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Isocitrate dehydrogenase 1 (IDH1) is a necessary enzyme for cellular respiration in the tricarboxylic acid cycle. Mutant isocitrate dehydrogenase 1 (mIDH1) has been detected overexpressed in a variety of cancers. mIDH1 inhibitor ivosidenib (AG-120) was only approved by the Food and Drug Administration (FDA) for marketing, nevertheless, a range of resistance has been frequently reported. In this study, several mIDH1 inhibitors with the common backbone pyridin-2-one were explored using the three-dimensional structure–activity relationship (3D-QSAR), scaffold hopping, absorption, distribution, metabolism, excretion (ADME) prediction, and molecular dynamics (MD) simulations. Comparative molecular field analysis (CoMFA, R2 = 0.980, Q2 = 0.765) and comparative molecular similarity index analysis (CoMSIA, R2 = 0.997, Q2 = 0.770) were used to build 3D-QSAR models, which yielded notably decent predictive ability. A series of novel structures was designed through scaffold hopping. The predicted pIC50 values of C3, C6, and C9 were higher in the model of 3D-QSAR. Additionally, MD simulations culminated in the identification of potent mIDH1 inhibitors, exhibiting strong binding interactions, while the analyzed parameters were free energy landscape (FEL), radius of gyration (Rg), solvent accessible surface area (SASA), and polar surface area (PSA). Binding free energy demonstrated that C2 exhibited the highest binding free energy with IDH1, which was −93.25 ± 5.20 kcal/mol. This research offers theoretical guidance for the rational design of novel mIDH1 inhibitors. [ABSTRACT FROM AUTHOR]

Fungal infections are a growing public health problem worldwide. Despite the availability of several medicines, their efficacy is still constrained by fungal resistance. This research conducted the 2D/3D-QSAR analysis on twenty-nine triazole molecules previously evaluated for their antifungal activity. The HQSAR/B-H, CoMFA and CoMSIA models were built using twenty-three molecules in the training set. They show high Q2 values (0.646, 0.564 and 0.561, respectively) and important R2 values (0.764, 0.805 and 0.787, respectively). The predictive capacity of the established models was validated by external validation; they performed well. The contour maps derived from the HQSAR/B-H, CoMFA and CoMSIA models provide more detail to identify favorable and unfavorable groupings impacting the activity. Then, 4 proposed new triazole molecules with significant antifungal activity were suggested. In addition, the molecular docking results showed good binding energies and interactions of the proposed inhibitors in the active site of the receptor studied. The molecular dynamics and MM/PBSA methods confirmed and validated the molecular docking results. The new triazole molecules were evaluated for their oral bioavailability and toxicity using ADME/Tox properties. Finally, the retrosynthesis method created a synthetic pathway for the candidate inhibitor Z1.

According to the WHO, antimicrobial resistance is among the top 10 threats to global health. Due to increased resistance rates, an increase in the mortality and morbidity of patients has been observed, with projections of more than 10 million deaths associated with infections caused by antibacterial resistant microorganisms. Our research group has developed a new family of pyrimido-isoquinolin-quinones showing antibacterial activities against multidrug-resistant Staphylococcus aureus. We have developed 3D-QSAR CoMFA and CoMSIA studies (r2 = 0.938; 0.895), from which 13 new derivatives were designed and synthesized. The compounds were tested in antibacterial assays against methicillin-resistant Staphylococcus aureus and other bacterial pathogens. There were 12 synthesized compounds active against Gram-positive pathogens in concentrations ranging from 2 to 32 µg/mL. The antibacterial activity of the derivatives is explained by the steric, electronic, and hydrogen-bond acceptor properties of the compounds. [ABSTRACT FROM AUTHOR]

Isocitrate dehydrogenase 1 (IDH1) is a necessary enzyme for cellular respiration in the tricarboxylic acid cycle. Mutant isocitrate dehydrogenase 1 (mIDH1) has been detected overexpressed in a variety of cancers. mIDH1 inhibitor ivosidenib (AG-120) was only approved by the Food and Drug Administration (FDA) for marketing, nevertheless, a range of resistance has been frequently reported. In this study, several mIDH1 inhibitors with the common backbone pyridin-2-one were explored using the three-dimensional structure–activity relationship (3D-QSAR), scaffold hopping, absorption, distribution, metabolism, excretion (ADME) prediction, and molecular dynamics (MD) simulations. Comparative molecular field analysis (CoMFA, R2 = 0.980, Q2 = 0.765) and comparative molecular similarity index analysis (CoMSIA, R2 = 0.997, Q2 = 0.770) were used to build 3D-QSAR models, which yielded notably decent predictive ability. A series of novel structures was designed through scaffold hopping. The predicted pIC50 values of C3, C6, and C9 were higher in the model of 3D-QSAR. Additionally, MD simulations culminated in the identification of potent mIDH1 inhibitors, exhibiting strong binding interactions, while the analyzed parameters were free energy landscape (FEL), radius of gyration (Rg), solvent accessible surface area (SASA), and polar surface area (PSA). Binding free energy demonstrated that C2 exhibited the highest binding free energy with IDH1, which was −93.25 ± 5.20 kcal/mol. This research offers theoretical guidance for the rational design of novel mIDH1 inhibitors.

Human leukotriene A4 hydrolase enzyme (LTA4H) catalyses the biotransformation of the inactive precursor leukotriene A4 (LTA4) to the bioactive Leukotriene B4 (LTB4), which causes many inflammatory responses in the human body. Therefore, the selective inhibition of this enzyme becomes a useful strategy for the treatment of several illnesses such as asthma, allergic rhinitis, cardiovascular diseases, and cancer. Herein we report a 3D-QSAR/ /CoMFA and CoMSIA study on a series of 47 benzimidazoles, benzoxazoles, benzothiazoles and thiazolopyridines reported as potent LTA4H inhibitors. Good statistical parameters were obtained for the best model (q2 = 0.568, r2 ncv = 0.891 and r2 test = 0.851). A new series of 10 compounds capable of inhibiting leukotriene A4 hydrolase with high potency was presented. All designed inhibitors showed low IC50 in nano- and sub-nanomolar ranges, when they were evaluated in 3D-QSAR models. Subsequently, the designed molecules, as well as the least and most active compounds were subjected to docking and molecular dynamics studies into LTA4H. In conclusion, we summarised a thorough structure–activity relationship (SAR) of LTA4H inhibitors of heterocyclic structure. These models can be used for the rational proposal of new inhibitors.

