3D QSAR Research Articles

Molecular Docking, Pharmacophore Modelling, 3D QSAR, Molecular Dynamics Simulation and MMPBSA Studies On Hydrazine-Linked Thiazole Analogues as MAO-B Inhibitors

Molecular Docking, Pharmacophore Modelling, 3D QSAR, Molecular Dynamics Simulation and MMPBSA Studies On Hydrazine-Linked Thiazole Analogues as MAO-B Inhibitors

Exploring characteristic features for effective HCN1 channel inhibition using integrated analytical approaches: 3D QSAR, molecular docking, homology modelling, ADME and molecular dynamics.

Neuropathic pain (NP) is characterized by hyperalgesia, allodynia, and spontaneous pain. Hyperpolarization-activated cyclic nucleotide-gated (HCN) channel involved in neuronal hyperexcitability, has emerged as an important target for the drug development of NP. HCN channels exist in four different isoforms, where HCN1 is majorly expressed in dorsal root ganglion having an imperative role in NP pathophysiology. A specific HCN1 channel inhibitor will hold the better potential to treat NP without disturbing the physiological roles of other HCN isoforms. The main objective is to identify and analyze the chemical properties of scaffolds with higher HCN1 channel specificity. The 3D-QSAR studies highlight the hydrophobic & hydrogen bond donor groups enhance specificity towards the HCN1 channel. Further, the molecular interaction of the scaffolds with the HCN1 pore was studied by generating an open-pore model of the HCN1 channel using homology modelling and then docking the molecules with it. In addition, the important residues involved in the interaction between HCN1 pore and scaffolds were also identified. Moreover, ADME predictions revealed that compounds had good oral bioavailability and solubility characteristics. Subsequently, molecular dynamics simulation studies revealed the better stability of the lead molecules A7 and A9 during interactions and ascertained them as potential drug candidates. Cumulative studies provided the important structural features for enhancing HCN1 channel-specific inhibition, paving the way to design and develop novel specific HCN1 channel inhibitors.

Screening of Novel Hydroxamic Acid Derivatives as ASM Inhibitors for the Treatment of Depression

AbstractIn the present work, we performed a computational study on hydroxamic acid containing compounds as acid sphingomyelinase (ASM) inhibitors. The study starts from the development of 3D‐QSAR and pharmacophore models, which were further taken as a source for the enumeration and virtual screening study. The 3D‐QSAR results showed the best statistical model with Q2, R2, and R2 scrambling values of 0.7175, 0.9019, and 0.7128, respectively. The pharmacophore hypothesis generated one of the best hypotheses including five features such as 2 aromatic rings, 2 hydrogen bond donors, and 1 hydrogen bond acceptor. The enumeration study paved the path in the discovery of novel compounds where pharmacophore hypothesis and 3D QSAR study data was used for the identification of novel compounds. Compound 9f_20 showed good docking score −11.399 and binding interactions with amino acids HIP317, ASN316, GLH386, Zn701, Zn702, HIP317, and HIP280 required for ASM inhibitory activity. The virtual screening study was performed on the basis of developed pharmacophore ADDRR_1 where ZINC000013941849 showed good binding interactions with receptor including amino acids Zn701, Zn702, HIP280, LYS103, HIP317, ASN316, and ILE487. ZINC000013941849 with docking score −13.101. The screened compounds may be taken for the further development of novel antidepressant agents.

Discovery of Potential Inhibitors of CDK1 by Integrating Pharmacophore-Based Virtual Screening, Molecular Docking, Molecular Dynamics Simulation Studies, and Evaluation of Their Inhibitory Activity.

