AIMC Topic: Quantum Theory
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Accelerating reliable multiscale quantum refinement of protein-drug systems enabled by machine learning.
Nature communications
May 16, 2024
Biomacromolecule structures are essential for drug development and biocatalysis. Quantum refinement (QR) methods, which employ reliable quantum mechanics (QM) methods in crystallographic refinement, showed promise in improving the structural quality ...
Advancing biomolecular simulation through exascale HPC, AI and quantum computing.
Current opinion in structural biology
May 10, 2024
Biomolecular simulation can act as both a digital microscope and a crystal ball; offering the potential for a deeper understanding of experimental observations whilst also presenting a forward-looking avenue for the in silico design and evaluation of...
MISATO: machine learning dataset of protein-ligand complexes for structure-based drug discovery.
Nature computational science
May 10, 2024
Large language models have greatly enhanced our ability to understand biology and chemistry, yet robust methods for structure-based drug discovery, quantum chemistry and structural biology are still sparse. Precise biomolecule-ligand interaction data...
Carbon-based molecular properties efficiently predicted by deep learning-based quantum chemical simulation with large language models.
Computers in biology and medicine
May 1, 2024
The prediction of thermodynamic properties of carbon-based molecules based on their geometrical conformation using fluctuation and density functional theories has achieved great success in the field of energy chemistry, while the excessive computatio...
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...
Predicting Solvatochromism of Chromophores in Proteins through QM/MM and Machine Learning.
The journal of physical chemistry. A
Apr 29, 2024
Solvatochromism occurs in both homogeneous solvents and more complex biological environments, such as proteins. While in both cases the solvatochromic effects report on the surroundings of the chromophore, their interpretation in proteins becomes mor...
From GPUs to AI and quantum: three waves of acceleration in bioinformatics.
Drug discovery today
Apr 23, 2024
The enormous growth in the amount of data generated by the life sciences is continuously shifting the field from model-driven science towards data-driven science. The need for efficient processing has led to the adoption of massively parallel acceler...
How exascale computing can shape drug design: A perspective from multiscale QM/MM molecular dynamics simulations and machine learning-aided enhanced sampling algorithms.
Current opinion in structural biology
Apr 16, 2024
Molecular simulations are an essential asset in the first steps of drug design campaigns. However, the requirement of high-throughput limits applications mainly to qualitative approaches with low computational cost, but also low accuracy. Unlocking t...
Biomarker discovery with quantum neural networks: a case-study in CTLA4-activation pathways.
BMC bioinformatics
Apr 12, 2024
BACKGROUND: Biomarker discovery is a challenging task due to the massive search space. Quantum computing and quantum Artificial Intelligence (quantum AI) can be used to address the computational problem of biomarker discovery from genetic data.
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...
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