Impact Factor
3.46
Journal Citation Impact
Estimated influence, citation density, publishing volume, and citation integrity from the analytics table.
Citation rate
3.86
463 total citations
h5-index
29
h5 depth signal
Cited share
64.8%
81 of 125
Total citations
463
Citation footprint
Metric signal
3.81
External metric anchor
Self-citation
2.2%
10 self-citations
Citations Trend
Monthly Publications Cadence
Citing Geographic Demographics
France
77
China
72
Japan
67
Germany
61
United States
57
Citing Fields of Research
Protein Structure & Folding
401
AI & Machine Learning
264
Chemometrics
100
Genetics & Genomics
80
Physical Chemistry
44
Publishing Activity & Reach
Volume, recency, access pattern, and citing-community signals from the journal analytics record.
All-time article footprint
1,342
Articles tracked across the journal lifetime
Indexed publication set
125
81 cited publications
Last 12 months
47
4.3 publications/month
Open access share
48.9%
23 OA publications in the last year
Leading citing country
France
77 citing publications
Leading citing field
Protein Structure & Folding
401 citing publications
Latest tracked publication
14 October 2026
10 recent records available
Coverage & Indexing History
v35n1, Jan. 2016-
v35n1, Jan. 2016- ; Selected citations only before this date
Research Focus & Classification
Indexed Subjects
AI & Machine Learning
Protein Structure & Folding
Broad Categories
Chemistry
Computational Biology
Molecular Biology
Protein Structure & Folding
MeSH Descriptors
Biochemical Phenomena
Computational Biology
Computer-Aided Design
Latest Publications
Recent article records with DOI-first linking and condensed abstracts.
01
DOI 10.1002/minf.70061
Open DOI
Identification of YES1 Inhibitors From Approved Drugs Using a Multimodal Deep Learning Framework
While anti‐human epidermal growth factor receptor 2 (HER2) drugs, including trastuzumab improve the prognosis of patients with HER2‐positive cancers, acquired resistance by cancer cells remains a significant clinical challenge. We had pr...
02
DOI 10.1002/minf.70057
Open DOI
Graph‐Based Nitrogen Substitution and CatBoost Regression for Virtual Screening of Small‐Molecule Acceptors in Organic Photovoltaics
Machine learning‐driven high‐throughput screening strategy was used for designing efficient nitrogen‐containing small‐molecule acceptors (SMAs) for organic solar cells. First, a database containing 1027 experimentally determined SMAs was...
03
DOI 10.1002/minf.70059
Open DOI
LigGen: A Tool for Predicting Water Positions in Proteins
To create a drug‐like chemical space for a specific binding pocket of protein,it is important to take into account not only the topology of the protein's amino acids, but also their local environment—at least water molecules. In this art...
04
DOI 10.1002/minf.70056
Open DOI
Data‐Driven Prediction of Ultraviolet–Visible Spectra From Molecular Structure Using Attention‐Based Graph Neural Networks
Predicting UV–vis spectra from molecular structure is an important but relatively underexplored task. In this study, we developed a deep learning approach based on graph neural networks (GNNs) to directly predict UV–vis spectra from SMIL...
05
DOI 10.1002/minf.70055
Open DOI
Property‐Conditioned Transformer Language Model for De Novo Molecular Generation Using Self‐Referencing Embedded Strings
Transformer‐based molecular language models have demonstrated strong capabilities for de novo molecular generation by modeling chemical structures as token sequences. However, controllable generation of molecules with desired physicochem...
06
DOI 10.1002/minf.70054
Open DOI
Structural and Biological Evidence for Acetylcholinesterase‐Targeted Insecticidal Activity in Musca domestica : A 4.5 Å Distance Correlation From Novel Benzenesulfonamide Derivatives
House fly ( Musca domestica ) control faces mounting resistance to conventional insecticides, driving interest in novel chemistries targeting acetylcholinesterase (AChE). We examined eight benzenesulfonamide derivatives originally develo...
07
DOI 10.1002/minf.70052
Open DOI
Predicting the Toxicity of Chemical Compounds via Hyperdimensional Computing
Accurately and efficiently assessing the potential toxicity of chemical compounds is critical given their wide application across pharmaceutical, industrial, and environmental domains. Traditional toxicological evaluations, which predomi...
08
DOI 10.1002/minf.70053
Open DOI
SMILES2Docking: An Open‐Source Desktop Workflow for Ligand Ionization, Stereochemistry‐Aware Preparation and Semi‐Empirical 3D Refinement
SMILES2Docking converts spreadsheet‐based SMILES libraries into docking‐ready 3D ligands through a single, configurable pipeline. Salt and coformer removal, a three‐mode stereocenter policy, prediction of the dominant protonation state w...
09
DOI 10.1002/minf.70051
Open DOI
MSI: A Mahalanobis‐Based Molecular Similarity Index for High‐Dimensional Embeddings
Quantifying molecular similarity is crucial for drug discovery and for exploring chemical space. A similarity assessment always combines two independent ingredients: a molecular representation and a similarity coefficient. The most commo...
10
DOI 10.1002/minf.70050
Open DOI
Mixture‐Quantitative Structure–Property Relationship Approaches for Jet Fuel‐Component Blends: A Review
Jet fuels (JFs) and sustainable aviation fuels (SAFs) are complex hydrocarbon mixtures whose properties must meet strict international specifications to ensure consistent quality. Their increasing variability, driven by environmental and...
Bibliographical & Catalog Notes
Description based on: Vol. 29, no. 1/2 (Jan. 2010); title from cover.
Print issues ceased with 2013.
Latest issue consulted: Vol. 29, no. 1/2 (Jan. 2010).
Also issued online.