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Amino Acids

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Add-on treatment with Cerebrolysin improves clinical symptoms in patients with ALS: results from a prospective, single-center, placebo-controlled, randomized, double-blind, phase II study.

Journal of medicine and life
Amyotrophic lateral sclerosis (ALS) is a devastating and progressive neurodegenerative disease with limited treatment options available. Cerebrolysin is a drug candidate for the treatment of ALS because of its neuroprotective and neuroregenerative ef...

HormoNet: a deep learning approach for hormone-drug interaction prediction.

BMC bioinformatics
Several experimental evidences have shown that the human endogenous hormones can interact with drugs in many ways and affect drug efficacy. The hormone drug interactions (HDI) are essential for drug treatment and precision medicine; therefore, it is ...

Protein design using structure-based residue preferences.

Nature communications
Recent developments in protein design rely on large neural networks with up to 100s of millions of parameters, yet it is unclear which residue dependencies are critical for determining protein function. Here, we show that amino acid preferences at in...

xCAPT5: protein-protein interaction prediction using deep and wide multi-kernel pooling convolutional neural networks with protein language model.

BMC bioinformatics
BACKGROUND: Predicting protein-protein interactions (PPIs) from sequence data is a key challenge in computational biology. While various computational methods have beenĀ proposed, the utilization of sequence embeddings from protein language models, wh...

Biomolecular Adsorption on Nanomaterials: Combining Molecular Simulations with Machine Learning.

Journal of chemical information and modeling
Adsorption free energies of 32 small biomolecules (amino acids side chains, fragments of lipids, and sugar molecules) on 33 different nanomaterials, computed by the molecular dynamics - metadynamics methodology, have been analyzed using statistical m...

KCD: A prediction web server of knowledge-based circular dichroism.

Protein science : a publication of the Protein Society
We present a web server that predicts the far-UV circular dichroism (CD) spectra of proteins by utilizing their three-dimensional (3D) structures from the Protein Data Bank (PDB). The main algorithm is based on the classical theory of optical activit...

Generalized biomolecular modeling and design with RoseTTAFold All-Atom.

Science (New York, N.Y.)
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...

Predicting Antimicrobial Peptides Using ESMFold-Predicted Structures and ESM-2-Based Amino Acid Features with Graph Deep Learning.

Journal of chemical information and modeling
Currently, antimicrobial resistance constitutes a serious threat to human health. Drugs based on antimicrobial peptides (AMPs) constitute one of the alternatives to address it. Shallow and deep learning (DL)-based models have mainly been built from a...

Enhancing Machine-Learning Prediction of Enzyme Catalytic Temperature Optima through Amino Acid Conservation Analysis.

International journal of molecular sciences
Enzymes play a crucial role in various industrial production and pharmaceutical developments, serving as catalysts for numerous biochemical reactions. Determining the optimal catalytic temperature () of enzymes is crucial for optimizing reaction cond...

Raman Spectra of Amino Acids and Peptides from Machine Learning Polarizabilities.

Journal of chemical information and modeling
Raman spectroscopy is an important tool in the study of vibrational properties and composition of molecules, peptides, and even proteins. Raman spectra can be simulated based on the change of the electronic polarizability with vibrations, which can n...