3D-QSAR Studies Research Articles

2D-QSAR Modeling, Docking, Synthesis and In-Vitro Evaluation of Novel Flavone Derivatives as Anticancer Agents

Background: Cancer is the second leading cause of death globally and is responsible for 10 million deaths in 2020 (2.26 million breast cancer deaths). Due to the problems like drug resistance, toxicities and economic burden, there is a need for the development of novel anticancer agents. Objectives: To design novel flavone derivatives by 2D QSAR studies and docking studies and to evaluate the compounds as potential anticancer agents against MCF7 cell line by MTT assay. Methods: We designed a series of novel flavone derivatives by 2D QSAR modelling using the software QSARINS.The molecular docking studies were carried out to study the molecular interaction and binding affinitiesof the designed compounds against tyrosine protein kinase (PDB ID: 2SRC) by Auto DockVina software. ADMET profiles were calculated for all the designed compounds and five compounds were chosen for synthesis.The synthesized compounds were characterized and evaluated in vitro for anticancer activity against MCF7 cell line by MTT assay. Based on 2D QSAR and molecular docking studies, compounds 3c, 3f, 3i and 3m were synthesized and evaluated for anticancer activity against MCF-7 cell lines. Results: Molecular docking studies of the compounds showed good binding affinity against tyrosine- protein kinase (2SRC). The synthesized flavone derivatives were evaluated for anti-cancer activity against human breast cancer cell line MCF-7 by MTT assay using cisplatin as a positive control. The novel flavone derivative (3c) exhibits more cytotoxicity effect, and the IC50 value of the compound was found to be 52.03 μg/ml. Optimization of these novel scaffolds requires extensive studies on more derivatives. Conclusion: The novel flavone derivatives will be good lead compounds targeting breast cancer.

Artificial Neural Network and Multiple Regression Analysis Applied to 2D-QSAR Studies: the Case of Imidazolidine-2,4-dione as PTP1B Inhibitors

In this investigation, we undertook a comprehensive quantitative structure-activity relationship (QSAR) analysis using both modern artificial neural network (ANN) methods and classical multiple linear regression methods (MLR). Our primary focus was on revealing the intricate connection between antidiabetic activity and the molecular structure of thirty-nine imidazolidine- 2,4-dione derivatives. The B3LYP hybrid functional and 6-31G (d) basis set computed electronic properties at the quantum level. Rigorous benchmarking against experimental data validated the reliability of our quantum theory approach. Our statistical model effectively predicted activities closely aligned with experimental antidiabetic activities, quantified by the IC50 values. They also revealed a significant superiority of the ANN architecture (6-4-1) over the MLR method. This study stands as a meaningful contribution to the field, providing valuable insights for designing new antidiabetic drugs, particularly as potential inhibitors of tyrosine phosphate 1B (PTP1B). The explicit articulation of our primary aim and emphasis on the study’s significance underscore its potential impact on advancing drug development within the realm of antidiabetic therapeutics.

4D-QSAR and MIA-QSAR Studies of Aminobenzimidazole Derivatives as Fourth-generation EGFR Inhibitors.

The epidermal growth factor receptor (EGFR) protein has been intensively studied as a therapeutic target for non-small cell lung cancer (NSCLC). The aminobenzimidazole derivatives as the fourth-generation EGFR inhibitors have achieved promising results and overcame EGFR mutations at C797S, del19 and T790M in NSCLC. In order to understand the quantitative structure-activity relationship (QSAR) of aminobenzimidazole derivatives as EGFRdel19 T790M C797S inhibitors, the four-dimensional QSAR (4D-QSAR) and multivariate image analysis (MIA-QSAR) have been performed on the data of 45 known aminobenzimidazole derivatives. The 4D-QSAR descriptors were acquired by calculating the association energies between probes and aligned conformational ensemble profiles (CEP), and the regression models were established by partial least squares (PLS). In order to further understand and verify the 4D-QSAR model, MIA-QSAR was constructed by using chemical structure pictures to generate descriptors and PLS regression. Furthermore, the molecular docking and averaged noncovalent interactions (aNCI) analysis were also performed to further understand the interactions between ligands and the EGFR targets, which was in good agreement with the 4D-QSAR model. The established 4D-QSAR and MIA-QSAR models have strong stability and good external prediction ability. These results will provide theoretical guidance for the research and development of aminobenzimidazole derivatives as new EGFRdel19 T790M C797S inhibitors.

