Displaying publications 61 - 80 of 553 in total

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  1. Algamal ZY, Lee MH
    SAR QSAR Environ Res, 2017 Jan;28(1):75-90.
    PMID: 28176549 DOI: 10.1080/1062936X.2017.1278618
    A high-dimensional quantitative structure-activity relationship (QSAR) classification model typically contains a large number of irrelevant and redundant descriptors. In this paper, a new design of descriptor selection for the QSAR classification model estimation method is proposed by adding a new weight inside L1-norm. The experimental results of classifying the anti-hepatitis C virus activity of thiourea derivatives demonstrate that the proposed descriptor selection method in the QSAR classification model performs effectively and competitively compared with other existing penalized methods in terms of classification performance on both the training and the testing datasets. Moreover, it is noteworthy that the results obtained in terms of stability test and applicability domain provide a robust QSAR classification model. It is evident from the results that the developed QSAR classification model could conceivably be employed for further high-dimensional QSAR classification studies.
    Matched MeSH terms: Quantitative Structure-Activity Relationship*
  2. Algamal ZY, Qasim MK, Lee MH, Ali HTM
    SAR QSAR Environ Res, 2020 Nov;31(11):803-814.
    PMID: 32938208 DOI: 10.1080/1062936X.2020.1818616
    High-dimensionality is one of the major problems which affect the quality of the quantitative structure-activity relationship (QSAR) modelling. Obtaining a reliable QSAR model with few descriptors is an essential procedure in chemometrics. The binary grasshopper optimization algorithm (BGOA) is a new meta-heuristic optimization algorithm, which has been used successfully to perform feature selection. In this paper, four new transfer functions were adapted to improve the exploration and exploitation capability of the BGOA in QSAR modelling of influenza A viruses (H1N1). The QSAR model with these new quadratic transfer functions was internally and externally validated based on MSEtrain, Y-randomization test, MSEtest, and the applicability domain (AD). The validation results indicate that the model is robust and not due to chance correlation. In addition, the results indicate that the descriptor selection and prediction performance of the QSAR model for training dataset outperform the other S-shaped and V-shaped transfer functions. QSAR model using quadratic transfer function shows the lowest MSEtrain. For the test dataset, proposed QSAR model shows lower value of MSEtest compared with the other methods, indicating its higher predictive ability. In conclusion, the results reveal that the proposed QSAR model is an efficient approach for modelling high-dimensional QSAR models and it is useful for the estimation of IC50 values of neuraminidase inhibitors that have not been experimentally tested.
    Matched MeSH terms: Quantitative Structure-Activity Relationship*
  3. Alharthi AM, Lee MH, Algamal ZY, Al-Fakih AM
    SAR QSAR Environ Res, 2020 Aug;31(8):571-583.
    PMID: 32628042 DOI: 10.1080/1062936X.2020.1782467
    One of the most challenging issues when facing a Quantitative structure-activity relationship (QSAR) classification model is to deal with the descriptor selection. Penalized methods have been adapted and have gained popularity as a key for simultaneously performing descriptor selection and QSAR classification model estimation. However, penalized methods have drawbacks such as having biases and inconsistencies that make they lack the oracle properties. This paper proposes an adaptive penalized logistic regression (APLR) to overcome these drawbacks. This is done by employing a ratio (BWR) of the descriptors between-groups sum of squares (BSS) to the within-groups sum of squares (WSS) for each descriptor as a weight inside the L1-norm. The proposed method was applied to one dataset that consists of a diverse series of antimicrobial agents with their respective bioactivities against Candida albicans. By experimental study, it has been shown that the proposed method (APLR) was more efficient in the selection of descriptors and classification accuracy than the other competitive methods that could be used in developing QSAR classification models. Another dataset was also successfully experienced. Therefore, it can be concluded that the APLR method had significant impact on QSAR analysis and studies.
