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MMP-2 overexpression is strongly related to several diseases including cancer. However, none of the MMP-2 inhibitors have been marketed as drug candidates due to various adverse effects. Here, a set of sulphonyl pyrrolidines was subjected to validation of molecular modelling followed by binding mode analysis to explore the crucial structural features required for the discovery of promising MMP-2 inhibitors. This study revealed the importance of hydroxamate as a potential zinc-binding group compared to the esters. Importantly, hydrophobic and sterical substituents were found favourable at the terminal aryl moiety attached to the sulphonyl group. The binding interaction study revealed that the S1′ pocket of MMP-2 similar to 'a basketball passing through a hoop' allows the aryl moiety for proper fitting and interaction at the active site to execute potential MMP-2 inhibition. Again, the sulphonyl pyrrolidine moiety can be a good fragment necessary for MMP-2 inhibition. Moreover, some novel MMP-2 inhibitors were also reported. They showed the significance of the 3rd position substitution of the pyrrolidine ring to produce interaction inside S2′ pocket. The current study can assist in the design and development of potential MMP-2 inhibitors as effective drug candidates for the management of several diseases including cancers in the future. [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.

Computer-Aided Drug Design (CADD) approaches, such as those employing quantitative structure-activity relationship (QSAR) methods, are known for their ability to uncover novel data from large databases. These approaches can help alleviate the lack of biological and chemical data, but some predictions do not generate sufficient positive information to be useful for biological screenings. QSAR models are often employed to explain biological data of chemicals and to design new chemicals based on their predictions. In this review, we discuss the importance of data set size with a focus on false hits for QSAR approaches. We assess the challenges and reliability of an initial in silico strategy for the virtual screening of bioactive molecules. Lastly, we present a case study reporting a combination approach of hologram-based quantitative structure-activity relationship (HQSAR) models and random forest-based QSAR (RF-QSAR), based on the 3D structures of 25 synthetic SARS-CoV-2 Mpro inhibitors, to virtually screen new compounds for potential inhibitors of enzyme activity. In this study, optimal models were selected and employed to predict Mpro inhibitors from the database Brazilian Compound Library (BraCoLi). Twenty-four compounds were then assessed against SARS-CoV-2 Mpro at 10 µM. At the time of this study (March 2021), the availability of varied and different Mpro inhibitors that were reported definitely affected the reliability of our work. Since no hits were obtained, the data set size, parameters employed, external validations, as well as the applicability domain (AD) could be considered regarding false hits data contribution, aiming to enhance the design and discovery of new bioactive molecules.

In this work, three quantitative structure–activity relationship (QSAR) methods involving comparative molecular field analysis (CoMFA) and GRid-INdependent Descriptors (GRIND) based 3D-QSAR and hologram QSAR (HQSAR) were evaluated for predicting adsorption coefficients of the simple benzene derivatives on mutiwalled carbon nanotubes (MWCNTs). The contour maps of CoMFA suggested that the steric hindrance had a significant impact on the adsorption process of substituted benzenes. GRIND studies investigate the important mutual distances between molecular features, which confirmed the role of hydrophobic groups as well as their distances from different steric hot spots in the benzene ring of the molecules. According to HQSAR model and its fragment contribution map, the hydrogen bond donor and acceptor were also found to play an important role in governing adsorption of substituted benzenes on CNTs. The CoMFA, GRIND, and HQSAR methods employed to build predictive 2D- and 3D-QSAR models for adsorption of simple benzene derivatives on CNTs in aqueous media successfully. [ABSTRACT FROM AUTHOR]

Background: Our research highlights the synthesis of newer antimalarial compounds using molecular modeling studies., Objective: The study investigates a series of isocryptolepine derivatives from previous literature, focusing on their biological activities as antimalarial agents., Methods: Computational methods such as molecular docking and QSAR were employed to gain insights into the interaction between the synthesized compounds and the target enzyme PfDHFR-TS., Results: Molecular docking studies helped to identify key binding interactions, supporting the design of more effective compounds. Using CoMFA and CoMSIA, the study explored steric, electrostatic, and hydrogen-bonding fields, providing a quantitative structure-activity relationship (QSAR) for 49 compounds., Conclusion: The CoMFA model yielded strong predictive r² values of 0.971, while the CoMSIA model highlighted the significance of hydrophobic and hydrogen bond interactions. These findings inform the design of novel isocryptolepine derivatives with improved antimalarial activity., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

A series of mIDH1 inhibitors derived from 3-pyrimidine-4-oxazolidin-2-ketone derivatives were studied by QSAR model to explore the key factors that inhibit mIDH1 activity. The generated model was cross-verified and non-cross-verified by Topomer CoMFA and HQSAR methods; the independent test set was verified by PLS method; the Topomer search technology was used for virtual screening and molecular design; and the Surflex-Dock method and ADMET technology were used for molecular docking, pharmacology and toxicity prediction of the designed drug molecules. The Topomer CoMFA and HQSAR cross-validation coefficients q2 are 0.783 and 0.784, respectively, and the non-cross-validation coefficients r2 are 0.978 and 0.934, respectively. Ten new drug molecules have been designed using Topomer search technology. The results of molecular docking and ADMET show that the newly designed drug molecules are effective. The docking situation, pharmacology and toxicity prediction results are good. The model can be used to predict the bioactivity of the same type of new compounds and their derivatives. The prediction results of molecular design, molecular docking and ADMET can provide some ideas for the design and development of novel mIDH1 inhibitor anticancer drugs, and provide certain theoretical basis of the experimental verification of new compounds in the future. Newly designed molecules after docking with corresponding proteins in the PDB library, it can explore the targets of drug molecules acting with large proteins and the related force, which is very helpful for the design of new drugs and the mechanism of drug action. [ABSTRACT FROM AUTHOR]

