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Journal articles on the topic '3D-QSAR model'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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1

Terzioglu, Nalan, and Hans-Dieter Höltje. "Receptor-Based 3D QSAR Analysis of Serotonin 5-HT1D Receptor Agonists." Collection of Czechoslovak Chemical Communications 70, no. 9 (2005): 1482–92. http://dx.doi.org/10.1135/cccc20051482.

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A three-dimensional quantitative structure-activity relationship study (3D QSAR) has been successfully applied to explain the binding affinities for the serotonin 5-HT1D receptor of a triptan series. The paper describes the development of a receptor-based 3D QSAR model of some known agonists and recently developed triptans on the 5-HT1D serotonergic receptor, showing a significant correlation between predicted and experimentally measured binding affinity (pIC50). The pIC50 values of these agonists are in the range from 5.40 to 9.50. The ligand alignment obtained from dynamic simulations was ta

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Zhao, Manman, Lin Wang, Linfeng Zheng, et al. "2D-QSAR and 3D-QSAR Analyses for EGFR Inhibitors." BioMed Research International 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/4649191.

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Epidermal growth factor receptor (EGFR) is an important target for cancer therapy. In this study, EGFR inhibitors were investigated to build a two-dimensional quantitative structure-activity relationship (2D-QSAR) model and a three-dimensional quantitative structure-activity relationship (3D-QSAR) model. In the 2D-QSAR model, the support vector machine (SVM) classifier combined with the feature selection method was applied to predict whether a compound was an EGFR inhibitor. As a result, the prediction accuracy of the 2D-QSAR model was 98.99% by using tenfold cross-validation test and 97.67% b

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Jagdale, Deepali M., and Ramaa C. S. "QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP ANALYSIS OF NOVEL PYRAZOLINE DERIVATIVES USING K NEAREST NEIGHBOUR MOLECULAR FIELD ANALYSIS METHOD." International Journal of Pharmacy and Pharmaceutical Sciences 9, no. 12 (2017): 87. http://dx.doi.org/10.22159/ijpps.2017v9i12.19401.

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Objective: Malonyl CoA decarboxylase (MCD) enzyme plays important role in fatty acid and glucose oxidation. Inhibition of MCD might turn to a novel approach to treat ischemia. The main objective of this research article was to develop a novel pharmacophore for enhanced activity.Methods: Three-dimensional quantitative structure-activity relationships (3D-QSAR) was performed for pyrazoline derivatives as MCD inhibitors using VLife MDS 4.6 software. The QSAR model was developed using the stepwise 3D-QSAR kNN-MFA method.Results: The statistical results generated from kNN-MFA method indicated the s

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4

Asgaonkar, K. D., S. M. Patil, T. S. Chitre, S. D. Wani, and M. T. Singh. "QSAR tool for optimization of nitrobenzamide pharmacophore for antitubercular activity." Bulletin of the Karaganda University. "Chemistry" series 105, no. 1 (2022): 60–68. http://dx.doi.org/10.31489/2022ch1/60-68.

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Tuberculosis (TB) is a leading cause of death worldwide from a single infectious agent, Mycobacterium tuberculosis (MTB), especially due to the development of resistant strains and its co-infections in HIV. Quantitative-structure activity relationship (QSAR) studies aid rapid drug discovery. In this work, 2D and 3D QSAR studies were carried out on a series of nitrobenzamide derivatives to design newer analogues for antitubercular activity. 2D QSAR was performed using MLR on a data set showing antitubercular activity. The 3D-QSAR studies were performed by kNN–MFA using simulated annealing varia

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5

Mishra, Puja, Sumit Nandi, Ankit Chatterjee, et al. "Development of 2D and 3D QSAR models of pyrazole derivatives as acetylcholine esterase inhibitors." Journal of the Serbian Chemical Society, no. 00 (2024): 39. http://dx.doi.org/10.2298/jsc230221039m.

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The drugs that are most useful in all stages of Alzheimer?s disease (AD) are acetylcholinesterase (AChE) inhibitors. The objectives of this work are to generate various QSAR models and to select robust predictive models from corresponding models. Studies were then focused on finding a range of pyrazole-like AChE inhibitors by 2D and 3D QSAR analysis. Genetic algorithm-based multiple linear regression (GA-MLR) provided the statistically robust 2D-QSAR model that depicted the significance of molecular volume and number of multiple bonds along with the presence/absence of specific atom-centred fr

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B.V.S, Suneel Kumar, Jagarlapudi A. R. P. Sarma, and Lakshmi Narasu. "3D-QSAR studies on Pyrido[2,3-d]pyrimidine Derivatives as Fibroblast Growth Factor Receptor 1 Inhibitors: Application of Molecular Field Analysis (MFA)." International Journal of Drug Design and Discovery 2, no. 4 (2024): 619–32. https://doi.org/10.37285/ijddd.2.4.2.

