Multi-Expression Programming (MEP): Water Quality Assessment Using Water Quality Indices

Water contamination is indeed a worldwide problem that threatens public health, environmental protection, and agricultural productivity. The distinctive attributes of machine learning (ML)-based modelling can provide in-depth understanding into increasing water quality challenges. This study presents the development of a multi-expression programming (MEP) based predictive model for water quality parameters, i.e., electrical conductivity (EC) and total dissolved solids (TDS) in the upper Indus River at two different outlet locations using 360 readings collected on a monthly basis. The optimized MEP models were assessed using different statistical measurements i.e., coefficient-of-determination (R2), root-mean-square error (RMSE), mean-absolute error (MAE), root-mean-square-logarithmic error (RMSLE) and mean-absolute-percent error (MAPE). The results show that the R2 in the testing phase (subjected to unseen data) for EC-MEP and TDS-MEP models is above 0.90, i.e., 0.9674 and 0.9725, respectively, reflecting the higher accuracy and generalized performance. Also, the error measures are quite lower. In accordance with MAPE statistics, both the MEP models shows an “excellent” performance in all three stages. In comparison with traditional non-linear regression models (NLRMs), the developed machine learning models have good generalization capabilities. The sensitivity analysis of the developed MEP models with regard to the significance of each input on the forecasted water quality parameters suggests that Cl and HCO3 have substantial impacts on the predictions of MEP models (EC and TDS), with a sensitiveness index above 0.90, although the influence of the Na is the less prominent. The results of this research suggest that the development of intelligence models for EC and TDS are cost effective and viable for the evaluation and monitoring of the quality of river water

Biophysical and In Silico Studies of the Interaction between the Anti-Viral Agents Acyclovir and Penciclovir, and Human Serum Albumin

Acyclovir (ACV) and penciclovir (PNV) have been commonly used during the last few decades as potent antiviral agents, especially for the treatment of herpes virus infections. In the present research their binding properties with human serum albumin (HSA) were studied using different advanced spectroscopic and in-silico methods. The interactions between ACV/PNV and HSA at the three investigated temperatures revealed a static type of binding. Extraction of the thermodynamic parameters of the ACV-HSA and PNV-HSA systems from the measured spectrofluorimetric data demonstrated spontaneous interactions with an enthalpy change (∆H0) of −1.79 ± 0.29 and −4.47 ± 0.51 kJ·mol−1 for ACV and PNV, respectively. The entropy change (∆S0) of 79.40 ± 0.95 and 69.95 ± 1.69 J·mol−1·K−1 for ACV and PNV, respectively, hence supported a potential contribution of electrostatic binding forces to the ACV-HSA and PNV-HSA systems. Putative binding of ACV/PNV to HSA, using previously reported site markers, showed that ACV/PNV were bound to HSA within subdomains IIA and IIIA (Sudlow sites I and II). Further confirmation was obtained through molecular docking studies of ACV-HSA and PNV-HSA binding, which confirmed the binding site of ACV/PNV with the most stable configurations of ACV/PNV within the HSA. These ACV/PNV conformers were shown to have free energies of −25.61 and −22.01 kJ·mol−1 for ACV within the HSA sites I and II and −22.97 and −26.53 kJ·mol−1 for PNV in HSA sites I and II, with hydrogen bonding and electrostatic forces being the main binding forces in such conformers

Comparative ANNs with Different Input Layers and GA-PLS Study for Simultaneous Spectrofluorimetric Determination of Melatonin and Pyridoxine HCl in the Presence of Melatonin’s Main Impurity

Melatonin (MLT) has many health implications, therefore it is important to develop specific analytical methods for the determination of MLT in the presence of its main impurity, N-{2-[1-({3-[2-(acetylamino)ethyl]-5-methoxy-1H-indol-2-yl}methyl)-5-methoxy-1H-indol-3-yl]ethyl}acetaamide (DMLT) and pyridoxine HCl (PNH) as a co-formulated drug. This work describes simple, sensitive, and reliable four multivariate calibration methods, namely artificial neural network preceded by genetic algorithm (GA-ANN), principal component analysis (PCA-ANN) and wavelet transform procedures (WT-ANN) as well as partial least squares preceded by genetic algorithm (GA-PLS) for the spectrofluorimetric determination of MLT and PNH in the presence of DMLT. Analytical performance of the proposed methods was statistically validated with respect to linearity, accuracy, precision and specificity. The proposed methods were successfully applied for the assay of MLT in laboratory prepared mixtures containing up to 15% of DMLT and in commercial MLT tablets with recoveries of no less than 99.00%. No interference was observed from common pharmaceutical additives and the results compared favorably with those obtained by a reference method

Synthesis and Biophysical Insights into the Binding of a Potent Anti-Proliferative Non-symmetric Bis-isatin Derivative with Bovine Serum Albumin: Spectroscopic and Molecular Docking Approaches

As part of the research endeavors to combat cancer, a non-symmetric bis-isatin derivative (compound 3) was synthesized and showed a significant anti-proliferative potency. The current study provides a comprehensive characterization of the interaction of compound 3 with the drug-transporting protein bovine serum albumin (BSA) via the use of spectroscopic tools along with molecular docking studies. Fluorescence spectral measurements showed that the BSA intrinsic fluorescence can be significantly quenched by the addition of compound 3 and the formation of a non-fluorescent complex. Further measurements revealed a static type of quenching with Stern–Volmer and Linweaver–Burk constants of 105. The thermodynamic parameters of the binding were calculated to be ΔS° 105.09 ± 5.32 with ΔH° of −0.72 ± 0.71 and negative ΔG° values. In addition, synchronous fluorescence and 3D fluorescence spectroscopy suggested that compound 3 did not induce conformational changes in BSA. Site competition experiments revealed that compound 3 competes with warfarin within the BSA binding domain (Sudlow site I). This was further confirmed by the molecular docking results showing a binding energy of −25.93 kJ/mol for compound 3-BSA. Hence, the observed results in the present study assumed that the compound 3-BSA binding is spontaneous, involving electrostatic forces and hydrogen bonding

Interaction Characterization of a Tyrosine Kinase Inhibitor Erlotinib with a Model Transport Protein in the Presence of Quercetin: A Drug–Protein and Drug–Drug Interaction Investigation Using Multi-Spectroscopic and Computational Approaches

The interaction between erlotinib (ERL) and bovine serum albumin (BSA) was studied in the presence of quercetin (QUR), a flavonoid with antioxidant properties. Ligands bind to the transport protein BSA resulting in competition between different ligands and displacing a bound ligand, resulting in higher plasma concentrations. Therefore, various spectroscopic experiments were conducted in addition to in silico studies to evaluate the interaction behavior of the BSA-ERL system in the presence and absence of QUR. The quenching curve and binding constants values suggest competition between QUR and ERL to bind to BSA. The binding constant for the BSA-ERL system decreased from 2.07 × 104 to 0.02 × 102 in the presence of QUR. The interaction of ERL with BSA at Site II is ruled out based on the site marker studies. The suggested Site on BSA for interaction with ERL is Site I. Stability of the BSA-ERL system was established with molecular dynamic simulation studies for both Site I and Site III interaction. In addition, the analysis can significantly help evaluate the effect of various quercetin-containing foods and supplements during the ERL-treatment regimen. In vitro binding evaluation provides a cheaper alternative approach to investigate ligand-protein interaction before clinical studies