Increasing evidence has shown collagen hydrolysate involves a variety of bioactivities. In our previous study, multiple antiplatelet peptides containing Hyp/Pro-Gly were identified in collagen hydrolysates from Salmo salar and silver carp skin and exhibited anti-thrombosis activity without bleeding risks in vivo. However, the relationship between structure and activity remains unknown. We performed 3D-QSAR studies on 23 Hyp/Pro-Gly-containing peptides in which 13 peptides were reported before. CoMFA, Topomer CoMFA and CoMSIA analyses were used to generate the QSAR models. Topomer CoMFA analysis showed a q2 value of 0.710, an r2 value of 0.826, an r2pred value of 0.930, and the results showed that Hyp instead of Pro was more important for improving the antiplatelet activity. CoMSIA analysis showed a q2 value of 0.461, an r2 value of 0.999, and an r2pred value of 0.999. Compared with the electrostatic field and hydrogen bond donor field, the steric field, hydrophobic field and hydrogen bond receptor field have great influence on the activity of antiplatelet peptides. The predicted peptide EOGE exhibited antiplatelet activity induced by ADP, and inhibited thrombus formation (300 μmol/kg bw) without bleeding risks. Combined results of these studies indicate that OG-containing peptides had a potential to be developed into an effective specific medical food in the prevention of thrombotic diseases. [ABSTRACT FROM AUTHOR]

Lim kinase (Limk), as an important cytoskeletal regulator, plays an important role in cancer manifestations and neuronal diseases. Limk1 is a member of the Limk family, which is mainly involved in the invasion and metastasis of tumor cells and is abnormally expressed in a variety of cell carcinoma tissues. In this paper, a series of Limk1 inhibitors with aminothiazole skeleton were used to design potent and efficient Limk1 inhibitors by computational approaches. Firstly, the 3D-QSAR model was constructed, and both CoMFA and CoMSIA models have good correlation and prediction ability. The binding requirements between ligand and receptor protein were then further explored through molecular docking, including the critical forces between Limk1 inhibitors and active site residues. Finally, based on the 3D-QSAR model and molecular docking results analysis, three new compounds with theoretically better activity were designed and their ADME properties were predicted. [ABSTRACT FROM AUTHOR]

Triple-negative breast cancer (TNBC) is defined as a kind of breast cancer that lacks estrogen receptors (ER), progesterone receptors (PR), and human epidermal growth factor receptors (HER2). This cancer accounts for 10–15% of all breast cancers and has the features of high invasiveness and metastatic potential. The treatment regimens are still lacking and need to develop novel inhibitors for therapeutic strategies. Three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses, based on a series of forty-seven thieno-pyrimidine derivatives, were performed to identify the key structural features for the inhibitory biological activities. The established comparative molecular field analysis (CoMFA) presented a leave-one-out cross-validated correlation coefficient q2 of 0.818 and a determination coefficient r2 of 0.917. In comparative molecular similarity indices analysis (CoMSIA), a q2 of 0.801 and an r2 of 0.897 were exhibited. The predictive capability of these models was confirmed by using external validation and was further validated by the progressive scrambling stability test. From these results of validation, the models were determined to be statistically reliable and robust. This study could provide valuable information for further optimization and design of novel inhibitors against metastatic breast cancer. [ABSTRACT FROM AUTHOR]

Lim kinase (Limk), as an important cytoskeletal regulator, plays an important role in cancer manifestations and neuronal diseases. Limk1 is a member of the Limk family, which is mainly involved in the invasion and metastasis of tumor cells and is abnormally expressed in a variety of cell carcinoma tissues. In this paper, a series of Limk1 inhibitors with aminothiazole skeleton were used to design potent and efficient Limk1 inhibitors by computational approaches. Firstly, the 3D-QSAR model was constructed, and both CoMFA and CoMSIA models have good correlation and prediction ability. The binding requirements between ligand and receptor protein were then further explored through molecular docking, including the critical forces between Limk1 inhibitors and active site residues. Finally, based on the 3D-QSAR model and molecular docking results analysis, three new compounds with theoretically better activity were designed and their ADME properties were predicted.

Background: 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., Objective: 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., Method: 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., Results: 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., Conclusion: 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., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2024.)

Anaplastic lymphoma kinase (ALK) is a promising target for the treatment of non-small cell lung cancer. Under crizotinib treatment, drug resistance and progressive disease appeared after the point mutations arising in the kinase domain of ALK. Second-generation ALK inhibitors can solve the deficiencies of the first generation, especially the drug resistance in cancer chemotherapy. Ceritinib (LDK378), a pyrimidine derivative, for example, can inhibit the activity of ALK with an IC50 value of 40.7 nmol/L, and can experience disease progression after initial treatment with crizotinib. Unfortunately, clear structure–activity relationships have not been identified to date, impeding the rational design of future compounds possessing ALK inhibition activity. To explore interesting insights into the structures of pyrimidine derivatives that influence the activities of the second-generation ALK inhibitors, three-dimensional quantitative structure–activity relationship (3D-QSAR) and molecular docking were performed on a total of 45 derivatives of pyrimidine. Comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) techniques were used to generate 3D-QSAR models. CoMFA and CoMSIA were performed using the Sybyl X 2.0 package. Molecular docking analysis was performed using the Surflex-Dock module in SYBYL-X 2.0 package. We found in the CoMFA model that the non-cross-validated r2 value was 0.998, the cross-validated q 2 value was 0.663, and the F statistic value was 2,401.970, while the r2 value was 0.988; q 2 value was 0.730, and F value was 542.933 in CoMSIA models, suggesting the good predictability of the CoMFA and CoMSIA models. 3D contour maps and docking results suggested that different groups on the core parts of the compounds could enhance the biological activities. Based on these results, the established 3D-QSAR models and the binding structures of ALK inhibitors obtained favor the prediction of the activity of new inhibitors and will be helpful in the reasonable design of ALK inhibitors in the future.

DNA gyrase B (GyrB) plays a critical role in DNA replication, repair, recombination, and transcription and has become an attractive target for a number of antibacterial agents. In the present work, to better comprehend the structure–activity relationship and mechanism of action of novel series of GyrB inhibitors, a theoretical study of three-dimensional-quantitative structure–activity relationship (3D-QSAR), molecular docking, molecular dynamics (MD) simulations, and binding free energy analysis were performed. The results showed that CoMFA (R2cv = 0.591, R2pred = 0.7698) and CoMSIA (R2cv = 0.629, R2pred = 0.6848) models possessed robust stability and predictability. The derived contour maps of steric, electrostatic, and hydrogen bond donor field further displayed the modified information of these inhibitors. Molecular docking was further conducted to provide the initial binding conformation for MD simulations. Subsequently, MD simulations were applied to explore the key amino acids and binding modes at the active site. The binding free energy decomposition analysis further indicates that the residues Ile54, Glu55, Arg83, Ala85, Val86 and Thr128 are essential for the high selectivity of inhibitors. Overall, these results would serve as a significant guideline for the discovery and design of novel GyrB inhibitors.

Increasing evidence has shown collagen hydrolysate involves a variety of bioactivities. In our previous study, multiple antiplatelet peptides containing Hyp/Pro-Gly were identified in collagen hydrolysates from Salmo salar and silver carp skin and exhibited anti-thrombosis activity without bleeding risks in vivo. However, the relationship between structure and activity remains unknown. We performed 3D-QSAR studies on 23 Hyp/Pro-Gly-containing peptides in which 13 peptides were reported before. CoMFA, Topomer CoMFA and CoMSIA analyses were used to generate the QSAR models. Topomer CoMFA analysis showed a q2 value of 0.710, an r2 value of 0.826, an r2pred value of 0.930, and the results showed that Hyp instead of Pro was more important for improving the antiplatelet activity. CoMSIA analysis showed a q2 value of 0.461, an r2 value of 0.999, and an r2pred value of 0.999. Compared with the electrostatic field and hydrogen bond donor field, the steric field, hydrophobic field and hydrogen bond receptor field have great influence on the activity of antiplatelet peptides. The predicted peptide EOGE exhibited antiplatelet activity induced by ADP, and inhibited thrombus formation (300 μmol/kg bw) without bleeding risks. Combined results of these studies indicate that OG-containing peptides had a potential to be developed into an effective specific medical food in the prevention of thrombotic diseases.