The ability of CDK1 to compensate for the absence of other cell cycle CDKs poses a great challenge to treat cancers that overexpress these proteins. Despite several studies focusing on the area, there are no FDA-approved drugs selectively targeting CDK1. Here, the study aimed to develop potential CDK1 selective inhibitors through drug repurposing and leveraging the structural insights provided by the hit molecules generated. Approximately 280,000 compounds from DrugBank, Selleckchem, Otava and an in-house library were screened initially based on fit values using 3D QSAR pharmacophores built for CDK1 and subsequently through Lipinski, ADMET, and TOPKAT filters. 10,310 hits were investigated for docking into the binding site of CDK1 determined using the crystal structure of human CDK1 in complex with NU6102. The best 55 hits with better docking scores were further analyzed, and 12 hits were selected for 100 ns MD simulations followed by binding energy calculations using the MM-PBSA method. Finally, 10 hit molecules were tested in an in vitro CDK1 Kinase inhibition assay. Out of these, 3 hits showed significant CDK1 inhibitory potential with IC50 < 5 μM. These results indicate these compounds can be used to develop subtype-selective CDK1 inhibitors with better efficacy and reduced toxicities in the future.

Synthesis, antimicrobial, anticancer activity, 3D QSAR, ADMET properties, and in silico target fishing of novel N,N-disubstituted chloroacetamides

The recent FDA approval of afatanib, ibrutinib, and osimertinib, which covalently bind to specific cysteine residues in target kinases, has renewed interest in covalent drug discovery. Besides α,β-unsaturated carbonyls, chloroacetamides have emerged as popular warheads for designing targeted covalent inhibitors. In this study, we synthesized thirteen N,N-disubstituted chloroacetamides (1–13) by acylating secondary amines with chloroacetyl chloride, selecting substituents to provide a wide range of lipophilicity. We evaluated their anticancer and antimicrobial activity, finding five compounds with significant cytotoxicity against HeLa, K562, and A549 cell lines (IC50 <10 μM). Notably, compound 10 activated caspases 3, 8, and 9, promoting both intrinsic and extrinsic apoptotic pathways, while compounds 9–12 were strong apoptosis inducers. A 3D QSAR model showed that aromatic substituents on nitrogen atoms reduced HeLa potency, whereas the overall molecular shape had a positive effect. ChemBL and pharmacophoric similarity searches suggested potential anticancer targets, including alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), glycogen synthase kinase-3β, and calmodulin. Docking studies indicated that chloroacetamides bind to ADH and ALDH via hydrogen bonds and hydrophobic interactions. Pharmacokinetics predictions suggest that chloroacetamides are druglike molecules with promising ADMET properties.

Molecular Investigations of Novel Pyrano[2,3-c]Pyrazole Congeners as Potential HCoV-229E Inhibitors: synthesis, Molecular Modeling, 3D QSAR, and ADMET Screening

The ongoing global pandemic caused by viral pathogens like SARS-CoV-2 (COVID-19) underscores that viral transmission is not confined by geographical boundaries. Thus, the development of novel antiviral therapies is critical to mitigate this crisis. Pyranopyrazoles have gained significant attention in medicinal chemistry due to their bioactive properties. In this study, we present a new series of pyranopyrazoles and their annulated derivatives, which were assessed for antiviral activity using a validated QSAR model and tested for their inhibitory effects against the viral 3CLpro enzyme. The findings were corroborated by various in silico techniques, including molecular docking, molecular dynamics simulations, and DFT calculations. Additionally, ADME studies were conducted to evaluate the pharmacokinetics and pharmacodynamics of the novel lead compound 2. These investigations identified a series of metabolically stable pyranopyrazoles and their annulated derivatives as effective inhibitors of the SARS-CoV-2 3CLpro enzyme, offering a promising therapeutic option for COVID-19. We believe that pyranopyrazoles warrant further evaluation and chemical optimization for potential use in COVID-19 treatment.

Pyrrole-Indoline-2-Ones as Aurora Kinase Inhibitors: Pharmacophore Modeling, 3D QSAR Studies and Molecular Dynamics

Pyrrole-Indoline-2-Ones as Aurora Kinase Inhibitors: Pharmacophore Modeling, 3D QSAR Studies and Molecular Dynamics

A Computational Study of Green Tea Extracts and their Derivatives as Potential Inhibitors for Squalene Monooxygenase.