Acute myeloid leukemia, a serious condition affecting stem cells, drives uncontrollable myeloblast proliferation, leading to accumulation. Extensive research seeks rapid, effective chemotherapeutics. A potential option is a BRD4 inhibitor, known for suppressing cell proliferation. Sulfonamide derivatives probed essential structural elements for potent BRD4 inhibitors. To achieve this goal, we employed 3D-QSAR molecular modeling techniques, including CoMFA, CoMSIA, and HQSAR models, along with molecular docking and molecular dynamics simulations. The validation of the 2D/3D QSAR models, both internally and externally, underscores their robustness and reliability. The contour plots derived from CoMFA, CoMSIA, and HQSAR analyses played a pivotal role in shaping the design of effective BRD4 inhibitors. Importantly, our findings highlight the advantageous impact of incorporating bulkier substituents on the pyridinone ring and hydrophobic/electrostatic substituents on the methoxy-substituted phenyl ring, enhancing interactions with the BRD4 target. The interaction mode of the new compounds with the BRD4 receptor (PDB ID: 4BJX) was investigated using molecular docking simulations, revealing favorable binding energies, supported by the formation of hydrogen and hydrophobic bonds with key protein residues. Moreover, these novel inhibitors exhibited good oral bioavailability and demonstrated non-toxic properties based on ADMET analysis. Furthermore, the newly designed compounds along with the most active one from series 58, underwent a molecular dynamics simulation to analyze their behavior. The simulation provided additional evidence to support the molecular docking results, confirming the sustained stability of the analyzed molecules over the trajectory. This outcome could serve as a valuable reference for designing and developing novel and effective BRD4 inhibitors.Communicated by Ramaswamy H. Sarma.

The docking and Quantitative structure-activity relationship (QSAR) studies of Pyrido [1, 2] a benzimidazoles nucleus were performed on a series of 40 analogues. The training set consisting of 32 molecules in Comparative Molecular Field (CoMFA), Comparative molecular similarity indices analysis (CoMSIA) and Hologram QSAR(HQSAR) models gives cross-validated r² (q²) and (S.E) standard error of 0.613, 0.980 and 0.021 and conventional on MMFF 94 q² 0.785 r² 0.942 and (S.E) standard error 0.033 respectively. The predicted r² values 0.882, 0.788 and 0.867 for Comparative Molecular Field Analysis (CoMFA) modeling, CoMSIA modeling and HQSAR modeling respectively, shows these generated models are appropriate for further designing. In addition to this work the docking studies were performed on Protein model of Plasmodium falciparum (PDB 2ANL) which further explore the binding affinity towards active site of protein receptor. The results guide us for the creation of more potent and effective compounds towards strain of Plasmodium falciparum relative to chloroquine. [ABSTRACT FROM AUTHOR]

The vascular endothelial growth factor (VEGF) is the main target of tumor treatment. VEGFR-2 is the main functional receptor of VEGF, which is involved in the regulation of angiogenesis. Based on hologram quantitative structure activity relationships (HQSAR) and topomer comparative molecular field analysis (topomer CoMFA), the contribution of 6-amide-2-aryl benzoxazole/benzimidazole derivatives (VEGFR-2 kinase inhibitors) to these structures was discussed and the corresponding modification strategies were proposed. The most effective HQSAR and topomer CoMFA models are generated by using a training set of 33 compounds. In order to ensure the robustness of the model, the randomization test was used, and 11 compounds were selected as the test set. The results show that the q2 of cross-validation is 0.646/0.659, and the r2 of non-cross-validation is 0.871/0.867, respectively. The data show that both models are reliable. Topomer CoMFA's steric/electrostatic contour and HQSAR's atomic contribution map show the structural characteristics controlling its inhibition ability. In addition, molecular docking is also used to study the interaction between these drugs and large proteins, and the ligand pair is connected to the active site of VEGFR-2 kinase, revealing the possible biological active conformation. This study showed that there was a wide interaction between 6-amide-2-aryl benzoxazole/benzimidazole derivatives and Hrg136 and Tyr356 residues of VEGFR-2 kinase active site. Finally, we used ADMET properties and drug-like properties to predict the newly designed molecules, and the results showed that they meet the conditions for becoming drugs and are expected to become potential anti-VEGFR-2 inhibitors. This study can provide a theoretical reference for the synthesis of target products of VEGFR-2 inhibitors. [ABSTRACT FROM AUTHOR]

The normal expression of SHP2 protein is a key factor in the production and action of cancer cells. Highly active SHP2 inhibitors could inhibit the promotion effect of SHP2 protein on cancer cells to effectively treating cancer. The QSAR modeling methods of 3D-QSAR (Topomer CoMFA) and HQSAR were utilized to discuss the relationship between the SHP2 inhibitory activity and the molecular structures of 35 inhibitors. A reliable and predictive model was obtained through different cutting methods and fragment combinations (Topomer CoMFA with q2 = 0.803, r2 = 0.996, r pred 2 = 0.817; HQSAR with q2 = 0.767, r2 = 0.959, r pred 2 = 0.876). Through the search of the R-group in Topomer search module and the combination of the higher activity contributing groups in the existing molecules, 18 new compounds with theoretically high anti-SHP2 activity were obtained. The docking results with SHP2 protein compared to the original ligand showed that most of the 18 new compounds could generate stable combinations in the form of hydrogen bonds. The prediction results of ADMET properties and drug-like properties indicate that they are eligible to become drugs, which is expected to become potential anti-SHP2 inhibitors and provide a certain amount of reference to foster the synthesis of SHP2 inhibitors. [ABSTRACT FROM AUTHOR]

The cytotoxicity of isosteviol and its twenty derivatives on three human tumor cell lines (ECA-109, MCF-7 and B16-F10) were evaluated. The results demonstrated that ECA-109 was the most sensitive cell line which was exposed to the compound (VI) with the lowest IC50 value of 1.30 ± 0.11 μM. By quantitative structure–activity relationship (QSAR) technique, the obtained cytotoxicity data were further utilized to respectively generate the statistically reliable HQSAR model (q2 = 0.828, r2 = 0.941, = 0.849) and topomer CoMFA model (q2 = 0.608, r2 = 0.919, = 0.747), which could provide the guidelines for the further development of novel and potent anti-esophageal agent. [ABSTRACT FROM AUTHOR]

