Displaying publications 1 - 20 of 59 in total

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  1. Fulltext Synthesis of novel cytotoxic tetracyclic acridone derivatives and study of their molecular docking, ADMET, QSAR, bioactivity and protein binding properties
    Veligeti R, Madhu RB, Anireddy J, Pasupuleti VR, Avula VKR, Ethiraj KS, et al.
    Sci Rep, 2020 11 26;10(1):20720.
    PMID: 33244007 DOI: 10.1038/s41598-020-77590-1
    Acridone based synthetic and natural products with inherent anticancer activity advancing the research and generating a large number of structurally diversified compounds. In this sequence we have designed, synthesized a series of tetracyclic acridones with amide framework viz., 3-(alkyloyl/ aryloyl/ heteroaryloyl/ heteroaryl)-2,3-dihydropyrazino[3,2,1-de]acridin-7(1H)-ones and screened for their in vitro anti-cancer activity. The in vitro study revealed that compounds with cyclopropyl-acetyl, benzoyl, p-hydroxybenzoyl, p-(trifluoromethyl)benzoyl, p-fluorobenzoyl, m-fluorobenzoyl, picolinoyl, 6-methylpicolinoyl and 3-nicotinoyl groups are active against HT29, MDAMB231 and HEK293T cancer cell lines. The molecular docking studies performed for them against 4N5Y, HT29 and 2VWD revealed the potential ligand-protein binding interactions among the neutral aminoacid of the enzymes and carbonyl groups of the title compounds with a binding energy ranging from - 8.1394 to - 6.9915 kcal/mol. In addition, the BSA protein binding assay performed for them has confirmed their interaction with target proteins through strong binding to BSA macromolecule. The additional studies like ADMET, QSAR, bioactivity scores, drug properties and toxicity risks ascertained them as newer drug candidates. This study had added a new collection of piperazino fused acridone derivatives to the existing array of other nitrogen heterocyclic fused acridone derivatives as anticancer agents.
    Matched MeSH terms: Quantitative Structure-Activity Relationship
  2. QSAR classification model for diverse series of antifungal agents based on binary coyote optimization algorithm
    Al-Fakih AM, Qasim MK, Algamal ZY, Alharthi AM, Zainal-Abidin MH
    SAR QSAR Environ Res, 2023 Apr;34(4):285-298.
    PMID: 37157994 DOI: 10.1080/1062936X.2023.2208374
    One of the recently developed metaheuristic algorithms, the coyote optimization algorithm (COA), has shown to perform better in a number of difficult optimization tasks. The binary form, BCOA, is used in this study as a solution to the descriptor selection issue in classifying diverse antifungal series. Z-shape transfer functions (ZTF) are evaluated to verify their efficiency in improving BCOA performance in QSAR classification based on classification accuracy (CA), the geometric mean of sensitivity and specificity (G-mean), and the area under the curve (AUC). The Kruskal-Wallis test is also applied to show the statistical differences between the functions. The efficacy of the best suggested transfer function, ZTF4, is further assessed by comparing it to the most recent binary algorithms. The results prove that ZTF, especially ZTF4, significantly improves the performance of the original BCOA. The ZTF4 function yields the best CA and G-mean of 99.03% and 0.992%, respectively. It shows the fastest convergence behaviour compared to other binary algorithms. It takes the fewest iterations to reach high classification performance and selects the fewest descriptors. In conclusion, the obtained results indicate the ability of the ZTF4-based BCOA to find the smallest subset of descriptors while maintaining the best classification accuracy performance.
    Matched MeSH terms: Quantitative Structure-Activity Relationship
  3. Theoretically-derived molecular descriptors important in human intestinal absorption
    Agatonovic-Kustrin S, Beresford R, Yusof AP
    J Pharm Biomed Anal, 2001 May;25(2):227-37.