Computational studies of pyrimidine derivatives as inhibitors of human σ1 receptor using 3D-QSAR analysis, molecular docking, ADMET properties and DFT investigation

Neuropathic pain syndrome has a profoundly negative and agonizing impact on the lives of the individuals it afflicts. In order to find an effective treatment for this condition, extensive and thorough scientific studies have demonstrated that the σ1 receptor serves as an exceptional target for therapeutic compounds. The 3D-QSAR studies were constructed using the technique of comparative molecular similarity indice analysis (CoMSIA). The outcomes of these studies demonstrated the reliability of CoMSIA model (with R2 train value of 0.96 and Q2 value of 0.54) in accurately predicting the activity of various compounds. By assimilating the valuable insights gathered from the field contributors of the 3D-QSAR models and conducting molecular docking studies on the highly potent compound C48, a total of sixteen new compounds were successfully designed to exhibit enhanced efficacy against neuropathic pain. In addition to the comprehensive 3D-QSAR analysis, the newly synthesized compounds were subjected to an absorption, distribution, metabolism, excretion, and toxicity evaluation. This evaluation aimed to assess the pharmacokinetic and toxicological properties of the compounds, providing valuable insight for future in vitro investigations. Calculations DFT of the new compounds mol2, mol3, and mol4, including the analysis of their molecular properties, geometric optimization, frontier molecular orbital (FMOs), density states (DOS), and energy evaluation, In order to compare these compounds with the reference ligand 61 w, their respective properties were thoroughly investigated. The most stable orientations for the compounds Mol2, Mol4, and Mol3 were determined to be the ones that yielded the highest stability and efficiency. The significant advancements made in this study, should serve as a strong motivation for future in vitro investigations on these compounds.

A virtual insight into mushroom secondary metabolites: 3D-QSAR, docking, pharmacophore-based analysis and molecular modeling to analyze their anti-breast cancer potential

Breast cancer is a major issue of investigation in drug discovery due to its rising frequency and global dominance. Plants are significant natural sources for the development of novel medications and therapies. Medicinal mushrooms have many biological response modifiers and are used for the treatment of many physical illnesses. In this research, a database of 89 macro-molecules with anti-breast cancer activity, which were previously isolated from the mushrooms in literature, has been selected for the three-dimensional quantitative structure–activity relationships (3D-QSAR) studies. The 3D-QSAR model was necessarily used in Pharmacopoeia virtual evaluation of the database to develop novel MCF-7 inhibitors. With the known potential targets of breast cancer, the docking studies were achieved. Using molecular dynamics simulations, the targets’ stability with the best-chosen natural product molecule was found. Furthermore, the absorption, distribution, metabolism, excretion, and toxicity of three compounds, resulting after the docking study, were predicted. The compound C1 (Pseudonocardian A) showed the features of effective compounds because it has bioavailability from different coral species and is toxicity-free for the prevention of many dermatological illnesses. C1 is chemically active and possesses charge transfer inside the monomer, as seen by the band gaps of highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) electrons. The reactivity descriptors ionization potential, electron affinity, chemical potential (μ), hardness (η), softness (S), electronegativity (χ), and electrophilicity index (ω) have been estimated using the energies of frontier molecular orbitals (HOMO–LUMO). Additionally, molecular electrostatic potential maps were created to show that the C1 is reactive. Communicated by Ramaswamy H. Sarma

Design of new small molecules derived from indolin-2-one as potent TRKs inhibitors using a computer-aided drug design approach

