Abstract
A newly developed three-dimensional holographic vector of atomic interaction field (3D-HoVAIF) was used to describe the chemical structures of 28 arylamide derivatives as antituberculosis drug. Here, a quantitative structure activity relationship model was built by partial least square regression (PLS). The estimation stability and generalization ability of the model was strictly analyzed by both internal and external validations. The correlation coefficients of established PLS model (R 2), leave-one-out cross-validation (Q 2LOO ), and predicted values versus experimental ones of external samples (Q 2ext ) were 0.800, 0.778 and 0.821, respectively. The results of PLS exhibited both favorable estimation stability and good prediction capability. Thus, this newly developed 3D-HoVAIF could preferably express information related to biological activity of arylamide derivatives.
Similar content being viewed by others
References
Abbasitabar F, Zare-Shahabadi V (2012) Development predictive QSAR models for artemisinin analogues by various feature selection methods: a comparative study. SAR QSAR Environ Res 23:1–15
Bak A, Magdziarz T, Polanski J (2012) Pharmacophore-based database mining for probing fragmental drug-likeness of diketo acid analogues. SAR QSAR Environ Res 23:185–204
Bonchev D, Thomas S, Apte A, Kier LB (2010) Cellular automata modelling of biomolecular networks dynamics. SAR QSAR Environ Res 21:77–102
Gaurav A, Gautam V, Singh R (2012) Quantitative structure–activity relationship and design of polysubstituted quinoline derivatives as inhibitors of phosphodiesterase 4. Med Chem Res 21:3087–3101
Golbraikh A, Tropsha A (2002) Beware of q2! J Mol Graph Model 20:269–276
Hahn M (1995) Receptor surface models. 1. Definition and construction. J Med Chem 38:2080–2090
Hasel W, Hendrikson TF, Still WC (1988) A rapid approximation to the solvent accessible surface areas of atoms. Tetrahedron Comput Methodol 1:103–116
Kellogg GE, Abraham DJ (1992) KEY, LOCK, and LOCKSMITH: complementary hydropathic map predictions of drug structure from a known receptor–receptor structure from known drugs. J Mol Graph 10:212–217
Kellogg GE, Semus SF, Abraham DJ (1991) HINT: a new method of empirical hydrophobic field calculation for CoMFA. J Comput Aided Mol Des 5:545–552
Kellogg GE, Joshi GS, Abraham DJ (1992) New tools for modeling and understanding hydrophobicity and hydrophobic interactions. Med Chem Res 1:444–453
Levitt M (1983) Protein folding by restrained energy minimization and molecular dynamics. J Mol Biol 170:723–764
Levitt M, Perutz MF (1988) Aromatic rings act as hydrogen bond acceptors. J Mol Biol 201:751–754
Nayak VR, Kellogg GE (1994) Cyclodextrin-barbiturate inclusion complexes: a CoMFA/HINT 3-D QSAR study. Med Chem Res 3:491–502
Nie NH, Bent DH (1975) SPSS: statistical package for the social sciences. McGraw-Hill, New York
Nowaczyk A, Kulig K (2012) QSAR studies on a number of pyrrolidin-2-one antiarrhythmic arylpiperazinyls. Med Chem Res 21:373–381
Pei J, Wang Q, Zhou J, Lai L (2004) Estimating protein–ligand binding free energy: atomic solvation parameters for partition coefficient and solvation free energy calculation. Proteins Struct Funct Genet 57:651–664
Polanski J, Gieleciak R, Bak A (2003) Probability issues in molecular design: predictive and modeling ability in 3D-QSAR schemes. Comb Chem High Throughput Screen 7:793–807
Polanski J, Bak A, Gieleciak R, Magdziarz T (2006) Modeling Robust QSAR. J Chem Inf Model 46:2310–2318
Punkvang A, Saparpakorn P, Hannongbua S, Wolschann P, Berner H, Pungpo P (2010) Insight into crucial inhibitor–enzyme interaction of arylamides as novel direct inhibitors of the enoyl ACP reductase (InhA) from Mycobacterium tuberculosis: computer-aided molecular design. Monatsh Chem 141:1029–1041
Stewart J (1990) MOPAC: a semiempirical molecular orbital program. J Comput Aided Mol Des 4:1–103
Tong JB, Liu SL (2008) Three-dimensional holographic vector of atomic interaction field applied in QSAR of anti-HIV HEPT analogues. QSAR & Comb Sci 27:330–337
Tong JB, Zhou P, Zhang SW, Zhou Y, Mei H, Zeng H, Li MP, Li ZL (2006) Three-dimensional holographic vector of atomic interaction field for quantitative structure-retention relationship of purine bases. Chin Sci Bull 51:1557–1562
Tong JB, Li YF, Liu SL, Meng YL (2010) Quantitative structure activity relationship studies of benzoxazinone derivative antithrombotic drug using new three-dimensional structure descriptors. Chin J Struct Chem 29:1893–1899
Tong JB, Che T, Liu SL, Li YF, Wang P, Xu XM, Chen Y (2011a) SVEEVA descriptor application to peptide QSAR. Arch Pharm 344(11):719–725
Tong JB, Che T, Li YF, Wang P, Xu XM, Chen Y (2011b) A descriptor of amino acids: SVRG and its application to peptide quantitative structure–activity relationship. SAR QSAR Environ Res 22(5–6):611–620
Tong JB, Chen Y, Liu SL, Che T, Xu XM (2012) A descriptor of amino acids SVWG and its applications in peptide QSAR. J Chemom 26:549–555
Tropsha A, Gramatica P, Gombar VK (2003) The importance of being earnest: validation is the absolute essential for successful application and interpretation of QSPR models. QSAR 22:69–77
Vilcheze C, Weisbrod TR, Chen B, Kremer L, Hazbon MH, Wang F, Alland D, Sacchettini JC, Jacobs WR Jr (2005) Altered NADH/NAD+ ratio mediates coresistance to isoniazid and ethionamide in mycobacteria. Antimicrob Agents Chemother 49:708–720
Wireko FC, Kellogg GE, Abraham DJ (1991) Allosteric modifiers of hemoglobin. 2. Crystallographically determined binding sites and hydrophobic binding/interaction analysis of novel hemoglobin oxygen effectors. J Med Chem 34:758–767
Wold S (1978) Cross-validation estimation of the number of components in factor and principal components models. Technometrics 20:897–903
Wold S, Sjostrom M (1977) SIMCA: a method for analyzing chemical data in terms of similarity and analogy. ACS symposium series 52: chapter 12, American Chemical Society, Washington, DC, pp 243–282
World Health Organization (WHO) (2012) Fact sheet on tuberculosis. Available at http://www.who.int/tb/publications/global_report/en/. Accessed 16 Jan 2013
Zhang Y (2005) The magic bullets and tuberculosis drug targets. Annu Rev Pharmacol Toxicol 45:529–564
Zhou P, Tian FF, Li ZL (2007) Three dimensional holographic vector of atomic interaction field (3D-HoVAIF). Chemom Intell Lab Syst 87:88–94
Acknowledgments
The authors appreciate the financial support from the National Natural Science Funds of China (21275094), the Scientific Research Planning Program of the Education Department of Shaanxi Province (12JK0629), and the Graduate Innovation Fund of Shaanxi University of Science and Technology.
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Tong, J., Chen, Y., Liu, S. et al. QSAR studies of antituberculosis drug using three-dimensional structure descriptors. Med Chem Res 22, 4946–4952 (2013). https://doi.org/10.1007/s00044-013-0502-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00044-013-0502-y