1,721,004 research outputs found
Enzymatic and Inhibition Mechanism of Human Aromatase (CYP19A1) Enzyme. A Computational Perspective from QM/MM and Classical Molecular Dynamics Simulations
No full textThe enzyme human aromatase (HA), a member of the cytochrome P450 family, catalyses in a highly specific and peculiar manner the conversion of estrogens to androgens. Thus, this enzyme is a relevant target for inhibitor design for the treatment of breast cancer and currently there are several HA inhibitors employed in clinical practice. The HA crystal structure was solved only in 2009 and, since then, several studies have been done to characterize a variety of its structural, dynamical and mechanistic properties. In the last decade, the predictive power and the accuracy of computer simulations techniques, either relying on force field or on "ab initio" description of the system, has enormously increased. This was mainly due to the development of more accurate algorithms, which allow accelerating the time-scale accessible by simulations techniques, and to the increase of computer power. Hence, computer simulations can now accurately paint an atomistic picture to the molecular mechanism of biomolecules providing also an estimate of the kinetic and thermodynamic properties of the enzyme at increasingly quantitative level. In this review, on the basis of selected examples taken from our work, we summarize current active research topics concerning HA enzyme, with a focus on computational studies. In particular, we will illustrate current results and novel hypothesis concerning the final (rate-determining) aromatization step promoted by this enzyme, on how the structural/dynamics/functional properties of HA are modulated in a membrane lipophilic environment, and finally on novel possible (allosteric) inhibition mechanisms which may modulate estrogen production in HA
Sodium-Galactose Transporter: The First Steps of the Transport Mechanism Investigated by Molecular Dynamics
No full textHow phosphorylation influences E1 subunit pyruvate dehydrogenase: A computational study
Full text linkPyruvate (PYR) dehydrogenase complex (PDC) is an enzymatic system that plays a crucial role in cellular metabolism as it controls the entry of carbon into the Krebs cycle. From a structural point of view, PDC is formed by three different subunits (E1, E2 and E3) capable of catalyzing the three reaction steps necessary for the full conversion of pyruvate to acetyl-CoA. Recent investigations pointed out the crucial role of this enzyme in the replication and survival of specific cancer cell lines, renewing the interest of the scientific community. Here, we report the results of our molecular dynamics studies on the mechanism by which posttranslational modifications, in particular the phosphorylation of three serine residues (Ser-264-alpha, Ser-271-alpha, and Ser-203-alpha), influence the enzymatic function of the protein. Our results support the hypothesis that the phosphorylation of Ser-264-alpha and Ser-271-alpha leads to (1) a perturbation of the catalytic site structure and dynamics and, especially in the case of Ser-264-alpha, to (2) a reduction in the affinity of E1 for the substrate. Additionally, an analysis of the channels connecting the external environment with the catalytic site indicates that the inhibitory effect should not be due to the occlusion of the access/egress pathways to/from the active site
Covalent docking of selected boron-based serine beta-lactamase inhibitors
No full textAmpC β-lactamase is a hydrolytic enzyme conferring resistance to β-lactam antibiotics in multiple Gram-negative bacteria. Therefore, identification of non-β-lactam compounds able to inhibit the enzyme is crucial for the development of novel antibacterial therapies. In general, AmpC inhibitors have to engage the highly solvent-exposed catalytic site of the enzyme. Therefore, understanding the implications of ligand–protein induced-fit and water-mediated interactions behind the inhibitor-enzyme recognition process is fundamental for undertaking structure-based drug design process. Here, we focus on boronic acids, a promising class of beta-lactamase covalent inhibitors. First, we optimized a docking protocol able to reproduce the experimentally determined binding mode of AmpC inhibitors bearing a boronic group. This goal was pursued (1) performing rigid and flexible docking calculations aiming to establish the role of the side chain conformations; and (2) investigating the role of specific water molecules in shaping the enzyme active site and mediating ligand protein interactions. Our calculations showed that some water molecules, conserved in the majority of the considered X-ray structures, are needed to correctly predict the binding pose of known covalent AmpC inhibitors. On this basis, we formalized our findings in a docking and scoring protocol that could be useful for the structure-based design of new boronic acid AmpC inhibitors
How Computational Chemistry and Drug Delivery Techniques Can Support the Development of New Anticancer Drugs
Full text linkThe early and late development of new anticancer drugs, small molecules or peptides can be slowed down by some issues such as poor selectivity for the target or poor ADME properties. Computer-aided drug design (CADD) and target drug delivery (TDD) techniques, although apparently far from each other, are two research fields that can give a significant contribution to overcome these problems. Their combination may provide mechanistic understanding resulting in a synergy that makes possible the rational design of novel anticancer based therapies. Herein, we aim to discuss selected applications, some also from our research experience, in the fields of anticancer small organic drugs and peptides
Computational Approaches Elucidate the Allosteric Mechanism of Human Aromatase Inhibition: A Novel Possible Route to Small-Molecule Regulation of CYP450s Activities?
