AIMC Topic: Protein Binding

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Machine Learning Methods as a Cost-Effective Alternative to Physics-Based Binding Free Energy Calculations.

Molecules (Basel, Switzerland) Feb 13, 2024
The rank ordering of ligands remains one of the most attractive challenges in drug discovery. While physics-based in silico binding affinity methods dominate the field, they still have problems, which largely revolve around forcefield accuracy and sa...
Machine Learning Binding Sites Proteins Thermodynamics Ligands Retrospective Studies Physics Cost-Benefit Analysis Protein Binding
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Predicting DNA structure using a deep learning method.

Nature communications Feb 9, 2024
Understanding the mechanisms of protein-DNA binding is critical in comprehending gene regulation. Three-dimensional DNA structure, also described as DNA shape, plays a key role in these mechanisms. In this study, we present a deep learning-based meth...
Proteins DNA Machine Learning Deep Learning Protein Binding
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A deep learning-based theoretical protocol to identify potentially isoform-selective PI3Kα inhibitors.

Molecular diversity Feb 2, 2024
Phosphoinositide 3-kinase alpha (PI3Kα) is one of the most frequently dysregulated kinases known for their pivotal role in many oncogenic diseases. While the side effects linked to existing drugs against PI3Kα-induced cancers provide an avenue for fu...
Molecular Docking Simulation Drug Design Humans Ligands Deep Learning Protein Binding Protein Kinase Inhibitors Class I Phosphatidylinositol 3-Kinases Phosphoinositide-3 Kinase Inhibitors Phosphatidylinositol 3-Kinases
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Evaluating NetMHCpan performance on non-European HLA alleles not present in training data.

Frontiers in immunology Jan 16, 2024
Bias in neural network model training datasets has been observed to decrease prediction accuracy for groups underrepresented in training data. Thus, investigating the composition of training datasets used in machine learning models with healthcare ap...
Genes, MHC Class I Protein Binding Humans Alleles Peptides Histocompatibility Antigens Class I
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T6496 targeting EGFR mediated by T790M or C797S mutant: machine learning, virtual screening and bioactivity evaluation study.

Journal of biomolecular structure & dynamics Jan 4, 2024
Acquired resistance to EGFR is a major impediment in lung cancer treatment, highlighting the urgent need to discover novel compounds to overcome EGFR drug resistance. In this study, we utilized in silico methods and bioactivity evaluation for drug di...
Protein Binding Cell Proliferation Apoptosis Drug Discovery Antineoplastic Agents Cell Line, Tumor ErbB Receptors Protein Kinase Inhibitors Drug Screening Assays, Antitumor Mutation Drug Resistance, Neoplasm Humans Machine Learning Molecular Docking Simulation
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Bound ion effects: Using machine learning method to study the kinesin Ncd's binding with microtubule.

Biophysical journal Dec 30, 2023
Drosophila Ncd proteins are motor proteins that play important roles in spindle organization. Ncd and the tubulin dimer are highly charged. Thus, it is crucial to investigate Ncd-tubulin dimer interactions in the presence of ions, especially ions tha...
Drosophila Proteins Static Electricity Tubulin Solvents Machine Learning Protein Multimerization Protein Binding Microtubules Kinesins Molecular Dynamics Simulation Animals Ions
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Harnessing deep learning for enhanced ligand docking.

Trends in pharmacological sciences Dec 30, 2023
Ligand docking (LD), a technology for predicting protein-ligand (PL)-binding conformations and strengths, plays key roles in virtual screening (VS). However, the accuracy and speed of current LD methodologies remain suboptimal. Here, we discuss how d...
Molecular Docking Simulation Deep Learning Protein Conformation Humans Protein Binding Proteins Ligands
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Investigating the bispecific lead compounds against methicillin-resistant SarA and CrtM using machine learning and molecular dynamics approach.

Journal of biomolecular structure & dynamics Dec 26, 2023
Methicillin-resistant Staphylococcus aureus (MRSA) is a notorious pathogen that has emerged as a serious global health concern over the past few decades. Staphylococcal accessory regulator A (SarA) and 4,4'-diapophytoene synthase (CrtM) play a crucia...
Molecular Docking Simulation Biofilms Protein Binding Methicillin-Resistant Staphylococcus aureus Bacterial Proteins Molecular Dynamics Simulation Machine Learning Anti-Bacterial Agents Quantitative Structure-Activity Relationship Hydrogen Bonding
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Deep learning-based design and screening of benzimidazole-pyrazine derivatives as adenosine A receptor antagonists.

Journal of biomolecular structure & dynamics Dec 22, 2023
The Adenosine A receptor (AAR) is considered a novel potential target for the immunotherapy of cancer, and AAR antagonists have an inhibitory effect on tumor growth, proliferation, and metastasis. In our previous studies, we identified a class of ben...
Adenosine A2 Receptor Antagonists Receptor, Adenosine A2B Protein Binding Pyrazines Structure-Activity Relationship Molecular Docking Simulation Drug Design Molecular Structure Humans Deep Learning Molecular Dynamics Simulation Benzimidazoles
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Evaluation of DNA-protein complex structures using the deep learning method.

Physical chemistry chemical physics : PCCP Dec 21, 2023
Biological processes such as transcription, repair, and regulation require interactions between DNA and proteins. To unravel their functions, it is imperative to determine the high-resolution structures of DNA-protein complexes. However, experimental...
Protein Binding Proteins DNA Neural Networks, Computer Research Design Deep Learning
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