Piperidine and piperazine derivatives exhibit a diverse range of biological applications, including antipsychotic activity. In this study, a dataset of molecules containing piperidine, piperazine moieties that possess serotonin 5-HT2A and dopamine D2 inhibitory activity have been chosen for Pharmacophore modeling, Quantitative Structure–Activity (3D-QSAR) Relationship, Molecular docking, and ADME studies. The pharmacophoric hypothesis was found to be AAHPRRR_1 having seven features as one H-bond acceptor (A), one hydrophobic (H), one positive ion acceptor (P), and three aromatic rings (R), with survival score = 6.465 and AUC = 0.92. Based on the best hypothesis, the ZINC-Data base was virtually screened to find out the lead molecules. 3D-QSAR model, including internal and external validation showed comparative molecular field analysis (CoMFA) against 5HT2A (q2 = 0.552, R2 = 0.889, and r2 poured. = 0.653 and number of component 5) and comparative molecular similarity indices analysis (CoMSIA) (q2 = 0.599, R2 = 0.893, and r2 pred. = 0.617), for D2 (CoMFA, q2 = 0.577, R2 = 0.863, and r2 pred. = 0.598) (CoMSIA, q2 = 0.532, R2 = 0.82) all results exhibited better productivity and significant statistical reliability of the model. The docking study was carried out on the crystal structure of 5-HT2A having PDB ID; 6A93 and D2 receptor having PDB ID; 6CM4. The screened compound ZINC74289318 possess a higher docking score − 10.744 and − 11.388 than co-crystallized ligand docking score − 8.840 and − 10.06 against 5-HT2A and D2 receptor respectively. Further, ZINC74289318 was screened for all drug-likeness parameters and no showed violation of the Lipinski rule of five. Also, it was found to possess good bioavailability of 0.55 with synthetic accessibility of 4.42 which is greater than risperidone. [ABSTRACT FROM AUTHOR]

The upregulation of phosphoinositol-3-kinase γ (PI3Kγ) is deemed to be positively correlated with tumor-associated-macrophage (TAM)-mediated gastric carcinoma (GC). PI3Kγ suppresses tumor necrosis factor-alpha (TNF-α) and interleukin-12 (IL-12) through activation of the AKT/mTOR pathway, which promotes the immunosuppressant phenotype of TAM. Unlike α and β isoforms, δ and γ isoforms are primarily distributed in leucocytes and macrophages. Dual inhibitors against PI3Kδ and PI3Kγ have been proven to have merits in targeting solid tumors. Furthermore, it has been found that PI3Kδ is activated by cytokines, while PI3Kγ is activated by G-protein-coupled receptors (GPCRs). This facilitates determining the functional difference between these two isoforms. For this goal, selective inhibitors would be immensely helpful. In the current manuscript, we conducted various molecular modeling studies with a series of isoindolin-1-one derivatives as potent PI3Kγ inhibitors by combining molecular docking, molecular dynamics (MD), molecular mechanics, Poisson–Boltzmann/generalized Born surface area (MM-PB/GBSA) binding free energy calculation, and three-dimensional structure–activity relationship (3D-QSAR) study. To evaluate the selectivity of γ isoform over δ, the molecular modeling studies of idelalisib analogs reported as PI3Kδ inhibitors were also investigated. The contour polyhedrons were generated from the comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) around the ligand-bound active site for both isoforms, which could emphasize plausible explanations for the physicochemical factors that affect selective ligand recognition. The binding modalities of the two isoforms using CoMFA and MD models were compared, which suggested some key differences in the molecular interactions with the ligands and could be summarized as three subsites (one affinity subsite near the C-helix and DFG and two hydrophobic subsites). In the context of the structure–activity relationship (SAR), several new compounds were designed using a fragment-substitution strategy with the aim of selectively targeting PI3Kγ. The pIC50 values of the designed compounds were predicted by the 3D-QSAR models, followed by the MM-PB/GBSA binding energy estimation. The overall findings suggest that the designed compounds have the potential to be used as PI3Kγ inhibitors with a higher binding affinity and selectivity. [ABSTRACT FROM AUTHOR]

PGAM1 is overexpressed in a wide range of cancers, thereby promoting cancer cell proliferation and tumor growth, so it is gradually becoming an attractive target. Recently, a series of inhibitors with various structures targeting PGAM1 have been reported, particularly anthraquinone derivatives. In present study, the structure–activity relationships and binding mode of a series of anthraquinone derivatives were probed using three-dimensional quantitative structure–activity relationships (3D-QSAR), molecular docking, and molecular dynamics (MD) simulations. Comparative molecular field analysis (CoMFA, r2 = 0.97, q2 = 0.81) and comparative molecular similarity indices analysis (CoMSIA, r2 = 0.96, q2 = 0.82) techniques were performed to produce 3D-QSAR models, which demonstrated satisfactory results, especially for the good predictive abilities. In addition, molecular dynamics (MD) simulations technology was employed to understand the key residues and the dominated interaction between PGAM1 and inhibitors. The decomposition of binding free energy indicated that the residues of F22, K100, V112, W115, and R116 play a vital role during the ligand binding process. The hydrogen bond analysis showed that R90, W115, and R116 form stable hydrogen bonds with PGAM1 inhibitors. Based on the above results, 7 anthraquinone compounds were designed and exhibited the expected predictive activity. The study explored the structure–activity relationships of anthraquinone compounds through 3D-QSAR and molecular dynamics simulations and provided theoretical guidance for the rational design of new anthraquinone derivatives as PGAM1 inhibitors. [ABSTRACT FROM AUTHOR]

Background: Src homology 2 (SH2)-containing protein tyrosine phosphatase 2 (SHP2) as a major phosphatase would affect the development of tumors by regulating several cellular processes, and is a significant potential target for cancer treatment. Methods: In the present work, a series of pyridine derivatives possessing a wide range of inhibitory activity was employed to investigate the structural requirements by developing three dimensional quantitative structure–activity relationship (3D-QSAR) models using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. The results show that CoMFA (R2cv = 0.646, R2pred = 0.5587) and CoMSIA (R2cv = 0.777, R2pred = 0.7131) have excellent stability and predictability. The relationship between the inhibitory activity and structure of the inhibitors was analyzed by the derived contour maps. Furthermore, the QSAR models were validated by molecular docking and molecular dynamics simulations, which were also applied to reveal the potential molecular mechanism of these inhibitors. Findings: It was found that Arg110, Asn216, Thr218, Thr252 and Pro490 play a crucial role in stabilizing the inhibitors. Additionally, MM/PBSA calculations provided the binding free energy were also conducted to explain the discrepancy of binding activities. Overall, the outcomes of this work could provide useful information and theoretical guidance for the development of novel and potent SHP2 inhibitors.