According to the World Health Organisation, cardiovascular complications have been recognized as the leading course of death between 2000 and 2019. Cardiovascular complications are caused by excess LDL cholesterol in the body or arteries that can build up to form a plaque. There are drugs currently in clinical use called statins that target HMGCoA reductase. However, these drugs result in several side effects. This work investigated using computational approaches to lower cholesterol by investigating green tea extracts as an inhibitors for squalene monooxygenase (the second-rate-controlling step in cholesterol synthesis). Pharmacophore modeling was done to identify possible pharmacophoric sites based on the pIC50 values. The best hypothesis generated by pharmacophore modeling was further validated by atom-based 3D QSAR, where 70% of the data set was treated as the training set. Prior molecular docking ADMET studies were done to investigate the physiochemical properties of these molecules. Glide docking was performed, followed by molecular dynamics to evaluate the protein conformational changes. Pharmacophore results suggest that the best molecules to interact with the biological target should have at least one hydrogen acceptor (A5), two hydrogen donors (D9 and D10), and two benzene rings (R14 and R15) for green tea polyphenols and theasinensin A. ADMET result shows that all molecules in this class have low oral adsorption. Molecular docking results showed that some green tea polyphenols have good binding affinities, with most of these structures having a docking score of less than -10 kcal/mol. Molecular dynamics further illustrated that the best-docked ligands perfectly stay within the active site over a 100 ns simulation. The results obtained from this study suggest that green tea polyphenols have the potential for inhibition of squalene monooxygenase, except for theasinensin A.

Lead Identification Through In Silico Studies: Targeting Acetylcholinesterase Enzyme Against Alzheimer's Disease.

In this work, we aimed to acquire the best potential small molecule for Alzheimer's disease (AD) treatment using different models in Biovia Discovery Studio to identify new potential inhibitors of acetylcholinesterase (AChE) via in silico studies. The prevalence of cognitive impairment-related neurodegenerative disorders, such as AD, has been observed to escalate rapidly. However, we still know little about the underlying functions, outcome predictors, or intervention targets causing AD. The objective of the study was to optimize and identify the lead compound to target AChE against Alzheimer's disease. Different in silico studies were employed, including the pharmacophore model, virtual screening, molecular docking, de novo evolution model, and molecular dynamics. The pharmacophoric features of AChE inhibitors were determined by ligand-based pharmacophore models and 3D QSAR pharmacophore generation. Further validation of the best pharmacophore model was done using the cost analysis method, Fischer's randomization method, and test set. The molecules that harmonized the best pharmacophore model with the estimated activity < 1 nM and ADMET parameters were filtered, and 12 molecules were subjected to molecular docking studies to obtain binding energy. 3vsp_EK8_1 secured the highest binding energy of 65.60 kcal/mol. Further optimization led to a 3v_Evo_4 molecule with a better binding energy of 70.17 kcal/mol. The molecule 3v_evo_4 was subjected to 100 ns molecular simulation compared to donepezil, which showed better stability at the binding site. A lead compound, 3v_Evo_4 molecule, was identified to inhibit AChE, and it could be further studied to develop as a drug with better efficacy than the existing available drugs for treating AD.

Synthesis, In Silico Study and Antimalarial Activity of Triazolo[1,5‐a]pyrimidine Derivatives

AbstractThe present study mainly focused on synthesizing novel triazolo[1,5‐a]pyrimidine‐6‐carboxamide derivatives using multicomponent reaction. Synthesized derivatives were duly characterized using spectroscopic methods of analysis FT‐IR and mass spectroscopy, and 1H NMR and 13C NMR confirmed the structure of compounds. Further, the potential of the synthesized compounds against Plasmodium falciparum dihydrofolate reductase (Pf‐DHFR) inhibitors was evaluated by in vitro antimalarial activity, and the results of the study showed moderate to good antimalarial profile of synthesized entities. In silico study of all the synthesized compounds was carried out using Schrödinger LLC‐2020‐3 Software to explain the binding mode and interactions between molecules and pf DHFR enzyme. To study the drug likeliness of molecules, 3D QSAR and Pharmacokinetic studies have been carried out, and the results obtained showed a good pharmacokinetics profile of two compounds, namely AMP‐24 and AMP‐28, having good IC50 values concerning standard drugs. Further, the in vitro enzyme inhibition assay results suggested that the synthesized compound interacts nicely with the enzyme and might be used as a potent antimalarial agent.

