MyMedR

Fulltext Antioxidant and Antidiabetic Effects of Flavonoids: A Structure-Activity Relationship Based Study

Sarian MN, Ahmed QU, Mat So'ad SZ, Alhassan AM, Murugesu S, Perumal V, et al.

Biomed Res Int, 2017;2017:8386065.

PMID: 29318154 DOI: 10.1155/2017/8386065

The best described pharmacological property of flavonoids is their capacity to act as potent antioxidant that has been reported to play an important role in the alleviation of diabetes mellitus. Flavonoids biochemical properties are structure dependent; however, they are yet to be thoroughly understood. Hence, the main aim of this work was to investigate the antioxidant and antidiabetic properties of some structurally related flavonoids to identify key positions responsible, their correlation, and the effect of methylation and acetylation on the same properties. Antioxidant potential was evaluated through dot blot, 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging, ABTS+ radical scavenging, ferric reducing antioxidant power (FRAP), and xanthine oxidase inhibitory (XOI) assays. Antidiabetic effect was investigated through α-glucosidase and dipeptidyl peptidase-4 (DPP-4) assays. Results showed that the total number and the configuration of hydroxyl groups played an important role in regulating antioxidant and antidiabetic properties in scavenging DPPH radical, ABTS+ radical, and FRAP assays and improved both α-glucosidase and DPP-4 activities. Presence of C-2-C-3 double bond and C-4 ketonic group are two essential structural features in the bioactivity of flavonoids especially for antidiabetic property. Methylation and acetylation of hydroxyl groups were found to diminish the in vitro antioxidant and antidiabetic properties of the flavonoids.

Matched MeSH terms: Structure-Activity Relationship

Discovery of oxindole-based FLT3 inhibitors as a promising therapeutic lead for acute myeloid leukemia carrying the oncogenic ITD mutation

Bender O, Shoman ME, Ali TFS, Dogan R, Celik I, Mollica A, et al.

Arch Pharm (Weinheim), 2023 Feb;356(2):e2200407.

PMID: 36403191 DOI: 10.1002/ardp.202200407

FMS-like tyrosine kinase 3 (FLT3) mutations occur in approximately 30% of acute myeloid leukemia (AML) patients. In the current study, the oxindole chemotype is employed as a structural motif for the design of new FLT3 inhibitors as potential hits for AML irradiation. Cell-based screening was performed with 18 oxindole derivatives and 5a-c inhibited 68%-73% and 83%-91% of internal tandem duplication (ITD)-mutated MV4-11 cell growth for 48- and 72-h treatments while only 0%-2% and 27%-39% in wild-type THP-1 cells. The most potent compound 5a inhibited MV4-11 cells with IC50 of 4.3 µM at 72 h while it was 8.7 µM in THP-1 cells, thus showing two-fold selective inhibition against the oncogenic ITD mutation. The ability of 5a to modulate cell death was examined. High-throughput protein profiling revealed low levels of the growth factors IGFBP-2 and -4 with the blockage of various apoptotic inhibitors such as Survivin. p21 with cellular stress mechanisms was characterized by increased expression of HSP proteins along with TNF-β. Mechanistically, compounds 5a and 5b inhibited FLT3 kinase with IC50 values of 2.49 and 1.45 µM, respectively. Theoretical docking studies supported the compounds' ability to bind to the FLT3 ATP binding site with the formation of highly stable complexes as evidenced by molecular dynamics simulations. The designed compounds also provide suitable drug candidates with no violation of drug likeability rules.

Matched MeSH terms: Structure-Activity Relationship

Synthesis of new urease enzyme inhibitors as antiulcer drug and computational study

Taha M, Ismail S, Imran S, Almandil NB, Alomari M, Rahim F, et al.

J Biomol Struct Dyn, 2022 Nov;40(18):8232-8247.

