AIMC Topic: Models, Molecular

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Modelling protein complexes with crosslinking mass spectrometry and deep learning.

Nature communications Sep 9, 2024
Scarcity of structural and evolutionary information on protein complexes poses a challenge to deep learning-based structure modelling. We integrate experimental distance restraints obtained by crosslinking mass spectrometry (MS) into AlphaFold-Multim...
Cross-Linking Reagents Mass Spectrometry Models, Molecular Bacterial Proteins Protein Conformation Iron Deep Learning Bacillus subtilis
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Pretrainable geometric graph neural network for antibody affinity maturation.

Nature communications Sep 6, 2024
Increasing the binding affinity of an antibody to its target antigen is a crucial task in antibody therapeutics development. This paper presents a pretrainable geometric graph neural network, GearBind, and explores its potential in in silico affinity...
Neural Networks, Computer Computer Simulation Deep Learning Humans Antibodies Antigens Antibody Affinity Enzyme-Linked Immunosorbent Assay Models, Molecular Protein Binding
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Conformational Space Profiling Enhances Generic Molecular Representation for AI-Powered Ligand-Based Drug Discovery.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Aug 29, 2024
The molecular representation model is a neural network that converts molecular representations (SMILES, Graph) into feature vectors, and is an essential module applied across a wide range of artificial intelligence-driven drug discovery scenarios. Ho...
Molecular Conformation Drug Discovery Neural Networks, Computer Artificial Intelligence Models, Molecular Ligands
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Predicting the Binding of Small Molecules to Proteins through Invariant Representation of the Molecular Structure.

Journal of chemical information and modeling Aug 28, 2024
We present a computational scheme for predicting the ligands that bind to a pocket of a known structure. It is based on the generation of a general abstract representation of the molecules, which is invariant to rotations, translations, and permutati...
Ligands Protein Conformation Binding Sites Models, Molecular Molecular Structure Small Molecule Libraries Machine Learning Protein Binding Proteins Algorithms
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An end-to-end framework for the prediction of protein structure and fitness from single sequence.

Nature communications Aug 27, 2024
Significant research progress has been made in the field of protein structure and fitness prediction. Particularly, single-sequence-based structure prediction methods like ESMFold and OmegaFold achieve a balance between inference speed and prediction...
Algorithms Computational Biology Proteins Neural Networks, Computer Protein Stability Models, Molecular Protein Conformation Sequence Analysis, Protein Mutation
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Generative artificial intelligence performs rudimentary structural biology modeling.

Scientific reports Aug 21, 2024
Natural language-based generative artificial intelligence (AI) has become increasingly prevalent in scientific research. Intriguingly, capabilities of generative pre-trained transformer (GPT) language models beyond the scope of natural language tasks...
Coronavirus 3C Proteases Models, Molecular COVID-19 SARS-CoV-2 Amino Acids Protein Conformation Humans Artificial Intelligence
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Chemical analogue based drug design for cancer treatment targeting PI3K: integrating machine learning and molecular modeling.

Molecular diversity Aug 17, 2024
Cancer is a generic term for a group of disorders defined by uncontrolled cell growth and the potential to invade or spread to other parts of the body. Gene and epigenetic alterations disrupt normal cellular control, leading to abnormal cell prolifer...
Humans Neoplasms Molecular Docking Simulation Machine Learning Protein Binding Models, Molecular Molecular Dynamics Simulation Phosphatidylinositol 3-Kinases Drug Design Antineoplastic Agents Ligands Phosphoinositide-3 Kinase Inhibitors Protein Kinase Inhibitors Class Ib Phosphatidylinositol 3-Kinase
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MCNN_MC: Computational Prediction of Mitochondrial Carriers and Investigation of Bongkrekic Acid Toxicity Using Protein Language Models and Convolutional Neural Networks.

Journal of chemical information and modeling Aug 12, 2024
Mitochondrial carriers (MCs) are essential proteins that transport metabolites across mitochondrial membranes and play a critical role in cellular metabolism. ADP/ATP (adenosine diphosphate/adenosine triphosphate) is one of the most important carrier...
Bongkrekic Acid Mitochondrial ADP, ATP Translocases Humans Neural Networks, Computer Models, Molecular Computational Biology Mitochondria
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High-Throughput Screening and Prediction of Nucleophilicity of Amines Using Machine Learning and DFT Calculations.

Journal of chemical information and modeling Aug 8, 2024
Nucleophilic index () as a significant parameter plays a crucial role in screening of amine catalysts. Indeed, the quantity and variety of amines are extensive. However, only limited amines exhibit an value exceeding 4.0 eV, rendering them potential...
Machine Learning Density Functional Theory Models, Molecular Amines High-Throughput Screening Assays Quantitative Structure-Activity Relationship
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Boosting the performance of molecular property prediction via graph-text alignment and multi-granularity representation enhancement.

Journal of molecular graphics & modelling Aug 5, 2024
Deep learning is playing an increasingly important role in accurate prediction of molecular properties. Prior to being processed by a deep learning model, a molecule is typically represented in the form of a text or a graph. While some methods attemp...
Algorithms Deep Learning Models, Molecular
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