    PMID: 11275432
    A quantitative structure-human intestinal absorption relationship was developed using artificial neural network (ANN) modeling. A set of 86 drug compounds and their experimentally-derived intestinal absorption values used in this study was gathered from the literature and a total of 57 global molecular descriptors, including constitutional, topological, chemical, geometrical and quantum chemical descriptors, calculated for each compound. A supervised network with radial basis transfer function was used to correlate calculated molecular descriptors with experimentally-derived measures of human intestinal absorption. A genetic algorithm was then used to select important molecular descriptors. Intestinal absorption values (IA%) were used as the ANN's output and calculated molecular descriptors as the inputs. The best genetic neural network (GNN) model with 15 input descriptors was chosen, and the significance of the selected descriptors for intestinal absorption examined. Results obtained with the model that was developed indicate that lipophilicity, conformational stability and inter-molecular interactions (polarity, and hydrogen bonding) have the largest impact on intestinal absorption.
    Matched MeSH terms: Quantitative Structure-Activity Relationship
  4. Occurrence, fate and environmental risk of linear alkylbenzene sulfonate in the Langat and Selangor River basins, Malaysia
    Sakai N, Shirasaka J, Matsui Y, Ramli MR, Yoshida K, Ali Mohd M, et al.
    Chemosphere, 2017 Apr;172:234-241.
    PMID: 28081507 DOI: 10.1016/j.chemosphere.2016.12.139
    Five homologs (C10-C14) of linear alkylbenzene sulfonate (LAS) were quantitated in surface water collected in the Langat and Selangor River basins using liquid chromatography-tandem mass spectrometry (LC-MS/MS). A geographic information system (GIS) was used to spatially analyze the occurrence of LAS in both river basins, and the LAS contamination associated with the population was elucidated by spatial analysis at a sub-basin level. The LAS concentrations in the dissolved phase (<0.45 μm) and 4 fractions separated by particle size (<0.1 μm, 0.1-1 μm, 1-11 μm and >11 μm) were analyzed to elucidate the environmental fate of LAS in the study area. The environmental risks of the observed LAS concentration were assessed based on predicted no effect concentration (PNEC) normalized by a quantitative structure-activity relationship model. The LAS contamination mainly occurred from a few populated sub-basins, and it was correlated with the population density and ammonia nitrogen. The dissolved phase was less than 20% in high contamination sites (>1000 μg/L), whereas it was more than 60% in less contaminated sites (<100 μg/L). The environmental fate of LAS in the study area was primarily subject to the adsorption to suspended solids rather than biodegradation because the LAS homologs, particularly in longer alkyl chain lengths, were considerably absorbed to the large size fraction (>11 μm) that settled in a few hours. The observed LAS concentrations exceeded the normalized PNEC at 3 sites, and environmental risk areas and susceptible areas to the LAS contamination were spatially identified based on their catchment areas.
    Matched MeSH terms: Quantitative Structure-Activity Relationship
  5. Designing hypothesis of substituted benzoxazinones as HIV-1 reverse transcriptase inhibitors: QSAR approach
    Veerasamy R, Subramaniam DK, Chean OC, Ying NM
    J Enzyme Inhib Med Chem, 2012 Oct;27(5):693-707.
    PMID: 21961709 DOI: 10.3109/14756366.2011.608664
    A linear quantitative structure activity relationship (QSAR) model is presented for predicting human immunodeficiency virus-1 (HIV-1) reverse transcriptase enzyme inhibition. The 2D QSAR and 3D-QSAR models were developed by stepwise multiple linear regression, partial least square (PLS) regression and k-nearest neighbor-molecular field analysis, PLS regression, respectively using a database consisting of 33 recently discovered benzoxazinones. The primary findings of this study is that the number of hydrogen atoms, number of (-NH2) group connected with solitary single bond alters the inhibition of HIV-1 reverse transcriptase. Further, presence of electrostatic, hydrophobic and steric field descriptors significantly affects the ability of benzoxazinone derivatives to inhibit HIV-1 reverse transcriptase. The selected descriptors could serve as a primer for the design of novel and potent antagonists of HIV-1 reverse transcriptase.
