Quantitative structure-activity relationships (QSAR) have been applied for decades in the development of relationships between physicochemical properties of chemical substances and their biological activities to obtain a reliable statistical model for prediction of the activities of new chemical entities. The fundamental principle underlying the formalism is that the difference in structural properties is responsible for the variations in biological activities of the compounds. In the classical QSAR studies, affinities of ligands to their binding sites, inhibition constants, rate constants, and other biological end points, with atomic, group or molecular properties such as lipophilicity, polarizability, electronic and steric properties (Hansch analysis) or with certain structural features (Free-Wilson analysis) have been correlated. However such an approach has only a limited utility for designing a new molecule due to the lack of consideration of the 3D structure of the molecules. 3D-QSAR has emerged as a natural extension to the classical Hansch and Free-Wilson approaches, which exploits the three-dimensional properties of the ligands to predict their biological activities using robust chemometric techniques such as PLS, G/PLS, ANN etc. It has served as a valuable predictive tool in the design of pharmaceuticals and agrochemicals. Although the trial and error factor involved in the development of a new drug cannot be ignored completely, QSAR certainly decreases the number of compounds to be synthesized by facilitating the selection of the most promising candidates. Several success stories of QSAR have attracted the medicinal chemists to investigate the relationships of structural properties with biological activity. This review seeks to provide a bird's eye view of the different 3D-QSAR approaches employed within the current drug discovery community to construct predictive structure-activity relationships and also discusses the limitations that are fundamental to these approaches, as well as those that might be overcome with the improved strategies. The components involved in building a useful 3D-QSAR model are discussed, including the validation techniques available for this purpose.

This paper has two objectives: first to develop an in silico model for the prediction of blood brain barrier permeability of new chemical entities and second to find the role of active transport specific to the P-glycoprotein (P-gp) substrate probability in blood brain barrier permeability. An Artificial Neural Network (ANN) model has been developed to predict the ratios of the steady-state concentrations of drugs in the brain to those in the blood (logBB) from their molecular structural parameters. Seven descriptors including P-gp substrate probability have been used for model development. The developed model is able to capture a relationship between P-gp and logBB. The predictive ability of the ANN model has also been compared with earlier computational models.

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Several intracellular pathogens arrest the phagosome maturation in the host cells to avoid transport to lysosomes. In contrast, the Leishmania containing parasitophorous vacuole (PV) is shown to recruit lysosomal markers and thus Leishmania is postulated to be residing in the phagolysosomes in macrophages. Here, we report that Leishmania donovani specifically upregulates the expression of Rab5a by degrading c-Jun via their metalloprotease gp63 to downregulate the expression of miR-494 in THP-1 differentiated human macrophages. Our results also show that miR-494 negatively regulates the expression of Rab5a in cells. Subsequently, L. donovani recruits and retains Rab5a and EEA1 on PV to reside in early endosomes and inhibits transport to lysosomes in human macrophages. Similarly, we have also observed that Leishmania PV also recruits Rab5a by upregulating its expression in human PBMC differentiated macrophages. However, the parasite modulates the endosome by recruiting Lamp1 and inactive pro-CathepsinD on PV via the overexpression of Rab5a in infected cells. Furthermore, siRNA knockdown of Rab5a or overexpression of miR-494 in human macrophages significantly inhibits the survival of the parasites. These results provide the first mechanistic insights of parasite-mediated remodeling of endo-lysosomal trafficking to reside in a specialized early endocytic compartment.

