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Background: Monoamine oxidase-B (MAO-B) is crucial in breaking down biogenic and dietary amines, with its dysregulation linked to Parkinson’s disease. Objective: This study aims to explore the MAO-B inhibitory potential of 34 hydrazine-linked thiazole derivatives through computational techniques. Methods: Molecular docking against MAO-B (2BYB) assessed binding affinity, complemented by MMGBSA for binding energy evaluation. Pharmacophore modeling and QSAR analysis identified structural features essential for inhibition, while molecular dynamics (MD) simulations validated the stability of ligand-MAO-B complexes. Results: Compound T18 exhibited outstanding binding affinity, while T9 showed the lowest. In vitro studies revealed that T2 had the weakest inhibitory potential, while T19 demonstrated the highest. Pharmacophore modeling identified the six-feature hypothesis ADHRRR_1 as the key structural feature for optimal inhibition. QSAR analysis provided insight into the importance of pharmacophoric features, including the electron-deficient 3-pyridine at N1 of hydrazine, which acts as an electron-withdrawing group that enhances interactions with the enzyme active site, making pyridine a valuable pharmacophore. Additionally, the electronegative fluorinated phenyl ring at C4 of thiazole enhances blood-brain barrier (BBB) permeability and selectivity for MAO-B. Notably, the methyl group on T19 acted as a hydrophobic feature, increasing electron density and boosting inhibitory activity. MD simulations confirmed the stability of the T18/2BYB and T19/2BYB complexes. Furthermore, T19 displayed superior CNS activity and BBB permeability, confirming the methyl group as crucial for enhanced action. Conclusion: These findings underscore the potential of hydrazine-linked thiazole derivatives as potent MAO-B inhibitors. Future in vivo studies are essential to explore their therapeutic benefits further. [ABSTRACT FROM AUTHOR]

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BACKGROUND: The threats to the safety of humans and the environment and the resistance of agricultural chemicals to plant pathogenic fungi and bacteria highlight an urgent need to find safe and efficient alternatives to chemical fungicides and bactericides. In this study, a series of Berberine (BBR) derivatives were designed, synthesized and evaluated for in vitro and in vivo antimicrobial activity against plant pathogenic fungi and bacteria. RESULTS: Bioassay results indicated that compounds A11, A14, A20, A21, A22, A25, A26, E1, E2, E3, Z1 and Z2 showed high inhibitory activity against Sclerotinia sclerotiorum and Botrytis cinerea. Especially, A25 showed a broad spectrum and the highest antifungal activity among these compounds. Its EC50 value against Botrytis cinerea was 1.34 μg mL−1. Compound E6 possessed high inhibitory activity against Xanthomonas oryzae and Xanthomonas Campestris, with MIC90 values of 3.12 μg mL−1 and 1.56 μg mL−1. A Topomer CoMFA model was generated for 3D‐QSAR studies based on anti‐B. cinerea effects, with high predictive accuracy, showed that the addition of an appropriate substituent group at the para‐position of benzyl of BBR derivatives could effectively improve the anti‐B. cinerea activity. In addition, compound A25 could significantly inhibit the spore germination of Botrytis cinerea at low concentration, and compound F4 exhibited remarkable curative and protective efficiencies on rice bacterial leaf blight. CONCLUSION: This study indicates that the BBR derivatives are hopeful for further exploration as the lead compound with novel antimicrobial agents. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Abstract Background Type-2 Diabetes (T2DM) is a long-term medical disorder characterized by Insulin deficiency and high blood glucose levels. Among other medications to cure T2DM, the review of the literature found that various Pyrimidine derivatives act as an agonist for G-protein-coupled receptor 119 (GPR119) was proposed to control blood glucose levels by enhancing the function of pancreatic Beta-cells and its mechanism of action with fewer adverse effects. In the present research work, In-silico investigations were carried out to investigate the potential of the Pyrimidine analog as an agonist to the protein target GPR119 receptor. We performed exhaustive molecular modeling and protein modeling methodologies such as homology modeling, and molecular docking along with various drug designing tools such as 3D-QSAR and Pharmacophore Mapping to ascertain the design of better GPR119 agonists. Results Based on in-depth computational studies, we designed new pyrimidine moiety and analyzed them for GPR119 receptor agonist and further explored the ADMET properties. Designed compounds were found to exhibit better-predicted activities as compared to reference compound. Conclusions The current research on pyrimidine derivatives, using molecular docking, 3D-QSAR and Pharmacophore mapping demonstrated that the obtained computational model has significant properties and the designed molecules and Dataset from this model, produced antidiabetic compound against the target GPR119 i.e., compound 1S, 1Z and 1D with the docking score of − 11.696, − 9.314 and − 8.721, respectively. The pharmacokinetics and drug-likeness studies revealed that these compounds may be the future candidates for the treatment of diabetes acting via the GPR119 agonist mechanism.

