CONCLUSION The QSAR model can predict the MIC of carbapenems and select the biologic-activity compounds, which offer a new way of thinking and references of carbapenems compounds design.

结论所建立QSAR模型能有效地进行碳青霉烯类化合物MIC测和化合物筛选，为类新药开发提供新和思路。

CONCLUSION The QSAR model can predict the MIC of carbapenems and select the biologic-activity compounds, which offer a new way of thinking and references of carbapenems compounds design.

结论所建立的QSAR模型能有效地进行碳青霉烯化合物的MIC值的预测和化合物筛，药开发提供的参考和思路。

CONCLUSION The QSAR model can predict the MIC of carbapenems and select the biologic-activity compounds, which offer a new way of thinking and references of carbapenems compounds design.

结论所建立的QSAR模型能有效地进行碳青霉烯类化合物的MIC值的预测和化合物筛选，为类新药开发提供新的参考和思路。

CONCLUSION The QSAR model can predict the MIC of carbapenems and select the biologic-activity compounds, which offer a new way of thinking and references of carbapenems compounds design.

结论所建立的QSAR模型能有效地进行碳青霉烯类化合物的MIC值的预测和化合物筛选，为类新药开发提供新的参考和思路。

CONCLUSION The QSAR model can predict the MIC of carbapenems and select the biologic-activity compounds, which offer a new way of thinking and references of carbapenems compounds design.

结论所建立的QSAR模型能有效地进行碳青霉合物的MIC值的预测和合物筛选，为新药开发提供新的参考和思路。

CONCLUSION The QSAR model can predict the MIC of carbapenems and select the biologic-activity compounds, which offer a new way of thinking and references of carbapenems compounds design.

结论所建立的QSAR模型能有效碳青霉烯类化合物的MIC值的预测和化合物筛选，为类新药开发提供新的参考和思路。

CONCLUSION The QSAR model can predict the MIC of carbapenems and select the biologic-activity compounds, which offer a new way of thinking and references of carbapenems compounds design.

结论所建立QSAR模型能有效地进行碳青霉烯类化合物MIC值和化合物筛选，为类药开发提供考和思路。

CONCLUSION The QSAR model can predict the MIC of carbapenems and select the biologic-activity compounds, which offer a new way of thinking and references of carbapenems compounds design.

结论所建立的QSAR模型能有效地进行青霉烯类化合物的MIC值的预测和化合物筛选，为类新药开发提供新的参考和思路。

CONCLUSION The QSAR model can predict the MIC of carbapenems and select the biologic-activity compounds, which offer a new way of thinking and references of carbapenems compounds design.

结论所建立QSAR模型能有效地进行碳青霉烯类化合物MIC预测化合物筛选，为类新药开发提供新思路。