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Three-dimensional quantitative structure–activity relationship (3D-QSAR) models were developed for 77 pyrido[2,3-d]pyrimidines derivatives, inhibiting fibroblast growth factor receptor 1 (FGFR1). The QSAR model was developed using 56 compounds and its predictive ability was assessed using a test set of 21 compounds. The predictive 3D-QSAR models have conventional r2 values of 0.920 for MFA and the cross-validated coefficient r2cv values of 0.884 for MFA. The results of 3D-QSAR methodologies provide a powerful tool directed to the design of potent and selective pyrido[2,3-d]pyrimidines inhibito

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Ren, Ji-Xia, Rui-Tao Zhang, and Hui Zhang. "Identifying Novel ATX Inhibitors via Combinatory Virtual Screening Using Crystallography-Derived Pharmacophore Modelling, Docking Study, and QSAR Analysis." Molecules 25, no. 5 (2020): 1107. http://dx.doi.org/10.3390/molecules25051107.

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Autotaxin (ATX) is considered as an interesting drug target for the therapy of several diseases. The goal of the research was to detect new ATX inhibitors which have novel scaffolds by using virtual screening. First, based on two diverse receptor-ligand complexes, 14 pharmacophore models were developed, and the 14 models were verified through a big test database. Those pharmacophore models were utilized to accomplish virtual screening. Next, for the purpose of predicting the probable binding poses of compounds and then carrying out further virtual screening, docking-based virtual screening was

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Chhajed, Priyanka N., and Ravindra B. Patil. "Exploring 3D QSAR Study of Pyridone-Pyrimidone Derivatives as Glucokinase Activators in Treatment of Diabetes Mellitus by using CoMFA Method." Asian Journal of Organic & Medicinal Chemistry 7, no. 1 (2022): 42–54. http://dx.doi.org/10.14233/ajomc.2022.ajomc-p360.

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In this work, we have performed 3D QSAR study of reported pyridone-pyrimidone derivatives. CoMFA was applied to generate 3D QSAR models. Total eight QSAR models were generated. Model 2 was close to standard set criteria. Effect of steric and electrostatic substituents on biological activity was observed on contour maps. This study will be helpful for future researchers in designing new pyridinepyrimidone derivatives.

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Vaddavalli, Radha, Bagyanaryana Gaddam, and Pradeep Kumar Maddikara. "Discovery of Novel Inhibitors Against Resistant Streptococcus pneumoniae MurF Enzyme using Phamracophore Modeling and QSAR Analysis." International Journal of Drug Design and Discovery 2, no. 1 (2024): 403–12. https://doi.org/10.37285/ijddd.2.1.7.

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Main aim of the current study was to discover novel inhibitors against Streptococcus pneumoniae MurF enzyme using analogue based drug design. Pharmacophore mapping and 3D-QSAR analysis was performed on some previously synthesized and evaluated sulfonamide derivatives which are known to be potent inhibitors of penicillin resistant Streptococcus pneumoniae MurF receptor. 3D-QSAR study based on the principle of alignment of pharmacophoric features was performed on the same set of inhibitors using the PHASE module of Schrodinger suite. A five point pharmacophore, ADHRR, with one hydrogen bond acce

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Zhang, Jiaming, Qinqin Liu, Haoxia Zhao, Guiyu Li, Yunpeng Yi, and Ruofeng Shang. "Design and Synthesis of Pleuromutilin Derivatives as Antibacterial Agents Using Quantitative Structure–Activity Relationship Model." International Journal of Molecular Sciences 25, no. 4 (2024): 2256. http://dx.doi.org/10.3390/ijms25042256.

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The quantitative structure–activity relationship (QSAR) is one of the most popular methods for the virtual screening of new drug leads and optimization. Herein, we collected a dataset of 955 MIC values of pleuromutilin derivatives to construct a 2D-QSAR model with an accuracy of 80% and a 3D-QSAR model with a non-cross-validated correlation coefficient (r2) of 0.9836 and a cross-validated correlation coefficient (q2) of 0.7986. Based on the obtained QSAR models, we designed and synthesized pleuromutilin compounds 1 and 2 with thiol-functionalized side chains. Compound 1 displayed the highest a

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11

Polański, J. "Self-organizing neural network for modeling 3D QSAR of colchicinoids." Acta Biochimica Polonica 47, no. 1 (2000): 37–45. http://dx.doi.org/10.18388/abp.2000_4060.

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A novel scheme for modeling 3D QSAR has been developed. A method involving multiple self-organizing neural network adjusted to be analyzed by the PLS (partial least squares) analysis was used to model 3D QSAR of the selected colchicinoids. The model obtained allows the identification of some structural determinants of the biological activity of compounds.

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Amin, Sk Abdul, Nilanjan Adhikari, Tarun Jha, and Shovanlal Gayen. "Exploring structural requirements of unconventional Knoevenagel-type indole derivatives as anticancer agents through comparative QSAR modeling approaches." Canadian Journal of Chemistry 94, no. 7 (2016): 637–44. http://dx.doi.org/10.1139/cjc-2016-0050.

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An indole ring system is considered as a versatile scaffold in the pharmaceutical field. In this article, comparative QSAR modeling (2D-QSAR, 3D-QSAR; kNN-MFA and CoMSIA) was performed on some Knoevenagel-type cytotoxic indole derivatives to understand the structural requirements for the cytotoxic property of these compounds. The 2D-QSAR model was statistically significant and imparted high predictive ability (nTrain = 30; R = 0.917; [Formula: see text] = 0.801; [Formula: see text] = 0.757; Q2 = 0.722; nTest = 9; [Formula: see text] = 0.799). A statistically significant 3D-QSAR kNN-MFA model (

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13

L. Sawant, Ramesh, Ganesh D Jadhav, Prashant D. Lanke, and Jyoti B. Wadekar. "QSAR and Docking Study for Rate of Mushroom Tyrosinase Inhibition by Some 5-Benzylidene Barbiturate Derivatives." International Journal of Drug Design and Discovery 4, no. 2 (2025): 1077–82. https://doi.org/10.37285/ijddd.4.2.6.

