A5000634472- Computational Drug Discovery Methods
- Machine Learning in Materials Science
- Chemical Synthesis and Analysis
- Protein Structure and Dynamics
- Cell Image Analysis Techniques
- Metabolomics and Mass Spectrometry Studies
- Enzyme function and inhibition
- Biochemical and Molecular Research
- ATP Synthase and ATPases Research
Finland University
2023
University of Eastern Finland
2023
University of Turku
1999
The emergence of ultra-large screening libraries, filled to the brim with billions readily available compounds, poses a growing challenge for docking-based virtual screening. Machine learning (ML)-boosted strategies like tool HASTEN combine rapid ML prediction brute-force docking small fractions such libraries increase throughput and take on giga-scale libraries. In our case study an anti-bacterial chaperone anti-viral kinase, we first generated baseline 1.56 billion compounds in Enamine...
Based on the primary structure, soluble inorganic pyrophosphatases can be divided into two families which exhibit no sequence similarity to each other. Family I, comprising most of known pyrophosphatase sequences, further prokaryotic, plant and animal/fungal pyrophosphatases. Interestingly, bear a closer prokaryotic than Only 17 residues are conserved in all 37 family I remarkably, 15 these located at active site. Subunit interface but not
The emergence of ultra-large screening libraries, filled to the brim with billions readily available compounds, poses a growing challenge for docking-based virtual screening. Machine Learning (ML)-boosted strategies like tool HASTEN combine rapid ML prediction brute-force docking small fractions such libraries increase throughput and take on giga-scale libraries. In our case study an anti-bacterial chaperone anti-viral kinase, we first generated baseline 1.56 billion compounds in Enamine...
The emergence of ultra-large screening libraries, filled to the brim with billions readily available compounds, poses a growing challenge for docking-based virtual screening. Machine Learning (ML)-boosted strategies like tool HASTEN combine rapid ML prediction brute-force docking small fractions such libraries increase throughput and take on giga-scale libraries. In our case study an anti-bacterial chaperone anti-viral kinase, we first generated baseline 1.56 billion compounds in Enamine...