    Matched MeSH terms: Quantitative Structure-Activity Relationship
  6. Development of a novel mathematical model using a group contribution method for prediction of ionic liquid toxicities
    Ismail Hossain M, Samir BB, El-Harbawi M, Masri AN, Abdul Mutalib MI, Hefter G, et al.
    Chemosphere, 2011 Oct;85(6):990-4.
    PMID: 21794892 DOI: 10.1016/j.chemosphere.2011.06.088
    A new mathematical model has been developed that expresses the toxicities (EC₅₀ values) of a wide variety of ionic liquids (ILs) towards the freshwater flea Daphnia magna by means of a quantitative structure-activity relationship (QSAR). The data were analyzed using summed contributions from the cations, their alkyl substituents and anions. The model employed multiple linear regression analysis with polynomial model using the MATLAB software. The model predicted IL toxicities with R²=0.974 and standard error of estimate of 0.028. This model affords a practical, cost-effective and convenient alternative to experimental ecotoxicological assessment of many ILs.
    Matched MeSH terms: Quantitative Structure-Activity Relationship
  7. Pd(II) complexes with chelating N-(1-alkylpyridin-4(1H)-ylidene)amide (PYA) ligands: Synthesis, characterization and evaluation of anticancer activity
    Zafar MN, Butt AM, Chaudhry GE, Perveen F, Nazar MF, Masood S, et al.
    J Inorg Biochem, 2021 11;224:111590.
    PMID: 34507110 DOI: 10.1016/j.jinorgbio.2021.111590
    The bidentate N-(1-Alkylpyridin-4(1H)-ylidene)amide (PYA) pro-ligands [H2LBn][Cl]2 (2), and [H2LMe][TfO]2 (3) were prepared by simple alkylation reactions of the known compound, N,N-di(pyridin-4-yl)oxalamide (H2L, 1). The Pd(II) complexes, [Pd(LBn)2][Cl]2 (4), [Pd(LMe)2][Cl][TfO] (5), Pd(LBn)Cl2 (6) and Pd(LMe)Cl2 (7) were synthesized through reactions between these pro-ligands and suitable Pd(II) substrates in the presence of base. The molecular structures of 3 and 6 were obtained by single crystal X-ray structure determinations. Studies of the experimental and computational DNA binding interactions of the compounds 1-7 revealed that overall 4 and 6 have the largest values for the binding parameters Kb and ΔGbo. The results showed a good correlation with the steric and electronic parameters obtained by quantitative structure activity relationship (QSAR) studies. In-vitro cytotoxicity studies against four different cell lines showed that the human breast cancer cell lines MCF-7, T47D and cervical cancer cell line HeLa had either higher or similar sensitivities towards 4, 6 and 2, respectively, compared to cisplatin. In general, the cytotoxicity of the compounds, represented by IC50 values, decreased in the order 4 > 6 > 2 > 5 > 3 > 1 > 7 in cancer cell lines. Apoptosis contributed significantly to the cytotoxic effects of these anticancer agents as evaluated by apoptosis studies.
    Matched MeSH terms: Quantitative Structure-Activity Relationship
  8. Exploring the Traditional Chinese Medicine (TCM) database chemical space to target I7L protease from monkeypox virus using molecular screening and simulation approaches
    Khan A, Shahab M, Nasir F, Waheed Y, Alshammari A, Mohammad A, et al.
    SAR QSAR Environ Res, 2023;34(9):689-708.
