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Knowledge Based Identification of Potent Antitubercular Compounds Using Structure Based Virtual Screening and Structure Interaction Fingerprints

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Virtual Screening for Submicromolar Leads of tRNA-guanine Transglycosylase Based on a New Unexpected Binding Mode Detected by Crystal Structure Analysis
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Structural Interaction Fingerprint (SIFt): A Novel Method for Analyzing Three-Dimensional Protein−Ligand Binding Interactions
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Discovery of Bicyclic Thymidine Analogues as Selective and High-Affinity Inhibitors of Mycobacterium tuberculosis Thymidine Monophosphate Kinase
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Interaction Profiles of Protein Kinase−Inhibitor Complexes and Their Application to Virtual Screening
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Enzymatic and Structural Analysis of Inhibitors Designed against Mycobacterium tuberculosis Thymidylate Kinase
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Structural Interaction Fingerprints: A New Approach to Organizing, Mining, Analyzing, and Designing Protein–Small Molecule Complexes
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A Computer Program for Classifying Plants

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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ChemInform Abstract: Knowledge Based Identification of Potent Antitubercular Compounds Using Structure Based Virtual Screening and Structure Interaction Fingerprints.
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