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The 3D QSAR study was employed to establish correlation between structural properties of 5-benzylidene barbiturate derivatives and rate of enzyme tyrosinase inhibition. The multiple linear regression (MLR) methods were used to derive QSAR models. Best QSAR model was selected on the basis of various statistical parameters like square correlation coefficient (r2 = 0.9180), cross validated square correlation coefficient (q2 =0.6769), standard error of estimation (SE) and sequential Fischer test (F). The 3D QSAR model reveals that the steric and electronic parameters are governing rate of inhibiti

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Desai, Sujit, Sachin Gadkari, Prafulla Choudhari, and Manish Bhatia. "3D QSAR, Pharmacophore Identification of 2-Methoxy Benzanilides and their Thioxo Analogues as Antimycobacterials." International Journal of Drug Design and Discovery 4, no. 3 (2025): 1153–57. https://doi.org/10.37285/ijddd.4.3.6.

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The three dimensional quantitative structure–activity relationship (3D-QSAR) and pharmacophore identification studies on 52 substituted 2- methoxy benzanilides and thioxo derivatives as antimycobacterials agents have been carried out. Multiple linear regressions (MLR) method was applied for QSAR model development considering training and test set approaches with various feature selection methods. Stepwise MLR method was applied to derive QSAR models which were further validated for statistical significance and predictive ability by internal and external validation. The results of pharmacophore

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15

Oh, Youri, Hoyong Jung, Hyejin Kim, et al. "Design and Synthesis of a Novel PLK1 Inhibitor Scaffold Using a Hybridized 3D-QSAR Model." International Journal of Molecular Sciences 22, no. 8 (2021): 3865. http://dx.doi.org/10.3390/ijms22083865.

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Polo-like kinase 1 (PLK1) plays an important role in cell cycle progression and proliferation in cancer cells. PLK1 also contributes to anticancer drug resistance and is a valuable target in anticancer therapeutics. To identify additional effective PLK1 inhibitors, we performed QSAR studies of two series of known PLK1 inhibitors and proposed a new structure based on a hybridized 3D-QSAR model. Given the hybridized 3D-QSAR models, we designed and synthesized 4-benzyloxy-1-(2-arylaminopyridin-4-yl)-1H-pyrazole-3-carboxamides, and we inspected its inhibitory activities to identify novel PLK1 inhi

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Sharma, M. C., and D. V. Kohli. "THREE-DIMENSIONAL QSAR MODELING BENZIMIDAZOLE ANALOGUES USING THE K-NEAREST NEIGHBOR METHOD." INDIAN DRUGS 56, no. 12 (2019): 62–67. http://dx.doi.org/10.53879/id.56.12.11234.

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We undertook the three-dimensional (3D) QSAR studies of a series of benzimidazole analogues to elucidate the structural properties required for angiotensin II. The 3D-QSAR studies were performed using the stepwise, simulated annealing (SA) and genetic algorithm (GA) selection k-nearest neighbor molecular field analysis approach; a leave-one-out cross-validated correlation coefficient q2 = 0.8216 and a pred_r2 = 0.7852 were obtained. The 3D QSAR model is expected to provide a good alternative to predict the biological activity prior to synthesis as antihypertensive agents.

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Sharma, M. C., and D. V. Kohli. "DEVELOPMENT OF A ROBUST QSAR MODEL OF ANGIOTENSIN RECEPTOR REVEALS A K NEAREST NEIGHBOR APPLICABLE TO DIVERSE SCAFFOLDS." INDIAN DRUGS 54, no. 06 (2017): 30–36. http://dx.doi.org/10.53879/id.54.06.10947.

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Quantitative structure–activity relationship (QSAR) studies were performed on quinazolinone analogues for prediction of antihypertensive activity. The best significant 2D-QSAR model having r2 = 0.8118 and pred_r2 = 0.7428 was developed by stepwise-partial least square method. k-nearest neighbor molecular field analysis was used to construct the best 3D-QSAR model, showing good correlative and predictive capabilities in terms of q2 = 0.7388 and pred_r2 = 0.6983. Results reveal that the 2D-QSAR studies signify positive contribution of SssOE index and SsCH3 count towards the biological activity.

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Pandit, Bibhas, Yogesh Vaishnav, Sanjib Bahadur, and Trilochan Satapathy. "2D & 3D-QSAR Studies on a Series of Quinoline-Amino-piperidine Derivatives as Potent Mycobacterium DNA-Gyrase-B Inhibitors." International Journal of Pharmaceutical Sciences and Nanotechnology(IJPSN) 16, no. 3 (2023): 6512–21. http://dx.doi.org/10.37285/ijpsn.2023.16.3.5.

