1,720,971 research outputs found
Novel in silico approaches to depict the protein-ligand recognition events
Full text linkThe discovery and commercialization of a new drug is a long and expensive process. Such process is divided into different phases during which the phisico-chemical and therapeutic properties of the compounds are determined. In particular, the aim of the first phase is to verify whether the compound recognises and interacts efficiently with the target protein.
In the last decade, several computational tools have been developed and used to support experimentalists. For this purpose, the scientist have to deal with high complex systems that are difficult to study in whole; thus, the methods and algorithms developers have to strongly simplify the system treatment. Moreover, the time required to obtain the results depends on the computational resources (hardware) available. Fortunately, the technological progress have increased the computing power at low cost, resulting in new and more complex techniques development.
During this Ph.D. project we were focused on the development and even the improvement of in silico methods, which allowed to answer certain questions by saving time and money. Furthermore, these methods were implemented in software presenting a Graphical Unit Interface (GUI) with the aim to enhance the user-friendliness.
The computational techniques often require a high understanding of the methodology theoretical aspects and also a good informatics proficiency, like different type files handling and hardware management. For this reason, our developed software were organized as pipelines to automatize the entire process and to make this tools useful also for non-expert users.
Finally, these methodologies were applied in several research projects demonstrating their usefulness by elucidating, for the first time, interesting aspects of the ligand-protein recognition pathway
Synthesis and preliminary structure-activity relationship study of 2-aryl-2H-pyrazolo[4,3-c]quinolin-3-ones as potential checkpoint kinase 1 (Chk1) inhibitors
Full text linkThe serine-threonine checkpoint kinase 1 (Chk1) plays a critical role in the cell cycle arrest in response to DNA damage. In the last decade, Chk1 inhibitors have emerged as a novel therapeutic strategy to potentiate the anti-tumour efficacy of cytotoxic chemotherapeutic agents. In the search for new Chk1 inhibitors, a congeneric series of 2-aryl-2 H-pyrazolo[4,3-c]quinolin-3-one (PQ) was evaluated by in-vitro and in-silico approaches for the first time. A total of 30 PQ structures were synthesised in good to excellent yields using conventional or microwave heating, highlighting that 14 of them are new chemical entities. Noteworthy, in this preliminary study two compounds 4e 2 and 4h 2 have shown a modest but significant reduction in the basal activity of the Chk1 kinase. Starting from these preliminary results, we have designed the second generation of analogous in this class and further studies are in progress in our laboratories.Fil: Malvacio, Ivana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; ArgentinaFil: Cuzzolin, Alberto. Università di Padova; ItaliaFil: Sturlese, Mattia. Università di Padova; ItaliaFil: Vera, Domingo Mariano Adolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones en Biodiversidad y Biotecnología; ArgentinaFil: Moyano, Elizabeth Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; ArgentinaFil: Moro, Stefano. Università di Padova; Itali
Exploring Protein-Peptide Recognition Pathways Using a Supervised Molecular Dynamics Approach
No full textPeptides have gained increased interest as therapeutic agents during recent years. The high specificity and relatively low toxicity of peptide drugs derive from their extremely tight binding to their targets. Indeed, understanding the molecular mechanism of protein-peptide recognition has important implications in the fields of biology, medicine, and pharmaceutical sciences. Even if crystallography and nuclear magnetic resonance are offering valuable atomic insights into the assembling of the protein-peptide complexes, the mechanism of their recognition and binding events remains largely unclear. In this work we report, for the first time, the use of a supervised molecular dynamics approach to explore the possible protein-peptide binding pathways within a timescale reduced up to three orders of magnitude compared with classical molecular dynamics. The better and faster understating of the protein-peptide recognition pathways could be very beneficial in enlarging the applicability of peptide-based drug design approaches in several biotechnological and pharmaceutical fields
Combining self- and cross-docking as benchmark tools: the performance of DockBench in the D3R Grand Challenge 2
No full textAbstract
