Original Research Article International Journal of Pharmaceutical Chemistry and Analysis, 3(3):174-182 174 Similarity Analysis studies on (Sulfonyl) Benzene Derivatives as Anti HIV Agents Shweta Sharma 1 , Smrita Singh 2 , Mymoona Akhter 3,* , Sarvesh Paliwal 4 1,3 Dept. of Pharmacy, Banasthali University, Tonk, Rajasthan, 2 Dept. of Bioinformatics Infrastructure Facility, 3 Dept. of Pharmaceutical Chemistry, Faculty of Pharmacy, Jamia Hamdard, New Delhi *Corresponding Author: Email: mymoonaakhter@gmail.com Abstract Introduction: The present investigation was undertaken to understand the overlaying problems of mutation in HIV virus leading to failure to combat AIDS. Materials and Methods: In present study Multiple Linear Regression (MLR) analysis was carried on a series of 71(sulfonyl) benzene analogs reported as viral nucleocapsid protein zinc finger modulators for HIV. Results: The MLR model obtained using carbo method (N*N) similarity showing good predictive ability, r 2 (training) = 0.655, r 2 (test) = 0.605. Conclusion: The results indicated that Refractivity Similarity (polarizability and volume) and Shape Similarity are important parameters in predicting the activity of viral nucleocapsid protein zinc finger inhibitors. Keywords: Refractivity Similarity, Shape Simliarity, Carbo, MLR, Viral Nucleocapsid Protein Zinc Finger, HIV. Access this article online Website: www.innovativepublication.com DOI: 10.5958/2394-2797.2016.00025.3 Introduction Acquired immunodeficiency syndrome (AIDS), one of the most important challenges for the chemotherapy of the early 21 st century [1] . Although, therapeutic interventions such as Highly Active Antireteroviral Therapy is existing but constant challenge is being featured due to the mutation of the virus. Current AIDS therapies are not sufficient in overcoming the disease so there is a high call for new improved drug candidates. The global scenario of AIDS is alarming and number of infected patients is regularly increasing and continued to grow in 2013, reaching an estimate of 34 million population [2,3] . The rapid mutation of the virus and hybridization of various subtypes, AIDS with TB is another important issue blocks the global efforts for remedy. Pneumocystis jirovecii (formerly known as Pneumocystis carinii) has been one of the hallmarks of late-stage HIV disease but is now less common because of ART and primary prophylaxis [4] . Protein Zinc finger, a validated target provide evidence to overcome problem of resistance due to non- permissive nature of mutation. It inhibits mainly by disrupting the shape of the Nucleocapsid (NC) which enables maturation of virus thereby controlling these process i.e. reverse transcription, integration and packaging in viral replication cycle. Molecular similarity was introduced as a concept by Carbo et al. [5] but its use as a 3D QSAR tool was introduced by Good et al. and has been widely used by several other groups since then [6] . Similarity indices represent a quantitative measure of the similarity between two molecules on the basis of their size, shape, electronic distribution, lipid solubility, water solubility, or chemical reactivity [7] . The most widely used form of similarity index applied for calculation of 3D molecular similarity was proposed by Carbo: RAB = ʃ PA.PB dv/(ʃ P 2 Adv) 1/2 (ʃ P 2 B dv) 1/2 (1) The numerator in the equation 1 measures property overlap while denominator normalizes similarity result. The difference between equations for Carbo and Petke (Hodgkin) index is only in the denominator part with respect to Carbo index, it is less sensitive to shape of the property but more sensitive to its magnitude [8,9] Richards and Hodgkin 1988]. It is defined as: Hst =. ૛.∑ ࢙. ࢚  =૚ .∑ ૛ ࢙+∑ ૛࢚  =૚  =૚ =૚− ૛ ∑ ૛ ࢙+∑ ૛࢚  =૚  =૚ (2) Mathematical graphs and matrices represent, characterize and analyze biological sequences, chemical structure features and gene expression analysis. Discovery of useful knowledge from databases, [10] Insights data mining that opens new door for optimization of compounds in terms of discovering new therapeutic compound for HIV. Data mining in 2D QSAR involves collection, selection, transformation, visualization and evaluation of the extracted knowledge (Descriptors). There are number of algorithms based on the nature of the data as well as the desired knowledge that try to fit a model to the data [11] . In this perspective Similarity analysis of a series of compounds was carried out to find the possible descriptors which unfolds important structural information about the viral nucleocapsid Zn finger