Alzheimer’s disease is a neurological disorder marked by the accumulation of amyloid beta (Aβ) aggregates, resulting from mutations in the amyloid precursor protein. The enzyme β-secretase, also known as β-site amyloid precursor protein cleaving enzyme 1 (BACE1), plays a crucial role in generating Aβ peptides. With no targeted therapy available for Alzheimer’s disease, inhibiting BACE1 aspartic protease has emerged as a primary treatment target. Since 1999, compounds demonstrating potential binding to the BACE1 receptor have advanced to human trials. Structural optimization of synthetically derived compounds, coupled with computational approaches, has offered valuable insights for developing highly selective leads with drug-like properties. This review highlights pivotal studies on the design and development of BACE1 inhibitors as anti-Alzheimer’s disease agents. It summarizes computational methods employed in facilitating drug discovery for potential BACE1 inhibitors and provides an update on their clinical status, indicating future directions for novel BACE1 inhibitors. The promising clinical results of Elenbecestat (E-2609) catalyze the development of effective, selective BACE1 inhibitors in the future.

Inserting Isatin (1H indole 2,3‐dione) stands out as an exceptionally captivating element in the realm of drug design and development. Hence, there has been a notable focus in numerous anticancer studies on investigating the potential of various derivatives of Isatin (1H indole 2,3‐dione), including imines, hydrazones, thiosemicarbazones, and other compounds. Therefore, to develop new compounds with anticipated high activity, a novel series of 40 Isatin derivatives have undergone 3D‐QSAR studies as potent anticancer agents against the leukemia cell line (K562). This approach has been pursued due to the significant importance placed on exploring the potential of these derivatives. Through the analysis of graphical contour maps, the generated models yielded favorable statistical outcomes and provided valuable insights into the structural elements that exert a significant influence on the activity. Furthermore, both CoMFA and CoMSIA models have shown suitable reliabilities (q2 = 0.689, 0.772, respectively) and predictive abilities (r2pred = 0.780, 0.892, respectively). As a result, the design of five new compounds (T1–T5) based on the Isatin moiety, which exhibited remarkable inhibitory activity, has successfully been accomplished. Accordingly, molecular docking and molecular dynamics (MD) simulations of 100 ns have been utilized to examine the interaction mechanism and conformational changes of the newly designed compounds at the binding site of BCR‐ABL tyrosine kinase. MD simulation revealed that both compounds T1 and T2 formed stable complexes with BCR‐ABL. Additionally, the assessment of the in‐silico pharmacokinetic parameters indicates favorable ADMET properties. These findings hold promise for the future development of potent BCR‐ABL tyrosine kinase inhibitors. [ABSTRACT FROM AUTHOR]

TRPV4 antagonists that could be potential drugs for treatment and management of neuropathic pain. This study was conducted to systematically design several amino derivatives of 2,4′‐dimethyl‐[4,5′‐bithiazol]‐2‐yl as antagonists. In silico computational methods, such as 3D quantitative structure‐activity relationship modeling (3D‐QSAR), molecular docking, and pharmacokinetic property assessment (ADMET), were used to discover new compounds with strong antagonistic activity. The best‐performing 3D‐QSAR model was developed using a partial least squares approach and comparative molecular similarity analysis (CoMSIA). The developed model demonstrated an excellent ability to correlate and predict properties (R2 = 0.932, Q2 = 0.620, and SEE = 0.109). It was observed that variations in biological activity were significantly influenced by interactions with steric, electrostatic, and hydrophobic fields. Molecular docking was used to validate the 3D‐QSAR methods and to explain the binding site and interactions between the most active ligands and the receptor. Based on these results, a new series of compounds was predicted. The best‐anchored molecules underwent MD simulation to confirm their dynamic behavior and stability, and they also underwent retrosynthetic analysis to assist in their synthesis. [ABSTRACT FROM AUTHOR]

Introduction: The epidermal growth factor receptor (EGFR) presents a crucial target for combatting cancer mortality. Methods: This study employs a suite of computational techniques, including 3D-QSAR, ligand-based virtual screening, molecular docking, fingerprinting analysis, ADME, and DFT-based analyses (MESP, HOMO, LUMO), supplemented by molecular dynamics simulations and MMGB/PBSA free energy calculations, to explore the binding dynamics of quinazoline derivatives with EGFR. With strong q2 and r2 values from CoMFA and CoMSIA models, our 3D- QSAR models reliably predict EGFR inhibitors' efficacy. Results and Discussion: Utilizing a potent model compound as a reference, an E-pharmacophore model was developed to sift through the eMolecules database, identifying 19 virtual screening hits based on ShapeTanimoto, ColourTanimoto, and TanimotoCombo scores. These hits, assessed via 3D- QSAR, showed pIC50 predictions consistent with experimental data. Our analyses elucidate key features essential for EGFR inhibition, reinforced by ADME studies that reveal favorable pharmacokinetic profiles for most compounds. Among the primary phytochemicals examined, potential EGFR inhibitors were identified. Detailed MD simulation analyses on three select ligands—1Q1, 2Q17, and VS1—demonstrated their stability and consistent interaction over 200 ns, with MM/GBSA values corroborating their docking scores and highlighting 1Q1 and VS1's superior EGFR1 affinity. These results position VS1 as an especially promising lead in EGFR1 inhibitor development, contributing valuable insights towards crafting novel, effective EGFR1 inhibitors. [ABSTRACT FROM AUTHOR]

