J. Appl. Cryst.の発刊に際して

Some remarks on protein attribute prediction and pseudo amino acid composition.

Motivation The use of drug combinations, termed polypharmacy, is common to treat patients with complex diseases or co-existing conditions However, a major consequence of polypharmacy is a much higher risk of adverse side effects for the patient Polypharmacy side effects emerge because of drug-drug interactions, in which activity of one drug may change, favorably or unfavorably, if taken with another drug The knowledge of drug interactions is often limited because these complex relationships are rare, and are usually not observed in relatively small clinical testing Discovering polypharmacy side effects thus remains an important challenge with significant implications for patient mortality and morbidity Results Here, we present Decagon, an approach for modeling polypharmacy side effects The approach constructs a multimodal graph of protein-protein interactions, drug-protein target interactions and the polypharmacy side effects, which are represented as drug-drug interactions, where each side effect is an edge of a different type Decagon is developed specifically to handle such multimodal graphs with a large number of edge types Our approach develops a new graph convolutional neural network for multirelational link prediction in multimodal networks Unlike approaches limited to predicting simple drug-drug interaction values, Decagon can predict the exact side effect, if any, through which a given drug combination manifests clinically Decagon accurately predicts polypharmacy side effects, outperforming baselines by up to 69% We find that it automatically learns representations of side effects indicative of co-occurrence of polypharmacy in patients Furthermore, Decagon models particularly well polypharmacy side effects that have a strong molecular basis, while on predominantly non-molecular side effects, it achieves good performance because of effective sharing of model parameters across edge types Decagon opens up opportunities to use large pharmacogenomic and patient population data to flag and prioritize polypharmacy side effects for follow-up analysis via formal pharmacological studies Availability and implementation Source code and preprocessed datasets are at: http://snapstanfordedu/decagon

Modeling polypharmacy side effects with graph convolutional networks.

Privileged structures have been widely used as an effective template in medicinal chemistry for drug discovery. Chalcone is a common simple scaffold found in many naturally occurring compounds. Many chalcone derivatives have also been prepared due to their convenient synthesis. These natural products and synthetic compounds have shown numerous interesting biological activities with clinical potentials against various diseases. This review aims to highlight the recent evidence of chalcone as a privileged scaffold in medicinal chemistry. Multiple aspects of chalcone will be summarized herein, including the isolation of novel chalcone derivatives, the development of new synthetic methodologies, the evaluation of their biological properties, and the exploration of the mechanisms of action as well as target identification. This review is expected to be a comprehensive, authoritative, and critical review of the chalcone template to the chemistry community.

/pdf/chalcone-a-privileged-structure-in-medicinal-chemistry-2glhtivnj7.pdf

Chalcone: A Privileged Structure in Medicinal Chemistry.

10. Patented Literature 2616 10.1. Esterification 2616 10.2. Ether Formation 2619 10.2.1. Etherification without Cyclization 2619 10.2.2. Etherification with Cyclization 2624 10.3. N-Alkylation 2625 10.4. Other Reactions 2627 11. Summary and Outlook 2628 12. Note Added in Proof 2628 13. Abbreviations Used in This Review 2629 14. Acknowledgments 2629 15. Supporting Information Available 2630 16. References 2630

Mitsunobu and Related Reactions: Advances and Applications

A series of o ne t wo c arbonucleoside (OTC) analogues of thymine was synthetized and their conformation was studied by AM1 theoretical calculations. The low-energy conformations of Compound 1 and 2′,3′-dideoxythymidine, showed a degree of steric congruity.

1,2-Disubstituted Carbocyclic Analogues of Thymine Nucleosides

Synthesis, Conformational Analysis and Antiviral and Antitumoral Activity of New 1,2-Disubstituted Carbocyclic Nucleosides.

The compound 6-hydroxy-4-methyl-5,7-dinitrocoumarin (2) was synthesized with high yield by the nitration of compound 1. Its molecular structure was determined using X-ray diffractometry and compared with the structure obtained from semiempirical, HF, and B3LYP methods. B3LYP calculations offer the best conformity with X-ray diffractometry for bond lengths and bond angles, whereas AM1 results are significantly close to them and provide the best superimposition with the entire 3D crystal structure.

3D comparative structural study of 6-hydroxy-4-methyl-5,7-dinitrocoumarin using experimental and theoretical approaches

NMR study of some coumarins and furocoumarins methylated

Linear and angular furocoumarins can be obtained starting from phloroglucinol in a versatile, simple, direct, and efficient way, as demonstrated in the divergent syntheses described here. The key step is the alkali-mediated rearrangement of 4-halomethylcoumarins to benzofuran-3-acetic acids via α,β-unsaturated acids and the key intermediates are benzodipyrones, which, depending on their substitution, can either give or fail to give the ring-contraction reaction.

Divergent synthesis of linear and angular furocoumarin acetic acids from phloroglucinol

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