    PMID: 37675795 DOI: 10.1080/1062936X.2023.2250723
    In the current study, we used molecular screening and simulation approaches to target I7L protease from monkeypox virus (mpox) from the Traditional Chinese Medicines (TCM) database. Using molecular screening, only four hits TCM27763, TCM33057, TCM34450 and TCM31564 demonstrated better pharmacological potential than TTP6171 (control). Binding of these molecules targeted Trp168, Asn171, Arg196, Cys237, Ser240, Trp242, Glu325, Ser326, and Cys328 residues and may affect the function of I7L protease in in vitro assay. Moreover, molecular simulation revealed stable dynamics, tighter structural packing and less flexible behaviour for all the complexes. We further reported that the average hydrogen bonds in TCM27763, TCM33057, TCM34450 and TCM31564I7L complexes remained higher than the control drug. Finally, the BF energy results revealed -62.60 ± 0.65 for the controlI7L complex, for the TCM27763I7L complex -71.92 ± 0.70 kcal/mol, for the TCM33057I7L complex the BF energy was -70.94 ± 0.70 kcal/mol, for the TCM34450I7L the BF energy was -69.94 ± 0.85 kcal/mol while for the TCM31564I7L complex the BF energy was calculated to be -69.16 ± 0.80 kcal/mol. Although, we used stateoftheart computational methods, these are theoretical insights that need further experimental validation.
    Matched MeSH terms: Quantitative Structure-Activity Relationship
  9. Fulltext Antioxidant activity of hispidin oligomers from medicinal fungi: a DFT study
    El Hassane A, Shah SA, Hassan NB, El Moussaoui N, Ahmad R, Zulkefeli M, et al.
    Molecules, 2014;19(3):3489-507.
    PMID: 24662069 DOI: 10.3390/molecules19033489
    Hispidin oligomers are styrylpyrone pigments isolated from the medicinal fungi Inonotus xeranticus and Phellinus linteus. They exhibit diverse biological activities and strong free radical scavenging activity. To rationalize the antioxidant activity of a series of four hispidin oligomers and determine the favored mechanism involved in free radical scavenging, DFT calculations were carried out at the B3P86/6-31+G (d, p) level of theory in gas and solvent. The results showed that bond dissociation enthalpies of OH groups of hispidin oligomers (ArOH) and spin density delocalization of related radicals (ArO•) are the appropriate parameters to clarify the differences between the observed antioxidant activities for the four oligomers. The effect of the number of hydroxyl groups and presence of a catechol moiety conjugated to a double bond on the antioxidant activity were determined. Thermodynamic and kinetic studies showed that the PC-ET mechanism is the main mechanism involved in free radical scavenging. The spin density distribution over phenoxyl radicals allows a better understanding of the hispidin oligomers formation.
    Matched MeSH terms: Quantitative Structure-Activity Relationship
  10. Study of the antimicrobial activity of cyclic cation-based ionic liquids via experimental and group contribution QSAR model
    Ghanem OB, Shah SN, Lévêque JM, Mutalib MIA, El-Harbawi M, Khan AS, et al.
    Chemosphere, 2018 Mar;195:21-28.
    PMID: 29248749 DOI: 10.1016/j.chemosphere.2017.12.018
    Over the past decades, Ionic liquids (ILs) have gained considerable attention from the scientific community in reason of their versatility and performance in many fields. However, they nowadays remain mainly for laboratory scale use. The main barrier hampering their use in a larger scale is their questionable ecological toxicity. This study investigated the effect of hydrophobic and hydrophilic cyclic cation-based ILs against four pathogenic bacteria that infect humans. For that, cations, either of aromatic character (imidazolium or pyridinium) or of non-aromatic nature, (pyrrolidinium or piperidinium), were selected with different alkyl chain lengths and combined with both hydrophilic and hydrophobic anionic moieties. The results clearly demonstrated that introducing of hydrophobic anion namely bis((trifluoromethyl)sulfonyl)amide, [NTF2] and the elongation of the cations substitutions dramatically affect ILs toxicity behaviour. The established toxicity data [50% effective concentration (EC50)] along with similar endpoint collected from previous work against Aeromonas hydrophila were combined to developed quantitative structure-activity relationship (QSAR) model for toxicity prediction. The model was developed and validated in the light of Organization for Economic Co-operation and Development (OECD) guidelines strategy, producing good correlation coefficient R2 of 0.904 and small mean square error (MSE) of 0.095. The reliability of the QSAR model was further determined using k-fold cross validation.