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Introduction: Mycobacterium tuberculosis is a familiar infectious bacillus that causes tuberculosis, which primarily affects the lungs and the spinal cord. To combat the growing difficulties in treating MTB, it is necessary to create safe medications with novel mechanisms of action. Objective: To design and develop some novel quinolone-amino piperidine derivatives with potent mycobacterium DNAgyraseB inhibitory using the QSAR technique. Methods: Multiple linear regression (MLR), partial least squares (PLS), and k-nearest neighbour molecular field analysis ((kNN-MFA) were utilised i

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Radhika, V., S. Sree Kanth, and M. Vijjulatha. "CoMFA and CoMSIA Studies on Inhibitors of HIV-1 Integrase - Bicyclic Pyrimidinones." E-Journal of Chemistry 7, s1 (2010): S75—S84. http://dx.doi.org/10.1155/2010/717865.

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To understand the structural requirements of HIV-1 integrase inhibitors and to design new ligands against human HIV-1 integrase with enhanced inhibitory potency, a 3D QSAR (quantitative structure-activity relationship) study with comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) for a dataset of 35 bicyclic pyrimidinones which are inhibitors of human HIV-1 integrase was performed. QSAR models were computed with Sybyl. The 3D QSAR model showed very good statistical result, namely q2, r2and r2predvalues were high for both CoMFA and CoMSIA

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Dutkiewicz, Zbigniew, and Renata Mikstacka. "Molecular Docking Study and 3D-QSAR Model for Trans-Stilbene Derivatives as Ligands of CYP1B1." International Journal of Molecular Sciences 26, no. 3 (2025): 1002. https://doi.org/10.3390/ijms26031002.

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Scientific research on stilbenes is conducted for their chemopreventive and therapeutic properties. In experimental studies, natural and synthetic trans-stilbenes exhibit antioxidant, anti-inflammatory, cardioprotective, and anticancer effects. The antitumor activity of some natural and synthetic stilbenes is associated with their interaction with cytochrome P450 family 1, which leads to the inhibition of procarcinogen activation. In the present study, three-dimensional quantitative structure–activity relationship analysis (3D-QSAR) was performed on a series of forty-one trans-stilbene derivat

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Nakka, Srinivas, and Lalitha Guruprasad. "Structural Insights into the Active Site of Human Sodium Dependent Glucose Co-Transporter 2: Homology Modelling, Molecular Docking, and 3D - QSAR Studies." Australian Journal of Chemistry 65, no. 9 (2012): 1314. http://dx.doi.org/10.1071/ch12051.

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Human sodium dependent glucose co-transporter 2 (hSGLT2) is a target for diabetes mellitus type 2 (T2DM). The 3D (three dimensional) homology model of hSGLT2 comprising 14 transmembrane helical domains was constructed and molecular docking of the inhibitors, C-aryl glucoside analogues, into the active site was studied. The 3D-QSAR (quantitative structure activity relationship) analysis was carried out on 43 C-aryl glucoside analogues as a training set. The molecular field analysis (MFA) with G/PLS (genetic partial least-squares) method was used to generate statistically significant 3D-QSAR (r2

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Tong, Jian-Bo, Feng Yi, Ding Luo, and Tian-Hao Wang. "QSAR Studies of Sulfonamide Hydroxamates Derivatives as MMP-2 Inhibitors Topomer CoMFA and Molecular Docking." Letters in Drug Design & Discovery 17, no. 11 (2020): 1364–71. http://dx.doi.org/10.2174/1570180817999200630124920.

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Background: In recent years, cancer has become the main cause of death and it is a serious threat to human health, so the development of new, selective and safe anticancer drugs is still the focus of medical research. Matrix metalloproteinases-2 (MMP-2) has been determined to play an important role in the regulation of tumor angiogenesis, which is closely related to the development of the tumor. Therefore, MMP-2 is considered as a promising target for tumor therapy. In this study, Tomper comparative molecular field analysis (Topomer CoMFA) and molecular docking were used to investigate the imp

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Edache, Emmanuel Israel, Adamu Uzairu, Paul Andrew Mamza, and Gideon Adamu Shallangwa. "A comparative QSAR analysis, 3D-QSAR, molecular docking and molecular design of iminoguanidine-based inhibitors of HemO: A rational approach to antibacterial drug design." Journal of Drugs and Pharmaceutical Science 4, no. 3 (2020): 21–36. http://dx.doi.org/10.31248/jdps2020.036.

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QSAR models of 25 iminoguanidine derivatives with inhibitory HemO were developed. The QSAR model was built by using DFT-MLR and the best QSAR model has R2, Q2 values of 0.6569 and 0.5493 for cross-validated and non-cross-validated. The predictive ability of QSAR model was further validated by a test set of 7 compounds, giving R2pred value of 0.7123. 3D-QSAR and docking studies were used to find the actual conformations of chemicals in active site of HemO, as well as the binding mode pattern to the binding site in HemO enzyme. Molecular dynamics and simulations study revealed that A-chain of He

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Rogić, Sanja, and Žarko Gagić. "3D-QSAR-based pharmacophore determination and design of novel DPP-4 inhibitors." Scripta Medica 53, no. 4 (2022): 271–79. http://dx.doi.org/10.5937/scriptamed53-40866.