In Silico Analysis for Exploring the Potential Inhibitors Against Breast Cancer (MCF7) Using Curcumin Analogue Compounds

Breast cancer is one of the most problematic diseases in the world. Currently, there are no potential vaccines for the treatment of this disease. Therefore, finding effective compounds, such as curcumin analogs, is crucial to inhibit breast cancer. Forty-five synthesized curcumin analogs were tested on the MCF7 cell line using the MTT assay. It was shown that nine curcumin compounds, Cpd 5, Cpd 9, Cpd 17, Cpd 18, Cpd 21, Cpd 25, Cpd 28, Cpd 32, and Cpd 45, had better inhibitory activities against breast cancer. Furthermore, in silico analysis was developed using 2D and 3D QSAR models with high predictive ability, with an r2 value of 0.834. In addition, based on molecular docking, molecular dynamics, and pharmacophore results, it was shown that these nine compounds had the lowest binding free energy and were also stable during the simulation. The presence of methoxy groups, hydrogen bond donors, and aromatic ring features are the main factors that enhance the biological activity of curcumin analogs. Therefore, these compounds could serve as references for the next stage of drug design.

Identification of Novel Thiazolidinedione Based Pancreatic Lipase Inhibitors for the Management of Obesity Using In Silico Approach

AbstractAccumulation of excessive fat in the body is an indication of obesity, which is becoming an alarming health concern around the world. Pancreatic lipase has been found to have a promising role in the digestion of dietary fats thereby inhibition of pancreatic lipase can be a therapeutic strategy for the management of obesity. Literature showed the anti‐pancreatic lipase potential of thiazolidinediones thereby the current study is designed to identify substituted thiazolidinedione‐based molecules as pancreatic lipase inhibitors. A 3D QSAR model with R2 value of 0.7283 and Stability of 0.843 was generated to determine the nature of substitution necessary for the inhibitory activity. Based on the generated 3D QSAR, the activity of 352 novel‐designed molecules was predicted and further screened through pharmacokinetic parameters. These compounds were docked into the binding site of the pancreatic lipase which led to the identification of 14 hit molecules with dock score between −9.523 to −7.604 kcal/mol. The molecular simulation studies and free energy calculation of the hit compounds i. e. 87 and 80 revealed good stability and binding in the active site of pancreatic lipase. The current study provides 14 hit molecules, which can be synthesized and further evaluated to explore their anti‐pancreatic lipase inhibitory activity.

An In Silico Study Based on QSAR and Molecular Docking and Molecular Dynamics Simulation for the Discovery of Novel Potent Inhibitor against AChE.

Acetylcholinesterase (AChE) is one of the main drug targets for treating Alzheimer's disease. This current study relies on multiple molecular modeling approaches to develop new potent inhibitors of AChE. We explored a 2D QSAR study using the statistical method of multiple linear regression based on a set of substituted 5-phenyl-1,3,4-oxadiazole and N-benzylpiperidine analogs, which were recently synthesized and proved their inhibitory activities against acetylcholinesterase (AChE). The molecular descriptors, polar surface area, dipole moment, and molecular weight are the key structural properties governing AChE inhibition activity. The MLR model was selected based on its statistical parameters: R2 = 0.701, R2test = 0.76, Q2CV = 0.638, and RMSE = 0.336, demonstrating its predictive reliability. Randomization tests, VIF tests, and applicability domain tests were adopted to verify the model's robustness. As a result, 11 new molecules were designed with higher anti-Alzheimer's activities than the model molecule. We demonstrated their improved pharmacokinetic properties through an in silico ADMET study. A molecular docking study was conducted to explore their AChE inhibition mechanisms and binding affinities in the active site. The binding scores of compounds M1, M2, and M6 were (-12.6 kcal/mol), (-13 kcal/mol), and (-12.4 kcal/mol), respectively, which are higher than the standard inhibitor Donepezil with a binding score of (-10.8 kcal/mol). Molecular dynamics simulations over 100 ns were used to validate the molecular docking results, indicating that compounds M1 and M2 remain stable in the active site, confirming their potential as promising anti-AChE inhibitors.