PGAM1 is overexpressed in a wide range of cancers, thereby promoting cancer cell proliferation and tumor growth, so it is gradually becoming an attractive target. Recently, a series of inhibitors with various structures targeting PGAM1 have been reported, particularly anthraquinone derivatives. In present study, the structure–activity relationships and binding mode of a series of anthraquinone derivatives were probed using three-dimensional quantitative structure–activity relationships (3D-QSAR), molecular docking, and molecular dynamics (MD) simulations. Comparative molecular field analysis (CoMFA, r2 = 0.97, q2 = 0.81) and comparative molecular similarity indices analysis (CoMSIA, r2 = 0.96, q2 = 0.82) techniques were performed to produce 3D-QSAR models, which demonstrated satisfactory results, especially for the good predictive abilities. In addition, molecular dynamics (MD) simulations technology was employed to understand the key residues and the dominated interaction between PGAM1 and inhibitors. The decomposition of binding free energy indicated that the residues of F22, K100, V112, W115, and R116 play a vital role during the ligand binding process. The hydrogen bond analysis showed that R90, W115, and R116 form stable hydrogen bonds with PGAM1 inhibitors. Based on the above results, 7 anthraquinone compounds were designed and exhibited the expected predictive activity. The study explored the structure–activity relationships of anthraquinone compounds through 3D-QSAR and molecular dynamics simulations and provided theoretical guidance for the rational design of new anthraquinone derivatives as PGAM1 inhibitors.

Triple-negative breast cancer (TNBC) is defined as a kind of breast cancer that lacks estrogen receptors (ER), progesterone receptors (PR), and human epidermal growth factor receptors (HER2). This cancer accounts for 10–15% of all breast cancers and has the features of high invasiveness and metastatic potential. The treatment regimens are still lacking and need to develop novel inhibitors for therapeutic strategies. Three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses, based on a series of forty-seven thieno-pyrimidine derivatives, were performed to identify the key structural features for the inhibitory biological activities. The established comparative molecular field analysis (CoMFA) presented a leave-one-out cross-validated correlation coefficient q2 of 0.818 and a determination coefficient r2 of 0.917. In comparative molecular similarity indices analysis (CoMSIA), a q2 of 0.801 and an r2 of 0.897 were exhibited. The predictive capability of these models was confirmed by using external validation and was further validated by the progressive scrambling stability test. From these results of validation, the models were determined to be statistically reliable and robust. This study could provide valuable information for further optimization and design of novel inhibitors against metastatic breast cancer.

Rho-associated kinase-1 (ROCK1) has been recognized for its pivotal role in heart diseases, different types of malignancy, and many neurological disorders. Hyperactivity ofROCKphosphorylates the protein kinase-C (PKC), which ultimately induces smooth muscle cell contraction in the vascular system. Inhibition of ROCK1 has been shown to be a promising therapy for patients with cardiovascular disease. In this study, we have conducted molecular modeling techniques such as docking, molecular dynamics (MD), and 3-Dimensional structure-activity relationship (3D-QSAR) on a series of Nethyl- 4-(pyridin-4-yl)benzamide-based compounds. Docking and MD showed critical interactions and binding affinities between ROCK1 and its inhibitors. To establish the structure-activity relationship (SAR) of the compounds, 3D-QSAR techniques such as Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were used. The CoMFA (q² =0.774, r² =0.965, ONC = 6, and r²pred = 0.703) and CoMSIA (q² = 0.676, r² = 0.949, ONC = 6, and r²pred = 0.548) both models have shown reasonable external predictive activity, and contour maps revealed favorable and unfavorable substitutions for chemical group modifications. Based on the contour maps, we have designed forty new compounds, among which, seven compounds exhibited higher predictive activity (pIC50). Further, we conducted the MD study, ADME/Tox, and SA score prediction using the seven newly designed compounds. The combination of docking, MD, and 3D-QSAR studies helps to understand the coherence modification of existing molecules. Our study may provide valuable insight into the development of more potent ROCK1 inhibitors. [ABSTRACT FROM AUTHOR]

Focal adhesion kinase (FAK) is a promising target for developing more effective anticancer drugs. To better understand the structure-activity relationships and mechanism of actions of FAK inhibitors, a molecular modeling study using 3D-QSAR, molecular docking, molecular dynamics simulations, and binding free energy analysis were conducted. Two types of satisfactory 3D-QSAR models were generated, comprising the CoMFA model (R2cv = 0.528, R2pred = 0.7557) and CoMSIA model (R2cv = 0.757, R2pred = 0.8362), for predicting the inhibitory activities of novel inhibitors. The derived contour maps indicate structural characteristics for substituents on the template. Molecular docking, molecular dynamic simulations and binding free energy calculations further reveal that the binding of inhibitors to FAK is mainly contributed from hydrophobic, electrostatic and hydrogen bonding interactions. In addition, some key residues (Arg14, Glu88, Cys90, Arg138, Asn139, Leu141, and Leu155) responsible for ligand-receptor binding are highlighted. All structural information obtained from 3D-QSAR models and molecular dynamics is consist with the available experimental activities. All the results will facilitate the optimization of this series of FAK inhibitors with higher inhibitory activities.

Abstract Background An alarming requirement for finding newer antidiabetic glitazones as agonists to PPARγ are on its utmost need from past few years as the side effects associated with the available drug therapy is dreadful. In this context, herein, we have made an attempt to develop some novel glitazones as PPARγ agonists, by rational and computer aided drug design approach by implementing the principles of bioisosterism. The designed glitazones are scored for similarity with the developed 3D pharmacophore model and subjected for docking studies against PPARγ proteins. Synthesized by adopting appropriate synthetic methodology and evaluated for in vitro cytotoxicity and glucose uptake assay. Illustrations about the molecular design of glitazones, synthesis, analysis, glucose uptake activity and SAR via 3D QSAR studies are reported. Results The computationally designed and synthesized ligands such as 2-(4-((substituted phenylimino)methyl)phenoxy)acetic acid derivatives were analysed by IR, 1H-NMR, 13C-NMR and MS-spectral techniques. The synthesized compounds were evaluated for their in vitro cytotoxicity and glucose uptake assay on 3T3-L1 and L6 cells. Further the activity data was used to develop 3D QSAR model to establish structure activity relationships for glucose uptake activity via CoMSIA studies. Conclusion The results of pharmacophore, molecular docking study and in vitro evaluation of synthesized compounds were found to be in good correlation. Specifically, CPD03, 07, 08, 18, 19, 21 and 24 are the candidate glitazones exhibited significant glucose uptake activity. 3D-QSAR model revealed the scope for possible further modifications as part of optimisation to find potent anti-diabetic agents.

