Journal of chemical information and modeling
Aug 28, 2025
Antibody-antigen interaction prediction is essential for therapeutic development but remains experimentally costly. The dynamic conformational changes essential to antibody-antigen binding are often missed by structure-based methods relying on static...
PGE2 plays important roles in immune cell function and in potentiating tissue regeneration. 15-PGDH is the key enzyme involved in inactivation of PGE2 and its inhibition therefore provides valuable therapeutic opportunity. We have solved the first co...
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to accumulate mutations in the spike receptor-binding domain (RBD) region, leading to the emergence of new variants that potentially change the binding affinity for the human angi...
Journal of chemical information and modeling
Aug 14, 2025
Identifying functional sites of RNA, particularly those where small molecules bind, is crucial for understanding related biological processes and advancing drug design. Small molecule therapies, compared to traditional protein-targeted therapies, hav...
Journal of chemical information and modeling
Aug 12, 2025
Accurate modeling of protein-peptide interactions is essential for understanding fundamental biological processes and designing peptide-based drugs. However, predicting the complex structures of these interactions remains challenging, primarily due t...
Journal of chemical information and modeling
Aug 11, 2025
Noncanonical amino acids (NCAAs) occupy an important place, both in natural biology and in synthetic applications. However, modeling these amino acids still lies outside the capabilities of most deep learning methods due to sparse training data sets ...
This study explores how topological indices (TIs), which are mathematical descriptors of a drug's molecular structure, can support to predict vital properties and biological activities. This understanding is a key for more effective drug design. We f...
Journal of chemical information and modeling
Aug 4, 2025
Machine learning (ML) has become a standard tool for the exploration of the chemical space. Much of the performance of such models depends on the chosen database for a given task. Here, this aspect is investigated for "chemical tasks" including the p...
The 3D structure of molecules contains a wealth of important information, but traditional 3DCNN-based methods fail to adequately address the transformations of rigid motions (rotation, translation, and mapping). Equivariant graph neural networks (EGN...
Journal of chemical information and modeling
Jul 25, 2025
To understand the benefits and drawbacks of 3D combinatorial and deep learning generators, a novel benchmark was created focusing on the recreation of important protein-ligand interactions and 3D ligand conformations. Using the BindingMOAD data set w...
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