Computer aided drug design(cadd) for Rheumatoid arthritis using QSAR approach

Transcription

1 Review Article ISSN: Swaytha Raman /JPR:BioMedRx: An International Journal 2013,1(6), Available online through Computer aided drug design(cadd) for Rheumatoid arthritis using QSAR approach Swaytha Raman * Assistant Professor,Department of Information Technology,Jawahar Engineering College,Chennai-93, Tamil Nadu,India. Received on: ; Revised on: ; Accepted on: ABSTRACT Quantitative Structure Activity Relationship (QSAR) study was performed for 74 compounds to test their inhibitory concentration activity(ic 50 ) for 4,6-bis-anilino-1H-pyrrolo[2,3-d]pyrimidine derivatives for the disease Rheumatoid arthritis it has the important target of Insulin like growth factor 1 receptor(igf-1r). The compounds are divided in to training set and test set using the leave 3 out method. Multiple linear regression analysis was done by calculating various molecular descriptors such as molecular volume, molecular mass, molecular refractivity, log P, kappa 1 index, K alpha 1 index etc. The (regression coefficient r = ) & ( r= ) then cluster analysis was done for single linkage, group average & complete linkage method to compare which method is best to show maximum clusters. Using the software Tool for structure activity relationship (TSAR) 3.3 version is performed for QSAR study to prove which drug is best for rheumatoid arthritis disease Keywords:CADD,Rheumatoid arthritis,qsar INTRODUCTION RHEUMATOID ARTHRITIS Rheumatoid arthritis is an autoimmune disease which means the arthritis results from your immune system attacking your body s own tissues. It is a form of arthritis that causes pain swelling, stiffness & loss of function in our joints. (1)Autoimmune diseases are illness that occurs when the body s tissues are mistakenly attacked by their own immune system. The immune system is a complex organization of cells and antibodies designed normally to seek and destroy invaders of the body, particularly infections. Patients with autoimmune diseases have antibodies in their blood that target their own body tissues, where they can be associated with inflammation.(2) Because it can affect multiple other organs of the body, rheumatoid arthritis is referred to as a systemic illness and is sometimes called rheumatoid disease. Rheumatoid arthritis (RA) is a chronic, systemic, inflammatory disorder that may affect many tissues and organs, but principally attacks the joints producing an inflammatory synovitis that often progresses to destruction of the particular cartilage and ankylosis of *Corresponding author. Swaytha Raman Assistant Professor, Department of Information Technology, Jawahar Engineering College,Chennai-93, Tamil Nadu,India. the joints. Rheumatoid arthritis can also produce diffuse inflammation in the lungs, pericardium, pleura, and sclera, and also nodular lesions, most common in subcutaneous tissue under the skin. Although the cause of rheumatoid arthritis is unknown, autoimmunity plays a pivotal role in its chronicity and progression. A rheumatologist, an expert in the diseases of joints and connective tissues. INSULIN LIKE GROWTH FACTOR 1 RECEPTOR Insulin like growth factor 1 receptor (IGF-1R) is an important target in rheumatoid arthritis. The IGF-1R functions as agonist against the disease. The Insulin-like Growth Factor 1 (IGF-1) Receptor is a Transmembrane receptor that is activated by IGF-1 and by the related growth factor IGF-2.(3,4) It belongs to the large class of tyrosine kinase receptors. This receptor mediates the effects of IGF-1, which is a polypeptide protein hormone similar in molecular structure to insulin. IGF-1 plays an important role in growth and continues to have anabolic effects in adults - meaning that it can induce hypertrophy of skeletal muscle and other target tissues. Mice lacking the IGF-1 receptor die late in development, and show a dramatic reduction in body mass, testifying to the strong growth-promoting effect of this receptor. Mice carrying only one functional copy of igf1r are normal, but exhibit a ~15% decrease in body mass. ROLE OF IGF-1R IN RHEUMATOID ARHRITIS Insulin-like growth factor-1 (IGF-1) plays a key role in the regulation

