3D-QSAR, ADME-Tox, and molecular docking of semisynthetic triterpene derivatives as antibacterial and insecticide agents

Unveiling promising phytocompounds from Moringa oleifera as dual inhibitors of EGFR(T790M/C797S) and VEGFR-2 in non-small cell lung cancer through in silico screening, ADMET, dynamics simulation, and DFT analysis

Non-small cell lung cancer (NSCLC) is among the main causes of mortality from cancer around the globe, affecting all genders. Current treatments mainly focus on tyrosine kinase inhibitors (TKIs) targeting the epidermal growth factor receptor (EGFR). However, resistance mechanisms, such as the emergence of T790M and C797S EGFR mutations and upregulation of VEGFR-2, often hinder the effectiveness of TKIs. Thereby, EGFR and VEGFR-2 present an intriguing opportunity for the treatment of NSCLC by developing dual-acting drugs. This research aims to evaluate prospective Moringa oleifera L. (MO)-originated compounds to efficiently block both of these receptors. In our research, we screened a library of 200 compounds sourced from MO, a plant known for its remarkable therapeutic potential. We identified five intriguing phytocompounds: hesperetin, gossypetin, quercetin, gallocatechin, and epigallocatechin, as potential anti-cancer agents. The compounds have demonstrated notable binding affinity in virtual screening and multi-stage molecular docking analysis, surpassing the controls, Erlotinib and Bevacizumab + Rituximab. In addition, these compounds demonstrate top-notch drug-likeness and ADMET properties. The five promising drug candidates also had a strong ability to bind to receptors and stayed stable with them during the 200 ns molecular dynamics (MD) simulation and MM-GBSA calculation. Furthermore, DFT analysis indicates that hesperetin, gossypetin, and quercetagetin stand out as the most promising drug candidates among all others. The findings of our study suggest that these three therapeutic candidates can precisely target both EGFR and VEGFR-2 and can potentially act on both of these pathways as a single agent.

Spectroscopic investigation and structural simulation in human serum albumin with hydroxychloroquine/Silybum marianum and a possible potential COVID-19 drug candidate

In this study, the interaction between human serum albumin (HSA) and the hydroxychloroquine/Silybum marianum (HCQ/SM) mixture was investigated using various techniques. The observed high binding constant (Kb) and Stern-Volmer quenching constant (KSV) indicate a strong binding affinity between the HCQ/SM mixture and HSA. The circular dichroism (CD) analysis revealed that HCQ/SM induced conformational changes in the secondary structure of HSA, leading to a decrease in the α-helical content. UV-Vis analysis exhibited a slight redshift, indicating that the HCQ/SM mixture could adapt to the flexible structure of HSA. The experimental results demonstrated the significant conformational changes in HSA upon binding with HCQ/SM. Theoretical studies were carried out using molecular dynamics simulation via the Gromacs simulation package to explore insights into the drug interaction with HSA-binding sites. Furthermore, molecular docking studies demonstrated that HCQ/SM-HSA exhibited favorable docking scores with the receptor (5FUZ), suggesting a potential therapeutic relevance in combating COVID-19 with a value of -6.24 kcal mol-1. HCQ/SM exhibited stronger interaction with both SARS-CoV-2 virus main proteases compared to favipiravir. Ultimately, the experimental data and molecular docking analysis presented in this research offer valuable insights into the pharmaceutical and biological properties of HCQ/SM mixtures when interacting with serum albumin.

Py-CoMFA, docking, and molecular dynamics simulations of Leishmania (L.) amazonensis arginase inhibitors

