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 2021-09-01 to 2025-09-01.)
ArticleCitations
77
Application of Molecular Docking, Homology Modeling, and Chemometric Approaches to Neonicotinoid Toxicity against Aphis craccivora51
Development and Evaluation of Peptidomimetic Compounds against SARS‐CoV‐2 Spike Protein: An in silico and in vitro Study49
Fragment‐based deep molecular generation using hierarchical chemical graph representation and multi‐resolution graph variational autoencoder45
Cover Picture: (Mol. Inf. 4/2022)37
Development of a Novel Pharmacophore Model Guided by the Ensemble of Waters and Small Molecule Fragments Bound to SARS‐CoV‐2 Main Protease36
Cover Picture: (Mol. Inf. 1/2023)30
A community effort in SARS‐CoV‐2 drug discovery29
A Descriptor Set for Quantitative Structure‐property Relationship Prediction in Biologics27
Chemical Reactivity Prediction: Current Methods and Different Application Areas27
Identification of Trovafloxacin, Ozanimod, and Ozenoxacin as Potent c‐Myc G‐Quadruplex Stabilizers to Suppress c‐Myc Transcription and Myeloma Growth26
Cover Picture: (Mol. Inf. 1/2024)22
Review of the 8th autumn school in chemoinformatics22
Virtual screening of natural products to enhance melanogenosis20
Technique of Augmenting Molecular Graph Data by Perturbating Hidden Features20
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 COPD19
Cumulative phylogenetic, sequence and structural analysis of Insulin superfamily proteins provide unique structure‐function insights19
Predicting the duration of action of β2‐adrenergic receptor agonists: Ligand and structure‐based approaches19
17
Cover Picture: (Mol. Inf. 6/2022)15
Drug Search and Design Considering Cell Specificity of Chemically Induced Gene Expression Profiles for Disease‐Associated Tissues15
Kinematic analysis of kinases and their oncogenic mutations – Kinases and their mutation kinematic analysis15
14
Cover Picture: (Mol. Inf. 5/2024)14
14
Predicting the bandgap and efficiency of perovskite solar cells using machine learning methods14
Use of tree‐based machine learning methods to screen affinitive peptides based on docking data13
Natural‐Language Processing (NLP) based feature extraction technique in Deep‐Learning model to predict the Blood‐Brain‐Barrier permeability of molecules13
Cover Picture: (Mol. Inf. 7/2024)12
Cover Picture: (Mol. Inf. 6/2024)12
Cover Picture: (Mol. Inf. 4/2025)12
Multi‐Task ADME/PK prediction at industrial scale: leveraging large and diverse experimental datasets**11
Cover Picture: (Mol. Inf. 11/2023)11
Rapid Assessment of Virtually Synthesizable Chemical Structures via Support Vector Machine Models10
Antibacterial Activity Prediction of Plant Secondary Metabolites Based on a Combined Approach of Graph Clustering and Deep Neural Network10
Exploring drug repositioning possibilities of kinase inhibitors via molecular simulation**9
Data‐driven approaches for identifying hyperparameters in multi‐step retrosynthesis9
The VEGA web service: multipurpose online tools for molecular modelling and docking analyses9
Neural Network Models for Prediction of Biological Activity using Molecular Dynamics Data: A Case of Photoswitchable Peptides9
Cover Picture: (Mol. Inf. 9/2021)9
8
Cover Picture: (Mol. Inf. 7/2025)8
KNIME Workflows for Chemoinformatic Characterization of Chemical Databases8
LiProS: Findable, Accessible, Interoperable, and Reusable Data Simulation Workflow to Predict Accurate Lipophilicity Profiles for Small Molecules8
Discovery of a pocket network on the domain 5 of the TrkB receptor – A potential new target in the quest for the new ligands8
7
Deimos: A novel automated methodology for optimal grouping. Application to nanoinformatics case studies7
A comparison between 2D and 3D descriptors in QSAR modeling based on bio‐active conformations7
In Silico Identification of Novel and Potent Inhibitors Against Mutant BRAF (V600E), MD Simulations, Free Energy Calculations, and Experimental Determination of Binding Affinity7
7
BIOMX‐DB: A web application for the BIOFACQUIM natural product database7
Cover Picture: (Mol. Inf. 10/2024)6
Machine Learning in Drug Development for Neurological Diseases: A Review of Blood Brain Barrier Permeability Prediction Models6
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
Identification of a PD1/PD‐L1 inhibitor by structure‐based pharmacophore modelling, virtual screening, molecular docking and biological evaluation**6
Cover Picture: (Mol. Inf. 1/2022)6
Cover Picture: (Mol. Inf. 10/2022)6
6
Distinct binding hotspots for natural and synthetic agonists of FFA4 from in silico approaches**6
Cover Picture: (Mol. Inf. 12/2023)6
A Scaffold‐based Deep Generative Model Considering Molecular Stereochemical Information6
My 50 Years with Chemoinformatics5
5
Spherical GTM: A New Proposition for Visualization of Chemical Data5
5
Cover Picture: (Mol. Inf. 8‐9/2023)5
5
Network‐Based Approaches for Drug Repositioning5
PredictingS. aureusantimicrobial resistance with interpretable genomic space maps5
AliNA – a deep learning program for RNA secondary structure prediction4
4
The macrocycle inhibitor landscape of SLC‐transporter4
Modeling Carbon Basicity4
Exploring activity landscapes with extended similarity: is Tanimoto enough?4
GDMol: Generative Double‐Masking Self‐Supervised Learning for Molecular Property Prediction4
Feature importance‐based interpretation of UMAP‐visualized polymer space4
4
Cover Picture: (Mol. Inf. 5/2023)4
Cover Picture: (Mol. Inf. 5‐6/2025)4
Cover Picture: (Mol. Inf. 5/2022)4
Turbo Similarity Searching: Effect of Partial Ranking and Fusion Rules on ChEMBL Database4
A Molecular Representation to Identify Isofunctional Molecules4
4
Targeting of essential mycobacterial replication enzyme DnaG primase revealed Mitoxantrone and Vapreotide as novel mycobacterial growth inhibitors**4
Enhancing the Reliability of Integrated Consensus Strategies to Boost Docking‐Based Screening Campaigns Using Publicly Available Docking Programs4
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