2 Swaytha Raman /JPR:BioMedRx: An International Journal 2013,1(6), of cartilage degradation in osteoarthritis and90 rheumatoid arthritis. MATERIALS AND METHODS TSAR (TOOL FOR STRUCTURE ACTIVITY RELATIONSHIP) A tool for structure activity relationship (TSAR) is commercial software used for mainly QSAR study. TSAR is a program to investigate quantitative structure activity relationship (QSAR). (11) TSAR is fully integrated QSAR package for library design & lead optimization. TSAR 3.3 version is used for QSAR studies. It is intended to provide all the functions required to carry out any QSAR investigation, whether in pharmaceutical, agrochemical, toxicological or any other area of application. TSAR uses an integrated approach to provide all components together. It uses a chemically aware spreadsheet to store and manipulate different types of data, including: molecular descriptions, 3D structures, activity data, computed data. Tsar 3.2 is structure-activity software that assists in identifying new drug leads with automatic ADME calculation, FIRM analysis, virtual library enumeration, and database connectivity. This software computes Lipinski s Rules for identifying drug-like compounds. It then tests the rules for an entire series of compounds and then creates a new spreadsheet column with the number of violations counted. This software also features Formal Inference-based Recursive Modeling that automatically shows researchers a tree chart that ranks attributes in order of importance. The results are easy for chemists to use and firmly grounded in modern statistical properties.(5,6) Statistical Techniques: Independent and Dependent Variables Dependent variable The dependent variable (or response variable) is the variable that is

3 Swaytha Raman /JPR:BioMedRx: An International Journal 2013,1(6), being fitted to in a regression model. It is referred to as dependent as it is assumed that its values are dependent on the values of independent variables that will be used to generate the predictive model. Independent variable The independent variables are the variables that are being used to fit a regression to a dependent Variable in partial least squares, principal component analysis, or multiple linear regressions.they are referred to as independent as their values are assumed not to depend on the values of the dependent variable. Principal Component Analysis Principal component analysis (PCA) transforms a number of independent variables into a number of uncorrelated factors that explain the variance of the dependent variable. The first factor accounts for as much of the variability in the data as possible, and each succeeding factor accounts for as much of the remaining variability as possible. The eigenvalues of the covariance matrix from PCA indicate the portion of the total variance accounted for by each factor, where the total variance is generally defined as equal to the number of independent variables.principal component analysis can be applied in cases where the number of independent descriptors is greater than the number of molecules.principal component analysis is similar to partial least squares, but it focuses on explaining the maximum variance possible in only the dependent descriptors, while PLS considers the variance in both the dependent and independent descriptors.(9) While it is possible to use PCA to generate models to fit multiple dependent variables Multiple Linear Regressions Multiple linear regressions (MLR) generate linear equations that describe the relationship between a set of independent descriptors and a dependent descriptor. MLR fits a straight line to the dependent descriptor using the following linear relationship: P j =E i ci x ij +co In the above equation, Pj is the property or activity that is to be predicted for each molecule j,the ci values are the regression coefficients, ij is the ith independent property for molecule j,and c0 is a constant. Values of the coefficients and c0 are fitted to give Pj values that reproduce(7). The dependent value for the jth molecule(10). In general, when fitting data using MLR it is advisable to use a data set with at least five times as many molecules as there are independent descriptors. RESULT & DISCUSSION Multiple linear regression analysis 74 compounds were taken for QSAR study for the Insulin like growth factor 1 receptor. The total compound is divided in to training set & test set by using leave 3 out method. Then calculate molecular descriptors such as molecular volume, Molecular refractivity, Log P etc. Multiple linear regression (MLR) analysis was carried out for the compounds to check the relationship between molar refractivity & Activity. There should be a strong correlation between these parameters. The results shows the regression coefficient r= , r 2 = & the cross validation (test set) r^2 (cv) = then plot graph for identify points. Finally Eliminating the outliers & comparing the result in another result of Multiple linear regression analysis & the result of r= , r2= & r^2(cv)= finally second result shows low r, r 2, r^2cv & low residual variance. Insulin like growth factor 1 receptor is a target for Rheumatoid arthritis. 180 hits are totally present for the target. Out of these 74 compounds are taken for present study. Loading a whole molecule of insulin like growth factor compounds,compound name such as a set of 4,6-bis aniline-1 pyrrolo[2,3-d] pyrimidine, cyanoquinoline, benzimidazole scaffold, substituted benzimidazole, substituted pyrazolopyrimidine, Pyrrole Analogue, isoquinolinedione, aminopyrimidine carbamate & its inhibitory concentration activity are loaded in the project window of TSAR software. Molecular volume is one of the parameter needed for calculating multiple linear regressions. TSAR calculates the molecular volume in units of A 0 3. This calculation assumes standard van der Waals radii for the atoms in the substituent & requires accurate structures if it is to give meaningful results. After calculating molecular volume we need to calculate the molecular mass & molecular surface area. The target of IGF-1R has 74 compounds, name, IC50 activity & their molecular descriptors have calculated & used as parameters for multiple linear regression analysis. Independent variable is otherwise known as Molecular descriptors. Result shows that 74 rows included in model, 13 independent variables considered. 7 variables included in final model using f test stepping. Regression coefficient r= , r 2 = & the cross validation (test set) of r^2(cv) = Tsar performs a standard multiple regression calculation and displays the summary of results in the Results Manager Window. As one would expect, the multiple correlation (regression) coefficient (0.875) confirms that there is a strong relationship between Molar Refractivity and Activity. This result shows no strong correlation between molar refractivity & activity.

