Short Oxo–Titanium(IV) Bond in Bacterial Transferrin: A Protein Target for Metalloantibiotics

2006 ◽  
Vol 45 (17) ◽  
pp. 2758-2761 ◽  
Author(s):  
Maolin Guo ◽  
Ian Harvey ◽  
Dominic J. Campopiano ◽  
Peter J. Sadler
2006 ◽  
Vol 118 (17) ◽  
pp. 2824-2827 ◽  
Author(s):  
Maolin Guo ◽  
Ian Harvey ◽  
Dominic J. Campopiano ◽  
Peter J. Sadler

2020 ◽  
Author(s):  
Lewis Mervin ◽  
Avid M. Afzal ◽  
Ola Engkvist ◽  
Andreas Bender

In the context of bioactivity prediction, the question of how to calibrate a score produced by a machine learning method into reliable probability of binding to a protein target is not yet satisfactorily addressed. In this study, we compared the performance of three such methods, namely Platt Scaling, Isotonic Regression and Venn-ABERS in calibrating prediction scores for ligand-target prediction comprising the Naïve Bayes, Support Vector Machines and Random Forest algorithms with bioactivity data available at AstraZeneca (40 million data points (compound-target pairs) across 2112 targets). Performance was assessed using Stratified Shuffle Split (SSS) and Leave 20% of Scaffolds Out (L20SO) validation.


Author(s):  
Parth Sarthi Sen Gupta ◽  
Satyaranjan Biswal ◽  
Saroj Kumar Panda ◽  
Abhik Kumar Ray ◽  
Malay Kumar Rana

<p>While an FDA approved drug Ivermectin was reported to dramatically reduce the cell line of SARS-CoV-2 by ~5000 folds within 48 hours, the precise mechanism of action and the COVID-19 molecular target involved in interaction with this in-vitro effective drug are unknown yet. Among 12 different COVID-19 targets studied here, the RNA dependent RNA polymerase (RdRp) with RNA and Helicase NCB site show the strongest affinity to Ivermectin amounting -10.4 kcal/mol and -9.6 kcal/mol, respectively. Molecular dynamics of corresponding protein-drug complexes reveals that the drug bound state of RdRp with RNA has better structural stability than the Helicase NCB site, with MM/PBSA free energy of -135.2 kJ/mol, almost twice that of Helicase (-76.6 kJ/mol). The selectivity of Ivermectin to RdRp is triggered by a cooperative interaction of RNA-RdRp by ternary complex formation. Identification of the target and its interaction profile with Ivermectin can lead to more powerful drug designs for COVID-19 and experimental exploration. </p>


2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Abdullahi Bello Umar ◽  
Adamu Uzairu ◽  
Gideon Adamu Shallangwa ◽  
Sani Uba

Abstract Background V600E-BRAF is a major protein target involved in various types of human cancers. However, the acquired resistance of the V600E-BRAF kinase to the vemurafenib and the side effects of other identified drugs initiate the search for efficient inhibitors. In the current paper, virtual docking screening combined with drug likeness and ADMET properties predictions were jointly applied to evaluate potent 2-(1H-imidazol-2-yl) pyridines as V600E-BRAF kinase inhibitors. Results Most of the studied compounds showed better docking scores and favorable interactions with theiV600E-BRAF target. Among the screened compounds, the two most potent (14 and 30) with good rerank scores (−124.079 and − 122.290) emerged as the most effective, and potent V600E-BRAF kinase inhibitors which performed better than vemurafenib (−116.174), an approved V600E-BRAF kinase inhibitor. Thus, the docking studies exhibited that these compounds have shown competing inhibition of V600E-BRAF kinase with vemurafenib at the active site and revealed better pharmacological properties based on Lipinski’s and Veber’s drug-likeness rules for oral bioavailability and ADMET properties. Conclusion The docking result, drug-likeness rules, and ADMET parameters identified compounds (14 and 30) as the best hits against V600E-BRAF kinase with better pharmacological properties. This suggests that these compounds may be developed as potent V600E-BRAF inhibitors.


2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Markus Nyberg ◽  
Tobias Ambjörnsson ◽  
Per Stenberg ◽  
Ludvig Lizana

2021 ◽  
Vol 23 (6) ◽  
pp. 664-675
Author(s):  
Ruibao Su ◽  
Li-Hua Fan ◽  
Changchang Cao ◽  
Lei Wang ◽  
Zongchang Du ◽  
...  

Critical Care ◽  
2021 ◽  
Vol 25 (1) ◽  
Author(s):  
Pierre Singer ◽  
Itai Bendavid ◽  
Ilana BenArie ◽  
Liran Stadlander ◽  
Ilya Kagan

Abstract Background and aims Combining energy and protein targets during the acute phase of critical illness is challenging. Energy should be provided progressively to reach targets while avoiding overfeeding and ensuring sufficient protein provision. This prospective observational study evaluated the feasibility of achieving protein targets guided by 24-h urinary nitrogen excretion while avoiding overfeeding when administering a high protein-to-energy ratio enteral nutrition (EN) formula. Methods Critically ill adult mechanically ventilated patients with an APACHE II score > 15, SOFA > 4 and without gastrointestinal dysfunction received EN with hypocaloric content for 7 days. Protein need was determined by 24-h urinary nitrogen excretion, up to 1.2 g/kg (Group A, N = 10) or up to 1.5 g/kg (Group B, N = 22). Variables assessed included nitrogen intake, excretion, balance; resting energy expenditure (REE); phase angle (PhA); gastrointestinal tolerance of EN. Results Demographic characteristics of groups were similar. Protein target was achieved using urinary nitrogen excretion measurements. Nitrogen balance worsened in Group A but improved in Group B. Daily protein and calorie intake and balance were significantly increased in Group B compared to Group A. REE was correlated to PhA measurements. Gastric tolerance of EN was good. Conclusions Achieving the protein target using urinary nitrogen loss up to 1.5 g/kg/day was feasible in this hypercatabolic population. Reaching a higher protein and calorie target did not induce higher nitrogen excretion and was associated with improved nitrogen balance and a better energy intake without overfeeding. PhA appears to be related to REE and may reflect metabolism level, suggestive of a new phenotype for nutritional status. Trial registration 0795-18-RMC.


2021 ◽  
Vol 53 (2) ◽  
pp. 166-173
Author(s):  
Christopher Y. Park ◽  
Jian Zhou ◽  
Aaron K. Wong ◽  
Kathleen M. Chen ◽  
Chandra L. Theesfeld ◽  
...  

Bioanalysis ◽  
2017 ◽  
Vol 9 (20) ◽  
pp. 1573-1588 ◽  
Author(s):  
Hongwei Zhang ◽  
Huidong Gu ◽  
Petia Shipkova ◽  
Eugene Ciccimaro ◽  
Huadong Sun ◽  
...  

Biochemistry ◽  
2004 ◽  
Vol 43 (50) ◽  
pp. 15767-15774 ◽  
Author(s):  
Petra L. Roulhac ◽  
Kendall D. Powell ◽  
Suraj Dhungana ◽  
Katherine D. Weaver ◽  
Timothy A. Mietzner ◽  
...  

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