Rising mortality due to cancer has led to the development and identification of newer targets and molecules to cure the disease. Telomerase is one of the attractive targets for design of many chemotherapeutic drugs. This research highlights the designing of novel telomerase inhibitors using ligand-based (3D-QSAR) and structure-based (molecular docking and molecular dynamics simulation) approaches. For the development of the 3D-QSAR model, 37 synthetic molecules reported earlier as telomerase inhibitors were selected from diversified literature. Three different alignment methods were explored; among them, distill alignment was found to be the best method with good statistical results and was used for the generation of QSAR model. Statistically significant CoMSIA model with a correlation coefficient (r2ncv) value of 0.974, leave one out (q2) value of 0.662 and predicted correlation coefficient (r2pred) value of 0.560 was used for the analysis of QSAR. For the MDS study, A-chain of telomerase was stabilised for 50 ns with respect to 1-atm pressure, with an average temperature of 299.98 k and with potential energy of 1,145,336 kJ/m converged in 997 steps. Furthermore, the behaviour study of variants towards the target revealed that active variable gave better affinity without affecting amino acid sequences and dimensions of protein which was accomplished through RMSD, RMSF and Rg analysis. Results of molecular docking study supported the outcomes of QSAR contour maps as ligand showed similar interactions with surrounded amino acids which were identified in contour map analysis. The results of the comprehensive study might be proved valuable for the development of potent telomerase inhibitors. [ABSTRACT FROM AUTHOR]

Tuberculosis and fungal infections can pose serious threats to human health. In order to find novel antimicrobial agents, 26 novel quinoxaline-1,4-di-N-oxides containing a thiazolidinone moiety were designed and synthesized, and their antimycobacterial activities were evaluated. Among them, compounds 2t, 2u, 2y, and 2z displayed the most potent antimycobacterial activity against Mycobacterium tuberculosis strain H37Rv (minimal inhibitory concentration [MIC] = 1.56 μg/mL). The antifungal activity of all the compounds was also evaluated against Candida albicans, Candida tropicalis, Aspergillus fumigatus, and Cryptococcus neoformans. Compounds 2t, 2u, 2y, and 2z exhibited potential antifungal activities, with an MIC between 2 and 4 μg/mL. Comparative molecular field analysis (CoMFA: q2 = 0.914, r2 = 0.967) and comparative molecular similarity index analysis (CoMSIA: q2 = 0.918, r2 = 0.968) models were established to investigate the structure and antimycobacterial activity relationship. The results of contour maps revealed that electronegative and sterically bulky substituents play an important role in the antimycobacterial activity. Electronegative and sterically bulky substituents are preferred at the C7 position of the quinoxaline ring and the C4 position of the phenyl group to increase the antimycobacterial activity. Additionally, more hydrogen bond donor substituents should be considered at the C2 side chain of the quinoxaline ring to improve the activity.

Janus kinase 3 (JAK3) plays a critical role in the JAK/STAT signaling pathway and has become an attractive selective target for the treatment of immune-mediated disorders. Therefore, great efforts have been made for the development of JAK3 inhibitors, but developing selective JAK3 inhibitors remains a great challenge because of the high sequence homology with other kinases. In order to reveal the selective-binding mechanisms of JAK3 and to find the key structural features that refer to specific JAK3 inhibition, a systematic computational method, including 3D-QSAR, molecular dynamics simulation, and free energy calculations, was carried out on a series of JAK3 isoform-selective inhibitors. Necessary pharmacodynamic structures and key residues involved in efficient JAK3-inhibition were then highlighted. Finally, 10 novel JAK3 inhibitors were designed, the satisfactory predicted binding affinity to JAK3 of these analogous demonstrated that this study may facilitate the rational design of novel and selective JAK3 inhibitors.

Radiotherapy and chemotherapy are conventional cancer treatments. Around 60% of all patients who are diagnosed with cancer receive radio- or chemotherapy in combination with surgery during their disease. Only a few patients respond to the blockage of immune checkpoints alone, or in combination therapy, because their tumours might not be immunogenic. Under these circumstances, an increasing level of extracellular adenosine via the activation of ecto-5’-nucleotidase (CD73) and consequent adenosine receptor signalling is a typical mechanism that tumours use to evade immune surveillance. CD73 is responsible for the conversion of adenosine monophosphate to adenosine. CD73 is overexpressed in various tumour types. Hence, targetting CD73’s signalling is important for the reversal of adenosine-facilitated immune suppression. In this study, we selected a potent series of the non-nucleotide small molecule inhibitors of CD73. Molecular docking studies were performed in order to examine the binding mode of the inhibitors inside the active site of CD73 and 3D-QSAR was used to study the structure–activity relationship. The obtained CoMFA (q2 = 0.844, ONC = 5, r2 = 0.947) and CoMSIA (q2 = 0.804, ONC = 4, r2 = 0.954) models showed reasonable statistical values. The 3D-QSAR contour map analysis revealed useful structural characteristics that were needed to modify non-nucleotide small molecule inhibitors. We used the structural information from the overall docking and 3D-QSAR results to design new, potent CD73 non-nucleotide inhibitors. The newly designed CD73 inhibitors exhibited higher activity (predicted pIC50) than the most active compound of all of the derivatives that were selected for this study. Further experimental studies are needed in order to validate the new CD73 inhibitors.

Abstract The study on antitumor activities of artemisinin and its derivatives has been closely focused on in recent years. Herein, 2D and 3D QSAR analysis was performed on the basis of a series of artemisinin derivatives with known bioactivities against the non-small-cell lung adenocarcinoma A549 cells. Four QSAR models were successfully established by CoMSIA, CoMFA, topomer CoMFA and HQSAR approaches with respective characteristic values q2 = 0.567, R2 = 0.968, ONC = 5; q2 = 0.547, R2 = 0.980, ONC = 7; q2 = 0.559, R2 = 0.921, ONC = 7 and q2 = 0.527, R2 = 0.921, ONC = 6. The predictive ability of CoMSIA with r2 = 0.991 is the best one compared with the other three approaches, such as CoMFA (r2 = 0.787), topomer CoMFA (r2 = 0.819) and HQSAR (r2 = 0.743). The final QSAR models can provide guidance in structural modification of artemisinin derivatives to improve their anticancer activities.

A new series of twenty-two C-5 substituted N-arylsulfonylindoles was prepared with the aim of exploring the influence of C-5 substitution on 5-HT6 receptor affinity. Eleven compounds showed moderate to high affinity at the receptor (Ki = 58–403 nM), with compound 4d being identified as the most potent ligand. However, regarding C-5 substitution, both methoxy and fluorine were detrimental for receptor affinity compared to our previously published unsubstituted compounds. In order to shed light on these observations, we performed docking and molecular dynamics simulations with the most potent compounds of each series (4d and 4l) and PUC-10, a highly active ligand previously reported by our group. The comparison brings about deeper insight about the influence of the C-5 substitution on the binding mode of the ligands, suggesting that these replacements are detrimental to the affinity due to precluding a ligand from reaching deeper inside the binding site. Additionally, CoMFA/CoMSIA studies were performed to systematize the information of the main structural and physicochemical characteristics of the ligands, which are responsible for their biological activity. The CoMFA and CoMSIA models presented high values of q2 (0.653; 0.692) and r2 (0.879; 0.970), respectively. Although the biological activity of the ligands can be explained in terms of the steric and electronic properties, it depends mainly on the electronic nature.

