Ntie-Kang Fidele, Kannan Srinivasaraghavan, Wichapong Kanin, Owono Owono Luc C, Sippl Wolfgang, Megnassan Eugene
CEPAMOQ, Faculty of Science, University of Douala, P.O. Box 8580, Douala, Cameroon.
Mol Biosyst. 2014 Feb;10(2):223-39. doi: 10.1039/c3mb70449a.
Recently, the search for new drugs against tuberculosis (TB) has been a hot topic and the search for new inhibitors against validated drug targets and pathways other than those currently targeted by known drugs is suggested to be the most promising way forward. Mycobacterium tuberculosis pantothenate synthetase (MTBPS) happens to be one of such targets. In a quest to carry out virtual screening for active inhibitors against MTBPS and to get ideas for the design of new inhibitors against this target, we have docked a set of pyrazole-based inhibitors to the active site of this enzyme. The docking solutions were post processed using the MM-PB(GB)SA method and molecular dynamic simulations in order to analyze and validate the two previously proposed binding modes. The results show that both the MM-PBSA and MM-GBSA were able to discriminate between active and inactive compounds. Moreover, the pharmacophore-based scoring method proved efficient in discriminating the active compounds from inactives. From this work a protocol for screening of potential inhibitors of the enzyme from commercially available databases has been devised.
最近，寻找抗结核病新药一直是热门话题，而寻找针对已验证的药物靶点和已知药物当前未靶向的途径的新型抑制剂被认为是最有前途的前进方向。结核分枝杆菌泛酸合成酶（MTBPS）恰好是这类靶点之一。为了对MTBPS的活性抑制剂进行虚拟筛选，并获得针对该靶点设计新型抑制剂的思路，我们将一组基于吡唑的抑制剂对接至该酶的活性位点。对接结果使用MM-PB(GB)SA方法和分子动力学模拟进行后处理，以分析和验证先前提出的两种结合模式。结果表明，MM-PBSA和MM-GBSA都能够区分活性和非活性化合物。此外，基于药效团的评分方法在区分活性化合物和非活性化合物方面被证明是有效的。通过这项工作，我们设计了一种从商业可用数据库中筛选该酶潜在抑制剂的方案。