    Matched MeSH terms: Quantitative Structure-Activity Relationship*
  4. Alharthi AM, Kadir DH, Al-Fakih AM, Algamal ZY, Al-Thanoon NA, Qasim MK
    SAR QSAR Environ Res, 2023;34(10):831-846.
    PMID: 37885432 DOI: 10.1080/1062936X.2023.2261855
    The horse herd optimization algorithm (HOA), one of the more contemporary metaheuristic algorithms, has demonstrated superior performance in a number of challenging optimization tasks. In the present work, the descriptor selection issue is resolved by classifying different essential oil retention indices using the binary form, BHOA. Based on internal and external prediction criteria, Z-shape transfer functions (ZTF) were tested to verify their efficiency in improving BHOA performance in QSPR modelling for predicting retention indices of essential oils. The evaluation criteria involved the mean-squared error of the training and testing datasets (MSE), and leave-one-out internal and external validation (Q2). The degree of convergence of the proposed Z-shaped transfer functions was compared. In addition, K-fold cross validation with k = 5 was applied. The results show that ZTF, especially ZTF1, greatly improves the performance of the original BHOA. Comparatively speaking, ZTF, especially ZTF1, exhibits the fastest convergence behaviour of the binary algorithms. It chooses the fewest descriptors and requires the fewest iterations to achieve excellent prediction performance.
    Matched MeSH terms: Quantitative Structure-Activity Relationship*
  5. Alhassan AM, Ahmed QU, Latip J, Shah SAA
    Nat Prod Res, 2019 Jan;33(1):1-8.
    PMID: 29417849 DOI: 10.1080/14786419.2018.1437427
    The bioactivity guided fractionation of Tetracera indica leaves crude ethanolic extract has afforded the isolation and characterization of six compounds including a new natural product viz., 5,7-dihydroxyflavone-O-8-sulphate (1) and five known flavonoids (2-6). The structures of the compounds were elucidated using 1D and 2D NMR and HRESIMS spectroscopic analyses. All the isolated compounds were evaluated for their in vitro inhibitory activity against alpha-glucosidase. Compound 1, 5 and 6 showed strong alpha-glucosidase inhibitory activity, 3 and 4 displayed weak activity while compound 2 was inactive. The interactions of the active compounds with alpha-glucosidase were further investigated using molecular docking to confirm their antidiabetic potential.
    Matched MeSH terms: Structure-Activity Relationship
  6. Ali F, Khan KM, Salar U, Iqbal S, Taha M, Ismail NH, et al.
    Bioorg Med Chem, 2016 08 15;24(16):3624-35.
    PMID: 27325448 DOI: 10.1016/j.bmc.2016.06.002
    Dihydropyrimidones 1-37 were synthesized via a 'one-pot' three component reaction according to well-known Biginelli reaction by utilizing Cu(NO3)2·3H2O as catalyst, and screened for their in vitro β-glucuronidase inhibitory activity. It is worth mentioning that amongst the active molecules, compounds 8 (IC50=28.16±.056μM), 9 (IC50=18.16±0.41μM), 10 (IC50=22.14±0.43μM), 13 (IC50=34.16±0.65μM), 14 (IC50=17.60±0.35μM), 15 (IC50=15.19±0.30μM), 16 (IC50=27.16±0.48μM), 17 (IC50=48.16±1.06μM), 22 (IC50=40.16±0.85μM), 23 (IC50=44.16±0.86μM), 24 (IC50=47.16±0.92μM), 25 (IC50=18.19±0.34μM), 26 (IC50=33.14±0.68μM), 27 (IC50=44.16±0.94μM), 28 (IC50=24.16±0.50μM), 29 (IC50=34.24±0.47μM), 31 (IC50=14.11±0.21μM) and 32 (IC50=9.38±0.15μM) found to be more potent than the standard d-saccharic acid 1,4-lactone (IC50=48.4±1.25μM). Molecular docking study was conducted to establish the structure-activity relationship (SAR) which demonstrated that a number of structural features of dihydropyrimidone derivatives were involved to exhibit the inhibitory potential. All compounds were characterized by spectroscopic techniques such as (1)H, (13)C NMR, EIMS and HREI-MS.
