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Tuberculosis (TB) is a life threatening disease caused due to infection from Mycobacterium tu¬berculosis (Mtb). That most of the TB strains have become resistant to various existing drugs, develop¬ment of effective novel drug candidates to combat this disease is a need of the day. In spite of intensive research world-wide, the success rate of discovering a new anti-TB drug is very poor. Therefore, novel drug discovery methods have to be tried. We have used a rule based computational method that utilizes a vertex index, named ‘distance exponent index (Dx)’ (taken x = –4 here) for predicting anti-TB activity of a series of acid alkyl ester derivatives. The method is meant to identify activity related substructures from a series a compounds and predict activity of a compound on that basis. The high degree of successful pre¬diction in the present study suggests that the said method may be useful in discovering effective anti-TB compound. It is also apparent that substructural approaches may be leveraged for wide purposes in com¬puter-aided drug design. (doi: 10.5562/cca2306

croatica chemica acta

Role of Vertex Index in Substructure Identification and Activity Prediction: A Study on Antitubercular Activity of a Series of Acid Alkyl Ester Derivatives