Leishmaniasis is a disease caused by a protozoan of the genus Leishmania, affecting millions of people, mainly in tropical countries, due to poor social conditions and low economic development. First-line chemotherapeutic agents involve highly toxic pentavalent antimonials, while treatment failure is mainly due to the emergence of drug-resistant strains. Leishmania arginase (ARG) enzyme is vital in pathogenicity and contributes to a higher infection rate, thus representing a potential drug target. This study helps in designing ARG inhibitors for the treatment of leishmaniasis. Py-CoMFA (3D-QSAR) models were constructed using 34 inhibitors from different chemical classes against ARG from L. (L.) amazonensis (LaARG). The 3D-QSAR predictions showed an excellent correlation between experimental and calculated pIC50 values. The molecular docking study identified the favorable hydrophobicity contribution of phenyl and cyclohexyl groups as substituents in the enzyme allosteric site. Molecular dynamics simulations of selected protein-ligand complexes were conducted to understand derivatives' interaction modes and affinity in both active and allosteric sites. Two cinnamide compounds, 7g and 7k, were identified, with similar structures to the reference 4h allosteric site inhibitor. These compounds can guide the development of more effective arginase inhibitors as potential antileishmanial drugs.

2,4-disubstituted 6-fluoroquinolines as potent antiplasmodial agents: QSAR, homology modeling, molecular docking and ADMET studies

Objective

This work was designed to study 2,4-disubstituted 6-fluoroquinolines as antiplasmodial agents by using in silico techniques, to aid in the design of novel analogs with high potency against malaria and high inhibition of Plasmodium falciparum translation elongation factor 2 (PfeEF2), a novel drug target.

Methods

Quantitative structure-activity relationships (QSAR) of 2,4-disubstituted 6-fluoroquinolines were studied with the genetic function approximation technique in Material Studio software. The 3D structure of PfeEF2 was modeled in the SWISS-MODEL workspace through homology modeling. A molecular docking study of the modeled PfeEF2 and 2,4-disubstituted 6-fluoroquinolines was conducted with Autodock Vina in Pyrx software. Furthermore, the in silico pharmacokinetic properties of selected compounds were investigated.

Results

A robust, reliable and predictive QSAR model was developed that related the chemical structures of 2,4-disubstituted 6-fluoroquinolines to their antiplasmodium activities. The model had an internal squared correlation coefficient R2 of 0.921, adjusted squared correlation coefficient R2adj of 0.878, leave-one-out cross-validation coefficient Q2cv of 0.801 and predictive squared correlation coefficient R2pred of 0.901. The antiplasmodium activity of 6-fluoroquinolines was found to depend on the n5Ring, GGI9, TDB7u, TDB8u and RDF75i physicochemical properties: n5Ring, TDB8u and RDF75i were positively associated, whereas GGI9 and TDB7u were negatively associated, with the antiplasmodium activity of the compounds. Stable complexes formed between the compounds and modeled PfeEF2, with binding affinity ranging from -8.200 to -10.700 kcal/mol. Compounds 5, 11, 16, 22 and 24 had better binding affinities than quinoline-4-carboxamide (DDD107498), as well as good pharmacokinetic properties, and therefore may be better inhibitors of this novel target.

Conclusion

QSAR and docking studies provided insight into designing novel 2,4-disubstituted 6-fluoroquinolines with high antiplasmodial activity and good structural properties for inhibiting a novel antimalarial drug target.

3D-QSAR and ADMET studies of morpholino-pyrimidine inhibitors of DprE1 from Mycobacterium tuberculosis

DprE1 is involved in the synthesis of Mycobacterium tuberculosis cell wall and is a potent drug target for Tuberculosis (TB) treatment. The structure and dynamics of the loops L-I and L-II flanking the inhibitor binding site was studied using molecular dynamics (MD) simulation and MMPBSA in Amber v18. Docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) of 55 Morpholino-pyrimidine (MP) inhibitors was carried out using Autodock v1.2.0 and Forge v10. ADMET analysis was done using SwissADME and pkCSM. All MP inhibitors docked in the DprE1 binding pocket, making contacts with L-II residues. MD studies showed that L-I and L-II unfold in the absence of the inhibitor but fold stably structure with reduced protein motions in the presence of MP-38, the highest affinity inhibitor. This was confirmed by k-means clustering and secondary structure analysis. L-II residues, L317, F320 and R325 contributed most towards the MMPBSA binding free energy of MP-38. A robust field-based 3D-QSAR model showed values of r2train = 0.982, r2test = 0.702 and q2 = 0.516. The MP inhibitor field points were broadly divided into negative electrostatics near the A, B rings and hydrophobic electrostatics near the D, E rings. Addition of negative groups at methanone position and ring B as well as addition of hydrophobic and bulky groups at ring E will improve activity. Highly active compounds 47, 49 and 50 of MP series exhibited highly favourable drug-like properties. SAR and ADMET insights attained from this model will help in the development of active DprE1 inhibitors in future.Communicated by Ramaswamy H. Sarma.

