1,720,997 research outputs found
Protein–Ligand Docking: Virtual Screening and Applications to Drug Discovery
No full text---The term virtual screening (VS) was rst reported in literature in 1997 (Horvath 1997), and refers to computational techniques aimed at streamlining the drug discovery process through in silico identication of novel hits from large chemical libraries. In the early 1990s, the drug discovery paradigm was overturned by the introduction of high-throughput screening (HTS) (Bleicher et al. 2003) and combinatorial chemistry (Geysen et al. 2003). These techniques promised to accelerate the drug discovery process by enabling the synthesis of large libraries of chemical compounds and the assay of their biological activity against several targets in a short period of time. However, the revolutionary approach soon proved to be expensive and not productive as expected, as many of the identied hits failed the lead optimization stage due to unsuitable pharmacokinetic properties. The development of alternative strategies to select appropriate compounds, while removing unsuitable structures, aimed at si..
Breakthrough in GPCR Crystallography and Its Impact on Computer-Aided Drug Design
No full textRecent crystallographic structures of G protein-coupled receptors (GPCRs) have greatly advanced our understanding of the recognition of their diverse agonist and antagonist ligands. We illustrate here how this applies to A2A adenosine receptors (ARs) and to P2Y1 and P2Y12 receptors (P2YRs) for ADP. These X-ray structures have impacted the medicinal chemistry aimed at discovering new ligands for these two receptor families, including receptors that have not yet been crystallized but are closely related to the known structures. In this Chapter, we discuss recent structure-based drug design projects that led to the discovery of: (a) novel A3AR agonists based on a highly rigidified (N)-methanocarba scaffold for the treatment of chronic neuropathic pain and other conditions, (b) fluorescent probes of the ARs and P2Y14R, as chemical tools for structural probing of these GPCRs and for improving assay capabilities, and (c) new more drug-like antagonists of the inflammation-related P2Y14R. We also describe the computationally enabled molecular recognition of positive (for A3AR) and negative (P2Y1R) allosteric modulators that in some cases are shown to be consistent with structure-activity relationship (SAR) data. Thus, computational modeling has become an essential tool for the design of purine receptor ligands
Exploring the recognition pathway at the human A2A adenosine receptor of the endogenous agonist adenosine using supervised molecular dynamics simulations
No full textAdenosine is a naturally occurring purine nucleoside that exerts a variety of important biological functions through the activation of four G protein-coupled receptor (GPCR) isoforms, namely the A1, A2A, A2B and A3 adenosine receptors (ARs). Recently, the X-ray structure of adenosine-bound hA2A AR has been solved, thus providing precious structural details on receptor recognition and activation mechanisms. To date, however, little is still known about the possible recognition pathway the endogenous agonist might go through while approaching the hA2A AR from the extracellular environment. In the present work, we report the adenosine-hA2A AR recognition pathway through the analysis of a series of Supervised Molecular Dynamics (SuMD) trajectories. Interestingly, a possible energetically stable meta-binding site has been detected and characterized
A3 adenosine receptor activation mechanisms: molecular dynamics analysis of inactive, active, and fully active states
No full textWe investigated the Gi-coupled A3 adenosine receptor (A3AR) activation mechanism by running 7.2 μs of molecular dynamics (MD) simulations. Based on homology to G protein-coupled receptor (GPCR) structures, three constitutively active mutant (CAM) and the wild-type (WT) A3ARs in the apo form were modeled. Conformational signatures associated with three different receptor states (inactive R, active R*, and bound to Gi protein mimic) were predicted by analyzing and comparing the CAMs with WT receptor and by considering site-directed mutagenesis data. Detected signatures that were correlated with receptor state included: Persistent salt-bridges involving key charged residues for activation (including a novel, putative ionic lock), rotameric state of conserved W6.48, and Na+ ions and water molecules present. Active-coupled state signatures similar to the X-ray structures of β2 adrenergic receptor-Gs protein and A2AAR-mini-Gs and the recently solved cryo-EM A1AR–Gi complexes were found. Our MD analysis suggests that constitutive activation might arise from the D1073.49–R1083.50 ionic lock destabilization in R and the D1073.49–R1113.53 ionic lock stabilization in R* that presumably lowers the energy barrier associated with an R to R* transition. This study provides new opportunities to understand the underlying interactions of different receptor states of other Gi protein-coupled GPCRs