Genetic mutations in APC or CNTBB1 gene with aberrant canonical Wnt/β-catenin pathway are responsible for more than 90% of colorectal carcinogenesis. Tankyrases (TNKS) are known to downregulate Wnt signaling by stabilizing AXIN protein through poly(ADP ribose)polymerization or PARSylation process and subsequently, promoting degradation of intracellular β-catenin. Tankyrase enzymes are modulated by a range of known inhibitors that bind individually to any of the nicotinamide or induced adenosine pockets or as dual binding antagonists. Hence, for designing dual tankyrase inhibitors as Wnt signaling antagonist; we carried out 3D-QSAR studies using a data set of 51 molecules of reported 3,4,5-trisubstituted 4H-1,2,4-triazole derivatives. These reported 51 molecules were divided into a training set (39 molecules) and test set (12 molecules), aligned and subjected to generate CoMFA, CoMSIA, and HQSAR models. CoMFA analysis showed q2 value of 0.694, r2ncv value of 0.991 and r2pred value of 0.641. Optimized CoMSIA analysis (SEHA) showed q2 value of 0.624, r2ncv value of 0.909 and r2pred value of 0.850. Both internal and external validations were performed for generated models of CoMFA and CoMSIA (SEHA) and satisfactory results were obtained. HQSAR analysis showed q2, r2, and r2pred values of 0.781, 0.901, and 0.811, respectively. Applicability domain was also found to be satisfactory with all compounds falling within the range and no outlier was observed. Contour maps from all studies provided significant results with identification of desired spatial arrangement of different atoms or functional groups in a molecule. Triazole ring system-based molecules were reported as potent tankyrase inhibitors. These noteworthy results were employed for the design of different triazole derivatives as potent tankyrase inhibitors, wherein a series of 20 different molecules were designed for evaluation of their potentials as novel tankyrase inhibitors. [ABSTRACT FROM AUTHOR]

Toxoplasma gondii is an obligate intracellular protozoa that can infect a wide variety of warm-blooded animals and humans. It was claimed that novel anti-Toxoplasma gondii agents were optimized as potential drug candidates, designed and created as significant agents. In this work, molecular modeling studies, including CoMFA, CoMFA-RF, CoMSIA, and HQSAR were performed on a set of 59 thiazolidin-4-one derivatives as anti-T. gondii agents. The statistical qualities of generating models were justified by internal and external validation, i.e., cross-validated correlation coefficient (q2), non-cross-validated correlation coefficient ( r ncv 2 ) and predicted correlation coefficient ( r pred 2 ), respectively. The CoMFA (q2, 0.897; r ncv 2 , 0.933; r pred 2 , 0.938), CoMFA-RF (q2, 0.900; r ncv 2 , 0.935; r pred 2 , 0.998), CoMSIA (q2, 0.910; r ncv 2 , 0.950; r pred 2 , 0.998), and HQSAR models (q2, 0.924; r ncv 2 , 0.953; r pred 2 , 0.995) for training and test set yielded significant statistical results. Therefore, these QSAR models were excellent, robust, and had better predictive capability. Contour maps of the QSAR models were generated and validated by molecular dynamics simulation-assisted molecular docking study. The final QSAR models could be useful for the design and development of novel potent anti-T. gondii agents. [ABSTRACT FROM AUTHOR]

The skin is an important barrier against environmental factors. Foregoing studies has shown that human KLK7 is a protease which promoted epidermal shedding, affected the epidermal barrier and increased the risk of atopic dermatitis. In this study, the structure and activity relationship of 40 human KLK7 inhibitors was explored by three-dimensional quantitative structure–activity relationship (3D-QSAR) and hologram quantitative structure–activity relationship (HQSAR). 3D-QSAR including comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis fields (CoMSIA), and Topomer comparative molecular field analysis (Topomer CoMFA). From the data we got, the 3D-QSAR models (CoMFA with q2 = 0.755, r2 = 0.994; CoMSIA with q2 = 0.602, r2 = 0.980; Topomer CoMFA with q2 = 0.644, r2 = 0.929) and the HQSAR model (q2 = 0.717, r2 = 0.950) had a good predictability. Molecular docking was used to reveal the binding mode between the inhibitors and KLK7 protein further. 3D-QSAR, HQSAR, and molecular docking results also provided guidance for discovering new human KLK7 inhibitors. Finally, 13 new compounds were designed as potential human KLK7 inhibitors, and the predicted activity values showed an effective inhibition on human KLK7. [ABSTRACT FROM AUTHOR]

hURAT1 (human urate transporter 1) is a successful target for hyperuricemia. Recently, the modification work on hURAT1 inhibitors showed that the flexible linkers would benefit biological activity. The study aimed to investigate the contribution of the linkers and give modification strategies on this kind of structures based on QSAR models (HQSAR and topomer CoMFA). The most effective HQSAR and topomer CoMFA models were generated by applying the training set containing 63 compounds, with the cross-validated q2 values of 0.869/0.818 and the non-cross-validated correlation coefficients r2 of 0.951/0.978, respectively. The Y-randomization test was applied to ensure the robustness of the models. The external predictive correlation coefficient (rpred2) grounded on the external test set (21 compounds) of two models was 0.910 and 0.907, respectively. In addition, the models were validated by Golbraikh–Tropsha and Roy methods, as well as other statistical metrics. The results showed that both models were reliable. Topomer CoMFA steric/electrostatic contours and HQSAR atomic contribution maps illustrated the structural features which governed their inhibitory potency. The dependable results could provide important insights to guide the designing of more potential hURAT1 inhibitors. [ABSTRACT FROM AUTHOR]

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.

Using the hologram quantitative structure-activity relationship (HQSAR) method, a quantitative model of the structure-activity relationship between the genotoxicity of quinolones towards gram-negative bacteria and structure of quinolones is constructed. A series of novel quinolones are designed, and 4 environmentally friendly quinolone derivatives are finally selected, because of their enhanced genotoxicity towards gram-negative/positive bacteria, decreased bioconcentration and increased photodegradability and biodegradability. The mechanisms underlying the genotoxicity of quinolones and its derivatives are analysed based on amino acid residues and molecular interactions. Three hydrophilic amino acids [arginine (ARG), asparagine (ASN) and aspartic acid (ASP)] play important roles in the antibacterial effects of quinolones. The introduction of highly hydrophilic groups into the C-7 position of amifloxacin (AMI) not only improved the stability of the AMI derivative-topoisomerase IV-DNA complex but also improved the antibacterial activities of AMI derivatives. [ABSTRACT FROM AUTHOR]