    Matched MeSH terms: Quantitative Structure-Activity Relationship*
  11. Fulltext Docking Based 3D-QSAR Study of Tricyclic Guanidine Analogues of Batzelladine K As Anti-Malarial Agents
    Ahmed N, Anwar S, Thet Htar T
    Front Chem, 2017;5:36.
    PMID: 28664157 DOI: 10.3389/fchem.2017.00036
    The Plasmodium falciparum Lactate Dehydrogenase enzyme (PfLDH) catalyzes inter-conversion of pyruvate to lactate during glycolysis producing the energy required for parasitic growth. The PfLDH has been studied as a potential molecular target for development of anti-malarial agents. In an attempt to find the potent inhibitor of PfLDH, we have used Discovery studio to perform molecular docking in the active binding pocket of PfLDH by CDOCKER, followed by three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of tricyclic guanidine batzelladine compounds, which were previously synthesized in our laboratory. Docking studies showed that there is a very strong correlation between in silico and in vitro results. Based on docking results, a highly predictive 3D-QSAR model was developed with q(2) of 0.516. The model has predicted r(2) of 0.91 showing that predicted IC50 values are in good agreement with experimental IC50 values. The results obtained from this study revealed the developed model can be used to design new anti-malarial compounds based on tricyclic guanidine derivatives and to predict activities of new inhibitors.
    Matched MeSH terms: Quantitative Structure-Activity Relationship
  12. Prediction of Anti-Alzheimer's Activity of Flavonoids Targeting Acetylcholinesterase in silico
    Das S, Laskar MA, Sarker SD, Choudhury MD, Choudhury PR, Mitra A, et al.
    Phytochem Anal, 2017 Jul;28(4):324-331.
    PMID: 28168765 DOI: 10.1002/pca.2679
    INTRODUCTION: Prenylated and pyrano-flavonoids of the genus Artocarpus J. R. Forster & G. Forster are well known for their acetylcholinesterase (AChE) inhibitory, anti-cholinergic, anti-inflammatory, anti-microbial, anti-oxidant, anti-proliferative and tyrosinase inhibitory activities. Some of these compounds have also been shown to be effective against Alzheimer's disease.

    OBJECTIVE: The aim of the in silico study was to establish protocols to predict the most effective flavonoid from prenylated and pyrano-flavonoid classes for AChE inhibition linking to the potential treatment of Alzheimer's disease.

    METHODOLOGY: Three flavonoids isolated from Artocarpus anisophyllus Miq. were selected for the study. With these compounds, Lipinski filter, ADME/Tox screening, molecular docking and quantitative structure-activity relationship (QSAR) were performed in silico. In vitro activity was evaluated by bioactivity staining based on the Ellman's method.

    RESULTS: In the Lipinski filter and ADME/Tox screening, all test compounds produced positive results, but in the target fishing, only one flavonoid could successfully target AChE. Molecular docking was performed on this flavonoid, and this compound gained the score as -13.5762. From the QSAR analysis the IC50 was found to be 1659.59 nM. Again, 100 derivatives were generated from the parent compound and docking was performed. The derivative compound 20 was the best scorer, i.e. -31.6392 and IC50 was predicted as 6.025 nM.

    CONCLUSION: Results indicated that flavonoids could be efficient inhibitors of AChE and thus, could be useful in the management of Alzheimer's disease. Copyright © 2017 John Wiley & Sons, Ltd.