Discovery of putative inhibitors of human Pkd1 enzyme: Molecular docking, dynamics and simulation, QSAR, and MM/GBSA

Polycystic kidney disease is the most prevalent hereditary kidney disease globally and is mainly linked to the overexpression of a gene called PKD1. To date, there is no effective treatment available for polycystic kidney disease, and the practicing treatments only provide symptomatic relief. Discovery of the compounds targeting the PKD1 gene by inhibiting its expression under the disease condition could be crucial for effective drug development. In this study, a molecular docking and molecular dynamic simulation, QSAR, and MM/GBSA-based approaches were used to determine the putative inhibitors of the Pkd1 enzyme from a library of 1379 compounds. Initially, fourteen compounds were selected based on their binding affinities with the Pkd1 enzyme using MOE and AutoDock tools. The selected drugs were further investigated to explore their properties as drug candidates and the stability of their complex formation with the Pkd1 enzyme. Based on the physicochemical and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties, and toxicity profiling, two compounds including olsalazine and diosmetin were selected for the downstream analysis as they demonstrated the best drug-likeness properties and highest binding affinity with Pkd1 in the docking experiment. Molecular dynamic simulation using Gromacs further confirmed the stability of olsalazine and diosmetin complexes with Pkd1 and establishing interaction through strong bonding with specific residues of protein. High biological activity and binding free energies of two complexes calculated using 3D QSAR and Schrodinger module, respectively further validated our results. Therefore, the molecular docking and dynamics simulation-based in-silico approach used in this study revealed olsalazine and diosmetin as potential drug candidates to combat polycystic kidney disease by targeting Pkd1 enzyme.

Use of Pharmacophore Modeling, 3D-atom-based QSAR, ADMET, Docking, and Molecular Dynamics Studies for the Development of Psoralen-based Derivatives as Antifungal Agents

Background:: The mortality and morbidity rates in patients caused by fungi are ex-tremely high. 3-4 % of species of fungi like Candida and Aspergillus are responsible for &gt;99% of invasive fungal infections. Aim:: The goal of the current work was to use several In-silico methods, such as Pharmacophore modeling and 3D-QSAR, to design New chemical entities (NCEs) that have antifungal activity. Material &amp; Method:: A dataset of 40 Psoralen derivatives was taken from available literature, and then, the pharmacophore hypothesis and 3D-QSAR model development were generated using Schrodinger 2023-1 software. After designing a library of 36 compounds, they were sub-jected to ADMET prediction. Screened compounds from the ADMET study were docked with 14 alpha demethylase CYP51 (PDB ID: 3LD6) using Schrödinger software. Molecular dynam-ics (MD) simulation studies were performed on PDB-3LD6 using Desmond-v7.2. Results &amp; Discussion:: The top-ranked hypothesis, AHRRR_1, was taken into consideration when designing the library of potential NCEs.In order to check the drug likeliness of the com-pounds, all 36 designed NCEs were subjected to ADMET prediction using the QikProp tool. The majority of compounds have a good partition coefficient index (less than five). Qplog HERG value was found to be less, making them safer and less toxic. C- 4, 6, 9, 13, 15, 22, 24, 27, 31, and 33 have shown compliance with Lipinski’s rule with zero violations. Compounds C-9, C-13, C-22, C-24, and C-27 have shown better docking scores than the standard Ketocon-azole. Compounds C-9, 24, and 27 have shown a greater number of hydrophobic and hydrogen bond interactions in comparison with the other compounds. Compounds 9, 24, and 27 showed good stability after 100ns molecular simulation simulations. result: The top ranked hypothesis AHRRR_1 was taken into consideration when designing the library of potential NCE&amp;#039;s.In order to check the drug likeliness of the compounds, all 36 designed NCE&amp;#039;s were subjected to ADMET prediction using QikProp tool. The majority of compounds have good partition coefficient index (less than five), and Qplog HERG value was found to be less, making them safer and less toxic.C- 4, 6, 9, 13, 15, 22, 24, 27, 31, 33 have shown compliance to Lipinski’s rule with zero violations. The majority of the compounds had greater binding affinity than the standard Ketoconazole. Three compounds C-9, 24 and 27 have the good hydrophobic and hydrogen bonding interactions required for antifungal activity.The Compounds 9, 24 and 27 showed good stability after 100ns molecular simulation simulations. Conclusion:: In the current work, the application of insilico methods such as pharmacophore hypothesis, 3D QSAR, ADMET study, docking, and simulation studies have helped to optimize Psoralen pharmacophore for potential antifungal activity. Therefore, the outcomes of the present study could provide insights into the discovery of new potential alpha demethylase inhibitors with improved selectivity and activity against fungal infections. other: Nil