Tropomyosin receptor kinase (TRKs) enzymes are responsible for cancers associated with the neurotrophic tyrosine kinase receptor gene fusion and are identified as effective targets for anticancer drug discovery. A series of small-molecule indolin-2-one derivatives showed remarkable biological activity against TRKs enzymatic activity. These small molecules could have an excellent profile for pharmaceutical application in the treatment of cancers caused by TRKs activity. The aim of this study is to modify the structure of these molecules to obtain new molecules with improved TRK inhibitory activity and pharmacokinetic properties favorable to the design of new drugs. Based on these series, we carried out a 3D-QSAR study. As a result, robust and reliable CoMFA and CoMSIA models are developed and applied to the design of 11 new molecules. These new molecules have a biological activity superior to the most active molecule in the starting series. The eleven designed molecules are screened using drug-likeness, ADMET proprieties, molecular docking, and MM-GBSA filters. The results of this screening identified the T1, T3, and T4 molecules as the best candidates for strong inhibition of TRKs enzymatic activity. In addition, molecular dynamics simulations are performed for TRK free and complexed with ligands T1, T3, and T4 to evaluate the stability of ligand-protein complexes over the simulation time. On the other hand, we proposed experimental synthesis routes for these newly designed molecules. Finally, the designed molecules T1, T2, and T3 have great potential to become reliable candidates for the conception of new drug inhibitors of TRKs. Communicated by Ramaswamy H. Sarma

An Integrated Computational Approaches for Designing of Potential Piperidine based Inhibitors of Alzheimer Disease by Targeting Cholinesterase and Monoamine Oxidases Isoenzymes.

The study aimed to evaluate the potential of piperidine-based 2H chromen-2-one derivatives against targeted enzymes, i.e., cholinesterase's and monoamine oxidase enzymes. The compounds were divided into three groups, i.e., 4a-m ((3,4-dimethyl-7-((1-methylpiperidin-4-yl)oxy)-2H-chromen-2-one derivatives), 5a-e (3,4-dimethyl-7-((1-methypipridin-3-yl)methoxy)-2H-chromen-2-one derivatives), and 7a-b (7-(3-(3,4-dihydroisoquinolin-2(1H)-yl)propoxy)-3,4-dimethyl-2H-chromen-2-one derivatives) with slight difference in the basic structure. The comprehensive computational investigations were conducted including density functional theories studies (DFTs), 2D-QSAR studies, molecular docking, and molecular dynamics simulations. The QSAR equation revealed that the activity of selected chromen-2-one-based piperidine derivatives is being affected by the six descriptors, i.e., Nitrogens Count, SdssCcount, SssOE-Index, T-2-2-7, ChiV6chain, and SssCH2E-Index. These descriptor values were further used for the preparation of chromen-2-one based piperidine derivatives. Based on this, 83 new derivatives were created from 7 selected parent compounds. The QSAR model predicted their IC50 values, with compound 4k and 4kk as the most potent multi-targeted derivative. Molecular docking results exhibited these compounds as the best inhibitors; however, 4kk exhibited greater activity than the parent compounds. The results were further validated by molecular dynamic simulation studies along with the suitable physicochemical properties. These results prove to be an essential guide for the further design and development of new piperidine based chromen-2-one derivatives having better activity against neurodegenerative disorder.

Evaluation of PPAR gamma agonists: A molecular docking and QSAR study of chalcone analog

In recent years, chalcones have attracted researchers with their unique structure and promising potential across a wide range of scientific disciplines. They are naturally occurring 1,3-diphenyl-2-propen-1-ones. As well as regulating cell proliferation, differentiation, and angiogenesis, PPARs are also involved in cell differentiation. The present study evaluates the molecular activity of 60 chalcone analogs and two marketed drugs as potential PPAR gamma agonists. Molecular docking studies, structural property calculations, and 2D QSAR studies were carried out to screen the best molecule in the library. The compound coded with 2i was found to have the highest binding affinity and selectivity for PPAR gamma. Firm interactions within 5.0 Å were considered for the docking analysis. Ramachandran plot interpretations also helped us to justify the firm binding at the catalytic site. The correlational studies using the QSAR model were carried out, and the coefficient of regression was found to be 0.9247, and the results were plotted. The 2i was found to be the most suitable compound from the library.

Pharmacophore mapping, 3D QSAR, molecular docking, and ADME prediction studies of novel Benzothiazinone derivatives.