The 5-hydroxytryptamine (5-HT1A) receptors represent an attractive target in drug discovery. In particular, 5-HT1A agonists and partial agonists are deeply investigated for their potential role in the treatment of anxiety, depression, ischaemic brain disorder and more recently, of pain. On the other hand, 5-HT1A antagonists have been revealed promising compounds in cognition disorders and, lately, in cancer. Thus, the discovery of 5HT1A ligands is nowadays an appealing research activity in medicinal chemistry. In this work, Comparative Molecular Fields Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA) were applied on an in-house library of 5-HT1A ligands bearing different chemical scaffolds in order to elucidate their affinity and selectivity for the target. Following this procedure, a number of structural modifications have been drawn for the development of much more effective 5-HT1AR ligands.

Respiratory syncytial virus (RSV) has been identified as a main cause of hospitalisation in infants and children. To date, the current therapeutic arsenal is limited to ribavirin and palivizumab with variable efficacy. In this work, starting from a number of in-house series of previously described anti-RSV agents based on the benzimidazole scaffold, with the aim at gaining a better understanding of the related chemical features involved in potency and safety profiles, we applied a computational study including two focussed comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The results allowed us to derive useful suggestions for the design of derivatives and also to set up statistical models predicting the potency and selectivity index (SI = CC50/EC50) of any new analogue prior to synthesis. Accordingly, here, we discuss preliminary results obtained through the applied exhaustive QSAR analyses, leading to design and synthesise more effective anti-RSV agents.

Oxytocin plays a vital role in the occurrence of preterm birth by interacting with oxytocin receptor (OTR), and thus OTR antagonists provide effective approaches for the treatment of early birth. Presently, for purpose of exploring the structural traits affecting the antagonism potency, the up-to-date largest set of 121 2,5-diketopiperazine derivatives as OTR antagonists was subjected to ligand-based three-dimensional quantitative structure–activity (3D-QSAR) analysis applying comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. The resultant optimal CoMSIA model displays proper validity and predictability with cross-validated correlation coefficient Q2 = 0.614, non-cross-validated correlation coefficient R2 ncv = 0.969 and predicted correlation coefficient R2 pre = 0.912 for the test set of compounds, respectively. In addition, docking study was carried out for further elucidating the binding modes of OTR antagonists. The final docking cavity was located among the TM2-TM7 helices of the target protein and proved to be the same as described by other scholars' researches of other type of OTR antagonists. The major amino acids forming the cavity are Q92, Q96, K116, Q119, V120, M123, G196, I201, Q295, W288, F311 and M315. Representative compound 118 forms two H-bonds with Q119 and two H-bonds with Q295, with also a π - π stacking effect with F311, respectively. Meanwhile, as a supplementary tool to study the antagonists' conformation in the binding cavity, molecular dynamics (MD) simulation was also performed to further elucidate the changes in the ligand-receptor complex. We hope that the obtained models and information may help to provide an insight into the interaction mechanism of OTR antagonists and facilitate the design and optimization of novel antagonists for preventing premature birth. Image 1 • Oxytocin receptor antagonists are effective for preventing preterm labour. • Structural traits affecting antagonism potency were explored. • Crucial amino acids for antagonists binding of OTR were discovered. • Binding conformation of 2,5-diketopiperazine derivatives were analyzed. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • We designed and synthesized 26 compounds containing a Michael acceptor. • The structural conditions required to obtain stronger cytotoxicity against cancer cells were derived based on the relationships between the cell growth inhibitory concentration of the compounds and their physicochemical properties. • The title compound triggered apoptosis through ROS generation, which then led to stimulation of the caspase pathway. Abstract A moderate elevation in reactive oxygen species (ROS) levels can generally be controlled in normal cells, but may lead to death of cancer cells as the ROS level in cancer cells is already elevated. Therefore, a ROS-generating compound can act as a selective chemotherapeutic agent for cancer cells that does not affect normal cells. In our previous study, a compound containing a Michael acceptor was selectively cytotoxic to cancer cells without affecting normal cells; therefore, we designed and synthesized 26 compounds containing a Michael acceptor. Their cytotoxicities against HCT116 human colon cancer cell lines were measured by using a clonogenic long-term survival assay. To derive the structural conditions required to obtain stronger cytotoxicity against cancer cells, the relationships between the half-maximal cell growth inhibitory concentration values of the synthesized compounds and their physicochemical properties were evaluated by Comparative Molecular Field Analysis and Comparative Molecular Similarity Indices Analysis. It was confirmed that the compound with the best half-maximal cell growth inhibitory concentration triggered apoptosis through ROS generation, which then led to stimulation of the caspase pathway. [ABSTRACT FROM AUTHOR]

Gastrointestinal stromal tumors (GISTs) are the most common Mesenchymal Neoplasm of the gastrointestinal tract. The tumorigenesis of GISTs has been associated with the gain-of-function mutation and abnormal activation of the stem cell factor receptor (c-KIT) and platelet-derived growth factor receptor alpha (PDGFRα) kinases. Hence, inhibitors that target c-KIT and PDGFRα could be a therapeutic option for the treatment of GISTs. The available approved c-KIT/PDGFRα inhibitors possessed low efficacy with off-target effects, which necessitated the development of potent inhibitors. We performed computational studies of 48 pyrazolopyridine derivatives that showed inhibitory activity against c-KIT and PDGFRα to study the structural properties important for inhibition of both the kinases. The derivative of phenylurea, which has high activities for both c-KIT (pIC50 = 8.6) and PDGFRα (pIC50 = 8.1), was used as the representative compound for the dataset. Molecular docking and molecular dynamics simulation (100 ns) of compound 14 was performed. Compound 14 showed the formation of hydrogen bonding with Cys673, Glu640, and Asp810 in c-KIT, and Cys677, Glu644, and Asp836 in PDGFRα. The results also suggested that Thr670/T674 substitution in c-KIT/PDGFRα induced conformational changes at the binding site of the receptors. Three-dimensional quantitative structure–activity relationship (3D-QSAR) models were developed based on the inhibitors. Contour map analysis showed that electropositive and bulky substituents at the para-position and the meta-position of the benzyl ring of compound 14 was favorable and may increase the inhibitory activity against both c-KIT and PDGFRα. Analysis of the results suggested that having bulky and hydrophobic substituents that extend into the hydrophobic pocket of the binding site increases the activity for both c-KIT and PDGFRα. Based on the contour map analysis, 50 compounds were designed, and the activities were predicted. An evaluation of binding free energy showed that eight of the designed compounds have potential binding affinity with c-KIT/PDGFRα. Absorption, distribution, metabolism, excretion and toxicity (ADMET) and synthetic feasibility tests showed that the designed compounds have reasonable pharmaceutical properties and synthetic feasibility. Further experimental study of the designed compounds is recommended. The structural information from this study could provide useful insight into the future development of c-KIT and PDGFRα inhibitors.