2D QSAR Modelling, Docking, Synthesis and Evaluation of 2-substituted Benzimidazole Derivatives as Anti-breast Cancer Agents

Background: Cancer is a leading cause of death worldwide and is anticipated to reach 28,4 million fresh cases globally by 2040. Despite all the progress made in cancer prevention, diagnosis, and treatment, mortality by cancer is in second place. Objectives: The design of novel 2-substituted benzimidazole modelled by QSAR study. Molecular docking studies on the novel derivatives and synthesis characterization and evaluation of the anticancer activity of the novel derivatives against breast cancer cell line MCF 7. Methods: We designed 10 novel benzimidazole derivatives modeled by 2D QSAR. From the ten compounds by applying insilico tools of ADME properties and toxicity and through molecular docking on Tyrosine Kinase (PDB ID: 2SRC). Compound 2AD showed the highest dock score of -9.5 kcal/mol followed by 2 BD and 2GD (-9.3kcal/mol) Molecular dynamic simulation studies were conducted using CABSflex an online molecular dynamic simulation tool. Six compounds were selected for synthesis. The synthesized compounds were characterized and the invitro pharmacological activity was tested on MCF-7 cell line by MTT assay. Results: The compounds 2AD and 2GD showed good percentage inhibition on MCF-7 cell line withIC50 values of 2.757 µg/ml and 2.875 µg/ml respectively. Conclusion: The novel 2-substituted benzimidazole derivatives are good lead compounds for cancer therapy. Optimization of these compounds will be providing more target-specific anticancer agents.

Potent inhibition of human and rat 17β-hydroxysteroid dehydrogenase 1 by curcuminoids and the metabolites: 3D QSAR and in silico docking analysis

ABSTRACT Curcumin, an extensively utilized natural pigment in the food industry, has attracted considerable attention due to its potential therapeutic effects, such as anti-tumorigenic and anti-inflammatory activities. The enzyme 17β-Hydroxysteroid dehydrogenase 1 (17β-HSD1) holds a crucial position in oestradiol production and exhibits significant involvement in oestrogen-responsive breast cancers and endometriosis. This study investigated the inhibitory effects of curcuminoids, metabolites, and analogues on 17β-HSD1, a key enzyme in oestradiol synthesis. Screening 10 compounds, including demethoxycurcumin (IC50, 3.97 μM) and dihydrocurcumin (IC50, 5.84 μM), against human and rat 17β-HSD1 revealed varying inhibitory potencies. These compounds suppressed oestradiol secretion in human BeWo cells at ≥ 5–10 μM. 3D-Quantitative structure-activity relationship (3D-QSAR) and molecular docking analyses elucidated the interaction mechanisms. Docking studies and Gromacs simulations suggested competitive or mixed binding to the steroid or NADPH/steroid binding sites of 17β-HSD1. Predictive 3D-QSAR models highlighted the importance of hydrophobic regions and hydrogen bonding in inhibiting 17β-HSD1 activity. In conclusion, this study provides valuable insights into the inhibitory effects and mode of action of curcuminoids, metabolites, and analogues on 17β-HSD1, which may have implications in the field of hormone-related disorders.

Rational Drug Discovery for Isoxazole Based VEGFR2 Inhibition.