In the quest to combat tuberculosis, DprE1, a challenging target for novel anti-tubercular agents due to its small size and membrane location, has been a focus of research. DprE1 catalyzes the transformation of DPR into Ketoribose DPX, with Benzothiazinone emerging as a potent pharmacophore for inhibiting DprE1. Clinical trial drugs such as BTZ043, BTZ038, PBTZ169, and TMC-207 have shown promising results as DprE1 inhibitors. This study employed pharmacophore mapping of Pyrazolopyridine, Dinitrobenzamide, and Benzothiazinone derivatives to identify crucial features for eliciting a biological response. Benzothiazinone (Ligand code: 73) emerged as a reference ligand with a fitness score of 3.000. ROC analysis validated the pharmacophore with an excellent score of 0.71. To build a 3D QSAR model, a series of Benzothiazinone congeneric derivatives were explored. The model exhibited strong performance, with a standard deviation of 0.1531, a correlation coefficient for the training set (R2) value of 0.9754, and a correlation coefficient for test set Q2 value of 0.7632, indicating robust predictive capabilities. Contour maps guided the design of novel benzothiazinone derivatives, emphasizing steric, electrostatic, hydrophobic, H-bond acceptor, and H-bond donor groups for structure-activity relationships. Docking studies against PDB ID: 4NCR demonstrated favorable scores, with interactions aligning well with the in-built ligand 26J. Docking validation via RMSD values supported the reliability of the docking results. This comprehensive approach aids in the design of novel benzothiazinone derivatives with potential anti-tubercular properties, contributing to the development of novel anti-tubercular agents which can be pivotal in the eradication of tuberculosis.

Quinoline-based Schiff bases as possible antidiabetic agents: ligand-based pharmacophore modeling, 3D QSAR, docking, and molecular dynamics simulations study.

α-Glucosidase enzyme inhibition is a legitimate approach to combat type 2 diabetes mellitus as it manages to control postprandial hyperglycemia. In this pursuit, a literature search identified quinoline-based molecules as potential α-glucosidase inhibitors. Thus our intended approach is to identify pharmacophoric features responsible for the α-glucosidase inhibition. This was achieved by performing, ligand-based pharmacophore modeling, 3D QSAR model development, pharmacophore-based screening of a rationally designed quinoline-based benzohydrazide Schiff base library, identifying, synthesizing and characterizing molecules (6a-6j) by IR, (1H and 13C) NMR, and mass studies. Further, these molecules were evaluated for α-glucosidase and α-amylase inhibitory potential. Compound 6c was found to inhibit α-glucosidase enzyme with an IC50 value of 12.95 ± 2.35 μM. Similarly, compound 6b was found to have an IC50 value of 19.37 ± 0.96 μM as compared to acarbose (IC50: 32.63 ± 1.07 μM); the inhibitory kinetics of compounds 6b and 6c revealed a competitive type of inhibition; the inhibitory effect can be attributed to its mapped pharmacophoric feature and model validation with a survival score of 5.0697 and vector score of 0.9552. The QSAR model showed a strong correlation with an R 2 value of 0.96. All the compounds (6a-6j) showed no toxicity in L929 cell lines by the MTT assay method. Further, the binding orientation and stability of the molecules were assessed using molecular docking studies and MD trajectory analysis. The energy profile of the molecules with protein as a complex and molecules alone was evaluated using MM/GBSA and DFT calculations, respectively; finally, the pharmacokinetic profile was computed using ADMET analysis.

3D-QSAR, ADMET, and molecular docking studies of aztreonam analogs as E. colis inhibitors.

The development of multidrug resistant strains of extended-spectrum β-lactamase-producing Escherichia coli has become a global problem; therefore, the discovery of new antibacterial agents is the only available solution. To improve and propose new compounds with antibacterial activity, the three-dimensional quantitative structure-activity relationship and molecular docking studies were carried out on Aztreonam analogs as E. coli inhibitors in DNA gyrase B. This study's 3D-Quantitative structure-activity relationship model was created using on the Comparative Molecular Field Analysis and the Comparative Molecular Similarity Indices Analysis. Using the Comparative Molecular Field Analysis (Q 2 = 0.73; R 2 = 0.82), excellent predictability was achieved, and the best Comparative Molecular Similarity Indices Analysis model (Q 2 = 0.88; R 2 = 0.9). The generated model's ability to predict outcomes was assessed through external validation using a test set compound and an applicability domain technique. In this study, the steric, electrostatic, and hydrogen bond acceptor fields played a key role in antibacterial activity. The results of the molecular docking revealed that the newly generated compound A6 has the highest binding affinity with DNA gyrase B. It forms 10 hydrogen bonds with amino acid residues of Asn104, Asn274, Asn132, Ser70, Ser237, Thr105, Glu273, and 2 salt bridges with amino acid residues of Ser70 and Glu273 and one pi-pi interacting with Gys271 amino acid residue in the binding site of 5G1, and this result was validated by a new assessment method. We created some novel, highly effective DNA gyrase B inhibitors based on the earlier findings, and the most accurate model predicted their inhibitory actions. The ADMET characteristics and pharmacological similarity of these novel inhibitors were also examined. These findings would be very beneficial in guiding the optimization process for the identification of novel drugs that can address the issue of multiple drug resistance.