PMID: 33860726 DOI: 10.1080/07391102.2021.1910072

In search of potent urease inhibitor indole analogues (1-22) were synthesized and evaluated for their urease inhibitory potential. All analogues (1-22) showed a variable degree of inhibitory interaction potential having IC50 value ranging between 0.60 ± 0.05 to 30.90 ± 0.90 µM when compared with standard thiourea having IC50 value 21.86 ± 0.90 µM. Among the synthesized analogues, the compounds 1, 2, 3, 5, 6, 8, 12, 14, 18, 20 and 22 having IC50 value 3.10 ± 0.10, 1.20 ± 0.10, 4.60 ± 0.10, 0.60 ± 0.05, 5.30 ± 0.20, 2.50 ± 0.10, 7.50 ± 0.20, 3.90 ± 0.10, 3.90 ± 0.10, 2.30 ± 0.05 and 0.90 ± 0.05 µM respectively were found many fold better than the standard thiourea. All other analogues showed better urease interaction inhibition. Structure activity relationship (SAR) has been established for all analogues containing different substituents on the phenyl ring. To understand the binding interaction of most active analogues with enzyme active site docking study were performed.Communicated by Ramaswamy H. Sarma.

Matched MeSH terms: Structure-Activity Relationship

Synthesis, in vitro biological screening and docking study of benzo[d]oxazole bis Schiff base derivatives as a potent anti-Alzheimer agent

Taha M, Rahim F, Zaman K, Anouar EH, Uddin N, Nawaz F, et al.

J Biomol Struct Dyn, 2023 Mar;41(5):1649-1664.

PMID: 34989316 DOI: 10.1080/07391102.2021.2023640

We have synthesized benzo[d]oxazole derivatives (1-21) through a multistep reaction. Alteration in the structure of derivatives was brought in the last step via using various substituted aromatic aldehydes. In search of an anti-Alzheimer agent, all derivatives were evaluated against acetylcholinesterase and butyrylcholinesterase enzyme under positive control of standard drug donepezil (IC50 = 0.016 ± 0.12 and 4.5 ± 0.11 µM) respectively. In case of acetylcholinesterase enzyme inhibition, derivatives 8, 9 and 18 (IC50 = 0.50 ± 0.01, 0.90 ± 0.05 and 0.3 ± 0.05 µM) showed very promising inhibitory potentials. While in case of butyrylcholinesterase enzyme inhibition, most of the derivatives like 6, 8, 9, 13, 15, 18 and 19 (IC50 = 2.70 ± 0.10, 2.60 ± 0.10, 2.20 ± 0.10, 4.25 ± 0.10, 3.30 ± 0.10, 0.96 ± 0.05 and 3.20 ± 0.10 µM) displayed better inhibitory potential than donepezil. Moreover, derivative 18 is the most potent one among the series in both inhibitions. The binding interaction of derivatives with the active gorge of the enzyme was confirmed via a docking study. Furthermore, the binding interaction between derivatives and the active site of enzymes was correlated through the SAR study. Structures of all derivatives were confirmed through spectroscopic techniques such as 1H-NMR, 13C-NMR and HREI-MS, respectively.Communicated by Ramaswamy H. Sarma.

Matched MeSH terms: Structure-Activity Relationship

Molecular modelling and structure-activity relationship of a natural derivative of o-hydroxybenzoate as a potent inhibitor of dual NSP3 and NSP12 of SARS-CoV-2: in silico study

Ayipo YO, Ahmad I, Najib YS, Sheu SK, Patel H, Mordi MN

J Biomol Struct Dyn, 2023 Mar;41(5):1959-1977.