Cyclin-dependent kinase 9 (CDK9) and cytochrome P450 3A4 (CYP3A4) have emerged as promising targets in the development of anticancer drugs, presenting a consistent challenge in the quest for potent inhibitors. CDK9 inhibitors can selectively target fast-growing cancer cells by disrupting transcription elongation, which in turn hinders the production of proteins essential for cell cycle progression and survivaŚ. Understanding how CYP3A4 metabolizes specific chemotherapy drugs allows for personalized treatment plans, optimizing drug dosages according to a patient's metabolic profile. Since many cancer patients undergo combination therapies, and CYP3A4 is vital in drug metabolism, its inhibition or induction by one drug can alter the plasma levels of others, potentially leading to treatment failure or increased toxicity. Therefore, managing CYP3A4 activity is critical for effective cancer treatment. Employing a range of computational methodologies, this study systematically investigated the binding mechanisms of pyrimidine derivatives against CDK9 and CYP3A4. The field-based model demonstrated high R 2 values (0.99), with Q2 (0.66), demonstrating its ability to predict in silico inhibitory activity against the target of this study. The screening process followed in this work led to the discovery of powerful new inhibitor compounds. Of the 15 new compounds designed, three have a high affinity with the target (ranging from −8 to −9 kcal/mol kcal/mol) and were singled out through docking filtration for more detailed investigation. As well as, a reference compound with a substantial pIC50 value of 8.4, serving as the foundation for the development of the new compounds, was included for comparative analysis. To elucidate the essential features of CDK9 and CYP3A4 inhibitor design, a comparative analysis was conducted between 3D-QSAR-generated contours and molecular docking conformations of ligands. Molecular dynamics simulations were carried out for a duration of 100 ns on selected docked complexes, specifically those involving novel compounds with CDK9 and CYP3A4 enzymes. Additionally, the binding free energy for these complexes was assessed using the MM/PBSA method, which evaluates the free energy landscape of protein-ligand interactions. The results of MM/PBSA highlighted the strength of the new compounds in enhancing interactions with the target protein, which favors the results of molecular docking and MD simulation. These insights contribute to a deeper understanding of the mechanisms underlying CDK9 and CYP3A4 inhibition, offering potential avenues for the development of innovative and effective CDK9 inhibitors. [ABSTRACT FROM AUTHOR]

CDK/Cyclins are dysregulated in several human cancers. Recent studies showed inhibition of CDK4/6 was responsible for controlling cell cycle progression and cancer cell growth. In the present study, atom-based and field-based 3D-QSAR, virtual screening, molecular docking and molecular dynamics studies were done for the development of novel pyrrolo[2,3-d]pyrimidine (P2P) derivatives as anticancer agents. The developed models showed good Q2 and r2 values for atom-based 3D-QSAR, which were equal to 0.7327 and 0.8939, whereas for field-based 3D-QSAR the values were 0.8552 and 0.6255, respectively. Molecular docking study showed good-binding interactions with amino acid residues such as VAL-101, HIE-100, ASP-104, ILE-19, LYS-147 and GLU-99, important for CDK4/6 inhibitory activity by using PDB ID: 5L2S. Pharmacophore hypothesis (HHHRR_1) was used in the screening of ZINC database. The top scored ZINC compound ZINC91325512 showed binding interactions with amino acid residues VAL-101, ILE-19, and LYS-147. Enumeration study revealed that the screened compound R1 showed binding interactions with VAL 101 and GLN 149 residues. Furthermore, the Molecular dynamic study showed compound R1, ZINC91325512 and ZINC04000264 having RMSD values of 1.649, 1.733 and 1.610 Å, respectively. These ZINC and enumerated compounds may be used for the development of novel pyrrolo[2,3-d]pyrimidine derivatives as anticancer agent. [ABSTRACT FROM AUTHOR]

Context: Alpha-glucosidase enzyme is considered an important therapeutic target for controlling hyperglycemia associated with type 2 diabetes. Novel scaffolds identified as potential alpha-glucosidase inhibitors from the Maybridge library utilizing pharmacophore modeling, molecular docking and biological evaluation are reported in this manuscript. Method: A total of 51 xanthone series scaffolds previously reported as alpha-glucosidase inhibitors were collected and used as training and test sets. These sets were employed to develop and validate a pharmacophore-based 3D-QSAR model with statistically meaningful results using Schrodinger software. The model showed a high F value (F, 80.1) at five component partial least square factors, a high cross-validation coefficient (Q2, 0.66) and a good correlation coefficient (R2, 0.95). Pearson correlation coefficient (r) of 0.8400 indicated a greater degree of confidence in the model. Subsequently, virtual screening was performed with PHASE module of Schrodinger software using the above model to identify novel alpha-glucosidase inhibitors, and mapped compounds were evaluated for their interactions with the protein. The X-ray co-crystallised structure of the alpha-glucosidase protein in complex with acarbose (PDB Code: 5NN8) was used for molecular docking analysis using GLIDE module and a total of eight compounds were further selected for biological evaluation. Molecular dynamics analysis using GROMACS software was performed in the active site of alpha-glucosidase protein to gain insights into binding mechanism of the four active compounds which were finally found to exhibit inhibitory activity in the biological assay. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Staphylococcus aureus is a prevalent foodborne pathogen, and its resistance has become more pronounced due to antibiotic overuse. In this paper, we constructed a 3D‐QSAR model using 47 naphthalimidopropanediols derivatives (NIOLs). The results indicate that the CoMFA model (q2 = 0.771, r2 = 0.998) and CoMSIA‐ASH model (q2 = 0.638, r2 = 0.995) exhibit favorable predictive capabilities, leading to the design of 11 novel NIOLs as antibacterial agents. ADMET was used to validate their pharmacokinetic characteristics, molecular docking was performed to validate the binding capability of the designed molecules, dynamics simulations, and binding free energy were employed to verify the accuracy of docking results. The results demonstrate excellent performance of the designed novel molecules, which may provide significant references for the development of novel and effective antibacterial agents against S. aureus. [ABSTRACT FROM AUTHOR]

