Synthesis of Spiro 3,3'-Cyclopropyl Oxindoles Via N-Bromosuccinimide-Mediated Ring-Closing and Contraction Cascade.

An N-bromosuccinimide-mediated cascade reaction involving the cyclization/oxygen-migration/ring-contraction process of 3-(ß, ß-diaryl) indolylethanol was disclosed. A variety of spiro 3,3'-cyclopropyl oxindole derivatives were efficiently synthesized in good yields under mild reaction conditions. A possible mechanism was suggested based on intermediate isolation and computational studies.

Copper-Catalyzed Oxidative sp3-Carbon Radical Cross-Coupling with Trialkylphosphites Leading to α-Phosphonyl 1,3-Dicarbonyl Compounds.

A copper-catalyzed radical Csp3-H/P(OR)3 cross-coupling reaction for the formation of Csp3-P bonds is described. A range of 1,3-dicarbonyl compounds and trialkylphosphites were coupled in this fashion to give the corresponding products in moderate to good yields. This protocol provides direct access to α-phosphonyl 1,3-dicarbonyl compounds.

A Novel Algorithm for Solving the Prize Collecting Traveling Salesman Problem Based on DNA Computing.

DNA computing is a new pattern of computing that combines biotechnology and information technology. As a new technology born in less than three decades, it has developed at an extremely rapid rate, which can be attributed to its advantages, including high parallelism, powerful data storage capacity, and low power consumption. Nowadays, DNA computing has become one of the most popular research fields worldwide and has been effective in solving certain combinatorial optimization problems. In this study, we use the Adleman-Lipton model based on DNA computing for solving the Prize Collecting Traveling Salesman Problem (PCTSP) and demonstrate the feasibility of this model. Then, we design a simulation experiment of the model to solve some open instances of PCTSP. The results illustrate that the model can satisfactorily solve these instances. Finally, the comparison with the results of the Clustering Search algorithm and the Greedy Stochastic Adaptive Search Procedure/Variable Neighborhood Search method reveals that the optimal solutions obtained by this simulation experiment are significantly superior to those of the other two algorithms in all instances. This research also provides a method for proficiently solving additional combinatorial optimization problems.

Pharmacophore-based virtual screening versus docking-based virtual screening: a benchmark comparison against eight targets.

AIM: This study was conducted to compare the efficiencies of two virtual screening approaches, pharmacophore-based virtual screening (PBVS) and docking-based virtual screening (DBVS) methods. METHODS: All virtual screens were performed on two data sets of small molecules with both actives and decoys against eight structurally diverse protein targets, namely angiotensin converting enzyme (ACE), acetylcholinesterase (AChE), androgen receptor (AR), D-alanyl-D-alanine carboxypeptidase (DacA), dihydrofolate reductase (DHFR), estrogen receptors alpha (ERalpha), HIV-1 protease (HIV-pr), and thymidine kinase (TK). Each pharmacophore model was constructed based on several X-ray structures of protein-ligand complexes. Virtual screens were performed using four screening standards, the program Catalyst for PBVS and three docking programs (DOCK, GOLD and Glide) for DBVS. RESULTS: Of the sixteen sets of virtual screens (one target versus two testing databases), the enrichment factors of fourteen cases using the PBVS method were higher than those using DBVS methods. The average hit rates over the eight targets at 2% and 5% of the highest ranks of the entire databases for PBVS are much higher than those for DBVS. CONCLUSION: The PBVS method outperformed DBVS methods in retrieving actives from the databases in our tested targets, and is a powerful method in drug discovery.