Differential functions of Rab5 isoforms in endocytosis are not well characterized. Here, we cloned, expressed, and characterized Rab5a and Rab5b from Leishmania and found that both of them are localized in the early endosome. To understand the role of LdRab5 isoforms in different modes of endocytosis in Leishmania, we generated transgenic parasites overexpressing LdRab5a, LdRab5b, or their dominant-positive (LdRab5a:Q93L and LdRab5b:Q80L) or dominant-negative mutants (LdRab5a: N146I and LdRab5b:N133I). Using LdRab5a or its mutants overexpressing parasites, we found that LdRab5a specifically regulates the fluid-phase endocytosis of horseradish peroxidase and also specifically induced the transport of dextran-Texas Red to the lysosomes. In contrast, cells overexpressing LdRab5b or its mutants showed that LdRab5b explicitly controls receptormediated endocytosis of hemoglobin, and overexpression of LdRab5b:WT enhanced the transport of internalized Hb to the lysosomes in comparison with control cells. To unequivocally demonstrate the role of Rab5 isoforms in endocytosis in Leishmania, we tried to generate null-mutants of LdRab5a and LdRab5b parasites, but both were lethal indicating their essential functions in parasites. Therefore, we used heterozygous LdRab5a ؉/؊ and LdRab5b ؉/؊ cells. LdRab5a ؉/؊ Leishmania showed 50% inhibition of HRP uptake, but hemoglobin endocytosis was uninterrupted. In contrast, about 50% inhibition of Hb endocytosis was observed in LdRab5b ؉/؊ cells without any significant effect on HRP uptake. Finally, we tried to identify putative LdRab5a and LdRab5b effectors. We found that LdRab5b interacts with clathrin heavy chain and hemoglobin receptor. However, LdRab5a failed to interact with the clathrin heavy chain, and interaction with hemoglobin receptor was significantly less. Thus, our results showed that LdRab5a and LdRab5b differentially regulate fluid phase and receptor-mediated endocytosis in Leishmania.

Endosome biogenesis in eukaryotic cells is critical for nutrient uptake and plasma membrane integrity. Early endosomes initially contain Rab5, which is replaced by Rab7 on late endosomes prior to their fusion with lysosomes. Recruitment of Rab7 to endosomes requires the Mon1-Ccz1 guanosine exchange factor (GEF). Here, we show that full function of the Drosophila Mon1-Ccz1 complex requires a third stoichiometric subunit, termed Bulli. Bulli localises to Rab7 positive endosomes, in agreement with its function in the GEF complex. Using Drosophila nephrocytes as a model system, we observe that absence of Bulli results in (i) reduced endocytosis, (ii) Rab5 accumulation within non-acidified enlarged endosomes, and (iii) defective Rab7 localisation and (iv) impaired endosomal maturation. Moreover, longevity of animals lacking bulli is affected. Both Mon1-Ccz1 dimer and a Bulli-containing trimer display Rab7 GEF activity. In summary, this suggests a key role of Bulli in Rab5 to Rab7 transition during endosomal maturation rather than a direct influence on the GEF activity of Mon1-Ccz1.

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Quantitative Structure-Activity Relationships (QSAR) are being used since decades for prediction of biological activity, lead optimization, classification, identification and explanation of the mechanisms of drug action, and prediction of novel structural leads in drug discovery. Though the technique has lived up to its expectations in many aspects, much work still needs to be done in relation to problems related to the rational design of peptides. Peptides are the drugs of choice in many situations, however, designing them rationally is a complicated task and the complexity increases with the length of their sequence. In order to deal with the problem of peptide optimization, one of our recently developed QSAR formalisms CoRIA (Comparative Residue Interaction Analysis) is being expanded and modified as: reverse-CoRIA (rCoRIA) and mixed-CoRIA (mCoRIA) approaches. In these methodologies, the peptide is fragmented into individual units and the interaction energies (van der Waals, Coulombic and hydrophobic) of each amino acid in the peptide with the receptor as a whole (rCoRIA) and with individual active site residues in the receptor (mCoRIA) are calculated, which along with other thermodynamic descriptors, are used as independent variables that are correlated to the biological activity by chemometric methods. As a test case, the three CoRIA methodologies have been validated on a dataset of diverse nonamer peptides that bind to the Class I major histocompatibility complex molecule HLA-A*0201, and for which some structure activity relationships have already been reported. The different models developed, and validated both internally as well as externally, were found to be robust with statistically significant values of r(2) (correlation coefficient) and r(2)(pred) (predictive r(2)). These models were able to identify all the structure activity relationships known for this class of peptides, as well uncover some new relationships. This means that these methodologies will perform well for other peptide datasets too. The major advantage of these approaches is that they explicitly utilize the 3D structures of small molecules or peptides as well as their macromolecular targets, to extract position-specific information about important interactions between the ligand and receptor, which can assist the medicinal and computational chemists in designing new molecules, and biologists in studying the influence of mutations in the target receptor on ligand binding.