16,391 research outputs found
Docking-based virtual screening of known drugs against murE of Mycobacterium tuberculosis towards repurposing for TB.
Repurposing has gained momentum globally and become an alternative avenue for drug discovery because of its better success rate, and reduced cost, time and issues related to safety than the conventional drug discovery process. Several drugs have already been successfully repurposed for other clinical conditions including drug resistant tuberculosis (DR-TB). Though TB can be cured completely with the use of currently available anti-tubercular drugs, emergence of drug resistant strains of Mycobacterium tuberculosis and the huge death toll globally, together necessitate urgently newer and effective drugs for TB. Therefore, we performed virtual screening of 1554 FDA approved drugs against murE, which is essential for peptidoglycan biosynthesis of M. tuberculosis. We used Glide and AutoDock Vina for virtual screening and applied rigid docking algorithm followed by induced fit docking algorithm in order to enhance the quality of the docking prediction and to prioritize drugs for repurposing. We found 17 drugs binding strongly with murE and three of them, namely, lymecycline, acarbose and desmopressin were consistently present within top 10 ranks by both Glide and AutoDock Vina in the induced fit docking algorithm, which strongly indicates that these three drugs are potential candidates for further studies towards repurposing for TB
Evolutionary conservation of influenza A PB2 sequences reveals potential target sites for small molecule inhibitors.
The influenza A basic polymerase protein 2 (PB2) functions as part of a heterotrimer to replicate the viral RNA genome. To investigate novel PB2 antiviral target sites, this work identified evolutionary conserved regions across the PB2 protein sequence amongst all sub-types and hosts, as well as ligand binding hot spots which overlap with highly conserved areas. Fifteen binding sites were predicted in different PB2 domains; some of which reside in areas of unknown function. Virtual screening of ~50,000 drug-like compounds showed binding affinities of up to 10.3 kcal/mol. The highest affinity molecules were found to interact with conserved residues including Gln138, Gly222, Ile529, Asn540 and Thr530. A library containing 1738 FDA approved drugs were screened additionally and revealed Paliperidone as a top hit with a binding affinity of -10 kcal/mol. Predicted ligands are ideal leads for new antivirals as they were targeted to evolutionary conserved binding sites
A New Multi-Objective Approach for Molecular Docking Based on RMSD and Binding Energy
Ligand-protein docking is an optimization problem based on predicting the position of a ligand with the lowest binding energy in the active site of the receptor. Molecular docking problems are traditionally tackled with single-objective, as well as with multi-objective approaches, to minimize the binding energy. In this paper, we propose a novel multi-objective formulation that considers: the Root Mean Square Deviation (RMSD) difference in the coordinates of ligands and the binding (intermolecular) energy, as two objectives to evaluate the quality of the ligand-protein interactions. To determine the kind of Pareto front approximations that can be obtained, we have selected a set of representative multi-objective algorithms such as NSGA-II, SMPSO, GDE3, and MOEA/D. Their performances have been assessed by applying two main quality indicators intended to measure convergence and diversity of the fronts. In addition, a comparison with LGA, a reference single-objective evolutionary algorithm for molecular docking (AutoDock) is carried out. In general, SMPSO shows the best overall results in terms of energy and RMSD (value lower than 2A for successful docking results). This new multi-objective approach shows an improvement over the ligand-protein docking predictions that could be promising in in silico docking studies to select new anticancer compounds for therapeutic targets that are multidrug resistant.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech
Non-bisphosphonate inhibitors of isoprenoid biosynthesis identified via computer-aided drug design.
The relaxed complex scheme, a virtual-screening methodology that accounts for protein receptor flexibility, was used to identify a low-micromolar, non-bisphosphonate inhibitor of farnesyl diphosphate synthase. Serendipitously, we also found that several predicted farnesyl diphosphate synthase inhibitors were low-micromolar inhibitors of undecaprenyl diphosphate synthase. These results are of interest because farnesyl diphosphate synthase inhibitors are being pursued as both anti-infective and anticancer agents, and undecaprenyl diphosphate synthase inhibitors are antibacterial drug leads
Evaluation of a novel virtual screening strategy using receptor decoy binding sites
Virtual screening is used in biomedical research to predict the binding affinity of a large set of small organic molecules to protein receptor targets. This report shows the development and evaluation of a novel yet straightforward attempt to improve this ranking in receptor-based molecular docking using a receptor-decoy strategy. This strategy includes defining a decoy binding site on the receptor and adjusting the ranking of the true binding-site virtual screen based on the decoy-site screen. The results show that by docking against a receptor-decoy site with Autodock Vina, improved Receiver Operator Characteristic Enrichment (ROCE) was achieved for 5 out of fifteen receptor targets investigated, when up to 15 % of a decoy site rank list was considered. No improved enrichment was seen for 7 targets, while for 3 targets the ROCE was reduced. The extent to which this strategy can effectively improve ligand prediction is dependent on the target receptor investigated
A Study of Archiving Strategies in Multi-Objective PSO for Molecular Docking
Molecular docking is a complex optimization problem aimed at predicting the position of a ligand molecule in the active site of a receptor with the lowest binding energy. This problem can be formulated as a bi-objective optimization problem by minimizing the binding energy and the Root Mean Square Deviation (RMSD) difference in the coordinates of ligands. In this context, the SMPSO multi-objective swarm-intelligence algorithm has shown a remarkable performance. SMPSO is characterized by having an external archive used to store the non-dominated solutions and also as the basis of the leader selection strategy. In this paper, we analyze several SMPSO variants based on different archiving strategies in the scope of a benchmark of molecular docking instances. Our study reveals that the SMPSOhv, which uses an hypervolume contribution based archive, shows the overall best performance.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech
Rational Design, Synthesis and Biological Evaluation of Pyrimidine-4,6-diamine derivatives as Type-II inhibitors of FLT3 Selective Against c-KIT.
FMS-like Tyrosine Kinase 3 (FLT3) is a clinically validated target for acute myeloid leukemia (AML). Inhibitors targeting FLT3 have been evaluated in clinical studies and have exhibited potential to treat FLT3-driven AML. A frequent, clinical limitation is FLT3 selectivity, as concomitant inhibition of FLT3 and c-KIT is thought to cause dose-limiting myelosuppression. Through a rational design approach, novel FLT3 inhibitors were synthesized employing a pyridine/pyrimidine warhead. The most potent compound identified from the studies is compound 13a, which exhibited an IC50 value of 13.9 ± 6.5 nM against the FLT3 kinase with high selectivity over c-KIT. Mechanism of action studies suggested that 13a is a Type-II kinase inhibitor, which was also supported through computer aided drug discovery (CADD) efforts. Cell-based assays identified that 13a was potent on a variety of FLT3-driven cell lines with clinical relevance. We report herein the discovery and therapeutic evaluation of 4,6-diamino pyrimidine-based Type-II FLT3 inhibitors, which can serve as a FLT3-selective scaffold for further clinical development
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