4 Swaytha Raman /JPR:BioMedRx: An International Journal 2013,1(6), MLR analysis is done for another time mainly for comparing the regression coefficient, r 2 & graph. Again we repeat multiple regressions for compare the first regression result.

5 Swaytha Raman /JPR:BioMedRx: An International Journal 2013,1(6), Cluster analysis: Cluster analysis is done for identifying similar substituent in a group. In the Agglomeration method section three groups are present, such as Single linkage minimum distance, Group average (weighted average), Complete linkage (maximum distance). We compare the three groups result & conclude which group shows even clustering & maximum clusters. Finally the group average method shows 10 clusters & the complete linkage method shows the maximum distance of & shows even clustering in dendrogram window so conclude complete linkage method is best to show even clustering. Result of single linkage, group average& complete linkage method shows complete linkage clustering compare to three methods. method have maximum distance of & show even

6 Swaytha Raman /JPR:BioMedRx: An International Journal 2013,1(6), CONCLUSION In the present work QSAR analysis on a series of IGF1R compounds against Rheumatoid arthritis was carried out using the multiple linear regression analysis technique. The best model was selected based on the statistical parameters & molecular descriptors. The presented QSAR model has high regression coefficient r= , r 2 = & the cross validation r^2(cv= The second MLR result shows r= , r 2 = it conforms the no improvement in linear correlation coefficient. Then cluster analysis is done to identify similar substituent in a group & the dendrogram is drawn for three method finally complete linkage methods shows best even clustering & the maximum distance of compared to two methods. The MLR & cluster analysis is done by using the software TSAR 3.3 version. The 4, 6-bis-anilino-1H-pyrrolo [2, 3-d] pyrimidine, 9 derivatives shows lowest inhibitory activity& give best result in multiple linear regression analysis for the rheumatoid arthritis disease, so finally Anakinra is a best drug proven for rheumatoid arthritis disease using this QSAR study. REFERENCES: 1. National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS). Questions and answers about arthritis and rheumatic diseases. July Available at arthritis_rheumatic_qa.asp (accessed on 15 July 2012). 2. Silman AJ. Rheumatoid arthritis. In: Silman AJ, Hochberg MC, eds. Epidemiology of the rheumatic diseases. Oxford Press, Oxford; Winchester R, Dwyer E, Rose S. The genetic basis of rheumatoid arthritis: the shared epitope hypothesis. Rheumatic Diseases Clinics of North America. 1992; 18: Lawrence RC, Helmick CG, Arnett FC, et al. Estimates of the prevalence of arthritis and selected musculoskeletal disorders in the United States. Arthritis and Rheumatism. 1998; 41: Wilder RL. Neuroimmunoendocrinology of the rheumatic diseases: past, present, and future. Annals of the New York Academy of Sciences. 2002; 966: Centers for Disease Control and Prevention. Prevalence of arthritis: United States, Morbidity and Mortality Weekly Report. 2001; 50: Lee DM, Weinblatt ME. Rheumatoid arthritis. Lancet. 2001; 358: Akil M, Amos RS. ABC of rheumatology. Rheumatoid arthritis I: Clinical features and diagnosis. BMJ. 1995; 310: Yocum DE, Castro WL, Cornett M. Exercise, education, and behavioral modification as alternative therapy for pain and stress in rheumatic disease. Rheumatic Diseases Clinics of North America. 2000; 26: Wright A, Sluka KA. Nonpharmacological treatments for musculoskeletal pain. Clinical Journal of Pain. 2001; 17: Macfarlane GJ, El-Metwally A, De Silva V, et al. Evidence for the efficacy of complementary and alternative medicines in the management of rheumatoid arthritis: a systematic review. Rheumatology. 2011; 50: Wang C, de Pablo P, Chen X, et al. Acupuncture for pain relief in patients with rheumatoid arthritis: a systematic review. Arthritis and Rheumatism. 2008; 59: Source of support: Nil, Conflict of interest: None Declared