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Background/Aim: Therapy of diabetes mellitus type 2 includes drugs that act as inhibitors of dipeptidyl peptidase 4 (DPP-4) enzyme. Several DPP-4 inhibitors are marketed today and although they have favourable safety profile and tolerability, they show moderate activity in controlling glycaemia. The 3D quantitative structure-activity relationship (3D-QSAR) methodology was employed in order to find pharmacophore responsible for good DPP-4 inhibitory activity and designed new compounds with enhanced activity. Methods: For 3D-QSAR model development, 48 compounds structurally related to sitaglipti

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Khalid, Ali Qusay, Vasudeva Rao Avupati, Husniza Hussain, and Tabarek Najeeb Zaidan. "Computational Atom-based Three-Dimensional Quantitative Structure-Activity Relationship (3D QSAR) Model for Predicting Anti-Dengue Agents." Research Journal of Biotechnology 16, no. 10 (2021): 50–58. http://dx.doi.org/10.25303/1610rjbt5058.

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Dengue fever is a viral infection spread by the female mosquito Aedes aegypti. It is a virus spread by mosquitoes found all over the tropics with risk levels varying depending on rainfall, relative humidity, temperature and urbanization. There are no specific medications that can be used to treat the condition. The development of possible bioactive ligands to combat Dengue fever before it becomes a pandemic is a global priority. Few studies on building three-dimensional quantitative structure-activity relationship (3D QSAR) models for anti-dengue agents have been reported. Thus, we aimed at bu

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Gupta, Amit K., and Sun Choi. "Integrated Ligand and Structure-Based Investigation of Structural Requirements for Silent Information Regulator 1 (SIRT1) Activation." Current Topics in Medicinal Chemistry 18, no. 27 (2019): 2313–24. http://dx.doi.org/10.2174/1568026619666181220111059.

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A series of imidazothiazole and oxazolopyridine derivatives as human Silent Information Regulator 1 (SIRT1) activators were subjected to the integrated 2D and 3D QSAR approaches. The derived 3D QSAR models yielded high cross-validated q2 values of 0.682 and 0.628 for CoMFA and CoMSIA, respectively. The non-cross validated values of r2 training = 0.89; predictive r2 test = 0.69 for CoMFA and r2=0.87; predictive r2 test =0.67 for CoMSIA reflected the statistical significance of the developed model. The steric, electrostatic, hydrophobic and hydrogen bond acceptor interactions have been found imp

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Polamreddy, Prasanthi, Vinita Vishwakarma, and Manoj Kumar Mahto. "COMBINATORIAL PHARMACOPHORE MODELING AND ATOM BASED 3D QSAR STUDIES OF BENZOTHIADIAZINES AS HCV-NS5B INHIBITORS." International Journal of Pharmacy and Pharmaceutical Sciences 10, no. 3 (2018): 43. http://dx.doi.org/10.22159/ijpps.2018v10i3.23734.

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Objective: The objective of the current study was to elucidate the 3D pharmacophoric features of benzothiadiazine derivatives that are crucial for inhibiting Hepatitis C virus (HCV) Non-structural protein 5B (NS5B) and quantifying the features by building an atom based 3D quantitative structure-activity relationship (3D QSAR) model.Methods: Generation of QSAR model was carried out using PHASE 3.3.Results: A five-point pharmacophore model with two hydrogen bond acceptors, one negative ionization potential and two aromatic rings (AANRR) was found to be common among a maximum number of benzothiad

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Bhadoriya, Kamlendra S., Shailesh V. Jain, Sanjaykumar B. Bari, Manish L. Chavhan, and Kuldeep R. Vispute. "3D-QSAR Study of Indol-2-yl Ethanones Derivatives as Novel Indoleamine 2,3-Dioxygenase (IDO) Inhibitors." E-Journal of Chemistry 9, no. 4 (2012): 1753–59. http://dx.doi.org/10.1155/2012/368617.

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3D-QSAR approach usingkNN-MFA was applied to a series of Indol-2-yl ethanones derivatives as novel IDO inhibitors. For the purpose, 22 compounds were used to develop models. To elucidate the structural properties required for IDO inhibitory activity, we report herek-nearest neighbor molecular field analysis (kNN-MFA)-based 3D-QSAR model for Indol-2-yl ethanones derivatives as novel IDO inhibitors. Overall model classification accuracy was 76.27% (q2= 0.7627, representing internal validation) in training set and 79.35% (pred_r2= 0.7935, representing external validation) in test set using sphere

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Matsuzaka, Yasunari, and Yoshihiro Uesawa. "A Deep Learning-Based Quantitative Structure–Activity Relationship System Construct Prediction Model of Agonist and Antagonist with High Performance." International Journal of Molecular Sciences 23, no. 4 (2022): 2141. http://dx.doi.org/10.3390/ijms23042141.

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Molecular design and evaluation for drug development and chemical safety assessment have been advanced by quantitative structure–activity relationship (QSAR) using artificial intelligence techniques, such as deep learning (DL). Previously, we have reported the high performance of prediction models molecular initiation events (MIEs) on the adverse toxicological outcome using a DL-based QSAR method, called DeepSnap-DL. This method can extract feature values from images generated on a three-dimensional (3D)-chemical structure as a novel QSAR analytical system. However, there is room for improveme

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da Cunha, Elaine Fontes Ferreira, Rita Cristina Azevedo Martins, Magaly Girão Albuquerque, and Ricardo Bicca de Alencastro. "LIV-3D-QSAR model for estrogen receptor ligands." Journal of Molecular Modeling 10, no. 4 (2004): 297–304. http://dx.doi.org/10.1007/s00894-004-0198-5.