    Matched MeSH terms: Structure-Activity Relationship
  7. Ali F, Khan KM, Salar U, Taha M, Ismail NH, Wadood A, et al.
    Eur J Med Chem, 2017 Sep 29;138:255-272.
    PMID: 28672278 DOI: 10.1016/j.ejmech.2017.06.041
    Acarbose, miglitol, and voglibose are the inhibitors of α-glucosidase enzyme and being clinically used for the management of type-II diabetes mellitus. However, many adverse effects are also associated with them. So, the development of new therapeutic agents is an utmost interest in medicinal chemistry research. Current study is based on the identification of new α-glucosidase inhibitors. For that purpose, hydrazinyl arylthiazole based pyridine derivatives 1-39 were synthesized via two step reaction and fully characterized by spectroscopic techniques EI-MS, HREI-MS, (1)H-, and (13)C NMR. However, stereochemistry of the iminic bond was confirmed by NOESY. All compounds were subjected to in vitro α-glucosidase inhibitory activity and found many folds active (IC50 = 1.40 ± 0.01-236.10 ± 2.20 μM) as compared to the standard acarbose having IC50 value of 856.45 ± 5.60 μM. A limited structure-activity relationship was carried out in order to make a presumption about the substituent's effect on inhibitory activity which predicted that substituents of more negative inductive effect played important role in the activity as compared to the substituents of less negative inductive effect. However, in order to have a good understanding of ligand enzyme interactions, molecular docking study was also conducted. In silico study was confirmed that substituents like halogens (Cl) and nitro (NO2) which have negative inductive effect were found to make important interactions with active site residues.
    Matched MeSH terms: Structure-Activity Relationship
  8. Ali MA, Ismail R, Choon TS, Pandian S, Hassan Ansari MZ
    J Enzyme Inhib Med Chem, 2011 Aug;26(4):598-602.
    PMID: 21714764 DOI: 10.3109/14756366.2010.529805
    In this study, a series of novel 3-(substituted phenyl)-6,7-dimethoxy-3a,4-dihydro-3H-indeno[1,2-c]isoxazole analogues were synthesized and evaluated for antimycobacterial activity against Mycobacterium tuberculosis (MTB) H(37)Rv and isoniazid resistant M. tuberculosis (INHR-MTB). All the newly synthesized compounds were showing moderate to high inhibitory activities. The compound 6,7-dimethoxy-3-(4-chloro phenyl)-4H-indeno[1,2-c]isoxazole (4b) was found to be the most promising compound, active against MTB H(37)Rv and INHR-MTB with minimum inhibitory concentrations of 0.22 and 0.34 μM.
    Matched MeSH terms: Structure-Activity Relationship
  9. Ali MA, Ismail R, Choon TS, Yoon YK, Wei AC, Pandian S, et al.
    Acta Pol Pharm, 2011 May-Jun;68(3):343-8.
    PMID: 21648188
    A series of novel 3-(substituted phenyl)-6,7-dimethoxy-3a,4-dihydro-3H-indeno[1,2-c]isoxazole analogues were synthesized by the reaction of 5,6-dimethoxy-2-[(E)-1-phenylmethylidene]-1-indanone with hydroxylamine hydrochloride. The title compounds were tested for their in vitro anti-HIV activity. Among the compounds, (4g) showed a promising anti-HIV activity in the in vitro testing against IIIB and ROD strains. The IC50 of both IIIB and ROD were found to be 9.05 microM and > 125 microM, respectively.
    Matched MeSH terms: Structure-Activity Relationship
  10. Ali MA, Bastian S, Ismail R, Choon TS, Ali S, Aubry A, et al.
    J Enzyme Inhib Med Chem, 2011 Dec;26(6):890-4.