In this work, we performed a 3D‐QSAR study on a dataset of benzimidazole‐indazole‐derived molecules reported as FLT3 inhibitors for the treatment of acute myeloid leukemia (AML). This study led to the design of six new molecules with better FLT3 inhibitory activity than the reference inhibitor (gilteritinib) and the synthesized template molecule (M20). The designed molecules are screened for their drug‐like and ADMET proprieties. The obtained results enabled us to select three molecules as the best candidate FLT3 inhibitors. Molecular docking and MM‐GBSA calculations show that the three molecules are more localized and targeted in the FLT3 active site compared to gilteritinib and M20 molecules. Through molecular dynamics simulations, the insertion of the three designed molecules in the FLT3 active site leads to stable complexes during the simulation period. Finally, the three newly designed molecules represent an interesting proposal for the development of drugs against AML. [ABSTRACT FROM AUTHOR]

In recent years, hepatitis B virus (HBV) core protein allosteric modulators (CpAMs) have become a hot spot to develop new anti‐HBV drugs. Sulfonamide analogues are a new class of CpAMs targeting HBV core protein (Cp), while their biological activity is still needed to be improved and the binding mechanism is unclear still. In this study, we utilized molecular docking and molecular dynamics simulation to explore the binding mode between the novel compounds and HBV Cp. Combining with binding free energy calculation and decomposition, we inferred that TyrE132, ValE124, ThrE128, ThrD109, and IleD105 were key residues during the binding process, and especially, the conformational change of TryE132 was responsible for the stable binding. Besides, reasonable CoMFA (q2 = 0.515, r2ncv = 0.994, and r2pred = 0.628) and CoMSIA (q2 = 0.602, r2ncv = 0.988, and r2pred = 0.681) models were constructed to explore the 3D structure‐activity relationship of the novel compounds. The results suggested that it was favorable to increase the biological activity of sulfonamide analogues when introducing hydrophobic groups to R1 and electronegative groups to R2. In conclusion, we explored the binding mode and structure‐activity relationship between sulfonamides and HBV Cp and provided a theoretical basis for the optimization of this series of compounds. [ABSTRACT FROM AUTHOR]

Background/Objectives: Alterations in the actin cytoskeleton correlates to tumor progression and affect critical cellular processes such as adhesion, migration and invasion. Rho-associated coiled-coil-containing protein kinases (ROCK1 and ROCK2), important regulators of the actin cytoskeleton, are frequently overexpressed in various malignancies. The aim of this study was therefore to identify the key structural features of ROCK1/ROCK2 inhibitors using computer-aided drug design (CADD) approaches. In addition, new developed ROCK inhibitors provided a significant framework for the development of multitarget therapeutics—ROCK/HDAC (histone deacetylases) multitarget inhibitors. Methods: 3D-QSAR (Quantitative structure-activity relationship study) and molecular docking study were employed in order to identify key structural features that positively correlate with ROCK inhibition. MDA-MB-231, HCC1937, Panc-1 and Mia PaCa-2 cells were used for evaluation of anticancer properties of synthesized compounds. Results: C-19 showed potent anti-cancer properties, especially enhancement of apoptosis and cell cycle modulation in pancreatic cancer cell lines. In addition, C-19 and C-22 showed potent anti-migratory and anti-invasive effects comparable to the well-known ROCK inhibitor fasudil. Conclusions: In light of the results of this study, we propose a novel multi-target approach focusing on developing dual HDAC/ROCK inhibitors based on the structure of both C-19 and C-22, exploiting the synergistic potential of these two signaling pathways to improve therapeutic efficacy in metastatic tumors. Our results emphasize the potential of multi-target ROCK inhibitors as a basis for future cancer therapies. [ABSTRACT FROM AUTHOR]

A wealth of literature has highlighted the discovery of various immune modulators, frequently used in clinical practice, yet associated with numerous drawbacks. In light of this pharmacological deficiency, medical scientists are motivated to develop new immune modulators with minimized adverse effects yet retaining the improved therapeutic potential. T-cell differentiation and growth are central to human defense and are regulated by interleukin-2 (IL-2), an immune-modulatory cytokine. However, scientific investigation is hindered due to its flat binding site and widespread hotspot residues. In this regard, a prompt and logical investigation guided by integrated computational techniques was undertaken to unravel new and potential leads against IL-2. In particular, the combination of score-based and pharmacophore-based virtual screening approaches were employed, reducing the data from millions of small molecules to a manageable number. Subsequent docking and 3D-QSAR prediction via CoMFA further helped remove false positives from the data. The reliability of the model was assessed via standard metrics, which explain the model's fitness and the robustness of the model in predicting the activity of new compounds. The extensive virtual screening herein led to the identification of a total of 24 leads with potential anti-IL-2 activity. Furthermore, the theoretical findings were corroborated with in vitro testing, further endorsing the anti-inflammatory potential of the identified leads. [ABSTRACT FROM AUTHOR]