Mycobacterium tuberculosis DNA gyrase subunit B (GyrB) has been identified as a promising target for rational drug design against fluoroquinolone drug-resistant tuberculosis. In this study, we attempted to identify the key structural feature for highly potent GyrB inhibitors through 2D-QSAR using HQSAR, 3D-QSAR using CoMSIA and molecular dynamics (MD) simulations approaches on a series of thiazole urea core derivatives. The best HQSAR and CoMSIA models based on IC50 and MIC displayed the structural basis required for good activity against both GyrB enzyme and mycobacterial cell. MD simulations and binding free energy analysis using MM-GBSA and waterswap calculations revealed that the urea core of inhibitors has the strongest interaction with Asp79 via hydrogen bond interactions. In addition, cation-pi interaction and hydrophobic interactions of the R2 substituent with Arg82 and Arg141 help to enhance the binding affinity in the GyrB ATPase binding site. Thus, the present study provides crucial structural features and a structural concept for rational design of novel DNA gyrase inhibitors with improved biological activities against both enzyme and mycobacterial cell, and with good pharmacokinetic properties and drug safety profiles. [ABSTRACT FROM AUTHOR]

Trichomonas vaginalis is the causative agent of trichomoniasis, a highly prevalent sexually transmitted infection worldwide. Nitroimidazole drugs, such as metronidazole and tinidazole, are the only recommended treatment, but cases of resistance represent at least 5%. In case of resistance or therapeutic failure, posology with higher doses is used, culminating in the increase of the toxic effects of the treatment. In this context, the development of new drugs becomes an eminent necessity. Hologram quantitative structure-activity relationship (HQSAR) models using nitroimidazole derivatives were generated to discover the relationship between the different chemical structures and the activity against cells and the selectivity against susceptible and resistant strains. One model of each strain was chosen for interpretation, both showed good internal coefficient (q2 LOO values: 0.607 for susceptible strain and 0.646 for resistant strain subsets) and great values in other internal and external validations metrics. From the contribution of fragments to HQSAR models, several differences between the most and least potent compounds were found: 5-nitroimidazole contributes positively while 4-nitroimidazole negatively. QSAR models employing random forest (RF-QSAR) machine learning technique were also built and a robust model was obtained from resistant strain activity prediction (q2 LOO equals to 0.618). The constructed HQSAR and RF-QSAR models were employed to predict the activity of three newly planned nitroimidazole derivatives in the design of new drugs candidates against T. vaginalis strains. Image 1 • Nitroimidazole drugs, such as metronidazole and tinidazole, are the only treatment option against T. vaginalis infection. • Generated quantitative structure-activity relationship models have acceptable predictive quality according literature and OECD guidelines. • QSAR based on metronidazole derivatives explains chemical substituents related to anti- T. vaginalis activities. • Substitutions in the position 5′ of the nitroimidazole contributes positively while in the position 4′, negatively. • HOMO – LUMO gap for the MTZ derivatives are smaller for more active compounds. [ABSTRACT FROM AUTHOR]

Abstract Zinc-dependent ADAM17 takes part in a number of life-threatening conditions such as inflammatory diseases, cancer, Alzheimer's disease and rheumatoid arthritis. Therefore, ADAM17 may be a valuable target to design specific inhibitors for combating these diseases. In this scenario, it is a challenging task to design specific ADAM17 inhibitors as none of the earlier investigated compounds has come into the market as a potential drug candidate. Here, molecular modelling including 2D-QSAR, HQSAR, Bayesian classification, pharmacophore mapping and molecular docking studies of arylsulfonamides were performed to explore the structural and pharmacophoric requirements for exerting higher ADAM17 inhibitory activity. All these molecular modelling approaches were validated individually and these were statistically significant and reliable. The bulky steric and hydrophobic P1′ substituents at the para position of the arylsulfonamido moiety favoured ADAM17 inhibition that supported and validated by molecular docking study. These crucial observations of arylsulfonamides may be considered for designing higher effective ADAM17 inhibitors in future. Graphical abstract Image 1 Highlights • Targeting ADAM17 enzyme may be a valuable weapon to combat inflammatory diseases, cancer, Alzheimer's disease and rheumatoid arthritis. • None of the ADAM17 inhibitors has come into the market as drug candidate till now. • Multi-QSAR modelling studies and molecular docking study were performed on arylsulfonamide-based ADAM17 inhibitors. • This study may be beneficial in designing potent ADAM17 inhibitors in future. [ABSTRACT FROM AUTHOR]

• mTOR has become a promising target for the treatment of Breast Cancer. • Triazine Morpholino derivatives as mTOR inhibitors were selected for 3D-QSAR study. • 3D-QSAR contour maps were validated by MD/MS assisted molecular docking study. • Contour maps and molecular docking were used for the designing of mTOR inhibitors. mTOR has become a promising target for many types of cancer like breast, lung and renal cell carcinoma. CoMFA, CoMSIA, Topomer CoMFA and HQSAR were performed on the series of 39 triazine morpholino derivatives. CoMFA analysis showed q2 value of 0.735, r2 cv value of 0.722 and r2 pred value of 0.769. CoMSIA analysis (SEHD) showed q2 value of 0.761, r2 cv value of 0.775 and r2 pred value of 0.651. Topomer CoMFA analysis showed q2 value of 0.693, r2 (conventional correlation coefficient) value of 0.940 and r2 pred value of 0.720. HQSAR analysis showed q2 , r2 and r2 pred values of 0.694, 0.920 and 0.750, respectively. HQSAR analysis with the combination of atomic number (A), bond type (B) and atomic connections showed q2 and r2 values of 0.655 and 0.891, respectively. Contour maps from all studies provided significant insights. Molecular docking studies with molecular dynamics simulations were carried out on the highly potent compound 36. Furthermore, four acridine derivatives were designed and docking results of these designed compounds showed the same interactions as that of the standard PI-103 which proved the efficiency of 3D-QSAR and MD/MS study. In future, this study might be useful prior to synthesis for the designing of novel mTOR inhibitors. [ABSTRACT FROM AUTHOR]