PMID: 35037841 DOI: 10.1080/07391102.2022.2026818

The nsp3 macrodomain and nsp12 (RdRp) enzymes are strongly implicated in the virulent regulation of the host immune response and viral replication of SARS-CoV-2, making them plausible therapeutic targets for mitigating infectivity. Remdesivir remains the only FDA-approved small-molecule inhibitor of the nsp12 in clinical conditions while none has been approved yet for the nsp3 macrodomain. In this study, 69,067 natural compounds from the IBScreen database were screened for efficacious potentials with mechanistic multitarget-directed inhibitory pharmacology against the dual targets using in silico approaches. Standard and extra precision (SP and XP) Maestro glide docking analyses were employed to evaluate their inhibitory interactions against the enzymes. Four compounds, STOCK1N-45901, 03804, 83408, 08377 consistently showed high XP scores against the respective targets and interacted strongly with pharmacologically essential amino acid and RNA residues, in better terms than the standard, co-crystallized inhibitors, GS-441524 and remdesivir. Further assessments through the predictions of ADMET and mutagenicity distinguished STOCK1N-45901, a natural derivative of o-hydroxybenzoate as the most promising candidate. The ligand maintained a good conformational and thermodynamic stability in complex with the enzymes throughout the trajectories of 100 ns molecular dynamics, indicated by RMSD, RMSF and radius of gyration plots. Its binding free energy, MM-GBSA was recorded as -54.24 and -31.77 kcal/mol against the respective enzyme, while its structure-activity relationships confer high probabilities as active antiviral, anti-inflammatory, antiinfection, antitussive and peroxidase inhibitor. The IBScreen database natural product, STOCK1N-45901 (2,3,4,5,6-pentahydroxyhexyl o-hydroxybenzoate) is thus recommended as a potent inhibitor of dual nsp3 and nsp12 of SARS-CoV-2 for further study. Communicated by Ramaswamy H. Sarma.

Matched MeSH terms: Structure-Activity Relationship

Pectin-interactions and the digestive stability of anthocyanins in thermal and non-thermal processed strawberry pulp

Xing Y, Wang K, Zhang M, Law CL, Lei H, Wang J, et al.

Food Chem, 2023 Oct 30;424:136456.

PMID: 37267648 DOI: 10.1016/j.foodchem.2023.136456

This study investigated the digestive stability of anthocyanins (ACNs) and their interaction with three pectin fractions-water-soluble pectin (WSP), cyclohexanetrans-1,2-diamine tetra-acetic acid-soluble pectin (CSP), and sodium carbonate-soluble pectin (NSP)-in strawberry pulp processed by pasteurization (PS), ultrasound (US), electron beam (EB) irradiation, and high pressure (HP). Compared with the control group, the ACNs content increased to the highest level (312.89 mg/mL), but the retention rate of ACNs in the simulated intestine decreased significantly after US treatment. The monosaccharide compositions indicated that the WSP and CSP possessed more homogalacturonan (HG) domains than the NSP, which contains more rhamngalacturonan-I (RG-I) domains. The microstructure of US-treated pectin was damaged and fragmented. Comprehensive analysis showed that the retention rate of ACNs was closely related to the pectin structure, primarily reflected by the degree of linearity and the integrity of structure. These results revealed the structure-activity relationship between ACNs and pectin during pulp processing.

Matched MeSH terms: Structure-Activity Relationship

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

Utilizing machine learning techniques to predict the blood-brain barrier permeability of compounds detected using LCQTOF-MS in Malaysian Kelulut honey

Edros R, Feng TW, Dong RH

SAR QSAR Environ Res, 2023;34(6):475-500.

PMID: 37409842 DOI: 10.1080/1062936X.2023.2230868

Current in silico modelling techniques, such as molecular dynamics, typically focus on compounds with the highest concentration from chromatographic analyses for bioactivity screening. Consequently, they reduce the need for labour-intensive in vitro studies but limit the utilization of extensive chromatographic data and molecular diversity for compound classification. Compound permeability across the blood-brain barrier (BBB) is a key concern in central nervous system (CNS) drug development, and this limitation can be addressed by applying cheminformatics with codeless machine learning (ML). Among the four models developed in this study, the Random Forest (RF) algorithm with the most robust performance in both internal and external validation was selected for model construction, with an accuracy (ACC) of 87.5% and 86.9% and area under the curve (AUC) of 0.907 and 0.726, respectively. The RF model was deployed to classify 285 compounds detected using liquid chromatography quadrupole time-of-flight mass spectrometry (LCQTOF-MS) in Kelulut honey; of which, 140 compounds were screened with 94 descriptors. Seventeen compounds were predicted to permeate the BBB, revealing their potential as drugs for treating neurodegenerative diseases. Our results highlight the importance of employing ML pattern recognition to identify compounds with neuroprotective potential from the entire pool of chromatographic data.

