Prediction of GLMU inhibitors using QSAR and AutoDock

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Inhibitor Prediction

  KiDoQ (Mtb target)

  GDoQ (Mtb target)

  ABMpred (Mtb target)

  eBooster (Mtb target)

  MDRIpred (Mtb cell)

  CancerIN (Cancer)

  ntEGFR (Cancer EGFR)

  EGFRpred (Cancer EGFR)

  DiPCell (Pancreatic Cancer)

  DMKPred (Human Kinases)

  TLR4HI (Human TLR4)

  HIVFin (HIV)

Antigenic Properties

ADMET Properties

  MetaPred (Cytochrome P450)

  ToxiPred (Aqueous toxicity)

  DrugMint (Drug-like)

  QED (Oral drug-like)

  Format Conversion


      GDoQ: Prediction of GLMU inhibiotors using QSAR and Docking
1. Compound Information

In the submission form we have provided the option for user to either a) draw chemcial structure or b) paste/upload structure file in either mol or mol2 format.

2. Prediction Approach :

GDoQ is a web-server specially trained for the IC50 value prediction of chemical compounds in M.tuberculosis Glmu protein. For prediction we have calculated the descriptors from different software and selection of the descriptors by Weka and take those input features as the input of Multiple Linear Regression (MLR) for model development. This model will predict the inhibitory activity of the new chemical entity and also helping in finding new molecule by generating analogs of known inhibitors that shows good inhibitory activity.

Indraprastha Institute of Information Technology