2-Amino Thiazole Derivatives as Prospective Aurora Kinase Inhibitors against Breast Cancer: QSAR, ADMET Prediction, Molecular Docking, and Molecular Dynamic Simulation Studies

The aurora kinase is a key enzyme that is implicated in tumor growth. Research revealed that small molecules that target aurora kinase have beneficial effects as anticancer agents. In the present study, in order to identify potential antibreast cancer agents with aurora kinase inhibitory activity, we employed QSARINS software to perform the quantitative structure-activity relationship (QSAR). The statistical values resulted from the study include R2 = 0.8902, CCCtr = 0.7580, Q2 LOO = 0.7875, Q2LMO = 0.7624, CCCcv = 0.7535, R2ext = 0.8735, and CCCext = 0.8783. Among the four generated models, the two best models encompass five important variables, including PSA, EstateVSA5, MoRSEP3, MATSp5, and RDFC24. The parameters including the atomic volume, atomic charges, and Sanderson's electronegativity played an important role in designing newer lead compounds. Based on the above data, we have designed six series of compounds including 1a-e, 2a-e, 3a-e, 4a-e, 5a-e, and 6a-e. All these compounds were subjected to molecular docking studies by using AutoDock v4.2.6 against the aurora kinase protein (1MQ4). Among the above 30 compounds, the 2-amino thiazole derivatives 1a, 2a, 3e, 4d, 5d, and 6d have excellent binding interactions with the active site of 1MQ4. Compound 1a had the highest docking score (-9.67) and hence was additionally subjected to molecular dynamic simulation investigations for 100 ns. The stable binding of compound 1a with 1MQ4 was verified by RMSD, RMSF, RoG, H-bond, molecular mechanics-generalized Born surface area (MM-GBSA), free binding energy calculations, and solvent-accessible surface area (SASA) analyses. Furthermore, newly designed compound 1a exhibited excellent ADMET properties. Based on the above findings, we propose that the designed compound 1a may be utilized as the best theoretical lead for future experimental research of selective inhibition of aurora kinase, therefore assisting in the creation of new antibreast cancer drugs.

Structure-based virtual screening, ADMET analysis, and molecular dynamics simulation of Moroccan natural compounds as candidates for the SARS-CoV-2 inhibitors

The lack of treatments and vaccines effective against SARS-CoV-2 has forced us to explore natural compounds that could potentially inhibit this virus. Additionally, Morocco is renowned for its rich plant diversity and traditional medicinal uses, which inspires us to leverage our cultural heritage and the abundance of natural resources in our country for therapeutic purposes. In this study, an extensive investigation was conducted to gather a collection of phytoconstituents extracted from Moroccan plants, aiming to evaluate their ability to inhibit the proliferation of the SARS-CoV-2 virus. Molecular docking of the studied compounds was performed at the active sites of the main protease (6lu7) and spike (6m0j) proteins to assess their binding affinity to these target proteins. Compounds exhibiting high affinity to the proteins underwent further evaluation based on Lipinski's rule and ADME-Tox analysis to gain insights into their oral bioavailability and safety. The results revealed that the two compounds demonstrated strong binding affinity to the target proteins, making them potential candidates for oral antiviral drugs against SARS-CoV-2. The molecular dynamics results from this computational analysis supported the overall stability of the resulting complex.