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Veselovsky, A. V., E. G. Matveeva, N. N. Zolotov, and A. S. Ivanov. "3D-QSAR with CoMFA Model of Prolylendopeptidase Substrates." Molecular Simulation 24, no. 4-6 (2000): 411–19. http://dx.doi.org/10.1080/08927020008022385.

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S, Janardhan, та Padmanabha Reddy Y. "Molecular Modeling Studies of β-aminoacyl containing Homopiperazine derivatives as DPP4 Inhibitors". International Journal of Drug Design and Discovery 2, № 3 (2024): 533–47. https://doi.org/10.37285/ijddd.2.3.4.

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Dipeptidyl peptidase IV (DPP4) is a promising target for developing novel anti-diabetic and anti-obesity drugs. Pharmacophore based three dimensional quantitative structure activity relationship studies (3D-QSAR) and molecular docking were performed on a series of 56 β-aminoacyl-containing homopiperazine derivatives of DPP4 inhibitors to find out the structural relationship with the activity. The best predictive 3D-QSAR model with pharmacophore based alignment resulted in R2 (training set) value of 0.9407, Q2 (internal test set) value of 0.9053, Pearson-R value of 0.9517 and root mean square e

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Jin, Yuanyuan, Shuai Fan, Guangxin Lv, et al. "Computer-aided drug design of capuramycin analogues as anti-tuberculosis antibiotics by 3D-QSAR and molecular docking." Open Chemistry 15, no. 1 (2017): 299–307. http://dx.doi.org/10.1515/chem-2017-0039.

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AbstractCapuramycin and a few semisynthetic derivatives have shown potential as anti-tuberculosis antibiotics.To understand their mechanism of action and structureactivity relationships a 3D-QSAR and molecular docking studies were performed. A set of 52 capuramycin derivatives for the training set and 13 for the validation set was used. A highly predictive MFA model was obtained with crossvalidated q2 of 0.398, and non-cross validated partial least-squares (PLS) analysis showed a conventional r2 of 0.976 and r2pred of 0.839. The model has an excellent predictive ability. Combining the 3D-QSAR

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Bernal, Freddy A., and Thomas J. Schmidt. "A QSAR Study for Antileishmanial 2-Phenyl-2,3-dihydrobenzofurans †." Molecules 28, no. 8 (2023): 3399. http://dx.doi.org/10.3390/molecules28083399.

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Leishmaniasis, a parasitic disease that represents a threat to the life of millions of people around the globe, is currently lacking effective treatments. We have previously reported on the antileishmanial activity of a series of synthetic 2-phenyl-2,3-dihydrobenzofurans and some qualitative structure–activity relationships within this set of neolignan analogues. Therefore, in the present study, various quantitative structure–activity relationship (QSAR) models were created to explain and predict the antileishmanial activity of these compounds. Comparing the performance of QSAR models based on

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Sugumar, Shobana. "VIRTUAL SCREENING, PHARMACOPHORE MODELING, AND QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP STUDIES ON HISTAMINE 4 RECEPTOR." Asian Journal of Pharmaceutical and Clinical Research 10, no. 12 (2017): 150. http://dx.doi.org/10.22159/ajpcr.2017.v10i12.19991.

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Objective: To find out novel inhibitors for histamine 4 receptor (H4R), the target for various allergic and inflammatory pathophysiological conditions.Methods: Homology modeling of H4R was performed using easy modeler and validated using structure analysis and verification server, and with the modeled structure, virtual screening, pharmacophore modeling, and quantitative structure activity relationship (QSAR) studies were performed using the Schrodinger 9.3 software.Results: Among all the synthetic and natural ligands, hesperidin, vitexin, and diosmin were found to have the highest dock score,

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Matusevičiūtė, Ramona, Eglė Ignatavičiūtė, Rokas Mickus, Sergio Bordel, Vytenis Arvydas Skeberdis, and Vytautas Raškevičius. "Evaluation of Cx43 Gap Junction Inhibitors Using a Quantitative Structure-Activity Relationship Model." Biomedicines 11, no. 7 (2023): 1972. http://dx.doi.org/10.3390/biomedicines11071972.

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Gap junctions (GJs) made of connexin-43 (Cx43) are necessary for the conduction of electrical impulses in the heart. Modulation of Cx43 GJ activity may be beneficial in the treatment of cardiac arrhythmias and other dysfunctions. The search for novel GJ-modulating agents using molecular docking allows for the accurate prediction of binding affinities of ligands, which, unfortunately, often poorly correlate with their potencies. The objective of this study was to demonstrate that a Quantitative Structure-Activity Relationship (QSAR) model could be used for more precise identification of potent

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Babu Jatavath, Mohan, Sree Kanth Sivan, Yamini Lingala та Vijjulatha Manga. "Docking and 3D QSAR Studies on p38α MAP Kinase Inhibitors". E-Journal of Chemistry 8, № 4 (2011): 1596–605. http://dx.doi.org/10.1155/2011/184863.

