title: DrugMint: a webserver for predicting and designing of drug-like molecules.
abstract: BACKGROUND
  Identification of drug-like molecules is one of the major challenges in the field of drug discovery. Existing approach like Lipinski rule of 5 (Ro5), Operea have their own limitations. Thus, there is a need to develop computational method that can predict drug-likeness of a molecule with precision. In addition, there is a need to develop algorithm for screening chemical library for their drug-like properties.
  
  
  RESULTS
  In this study, we have used 1347 approved and 3206 experimental drugs for developing a knowledge-based computational model for predicting drug-likeness of a molecule. We have used freely available PaDEL software for computing molecular fingerprints/descriptors of the molecules for developing prediction models. Weka software has been used for feature selection in order to identify the best fingerprints. We have developed various classification models using different types of fingerprints like Estate, PubChem, Extended, FingerPrinter, MACCS keys, GraphsOnlyFP, SubstructureFP, Substructure FPCount, Klekota-RothFP, Klekota-Roth FPCount. It was observed that the models developed using MACCS keys based fingerprints, discriminated approved and experimental drugs with higher precision. Our model based on one hundred fifty nine MACCS keys predicted drug-likeness of the molecules with 89.96% accuracy along with 0.77 MCC. Our analysis indicated that MACCS keys (ISIS keys) 112, 122, 144, and 150 were highly prevalent in the approved drugs. The screening of ZINC (drug-like) and ChEMBL databases showed that around 78.33% and 72.43% of the compounds present in these databases had drug-like potential.
  
  
  CONCLUSIONS
  It was apparent from above study that the binary fingerprints could be used to discriminate approved and experimental drugs with high accuracy. In order to facilitate researchers working in the field of drug discovery, we have developed a webserver for predicting, designing, and screening novel drug-like molecules (http://crdd.osdd.net/oscadd/drugmint/).
authors.forename: Sandeep Kumar
authors.initials: SK
authors.lastname: Dhanda
authors.forename: Deepak
authors.initials: D
authors.lastname: Singla
authors.forename: Alok K
authors.initials: AK
authors.lastname: Mondal
authors.affiliation: Institute of Microbial Technology, Chandigarh, India. raghava@imtech.res.in.
authors.forename: Gajendra P S
authors.initials: GP
authors.lastname: Raghava
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D015195:Drug Design; D008956:Models, Chemical; D004364:Pharmaceutical Preparations / Q000032:analysis*; D012984:Software
chemical_list: D004364:Pharmaceutical Preparations