AIMC Topic: Structure-Activity Relationship
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Neural Network Modeling of AChE Inhibition by New Carbazole-Bearing Oxazolones.
Interdisciplinary sciences, computational life sciences
Dec 13, 2017
Acetylcholine esterase (AChE) is one of the targeted enzymes in the therapy of important neurodegenerative diseases such as Alzheimer's disease. Many studies on carbazole- and oxazolone-based compounds have been conducted in the last decade due to th...
Differential Compound Prioritization via Bidirectional Selectivity Push with Power.
Journal of chemical information and modeling
Dec 13, 2017
Effective in silico compound prioritization is a critical step to identify promising drug candidates in the early stages of drug discovery. Current computational methods for compound prioritization usually focus on ranking the compounds based on one ...
Selenazolinium Salts as "Small Molecule Catalysts" with High Potency against ESKAPE Bacterial Pathogens.
Molecules (Basel, Switzerland)
Dec 8, 2017
In view of the pressing need to identify new antibacterial agents able to combat multidrug-resistant bacteria, we investigated a series of fused selenazolinium derivatives (-) regarding their in vitro antimicrobial activities against 25 ESKAPE-pathog...
The synthesis, antifungal and apoptotic effects of triazole-oxadiazoles against Candida species.
European journal of medicinal chemistry
Dec 7, 2017
In search of potent and safe antifungal agents, herein, we report the synthesis, characterization and biological activities of triazole-oxadiazole compounds. The structural verification of the molecules was carried out by H NMR, C NMR and mass spectr...
Design, synthesis, antibacterial evaluation and molecular docking studies of some new quinoxaline derivatives targeting dihyropteroate synthase enzyme.
Bioorganic chemistry
Dec 5, 2017
Development of new antimicrobial agents is a good solution to overcome drug-resistance problems. From this perspective, new quinoxaline derivatives bearing various bioactive heterocyclic moieties (thiadiazoles, oxadiazoles, pyrazoles and thiazoles) w...
Quinoxalines
Anti-Bacterial Agents
Gram-Positive Bacteria
Levofloxacin
Molecular Docking Simulation
Hydrophobic and Hydrophilic Interactions
Hydrogen Bonding
Protein Binding
Yersinia pestis
Catalytic Domain
Drug Design
Dihydropteroate Synthase
Structure-Activity Relationship
Gram-Negative Bacteria
Microbial Sensitivity Tests
Molecular Structure
Coupling Matched Molecular Pairs with Machine Learning for Virtual Compound Optimization.
Journal of chemical information and modeling
Nov 27, 2017
Matched molecular pair (MMP) analyses are widely used in compound optimization projects to gain insights into structure-activity relationships (SAR). The analysis is traditionally done via statistical methods but can also be employed together with ma...
Novel cationic chitosan derivative bearing 1,2,3-triazolium and pyridinium: Synthesis, characterization, and antifungal property.
Carbohydrate polymers
Nov 7, 2017
In this paper, novel cationic chitosan derivative possessing 1,2,3-triazolium and pyridinium groups was synthesized conveniently via cuprous-catalyzed azide-alkyne cycloaddition (CuAAC) and methylation. FTIR, H NMR, and elemental analysis examined th...
Machine learning to design integral membrane channelrhodopsins for efficient eukaryotic expression and plasma membrane localization.
PLoS computational biology
Oct 23, 2017
There is growing interest in studying and engineering integral membrane proteins (MPs) that play key roles in sensing and regulating cellular response to diverse external signals. A MP must be expressed, correctly inserted and folded in a lipid bilay...
The Liver Toxicity Knowledge Base (LKTB) and drug-induced liver injury (DILI) classification for assessment of human liver injury.
Expert review of gastroenterology & hepatology
Oct 9, 2017
Drug-induced liver injury (DILI) is challenging for drug development, clinical practice and regulation. The Liver Toxicity Knowledge Base (LTKB) provides essential data for DILI study. Areas covered: The LTKB provided various types of data that can b...
Systematic Identification of Machine-Learning Models Aimed to Classify Critical Residues for Protein Function from Protein Structure.
Molecules (Basel, Switzerland)
Oct 9, 2017
Protein structure and protein function should be related, yet the nature of this relationship remains unsolved. Mapping the critical residues for protein function with protein structure features represents an opportunity to explore this relationship,...
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