A new series of sulfonamide flavone derivatives are designed as non-covalent inhibitors of proteasome assisted with computer-aided drug design （CADD）. The desired compounds were synthesized successfully and the biol...A new series of sulfonamide flavone derivatives are designed as non-covalent inhibitors of proteasome assisted with computer-aided drug design （CADD）. The desired compounds were synthesized successfully and the biological evaluation was subsequently accomplished. The results showed negligible improvement from our lead compound （IC50 for β5 subunit was 14.0 μM）. Thus, these flavone derivatives might be improved as potential 20S proteasome inhibitors.展开更多
String kernels are popular tools for analyzing protein sequence data and they have been successfully applied to many computational biology problems. The traditional string kernels assume that different substrings are ...String kernels are popular tools for analyzing protein sequence data and they have been successfully applied to many computational biology problems. The traditional string kernels assume that different substrings are independent. However, substrings can be highly correlated due to their substructure relationship or common physico-chemical properties. This paper proposes two kinds of weighted spectrum kernels： The correlation spectrum kernel and the AA spectrum kernel. We evMuate their performances by predicting glycan-binding proteins of 12 glycans. The results show that the correlation spectrum kernel and the AA spectrum kernel perform significantly better than the spectrum kernel for nearly all the 12 glycans. By comparing the predictive power of AA spectrum kernels constructed by different physico-chemical properties, the authors can also identify the physico- chemical properties which contributes the most to the glycan-protein binding. The results indicate that physico-chemical properties of amino acids in proteins play an important role in the mechanism of glycamprotein binding.展开更多
基金The National Natural Science Foundation of China(Grant No.21202003)the National Basic Research Program of China(Grant No.2012CB518000)the Specialized Research Fund for the Doctoral Program of Higher Education of China(Grant No.20120001110010)
文摘A new series of sulfonamide flavone derivatives are designed as non-covalent inhibitors of proteasome assisted with computer-aided drug design （CADD）. The desired compounds were synthesized successfully and the biological evaluation was subsequently accomplished. The results showed negligible improvement from our lead compound （IC50 for β5 subunit was 14.0 μM）. Thus, these flavone derivatives might be improved as potential 20S proteasome inhibitors.
基金supported in part by Research Grants Council of Hong Kong under Grant No.17301214HKU CERG Grants+2 种基金Hung Hing Ying Physical Research Grantthe Research Funds of Renmin University of Chinathe National Natural Science Foundation of China under Grant Nos.11271144,11101382,11471256,and S201201009985
文摘String kernels are popular tools for analyzing protein sequence data and they have been successfully applied to many computational biology problems. The traditional string kernels assume that different substrings are independent. However, substrings can be highly correlated due to their substructure relationship or common physico-chemical properties. This paper proposes two kinds of weighted spectrum kernels： The correlation spectrum kernel and the AA spectrum kernel. We evMuate their performances by predicting glycan-binding proteins of 12 glycans. The results show that the correlation spectrum kernel and the AA spectrum kernel perform significantly better than the spectrum kernel for nearly all the 12 glycans. By comparing the predictive power of AA spectrum kernels constructed by different physico-chemical properties, the authors can also identify the physico- chemical properties which contributes the most to the glycan-protein binding. The results indicate that physico-chemical properties of amino acids in proteins play an important role in the mechanism of glycamprotein binding.
