Journal of chemical information and modeling

01 16 October 2026

DOI 10.1021/acs.jcim.6c01050

An Integrated Computational-Experimental Workflow for Fungal Peroxygenase Discovery and Enzyme–Substrate Prediction

Open DOI

Victor J. Y. Lim, Yee-Song Law, Guangrong Peh et al.

Recent advances in enzyme informatics have produced increasingly powerful general models for the prediction of protein function prediction. However, their performance remains limited for underexplored enzyme families where experimental d...

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02 16 October 2026

DOI 10.1021/acs.jcim.6c02792

Kinase Inhibitors can Change Protonation or Tautomeric State upon Binding

Open DOI

Gehan A. Ranepura, Saqibul I. Chowdhury, Elizabeth A. Rosenzweig et al.

The binding affinity of a ligand to a protein is influenced by the protonation and tautomeric states of both partners. However, this relationship remains under-investigated due to the limited availability of computational tools capable o...

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03 16 October 2026

DOI 10.1021/acs.jcim.6c02504

Ga3+ Replacing of Fe3+ as a “Trojan Horse” Antimicrobial Strategy: Modeling the Process within Bacterial Catalase–Peroxidase KatG

Open DOI

Lorenzo Gramolini, Richard LópEz-Corbalán, Jorge García-Millán et al.

Replacement of Fe3+ by Ga3+ has emerged as a promising “Trojan horse” antimicrobial strategy in response to the growing threat of antibiotic-resistant bacteria. Because many bacterial proteins hijack host iron to sustain essential redox ...

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04 16 October 2026

DOI 10.1021/acs.jcim.6c03208

Interpretive Limits of Cross-Split AUPRC Differences in Deep Learning-Based Antibiotic Screening

Open DOI

Zhijie Pan, Tianming Han, Wenchi Ge et al.

Deep learning expands the chemical space accessible to antibiotic discovery, making interpretation of evaluation results increasingly important when only a few compounds can be prioritized from vast candidate libraries. AUPRC depends on ...

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05 16 October 2026

DOI 10.1021/acs.jcim.6c01542

Building a Physically Interpretable Compressed Chemical Space via Grid-Based Optimization

Open DOI

Seungmin Yoon, Alex Dickson

In recent years, deep generative models have been increasingly adopted for molecular optimization and design. In many such models, molecules are encoded into latent spaces that provide compact representations of their features. However, ...

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06 16 October 2026

DOI 10.1021/acs.jcim.6c01975

Cross-Modal Semantic Alignment for Cold-Start Drug–Target Interaction Prediction

Open DOI

Jia He, Le Chen, Wenqi Fang et al.

Drug–target interaction (DTI) prediction is essential for drug discovery, yet existing models often suffer from limited generalization when drugs or targets are unseen during training. This challenge is particularly severe in cold-start ...

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07 16 October 2026

DOI 10.1021/acs.jcim.6c00645

CASyM: Chemotype Annotation through Synthesis Mapping

Open DOI

Paula Torren-Peraire, Jonas Verhoeven, Dorota Herman et al.

The identification and annotation of chemotypes is central to structure–activity relationship studies and property optimization in drug discovery. Current computational approaches rely on predefined fragmentation rules or structural simi...

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08 15 October 2026

DOI 10.1021/acs.jcim.6c01373

Subpocket-Aware Fragment-Based Docking Pipeline for Kinase Ligand Design: Methodology and a PKA Case Study

Open DOI

Katharina Buchthal, Paula Linh Kramer, Dominik Hubach et al.

Protein kinases regulate signal transduction through phosphorylation, and their dysregulation drives diseases like cancer, autoimmune disorders, and Alzheimer’s, making them key drug targets. Fragment-based drug design offers a powerful ...

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09 15 October 2026

DOI 10.1021/acs.jcim.6c02502

UCEC: A Knowledge Graph-Assisted Machine Learning for Molecular-Mechanism-Interpretable Natural Product-Disease Association Prioritization

Open DOI

Wenyu Lu, Yihui Cai, Xiaoqian Peng et al.

Natural products (NPs) have been considered a critical source of therapeutic drugs, but prioritizing NP-disease associations remain challenging because supporting evidence is distributed across multiple ingredients, targets, protein inte...

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10 15 October 2026

DOI 10.1021/acs.jcim.6c02262

Integrating Gaussian Accelerated Molecular Dynamics, β-Variational Autoencoders, and Markov State Models Reveals the Activation Landscape of FGFR3 Kinase

Open DOI

Subhasmita Mahapatra, Parimal Kar

Fibroblast growth factor receptor 3 (FGFR3) kinase plays a crucial role in cellular differentiation, proliferation, and skeletal development. Activation of the kinase domain through phosphorylation regulates the downstream signaling casc...

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