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The p38 signaling cascade has emerged as an attractive target for the design of novel chemotherapeutic agents for the treatment of inflammatory diseases. Three dimensional quantitative structure- activity relationship (3D- QSAR) studies were performed on a series of 25, 2-aminothiazole analogs as inhibitors of p38α mitogen activated protein (MAP) kinase. The docking results provided a reliable conformational alignment scheme for the 3D-QSAR model. The 3D-QSAR model showed very good statistical results namely q2, r2and r2predvalues for both comparative molecular field analysis (CoMFA) and compa

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Gianibbi, Beatrice, Anna Visibelli, Giacomo Spinsanti, and Ottavia Spiga. "Three-Dimensional Quantitative Structure–Activity Relationship Study of Transient Receptor Potential Vanilloid 1 Channel Antagonists Reveals Potential for Drug Design Purposes." International Journal of Molecular Sciences 25, no. 14 (2024): 7951. http://dx.doi.org/10.3390/ijms25147951.

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Transient receptor potential vanilloid 1 (TRPV1) was reported to be a putative target for recovery from chronic pain, producing analgesic effects after its inhibition. A series of drug candidates were previously developed, without the ability to ameliorate the therapeutic outcome. Starting from previously designed compounds, derived from the hybridization of antagonist SB-705498 and partial agonist MDR-652, we performed a virtual screening on a pharmacophore model built by exploiting the Cryo-EM 3D structure of a nanomolar antagonist in complex with the human TRPV1 channel. The pharmacophore m

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Mayura, Kale, Khan Sharuk, and Hature Jyoti. "Investigating Structural Requirements of Some Pyrimidine-linked Benzimidazole Derivatives as Anticancer Agents Against MCF-7 Cancerous Cell Line Through the use of 2D and 3D QSARs." Current Chemical Biology 13, no. 3 (2019): 232–49. http://dx.doi.org/10.2174/2212796813666190207144407.

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Background: Cancer is an extremely fast, unrestrained and pathological propagation of cells. Yet there is no cancer treatment that is 100% efficient against scattered cancer. Heterocycles have been considered as a boon to treat several cancers of which pyrimidine is a core nucleus and holds an important place in cancer chemotherapy which is reflected in the use of drugs such as 5-fluorouracil, erlotinib, gefitinib and caneratinib. Also, many good antitumor active agents possess benzimidazoleas its core nucleus. Objective: To design novel pyrimidine-linked benzimidazoles and to explore their st

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LIAO, SI YAN, LI QIAN, JIN CAN CHEN, YONG SHEN, and KANG CHENG ZHENG. "2D/3D-QSAR STUDY ON ANALOGUES OF 2-METHOXYESTRADIOL WITH ANTICANCER ACTIVITY." Journal of Theoretical and Computational Chemistry 07, no. 02 (2008): 287–301. http://dx.doi.org/10.1142/s0219633608003745.

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Two-dimensional (2D) and three-dimensional (3D) quantitative structure–activity relationships (QSARs) of 23 analogs of 2-Methoxyestradiol with anticancer activity (expressed as p GI50) against MCF-7 human breast cancer cells have been studied by using a combined method of the DFT, MM2 and statistics for 2D, as well as the comparative molecular field analysis (CoMFA) for 3D. The established 2D-QSAR model in training set shows not only significant statistical quality, but also predictive ability, with the square of adjusted correlation coefficient [Formula: see text] and the square of the cross-

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Nandi, Sisir, Mridula Saxena, and Anil Kumar Saxena. "QSAR Modeling of CCK2 Receptor Antagonists Utilizing Computed Structural Indices." International Journal of Quantitative Structure-Property Relationships 4, no. 3 (2019): 20–33. http://dx.doi.org/10.4018/ijqspr.2019070102.

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In the present case study, a QSAR model has been developed to identify CCK2 receptor antagonists. The earlier reported 3D pharmacophore modeling of these molecules involved commercial software. Since the reduction in the cost involved in the drug discovery phase is very crucial, in the present study, QSAR models based on the structural indices including 1D, 2D and 3D indices computed from the structures of CCK2 receptor antagonists has been developed utilizing NanoBRIDGES software which is openly accessible (http://nanobridges.eu/software/). This QSAR model is not only comparable to the earlie

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Kim, Taeho, Kee-Choo Chung, and Hwangseo Park. "Derivation of Highly Predictive 3D-QSAR Models for hERG Channel Blockers Based on the Quantum Artificial Neural Network Algorithm." Pharmaceuticals 16, no. 11 (2023): 1509. http://dx.doi.org/10.3390/ph16111509.

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The hERG potassium channel serves as an annexed target for drug discovery because the associated off-target inhibitory activity may cause serious cardiotoxicity. Quantitative structure–activity relationship (QSAR) models were developed to predict inhibitory activities against the hERG potassium channel, utilizing the three-dimensional (3D) distribution of quantum mechanical electrostatic potential (ESP) as the molecular descriptor. To prepare the optimal atomic coordinates of dataset molecules, pairwise 3D structural alignments were carried out in order for the quantum mechanical cross correla

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Ambre, Premlata K., Raghuvir R. S. Pissurlenkar, Evans C. Coutinho, and Radhakrishnan P. Iyer. "Identification of new checkpoint kinase-1 (Chk1) inhibitors by docking, 3D-QSAR, and pharmacophore-modeling methods." Canadian Journal of Chemistry 90, no. 8 (2012): 675–92. http://dx.doi.org/10.1139/v2012-047.

