AI Medical Compendium Journal:
Current opinion in structural biology

Showing 51 to 60 of 82 articles

Everything is connected: Graph neural networks.

Current opinion in structural biology
In many ways, graphs are the main modality of data we receive from nature. This is due to the fact that most of the patterns we see, both in natural and artificial systems, are elegantly representable using the language of graph structures. Prominent...

Industrializing AI/ML during the end-to-end drug discovery process.

Current opinion in structural biology
Drug discovery aims to select proper targets and drug candidates to address unmet clinical needs. The end-to-end drug discovery process includes all stages of drug discovery from target identification to drug candidate selection. Recently, several ar...

Machine learned coarse-grained protein force-fields: Are we there yet?

Current opinion in structural biology
The successful recent application of machine learning methods to scientific problems includes the learning of flexible and accurate atomic-level force-fields for materials and biomolecules from quantum chemical data. In parallel, the machine learning...

Deep learning for protein complex structure prediction.

Current opinion in structural biology
Recent developments in the structure prediction of protein complexes have resulted in accuracies rivalling experimental methods in many cases. The high accuracy is mainly observed in dimeric complexes and other problems such as protein disorder and p...

AlphaFold2 protein structure prediction: Implications for drug discovery.

Current opinion in structural biology
The drug discovery process involves designing compounds to selectively interact with their targets. The majority of therapeutic targets for low molecular weight (small molecule) drugs are proteins. The outstanding accuracy with which recent artificia...

Using machine learning to predict the effects and consequences of mutations in proteins.

Current opinion in structural biology
Machine and deep learning approaches can leverage the increasingly available massive datasets of protein sequences, structures, and mutational effects to predict variants with improved fitness. Many different approaches are being developed, but syste...

Mutually beneficial confluence of structure-based modeling of protein dynamics and machine learning methods.

Current opinion in structural biology
Proteins sample an ensemble of conformers under physiological conditions, having access to a spectrum of modes of motions, also called intrinsic dynamics. These motions ensure the adaptation to various interactions in the cell, and largely assist in,...

Protein structure prediction in the deep learning era.

Current opinion in structural biology
Significant advances have been achieved in protein structure prediction, especially with the recent development of the AlphaFold2 and the RoseTTAFold systems. This article reviews the progress in deep learning-based protein structure prediction metho...

New opportunities in integrative structural modeling.

Current opinion in structural biology
Integrative structural modeling enables structure determination of macromolecules and their complexes by integrating data from multiple sources. It has been successfully used to characterize macromolecular structures when a single structural biology ...