Matched MeSH terms: Quantitative Structure-Activity Relationship

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

Insight into the Structure and Physicochemical Properties of Potent Chemokine Receptor 5 Inhibitors for the Discovery of Novel Alzheimer's Disease Drugs

Mohamed Yusof NIS, Awaluddin NA, Fauzi FM

Cent Nerv Syst Agents Med Chem, 2023;23(2):95-108.

PMID: 37496242 DOI: 10.2174/1871524923666230726102846

BACKGROUND: In Alzheimer's Disease (AD), chemokines recruit pro-inflammatory mediators and increase the aggregation of both Aβ (amyloid-β) plaque and neurofibrillary tangles (NFTs). Chemokine receptor 5 (CCR5) has been demonstrated to be involved in neuroinflammation and neuroimmunology, where its inhibition was shown to enhance memory, plasticity and learning.

OBJECTIVE: In this study, compounds that inhibit CCR5 obtained from the ChEMBL database were analysed, specifically for whether specific substructures and physicochemical properties are correlated to biological activity.

METHODS: Clustering was first performed to group 1,237 compounds into 10 clusters based on the similarities of their structure. Then, molecular docking was performed on 10 compounds representative of each cluster. Lastly, the Spearman correlation was computed between physicochemical properties and biological activity.

RESULTS: Results showed that potent CCR5 inhibitors tend to: (i) be larger in size (molecular weight of more than 500 g/mol), (ii) bind at the deep hydrophobic pocket, mostly through π-π stacking and (iii) have more than 1 aromatic ring. The larger size may aid in reaching the deep hydrophobic pocket. However, these requirements may lead to the violation of more than 1 Lipinski's Rule of 5.

CONCLUSION: Future studies should include analyses of the analogues or derivatives of the representative compounds to further expand on the findings here and establish the structure-activity relationship for CCR5 inhibition. This would aid in the development of new AD drugs since drug discovery and development of AD drugs are suffering from high attrition.

Matched MeSH terms: Structure-Activity Relationship

Synthesis, biological evaluation, and molecular modelling of novel quinoxaline-isoxazole hybrid as anti-hyperglycemic

Phongphane L, Mohd Radzuan SN, Abu Bakar MH, Che Omar MT, Supratman U, Harneti D, et al.

Comput Biol Chem, 2023 Oct;106:107938.

PMID: 37542847 DOI: 10.1016/j.compbiolchem.2023.107938

In our effort to develop potent anti-hyperglycemic compounds with inhibitory activity against α-amylase and α-glucosidase, a series of novel quinoxaline-isoxazole moieties were synthesized. The novel quinoxaline-isoxazole derivatives were assessed in vitro for their anti-hyperglycemic activities on α-amylase and α-glucosidase inhibitions. The results revealed promising IC50 values compared to acarbose as a positive control for α-amylase and α-glucosidase. Among them, N-Ethyl-7-chloro-3-((3-phenylisoxazol-5-yl)methoxy)quinoxalin-2-amine 5b showed dual inhibitory with IC50 of 24.0 µM for α-amylase and 41.7 µM for α-glucosidase. In addition, N-Ethyl-7-methoxy-3-((3-(2-chlorophenyl)isoxazol-5-yl)methoxy)quinoxalin-2-amine 5j also had dual bioactivities against α-amylase and α-glucosidase with IC50 of 17.0 and 40.1 µM, respectively. Nevertheless, two more compounds N-Ethyl-7-cyano-3-((3-phenylisoxazol-5-yl)methoxy)quinoxaline-2-amine 5e showed strong mono-inhibition for α-glucosidase with IC50 of 16.6 µM followed by N-Ethyl-7-methoxy-3-((3-phenylisoxazol-5-yl)methoxy)quinoxalin-2-amine 5 f with IC50 of 18.6 µM. The molecular docking study for α-glucosidase inhibitor provided the binding energy ranging from 8.3 to 9.1 kcal/mol and α-amylase inhibitor showed the binding energy score at 8.4 and 8.5 kcal/mol. The dual inhibitions nature of 5b and 5j were further analyzed and confirmed via molecular dynamics including the stability of the compound, interaction energy, binding free energy, and the interaction residue analysis using the MM-GBSA approach. The results showed that compound 5j was the most potent compound. Lastly, the drug-likeness properties were also evaluated with all synthesized compounds 5a-5j and the results reveal that all potent compounds meet Lipinski's rules of five.