    PMID: 21395486 DOI: 10.3109/14756366.2011.559945
    A series of pyrazoline derivatives were synthesized and in vitro activity against Mycobacterium tuberculosis H37Rv was carried out. Among the synthesized compounds, compounds (4d) and (4f) 4-aminophenyl-3-(3,4-dimethoxyphenyl)-6,7-dimethoxy-2,3,3a,4-tetrahydroindeno[1,2-c]pyrazol-2-ylmethanone and 4-aminophenyl-6,7-dimethoxy-3-phenyl-2,3,3a,4-tetrahydroindeno[1,2-c]pyrazol-2-ylmethanone were found to be the most active agent against M. tuberculosis H37Rv with a minimum inhibitory concentration of 10 μg/mL.
    Matched MeSH terms: Structure-Activity Relationship
  11. Ali MA, Ismail R, Choon TS, Yoon YK, Wei AC, Pandian S, et al.
    Bioorg Med Chem Lett, 2010 Dec 1;20(23):7064-6.
    PMID: 20951037 DOI: 10.1016/j.bmcl.2010.09.108
    Series of pyrolidine analogues were synthesized and examined as acetylcholinesterase (AChE) inhibitors. Among the compounds, compounds 4k and 6k were the most potent inhibitors of the series. Compound 4k, showed potent inhibitory activity against acetyl cholinesterase enzyme with IC(50) 0.10 μmol/L. Pyrolidine analogues might be potential acetyl cholinesterase agents for AD.
    Matched MeSH terms: Structure-Activity Relationship
  12. Aljohani G, Said MA, Lentz D, Basar N, Albar A, Alraqa SY, et al.
    Molecules, 2019 Feb 07;24(3).
    PMID: 30736403 DOI: 10.3390/molecules24030590
    An efficient microwave-assisted one-step synthetic route toward Mannich bases is developed from 4-hydroxyacetophenone and different secondary amines in quantitative yields, via a regioselective substitution reaction. The reaction takes a short time and is non-catalyzed and reproducible on a gram scale. The environmentally benign methodology provides a novel alternative, to the conventional methodologies, for the synthesis of mono- and disubstituted Mannich bases of 4-hydroxyacetophenone. All compounds were well-characterized by FT-IR, ¹H NMR, 13C NMR, and mass spectrometry. The structures of 1-{4-hydroxy-3-[(morpholin-4-yl)methyl]phenyl}ethan-1-one (2a) and 1-{4-hydroxy-3-[(pyrrolidin-1-yl)methyl]phenyl}ethan-1-one (3a) were determined by single crystal X-ray crystallography. Compound 2a and 3a crystallize in monoclinic, P2₁/n, and orthorhombic, Pbca, respectively. The most characteristic features of the molecular structure of 2a is that the morpholine fragment adopts a chair conformation with strong intramolecular hydrogen bonding. Compound 3a exhibits intermolecular hydrogen bonding, too. Furthermore, the computed Hirshfeld surface analysis confirms H-bonds and π⁻π stack interactions obtained by XRD packing analyses.
    Matched MeSH terms: Structure-Activity Relationship
  13. Almandil NB, Taha M, Rahim F, Wadood A, Imran S, Alqahtani MA, et al.
    Bioorg Chem, 2019 04;85:109-116.
    PMID: 30605884 DOI: 10.1016/j.bioorg.2018.12.025
    New series of quinoline-based thiadiazole analogs (1-20) were synthesized, characterized by EI-MS, 1H NMR and 13C NMR. All synthesized compounds were subjected to their antileishmanial potential. Sixteen analogs 1-10, 12, 13, 16, 17, 18 and 19 with IC50 values in the range of 0.04 ± 0.01 to 5.60 ± 0.21 µM showed tremendously potent inhibition as compared to the standard pentamidine with IC50 value 7.02 ± 0.09 µM. Analogs 11, 14, 15 and 20 with IC50 8.20 ± 0.35, 9.20 ± 0.40, 7.20 ± 0.20 and 9.60 ± 0.40 µM respectively showed good inhibition when compared with the standard. Structure-activity relationships have been also established for all compounds. Molecular docking studies were performed to determine the binding interaction of the compounds with the active site target.