    Matched MeSH terms: Quantitative Structure-Activity Relationship
  13. Discovery of new nanomolar peroxisome proliferator-activated receptor γ activators via elaborate ligand-based modeling
    Al-Najjar BO, Wahab HA, Tengku Muhammad TS, Shu-Chien AC, Ahmad Noruddin NA, Taha MO
    Eur J Med Chem, 2011 Jun;46(6):2513-29.
    PMID: 21482446 DOI: 10.1016/j.ejmech.2011.03.040
    Peroxisome Proliferator-Activated Receptor γ (PPARγ) activators have drawn great recent attention in the clinical management of type 2 diabetes mellitus, prompting several attempts to discover and optimize new PPARγ activators. With this in mind, we explored the pharmacophoric space of PPARγ using seven diverse sets of activators. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of pharmacophoric models and 2D physicochemical descriptors capable of accessing self-consistent and predictive quantitative structure-activity relationship (QSAR) (r2(71)=0.80, F=270.3, r2LOO=0.73, r2PRESS against 17 external test inhibitors=0.67). Three orthogonal pharmacophores emerged in the QSAR equation and were validated by receiver operating characteristic (ROC) curves analysis. The models were then used to screen the national cancer institute (NCI) list of compounds. The highest-ranking hits were tested in vitro. The most potent hits illustrated EC50 values of 15 and 224 nM.
    Matched MeSH terms: Quantitative Structure-Activity Relationship
  14. QSAR study of substituted 1,3,4-oxadiazole naphthyridines as HIV-1 integrase inhibitors
    Ravichandran V, Shalini S, Sundram K, Sokkalingam AD
    Eur J Med Chem, 2010 Jul;45(7):2791-7.
    PMID: 20347187 DOI: 10.1016/j.ejmech.2010.02.062
    A linear quantitative structure activity relationship (QSAR) model is presented for modeling and predicting the inhibition of HIV-1 integrase. The model was produced by using the stepwise multiple linear regression technique on a database that consists of 67 recently discovered 1,3,4-oxadiazole substituted naphthyridine derivatives. The developed QSAR model was evaluated for statistical significance and predictive power. The key conclusion of this study is that valence connectivity index order 1, lowest unoccupied molecular orbital and dielectric energy significantly affect the inhibition of HIV-1 integrase activity by 1,3,4-oxadiazole substituted naphthyridine derivatives. The selected physicochemical descriptors serve as a first guideline for the design of novel and potent antagonists of HIV-1 integrase.
    Matched MeSH terms: Quantitative Structure-Activity Relationship*
  15. TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers
    Cao H, Ng MCK, Jusoh SA, Tai HK, Siu SWI
    J Comput Aided Mol Des, 2017 Sep;31(9):855-865.
    PMID: 28864946 DOI: 10.1007/s10822-017-0047-0
    [Formula: see text]-Helical transmembrane proteins are the most important drug targets in rational drug development. However, solving the experimental structures of these proteins remains difficult, therefore computational methods to accurately and efficiently predict the structures are in great demand. We present an improved structure prediction method TMDIM based on Park et al. (Proteins 57:577-585, 2004) for predicting bitopic transmembrane protein dimers. Three major algorithmic improvements are introduction of the packing type classification, the multiple-condition decoy filtering, and the cluster-based candidate selection. In a test of predicting nine known bitopic dimers, approximately 78% of our predictions achieved a successful fit (RMSD <2.0 Å) and 78% of the cases are better predicted than the two other methods compared. Our method provides an alternative for modeling TM bitopic dimers of unknown structures for further computational studies. TMDIM is freely available on the web at https://cbbio.cis.umac.mo/TMDIM . Website is implemented in PHP, MySQL and Apache, with all major browsers supported.
    Matched MeSH terms: Quantitative Structure-Activity Relationship
  16. Synthesis, anti-diabetic and in silico QSAR analysis of flavone hydrazide Schiff base derivatives
    Jamil W, Shaikh J, Yousuf M, Taha M, Khan KM, Shah SAA
    J Biomol Struct Dyn, 2022;40(23):12723-12738.
