| Development of prediction model for fructose-6-bisphosphatase inhibitors using the Monte Carlo method |
22 |
| Design and development of novel focal adhesion kinase (FAK) inhibitors using Monte Carlo method with index of ideality of correlation to validate QSAR |
20 |
| In silico design of diacylglycerol acyltransferase-1 (DGAT1) inhibitors based on SMILES descriptors using Monte-Carlo method |
14 |
| Prediction of the adsorption coefficients of some aromatic compounds on multi-wall carbon nanotubes by the Monte Carlo method |
11 |
| Structural exploration of hydroxyethylamines as HIV-1 protease inhibitors: new features identified |
10 |
| Molecular docking revealed the binding of nucleotide/side inhibitors to Zika viral polymerase solved structures |
9 |
| Development of classification models for predicting chronic toxicity of chemicals to Daphnia magna and Pseudokirchneriella subcapitata |
8 |
| Finding the structural requirements of diverse HIV-1 protease inhibitors using multiple QSAR modelling for lead identification |
8 |
| Molecular modelling studies on adamantane-based Ebola virus GP-1 inhibitors using docking, pharmacophore and 3D-QSAR |
8 |
| Idealization of correlations between optimal simplified molecular input-line entry system-based descriptors and skin sensitization |
8 |
| Multi-targeted directed ligands for Alzheimer's disease: design of novel lead coumarin conjugates |
7 |
| Docking analysis targeted to the whole enzyme: an application to the prediction of inhibition of PTP1B by thiomorpholine and thiazolyl derivatives |
6 |
| Identification of potential CRAC channel inhibitors: Pharmacophore mapping, 3D-QSAR modelling, and molecular docking approach |
5 |
| Prediction of the binding affinity of aptamers against the influenza virus |
5 |
| Combining molecular docking and molecular dynamics studies for modelling Staphylococcus aureus MurD inhibitory activity |
5 |
| Insight into structural features of phenyltetrazole derivatives as ABCG2 inhibitors for the treatment of multidrug resistance in cancer |
5 |
| QSPR models for bioconcentration factor (BCF): are they able to predict data of industrial interest? |
5 |
| Modelling methods and cross-validation variants in QSAR: a multi-level analysis |
5 |
| Molecular modelling studies on cinnoline-based BTK inhibitors using docking and structure-based 3D-QSAR |
5 |
| Prediction of apoptosis protein subcellular localization via heterogeneous features and hierarchical extreme learning machine |
5 |
| Multiple molecular modelling studies on some derivatives and analogues of glutamic acid as matrix metalloproteinase-2 inhibitors |
4 |
| A large comparison of integrated SAR/QSAR models of the Ames test for mutagenicity($) |
4 |
| A simple approach for assessment of toxicity of nitroaromatic compounds without using complex descriptors and computer codes |
4 |
| Conformal prediction of HDAC inhibitors |
4 |
| An ensemble method for multi-type Gram-negative bacterial secreted protein prediction by integrating different PSSM-based features |
4 |
| QSAR classification model for diverse series of antifungal agents based on improved binary differential search algorithm |
4 |
| Repurposing drugs for use against Zika virus infection |
4 |
| In silico study directed towards identification of novel high-affinity inhibitors targeting an oncogenic protein: BRD4-BD1 |
3 |
| Could we expect new praziquantel derivatives? A meta pharmacometrics/pharmacoinformatics analysis of all antischistosomal praziquantel derivatives found in the literature |
3 |
| Understanding the toxic potencies of xenobiotics inducing TCDD/TCDF-like effects |
3 |
| Probability-driven 3D pharmacophore mapping of antimycobacterial potential of hybrid molecules combining phenylcarbamoyloxy and N-arylpiperazine fragments |
3 |
| Prediction of therapeutic potency of tacrine derivatives as BuChE inhibitors from quantitative structure-activity relationship modelling |
3 |
| A binary QSAR model for classifying neuraminidase inhibitors of influenza A viruses (H1N1) using the combined minimum redundancy maximum relevancy criterion with the sparse support vector machine |
3 |
| Development of non-peptide ACE inhibitors as novel and potent cardiovascular therapeutics: An in silico modelling approach |
3 |
| Filter feature selectors in the development of binary QSAR models |
3 |
| QSAR modelling of synergists to increase the efficacy of deltamethrin against pyrethroid-resistant Aedes aegypti mosquitoes($) |
3 |
| Mathematical structural descriptors and mutagenicity assessment: a study with congeneric and diverse datasets($) |
3 |
| In silico study directed towards identification of the key structural features of GyrB inhibitors targeting MTB DNA gyrase: HQSAR, CoMSIA and molecular dynamics simulations |
3 |
| Rivality index neighbourhood algorithm with density and distances weighted schemes for the building of robust QSAR classification models with high reliable applicability domain |
2 |
| Multiple target-based pharmacophore design from active site structures |
2 |
| Pharmacological repositioning of Achyranthes aspera as an antidepressant using pharmacoinformatic tools PASS and PharmaExpert: a case study with wet lab validation |
2 |
| PASS-based prediction of metabolites detection in biological systems |
2 |
| 2D and 3D structure-activity modelling of mosquito repellents: a review |
2 |
| Classification models for identifying substances exhibiting acute contact toxicity in honeybees (Apis mellifera)($) |
2 |
| Performance evaluation of the GastroPlus (TM) software tool for prediction of the toxicokinetic parameters of chemicals |
2 |
| iDHS-DMCAC: identifying DNase I hypersensitive sites with balanced dinucleotide-based detrending moving-average cross-correlation coefficient |
2 |
| QSAR modelling on a series of arylsulfonamide-based hydroxamates as potent MMP-2 inhibitors |
2 |
| Modelling the water-plant cuticular polymer matrix membrane partitioning of diverse chemicals in multiple plant species using the support vector machine-based QSAR approach |
2 |
| Development and rigorous validation of antimalarial predictive models using machine learning approaches |
2 |
| Molecular activities and ligand-binding specificities of StAR-related lipid transfer domains: exploring integrated in silico methods and ensemble-docking approaches |
2 |
