AIMC Topic: Drug Discovery

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Application of Machine Learning (ML) approach in discovery of novel drug targets against Leishmania: A computational based approach.

Computational biology and chemistry Aug 1, 2025
Molecules with potent anti-leishmanial activity play a crucial role in identifying treatments for leishmaniasis and aiding in the design of novel drugs to combat the disease, ultimately protecting individuals and populations. Various methods have bee...
Drug Discovery Antiprotozoal Agents Leishmaniasis Humans Machine Learning Leishmania
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PocketDTA: A pocket-based multimodal deep learning model for drug-target affinity prediction.

Computational biology and chemistry Aug 1, 2025
Drug-target affinity prediction is a fundamental task in the field of drug discovery. Extracting and integrating structural information from proteins effectively is crucial to enhance the accuracy and generalization of prediction, which remains a sub...
Pharmaceutical Preparations Humans Neural Networks, Computer Deep Learning Proteins Drug Discovery
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A small-scale data driven and graph neural network based toxicity prediction method of compounds.

Computational biology and chemistry Aug 1, 2025
Toxicity prediction is crucial in drug discovery, helping identify safe compounds and reduce development risks. However, the lack of known toxicity data for most compounds is a major challenge. Recently, data-driven models have gained attention as a ...
Drug Discovery Graph Neural Networks Drug-Related Side Effects and Adverse Reactions Neural Networks, Computer Humans Machine Learning
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Artificial intelligence revolution in drug discovery: A paradigm shift in pharmaceutical innovation.

International journal of pharmaceutics Jul 25, 2025
Integrating artificial intelligence (AI) into drug discovery has revolutionized pharmaceutical innovation, addressing the challenges of traditional methods that are costly, time-consuming, and suffer from high failure rates. By utilizing machine lear...
Drug Repositioning COVID-19 Drug Treatment Drug Design Humans Drug Discovery Artificial Intelligence
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MSCMLCIDTI: Drug-Target Interaction Prediction Based on Multiscale Feature Extraction and Deep Interactive Attention Fusion Mechanisms.

Journal of computational chemistry Jul 15, 2025
Drug-target interaction prediction serves as a crucial component in accelerating drug discovery. To overcome current limitations in deep learning approaches, specifically the inadequate representation of local features and insufficient modeling of dr...
Humans Proteins Pharmaceutical Preparations Drug Discovery Deep Learning
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Enhancing Drug-Target Interaction Prediction through Transfer Learning from Activity Cliff Prediction Tasks.

Journal of chemical information and modeling Jul 14, 2025
Recently, machine learning (ML) has gained popularity in the early stages of drug discovery. This trend is unsurprising given the increasing volume of relevant experimental data and the continuous improvement of ML algorithms. However, conventional m...
Pharmaceutical Preparations Drug Discovery Proteins Machine Learning
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Distance-Aware Molecular Property Prediction in Nonlinear Structure-Property Space.

Journal of chemical information and modeling Jul 14, 2025
Molecular property prediction with limited data in novel chemical domains remains challenging. We introduce an approach based on the hypothesis that prediction difficulty increases systematically with distance from well-characterized regions in an ap...
Machine Learning Nonlinear Dynamics Drug Discovery Uncertainty
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Advancing Drug Discovery with Enhanced Chemical Understanding via Asymmetric Contrastive Multimodal Learning.

Journal of chemical information and modeling Jul 14, 2025
The versatility of multimodal deep learning holds tremendous promise for advancing scientific research and practical applications. As this field continues to evolve, the collective power of cross-modal analysis promises to drive transformative innova...
Machine Learning Drug Discovery Deep Learning
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CACHE Challenge #2: Targeting the RNA Site of the SARS-CoV-2 Helicase Nsp13.

Journal of chemical information and modeling Jul 14, 2025
A critical assessment of computational hit-finding experiments (CACHE) challenge was conducted to predict ligands for the SARS-CoV-2 Nsp13 helicase RNA binding site, a highly conserved COVID-19 target. Twenty-three participating teams comprised of co...
COVID-19 Drug Treatment Methyltransferases Ligands RNA Helicases Viral Nonstructural Proteins Binding Sites Drug Discovery Antiviral Agents Protein Binding RNA, Viral SARS-CoV-2 Molecular Docking Simulation COVID-19 Humans Machine Learning
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BalancedDiff: Balanced Diffusion Network for High-Quality Molecule Generation.

Journal of chemical information and modeling Jul 14, 2025
Traditional drug discovery and development are time-consuming and expensive. Deep learning-based molecule generation techniques can reduce costs and improve efficiency, helping to generate high-quality molecules with desirable properties. However, ex...
Drug Discovery Deep Learning Diffusion
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