Energy and CDOCKER Interaction Energy were used to rank the obtained binding poses [ 63 , 64 ]. After an evaluation of poses and comparison to known crystal structures of AChE or BChE inhibitor complexes, we selected the final ones [ 65 ]. The crystal structures of human BChE and human AChE deposited in the Protein Data Bank, PDB code 2PM8 [ 42 ] and 4PQE [ 66 ], respectively, were used.…”

A Multivariate Interpolation Approach for Predicting Drug Ld50 Value

“…ALogP is employed to assess a compound's solubility in nonpolar solvents (e.g., octanol) and polar solvents (e.g., water) [18]. It provides information about the lipophilicity of a drug and its ability to permeate and accumulate in biological membranes.…”