    Matched MeSH terms: Structure-Activity Relationship
  14. Alomari M, Taha M, Imran S, Jamil W, Selvaraj M, Uddin N, et al.
    Bioorg Chem, 2019 11;92:103235.
    PMID: 31494327 DOI: 10.1016/j.bioorg.2019.103235
    Hybrid bis-coumarin derivatives 1-18 were synthesized and evaluated for their in vitro urease inhibitory potential. All compounds showed outstanding urease inhibitory potential with IC50 value (The half maximal inhibitory concentration) ranging in between 0.12 SD 0.01 and 38.04 SD 0.63 µM (SD standard deviation). When compared with the standard thiourea (IC50 = 21.40 ± 0.21 µM). Among these derivatives, compounds 7 (IC50 = 0.29 ± 0.01), 9 (IC50 = 2.4 ± 0.05), 10 (IC50 = 2.25 ± 0.05) and 16 (IC50 = 0.12 ± 0.01) are better inhibitors of the urease compared with thiourea (IC50 = 21.40 ± 0.21 µM). To find structure-activity relationship molecular docking as well as absorption, distribution, metabolism, and excretion (ADME) studies were also performed. Various spectroscopic techniques like 1H NMR, 13C NMR, and EI-MS were used for characterization of all synthesized analogs. All compounds were tested for cytotoxicity and found non-toxic.
    Matched MeSH terms: Structure-Activity Relationship
  15. Alomari M, Taha M, Rahim F, Selvaraj M, Iqbal N, Chigurupati S, et al.
    Bioorg Chem, 2021 03;108:104638.
    PMID: 33508679 DOI: 10.1016/j.bioorg.2021.104638
    A series of nineteen (1-19) indole-based-thiadiazole derivatives were synthesized, characterized by 1HNMR, 13C NMR, MS, and screened for α-glucosidase inhibition. All analogs showed varied α-glucosidase inhibitory potential with IC50 value ranged between 0.95 ± 0.05 to 13.60 ± 0.30 µM, when compared with the standard acarbose (IC50 = 1.70 ± 0.10). Analogs 17, 2, 1, 9, 7, 3, 15, 10, 16, and 14 with IC50 values 0.95 ± 0.05, 1.10 ± 0.10, 1.30 ± 0.10, 1.60 ± 0.10, 2.30 ± 0.10, 2.30 ± 0.10, 2.80 ± 0.10, 4.10 ± 0.20 and 4.80 ± 0.20 µM respectively showed highest α-glucosidase inhibition. All other analogs also exhibit excellent inhibitory potential. Structure activity relationships have been established for all compounds primarily based on substitution pattern on the phenyl ring. Through molecular docking study, binding interactions of the most active compounds were confirmed. We further studied the kinetics study of analogs 1, 2, 9 and 17 and found that they are Non-competitive inhibitors.
    Matched MeSH terms: Structure-Activity Relationship
  16. Alrosan M, Tan TC, Koh WY, Easa AM, Gammoh S, Alu'datt MH
    Crit Rev Food Sci Nutr, 2023;63(25):7677-7691.
