“…The 17,538 molecular descriptors derived with PaDEL and EPI Suite softwares are simultaneously analyzed through linear regressions obtained with the Replacement Method variable subset selection technique. …”
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“…The structural descriptors are derived with different freeware, such as PaDEL, Mold(2), and QuBiLs-MAS; such descriptor software complements each other and improves the QSAR results. …”
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“…This study has been performed with the help of Chemdraw Ultra 7.0, GUSAR online tool for IC(50) and LD(50) predictions, AutoDock Vina (Python Prescription 0.8), and PaDEL software. Results revealed that ligand-protein interaction affinity of all 10 designed molecules ranges from -5.7 Kcal/mol to -5.2 Kcal/mol, which is approximately comparable to pre-existing GABA(1) inhibitor i.e. phenytoin (CID: 1775, ligand-protein interaction affinity is -6.5 Kcal/mol).…”
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“…A k-nearest neighbor (k-NN) classification model was constructed for 118 RDT NEDO (Repeated Dose Toxicity New Energy and industrial technology Development Organization; currently known as the Hazard Evaluation Support System (HESS)) database chemicals, employing two acute toxicity (LD(50))-based classes as a response and using a series of eight PaDEL software-derived fingerprints as predictor variables. …”
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“…A series of 172 molecular structures that block the hERG K(+) channel were used to develop a classification model where, initially, eight types of PaDEL fingerprints were used for k-nearest neighbor model development. …”
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“…In this work, we developed five machine learning models to predict antimalarial bioactivities of a drug against plasmodium falciparum from the features (i.e., molecular descriptors values) obtained from PaDEL software from SMILES of compounds and compare the machine learning models by experiments with our collected data of 4794 instances. …”
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“…The docking scores/binding free energies were predicted and calculated using AutoDock Vina along with physicochemical and structural properties of the NPs, using PaDEL descriptors. These were compared to the established inhibitor (control) drugs for each mycobacterial target. …”
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“…Performance benchmark results show that Mordred is at least twice as fast as the well-known PaDEL-Descriptor and it can calculate descriptors for large molecules, which cannot be accomplished by other software. …”
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“…Secondly, a wide range of features was computed from the structure of these peptides using software PaDEL. Finally, models were developed for predicting the antimicrobial potential of chemically modified peptides using a wide range of structural features of these peptides. …”
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“…The software used were Spartan 14, material studio, Padel, Pymol, Autodock tool, Autodock vina and discovery studio. …”
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“…Twelve molecular fingerprints from PaDeL-Descriptor were calculated for model training. …”
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“…Random Forest model developed by using PaDEL descriptors (combination of 2D, 3D, and fingerprints) achieved maximum accuracy of 95.10%, MCC of 0.90 and AUROC of 0.99 on the main dataset. …”
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“…Thereafter, a model based on a sequence-based feature is used to code the protein sequences of human and spike proteins using the well-known Moran autocorrelation technique, while the drugs are coded using another well-known technique, viz., PaDEL descriptors, to predict new human–spike PPIs and eventually new drug–protein interactions for the top 20 predicted human proteins interacting with the original spike protein and its different mutated variants like Alpha, Beta, Delta, Gamma, and Omicron. …”
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“…The ionization efficiency values were predicted based on a random forest regression model from PaDEL descriptors and predicted values showed statistically significant correlation with the measured response factors (p < 0.05) with Spearman’s rho of 0.584 and 0.669 for SFC and LC data, respectively. …”
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“…Several types of descriptors (calculated from 4 softwares i.e., Gaussian 09, Dragon, PaDEL and Mold(2 )softwares) were used to generate three multiple linear regression (MLR) models with preferable predictive performance (Q(2)(LOO-CV) = 0.813-0.908; RMSE(LOO-CV) = 0.150-0.210; Q(2)(Ext) = 0.875-0.952; RMSE(Ext) = 0.104-0.166). …”
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“…To overcome this, a thorough investigation under the Expedition “GRACIOSA/2004”, the Campaigns “PADEL/2006”, “MACROBIOLMOL/2014” and “PIMA-BALA/2017” involving sample collecting and presence data recording, was undertaken over an area of 19 km(2) encompassing littoral and sublittoral levels down to about 40 m around the Island. …”
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“…The introduced drug repurposing pipeline consists of compound similarity with C3 fungicides and molecular docking (MD) simulations with final QM/MM binding energy determination, while aiming for potential novel chromophores and perserving at least an amide (R1HN(C=O)R2) or ester functional group of almost all up to date C3 fungicides. 3D descriptors used for a similarity test were based on the 280 most stable Padel descriptors. Hit compounds that passed fingerprint and 3D descriptor similarity condition and had either an amide or an ester group were submitted to docking where they further had to satisfy both Chemscore fitness and specific conformation constraints. …”
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“…QSPR modelling was then executed using the software PaDEL for descriptor calculation and the software QSARINS for the overall modelling process including genetic algorithm (GA) and multiple linear regression (MLR). …”
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“…To ensure the symmetry and fairness of the data splitting and to generate multiple chemically diverse training and validation sets, we used a self-organizing mapping (SOM) neural network to split the modeling dataset (containing 955 compounds) characterized by PaDEL-descriptors. After preliminary selection of descriptors via the mean decrease impurity method, a hybrid quantum particle swarm optimization (HQPSO) algorithm was used to jointly optimize the parameters of RBF and select the key descriptors. …”
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