    PMID: 34514955 DOI: 10.1080/07391102.2021.1975565
    This study reports synthesis of flavone hydrazide Schiff base derivatives with diverse functionalities for the cure of diabetic mellitus and their a-glucosidase inhibitor and in silico studies. In this regard, Flavone derivatives 1-20 has synthesized and characterized by various spectroscopic techniques. These compounds showed significant potential towards a-glucosidase enzyme inhibition activity and found to be many fold better active than the standard Acarbose (IC50 = 39.45 ± 0.11 µM). The IC50values ranges 1.02-38.1 µM. Among these, compounds 1(IC50 = 4.6 ± 0.23 µM), 2(IC50 = 1.02 ± 0.2 µM), 3(IC50 = 7.1 ± 0.11 µM), 4(IC50 = 8.3 ± 0.34 µM), 5(IC50 = 7.4 ± 0.15 µM), 6(IC50 = 8.5 ± 0.27 µM) and 18 (IC50 = 1.09 ± 0.26 µM) showed highest activity. It was revealed that the analogues having -OH substitution have higher activity than their look likes. The molecular docking analysis revealed that these molecules have high potential to interact with the protein molecule and have high ability to bind with the enzyme. Furthermore, in silico pharmacokinetics, physicochemical studies were also performed for these derivatives. The bioavailability radar analysis explored that of all these compounds have excellent bioavailability for five (5) descriptors, however, the sixth descriptor of instauration is slightly increased in all compounds.Communicated by Ramaswamy H. Sarma.
    Matched MeSH terms: Quantitative Structure-Activity Relationship
  17. Fulltext Ligand-based virtual screening using Bayesian inference network and reweighted fragments
    Ahmed A, Abdo A, Salim N
    ScientificWorldJournal, 2012;2012:410914.
    PMID: 22623895 DOI: 10.1100/2012/410914
    Many of the similarity-based virtual screening approaches assume that molecular fragments that are not related to the biological activity carry the same weight as the important ones. This was the reason that led to the use of Bayesian networks as an alternative to existing tools for similarity-based virtual screening. In our recent work, the retrieval performance of the Bayesian inference network (BIN) was observed to improve significantly when molecular fragments were reweighted using the relevance feedback information. In this paper, a set of active reference structures were used to reweight the fragments in the reference structure. In this approach, higher weights were assigned to those fragments that occur more frequently in the set of active reference structures while others were penalized. Simulated virtual screening experiments with MDL Drug Data Report datasets showed that the proposed approach significantly improved the retrieval effectiveness of ligand-based virtual screening, especially when the active molecules being sought had a high degree of structural heterogeneity.
    Matched MeSH terms: Quantitative Structure-Activity Relationship*
  18. In vitro evaluation and in silico screening of synthetic acetylcholinesterase inhibitors bearing functionalized piperidine pharmacophores
    Brahmachari G, Choo C, Ambure P, Roy K
    Bioorg Med Chem, 2015 Aug 01;23(15):4567-4575.
    PMID: 26105711 DOI: 10.1016/j.bmc.2015.06.005
    A series of densely functionalized piperidine (FP) scaffolds was synthesized following a diastereoselective one-pot multicomponent protocol under eco-friendly conditions. The FPs were evaluated in vitro for their acetylcholinesterase (AChE) inhibitory activity, and in silico studies for all the target compounds were carried out using pharmacophore mapping, molecular docking and quantitative structure-activity relationship (QSAR) analysis in order to understand the structural features required for interaction with the AChE enzyme and the key active site residues involved in the intermolecular interactions. Halogenation, nitration or 3,4-methylenedixoxy-substitution at the phenyl ring attached to the 2- and 6-positions of 1,2,5,6-tetrahydropyridine nucleus in compounds 14-17, 19, 20, 24 and 26 greatly enhanced the AChE inhibitory activity. The docking analysis demonstrated that the inhibitors are well-fitted in the active sites. The in silico studies enlighten the future course of studies in modifying the scaffolds for better therapeutic efficacy against the deadly Alzheimer's disease.