    PMID: 35266840 DOI: 10.1080/10408398.2022.2049200
    Demands for high nutritional value-added food products and plant-based proteins have increased over the last decade, in line with the growth of the human population and consumer health awareness. The quality of the plant-based proteins depends on their digestibility, amino acid content, and residues of non-nutritive compounds, such as phenolic compounds, anti-nutritional compounds, antioxidants, and saponins. The presence of these non-nutritive compounds could have detrimental effects on the quality of the proteins. One of the solutions to address these shortcomings of plant-based proteins is fermentation, whereby enzymes that present naturally in microorganisms used during fermentation are responsible for the cleavage of the bonds between proteins and non-nutritive compounds. This mechanism has pronounced effects on the non-nutritive compounds, resulting in the enhancement of protein digestibility and functional properties of plant-based proteins. We assert that the types of plant-based proteins and microorganisms used during fermentation must be carefully addressed to truly enhance the quality, functional properties, and health functionalities of plant-based proteins.Supplemental data for this article is available online at here. show.
    Matched MeSH terms: Structure-Activity Relationship
  17. Altamimi AS, Alafeefy AM, Balode A, Vozny I, Pustenko A, El Shikh ME, et al.
    J Enzyme Inhib Med Chem, 2018 Dec;33(1):147-150.
    PMID: 29199484 DOI: 10.1080/14756366.2017.1404593
    A series of symmetric molecules incorporating aryl or pyridyl moieties as central core and 1,4-substituted triazoles as a side bridge was synthesised. The new compounds were investigated as lactate dehydro-genase (LDH, EC 1.1.1.27) inhibitors. The cancer associated LDHA isoform was inhibited with IC50 = 117-174 µM. Seven compounds exhibited better LDHA inhibition (IC50 117-136 µM) compared to known LDH inhibitor - galloflavin (IC50 157 µM).
    Matched MeSH terms: Structure-Activity Relationship
  18. Ambrosio L, Battista S, Borzacchiello A, Borselli C, Causa F, De Santis R, et al.
    Med J Malaysia, 2004 May;59 Suppl B:71-2.
    PMID: 15468824
    Matched MeSH terms: Structure-Activity Relationship
  19. Anasamy T, Thy CK, Lo KM, Chee CF, Yeap SK, Kamalidehghan B, et al.
    Eur J Med Chem, 2017 Jan 05;125:770-783.
    PMID: 27723565 DOI: 10.1016/j.ejmech.2016.09.061
    This study seeks to investigate the relationship between the structural modification and bioactivity of a series of tribenzyltin complexes with different ligands and substitutions. Complexation with the N,N-diisopropylcarbamothioylsulfanylacetate or isonicotinate ligands enhanced the anticancer properties of tribenzyltin compounds via delayed cancer cell-cycle progression, caspase-dependent apoptosis induction, and significant reduction in cell motility, migration and invasion. Halogenation of the benzyl ring improved the anticancer effects of the tribenzyltin compounds with the N,N-diisopropylcarbamothioylsulfanylacetate ligand. These compounds also demonstrated far greater anticancer effects and selectivity than cisplatin and doxorubicin, which provides a rationale for their further development as anticancer agents.
    Matched MeSH terms: Structure-Activity Relationship
  20. Anasir MI, Ramanathan B, Poh CL
    Viruses, 2020 03 26;12(4).
    PMID: 32225021 DOI: 10.3390/v12040367
    Dengue virus (DENV) presents a significant threat to global public health with more than 500,000 hospitalizations and 25,000 deaths annually. Currently, there is no clinically approved antiviral drug to treat DENV infection. The envelope (E) glycoprotein of DENV is a promising target for drug discovery as the E protein is important for viral attachment and fusion. Understanding the structure and function of DENV E protein has led to the exploration of structure-based drug discovery of antiviral compounds and peptides against DENV infections. This review summarizes the structural information of the DENV E protein with regards to DENV attachment and fusion. The information enables the development of antiviral agents through structure-based approaches. In addition, this review compares the potency of antivirals targeting the E protein with the antivirals targeting DENV multifunctional enzymes, repurposed drugs and clinically approved antiviral drugs. None of the current DENV antiviral candidates possess potency similar to the approved antiviral drugs which indicates that more efforts and resources must be invested before an effective DENV drug materializes.
    Matched MeSH terms: Structure-Activity Relationship
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