Deazaflavin-dependent nitroreductase (Ddn) is an emerging target in the field of anti-tuberculosis agents. In the present study, 2-nitroimidazooxazine derivatives as Ddn activators were aligned for CoMFA, CoMSIA and HQSAR analysis. The best CoMFA and CoMSIA model were generated with leave-one-out correlation coefficients (q2) of 0.585 and 0.571, respectively. Both the CoMFA and CoMSIA models were also validated by a test set of 11 compounds with satisfactory r pred 2 value of 0.701 and 0.667, respectively. Results of 3D QSAR and HQSAR study were used for the designing of novel and potent nitroimidazooxazine derivatives as Ddn activators. 21 novel compounds were designed, and docked into the Ddn enzyme. In docking study compound ng11 showed interaction with key amino acid residues such as Tyr65 and Tyr133, and also showed better ADMET compatibility. The ADMET prediction, docking study and the predicted activity of novel designed compounds revealed that compound ng11 showed good potential as Ddn activators for the treatment of tuberculosis. [ABSTRACT FROM AUTHOR]

The inability of the systemic antioxidants to alleviate the exacerbation of free radical formation from metabolic outputs and environmental pollutants claims an urgent demand for the identification and design of new chemical entities with potent antioxidant activity. In the present work, different QSAR approaches have been utilized for identifying the essential structural attributes imparting a potential antioxidant activity profile of the coumarin derivatives. The descriptor-based QSAR model provides a quantitative outline regarding the structural prerequisites of the molecules, while 3D pharmacophore and HQSAR models emphasize the favourable spatial arrangement of the various chemical features and the crucial molecular fragments, respectively. All the models infer that the fused benzene ring and the oxygen atom of the pyran ring constituting the parent coumarin nucleus capture the prime pharmacophoric features, imparting superior antioxidant activity to the molecules. The developed models may serve as indispensable query tools for screening untested molecules belonging to the class of coumarin derivatives.

Focal Adhesion Kinase (FAK) is an important target for tumor therapy and is closely related to tumor cell genesis and progression. In this paper, we selected 46 FAK inhibitors with anticancer activity in the pyrrolo pyrimidine backbone to establish 3D/2D-QSAR models to explore the relationship between inhibitory activity and molecular structure. We have established two ideal models, namely, the Topomer CoMFA model ( q 2 = 0.715, r 2 = 0.984) and the Holographic Quantitative Structure-Activity Relationship (HQSAR) model ( q 2 = 0.707, r 2 = 0.899). Both models demonstrate excellent external prediction capabilities.Based on the QSAR results, we designed 20 structurally modified novel compounds, which were subjected to molecular docking and molecular dynamics studies, and the results showed that the new compounds formed many robust interactions with residues within the active pocket and could maintain stable binding to the receptor proteins. This study not only provides a powerful screening tool for designing novel FAK inhibitors, but also presents a series of novel FAK inhibitors with high micromolar activity that can be used for further characterization. It provides a reference for addressing the shortcomings of drug metabolism and drug resistance of traditional FAK inhibitors, as well as the development of novel clinically applicable FAK inhibitors.Communicated by Ramaswamy H. Sarma.

Human meprin β is a Zn 2+ -containing multidomain metalloprotease enzyme that belongs to the astacin family of the metzincin endopeptidase superfamily. Meprin β, with its diverse tissue expression pattern and wide substrate specificity, plays a significant role in various biological processes, including regulation of IL-6R pathways, lung fibrosis, collagen deposition, cellular migration, neurotoxic amyloid β levels, and inflammation. Again, meprin β is involved in Alzheimer's disease, hyperkeratosis, glomerulonephritis, diabetic kidney injury, inflammatory bowel disease, and cancer. Despite a crucial role in diverse disease processes, no such promising inhibitors of meprin β are marketed to date. Thus, it is an unmet requirement to find novel promising meprin β inhibitors that hold promise as potential therapeutics. In this study, a series of arylsulfonamide and tertiary amine-based hydroxamate derivatives as meprin β inhibitors has been analyzed through ligand-based and structure-based in silico approaches to pinpoint their structural and physiochemical requirements crucial for exerting higher inhibitory potential. This study identified different crucial structural features such as arylcarboxylic acid, sulfonamide, and arylsulfonamide moieties, as well as hydrogen bond donor and hydrophobicity, inevitable for exerting higher meprin β inhibition, providing valuable insight for their further future development.Communicated by Ramaswamy H. Sarma.

The inhibition of phosphodiesterase (PDE) 10A enzyme as an alternative approach is shown to have potential in the current treatment of schizophrenia. In the present work, the inhibition activity of 87 structurally diverse pyrimidine derivatives as PDE10A inhibitors were subjected to 2‐dimensional quantitative structure activity relationship (2D‐QSAR) and 3D‐QSAR studies using hologram QSAR and comparative molecular field analysis (CoMFA), respectively. The best CoMFA model gave a noncross‐validated correlation coefficient, (rncv2) = 0.977, SEtrain = 0.247 and predictive correlation coefficient (rpred2) = 0.957, and SEtest = 0.358. For the hologram QSAR (HQSAR) model, the similar parameters were rncv2=0.889, SEtrain = 0.565, rpred2=0.801, and SEtest = 0.872. The leave‐one‐out (LOO) cross‐validated r2 (q2) were 0.78 and 0.8 for the CoMFA and HQSAR models, respectively. These statistics indicate that the CoMFA model is more satisfactory than the HQSAR. Analysis of CoMFA steric and electrostatic contour maps strongly demonstrate that the presence of bulky group at the end of R1 substituent, especially heterocyclic aromatic rings, increase the inhibitory activities, and electronegative groups, such as alkoxide at the R2 position, enhance the inhibitory activities of studied chemicals. The results of this study serves as a guide for the possible modifications and designing of novel pyrimidine derivatives as new potent PDE10A inhibitors. The comparative molecular field analysis (CoMFA) model was successfully developed on 87 pyrimidine‐based derivatives as a PDE10A inhibitor. Analysis of steric and electrostatic contour maps of the derived CoMFA model suggests sufficient information to improve the inhibitory activity by modification of the structure of the studied inhibitor compounds. The constructed CoMFA model demonstrates statistically robust results with a q2 of 0.782, r2ncv of 0.977, and a high predictive ability for the test set (r2pred = 0.957). [ABSTRACT FROM AUTHOR]

