AIMC Topic: Models, Molecular

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Ligand-based pharmacophore modeling and machine learning for the discovery of potent aurora A kinase inhibitory leads of novel chemotypes.

Molecular diversity Mar 6, 2024
Aurora-A (AURKA) is serine/threonine protein kinase involved in the regulation of numerous processes of cell division. Numerous studies have demonstrated strong association between AURKA and cancer. AURKA is overexpressed in many cancers, such as col...
Drug Discovery Models, Molecular Humans Machine Learning Protein Kinase Inhibitors Pharmacophore Aurora Kinase A Ligands Quantitative Structure-Activity Relationship
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Epitope Identification of an mGlu5 Receptor Nanobody Using Physics-Based Molecular Modeling and Deep Learning Techniques.

Journal of chemical information and modeling Feb 29, 2024
The world has witnessed a revolution in therapeutics with the development of biological medicines such as antibodies and antibody fragments, notably nanobodies. These nanobodies possess unique characteristics including high specificity and modulatory...
Protein Conformation Single-Domain Antibodies Animals Epitope Mapping Deep Learning Epitopes Molecular Dynamics Simulation Receptor, Metabotropic Glutamate 5 Rats Models, Molecular
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Investigating the ability of deep learning-based structure prediction to extrapolate and/or enrich the set of antibody CDR canonical forms.

Frontiers in immunology Feb 28, 2024
Deep learning models have been shown to accurately predict protein structure from sequence, allowing researchers to explore protein space from the structural viewpoint. In this paper we explore whether "novel" features, such as distinct loop conforma...
Complementarity Determining Regions Antibodies Deep Learning Protein Conformation Models, Molecular
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Automated model building and protein identification in cryo-EM maps.

Nature Feb 26, 2024
Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention in three-dimensional computer graphics programs. Here we present ModelAngelo, a machine-learning approa...
Neural Networks, Computer Markov Chains Protein Conformation Computer Graphics Cryoelectron Microscopy Models, Molecular Amino Acid Sequence Machine Learning Proteins
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Improved QSAR models for PARP-1 inhibition using data balancing, interpretable machine learning, and matched molecular pair analysis.

Molecular diversity Feb 20, 2024
The poly (ADP-ribose) polymerase-1 (PARP-1) enzyme is an important target in the treatment of breast cancer. Currently, treatment options include the drugs Olaparib, Niraparib, Rucaparib, and Talazoparib; however, these drugs can cause severe side ef...
Models, Molecular Quantitative Structure-Activity Relationship Machine Learning Algorithms Poly(ADP-ribose) Polymerase Inhibitors Phthalazines Poly (ADP-Ribose) Polymerase-1 Humans
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Investigation of bacterial DNA gyrase Inhibitor classification models and structural requirements utilizing multiple machine learning methods.

Molecular diversity Feb 19, 2024
Infections from multidrug-resistant (MDR) bacteria have emerged as a paramount global health concern, and the therapeutic effectiveness of current treatments is swiftly diminishing. An urgent need exists to explore innovative strategies for counterin...
Machine Learning Anti-Bacterial Agents Topoisomerase II Inhibitors Models, Molecular Molecular Docking Simulation DNA Gyrase Bacteria
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Recent Progress of Protein Tertiary Structure Prediction.

Molecules (Basel, Switzerland) Feb 13, 2024
The prediction of three-dimensional (3D) protein structure from amino acid sequences has stood as a significant challenge in computational and structural bioinformatics for decades. Recently, the widespread integration of artificial intelligence (AI)...
Databases, Protein Models, Molecular Protein Folding Protein Conformation Computational Biology Proteins Software Algorithms Artificial Intelligence
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De novo design of cavity-containing proteins with a backbone-centered neural network energy function.

Structure (London, England : 1993) Feb 6, 2024
The design of small-molecule-binding proteins requires protein backbones that contain cavities. Previous design efforts were based on naturally occurring cavity-containing backbone architectures. Here, we designed diverse cavity-containing backbones ...
Neural Networks, Computer Models, Molecular Protein Conformation Proteins
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Machine learning in RNA structure prediction: Advances and challenges.

Biophysical journal Jan 30, 2024
RNA molecules play a crucial role in various biological processes, with their functionality closely tied to their structures. The remarkable advancements in machine learning techniques for protein structure prediction have shown promise in the field ...
Nucleic Acid Conformation Machine Learning Models, Molecular RNA
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Predictive modeling and cryo-EM: A synergistic approach to modeling macromolecular structure.

Biophysical journal Jan 23, 2024
Over the last 15 years, structural biology has seen unprecedented development and improvement in two areas: electron cryo-microscopy (cryo-EM) and predictive modeling. Once relegated to low resolutions, single-particle cryo-EM is now capable of achie...
Proteins Models, Molecular Machine Learning Cryoelectron Microscopy Macromolecular Substances Protein Conformation
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