Background: Type-2 Diabetes (T2DM) is a long-term medical disorder characterized by Insulin deficiency and high blood glucose levels. Among other medications to cure T2DM, the review of the literature found that various Pyrimidine derivatives act as an agonist for G-protein-coupled receptor 119 (GPR119) was proposed to control blood glucose levels by enhancing the function of pancreatic Beta-cells and its mechanism of action with fewer adverse effects. In the present research work, In-silico investigations were carried out to investigate the potential of the Pyrimidine analog as an agonist to the protein target GPR119 receptor. We performed exhaustive molecular modeling and protein modeling methodologies such as homology modeling, and molecular docking along with various drug designing tools such as 3D-QSAR and Pharmacophore Mapping to ascertain the design of better GPR119 agonists. Results: Based on in-depth computational studies, we designed new pyrimidine moiety and analyzed them for GPR119 receptor agonist and further explored the ADMET properties. Designed compounds were found to exhibit better-predicted activities as compared to reference compound. Conclusions: The current research on pyrimidine derivatives, using molecular docking, 3D-QSAR and Pharmacophore mapping demonstrated that the obtained computational model has significant properties and the designed molecules and Dataset from this model, produced antidiabetic compound against the target GPR119 i.e., compound 1S, 1Z and 1D with the docking score of − 11.696, − 9.314 and − 8.721, respectively. The pharmacokinetics and drug-likeness studies revealed that these compounds may be the future candidates for the treatment of diabetes acting via the GPR119 agonist mechanism. [ABSTRACT FROM AUTHOR]

AbstractTo elucidate the structure-activity relationship of 17 matrine alkaloids from Oxytropis ochrocephala Bunge, their effect on hepatitis B surface antigen (HBsAg) secretion was studied using the MTT assay. A 3D-QSAR analysis showed a strong correlation between chemical structures and biological activities (q2 = 0.625, r2 = 0.859). Molecular docking and molecular dynamics simulations revealed that hydrogen bonding and hydrophobic interactions with hepatitis B core protein (PDB:5T2P) are key to inhibiting HBsAg secretion, suggesting potential for developing natural anti-hepatitis B drugs. [ABSTRACT FROM AUTHOR]

Prostate cancer is a well-known disease that has gained significant attention in recent years. To improve and suggest new compounds with anticancer activity, it has become essential to identify new proposed agents through innovative and reliable methods such as computational small molecule discovery methods. In this regard, 3D-QSAR and Molecular Docking studies have been conducted on disubstituted 1,2,3-triazole derivatives as antiproliferative analogs, using static methods to find the right model. The study established 3D-QSAR model based on Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA). The best model was obtained with CoMFA model (Q2 = 0.696, R2 = 0.992, R = 0.985) and CoMSIA model (Q2 = 0.582, R2 = 0.992, R = 0.984) statistical coefficients. To determine the predictive power of the model, we need to calculate the parameters of k, Roy, Golbraikh, and Tropsha for the test set and the y, SEE, and t-F randomization tests for the training set. Docking's results suggest that amino acids (PDB; 3 ERT), Asp351, Leu384, Arg394, Phe404, Leu346, Leu525, and Thr347, have a significant interest in anticancer activity. The CoMFA model's steric and electrostatic field contours were studied to determine the results further. The study suggests four new antiproliferative agents that have demonstrated reliability through ADMET and toxicophore methods. [ABSTRACT FROM AUTHOR]

Alzheimer's disease is a neurological disorder marked by the accumulation of amyloid beta (Aβ) aggregates, resulting from mutations in the amyloid precursor protein. The enzyme β-secretase, also known as β-site amyloid precursor protein cleaving enzyme 1 (BACE1), plays a crucial role in generating Aβ peptides. With no targeted therapy available for Alzheimer's disease, inhibiting BACE1 aspartic protease has emerged as a primary treatment target. Since 1999, compounds demonstrating potential binding to the BACE1 receptor have advanced to human trials. Structural optimization of synthetically derived compounds, coupled with computational approaches, has offered valuable insights for developing highly selective leads with drug-like properties. This review highlights pivotal studies on the design and development of BACE1 inhibitors as anti-Alzheimer's disease agents. It summarizes computational methods employed in facilitating drug discovery for potential BACE1 inhibitors and provides an update on their clinical status, indicating future directions for novel BACE1 inhibitors. The promising clinical results of Elenbecestat (E-2609) catalyze the development of effective, selective BACE1 inhibitors in the future. [ABSTRACT FROM AUTHOR]

To discover novel and efficient compounds against Aphis gossypii Glover, a series of novel terpene ester derivatives containing the structure of bicyclo[2.2.1]heptane were designed and synthesized using tschimganin as the lead compound. Bioactivity assays showed that most tschimganin analogs exhibited moderate to outstanding insecticidal activity against A. gossypii. In particular, compound 56 (LC50 = 0.28 μg mL−1), identified as (1S,2S,4R)-1,7,7-trimethylbicyclo[2.2.1]heptan-2-yl nicotinate, exhibited the best activity, which was significantly superior to that of imidacloprid (LC50 = 0.54 μg mL−1) and sulfoxaflor (LC50 = 0.70 μg mL−1). The precise and dependable 3D-QSAR model suggests a promising direction for further design of more active tschimganin-based insecticides. Metabolomics showed that compound 56 disrupted detoxification, amino acid biosynthesis, and energy metabolism and may affect the central nervous system of A. gossypii. The results of this study indicated that tschimganin analogs are a potential new class of green insecticides that can be used for the integrated management of A. gossypii.

