AIMC Topic: Models, Molecular

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MolLoG: A Molecular Level Interpretability Model Bridging Local to Global for Predicting Drug Target Interactions.

Journal of chemical information and modeling May 6, 2024
Developing new pharmaceuticals is a costly and time-consuming endeavor fraught with significant safety risks. A critical aspect of drug research and disease therapy is discerning the existence of interactions between drugs and proteins. The evolution...
Proteins Drug Discovery Deep Learning Models, Molecular Pharmaceutical Preparations
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Cryo2StructData: A Large Labeled Cryo-EM Density Map Dataset for AI-based Modeling of Protein Structures.

Scientific data May 6, 2024
The advent of single-particle cryo-electron microscopy (cryo-EM) has brought forth a new era of structural biology, enabling the routine determination of large biological molecules and their complexes at atomic resolution. The high-resolution structu...
Proteins Models, Molecular Artificial Intelligence Protein Conformation Cryoelectron Microscopy
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Reactivities of acrylamide warheads toward cysteine targets: a QM/ML approach to covalent inhibitor design.

Journal of computer-aided molecular design May 1, 2024
Covalent inhibition offers many advantages over non-covalent inhibition, but covalent warhead reactivity must be carefully balanced to maintain potency while avoiding unwanted side effects. While warhead reactivities are commonly measured with assays...
Humans Models, Molecular Molecular Structure Quantitative Structure-Activity Relationship Machine Learning Drug Design Acrylamide Cysteine Quantum Theory Linear Models
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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 Models, Molecular Machine Learning Prodrugs Oxidation-Reduction
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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...
Protein Conformation Protein Engineering Artificial Intelligence Proteins 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 Computational Biology Base Sequence Models, Molecular 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...
Amino Acids Protein Engineering DNA Models, Molecular Crystallography Deep Learning Proteins
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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 Proto-Oncogene Proteins c-myc Machine Learning Models, Molecular NF-E2-Related Factor 2 Protein Conformation Computational Biology Genetic Variation
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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 Neural Networks, Computer Protein Engineering Models, Molecular Mutation Deep Learning Proteins
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