Synthesis, Antiproliferative Activity, 3D-QSAR and Molecular Docking Study of Novel Longifolene-Derived Tetraline Fused N-Acyl-pyrazole Compounds

Synthesis, Antiproliferative Activity, 3D-QSAR and Molecular Docking Study of Novel Longifolene-Derived Tetraline Fused N-Acyl-pyrazole Compounds

Robust and predictive 3D-QSAR models for predicting the activities of novel oxadiazole derivatives as multifunctional anti-Alzheimer agents.

In recent years, Alzheimer disease (AD) as a neurodegenerative disorder has been increasing annually with the aging of the global population, therefore, development of novel anti-AD drugs is imperative. Studies have proven that glycogen synthase kinase-3β (GSK-3β) is a pivotal factor in the development of AD. Therefore, GSK-3β inhibitors would provide powerful means to treat the disorders, such as AD. To in-depth study the structure-activity relationship of a series of oxadiazole derivatives as multifunctional anti-Alzheimer agents, computational three dimensional quantitative structure-activity relationship (3D-QSAR) studies, molecular docking and molecular dynamics were conducted. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods were conducted to build up the 3D-QSAR models, and exhibited significant results (R cv 2 = 0.692, R pred 2 = 0.6885/CoMFA, R cv 2 = 0.696, R pred 2 = 0.6887/CoMSIA). The accuracy of the 3D-QSAR models was validated by external validation and applicability domain analysis. The derived contour maps provided structural information for designing novel compounds to improve the inhibitory activities. Additionally, molecular docking and molecular dynamics were also employed to investigate the bonding interactions and stability of this series of inhibitors in the active site of GSK-3β, and the results revealed that the importance of residues Ile62, Asn64 Val70, Tyr128, Val129 and Leu182 for ligand binding to the receptor GSK-3β. All the results would be of great help for the discovery of new GSK-3β agents that can solve the problem of AD.

2D-QSAR and molecular docking study on nitrofuran analogues as antitubercular agents

<abstract><sec> <title>Background</title> <p>Resistance to most of the antitubercular drugs has been on rising trends due to the misuse of existing drugs. This has encouraged us to explore a novel scaffold that has the potential for quick antimicrobial action with minimum side effects. Nitrofurans have attracted us due to their extensive biological activities, such as antibacterial and antifungal activities.</p> </sec><sec> <title>Objective</title> <p>The antitubercular activities of 126 nitrofuran derivatives have been investigated by using indicator parameters and topological and structural fragment descriptors.</p> </sec><sec> <title>Methods</title> <p>The different quantitative structure activity relationship (QSAR) models have been created and validated by using two different methodologies: combinatorial protocol in multiple linear regression (CP-MLR) and partial least-squares (PLS) analysis.</p> </sec><sec> <title>Results</title> <p>The 16 descriptors identified in CP-MLR are from six different classes: Constitutional, Functional, Atom Centered Fragments, Topological, Galvez, and 2D autocorrelation. Indicator parameters and Dragon descriptors suggested that the presence of a furan ring substituted by nitro group is essential for antitubercular activity. Further descriptors from constitutional, and functional classes suggest that the number of double bonds, number of sulphur atoms and number of fragments like thiazole, morpholine and thiophene should be minimum, along with the positive influence of Kier-Hall electrotopological states (Ss) for improved activity. The ACF class descriptors, GALVEZ class descriptors, and 2D-AUTO descriptor GATS4p have also shown positive influence on the antitubercular activity. The TOPO class descriptor T(O…S) suggests that the minimum gap between sulphur and oxygen is favorable for activity.</p> </sec><sec> <title>Conclusions</title> <p>The models acknowledged in the study have explained the variance between 72 to 76% in the training set and in the prediction of the test set compounds. Also, compounds <bold>122</bold>, <bold>123</bold> and <bold>82</bold> were found to possess good binding affinity towards nitroreductase.</p> </sec></abstract>

