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Quantum Theory

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The study of dual COX-2/5-LOX inhibitors by using electronic-topological approach based on data on the ligand-receptor interactions.

Journal of molecular graphics & modelling
Structural and electronic factors influencing selective inhibition of cyclooxygenase-2 and 5-lipoxygenase (COX-2/5-LOX) were studied by using Electronic-Topological Method combined with Neural Networks (ETM-NN), molecular docking, and Density Functio...

Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach.

Journal of chemical theory and computation
Chemically accurate and comprehensive studies of the virtual space of all possible molecules are severely limited by the computational cost of quantum chemistry. We introduce a composite strategy that adds machine learning corrections to computationa...

Dicke simulators with emergent collective quantum computational abilities.

Physical review letters
Using an approach inspired from spin glasses, we show that the multimode disordered Dicke model is equivalent to a quantum Hopfield network. We propose variational ground states for the system at zero temperature, which we conjecture to be exact in t...

Machine learning in computational docking.

Artificial intelligence in medicine
OBJECTIVE: The objective of this paper is to highlight the state-of-the-art machine learning (ML) techniques in computational docking. The use of smart computational methods in the life cycle of drug design is relatively a recent development that has...

The Quest for Cognition in Purposive Action: From Cybernetics to Quantum Computing.

Journal of integrative neuroscience
Norbert Wiener and Nikolai Bernstein set the stage for a worldwide multidisciplinary attempt to understand how purposive action is integrated with cognition in a circular, bidirectional manner, both in life sciences and engineering. Such a 'workshop'...

A deep transfer learning-based protocol accelerates full quantum mechanics calculation of protein.

Briefings in bioinformatics
Effective full quantum mechanics (FQM) calculation of protein remains a grand challenge and of great interest in computational biology with substantial applications in drug discovery, protein dynamic simulation and protein folding. However, the huge ...

Interatomic force from neural network based variational quantum Monte Carlo.

The Journal of chemical physics
Accurate ab initio calculations are of fundamental importance in physics, chemistry, biology, and materials science, which have witnessed rapid development in the last couple of years with the help of machine learning computational techniques such as...

Gell-Mann-Low Criticality in Neural Networks.

Physical review letters
Criticality is deeply related to optimal computational capacity. The lack of a renormalized theory of critical brain dynamics, however, so far limits insights into this form of biological information processing to mean-field results. These methods ne...

Artificial Intelligence and Quantum Computing as the Next Pharma Disruptors.

Methods in molecular biology (Clifton, N.J.)
Artificial intelligence (AI) consists of a synergistic assembly of enhanced optimization strategies with wide application in drug discovery and development, providing advanced tools for promoting cost-effectiveness throughout drug life cycle. Specifi...

Mol2Context-vec: learning molecular representation from context awareness for drug discovery.

Briefings in bioinformatics
With the rapid development of proteomics and the rapid increase of target molecules for drug action, computer-aided drug design (CADD) has become a basic task in drug discovery. One of the key challenges in CADD is molecular representation. High-qual...