Inhibiting receptor-tyrosine-kinase (RTK) signalling pathways has emerged as a key focus of novel cancer therapy development. Vascular endothelial growth factor receptor (VEGFR) is a member of the RTK family and is required for vasculogenesis and angiogenesis. Because VEGFR 2 is the subtype responsible for cellular angiogenesis and vasculogenesis, blocking it will impair tumour cell blood supply, reducing their development, proliferation, and metastasis. The aim of this study is to obtain an optimised pharmacophore as a VEGFR2 inhibitor using QSAR investigations. This aids in determining the link between structure and activity in new chemical entities (NCEs). The multi-linear regression approach (MLR) method was utilised to generate the QSAR Model using the programme QSARINS v.2.2.4. For 2D QSAR, the best models produced has correlation coefficients of R2= 0.9396. The 3D-QSAR model obtained with R2= 0.9121 and Q2 = 0.8377. Taking docking observations, pharmacological behaviour, and toxicity analyses into account, most of the derivatives demonstrated VEGFR2 inhibitory competence. According to QSAR studies, more electron-donating groups on the benzene ring linked to the isoxazole were shown to be necessary for activity. In molecular docking studies, most compounds have shown stronger affinity for the crucial amino acids Cys:919, Asp:1046, and Glu:885, which are found in typical drugs. All NCEs passed the Lipinski screening.

3D computer modeling of inhibitors targeting the MCF-7 breast cancer cell line.

This study focused on developing new inhibitors for the MCF-7 cell line to contribute to our understanding of breast cancer biology and various experimental techniques. 3D QSAR modeling was used to design new tetrahydrobenzo[4, 5]thieno[2, 3-d]pyrimidine derivatives with good characteristics. Two robust 3D-QSAR models were developed, and their predictive capacities were confirmed through high correlations [CoMFA (Q2 = 0.62, R 2 = 0.90) and CoMSIA (Q2 = 0.71, R 2 = 0.88)] via external validations (R2 ext = 0.90 and R2 ext = 0.91, respectively). These successful evaluations confirm the potential of the models to provide reliable predictions. Six candidate inhibitors were discovered, and two new inhibitors were developed in silico using computational methods. The ADME-Tox properties and pharmacokinetic characteristics of the new derivatives were evaluated carefully. The interactions between the new tetrahydrobenzo[4, 5]thieno[2, 3-d]pyrimidine derivatives and the protein ERα (PDB code: 4XO6) were highlighted by molecular docking. Additionally, MM/GBSA calculations and molecular dynamics simulations provided interesting information on the binding stabilities between the complexes. The pharmaceutical characteristics, interactions with protein, and stabilities of the inhibitors were examined using various methods, including molecular docking and molecular dynamics simulations over 100ns, binding free energy calculations, and ADME-Tox predictions, and compared with the FDA-approved drug capivasertib. The findings indicate that the inhibitors exhibit significant binding affinities, robust stabilities, and desirable pharmaceutical characteristics. These newly developed compounds, which act as inhibitors to mitigate breast cancer, therefore possess considerable potential as prospective drug candidates.

Designing JAK2 Inhibitors Beyond Myeloproliferative Neoplasms ‐ Theoretical and Experimental Analysis for Solid Cancers

AbstractSomatic mutations in JAK2 have been reported to cause myeloproliferative neoplasms, autoimmune disorders, rheumatoid arthritis, and inflammation. JAK2 protein with PDB id 3FUP was selected for docking analysis via cross‐docking. Molecular docking of JAK2 with ATP and crystal ligand revealed their binding affinities and interactions. 3D QSAR models with R2=0.997 and Q2=0.984 having high stability and predictivity were generated. The biological activity of the hit compound obtained from virtual screening, LAS 26879206, was predicted to be 4.21 using the 3D QSAR model. Modification of LAS 26879206 utilizing 3D QSAR contours for modulating its JAK2 inhibitory potential yielded two novel inhibitors with a 2‐aminopyrimidine core – ACP1 and ACPM1. Molecular docking, molecular dynamics simulations, and ADMET analysis indicated improvements in the efficiency of these compounds compared to the hit compound. Synthesis of these compounds was carried out using a two‐step reaction‐ first Buchwald – Hartwig coupling reaction to yield an intermediate ACB1 which was then coupled with appropriate boronic acids via Suzuki reaction to get ACP1 and ACPM1. The effects of these designed compounds as anticancer agents were analyzed in hCT‐116 (human colorectal carcinoma), HeLa (cervical carcinoma), A549 (human lung adenocarcinoma), and A375 (human melanoma) cell lines. ACPM1 was found to be active in all the cell lines with a pIC50 of 5 which was in concordance with the in silico studies. Western blot analysis validated the JAK2 inhibitory property of ACPM1 which can be further ensured by in vivo studies.