Presently, 151 widely-diverse pyridinylimidazole-based compounds that show inhibitory activities at the TNF-α release were investigated. By using the distance comparison technique (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) methods, the pharmacophore models and the three-dimensional quantitative structure-activity relationships (3D-QSAR) of the compounds were explored. The proposed pharmacophore model, including two hydrophobic sites, two aromatic centers, two H-bond donor atoms, two H-bond acceptor atoms, and two H-bond donor sites characterizes the necessary structural features of TNF-α release inhibitors. Both the resultant CoMFA and CoMSIA models exhibited satisfactory predictability (with Q2 (cross-validated correlation coefficient) = 0.557, R2ncv (non-cross-validated correlation coefficient) = 0.740, R2pre (predicted correlation coefficient) = 0.749 and Q2 = 0.598, R2ncv = 0.767, R2pre = 0.860, respectively). Good consistency was observed between the 3D-QSAR models and the pharmacophore model that the hydrophobic interaction and hydrogen bonds play crucial roles in the mechanism of actions. The corresponding contour maps generated by these models provide more diverse information about the key intermolecular interactions of inhibitors with the surrounding environment. All these models have extended the understanding of imidazole-based compounds in the structure-activity relationship, and are useful for rational design and screening of novel 2-thioimidazole-based TNF-α release inhibitors.

Aromatase inhibitors are the most important targets in treatment of estrogen-dependent cancers. In order to search for potent steroidal aromatase inhibitors (SAIs) with lower side effects and overcome cellular resistance, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of SAIs to build 3D QSAR models. The reliable and predictive CoMFA and CoMSIA models were obtained with statistical results (CoMFA: q2 = 0.636, r2ncv = 0.988, r2pred = 0.658; CoMSIA: q2 = 0.843, r2ncv = 0.989, r2pred = 0.601). This 3D QSAR approach provides significant insights that can be used to develop novel and potent SAIs. In addition, Genetic algorithm with linear assignment of hypermolecular alignment of database (GALAHAD) was used to derive 3D pharmacophore models. The selected pharmacophore model contains two acceptor atoms and four hydrophobic centers, which was used as a 3D query for virtual screening against NCI2000 database. Six hit compounds were obtained and their biological activities were further predicted by the CoMFA and CoMSIA models, which are expected to design potent and novel SAIs.

The bromodomain containing protein 4 (BRD4) recognizes acetylated histone proteins and plays numerous roles in the progression of a wide range of cancers, due to which it is under intense investigation as a novel anti-cancer drug target. In the present study, we performed three-dimensional quantitative structure activity relationship (3D-QSAR) molecular modeling on a series of 60 inhibitors of BRD4 protein using ligand- and structure-based alignment and different partial charges assignment methods by employing comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches. The developed models were validated using various statistical methods, including non-cross validated correlation coefficient (r2), leave-one-out (LOO) cross validated correlation coefficient (q2), bootstrapping, and Fisher’s randomization test. The highly reliable and predictive CoMFA (q2 = 0.569, r2 = 0.979) and CoMSIA (q2 = 0.500, r2 = 0.982) models were obtained from a structure-based 3D-QSAR approach using Merck molecular force field (MMFF94). The best models demonstrate that electrostatic and steric fields play an important role in the biological activities of these compounds. Hence, based on the contour maps information, new compounds were designed, and their binding modes were elucidated in BRD4 protein’s active site. Further, the activities and physicochemical properties of the designed molecules were also predicted using the best 3D-QSAR models. We believe that predicted models will help us to understand the structural requirements of BRD4 protein inhibitors that belong to quinolinone and quinazolinone classes for the designing of better active compounds. [ABSTRACT FROM AUTHOR]

Type 2 diabetes is becoming a global pandemic disease. As an important target for the generation and development of diabetes mellitus, peroxisome proliferator-activated receptor γ (PPARγ) has been widely studied. PPARγ agonists have been designed as potential anti-diabetic agents. The advanced development of PPARγ agonists represents a valuable research tool for diabetes therapy. To explore the structural requirements of PPARγ agonists, three-dimensional quantitative structure–activity relationship (3D-QSAR) and molecular docking studies were performed on a series of N-benzylbenzamide derivatives employing comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and surflex-dock techniques. The generated models of CoMFA and CoMSIA exhibited a high cross-validation coefficient (q2) of 0.75 and 0.551, and a non-cross-validation coefficient (r2) of 0.958 and 0.912, respectively. The predictive ability of the models was validated using external validation with predictive factor (r2pred) of 0.722 and 0.682, respectively. These results indicate that the model has high statistical reliability and good predictive power. The probable binding modes of the best active compounds with PPARγ active site were analyzed, and the residues His323, Tyr473, Ser289 and Ser342 were found to have hydrogen bond interactions. Based on the analysis of molecular docking results, and the 3D contour maps generated from CoMFA and CoMSIA models, the key structural features of PPARγ agonists responsible for biological activity could be determined, and several new molecules, with potentially higher predicted activity, were designed thereafter. This work may provide valuable information in further optimization of N-benzylbenzamide derivatives as PPARγ agonists. [ABSTRACT FROM AUTHOR]

Mechanistic target of rapamycin is involved in the formation of tumor microvasculature was an ideal target for computer-aided drug design. The predictive study of quantitative structure-activity relationship and molecular docking can shorten the cycle and reduce the cost of designing the higher activity mTOR inhibitors. In this article, comparative molecular field analysis and comparative molecular similarity indices analysis fields were used to analyse three-dimensional quantitative structure-activity relationship model. The model (comparative molecular similarity indices analysis with q2=0.607, r2=0.909; comparative molecular similarity indices analysis with q2=0.703, r2=0.935) has a good predictability. Three-dimensional quantitative structure-activity relationship model contour maps indicate the electrostatic, hydrophobic and hydrogen bond donor fields have crucial effects to derivatives biological activity. Molecular docking was employed to explore the conformations of 55 compounds with key amino acid residues. Finally, combining contour maps with molecular docking results, ten derivatives as potential mechanistic target of rapamycin inhibitors were designed to further verify established three-dimensional quantitative structure-activity relationship models. These data provide significant theoretical foundation for designing better activity mechanistic target of rapamycin inhibitors. [ABSTRACT FROM AUTHOR]

In the present study, we have employed the ligand-based drug design technique, 3D-QSAR, through a comparative molecular field analysis (CoMFA) and a comparative molecular similarity indices analysis (CoMSIA) to determine the key factors for the plant growth promoting activity of brassinosteroids reported in literature, using the bean second-internode bioassay measured on two groups of compounds with different molar concentrations. This is the first 3D-QSAR study using the second internode elongation as biological activity. These results provide useful ideas for the design of new molecules, which could be explored in the future to identify novel vegetable growth promoters with similar or greater biological activity than natural brassinosteroids. The reliability of this study was supported by the robust statistical parameters obtained from CoMFA (Model A, r²pred = 0.751; Model B, r²pred = 0.770) and CoMSIA (Model A, r²pred = 0.946; Model B, r²pred = 0.923) analysis. [ABSTRACT FROM AUTHOR]

A collection of 36 thiosemicarbazone analogues possessed a broad span of tyrosinase inhibitory activities was designed and obtained. Robust and reliable CoMFA and CoMSIA models were gained to predict the structure–activity relationship and the new modifier direction. Inhibitory activities of the compounds were found to greatly depend upon molecular shape, size, and charge. The sterically bulky group at the C-4 position of the thiophene ring contributed a high capacity for biological activity. Some bulky substituents at the C1-position and C12-position, and electron-negative groups at the C3-position, helped to improve the activity of these analogues. The molecular docking results provided visual evidence for QSAR analysis and detailed information about binding mode, affinity, and the principal mechanism between the ligands and tyrosinase. Based on these, a prospective structure modification and optimization of the most potent compound, T32 , was suggested for further research. [ABSTRACT FROM AUTHOR]

