AI Medical Compendium Journal:
Current opinion in structural biology

Showing 21 to 30 of 82 articles

Structures, dynamics, complexes, and functions: From classic computation to artificial intelligence.

Current opinion in structural biology
Computational approaches can provide highly detailed insight into the molecular recognition processes that underlie drug binding, the assembly of protein complexes, and the regulation of biological functional processes. Classical simulation methods c...

Advancing biomolecular simulation through exascale HPC, AI and quantum computing.

Current opinion in structural biology
Biomolecular simulation can act as both a digital microscope and a crystal ball; offering the potential for a deeper understanding of experimental observations whilst also presenting a forward-looking avenue for the in silico design and evaluation of...

Deep learning for low-data drug discovery: Hurdles and opportunities.

Current opinion in structural biology
Deep learning is becoming increasingly relevant in drug discovery, from de novo design to protein structure prediction and synthesis planning. However, it is often challenged by the small data regimes typical of certain drug discovery tasks. In such ...

Generative artificial intelligence for de novo protein design.

Current opinion in structural biology
Engineering new molecules with desirable functions and properties has the potential to extend our ability to engineer proteins beyond what nature has so far evolved. Advances in the so-called 'de novo' design problem have recently been brought forwar...

Apprehensions and emerging solutions in ML-based protein structure prediction.

Current opinion in structural biology
The three-dimensional structure of proteins determines their function in vital biological processes. Thus, when the structure is known, the molecular mechanism of protein function can be understood in more detail and obtained information utilized in ...

How exascale computing can shape drug design: A perspective from multiscale QM/MM molecular dynamics simulations and machine learning-aided enhanced sampling algorithms.

Current opinion in structural biology
Molecular simulations are an essential asset in the first steps of drug design campaigns. However, the requirement of high-throughput limits applications mainly to qualitative approaches with low computational cost, but also low accuracy. Unlocking t...

Emerging structure-based computational methods to screen the exploding accessible chemical space.

Current opinion in structural biology
Structure-based virtual screening can be a valuable approach to computationally select hit candidates based on their predicted interaction with a protein of interest. The recent explosion in the size of chemical libraries increases the chances of hit...

Deep learning in modeling protein complex structures: From contact prediction to end-to-end approaches.

Current opinion in structural biology
Protein-protein interactions play crucial roles in many biological processes. Traditionally, protein complex structures are normally built by protein-protein docking. With the rapid development of artificial intelligence and its great success in mono...

Machine learning approaches in predicting allosteric sites.

Current opinion in structural biology
Allosteric regulation is a fundamental biological mechanism that can control critical cellular processes via allosteric modulator binding to protein distal functional sites. The advantages of allosteric modulators over orthosteric ones have sparked t...

Artificial intelligence for drug discovery and development in Alzheimer's disease.

Current opinion in structural biology
The complex molecular mechanism and pathophysiology of Alzheimer's disease (AD) limits the development of effective therapeutics or prevention strategies. Artificial Intelligence (AI)-guided drug discovery combined with genetics/multi-omics (genomics...