AIMC Topic: Drug Design

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Design, Synthesis, and Aphicidal Activity of Novel Insect Neuropeptide Kinin Receptor Antagonists, Targeting the Ser Ligand Position.

Journal of agricultural and food chemistry
Traditional chemical pesticides have raised significant environmental and health concerns, driving the pursuit of safer alternatives. Aphids, notorious for causing extensive agricultural damage and transmitting plant diseases, represent prime targets...

Enhancing accuracy of virtual kinase profiling via application of graph neural network to 3D pharmacophore ensembles.

Journal of computer-aided molecular design
Kinase profiling is an essential step in both hit identification and selectivity evaluation. Since in vitro testing of large chemical libraries is costly and time-consuming, a computational approach can be applied to narrow down the reasonable chemic...

Investigate the potential inhibitors of sphingosine kinase 1 (SphK1) with molecular dynamics and artificial intelligence drug design methods.

Journal of molecular modeling
CONTEXT: Sphingosine kinase 1 (SphK1) is a sphingosine kinase that can catalyze the phosphorylation of sphingosine to generate sphingosine-1-phosphate. The J-type channel of SPHK1 plays an important role in processes such as cell signaling. Therefore...

Structure based drug design and machine learning approaches for identifying natural inhibitors against the human αβIII tubulin isotype.

Scientific reports
Microtubules (MTs) play a crucial role in mitosis and are composed of α-/β-tubulin heterodimeric subunits. In eukaryotes, eight α-tubulin and ten β-tubulin isotypes have been reported, each displaying tissue-specific expression patterns. Among them, ...

De novo design of potent inhibitors of clostridial family toxins.

Proceedings of the National Academy of Sciences of the United States of America
remains a leading cause of hospital-acquired infections, with its primary virulence factor, toxin B (TcdB), responsible for severe colitis and recurrent disease. The closely related toxin, TcsL, from , causes a rarer but often fatal toxic shock synd...

Integrating Machine Learning into Free Energy Perturbation Workflows.

Journal of chemical information and modeling
Free energy perturbation (FEP) methods are among the most accurate tools in structure-based drug design for predicting protein-ligand binding affinities. However, their adoption remains limited due to high computational demands and complex setup proc...

HPDAF: A practical tool for predicting drug-target binding affinity using multimodal features.

European journal of medicinal chemistry
Accurate prediction of drug-target binding affinity is crucial for efficient drug discovery and design, enabling researchers to better understand molecular interactions and accelerate the identification of promising drug candidates. Despite recent ad...

In Search of Beautiful Molecules: A Perspective on Generative Modeling for Drug Design.

Journal of chemical information and modeling
Generative modeling with artificial intelligence (GenAI) offers an emerging approach to discover novel, efficacious, and safe drugs by enabling the systematic exploration of chemical space and to design molecules that are synthesizable while also hav...

Knowledge and Structure-Based Drug Design of 15-PGDH Inhibitors.

Journal of medicinal chemistry
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...

AI-Designed Molecules in Drug Discovery, Structural Novelty Evaluation, and Implications.

Journal of chemical information and modeling
Achieving structural novelty in drug discovery remains a critical challenge. Artificial intelligence (AI) has demonstrated remarkable potential in deciphering the complex relationships between molecular structures and activities from vast amounts of ...