Pharmacophore modeling and QSAR analysis of anti-HBV flavonols. by Basireh Baei, Parnia Askari, Fatemeh Sana Askari, Seyed Jalal Kiani, Alireza Mohebbi

“…Screening was performed using the PharmIt server. A QSAR equation was developed and validated with independent sets of compounds. …”
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QSAR modeling of benzoquinone derivatives as 5-lipoxygenase inhibitors by T.K. Shameera Ahamed, Vijisha K. Rajan, K. Muraleedharan

“…Keywords: 5-lipoxygenase, Benzoquinone, 2D-QSAR, 3D-QSAR, Molecular docking…”
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QSAR Study of the Biologically Active Organosulfurs in Natural Products by Fakhr M. Abu-Awwad

“…The biological activities of two sets of a total of 30 different polysulfides were investigated using QSAR. The semiempirical AM1 in Gaussian 2003 for windows was used to optimize the structures whereas a subsequent calculation of hundreds of various types of descriptors at the density functional (B3LYP/6-31G*) using CODESSA package was employed. …”
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Internal validation parameters of linear regression equations in QSAR problem by Inna Khristenko, Volodymyr Ivanov

Subjects: “…quantitative structure-activity relationships (qsar)…”
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Synthesis and QSAR Study of Some HDL Cholesterol Increasing Quinazolinone Derivatives by M. B. Deshmukh, Savita Dhongade (Desai)

“…The alkylated thio quinazolinones were further sequentially condensed with hydrazine hydrate and different aromatic aldehydes to get the hydrazones, which were studied for QSAR. The synthesized compounds were subjected to a prediction of biological activities. …”
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A QSAR Study Based on SVM for the Compound of Hydroxyl Benzoic Esters by Li Wen, Qing Li, Wei Li, Qiao Cai, Yong-Ming Cai

“…To explore the relationship between the molecular structure and antibacterial activity of these compounds and predict the compounds with similar structures, Quantitative Structure-Activity Relationship (QSAR) models of 25 kinds of hydroxyl benzoic esters with the quantum chemical parameters and molecular connectivity indexes are built based on support vector machine (SVM) by using R language. …”
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QSAR modelling and docking analysis of some thiazole analogues as alfa-glucosidase inhibitors by Muhammad Tukur Ibrahim, Adamu Uzairu, Gideon Adamu Shallangwa, Sani Uba

Subjects: “…QSAR…”
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Evaluation of phenylethylamine type entactogens and their metabolites relevant to ecotoxicology – a QSAR study by Takač Milena Jadrijević-Mladar, Magina Joao Daniel Casimiro, Takač Tin

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3D QSAR Studies of DAMNI Analogs as Possible Non-nucleoside Reverse Transcriptase Inhibitors by S. Ganguly, V. Gopalakrishnan

“…Recently, a novel family of NNRTIs commonly referred to as 1-[2-diarylmethoxy] ethyl) 2-methyl-5-nitroimidazoles (DAMNI) derivatives have been discovered. The 3D-QSAR studies on DAMNI derivatives as NNRTIs was performed by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods to determine the factors required for the activity of these compounds. …”
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Combined interaction of fungicides binary mixtures: experimental study and machine learning-driven QSAR modeling by Mohsen Abbod, Ahmad Mohammad

“…The interaction of these mixtures was then analyzed using CA and IA models. QSAR modeling was conducted to assess their fungicidal activity through multiple linear regression (MLR), support vector machine (SVM), and artificial neural network (ANN). …”
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QSAR STUDY OF 2-SUBSTITUTED PHENYL-2-OXO-, 2-HYDROXYL- AND 2-ACYLLOXYETHYLSULFONAMIDES AS FUNGICIDES by Yusuf Isyaku, Adamu Uzairu, Sani Uba

Subjects: “…QSAR 2-substituted Sulfonamides Fungicides…”
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Fluconazole-Like Compounds as Potential Antifungal Agents: QSAR, Molecular Docking, and Molecular Dynamics Simulation by Farnaz Salehi, Leila Emami, Zahra Rezaei, Soghra Khabnadideh, Behnaz Tajik, Razieh Sabet

“…Also, there was a convenient relevance between QSAR and docking results. With the compound F13 which demonstrated the most promising minimum inhibitory concentration (MIC) values, it can be concluded that F13 is appropriate candidate for the development as antifungal agent.…”
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QSAR Studies of 6-Amino Uracil Base Analogues: A Thymidine Phosphorylase Inhibitor in Cancer Therapy by Surya Prakash B. N. Gupta, Neeraj Upmanyu, N. S. Hari Narayana Moorthy, S. Bhattacharya

“…A novel series of 6-amino uracil base analogue were synthesized. QSAR study was used to relate the selective nonsubstrate inhibitory activity of 6-amino uracil base analogue with various physicochemical descriptors. …”
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3D-QSAR and Docking Studies of a Series of β-Carboline Derivatives as Antitumor Agents of PLK1 by Jahan B. Ghasemi, Valentin Davoudian

“…An alignment-free, three dimensional quantitative structure-activity relationship (3D-QSAR) analysis has been performed on a series of β-carboline derivatives as potent antitumor agents toward HepG2 human tumor cell lines. …”
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2D-QSAR Analysis of Oxadiazole Substituted α-Isopropoxy phenylpropionic Acids as PPAR-α & PPAR-λ Agonists by Soni L. K., Gupta A. K., Kaskhedikar S. G.

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AI-enhanced 3D-QSAR screening of fragment-based novel designed molecules targeting Phalaris minor ACCase by Bikash Kumar Rajak, Priyanka Rani, Durg Vijay Singh, Nitesh Singh

“…The selected herbicide-like molecules are further processed through fragment-based design to generate a library of new compounds, refined using binding affinity thresholds (-8.5 kcal/mol) and Quantitative Structure-Activity Relationship (QSAR) models. Finally, molecular dynamics (MD) simulations validated the interaction stability of these potential herbicides over 100 ns, yielding four promising candidates optimized for ACCase inhibition. …”
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QUANTITATIVE STRUCTURE–ACTIVITY RELATIONSHIPS (QSAR) STUDY ON NOVEL 4-AMIDINOQUINOLINE AND 10-AMIDINOBENZONAPHTHYRIDINE DERIVATIVES AS POTENT ANTIMALARIA AGENT by Aliyu Wappah Mahmud, Gideon Adamu Shallangwa, Adamu Uzairu

Subjects: “…QSAR…”
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One size does not fit all: revising traditional paradigms for assessing accuracy of QSAR models used for virtual screening by James Wellnitz, Sankalp Jain, Joshua E. Hochuli, Travis Maxfield, Eugene N. Muratov, Alexander Tropsha, Alexey V. Zakharov

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QSPR/QSAR study of antiviral drugs modeled as multigraphs by using TI’s and MLR method to treat COVID-19 disease by Ugasini Preetha P, M. Suresh, Fikadu Tesgera Tolasa, Ebenezer Bonyah

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Identification of dequalinium as a potent inhibitor of human organic cation transporter 2 by machine learning based QSAR model by Fumihiro Yamane, Kenji Ikemura, Masayoshi Kondo, Manami Ueno, Masahiro Okuda

“…Using our QSAR model, we identified 162 candidate hOCT2 inhibitors among the FDA-approved drugs registered in the DrugBank database. …”
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