Effects of 1,4-dihydropyridine derivatives on cell injury and mTOR of HepG2 and 3D-QSAR study

1,4-dihydropyridine derivatives (1,4-DHPs) are a class of drugs used to treat cardiovascular diseases, but these drugs can cause liver injury. To reveal the toxicity characteristics of these compounds, we used a series of assays, including cell viability, enzyme activity detection, and western blotting, to investigate the toxicity of seven kinds of 1,4-DHPs (0–100 μM) on HepG2 cells and establish 3D-QSAR model based on relevant toxicity data. After HepG2 cells were treated with 1,4-DHPs for 24 h, high-dose (100 μM) 1,4-DHPs decreased cell viability to varying degrees, while ROS and MDA contents were significantly increased, and ATP content was reduced. Moreover, with the concentration of 100 μM 1,4-DHPs (Nimodipine, Nitrendipine, Cilnidipine, and Manidipine) were markedly inhibited the phosphorylation levels of mTOR protein. The results of the 3D-QSAR model showed that the non-cross validation coefficient (R2) and cross validation coefficient (Q2) of the model were 0.982 and 0.652, respectively. Combined with external validation and the Williams diagram, the model showed good predictability and application domain. Based on the CoMSIA 3D contour map, the introduction of large volume and hydrogen bond receptor groups on the carbonyl oxygen side chains of the 1,4-DHPs ring 3- and 5- was beneficial for reducing the toxicity of 1,4-DHPs. The results of this study could supplement information on the cytotoxicity of 1,4-DHPs, and could provide theoretical support for predicting the toxicity of 1,4-DHPs.

Design of new dipeptide inhibitors against SARS-CoV 3CLpro: 3D-QSAR, molecular docking, MD simulation, ADMET studies and retrosynthesis strategy

The 3CL protease plays a crucial role in the life cycle of SARS-CoV. This protease is considered an important antiviral target. In the present work, the 3D-QSAR study was performed on a set composed of twenty-six dipeptide SARS-CoV 3CLpro inhibitors in order to propose the new potent anti-SARS agents with a high predicted activity value. The model of CoMSIA/SH is the optimal, with good statistical results presenting a high value of the cross-validation coefficient Q2 = 0.796 and a good value of the determination coefficient R2 = 0.887, the external validation of this model is justified by the high value of the prediction coefficient R2pred = 0.884 and the validation of Globraikh, Roy and Tropsha criteria. The exploitation of the different results provided key information about the structures favored to improve the inhibitory activity against 3CLpro, and has enabled us to propose seven new potent inhibitors with significant predictive activity values, notably compound M−1 with pKipred = 7.080. Then, a molecular docking study was performed to determine the binding energy and to identify the key interactions between the receptor (PDB ID: 1WOF) and the ligands. All the newly designed compounds showed low binding energy values as compared to the Remdesivir −8.144 kcal. mol−1 especially for compounds M−5 and M−4 with the binding affinity values −10.022 kcal. mol−1 and −9.727 kcal.mol−1 respectively. In addition, these inhibitors were verified for in silico pharmacokinetic proprieties and toxicity profile using ADMET. Two compounds M−4 and M−5 with potential results in the molecular docking were selected for the molecular dynamic simulation of 100 ns. The MM-GBSA results show that the predicted compound M−5 has the lowest free energy with −38.200 KJ/mol. We exploited the computer-aided synthesis technology using the ASKCOS website to perform a retrosynthetic analysis of compound M−5.