Cellular and Non-cellular Antioxidant Properties of Vitamin E-Loaded Metallic-Quercetin/Polycaprolactone Nanoparticles for the Treatment of Melanogenesis

Inhibition of melanogenesis by quercetin and vitamin E is extensively reported in the literature, independently, with limitations in antioxidant potential owing to less permeation, solubility, decreased bioavailability, and reduced stability. Thus, the aim of the present study was to synthesize a novel complex of metal ions (copper and zinc) with quercetin to enhance antioxidant properties which were confirmed by docking studies. Polycaprolactone-based nanoparticles of the synthesized complex (PCL-NPs, Q-PCL-NPs, Zn-Q-PCL-NPs, Cu-Q-PCL-NPs) were made later loaded with vitamin E which made the study more interesting in enhancing antioxidant profile. Nanoparticles were characterized for zeta size, charge, and polydispersity index, while physiochemical analysis of nanoparticles was strengthened by FTIR. Cu-Q-PCL-NPs-E showed maximum in vitro release of vitamin E, i.e., 80 ± 0.54%. Non-cellular antioxidant effect by 2,2-diphenyl-1-picrylhydrazyl was observed at 93 ± 0.23% in Cu-Q-PCL-NPs-E which was twofold as compared to Zn-Q-PCL-NPs-E. Michigan Cancer Foundation-7 (MCF-7) cancer cell lines were used to investigate the anticancer and cellular antioxidant profile of loaded and unloaded nanoparticles. Results revealed reactive oxygen species activity of 90 ± 0.32% with the addition of 89 ± 0.64% of its anticancer behavior shown by Cu-Q-PCL-NPs-E after 6 and 24h. Similarly, 80 ± 0.53% inhibition of melanocyte cells and 95 ± 0.54% increase of keratinocyte cells were also shown by Cu-Q-PCL-NPs-E that confirmed the tyrosinase enzyme inhibitory effect. Conclusively, the use of zinc and copper complex in unloaded and vitamin E-loaded nanoparticles can provide enhanced antioxidant properties with inhibition of melanin, which can be used for treating diseases of melanogenesis.

Cyclohexane-1,3-dione Derivatives as Future Therapeutic Agents for NSCLC: QSAR Modeling, In Silico ADME-Tox Properties, and Structure-Based Drug Designing Approach

The abnormal expression of the c-Met tyrosine kinase has been linked to the proliferation of several human cancer cell lines, including non-small-cell lung cancer (NSCLC). In this context, the identification of new c-Met inhibitors based on heterocyclic small molecules could pave the way for the development of a new cancer therapeutic pathway. Using multiple linear regression (MLR)-quantitative structure-activity relationship (QSAR) and artificial neural network (ANN)-QSAR modeling techniques, we look at the quantitative relationship between the biological inhibitory activity of 40 small molecules derived from cyclohexane-1,3-dione and their topological, physicochemical, and electronic properties against NSCLC cells. In this regard, screening methods based on QSAR modeling with density-functional theory (DFT) computations, in silico pharmacokinetic/pharmacodynamic (ADME-Tox) modeling, and molecular docking with molecular electrostatic potential (MEP) and molecular mechanics-generalized Born surface area (MM-GBSA) computations were used. Using physicochemical (stretch-bend, hydrogen bond acceptor, Connolly molecular area, polar surface area, total connectivity) and electronic (total energy, highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy levels) molecular descriptors, compound 6d is identified as the optimal scaffold for drug design based on in silico screening tests. The computer-aided modeling developed in this study allowed us to design, optimize, and screen a new class of 36 small molecules based on cyclohexane-1,3-dione as potential c-Met inhibitors against NSCLC cell growth. The in silico rational drug design approach used in this study led to the identification of nine lead compounds for NSCLC therapy via c-Met protein targeting. Finally, the findings are validated using a 100 ns series of molecular dynamics simulations in an aqueous environment on c-Met free and complexed with samples of the proposed lead compounds and Foretinib drug.

A strategy to enhance VOC of π-conjugated molecules based on thieno[2,3-b] indole for applications in bulk heterojunction organic solar cells using DFT, TD-DFT, and 3D-QSPR modeling studies

The electronic structure and optical properties of eight novel molecules based on 8-alkyl-8H-thieno[2,3-b] indole was determined using density functional theory DFT, TD-DFT and 3D-QSPR.

