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Background & objectives: the interaction of albumin- the most important plasma protein- with various drugs leads to variations in the pharmacokinetics of drugs. Since interaction of different pharmaceuticals with albumin is determinant in the estimation of dose and prediction of drug-drug and drug-food interferences, studying the binding ability of different drugs with albumin is an active area of research.
Methods: Docking studies were performed by Lamarckian Genetic Algorithm of AutoDock 4.2 program. The three-dimensional structures of albumin were obtained from Brookhaven protein data bank (2BXD & 2BXF; www.rcsb.org). Pre-processing of molecules was done using AM1 method and AutoDock Tools 1.5.4 software. AM1 optimization method was performed using Polak-Ribiere (conjugate gradient) algorithm with termination condition as RMS gradient of 0.1 Kcal/Å mol. Schematic representation of drug-albumin complexes were obtained by Ligplot.
Results: Oxiconazole and fenticonazole were top-ranked drugs in binding to site 1 (subdomain IIA) and 2 (subdomain IIIA) of albumin, respectively (∆G_b -9.01 and -9.89 kcal.mol^-1). Leu238 and Ala291 were the key residues of site 1 due to hydrophobic contacts with all of the antifungals, while Ile388, Asn391 and Leu430 were the key residues of site 2. A few structure binding relationship rules could be extracted from the binding pattern of antifungal drugs.
Conclusion: It was found that antifungal agents might have higher affinity toward site 2 of albumin rather than site 1. Estimated high albumin affinities of antifungals provided the possibility of drug-drug or drug-food interactions. It seemed that hydrophobic contacts were more significant in binding antifungals to albumin.
 

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Background & objectives: Drug-repurposing is the study on application of existing drugs for treatment or control of other diseases. Major advantage of the technique relies on a nominated drug molecule that is applied for pharmacodynamics optimization due to lack of serious pharmacokinetics challenges. According to the importance of the subject, a present contribution has been dedicated to the in-silico analysis of a few drug classes with the aim of achieving potential anti-leishmanial pharmacophores.   
Methods: 3D structure of protein targets within leishmania parasite were retrieved from Brookhaven Protein Data Bank (PDB) on the basis of literature reports to evaluate the related complexes with drugs via molecular docking. Qualitative and quantitative analysis of drug-target interaction patterns in docked complexes offered drugs with higher binding affinities toward targets and finally structural patterns or hypothetical anti-leishmanial pharmacophores were proposed with regard to the top-ranked pharmaceutical compounds.
Results: Highest free binding energy could be estimated for Nateglinide in binding to farnesyl diphosphate synthase (ΔG_b -13.30 kcal/mol). Among steroids, Norgestrel synthase (ΔG_b -9.48 kcal/mol) and Testosterone synthase (ΔG_b -8.05 kcal/mol) exhibited higher enzyme binding affinities and Arg82 was a key residue in making hydrogen bonds. Within fused tricyclic structural patterns, mirtazapine exhibited highest binding affinity to deoxy uridine triphosphate (ΔG_b -8.64 kcal/mol). In Carbamazepine, amide substituent of the central ring facilitated the formation of two effective hydrogen bonds with Gln21 and Asn25 in deoxy uridine triphosphate. 
Conclusion: On the basis of obtained results for steroids and fused tricyclic scaffolds, it will be possible to design molecules that can inhibit several pathogenic targets simultaneously.