Molecular Informatics

Papers
(The TQCC of Molecular Informatics is 4. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-08-01 to 2025-08-01.)
ArticleCitations
76
Application of Molecular Docking, Homology Modeling, and Chemometric Approaches to Neonicotinoid Toxicity against Aphis craccivora48
Development and Evaluation of Peptidomimetic Compounds against SARS‐CoV‐2 Spike Protein: An in silico and in vitro Study44
Fragment‐based deep molecular generation using hierarchical chemical graph representation and multi‐resolution graph variational autoencoder43
A community effort in SARS‐CoV‐2 drug discovery37
Cover Picture: (Mol. Inf. 4/2022)36
Development of a Novel Pharmacophore Model Guided by the Ensemble of Waters and Small Molecule Fragments Bound to SARS‐CoV‐2 Main Protease30
Chemical Reactivity Prediction: Current Methods and Different Application Areas26
Cover Picture: (Mol. Inf. 1/2023)26
A Descriptor Set for Quantitative Structure‐property Relationship Prediction in Biologics25
Review of the 8th autumn school in chemoinformatics25
Cover Picture: (Mol. Inf. 1/2024)23
Virtual screening of natural products to enhance melanogenosis22
Application of automated machine learning in the identification of multi‐target‐directed ligands blocking PDE4B, PDE8A, and TRPA1 with potential use in the treatment of asthma and COPD22
Cumulative phylogenetic, sequence and structural analysis of Insulin superfamily proteins provide unique structure‐function insights20
Predicting the duration of action of β2‐adrenergic receptor agonists: Ligand and structure‐based approaches20
Structure‐based Pharmacophore Screening Coupled with QSAR Analysis Identified Potent Natural‐product‐derived IRAK‐4 Inhibitors19
Technique of Augmenting Molecular Graph Data by Perturbating Hidden Features18
Identification of Trovafloxacin, Ozanimod, and Ozenoxacin as Potent c‐Myc G‐Quadruplex Stabilizers to Suppress c‐Myc Transcription and Myeloma Growth17
Ambit‐SLN: an Open Source Software Library for Processing of Chemical Objects via SLN Linear Notation16
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Drug Search and Design Considering Cell Specificity of Chemically Induced Gene Expression Profiles for Disease‐Associated Tissues15
Predicting the bandgap and efficiency of perovskite solar cells using machine learning methods14
Cover Picture: (Mol. Inf. 5/2024)14
Cover Picture: (Mol. Inf. 6/2022)14
Kinematic analysis of kinases and their oncogenic mutations – Kinases and their mutation kinematic analysis13
Use of tree‐based machine learning methods to screen affinitive peptides based on docking data12
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Rapid Assessment of Virtually Synthesizable Chemical Structures via Support Vector Machine Models12
Neural Network Models for Prediction of Biological Activity using Molecular Dynamics Data: A Case of Photoswitchable Peptides12
Cover Picture: (Mol. Inf. 7/2024)11
Multi‐Task ADME/PK prediction at industrial scale: leveraging large and diverse experimental datasets**11
Cover Picture: (Mol. Inf. 4/2025)11
Cover Picture: (Mol. Inf. 6/2024)11
Natural‐Language Processing (NLP) based feature extraction technique in Deep‐Learning model to predict the Blood‐Brain‐Barrier permeability of molecules10
Antibacterial Activity Prediction of Plant Secondary Metabolites Based on a Combined Approach of Graph Clustering and Deep Neural Network10
Cover Picture: (Mol. Inf. 11/2023)9
Cover Picture: (Mol. Inf. 9/2021)9
Data‐driven approaches for identifying hyperparameters in multi‐step retrosynthesis9
Chemoinformatic Analysis of Isothiocyanates: Their Impact in Nature and Medicine9
A comparison between 2D and 3D descriptors in QSAR modeling based on bio‐active conformations8
The VEGA web service: multipurpose online tools for molecular modelling and docking analyses8
KNIME Workflows for Chemoinformatic Characterization of Chemical Databases8
Discovery of a pocket network on the domain 5 of the TrkB receptor – A potential new target in the quest for the new ligands8
Cover Picture: (Mol. Inf. 7/2025)8
Exploring drug repositioning possibilities of kinase inhibitors via molecular simulation**8
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In Silico Identification of Novel and Potent Inhibitors Against Mutant BRAF (V600E), MD Simulations, Free Energy Calculations, and Experimental Determination of Binding Affinity7
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Deimos: A novel automated methodology for optimal grouping. Application to nanoinformatics case studies7
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BIOMX‐DB: A web application for the BIOFACQUIM natural product database7
Cover Picture: (Mol. Inf. 10/2024)6
Cover Picture: (Mol. Inf. 1/2022)6
Cover Picture: (Mol. Inf. 10/2022)6
Machine Learning in Drug Development for Neurological Diseases: A Review of Blood Brain Barrier Permeability Prediction Models6
Identification of a PD1/PD‐L1 inhibitor by structure‐based pharmacophore modelling, virtual screening, molecular docking and biological evaluation**6
Cover Picture: (Mol. Inf. 12/2023)6
A Scaffold‐based Deep Generative Model Considering Molecular Stereochemical Information6
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Distinct binding hotspots for natural and synthetic agonists of FFA4 from in silico approaches**6
Cover Picture: (Mol. Inf. 7/2023)6
Machine Learning for Prediction of Drug Targets in Microbe Associated Cardiovascular Diseases by Incorporating Host‐pathogen Interaction Network Parameters6
Turbo Similarity Searching: Effect of Partial Ranking and Fusion Rules on ChEMBL Database5
Cover Picture: (Mol. Inf. 8‐9/2023)5
PredictingS. aureusantimicrobial resistance with interpretable genomic space maps5
Spherical GTM: A New Proposition for Visualization of Chemical Data5
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Network‐Based Approaches for Drug Repositioning5
My 50 Years with Chemoinformatics5
AliNA – a deep learning program for RNA secondary structure prediction5
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A Molecular Representation to Identify Isofunctional Molecules4
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Cover Picture: (Mol. Inf. 5/2022)4
Modeling Carbon Basicity4
Feature importance‐based interpretation of UMAP‐visualized polymer space4
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Network Analysis of the Organic Chemistry in Patents, Literature, and Pharmaceutical Industry4
Cover Picture: (Mol. Inf. 5/2023)4
Cover Picture: (Mol. Inf. 5‐6/2025)4
GDMol: Generative Double‐Masking Self‐Supervised Learning for Molecular Property Prediction4
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The macrocycle inhibitor landscape of SLC‐transporter4
Targeting of essential mycobacterial replication enzyme DnaG primase revealed Mitoxantrone and Vapreotide as novel mycobacterial growth inhibitors**4
Molecular Energies Derived from Deep Learning: Application to the Prediction of Formation Enthalpies Up to High Energy Compounds4
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