The study on antitumor activities of artemisinin and its derivatives has been closely focused on in recent years. Herein, 2D and 3D QSAR analysis was performed on the basis of a series of artemisinin derivatives with known bioactivities against the non-small-cell lung adenocarcinoma A549 cells. Four QSAR models were successfully established by CoMSIA, CoMFA, topomer CoMFA and HQSAR approaches with respective characteristic values q = 0.567, R = 0.968, ONC = 5; q = 0.547, R = 0.980, ONC = 7; q = 0.559, R = 0.921, ONC = 7 and q = 0.527, R = 0.921, ONC = 6. The predictive ability of CoMSIA with r = 0.991 is the best one compared with the other three approaches, such as CoMFA (r = 0.787), topomer CoMFA (r = 0.819) and HQSAR (r = 0.743). The final QSAR models can provide guidance in structural modification of artemisinin derivatives to improve their anticancer activities. [ABSTRACT FROM AUTHOR]

Protein kinase B (PKB/Akt) regulates all aspects of cell growth, differentiation, and division. PKB/Akt has recently garnered a great deal of attention as a promising molecular target for cancer therapy due to its involvement in the development of several human cancers. In this study a diverse set of 56 Akt1 inhibitors were aligned by three different methods (pharmacophore-, docking-based and rigid body alignment) for CoMFA, CoMSIA and HQSAR analysis. The best QSAR models were obtained using rigid body alignment (Distill). CoMFA and CoMSIA models were found statistically significant with leave-one-out correlation coefficient (q2) of 0.627 and 0.598, respectively, cross validated coefficient (rcv2) of 0.644 and 0.563, respectively, and conventional coefficient (r2) of 0.867 and 0.865, respectively. QSAR models were validated by a test set of 9 compounds giving satisfactory predicted correlation coefficient (rpred2) of 0.603 and 0.613 for CoMFA and CoMSIA models, respectively. Leave-one-out correlation value (q2) of 0.687, rpred2 of 0.742 and r2 of 0.868 were obtained for HQSAR analysis and found satisfactory. This study provides valuable clues to design new compounds against PKB/Akt.

Caspase-3 has become an attractive target in the treatment of many diseases such as Alzheimer, Parkinson’s, myocardial infarction and cancer. In the present study, molecular three-dimensional quantitative structure activity relationship (3D-QSAR) and docking studies were performed on a series of caspase-3 activators. Comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and step-wise k-nearest neighboring molecular field analysis [(SW) kNN MFA] were performed to gain insight into the key structural factors affecting the activity. The results of 3D-QSAR are reliable and significant having high predictive (q2) ability showing good correlation between predicted and observed activity. The lower value of standard error of estimation shows that most of the observed values cluster fairly close to the regression line. Molecular docking was performed with the GOLD docking program used to explore the binding mode between the ligands and the receptor.

Acetyl-CoA carboxylase (ACC) is a crucial metabolic enzyme, which plays a vital role in fatty acid metabolism and obesity induced type 2 diabetes. Herein, we have performed 3D-QSAR and molecular docking analysis on a novel series of (4-piperidinyl)-piperazines to design potent ACC inhibitors. This study correlates the ACC inhibitory activities of 68 (4-piperidinyl)-piperazine derivatives with several stereo-chemical parameters representing steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor fields. The CoMFA and CoMSIA models exhibited excellent rncv2 values of 0.974 and 0.985, and rcv2 values of 0.671 and 0.693, respectively. CoMFA predicted rpred2 of 0.910 and CoMSIA predicted rpred2 of 0.963 showed that the predicted values were in good agreement with experimental values. Glide5.5 program was used to explore the binding mode of inhibitors inside the active site of ACC. We have accordingly designed novel ACC inhibitors by utilising the LeapFrog and predicted with excellent inhibitory activity in the developed models.

HER-2 and EGFR are biological targets related to the development of cancer and the discovery and/or development of a dual inhibitor could be a good strategy to design an effective drug candidate. In this study, analyses of the chemical properties of a group of substances having affinity for both HER-2 and EGFR were carried out with the aim of understanding the main factors involved in the interaction between these inhibitors and the biological targets. Comparative analysis of molecular interaction fields (CoMFA) and comparative molecular similarity index analysis (CoMSIA) techniques were applied on 63 compounds. From CoMFA analyses, we found for both HER-2 (r2 calibration = 0.98 and q2cv = 0.83) and EGFR (r2 calibration = 0.98 and q2cv = 0.73) good predictive models. Good models for CoMSIA technique have also been found for HER-2 (r2 calibration = 0.92 and q2cv = 0.74) and EGFR (r2 calibration = 0.97 and q2cv = 0.72). The constructed models could indicate some important characteristics for the inhibition of the biological targets. New compounds were proposed as candidates to inhibit both proteins. Therefore, this study may guide future projects for the development of new drug candidates for the treatment of breast cancer.

To explore the relationship between the structures of substituted pyrrolidine derivatives and their inhibition of dipeptidyl peptidase IV inhibitors. The QSAR, including CoMFA, CoMSIA and HQSAR, were applied to identify the key structures impacting their inhibitory potencies. The CoMFA, CoMSIA and HQSAR with cross-validated correlation coefficient (q) value of 0.727, 0.870 and 0.939 and r value of 0.973, 0.981 and 0.949. Based on the structure-activity relationship revealed by the present study, we have designed a set of novel dipeptidyl peptidase IV inhibitors that showed excellent potencies in the developed models. Thus, our results allowed us to design new derivatives with desired activities. [ABSTRACT FROM AUTHOR]

Background: Bruton tyrosine kinase (Btk) plays an important role in B-cell development, differentiation, and signaling. It is also found be in involved in male immunodeficiency disease such as X-linked agammaglobulinemia (XLA). Btk is considered as a potential therapeutic target for treating autoimmune diseases and hematological malignancies. Results: In this work, a combined molecular modeling study was performed on a series of thieno [3,2-c] pyridine-4- amine derivatives as Btk inhibitors. Receptor-guided COMFA (q2 = 0.574, NOC= 3, r2 = 0.924) and COMSIA (q2 = 0.646, NOC = 6, r2 = 0.971) models were generated based on the docked conformation of the most active compound 26. All the developed models were tested for robustness using various validation techniques. Furthermore, a 5-ns molecular dynamics (MD) simulation and binding free energy calculations were carried out to determine the binding modes of the inhibitors and to identify crucial interacting residues. The rationality and stability of molecular docking and 3D-QSAR results were validated by MD simulation. The binding free energies calculated by the MM/PBSA method showed the importance of the van der Waals interaction. Conclusions: A good correlation between the MD results, docking studies, and the contour map analysis were observed. The study has identified the key amino acid residues in Btk binding pocket. The results from this study can provide some insights into the development of potent, novel Btk inhibitors. [ABSTRACT FROM AUTHOR]