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Inhibition of checkpoint kinase-1 (Chk1) by small molecules is of great therapeutic interest in the field of oncology and for understanding cell-cycle regulations. This paper presents a model with elements from docking, pharmacophore mapping, the 3D-QSAR approaches CoMFA, CoMSIA and CoRIA, and virtual screening to identify novel hits against Chk1. Docking, 3D-QSAR (CoRIA, CoMFA and CoMSIA), and pharmacophore studies delineate crucial site points on the Chk1 inhibitors, which can be modified to improve activity. The docking analysis showed residues in the proximity of the ligands that are invol

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Yadav, Mithlesh, Balasubramanian Narasimhan, and Archana Kapoor. "Development of 2-dimensional and 3-dimensional QSAR models of Indazole derivatives as TTK inhibitors having Anticancer potential." Current Chemistry Letters 13, no. 1 (2024): 225–40. http://dx.doi.org/10.5267/j.ccl.2023.6.006.

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The study aimed to explore the anticancer efficacy of indazole pharmacophore by analyzing a series of 109 derivatives of indazole as Tyrosine Threonine Kinase (TTK) inhibitors through quantitative activity relationship analysis using 2D and 3D QSAR techniques. The best 2D-QSAR model was generated by the MLR method, showing a high correlation coefficient (r2) of 0.9512, and good internal (q2), and external (pred_r2) cross-validation regression coefficients of 0.8998, and 0.8661, respectively. The residual values were modest, indicating good agreement between the observed and predicted pIC50 val

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Patel, Vijay K., and Harish Rajak. "Development of Structure Activity Correlation Model on Aroylindole Derivatives as Anticancer Agents." Letters in Drug Design & Discovery 15, no. 2 (2018): 143–53. http://dx.doi.org/10.2174/1570180814666170823161751.

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Background: Aroylindole derivatives, the structural analogs of Combretastatin A-4 has been found to possess potent growth inhibitory activity on several cancer cell lines due to its excellent antitumor and antivascular activities. The aim of present research work is to identify lead and establish structure activity correlation of trimethoxyaroylindole derivatives, using integrated ligand and structure based computational approaches. Materials and Methods: A correlation between structure and biological activity was established using computational approaches i.e., structure activity correlation

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Divya, V., V. L. Pushpa, S. Sarithamol, and K. B. Manoj. "2D and 3D QSAR model generation of CDK4 inhibitors." Bulletin of Pure & Applied Sciences- Chemistry 37c, no. 1 (2018): 53. http://dx.doi.org/10.5958/2320-320x.2018.00008.0.

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Nagarajan, Shanthi, Asif Ahmed, Hyunah Choo та ін. "3D QSAR pharmacophore model based on diverse IKKβ inhibitors". Journal of Molecular Modeling 17, № 2 (2010): 209–18. http://dx.doi.org/10.1007/s00894-010-0714-8.

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Bacilieri, Magdalena, Silvia Paoletta, Serena Basili, Marco Fanton, and Stefano Moro. "A Novel Generalized 3D-QSAR Model of Camptothecin Analogs." Molecular Informatics 30, no. 11-12 (2011): 927–38. http://dx.doi.org/10.1002/minf.201100060.

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Yogaswara, Radite, Maria Ludya Pulung, Sri Hartati Yuliani, and Enade Perdana Istyastono. "Docking-Guided 3D-QSAR Studies of 4-Aminoquinoline-1,3,5-triazines as Inhibitors for Plasmodium falciparum Dihydrofolate Reductase." Indonesian Journal of Chemistry 20, no. 6 (2020): 1455. http://dx.doi.org/10.22146/ijc.50674.

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Mutations in Plasmodium falciparum dihydrofolate reductase (PfDHFR), together with other mutations, hinder malaria elimination in Southeast Asia due to multiple drug resistance. In this article, molecular docking-guided three-dimensional (3D) quantitative structure-activity relationship (QSAR) analysis of 4-aminoquinoline-1,3,5-triazines as inhibitors for the wild-type (WT) PfDHFR to identify the molecular determinants of the inhibitors binding are presented. Compounds 4-aminoquinoline-1,3,5-triazines were reported promising to be developed as the non-resistant drugs. The 3D-QSAR analysis resu

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Sirous, Hajar, Giuseppe Campiani, Simone Brogi, Vincenzo Calderone, and Giulia Chemi. "Computer-Driven Development of an in Silico Tool for Finding Selective Histone Deacetylase 1 Inhibitors." Molecules 25, no. 8 (2020): 1952. http://dx.doi.org/10.3390/molecules25081952.

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Histone deacetylases (HDACs) are a class of epigenetic modulators overexpressed in numerous types of cancers. Consequently, HDAC inhibitors (HDACIs) have emerged as promising antineoplastic agents. Unfortunately, the most developed HDACIs suffer from poor selectivity towards a specific isoform, limiting their clinical applicability. Among the isoforms, HDAC1 represents a crucial target for designing selective HDACIs, being aberrantly expressed in several malignancies. Accordingly, the development of a predictive in silico tool employing a large set of HDACIs (aminophenylbenzamide derivatives)

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