Matched MeSH terms: Structure-Activity Relationship

Fulltext Shaping the future of antiviral Treatment: Spotlight on Nucleobase-Containing drugs and their revolutionary impact

Wong XK, Ng CS, Yeong KY

Bioorg Chem, 2024 Mar;144:107150.

PMID: 38309002 DOI: 10.1016/j.bioorg.2024.107150

Nucleobases serve as essential molecular frameworks present in both natural and synthetic compounds that exhibit notable antiviral activity. Through molecular modifications, novel nucleobase-containing drugs (NCDs) have been developed, exhibiting enhanced antiviral activity against a wide range of viruses, including the recently emerged SARS‑CoV‑2. This article provides a detailed examination of the significant advancements in NCDs from 2015 till current, encompassing various aspects concerning their mechanisms of action, pharmacology and antiviral properties. Additionally, the article discusses antiviral prodrugs relevant to the scope of this review. It fills in the knowledge gap by examining the structure-activity relationship and trend of NCDs as therapeutics against a diverse range of viral diseases, either as approved drugs, clinical candidates or as early-stage development prospects. Moreover, the article highlights on the status of this field of study and addresses the prevailing limitations encountered.

Matched MeSH terms: Structure-Activity Relationship

Synthesis, biological evaluation and molecular modeling studies of modulated benzyloxychalcones as potential acetylcholinesterase inhibitors

Abdalla Ali A, Mhamad SA, Hasan AH, Ahmad I, Abdullah SA, Jamil S, et al.

J Biomol Struct Dyn, 2024 Apr;42(7):3604-3615.

PMID: 37293930 DOI: 10.1080/07391102.2023.2220032

Acetylcholinesterase inhibitors (AChEIs) have become a significant target in the search for an efficient treatment of Alzheimer's disease. Chalcone-based compounds display a strong potency to hinder AChE. So, this study focused on the synthesis of a series of new chalcone derivatives with anti-cholinesterase potential and their structures were characterized based on spectroscopic methods including IR, 1H NMR, 13C NMR and HRMS. Chalcone derivatives were screened against AChE. Most of them exhibited potent inhibitory activity against AChE. Compound 11i showed the most potent activity toward acetylcholinesterase compared to the positive compound, Galantamine. Docking studies into the active site of the acetylcholinesterase enzyme ravealed the significant docking score of the synthesized compounds with docking score of -7.959 to -9.277 kcal/mol when compared to the co-crystallized ligand, Donepezil (-10.567 kcal/mol). The interaction's stability was further assessed using a conventional atomistic 100 ns dynamics simulation study, which revealed the conformational stability of representative compound 11i in the cavity of the acetylcholinesterase enzyme.Communicated by Ramaswamy H. Sarma.

Matched MeSH terms: Structure-Activity Relationship

Recent advances and structure-activity relationship studies of DPP-4 inhibitors as anti-diabetic agents

Singhal S, Manikrao Patil V, Verma S, Masand N

Bioorg Chem, 2024 May;146:107277.