The study deals with CoMFA, CoMSIA and HQSAR to explore the important features of tetrahydroimidazo[4,5,1-jk][1,4]benzodiazepinone (TIBO) derivatives for exerting potent HIV-1 reverse transcriptase (HIV-1 RT) inhibitors activity. The cross-validated q 2 value of CoMFA model is 0.641 and the non-cross-validated r 2 value is 0.847. The best cross-validated q 2 value of CoMSIA Model is 0.706 and the non-cross-vaildated r 2 value is 0.939. The most effective HQSAR model was obtained that the cross-validation q 2 value of 0.839, the non-cross-validated r 2 value of 0.942, the standard error of prediction SD CV value of 0.604, and the best hologram length value of 307 using atoms and bonds as fragment distinctions. The statistical parameters from models indicate that the data are well fitted and have high predictive ability. Furthermore, Molecular docking was employed to explore the binding requirements between the ligands and the receptor protein which included several hydrogen bonds between the TIBO inhibitors and active site residues. Observations derived from these QSAR modeling study may be utilized further in designing promising HIV-1 reverse transcriptase inhibitors. [ABSTRACT FROM AUTHOR]

The N-methyl-D-aspartate (NMDA) is the family of glutamate receptor, which is involved in controlling synaptic plasticity and memory function; but overactivation of this receptor results to excess intracellular calcium formation, triggers neuronal injury and also involves in several pathologies. Both ligand- and structure-based quantitative structure-activity relationship (QSAR), pharmacophore, docking and simulation studies have been performed on a set of structurally diverse inhibitors to explore prime molecular structural features involve for specific binding to NMDA, and vis-à-vis inhibiting enzyme activity. 3D QSAR studies, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models showed the importance of steric, electrostatic and hydrophobic features; while hydrogen bond acceptor and hydrophobic features are depicted as important pharmacophore features of the molecule. Molecular docking and simulation studies corroborated the consequence of the features obtained from ligand-based Bayesian model (AUROCcv = 0.878); 3D QSAR CoMFA (R2 = 0.895, se = 0.513, Q2 = 0.602, R2pred = 0.673); CoMSIA (R2 = 0.877, se = 0.555, Q2 = 0.615, R2pred = 0.727); hologram QSAR (Q2 = 0.812, R2 = 0.941, R2pred = 0.772), and pharmacophore models (Q2 = 0.926, R2 = 0.927, R2pred = 0.621). Presence of aromatic ring, hetero and halogen atoms along with alkyl group of molecular scaffold shows their importance for binding affinity to NMDA receptor. Stability of the complex is adjudged by both docking and simulation studies. [ABSTRACT FROM AUTHOR]

Phenylindole is reported to be an interesting scaffold having promising cytotoxic activities and can overcome the cancer drug resistance possibly via binding to the colchicine binding site of tubulin. In order to find out the molecular fingerprints for the better cytotoxic activity of phenylindole derivatives, multiple validated chemometric modeling approaches namely hologram QSAR (HQSAR), Bayesian classification model, and pharmacophore mapping analyses were applied into a dataset of 102 phenylindole derivatives. The final HQSAR model shows good statistical significance (Q2 = 0.760; R2Train = 0.868; R2Test = 0.660), and the best pharmacophore hypothesis has the highest regression coefficient value (r = 0.975) and the lowest RMS value of 0.679. Moreover, the Bayesian model is also statistically validated and robust to discriminate the cytotoxic and non-cytotoxic phenylindoles. These studies suggest that the amine group should be unsubstituted for retaining higher cytotoxicity. The pharmacophore mapping and Bayesian classification study suggest the importance of 2-phenyl group as a ring aromatic feature conducive to cytotoxicity. The steric and hydrophobic effect of long chain linear alkyl group has a positive influence on cytotoxicity as evidenced by the multi-QSAR study. Therefore, this multi-QSAR modeling reported here is beneficial in designing potential phenylindole cytotoxic agents in future. [ABSTRACT FROM AUTHOR]

To have a better understanding of the relationship between structures and inhibitory activities of HIV fusion inhibitors, topomer comparative molecular field analysis (Topomer CoMFA) and hologram quantitative structure-activity relationship (HQSAR) were applied to study a series of pyrrole derivatives as potential HIV fusion inhibitors. Statistical results from the Topomer CoMFA model showed believable predictability based on the non-cross-validated value (r2 = 0.96), and the cross-validated value (q2 = 0.63). The r2 and q2 from the HQSAR model were 0.96 and 0.66, respectively, which also indicated the excellent predictability. External validations further proved the predictive potent of these two models with the rpred2 values of 0.96 for both the two models. Statistical results of the two models showed that they are all credible. In addition, we found a phenomenon that for some compound, bulky and negatively charged substitutions were favourable to its activity in the Topomer COMFA, but nitrogen contributed more positively than the bulkier and more negative chorine in the HQSAR. Therefore, in order to obtain more potential hits, the two models should be combined together. These studies would provide insights for the structure-activity relationship understanding of the small-molecule fusion inhibitors and be helpful for the rational design of novel fusion inhibitors in the future.Steric and electrostatics contour maps of compound A1 were analysed to have a further study on structure necessities of pyrrole derivatives as HIV-1 fusion inhibitor. [ABSTRACT FROM AUTHOR]

The current study deals with chemometric modelling strategies (Naïve Bayes classification, hologram-based quantitative structure-activity relationship (HQSAR), comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA)) to explore the important features of hydroxylamine derivatives for exerting potent human immunodeficiency virus-1 (HIV-1) protease inhibition. Depending on the statistically validated reliable and robust quantitative structure-activity relationship (QSAR) models, important and crucial structural features have been identified that may be responsible for enhancing the activity profile of these hydroxylamine compounds. Arylsulfonamide function along with methoxy or fluoro substitution is important for enhancing activity. Bulky steric substitution at the sulfonamide nitrogen disfavours activity whereas smaller hydrophobic substitution at the same position is found to be favourable. Apart from the crucial oxazolidinone moiety, pyrrolidine, cyclic urea and methyl ester functions are also responsible for increasing the HIV-1 protease inhibitory profile. Observations derived from these modelling studies may be utilized further in designing promising HIV-1 protease inhibitors of this class. [ABSTRACT FROM AUTHOR]