Breast cancer is the most common illness among women, accounting for 25% of all diagnoses, as stated by the American Cancer Society. Current research focuses on 43 compounds of styrylquinoline derivatives as potential inhibitors of tubulin to design a new drug that could potentially be effective against breast cancer cells in humans. The target compounds were subjected to a three-dimensional quantitative structure-activity relationship/comparative molecular similarity indices analysis (CoMSIA) approach, where CoMSIA models were used; the best results obtained are (Q 2 = 0.84, R 2 = 0.97, rext2{r}_{\text{ext}}^{2} = 0.91), H-bond acceptor field was discovered to be important for increasing inhibitory activity by examining the contour maps (54%), and it plays a key role in the prediction of anticancer activity. Based on the contour maps of the CoMSIA models, we obtained information that allows us to propose four new molecules with higher cancer inhibitory than the 43 compounds found in the literature. The molecular docking was applied to determine the likely types of binding between the tubulin protein (PDB ID: 4O2B) and the proposed compounds, and the results show that M1 has a higher total score of 6.53 and two interactions with important conventional hydrogen bond type, followed by compound M2 with a total score of 5.74. Furthermore, the designed molecules showed better pharmacokinetic properties based on absorption, distribution, metabolism, excretion, and toxicity properties. Molecular dynamics simulations at 100 ns were conducted to confirm the binding stability of the selected ligands (M1 and M2) with tubulin protein. The simulation parameters used in the current study are root mean square deviation, root mean square fluctuation, H-bond, Rg, solvent accessible surface area, and binding energy. As a result, the designed compounds (ligands M1 and M2) have shown noteworthy potential as a drug candidate for experimental in vivo and in vitro testing due to their potential inhibition of breast cancer. Finally, the study of retrosynthesis in this work facilitates the synthesis of drug candidates.

Human neutrophil elastase (HNE) plays a key role in initiating inflammation in the cardiopulmonary and systemic contexts. Pathological auto-proteolysed two-chain (tc) HNE exhibits reduced binding affinity with inhibitors. Using AutoDock Vina v1.2.0, 66 flavonoid inhibitors, sivelestat and alvelestat were docked with single-chain (sc) HNE and tcHNE. Schrodinger PHASE v13.4.132 was used to generate a 3D-QSAR model. Molecular dynamics (MD) simulations were conducted with AMBER v18. The 3D-QSAR model for flavonoids with scHNE showed r2 = 0.95 and q2 = 0.91. High-activity compounds had hydrophobic A/A2 and C/C2 rings in the S1 subsite, with hydrogen bond donors at C5 and C7 positions of the A/A2 ring, and the C4' position of the B/B1 ring. All flavonoids except robustaflavone occupied the S1'-S2' subsites of tcHNE with decreased AutoDock binding affinities. During MD simulations, robustaflavone remained highly stable with both HNE forms. Principal Component Analysis suggested that robustaflavone binding induced structural stability in both HNE forms. Cluster analysis and free energy landscape plots showed that robustaflavone remained within the sc and tcHNE binding site throughout the 100 ns MD simulation. The robustaflavone scaffold likely inhibits both tcHNE and scHNE. It is potentially superior to sivelestat and alvelestat and can aid in developing therapeutics targeting both forms of HNE. [ABSTRACT FROM AUTHOR]

InhA is an enoyl acyl carrier reductase that catalyzes the chemo-selective reduction of its 2-trans-enoyl-ACP substrate. The pharmacological effects of the frontline medications used in the treatment of tuberculosis are elicited by inhibiting the enzyme InhA, which disrupts the mycolic acid biosynthesis pathway. The present study involves development of ligand-based pharmacophore model, docking studies, generation of 3D-QSAR model, and molecular dynamic simulation studies of virtually screened putative InhA inhibitors. The best field-based 3D-QSAR model was validated using partial least-square regression (PLS) method with high regression coefficient for training set (R2) = 0.9256 and test set (R2) = 0.7542, cross-validated coefficient (rcv2) = 0.72 and R2pred = 0.9764. Also, virtual screening yielded compounds 4, 25, 1, and 30 exhibiting appreciable interactions (docking scores −5.972, −3.819, −3.801, and −3.701, respectively with InhA synthetase; PDB ID: 1BVR). Further, ADMET studies supported drug-like potential of compounds 25, 1, and 30 whereas compound 4 showed negligible human oral absorption. The molecular dynamic simulation studies of the top scored molecule 25 suggested stability of 25-1BVR complex over the course of simulation run. Therefore, this work can be helpful for future discovery of novel InhA inhibitors against drug-resistant tuberculosis. [ABSTRACT FROM AUTHOR]

