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Models, Molecular

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Machine Learning-Based Prediction of Reduction Potentials for Pt Complexes.

Journal of chemical information and modeling Apr 29, 2024
Some of the well-known drawbacks of clinically approved Pt complexes can be overcome using six-coordinate Pt complexes as inert prodrugs, which release the corresponding four-coordinate active Pt species upon reduction by cellular reducing agents. Th...
Coordination Complexes Machine Learning Oxidation-Reduction Models, Molecular Prodrugs
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Generative artificial intelligence for de novo protein design.

Current opinion in structural biology Apr 24, 2024
Engineering new molecules with desirable functions and properties has the potential to extend our ability to engineer proteins beyond what nature has so far evolved. Advances in the so-called 'de novo' design problem have recently been brought forwar...
Artificial Intelligence Protein Conformation Proteins Protein Engineering Models, Molecular
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DEBFold: Computational Identification of RNA Secondary Structures for Sequences across Structural Families Using Deep Learning.

Journal of chemical information and modeling Apr 22, 2024
It is now known that RNAs play more active roles in cellular pathways beyond simply serving as transcription templates. These biological mechanisms might be mediated by higher RNA stereo conformations, triggering the need to understand RNA secondary ...
Thermodynamics Deep Learning Base Sequence Models, Molecular Computational Biology Nucleic Acid Conformation RNA
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Generalized biomolecular modeling and design with RoseTTAFold All-Atom.

Science (New York, N.Y.) Apr 19, 2024
Deep-learning methods have revolutionized protein structure prediction and design but are presently limited to protein-only systems. We describe RoseTTAFold All-Atom (RFAA), which combines a residue-based representation of amino acids and DNA bases w...
Protein Engineering Proteins Crystallography DNA Deep Learning Models, Molecular Amino Acids
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Machine Learning of Three-Dimensional Protein Structures to Predict the Functional Impacts of Genome Variation.

Journal of chemical information and modeling Apr 18, 2024
Research in the human genome sciences generates a substantial amount of genetic data for hundreds of thousands of individuals, which concomitantly increases the number of variants of unknown significance (VUS). Bioinformatic analyses can successfully...
Humans Genome, Human Protein Conformation NF-E2-Related Factor 2 Proto-Oncogene Proteins c-myc Models, Molecular Machine Learning Genetic Variation Computational Biology
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Encoding the space of protein-protein binding interfaces by artificial intelligence.

Computational biology and chemistry Apr 18, 2024
The physical interactions between proteins are largely determined by the structural properties at their binding interfaces. It was found that the binding interfaces in distinctive protein complexes are highly similar. The structural properties underl...
Models, Molecular Protein Conformation Binding Sites Protein Binding Proteins Artificial Intelligence
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Protein Engineering with Lightweight Graph Denoising Neural Networks.

Journal of chemical information and modeling Apr 17, 2024
Protein engineering faces challenges in finding optimal mutants from a massive pool of candidate mutants. In this study, we introduce a deep-learning-based data-efficient fitness prediction tool to steer protein engineering. Our methodology establish...
Protein Conformation Protein Engineering Models, Molecular Mutation Deep Learning Neural Networks, Computer Proteins
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Apprehensions and emerging solutions in ML-based protein structure prediction.

Current opinion in structural biology Apr 16, 2024
The three-dimensional structure of proteins determines their function in vital biological processes. Thus, when the structure is known, the molecular mechanism of protein function can be understood in more detail and obtained information utilized in ...
Protein Conformation Proteins Models, Molecular Machine Learning Computational Biology
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Modeling Zinc Complexes Using Neural Networks.

Journal of chemical information and modeling Apr 8, 2024
Understanding the energetic landscapes of large molecules is necessary for the study of chemical and biological systems. Recently, deep learning has greatly accelerated the development of models based on quantum chemistry, making it possible to build...
Models, Molecular Molecular Dynamics Simulation Neural Networks, Computer Zinc Coordination Complexes Thermodynamics Quantum Theory Molecular Conformation
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ALDELE: All-Purpose Deep Learning Toolkits for Predicting the Biocatalytic Activities of Enzymes.

Journal of chemical information and modeling Apr 4, 2024
Rapidly predicting enzyme properties for catalyzing specific substrates is essential for identifying potential enzymes for industrial transformations. The demand for sustainable production of valuable industry chemicals utilizing biological resources...
Enzymes Deep Learning Models, Molecular Biocatalysis Protein Conformation
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