Pathogenic Gram-negative bacteria are responsible for nearly half of the serious human infections. Hologram quantitative structure-activity relationships (HQSAR), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) were implemented on a group of 32 of potent Gram-negative LpxC inhibitors. The most effective HQSAR model was obtained using atoms, bonds, donor, and acceptor as fragment distinction. The cross-validated correlation coefficient (q2), non-cross-validated correlation coefficient (r2), and predictive correlation coefficient (r2Pred) for test set of HQSAR model were 0.937, 0.993, and 0.892, respectively. The generated models were found to be statistically significant as the CoMFA model had (r2 = 0.967, q2 = 0.804, r2Pred = 0.827); the CoMSIA model had (r2 = 0.963, q2 = 0.752, r2Pred = 0.857). Molecular docking was employed to validate the results of the HQSAR, CoMFA, and CoMSIA models. Based on the obtained information, six new LpxC inhibitors have been designed. [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.

Infectious diseases such as trypanosomiasis and leishmaniasis are considered neglected tropical diseases due the lack for many years of research and development into new drug treatments besides the high incidence of mortality and the lack of current safe and effective drug therapies. Natural products such as sesquiterpene lactones have shown activity against T. brucei and L. donovani, the parasites responsible for these neglected diseases. To evaluate structure activity relationships, HQSAR models were constructed to relate a series of 40 sesquiterpene lactones (STLs) with activity against T. brucei, T. cruzi, L. donovani and P. falciparum and also with their cytotoxicity. All constructed models showed good internal (leave-one-out q2 values ranging from 0.637 to 0.775) and external validation coefficients (r2test values ranging from 0.653 to 0.944). From HQSAR contribution maps, several differences between the most and least potent compounds were found. The fragment contribution of PLS-generated models confirmed the results of previous QSAR studies that the presence of α,β-unsatured carbonyl groups is fundamental to biological activity. QSAR models for the activity of these compounds against T. cruzi, L. donovani and P. falciparum are reported here for the first time. The constructed HQSAR models are suitable to predict the activity of untested STLs.

Matrix metalloproteinase-2 (MMP-2) is a potential target in anticancer drug discovery due to its association with angiogenesis, metastasis and tumour progression. In this study, 67 glutamic acid derivatives, synthesized and evaluated as MMP-2 inhibitors, were taken into account for multi-QSAR modelling study (regression-based 2D-QSAR, classification-based LDA-QSAR, Bayesian classification QSAR, HQSAR, 3D-QSAR CoMFA and CoMSIA as well as Open3DQSAR). All these QSAR studies were statistically validated individually. Regarding the 3D-QSAR analysis, the Open3DQSAR results were better than CoMFA and CoMSIA, although all these 3D-QSAR models supported each other. The importance of biphenylsulphonyl moiety over phenylacetyl/naphthylacetyl moieties was established due to its association with favourable steric and hydrophobic characters. HQSAR, LDA-QSAR and Bayesian classification QSAR studies also suggested that the biphenylsulphonamido group was better than the phenylacetylcarboxamido function. Additionally, glutamines were proven to be far better inhibitors than isoglutamines. Observations obtained from the current study were revalidated and supported by the earlier reported molecular modelling studies. Depending on these observations, newer glutamic acid-based compounds may be designed further in future for potent MMP-2 inhibitory activity. [ABSTRACT FROM AUTHOR]

Quionolone carboxylic acid derivatives as inhibitors of HIV-1 integrase were investigated as a potential class of drugs for the treatment of acquired immunodeficiency syndrome (AIDS). Hologram quantitative structure-activity relationships (HQSAR) and translocation comparative molecular field vector analysis (topomer CoMFA) were applied to a series of 48 quionolone carboxylic acid derivatives. The most effective HQSAR model was obtained using atoms and bonds as fragment distinctions: cross-validation q2 = 0.796, standard error of prediction SDCV = 0.36, the non-cross-validated r2 = 0.967, non-cross validated standard error SD = 0.17, the correlation coefficient of external validation Qext 2 = 0.955 and the best hologram length HL = 180. topomer CoMFA models were built based on different fragment cutting models, with the most effective model of q2 = 0.775, SDCV = 0.37, r2 = 0.967, SD = 0.15, Qext 2 = 0.915 and F = 163.255. These results show that the models generated form HQSAR and topomer CoMFA were able to effectively predict the inhibitory potency of this class of compounds. The molecular docking method was also used to study the interactions of these drugs by docking the ligands into the HIV-1 integrase active site, which revealed the likely bioactive conformations. This study showed that there are extensive interactions between the quionolone carboxylic acid derivatives and THR80, VAL82, GLY27, ASP29 and ARG8 residues in the active site of HIV-1 integrase. These results provide useful insights for the design of potent new inhibitors of HIV-1 integrase. [ABSTRACT FROM AUTHOR]

Aromatase is a multienzyme complex responsible for the biosynthesis of estrogen and its level has been found higher in breast cancer. Although the designing strategy of aromatase inhibitors (AIs) has continued for more than four decades, it may still be in demand to design highly effective and less toxic AIs. In this study, several chemometric approaches have been used to explore the important structural features of a series of letrozole-based analogs for their promising aromatase inhibitory activity. All techniques are statistically validated individually and in turn, validated with each other along with the structure-activity relationship (SAR) observations. The imidazole ring has been found to interact with the heme iron, whereas the triazole ring system has not shown any interaction. Moreover, imidazole function is better than 1,2,3-triazole, whereas 1,2,3-triazole is better than the 1,2,5-triazole ring system. Additionally, a bulky aryl substitution in the azole ring along with the orientation of the azole nitrogens and the cyanophenyl function has an essential role in the inhibition of aromatase. Furthermore, a cyano group substituted at the phenyl moiety interacts with Arg115, Met374, and Ser478 at the enzyme active site to form hydrogen bonding interactions. These observations are useful for designing potential AIs in the future. [ABSTRACT FROM AUTHOR]

