OOIR: Observatory of International Research

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 2021-04-01 to 2025-04-01.)

Article	Citations
	72
Cover Picture: (Mol. Inf. 6/2021)	41
Cover Picture: (Mol. Inf. 2/2025)	35
MAYA (Multiple ActivitY Analyzer): An Open Access Tool to Explore Structure‐Multiple Activity Relationships in the Chemical Universe	34
Cover Picture: (Mol. Inf. 1/2022)	32
Cover Picture: (Mol. Inf. 2/2022)	30
Cover Picture: (Mol. Inf. 9/2022)	29
	27
	26
Cover Picture: (Mol. Inf. 4/2022)	23
	22
	20
	19
Cover Picture: (Mol. Inf. 8/2022)	18
Development of a Novel Pharmacophore Model Guided by the Ensemble of Waters and Small Molecule Fragments Bound to SARS‐CoV‐2 Main Protease	17
Cover Picture: (Mol. Inf. 1/2023)	17
Cover Picture: (Mol. Inf. 10/2024)	17
Distinct binding hotspots for natural and synthetic agonists of FFA4 from in silico approaches**	17
The freedom space – a new set of commercially available molecules for hit discovery	16
Active learning approaches in molecule pKi prediction	16
Navigating a 1E+60 Chemical Space of Peptide/Peptoid Oligomers	16
Cover Picture: (Mol. Inf. 9/2024)	14
In Silicoprediction of inhibitors for multiple transporters via machine learning methods	14
Prediction of adverse drug reactions due to genetic predisposition using deep neural networks	14
Prediction of blood‐brain barrier permeability using machine learning approaches based on various molecular representation	13

Fragment‐based deep molecular generation using hierarchical chemical graph representation and multi‐resolution graph variational autoencoder	13
Computer‐aided design of muscarinic acetylcholine receptor M3 inhibitors: Promising compounds among trifluoromethyl containing hexahydropyrimidinones/thiones	12
Augmenting bioactivity by docking‐generated multiple ligand poses to enhance machine learning and pharmacophore modelling: discovery of new TTK inhibitors as case study	12
Highly Accurate Filters to Flag Frequent Hitters in AlphaScreen Assays by Suggesting their Mechanism	11
Chemical Reactivity Prediction: Current Methods and Different Application Areas	11
Application of Molecular Docking, Homology Modeling, and Chemometric Approaches to Neonicotinoid Toxicity against Aphis craccivora	11
Atom‐to‐atom Mapping: A Benchmarking Study of Popular Mapping Algorithms and Consensus Strategies	11
Structural Fractal Analysis of the Active Site of Acetylcholinesterase in Complexes with Huperzine A, Galantamine, and Donepezil	10
Block‐wise Exploration of Molecular Descriptors with Multi‐block Orthogonal Component Analysis (MOCA)	10
A Dataset of Computational Reaction Barriers for the Claisen Rearrangement: Chemical and Numerical Analysis	10
A new set of KNIME nodes implementing the QPhAR algorithm	9
Identification of a PD1/PD‐L1 inhibitor by structure‐based pharmacophore modelling, virtual screening, molecular docking and biological evaluation**	9
LCP: Simple Representation of Docking Poses for Machine Learning: A Case Study on Xanthine Oxidase Inhibitors	9
Gas‐to‐ionic liquid partition: QSPR modeling and mechanistic interpretation	9
Development and Evaluation of Peptidomimetic Compounds against SARS‐CoV‐2 Spike Protein: An in silico and in vitro Study	8
FetoML: Interpretable predictions of the fetotoxicity of drugs based on machine learning approaches	8
RENATE: A Pseudo‐retrosynthetic Tool for Synthetically Accessible de novo Design	8
Ensemble docking based virtual screening of SARS‐CoV‐2 main protease inhibitors	8
An in silico investigation of Kv2.1 potassium channel: Model building and inhibitors binding sites analysis**	8
Extensive Molecular Dynamics Simulations Disclosed the Stability of mPGES‐1 Enzyme and the Structural Role of Glutathione (GSH) Cofactor	7
A Descriptor Set for Quantitative Structure‐property Relationship Prediction in Biologics	7
A community effort in SARS‐CoV‐2 drug discovery	7
GUIDEMOL: A Python graphical user interface for molecular descriptors based on RDKit	6
Machine Learning in Drug Development for Neurological Diseases: A Review of Blood Brain Barrier Permeability Prediction Models	6
Cover Picture: (Mol. Inf. 8‐9/2023)	6
MGRNN: Structure Generation of Molecules Based on Graph Recurrent Neural Networks	6
The Relevance of Goodness‐of‐fit, Robustness and Prediction Validation Categories of OECD‐QSAR Principles with Respect to Sample Size and Model Type	6
	6
Application of machine learning‐based read‐across structure‐property relationship (RASPR) as a new tool for predictive modelling: Prediction of power conversion efficiency (PCE) for selected classes o	6
Comparing Explanations of Molecular Machine Learning Models Generated with Different Methods for the Calculation of Shapley Values	6
Cover Picture: (Mol. Inf. 12/2021)	6
Cover Picture: (Mol. Inf. 3/2022)	6
	5
	5
	5
Cover Picture: (Mol. Inf. 7/2021)	5
Discovery of natural‐derived M^pro inhibitors as therapeutic candidates for COVID‐19: Structure‐based pharmacophore screening combined with QSAR analysis	5
Cover Picture: (Mol. Inf. 1/2024)	5
PredictingS. aureusantimicrobial resistance with interpretable genomic space maps	5
	5
	5
Similarity searching for anticandidal agents employing a repurposing approach	5
	4
Discovery of a Novel Antimicrobial Agent by the Virtual Screening of a Library of Small Molecules	4
Exploring data‐driven chemical SMILES tokenization approaches to identify key protein–ligand binding moieties	4
My 50 Years with Chemoinformatics	4
Pharmacophore‐guided Virtual Screening to Identify New β₃‐adrenergic Receptor Agonists	4
Structural analysis of neomycin B and kanamycin A binding Aminoglycosides Modifying Enzymes (AME) and bacterial ribosomal RNA	4
	4
	4

Cover Picture: (Mol. Inf. 11/2024)	4
Cover Picture: (Mol. Inf. 3/2023)	4
Cell‐penetrating peptides predictors: A comparative analysis of methods and datasets	4
Predicting the duration of action of β2‐adrenergic receptor agonists: Ligand and structure‐based approaches	4
The Chemical Space Spanned by Manually Curated Datasets of Natural and Synthetic Compounds with Activities against SARS‐CoV‐2	4
Virtual screening of natural products to enhance melanogenosis	4