Structural Probing and Molecular Modeling of the A3 Adenosine Receptor: A Focus on Agonist Binding
No full textAdenosine is an endogenous modulator exerting its functions through the activation of four adenosine receptor (AR) subtypes, termed A1, A2A, A2B and A3, which belong to the G protein-coupled receptor (GPCR) superfamily. The human A3AR (hA3AR) subtype is implicated in several cytoprotective functions. Therefore, hA3AR modulators, and in particular agonists, are sought for their potential application as anti-inflammatory, anticancer, and cardioprotective agents. Structure-based molecular modeling techniques have been applied over the years to rationalize the structure–activity relationships (SARs) of newly emerged A3AR ligands, guide the subsequent lead optimization, and interpret site-directed mutagenesis (SDM) data from a molecular perspective. In this review, we showcase selected modeling-based and guided strategies that were applied to elucidate the binding of agonists to the A3AR and discuss the challenges associated with an accurate prediction of the receptor extracellular vestibule through homology modeling from the available X-ray templates
Inspecting receptor-ligand interaction using molecular dynamics simulations: new insights from Adenosiland
No full textOne of the most challenging issues for the future of drug discovery is the capability to understand the GPCR–ligand recognition pathway with the aim to facilitate the development of drug candidates with more favorable phamacodynamic profiles.
Unfortunately, the recognition process between a ligand and its receptor is a very rare event to describe at the molecular level, and even with the recent GPU-based computing resources, it is necessary to carry out classical molecular dynamics (MD) experiments in a long microsecond time scale. In order to overcome this limiting factor, we have implemented an alternative MD approach, named supervised molecular dynamics (SuMD), that enables us to follow GPCR–ligand approaching process within a time scale reduced up to three orders of magnitude compared to classical MD [1]. SuMD enables the investigation of ligand–receptor binding events independently from the starting position, chemical structure of the ligand, and also from its receptor binding affinity (Fig. 1).
We selected as a key study the human A2A adenosine receptor (hA2AAR) that has been recently crystallized with different ligands, both agonists and antagonists, characterized by different receptor binding affinities. We are able to accurately completely explore the receptor–ligand event in a nanosecond time scale. This approach is also very useful to analyze both orthosteric and allosteric binding events broadening our perspectives in several scientific areas from molecular pharmacology to drug discovery
Advances in Computational Techniques to Study GPCR-Ligand Recognition
No full textG-protein-coupled receptors (GPCRs) are among the most intensely investigated drug targets. The recent revolutions in protein engineering and molecular modeling algorithms have overturned the research paradigm in the GPCR field. While the numerous ligand-bound X-ray structures determined have provided invaluable insights into GPCR structure and function, the development of algorithms exploiting graphics processing units (GPUs) has made the simulation of GPCRs in explicit lipid-water environments feasible within reasonable computation times. In this review we present a survey of the recent advances in structure-based drug design approaches with a particular emphasis on the elucidation of the ligand recognition process in class A GPCRs by means of membrane molecular dynamics (MD) simulations
Activation of carboplatin by carbonate: A theoretical investigation
No full textWe carried out a theoretical study to investigate the thermodynamics and the kinetics of the activation of the anticancer drug carboplatin in a carbonate buffer, a process which has been suggested to play an important role in the uptake, antitumor activity and toxicity of this drug. The initial stages of this process have been investigated by considering both the carbonate and the bicarbonate ions, the main species in a carbonate buffer at physiological pH, as the attacking species and consist of an initial ring-opening step, involving the displacement of one arm of the chelating ring by the carbonate ion, followed by the protonation of the ring-opened carbonate to the corresponding bicarbonate species and its subsequent decarboxylation to give the final hydroxo product. The obtained results show that the overall process is exoergonic with relatively low activation free energy (below 120 kJ mol(-1)), suggesting that the reaction with carbonate might represent a viable pathway for the activation of carboplatin to give active intermediates which, in the biological environment, may easily further react to give thermodynamically more stable species
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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