AIMC Topic: Quantum Theory

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The next revolution in computational simulations: Harnessing AI and quantum computing in molecular dynamics.

Current opinion in structural biology
The integration of artificial intelligence, machine learning and quantum computing into molecular dynamics simulations is catalyzing a revolution in computational biology, improving the accuracy and efficiency of simulations. This review describes th...

Predicting DNA Reactions with a Quantum Chemistry-Based Deep Learning Model.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
In this study, a deep learning model based on quantum chemistry is introduced to enhance the accuracy and efficiency of predicting DNA reaction parameters. By integrating quantum chemical calculations with self-designed descriptor matrices, the model...

Exploring the Global Reaction Coordinate for Retinal Photoisomerization: A Graph Theory-Based Machine Learning Approach.

Journal of chemical information and modeling
Unraveling the reaction pathway of photoinduced reactions poses a great challenge owing to its complexity. Recently, graph theory-based machine learning combined with nonadiabatic molecular dynamics (NAMD) has been applied to obtain the global reacti...

SmartCADD: AI-QM Empowered Drug Discovery Platform with Explainability.

Journal of chemical information and modeling
Artificial intelligence (AI) has emerged as a pivotal force in enhancing productivity across various sectors, with its impact being profoundly felt within the pharmaceutical and biotechnology domains. Despite AI's rapid adoption, its integration into...

Quantum mechanical electronic and geometric parameters for DNA k-mers as features for machine learning.

Scientific data
We are witnessing a steep increase in model development initiatives in genomics that employ high-end machine learning methodologies. Of particular interest are models that predict certain genomic characteristics based solely on DNA sequence. These mo...

Predicting routes of phase I and II metabolism based on quantum mechanics and machine learning.

Xenobiotica; the fate of foreign compounds in biological systems
Unexpected metabolism could lead to the failure of many late-stage drug candidates or even the withdrawal of approved drugs. Thus, it is critical to predict and study the dominant routes of metabolism in the early stages of research.We describe the d...

Modern finance through quantum computing-A systematic literature review.

PloS one
Human intellectual restlessness originates from the need for knowledge of the modern world. The financial world is struggling to prototype accurate and fast data at low risk. The quantum approach to finance can support this desire. The goal of this p...

Near-Term Quantum Classification Algorithms Applied to Antimalarial Drug Discovery.

Journal of chemical information and modeling
Computational approaches are widely applied in drug discovery to explore properties related to bioactivity, physiochemistry, and toxicology. Over at least the last 20 years, the exploitation of machine learning on molecular data sets has been used to...

Quantum-level machine learning calculations of Levodopa.

Computational biology and chemistry
Many drug molecules contain functional groups, resulting in a torsional barrier corresponding to rotation around the bond linking the fragments. In medicinal chemistry and pharmaceutical sciences, inclusive of drug design studies, the exact calculati...

Gradient-based optimization for quantum architecture search.

Neural networks : the official journal of the International Neural Network Society
Quantum Architecture Search (QAS) has shown significant promise in designing quantum circuits for Variational Quantum Algorithms (VQAs). However, existing QAS algorithms primarily explore circuit architectures within a discrete space, which is inhere...