Molecular docking is a powerful tool in the field of computer-aided molecular design. In particular, it is the technique of choice for the prediction of a ligand pose within its target binding site. A multitude of docking methods is available nowadays, whose performance may vary depending on the data set. Therefore, some non-trivial choices should be made before starting a docking simulation. In the same framework, the selection of the target structure to use could be challenging, since the number of available experimental structures is increasing. Both issues have been explored within this work. The pose prediction of a pool of 36 compounds provided by D3R Grand Challenge 2 organizers was preceded by a pipeline to choose the best protein/docking-method couple for each blind ligand. An integrated benchmark approach including ligand shape comparison and cross-docking evaluations was implemented inside our DockBench software. The results are encouraging and show that bringing attention to the choice of the docking simulation fundamental components improves the results of the binding mode predictions
AquaMMapS: an alternative tool to monitor the role of water molecules during protein-ligand association
No full textUnquestionably water appears to be an active player in noncovalent protein-ligand association processes, as it can either bridge interactions between protein and ligand or can be replaced by the bound ligand. Accordingly, in the last decade, alternative computational methodologies have been sought, that guess the position and thermodynamic profile of water molecules (i.e., hydration sites) in the binding site using either the ligand-bound or ligand-free protein conformation. Herein, we present an alternative approach, named AquaMMapS, that provides a three-dimensional sampling of putative hydration sites. Interestingly, AquaMMapS can post-inspect molecular dynamics trajectories obtained from different molecular dynamics engines and using indifferently crystallographic or docking-driven structures as a starting point. Moreover, AquaMMapS is naturally integrated to supervised molecular dynamics (SuMD) simulations Finally, a penalty scoring method, named AquaMMapScoring,(AMS), has been developed to evaluate, during the binding event, the number and the nature of the water molecules displaced by a ligand approaching its binding site, guiding a medicinal chemist to explore the most suitable regions of a ligand that can be decorated either with or without interfering with the interaction networks mediated by water molecules with specific recognition regions of the protein
Can We Still Trust Docking Results? An Extension of the Applicability of DockBench on PDBbind Database
Full text linkThe number of entries in the Protein Data Bank (PDB) has doubled in the last decade, and it has increased tenfold in the last twenty years. The availability of an ever-growing number of structures is having a huge impact on the Structure-Based Drug Discovery (SBDD), allowing investigation of new targets and giving the possibility to have multiple structures of the same macromolecule in a complex with different ligands. Such a large resource often implies the choice of the most suitable complex for molecular docking calculation, and this task is complicated by the plethora of possible posing and scoring function algorithms available, which may influence the quality of the outcomes. Here, we report a large benchmark performed on the PDBbind database containing more than four thousand entries and seventeen popular docking protocols. We found that, even in protein families wherein docking protocols generally showed acceptable results, certain ligand-protein complexes are poorly reproduced in the self-docking procedure. Such a trend in certain protein families is more pronounced, and this underlines the importance in identification of a suitable protein�ligand conformation coupled to a well-performing docking protocol
Understanding allosteric interactions in G protein-coupled receptors using Supervised Molecular Dynamics: A prototype study analysing the human A3 adenosine receptor positive allosteric modulator LUF6000
No full textThe search for G protein-coupled receptors (GPCRs) allosteric modulators represents an active research field in medicinal chemistry. Allosteric modulators usually exert their activity only in the presence of the orthosteric ligand by binding to protein sites topographically different from the orthosteric cleft. They therefore offer potentially therapeutic advantages by selectively influencing tissue responses only when the endogenous agonist is present. The prediction of putative allosteric site location, however, is a challenging task. In facts, they are usually located in regions showing more structural variation among the family members. In the present work, we applied the recently developed Supervised Molecular Dynamics (SuMD) methodology to interpret at the molecular level the positive allosteric modulation mediated by LUF6000 toward the human adenosine A3 receptor (hA3 AR). Our data suggest at least two possible mechanisms to explain the experimental data available. This study represent, to the best of our knowledge, the first case reported of an allosteric recognition mechanism depicted by means of molecular dynamics simulations
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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