PMID: 38493634 DOI: 10.1016/j.bioorg.2024.107277

Diabetes mellitus (DM) is one of the largest public health problems worldwide and in the last decades various therapeutic targets have been investigated. For the treatment of type-2 DM (T2DM), dipeptidyl peptidase-4 (DPP-4) is one of the well reported target and has established safety in terms of cardiovascular complexicity. Preclinical and clinical studies using DPP-4 inhibitors have demonstrated its safety and effectiveness and have lesser risk of associated hypoglycaemic effect making it suitable for elderly patients. FDA has approved a number of structurally diverse DPP-4 inhibitors for clinical use. The present manuscript aims to focus on the well reported hybrid and non-hybrid analogues and their structural activity relationship (SAR) studies. It aims to provide structural insights for this class of compounds pertaining to favourable applicability of selective DPP-4 inhibitors in the treatment of T2DM.

Matched MeSH terms: Structure-Activity Relationship

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*

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*

A new adaptive L1-norm for optimal descriptor selection of high-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives

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*

A QSAR model for predicting antidiabetic activity of dipeptidyl peptidase-IV inhibitors by enhanced binary gravitational search algorithm

Al-Fakih AM, Algamal ZY, Lee MH, Aziz M, Ali HTM

SAR QSAR Environ Res, 2019 Jun;30(6):403-416.

PMID: 31122062 DOI: 10.1080/1062936X.2019.1607899

Time-varying binary gravitational search algorithm (TVBGSA) is proposed for predicting antidiabetic activity of 134 dipeptidyl peptidase-IV (DPP-IV) inhibitors. To improve the performance of the binary gravitational search algorithm (BGSA) method, we propose a dynamic time-varying transfer function. A new control parameter,
μ
, is added in the original transfer function as a time-varying variable. The TVBGSA-based model was internally and externally validated based on

Q

int

2

,

Q

L
G
O

2

,

Q

B
o
o
t

2

,

M
S

E

t
r
a
i
n

,

Q

e
x
t

2

,

M
S

E

t
e
s
t

, Y-randomization test, and applicability domain evaluation. The validation results indicate that the proposed TVBGSA model is robust and not due to chance correlation. The descriptor selection and prediction performance of TVBGSA outperform BGSA method. TVBGSA shows higher

Q

int

2

of 0.957,

Q

L
G
O

2

of 0.951,

Q

B
o
o
t

2

of 0.954,

Q

e
x
t

2

of 0.938, and lower

M
S

E

t
r
a
i
n

and

M
S

E

t
e
s
t

compared to obtained results by BGSA, indicating the best prediction performance of the proposed TVBGSA model. The results clearly reveal that the proposed TVBGSA method is useful for constructing reliable and robust QSARs for predicting antidiabetic activity of DPP-IV inhibitors prior to designing and experimental synthesizing of new DPP-IV inhibitors.

Matched MeSH terms: Quantitative Structure-Activity Relationship*

QSAR classification model for diverse series of antifungal agents based on improved binary differential search algorithm

Al-Fakih AM, Algamal ZY, Lee MH, Aziz M, Ali HTM

SAR QSAR Environ Res, 2019 Feb;30(2):131-143.

PMID: 30734580 DOI: 10.1080/1062936X.2019.1568298

An improved binary differential search (improved BDS) algorithm is proposed for QSAR classification of diverse series of antimicrobial compounds against Candida albicans inhibitors. The transfer functions is the most important component of the BDS algorithm, and converts continuous values of the donor into discrete values. In this paper, the eight types of transfer functions are investigated to verify their efficiency in improving BDS algorithm performance in QSAR classification. The performance was evaluated using three metrics: classification accuracy (CA), geometric mean of sensitivity and specificity (G-mean), and area under the curve. The Kruskal-Wallis test was also applied to show the statistical differences between the functions. Two functions, S1 and V4, show the best classification achievement, with a slightly better performance of V4 than S1. The V4 function takes the lowest iterations and selects the fewest descriptors. In addition, the V4 function yields the best CA and G-mean of 98.07% and 0.977%, respectively. The results prove that the V4 transfer function significantly improves the performance of the original BDS.

Matched MeSH terms: Quantitative Structure-Activity Relationship*

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*

Displaying publications 41 - 60 of 550 in total