Combined computational approaches for developing new anti-Alzheimer drug candidates: 3D-QSAR, molecular docking and molecular dynamics studies of liquiritigenin derivatives

Butyrylcholinesterase is an acetylcholine-degrading enzyme involved in the memorization process, which is becoming an interesting target for the symptomatic treatment of Alzheimer's disease. In the present investigation, the structure-activity relationship of a set of Liquiritigenin derivatives recently revealed to be Butyrylcholinesterase inhibitors was studied basing on comparative field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMISA). As a result, performant models with high predictive capability have been developed (CoMFA model: R² = 0.91, Q² = 0.62, R² _pred = 0.85; CoMISA model: R² = 0.92, Q² = 0.59, R² _pred = 0.83) and implemented to design new Liquiritigenin derivatives with improved activity. Besides, the affinity of the designed derivatives towards the active site of Butyrylcholinesterase, was confirmed by molecular docking and molecular dynamics studies. Moreover, they exhibited good pharmacokinetics properties. Accordingly, the outcomes of the present investigations can provide important direction for the development of new anti-Alzheimer's drug candidates.

Enhanced Photocatalytic CO2 Reduction by Novel Designed Porphyrin-Based MOFs: From Accurate QSPR Model to Experimental Exploration

A reliable quantitative structure-property relationship (QSPR) model was established for predicting the evolution rate of CO₂ photoreduction over porphyrin-based metal-organic frameworks (MOFs) as photocatalysts. The determination coefficient (R ²) for both training and test sets was 0.999. The root-mean-squared error of prediction (RMSEP) obtained was 0.006 and 0.005 for training and test sets, respectively. Based on the proposed model, two porphyrin-based MOFs, Cu-PMOF and Co-PMOF, were designed, synthesized, and applied for CO₂ photoreduction under UV-visible irradiation without any additional photosensitizer. The X-ray diffraction (XRD), diffuse reflectance spectroscopy (DRS), and Fourier transform infrared (FTIR) measurements revealed the successful formation of the porous MOFs. The N₂ adsorption isotherms at 77 K showed a high Brunauer-Emmett-Teller (BET) surface area of 932.64 and 974.06 m²·g^-1 for Cu-PMOF and Co-PMOF, respectively. Theoretical and experimental results showed that HCOOH evolution rates over Cu-PMOF and Co-PMOF were (127.80, 101.62 μmol) and (130.6, 103.47 μmol), respectively. These results were robust and satisfactory.

Rational identification of small molecules derived from 9,10-dihydrophenanthrene as potential inhibitors of 3CLpro enzyme for COVID-19 therapy: a computer-aided drug design approach

Small molecules such as 9,10-dihydrophenanthrene derivatives have remarkable activity toward inhibition of SARS-CoV-2 3CL^pro and COVID-19 proliferation, which show a strong correlation between their structures and bioactivity. Therefore, these small compounds could be suitable for clinical pharmaceutical use against COVID-19. The objective of this study was to remodel the structures of 9,10-dihydrophenanthrene derivatives to achieve a powerful biological activity against 3CL^pro and favorable pharmacokinetic properties for drug design and discovery. Therefore, by the use of bioinformatics techniques, we developed robust 3D-QSAR models that are capable of describing the structure–activity relationship for 46 molecules based on 9,10-dihydrophenanthrene derivatives using CoMFA/SE (R² = 0.97, Q² = 0.81, R²_pred = 0.95, ^cR²_p = 0.71) and CoMSIA/SEHDA (R² = 0.94, Q² = 0.76, R²_pred = 0.91, ^cR²_p = 0.65) techniques. Accordingly, 96 lead compounds were generated based on a template molecule that showed the highest observed activity in vitro (T40, pIC₅₀ = 5.81) and predicted their activities and bioavailability in silico. The rational screening outputs of 3D-QSAR, Molecular docking, ADMET, and MM-GBSA led to the identification of 9 novel modeled molecules as potent noncovalent drugs against SARS-CoV-2-3CL^pro. Finally, by molecular dynamics simulations, the stability and structural dynamics of 3CL^pro free and complex (PDB code: 6LU7) were discussed in the presence of samples of 9,10-dihydrophenanthrene derivative in an aqueous environment. Overall, the retrosynthesis of the proposed drug compounds in this study and the evaluation of their bioactivity in vitro and in vivo may be interesting for designing and discovering a new drug effective against COVID-19.