Transient receptor potential vanilloid 1 (TRPV1) was reported to be a putative target for recovery from chronic pain, producing analgesic effects after its inhibition. A series of drug candidates were previously developed, without the ability to ameliorate the therapeutic outcome. Starting from previously designed compounds, derived from the hybridization of antagonist SB-705498 and partial agonist MDR-652, we performed a virtual screening on a pharmacophore model built by exploiting the Cryo-EM 3D structure of a nanomolar antagonist in complex with the human TRPV1 channel. The pharmacophore model was described by three pharmacophoric features, taking advantage of both the bioactive pose of the antagonist and the receptor exclusion spheres. The results of the screening were implemented inside a 3D-QSAR model, correlating with the negative decadic logarithm of the inhibition rate of the ligands. After the validation of the obtained 3D-QSAR model, we designed a new series of compounds by introducing key modifications on the original scaffold. Again, we determined the compounds' binding poses after alignment to the pharmacophoric model, and we predicted their inhibition rates with the validated 3D-QSAR model. The obtained values resulted in being even more promising than parent compounds, demonstrating that ongoing research still leaves much room for improvement. [ABSTRACT FROM AUTHOR]

The 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. [ABSTRACT FROM AUTHOR]

Considering the escalating global prevalence and the huge therapeutic demand for the treatment of hypertension, there is a persistent need to identify novel target sites for vasodilator action. This study aimed to investigate the role of TRPA1 channels in carvacrol-induced vasodilation and to design novel compounds based on carvacrol structure with improved activities. In an isolated tissue bath experiment, it was shown that 1 µM of the selective TRPA1 antagonist A967079 significantly (p < 0.001) reduced vasodilation induced by 3 mM of carvacrol. A reliable 3D-QSAR model with good statistical parameters was created (R2 = 0.83; Q2 = 0.59 and R p r e d 2 = 0.84) using 29 TRPA1 agonists. Obtained results from this model were used for the design of novel TRPA1 activators, and to predict their activity against TRPA1. Predicted pEC50 activities of these molecules range between 4.996 to 5.235 compared to experimental pEC50 of 4.77 for carvacrol. Molecular docking studies showed that designed molecules interact with similar amino acid residues of the TRPA1 channel as carvacrol, with eight compounds showing lower binding energies. In conclusion, carvacrol-induced vasodilation is partly mediated by the activation of TRPA1 channels. Combining different in silico approaches pointed out that the molecule D27 (2-[2-(hydroxymethyl)-4-methylphenyl]acetamide) is the best candidate for further synthesis and experimental evaluation in in vitro conditions. [ABSTRACT FROM AUTHOR]

Inhibition of ACE is considered as one of the main strategies to reduce hypertension. ACE inhibitors derived from Suaeda salsa (S. salsa) present a novel antihypertensive agent source. This study employed 3D-QSAR pharmacophore, metabolomics, docking-based screening, and molecular dynamics simulations to identify ACE inhibitors from S. salsa. A set of 53 known molecules was chemically diverse to construct a 3D-QSAR model for predictive purposes. S. salsa was characterized using UPLC-QqQ-MS/MS and UPLC-Q-TOF-LC-MS techniques, 211 and 586 kinds of bioactive metabolites were identified, respectively. A total of 680 compounds were collected for database construction and virtual screening. An ADMET assessment was conducted to evaluate drug-likeness and pharmacokinetics parameters. Moreover, molecular docking results show that six top hit compounds bind to ACE tightly. Specially, diosmin could interact with ACE by hydrogen bond, Pi-cation bond, and metal bond. Molecular dynamics (MD) simulation and MMPBSA calculations were subsequently employed to elucidate complex stability and the interaction between diosmin and ACE, indicating it a strong ACE inhibitory activity. In conclusion, this study suggests that S.salsa represents a potential source of antihypertensive agents. [ABSTRACT FROM AUTHOR]

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, R² = 0.90) and CoMSIA (Q² = 0.71, R² = 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 100 ns, 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. [ABSTRACT FROM AUTHOR]