An amalgamated molecular dynamic and Gaussian based 3D-QSAR study for the design of 2,4-thiazolidinediones as potential PTP1B inhibitors

Overexpression of protein tyrosine phosphatase 1B (PTP1B) is the major cause of various diseases such as diabetes, obesity, and cancer. PTP1B has been identified as a negative regulator of the insulin signaling cascade, thereby causing diabetes. Numerous anti-diabetic medications based on thiazolidinedione have been successfully developed; however, 2,4-thiazolidinedione (2,4-TZD) scaffolds have been reported as potential PTP1B inhibitors for the manifestation of type 2 diabetes mellitus involving insulin resistance. In the present study, we have employed amalgamated approach involving MD-simulation studies (100 ns) as well as Gaussian field-based 3D-QSAR to develop a pharmacophoric model of 2,4-TZD as potent PTP1B inhibitors. MD simulation studies of the most potent compound in the PTP1B (PDB Id: 2QBS) binding pocket revealed that compound 43 was stable in the binding pocket and demonstrated excellent binding efficacy within the active site pocket. MM/GBSA results revealed that compound 43, bearing C-5 arylidine substitution, strongly bound to the target as compared to rosiglitazone with ΔGMM/GBSA difference of −11.13 kcal/mol. PCA, Rg, RMSF, RMSD, and SASA were analyzed from the complex's trajectories to anticipate the simulation outcome. We have suggested a series of 2,4-TZD as possible PTP1B inhibitors based on the results of MD simulation and 3D-QSAR studies.

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 r2 train = 0.982, r2 test = 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

“2D, 3D QSAR and Pharmacophore Identification of Thieno[3,2-d]pyrimidines as Cholesterol inhibitors.”

Introduction:: The present study reveals the 2D, 3D-QSAR analysis of Thieno[3,2-d]pyrimidine to express the biological activity against Cholesterol, structurally different ligands can fit the common receptor site, and Pharmacophore models well describe safety considerations of the said chemical entities Methods:: The organic exercises of the atoms were changed over into log IC50. The measurably huge of 2D-QSAR and 3D QSAR models are r2 = 0 .9762, q2 = 0.9379 and internal (q2 = 0.8837) and external (predictive r2 = 0.9162) respectively. 2D QSAR studies revealed that the Positive coefficient value of Quadrupole2 and Negative coefficient value of T_2_Cl_7 descriptors were major contributing descriptors. Results:: The 3D QSAR models indicate that steric and electrostatic effects primarily determine binding affinities. Conclusion:: From the best model obtained from the QSAR analyses, some newer compounds of the same series were developed, having better activity than the earlier compounds that have been reported.

QSAR modelling, molecular docking, molecular dynamic and ADMET prediction of pyrrolopyrimidine derivatives as novel Bruton’s tyrosine kinase (BTK) inhibitors

In recent years, there has been a focus on developing and discovering novel Bruton's tyrosine kinase (BTK) inhibitors, as they offer an effective treatment strategy for B-cell malignancies. BTK plays a crucial role in B cell receptor (BCR)-mediated activation and proliferation by regulating downstream factors such as the NF-κB and MAP kinase pathways. To address this challenge and propose potential therapeutic options for B-cell lymphomas, researchers conducted 2D-QSAR and ADMET studies on pyrrolopyrimidine derivatives that act as inhibitors of the BCR site in cytochrome b. These studies aim to improve and identify new compounds that could serve as more potent potential BTK inhibitors, which would lead to the identification of new drug candidates in this field.In our study, we used 2D-QSAR (multiple linear regression, multiple nonlinear regression, and artificial neural networks), molecular docking, molecular dynamics, and ADMET properties to investigate the potential of 35 pyrrolopyrimidine derivatives as BTK inhibitors. A molecular docking study and molecular dynamics simulations of molecule 13 over 10 ns revealed that it establishes multiple hydrogen bonds with several residues and exhibits frequent stability throughout the simulation period. Based on the results obtained by molecular modeling, we proposed six new compounds (Pred1, Pred2, Pred3, Pred4, Pred5, and Pred6) with highly significant predicted activity by MLR models. A study based on the in silico evaluation of the predicted ADMET properties of the new candidate molecules is strongly recommended to classify these molecules as promising candidates for new anticancer agents specifically designed to target Bruton's tyrosine kinase (BTK) inhibition.