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A multiple criteria approach is presented, that is used to perform a comparative analysis of four recently developed combinatorial libraries to drugs, Molecular Libraries Small Molecule Repository (MLSMR) and natural products. The compound databases were assessed in terms of physicochemical properties, scaffolds and fingerprints. The approach enables the analysis of property space coverage, degree of overlap between collections, scaffold and structural diversity and overall structural novelty. The degree of overlap between combinatorial libraries and drugs was assessed using the R-NN curve methodology, which measures the density of chemical space around a query molecule embedded in the chemical space of a target collection. The combinatorial libraries studied in this work exhibit scaffolds that were not observed in the drug, MLSMR and natural products collections. The fingerprint-based comparisons indicate that these combinatorial libraries are structurally different to current drugs. The R-NN curve methodology revealed that a proportion of molecules in the combinatorial libraries are located within the property space of the drugs. However, the R-NN analysis also showed that there are a significant number of molecules in several combinatorial libraries that are located in sparse regions of the drug space.

A prospective study was conducted on 90 patients of tuberculosis at 2 directly observed treatment short course (DOTS) cum microscopy centers in an urban area of Delhi. The WHOQOL-BREF (Hindi) questionnaire was used to assess the QOL at the onset of treatment, after 3 months of treatment under DOTS, and at completion of treatment. Patients with tuberculosis had significantly lower mean scores than controls for overall QOL. The most affected domains were physical and psychological. Women scored significantly better than men in the physical and environmental domains. Overall QOL scores were lowest for category II and significantly lower for the psychological and social domains. The mean scores after treatment were significantly lower than controls for overall QOL, the social and environmental domains. The DOTS regimen improves the QOL and its domains; however, they remain significantly affected compared to the healthy controls.

Polypharmacology has emerged as a new theme in drug discovery. In this paper, we studied polypharmacology using a ligand-based target fishing (LBTF) protocol. To implement the protocol, we first generated a chemogenomic database that links individual protein targets with a specified set of drugs or target representatives. Target profiles were then generated for a given query molecule by computing maximal shape/chemistry overlap between the query molecule and the drug sets assigned to each protein target. The overlap was computed using the program ROCS (Rapid Overlay of Chemical Structures). We validated this approach using the Directory of Useful Decoys (DUD). DUD contains 2950 active compounds, each with 36 property-matched decoys, against 40 protein targets. We chose a set of known drugs to represent each DUD target, and we carried out ligand-based virtual screens using data sets of DUD actives seeded into DUD decoys for each target. We computed Receiver Operator Characteristic (ROC) curves and associated area under the curve (AUC) values. For the majority of targets studied, the AUC values were significantly better than for the case of a random selection of compounds. In a second test, the method successfully identified off-targets for drugs such as rimantadine, propranolol, and domperidone that were consistent with those identified by recent experiments. The results from our ROCS-based target fishing approach are promising and have potential application in drug repurposing for single and multiple targets, identifying targets for orphan compounds, and adverse effect prediction.

DNA methyltransferases (DNMTs) are a family of enzymes that methylate DNA at the C5 position of cytosine residues, and their inhibition is a promising strategy for the treatment of various developmental and proliferative diseases, particularly cancers. In the present study, a binding model for hydralazine, with a validated homology model of human DNMT, was developed by the use of automated molecular docking and molecular dynamics simulations. The docking protocol was validated by predicting the binding mode of 2'-deoxycytidine, 5-azacytidine, and 5-aza-2'-deoxycytidine. The inhibitory activity of hydralazine toward DNMT may be rationalized at the molecular level by similar interactions within the binding pocket (e.g., by a similar pharmacophore) as established by substrate-like deoxycytidine analogues. These interactions involve a complex network of hydrogen bonds with arginine and glutamic acid residues that also play a major role in the mechanism of DNA methylation. Despite the different scaffolds of other non-nucleoside DNMT inhibitors such as procaine and procainamide, the current modeling work reveals that these drugs exhibit similar interactions within the DNMT1 binding site. These findings are valuable in guiding the rational design and virtual screening of novel DNMT inhibitors.

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␣-Conotoxins are peptide neurotoxins isolated from venomous cone snails that display exquisite selectivity for different subtypes of nicotinic acetylcholine receptors (nAChR). They are valuable research tools that have profound implications in the discovery of new drugs for a myriad of neuropharmacological conditions. They are characterized by a conserved two-disulfide bond framework, which gives rise to two intervening loops of extensively mutated amino acids that determine their selectivity for different nAChR subtypes. We have used a multistep synthetic combinatorial approach using ␣-conotoxin ImI to develop potent and selective ␣ 7 nAChR antagonists. A positional scan synthetic combinatorial library was constructed based on the three residues of the n-loop of ␣-conotoxin ImI to give a total of 10,648 possible combinations that were screened for functional activity in an ␣ 7 nAChR Fluo-4/Ca 2؉ assay, allowing amino acids that confer antagonistic activity for this receptor to be identified. A second series of individual ␣-conotoxin analogs based on the combinations of defined active amino acid residues from positional scan synthetic combinatorial library screening data were synthesized. Several analogs exhibited significantly improved antagonist activity for the ␣ 7 nAChR compared with WT-ImI. Binding interactions between the analogs and the ␣ 7 nAChR were explored using a homology model of the amino-terminal domain based on a crystal structure of an acetylcholine-binding protein. Finally, a third series of refined analogs was synthesized based on modeling studies, which led to several analogs with refined pharmacological properties. Of the 96 individual ␣-conotoxin analogs synthesized, three displayed >10-fold increases in antagonist potency compared with WT-ImI.

The models used for modeling the airflow in the human airways are either 0-dimensional compartmental or full 3-dimensional (3D) computational fluid dynamics (CFD) models. In the former, airways are treated as compartments, and the computations are performed with several assumptions, thereby generating a low-fidelity solution. The CFD method displays extremely high fidelity since the solution is obtained by solving the conservation equations in a physiologically consistent geometry. However, CFD models (1) require millions of degrees of freedom to accurately describe the geometry and to reduce the discretization errors, (2) have convergence problems, and (3) require several days to simulate a few breathing cycles. In this paper, we present a novel, fast-running, and robust quasi-3D wire model for modeling the airflow in the human lung airway. The wire mesh is obtained by contracting the high-fidelity lung airway surface mesh to a system of connected wires, with well-defined radii. The conservation equations are then solved in each wire. These wire meshes have around O(1000) degrees of freedom and hence are 3000 to 25 000 times faster than their CFD counterparts. The 3D spatial nature is also preserved since these wires are contracted out of the actual lung STL surface. The pressure readings between the 2 approaches showed minor difference (maximum error = 15%). In general, this formulation is fast and robust, allows geometric changes, and delivers high-fidelity solutions. Hence, this approach has great potential for more complicated problems including modeling of constricted/diseased lung sections and for calibrating the lung flow resistances through parameter inversion.