SAR and QSAR in Environmental Research

QSAR study of some anti-hyperglycaemic sulphonylurea drugs
pp. 439-448(10)
Authors: Dearden, J.C.; Hewitt, M.; Rowe, P.H.

Monte Carlo QSAR models for predicting organophosphate inhibition of acetycholinesterase
pp. 449-460(12)
Authors: Veselinović, J.B.; Nikolić, G.M.; Trutić, N.V.; Živković, J.V.; Veselinović, A.M.

3D-QSAR and docking studies on adenosine A_2A receptor antagonists by the CoMFA method
pp. 461-477(17)
Authors: Pourbasheer, E.; Shokouhi Tabar, S.; Masand, V.H.; Aalizadeh, R.; Ganjali, M.R.

Predicting the hazardous dose of industrial chemicals in warm-blooded species using machine learning-based modelling approaches
pp. 479-498(20)
Authors: Gupta, S.; Basant, N.; Singh, K.P.

QSPR study on refractive indices of solvents commonly used in polymer chemistry using flexible molecular descriptors
pp. 499-506(8)
Authors: Fioressi, S.E.; Bacelo, D.E.; Cui, W.P.; Saavedra, L.M.; Duchowicz, P.R.

Combined molecular dynamics and continuum solvent approaches (MM-PBSA/GBSA) to predict noscapinoid binding to γ-tubulin dimer
pp. 507-519(13)
Authors: Suri, C; Naik, P.K

Erratum
pp. 521-521(1)