Influenza endonuclease plays important role in the viral transcription and translation processes. Inhibition of endonuclease enzyme may be an interesting choice to restrict influenza infection. This current study deals with validated multi-chemometric modelling approaches namely regression-based and classification-based quantitative structure-activity relationships (QSARs), hologram QSAR, comparative molecular similarity analysis (CoMSIA), Open3DQSAR study and pharmacophore mapping to identify the structural and physicochemical requirements along with the chemico-biological interactions of pyridinones and pyranones for anti-endonuclease activity. The results suggest that the pyridinone scaffold is more preferable than the pyranone ring. The keto function at 4th position and aryl tetrazole substitution at 1st position of the parent moiety may be important for endonuclease inhibition. Hydroxyl group at 5th position of the parent ring may act as hydrogen bond acceptor feature. The steric substituent is suitable at 2nd position whereas hydrophobic substitution is found to be unfavourable at this position. Bulky hydrophobic substituents are not preferred at the 3rd position of the parent moiety. The information revealed from these integrated ligand-based modelling methods may provide useful informations for designing newer potential anti-influenza agents in future. [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]

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]

Prion diseases are fatal neurodegenerative disorders of the central nervous system characterized by the accumulation of a protease resistant form (PrP Sc ) of the cellular prion protein (PrP C ) in the brain. Two types of cellular prion (PrP C ) compounds have been identified that appear to affect prion conversion are known as Effective Binders (EBs) and Accelerators (ACCs). Effective binders shift the balance in favour of PrP C , whereas Accelerators favour the formation of PrP Sc . Molecular docking indicates EBs and ACCs both bind to pocket-D of the SHaPrP C molecule. However, EBs and ACCs may have opposing effects on the stability of the salt bridge between Arg 156 and Glu 196 /Glu 200 . Computational docking data indicate that the hydrophobic benzamide group of the EB, GFP23 and the 1-(3,3-dimethylcyclohexylidene)piperidinium group of the ACC, GFP22 play an important role in inhibition and conversion from SHaPrP C to SHaPrP Sc , respectively. Experimentally, NMR confirmed the amide chemical shift perturbations observed upon the binding of GFP23 to pocket-D of SHaPrP C . Consistent with its role as an ACC, titration of GFP22 resulted in widespread chemical shift changes and signal intensity loss due to protein unfolding. Virtual screening of a ligand database using the molecular scaffold developed from the set of EBs identified six of our compounds (previously studied using fluorescence quenching) as being among the top 100 best binders. Among them, compounds 5 and 6 were found to be particularly potent in decreasing the accumulation SHaPrP Sc in ScN2a cells with an IC 50 of ∼35 µM and 20 µM. [ABSTRACT FROM AUTHOR]

Glutaminase is one of the important key enzymes regulating cellular metabolism, growth, and proliferation in cancer. Therefore, it is being explored as a crucial target regarding anticancer drug design and development. However, none of the potent and selective glutaminase inhibitors is available in the market though two prototype glutaminase inhibitors are reported namely DON as well as BPTES. Due to severe toxicity in clinical trials, the use of DON is restricted. However, BPTES is an allosteric glutaminase inhibitor with less toxic profile and, therefore, lead optimization of BPTES may be a good option to develop newer drug candidates. In this study, a multi-QSAR modeling is carried out on a series of BPTES analogs. A significant connection between different descriptors and the glutaminase inhibitory activities is noticed by employing multiple linear regression, artificial neural network and support vector machine techniques. The classification-based QSAR such as linear discriminant analysis and Bayesian classification modeling are also performed to search important molecular fingerprints or substructures that may help in classifying the probability of finding ‘active’ and ‘inactive’ BPTES analogs. Moreover, HQSAR and Topomer CoMFA analyses are also performed. In addition, the SAR observations are interpreted with all these validated computational models along with the structure-based contours. Finally, new twenty two compounds are designed and predicted for their probable glutaminase inhibitory activity. [ABSTRACT FROM AUTHOR]

Comparative molecular field analysis (CoMFA), topomer CoMFA, and hologram QSAR as three efficient methods of QSAR have been performed on 40 newly synthesized inhibitors against HIV-1 protease. Molecular alignment was performed by aid of crystallographic structure of template inhibitor (indirect alignment) and also by the molecular mechanic (MM)-minimized structure. Both alignment methods produced satisfactory statistics for training set, but indirect alignment had more predictive power. Generated counter maps, especially by topomer CoMFA, give comprehensive information about structural features affecting the inhibitory activities of studied chemicals. Based on the obtained information, some new inhibitors were suggested. [ABSTRACT FROM AUTHOR]

The inhibition of β-secretase (BACE1) is currently the main pharmacological strategy available for Alzheimer’s disease (AD). 2D QSAR and 3D QSAR analysis on some cyclic sulfone hydroxyethylamines inhibitors against β-secretase (IC 50 : 0.002–2.75 μM) were carried out using hologram QSAR (HQSAR), comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA) methods. The best model based on the training set was generated with a HQSAR q 2 value of 0.693 and r 2 value of 0.981; a CoMFA q 2 value of 0.534 and r 2 value of 0.913; and a CoMSIA q 2 value of 0.512 and r 2 value of 0.973. In order to gain further understand of the vital interactions between cyclic sulfone hydroxyethylamines and the protease, the analysis was performed by combining the CoMFA and CoMSIA field distributions with the active sites of the BACE1. The final QSAR models could be helpful in the design and development of novel active BACE1 inhibitors. [ABSTRACT FROM AUTHOR]

DPP IV is an important biological target for treatment of diabetes. The CoMFA, CoMSIA and HQSAR models have been developed on thirty two aminomethyl piperidones derivatives. The data set consisting of twenty one training set compounds and eleven test set compounds that showed good statistical significance with internal cross validation (q2) 0.849, 0.790 and 0.901, non-cross validation (r2) 0.863, 0.793 and 0.903 and predicted (pred. r2) 0.845, 0.822 and 0.901 for CoMFA, CoMSIA and HQSAR, respectively for anti-diabetic activity. The docking study explored with active site of DPP IV, in particular, the contribution of the -NH, 2,5 di-F (Ar) with Asn 151, Asn 169 and Asn 170 of the compound 22, respectively, which is important for the bioactive conformation for DPP IV inhibition. The QSAR models, contour maps, and docking binding affinity obtained could be successfully utilized as a guiding tool for design and discovery of novel derivatives. [ABSTRACT FROM AUTHOR]