    Matched MeSH terms: Quantitative Structure-Activity Relationship
  19. QSAR and Pharmacophore Mapping Studies on Benzothiazinimines to Relate their Structural Features with anti-HIV Activity
    Geethaavacini G, Poh GP, Yan LY, Deepashini R, Shalini S, Harish R, et al.
    Med Chem, 2018;14(7):733-740.
    PMID: 29807521 DOI: 10.2174/1573406414666180529091618
    BACKGROUND: The development of severe drug resistance caused by the extensive use of anti-HIV agents has resulted in a greatly extensive reduction in these drugs efficacy.

    OBJECTIVES: To identify the important pharmacophoric features and correlate 3D chemical structure of benzothiazinimines with their anti-HIV potential using 2D, 3D-QSAR and pharmacophore modeling studies.

    METHODS: QSAR and pharmacophore mapping studies have been used to relate structural features. 2D QSAR and 3D QSAR studies were performed using partial least square and k-nearest neighbor methodology, coupled with various feature selection methods, viz. stepwise, genetic algorithm, and simulated annealing, to derive QSAR models which were further validated for statistical significance.

    RESULTS: The physicochemical descriptor XAHydrophilicArea and SsOHE-index, and alignmentindependent descriptor T_C_Cl_6 showed significant correlation with the anti-HIV activity of benzothiazinimines in 2D QSAR. 3D QSAR results showed the significant effect of electrostatic and steric field descriptors in the anti-HIV potential of benzothiazinimines. The generated pharmacophore hypothesis demonstrated the importance of aromaticity and hydrogen bond acceptors.

    CONCLUSION: The significant models obtained in this study suggested that these techniques could be used as a guidance for designing new benzothiazinimines with enhanced anti-HIV potential.

    Matched MeSH terms: Quantitative Structure-Activity Relationship
  20. QSAR modeling approaches to identify a novel ACE2 inhibitor that selectively bind with the C and N terminals of the ectodomain
    Jawarkar RD, Zaki MEA, Al-Hussain SA, Al-Mutairi AA, Samad A, Mukerjee N, et al.
    J Biomol Struct Dyn, 2024 Mar;42(5):2550-2569.
    PMID: 37144753 DOI: 10.1080/07391102.2023.2205948
    Due to the high rates of drug development failure and the massive expenses associated with drug discovery, repurposing existing drugs has become more popular. As a result, we have used QSAR modelling on a large and varied dataset of 657 compounds in an effort to discover both explicit and subtle structural features requisite for ACE2 inhibitory activity, with the goal of identifying novel hit molecules. The QSAR modelling yielded a statistically robust QSAR model with high predictivity (R2tr=0.84, R2ex=0.79), previously undisclosed features, and novel mechanistic interpretations. The developed QSAR model predicted the ACE2 inhibitory activity (PIC50) of 1615 ZINC FDA compounds. This led to the detection of a PIC50 of 8.604 M for the hit molecule (ZINC000027990463). The hit molecule's docking score is -9.67 kcal/mol (RMSD 1.4). The hit molecule revealed 25 interactions with the residue ASP40, which defines the N and C termini of the ectodomain of ACE2. The HIT molecule conducted more than thirty contacts with water molecules and exhibited polar interaction with the ARG522 residue coupled with the second chloride ion, which is 10.4 nm away from the zinc ion. Both molecular docking and QSAR produced comparable findings. Moreover, MD simulation and MMGBSA studies verified docking analysis. The MD simulation showed that the hit molecule-ACE2 receptor complex is stable for 400 ns, suggesting that repurposed hit molecule 3 is a viable ACE2 inhibitor.
    Matched MeSH terms: Quantitative Structure-Activity Relationship*
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