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Molecular Dynamics Simulation

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Machine Learning Enables Selection of Epistatic Enzyme Mutants for Stability Against Unfolding and Detrimental Aggregation.

Chembiochem : a European journal of chemical biology
Machine learning (ML) has pervaded most areas of protein engineering, including stability and stereoselectivity. Using limonene epoxide hydrolase as the model enzyme and innov'SAR as the ML platform, comprising a digital signal process, we achieved h...

AK-Score: Accurate Protein-Ligand Binding Affinity Prediction Using an Ensemble of 3D-Convolutional Neural Networks.

International journal of molecular sciences
Accurate prediction of the binding affinity of a protein-ligand complex is essential for efficient and successful rational drug design. Therefore, many binding affinity prediction methods have been developed. In recent years, since deep learning tech...

DeepFRET, a software for rapid and automated single-molecule FRET data classification using deep learning.

eLife
Single-molecule Förster Resonance energy transfer (smFRET) is an adaptable method for studying the structure and dynamics of biomolecules. The development of high throughput methodologies and the growth of commercial instrumentation have outpaced the...

Profiling SARS-CoV-2 Main Protease (M) Binding to Repurposed Drugs Using Molecular Dynamics Simulations in Classical and Neural Network-Trained Force Fields.

ACS combinatorial science
The current COVID-19 pandemic caused by a novel coronavirus SARS-CoV-2 urgently calls for a working therapeutic. Here, we report a computation-based workflow for efficiently selecting a subset of FDA-approved drugs that can potentially bind to the SA...

Integrated Variational Approach to Conformational Dynamics: A Robust Strategy for Identifying Eigenfunctions of Dynamical Operators.

The journal of physical chemistry. B
One approach to analyzing the dynamics of a physical system is to search for long-lived patterns in its motions. This approach has been particularly successful for molecular dynamics data, where slowly decorrelating patterns can indicate large-scale ...

Learning molecular dynamics with simple language model built upon long short-term memory neural network.

Nature communications
Recurrent neural networks have led to breakthroughs in natural language processing and speech recognition. Here we show that recurrent networks, specifically long short-term memory networks can also capture the temporal evolution of chemical/biophysi...

Evolutionary artificial intelligence based peptide discoveries for effective Covid-19 therapeutics.

Biochimica et biophysica acta. Molecular basis of disease
An epidemic caused by COVID-19 in China turned into pandemic within a short duration affecting countries worldwide. Researchers and companies around the world are working on all the possible strategies to develop a curative or preventive strategy for...

Machine Learning Prediction of Electronic Coupling between the Guanine Bases of DNA.

The journal of physical chemistry. A
Charge transport in deoxyribonucleic acid (DNA) is of immense interest in biology and molecular electronics. Electronic coupling between the DNA bases is an important parameter describing the efficiency of charge transport in DNA. A reasonable estima...

Discovering Protein Conformational Flexibility through Artificial-Intelligence-Aided Molecular Dynamics.

The journal of physical chemistry. B
Proteins sample a variety of conformations distinct from their crystal structure. These structures, their propensities, and the pathways for moving between them contain an enormous amount of information about protein function that is hidden from a pu...