AI Medical Compendium Topic:
Models, Molecular

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ModFOLD8: accurate global and local quality estimates for 3D protein models.

Nucleic acids research
Methods for estimating the quality of 3D models of proteins are vital tools for driving the acceptance and utility of predicted tertiary structures by the wider bioscience community. Here we describe the significant major updates to ModFOLD, which ha...

Using graph convolutional neural networks to learn a representation for glycans.

Cell reports
As the only nonlinear and the most diverse biological sequence, glycans offer substantial challenges for computational biology. These carbohydrates participate in nearly all biological processes-from protein folding to viral cell entry-yet are still ...

The breakthrough in protein structure prediction.

The Biochemical journal
Proteins are the essential agents of all living systems. Even though they are synthesized as linear chains of amino acids, they must assume specific three-dimensional structures in order to manifest their biological activity. These structures are ful...

State-of-the-art web services for de novo protein structure prediction.

Briefings in bioinformatics
Residue coevolution estimations coupled to machine learning methods are revolutionizing the ability of protein structure prediction approaches to model proteins that lack clear homologous templates in the Protein Data Bank (PDB). This has been patent...

AntiCP 2.0: an updated model for predicting anticancer peptides.

Briefings in bioinformatics
Increasing use of therapeutic peptides for treating cancer has received considerable attention of the scientific community in the recent years. The present study describes the in silico model developed for predicting and designing anticancer peptides...

Protein sequence design by conformational landscape optimization.

Proceedings of the National Academy of Sciences of the United States of America
The protein design problem is to identify an amino acid sequence that folds to a desired structure. Given Anfinsen's thermodynamic hypothesis of folding, this can be recast as finding an amino acid sequence for which the desired structure is the lowe...

Computational Ion Channel Research: from the Application of Artificial Intelligence to Molecular Dynamics Simulations.

Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry, and pharmacology
Although ion channels are crucial in many physiological processes and constitute an important class of drug targets, much is still unclear about their function and possible malfunctions that lead to diseases. In recent years, computational methods ha...

FireProtDB: database of manually curated protein stability data.

Nucleic acids research
The majority of naturally occurring proteins have evolved to function under mild conditions inside the living organisms. One of the critical obstacles for the use of proteins in biotechnological applications is their insufficient stability at elevate...

Trends in Deep Learning for Property-driven Drug Design.

Current medicinal chemistry
It is more pressing than ever to reduce the time and costs for the development of lead compounds in the pharmaceutical industry. The co-occurrence of advances in high-throughput screening and the rise of deep learning (DL) have enabled the developmen...