Blocking the interaction between programmed cell death‐1 (PD‐1) and programmed cell death‐ligand 1 (PD‐L1) is a crucial immunotherapeutic strategy for cancer. Currently, all inhibitors available on the market that target PD‐1/PD‐L1 are monoclonal antibodies, with no small molecule drugs yet accessible. This study focused on PD‐L1 and conducted three‐dimensional quantitative structure‐activity relationship (3D‐QSAR) research on 39 PD‐L1 inhibitors using Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA). The CoMFA (q2=0.593, r2=0.991) and CoMSIA (q2=0.542, r2=0.971) models were successfully established. Based on these models, a series of structurally novel and potentially active PD‐L1 inhibitors (37 a–37 e) were designed. Among these compounds, 37 c exhibited superior performance, with CoMFA predicting a pIC50 value of 9.204 and CoMSIA predicting a pIC50 value of 8.597. Further molecular docking and molecular dynamics simulations revealed that compound 37 c establishes hydrophobic interactions with BTyr56 and BVal68 of PD‐L1, engages in hydrogen bonds with AAsp122, ALys124, and BTyr123, and forms electrostatic interactions with ALys124 and AMet115. The design of this biphenyl series of inhibitors offers additional options for the development of small molecule inhibitors targeting PD‐L1, with 37 c expected to be a promising inhibitor of PD‐L1. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Plant pathogenic fungi pose a major threat to global food security, ecosystem services, and human livelihoods. Effective and broad-spectrum fungicides are needed to combat these pathogens. In this study, a novel antifungal 2-oxyacetate hydrazide quinoxaline scaffold as a simple analogue was designed and synthesized. Their antifungal activities were evaluated against Botrytis cinerea (B. cinerea), Altemaria solani (A. solani), Gibberella zeae (G. zeae), Rhizoctonia solani (R. solani), Colletotrichum orbiculare (C. orbiculare), and Alternaria alternata (A. alternata). These results demonstrated that most compounds exhibited remarkable inhibitory activities and possessed better efficacy than ridylbacterin, such as compound 15 (EC50 = 0.87 μg/mL against G. zeae, EC50 = 1.01 μg/mL against C. orbiculare) and compound 1 (EC50 = 1.54 μg/mL against A. alternata, EC50 = 0.20 μg/mL against R. solani). The 3D-QSAR analysis of quinoxaline-2-oxyacetate hydrazide derivatives has provided new insights into the design and optimization of novel antifungal drug molecules based on quinoxaline. [ABSTRACT FROM AUTHOR]

Objective: Acetylcholinesterase (AChE) is a crucial enzyme in the nervous system that catalyzes the degradation of acetylcholine, a neurotransmitter. Its primary role is to regulate the transmission of nerve signals by breaking down acetylcholine after it has conveyed its message to the target cell. Methods: This study employed computational methods, including 3D-QSAR, molecular docking, ADMET, and molecular dynamics simulations, to analyze the relationship between chemical structure and acetylcholinesterase inhibition mechanism by spiropyrazoline derivatives COMFA and COMSIA predicted the inhibitory activities of the proposed spiropyrazoline derivatives against acetylcholinesterase, where the best models are (COMSIA/S + E + H) (Q2 = 0.517, R2 = 0.904, R2 test = 0.931). Results and Discussion: Molecular docking results revealed that the new (I) complex interacts with critical residues in the major circuits of the AChE main chain, with residues TRP286, TRP86, TYR341, TYR72, TYR124, and TYR337 more than compound (II). This residue plays an essential role in the stability of the complex. A molecular dynamics simulation explored the binding stability and conformational interaction changes of (I) and molecule (II) with acetylcholinesterase complexes at 100 ns. Both compounds showed good stability regarding RMSD, Rg, RMSF, and SASA values. Compound (I) shows remarkable stability in the active site of AChE compared to compound (II). In addition, Lipinski's rule for predicting pharmacokinetics with ADMET is satisfactory. The retrosynthetic approach was used to develop an efficient and convenient synthetic route for preparing the target molecule (I). Conclusions: The present study offers theoretical insights into the development, prediction, and design of new compounds that specifically target acetylcholinesterase. [ABSTRACT FROM AUTHOR]

IntroductionThe epidermal growth factor receptor (EGFR) presents a crucial target for combatting cancer mortality.MethodsThis study employs a suite of computational techniques, including 3D-QSAR, ligand-based virtual screening, molecular docking, fingerprinting analysis, ADME, and DFT-based analyses (MESP, HOMO, LUMO), supplemented by molecular dynamics simulations and MMGB/PBSA free energy calculations, to explore the binding dynamics of quinazoline derivatives with EGFR. With strong q2 and r2 values from CoMFA and CoMSIA models, our 3D- QSAR models reliably predict EGFR inhibitors’ efficacy.Results and DiscussionUtilizing a potent model compound as a reference, an E-pharmacophore model was developed to sift through the eMolecules database, identifying 19 virtual screening hits based on ShapeTanimoto, ColourTanimoto, and TanimotoCombo scores. These hits, assessed via 3D- QSAR, showed pIC50 predictions consistent with experimental data. Our analyses elucidate key features essential for EGFR inhibition, reinforced by ADME studies that reveal favorable pharmacokinetic profiles for most compounds. Among the primary phytochemicals examined, potential EGFR inhibitors were identified. Detailed MD simulation analyses on three select ligands—1Q1, 2Q17, and VS1—demonstrated their stability and consistent interaction over 200 ns, with MM/GBSA values corroborating their docking scores and highlighting 1Q1 and VS1’s superior EGFR1 affinity. These results position VS1 as an especially promising lead in EGFR1 inhibitor development, contributing valuable insights towards crafting novel, effective EGFR1 inhibitors.

Abstract Decaprenylphosphoryl-β-D-ribose-2′-epimerase (DprE1), a crucial enzyme in the process of arabinogalactan and lipoarabinomannan biosynthesis, has become the target of choice for anti-TB drug discovery in the recent past. The current study aims to find the potential DprE1 inhibitors through in-silico approaches. Here, we built the pharmacophore and 3D-QSAR model using the reported 40 azaindole derivatives of DprE1 inhibitors. The best pharmacophore hypothesis (ADRRR_1) was employed for the virtual screening of the chEMBL database. To identify prospective hits, molecules with good phase scores (> 2.000) were further evaluated by molecular docking studies for their ability to bind to the DprE1 enzyme (PDB: 4KW5). Based on their binding affinities (

Abstract 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.