SAR and QSAR in Environmental Research

Quantitative bioactivity prediction and pharmacophore identification for benzotriazine derivatives using the electron conformational-genetic algorithm in QSAR
pp. 217-238(22)
Authors: Sahin, K.; Sarıpınar, E.; Yanmaz, E.; Gecen, N.

Pharmacophore modelling, molecular docking and virtual screening for EGFR (HER 1) tyrosine kinase inhibitors
pp. 239-263(25)
Authors: Gupta, A. K.; Bhunia, S. S.; Balaramnavar, V. M.; Saxena, A. K.

Androgen receptor binding affinity: a QSAR evaluation
pp. 265-291(27)
Authors: Todorov, M.; Mombelli, E.; Ait-Aissa, S.; Mekenyan, O.

QSAR modelling of integrin antagonists using enhanced Bayesian regularised genetic neural networks
pp. 293-314(22)
Authors: Jalali-Heravi, M.; Mani-Varnosfaderani, A.

Using molecular docking to investigate the anti-breast cancer activity of low molecular weight compounds present on wild mushrooms
pp. 315-328(14)
Authors: Froufe, H. J. C.; Abreu, R. M. V.; Ferreira, I. C. F. R.

Does the oestrogen receptor encourage oestrogenicity in environmental pollutants? The case of 4-nonylphenol
pp. 329-350(22)
Authors: Graham, L. A.; Shaw, I. C.

Screening for low aquatic bioaccumulation (2): physico-chemical constraints
pp. 351-364(14)
Authors: Nendza, M.; Herbst, T.

Modelling of serotonin reuptake inhibitory and histamine H3 antagonistic activity of piperazine and diazepane amides: QSAR rationales for co-optimization of the activity profiles
pp. 365-383(19)
Authors: Sharma, B. K.; Singh, P.; Shekhawat, M.; Sarbhai, K.; Prabhakar, Y. S.

Fragment-similarity-based QSAR (FS-QSAR) algorithm for ligand biological activity predictions
pp. 385-410(26)
Authors: Myint, K. Z.; Ma, C.; Wang, L.; Xie, X. -Q.