No full textHuman aromatase (HA) is a P450 cytochrome (CYP) with an essential role in estrogen biosynthesis. Since more than 70% of breast cancers are positive for estrogenic receptor (ER), the reduction of estrogen physiological concentrations through HA inhibition is one of most important therapeutic strategies against this cancer type. Recently, experimental evidence showed that selected taxmoxifen metabolites, which are typically used as estrogen receptor modulators (SERMs), inhibit HA through an allosteric mechanism. In this work, we present a computational protocol to (i) characterize the structural framework and (ii) define the atomistic details of the determinants for the noncompetitive inhibition mechanism. Our calculations identify two putative binding sites able to efficiently bind all tamoxifen metabolites. Analysis of long-scale molecular dynamics simulations reveal that endoxifen, the most effective noncompetitive inhibitor, induces significant enzyme rigidity by binding in one of the possible peripheral sites. The consequence of this binding event is the suppression of one of the functional enzymatic collective motions associated with breathing of the substrate access channel. Moreover, an internal dynamics-based alignment of HA with six other human cytochromes shows that this collective motion is common to other members of the CYP450 protein family. On this basis, our findings may thus be of help for the development of new (pan)inhibitors for the therapeutic treatment of cancer, targeting and modulating the activity of HA and of estrogen receptor, and may also stimulate the development of new drug design strategies for chemoprevention and chemoprotection via allosteric inhibition of CYP450 protein
Inactivation of TEM-1 by avibactam (NXL-104): Insights from quantum mechanics/molecular mechanics metadynamics simulations
No full textThe fast and constant development of drug-resistant bacteria represents a serious medical emergence. To overcome this problem, the development of drugs with new structures and modes of action is urgently needed. In this context, avibactam represents a promising, innovative inhibitor of beta-lactamases with a novel molecular structure compared to previously developed inhibitors, showing a promising inhibitory activity toward a significant number of beta-lactamase enzymes. In this work, we studied, at the atomistic level, the mechanisms of formation of the covalent complex between avibactam and TEM-1, an experimentally well-characterized class A beta-lactamase, using classical and quantum mechanics/molecular mechanics (QM/MM) simulations combined with metadynamics. Our simulations provide a detailed structural and energetic picture of the molecular steps leading to the formation of the avibactam/TEM-1 covalent adduct. In particular, they support a mechanism in which the rate-determining step is the water-assisted Glu166 deprotonation by Ser70. In this mechanistic framework, the predicted activation energy is in good agreement with experimental kinetic measurements. Additionally, our simulations highlight the important role of Lys73 in assisting the Ser70 and Ser130 deprotonations. While based on the specific case of the avibactam/TEM-1, the simple protocol we present here can be immediately extended and applied to the study of covalent complex formation in different enzyme-inhibitor pairs. © 2014 American Chemical Society
Strumenti della modellistica molecolare applicati allostudio e ottimizzazione strutturale di composti diinteresse farmaceutico
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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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