Computational Biophysics Group
Computational Biophysics Group
Sahun-Roncero M.,University of Zaragoza |
Rubio-Ruiz B.,University of Granada |
Saladino G.,Computational Biophysics Group |
Saladino G.,University College London |
And 7 more authors.
Angewandte Chemie - International Edition | Year: 2013
Applying a CHOK hold: Combined experimental and computational studies of the binding mode of a rationally designed inhibitor of the dimeric choline kinase α1 (CHOKα1) explain the molecular mechanism of negative cooperativity (see scheme) and how the monomers are connected. The results give insight into how the symmetry of the dimer can be partially conserved despite a lack of conservation in the static crystal structures. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Herbert C.,Sanofi S.A. |
Schieborr U.,Goethe University Frankfurt |
Saxena K.,Goethe University Frankfurt |
Juraszek J.,Computational Biophysics Group |
And 24 more authors.
Cancer Cell | Year: 2013
The fibroblast growth factor (FGF)/fibroblast growth factor receptor (FGFR) signaling network plays an important role in cell growth, survival, differentiation, and angiogenesis. Deregulation of FGFR signaling can lead to cancer development. Here, we report an FGFR inhibitor, SSR128129E (SSR), that binds to the extracellular part of the receptor. SSR does not compete with FGF for binding to FGFR but inhibits FGF-induced signaling linked to FGFR internalization in an allosteric manner, as shown by crystallography studies, nuclear magnetic resonance, Fourier transform infrared spectroscopy, molecular dynamics simulations, free energy calculations, structure-activity relationship analysis, and FGFR mutagenesis. Overall, SSR is a small molecule allosteric inhibitor of FGF/FGFR signaling, acting via binding to the extracellular part of the FGFR. © 2013 Elsevier Inc.
Bono F.,Sanofi S.A. |
De Smet F.,Catholic University of Leuven |
De Smet F.,Vesalius Research Center |
Herbert C.,Sanofi S.A. |
And 66 more authors.
Cancer Cell | Year: 2013
Receptor tyrosine kinases (RTK) are targets for anticancer drug development. To date, only RTK inhibitors that block orthosteric binding of ligands and substrates have been developed. Here, we report the pharmacologic characterization of the chemical SSR128129E (SSR), which inhibits fibroblast growth factor receptor (FGFR) signaling by binding to the extracellular FGFR domain without affecting orthosteric FGF binding. SSR exhibits allosteric properties, including probe dependence, signaling bias, and ceiling effects. Inhibition by SSR is highly conserved throughout the animal kingdom. Oral delivery of SSR inhibits arthritis and tumors that are relatively refractory to anti-vascular endothelial growth factor receptor-2 antibodies. Thus, orally-active extracellularly acting small-molecule modulators of RTKs with allosteric properties can be developed and may offer opportunities to improve anticancer treatment. © 2013 Elsevier Inc.
Bonomi M.,ETH Zurich |
Barducci A.,ETH Zurich |
Gervasio F.L.,Computational Biophysics Group |
Parrinello M.,ETH Zurich
PLoS ONE | Year: 2010
Proteins fold on a time scale incompatible with a mechanism of random search in conformational space thus indicating that somehow they are guided to the native state through a funneled energetic landscape. At the same time the heterogeneous kinetics suggests the existence of several different folding routes. Here we propose a scenario for the folding mechanism of the monomer of HIV-1 protease in which multiple pathways and milestone events coexist. A variety of computational approaches supports this picture. These include very long all-atom molecular dynamics simulations in explicit solvent, an analysis of the network of clusters found in multiple high-temperature unfolding simulations and a complete characterization of free-energy surfaces carried out using a structure-based potential at atomistic resolution and a combination of metadynamics and parallel tempering. Our results confirm that the monomer in solution is stable toward unfolding and show that at least two unfolding pathways exist. In our scenario, the formation of a hydrophobic core is a milestone in the folding process which must occur along all the routes that lead this protein towards its native state. Furthermore, the ensemble of folding pathways proposed here substantiates a rational drug design strategy based on inhibiting the folding of HIV-1 protease. © 2010 Bonomi et al.
News Article | October 23, 2015
The predicted profile for the conformational dynamics of the tyrosine kinase family is shown. Regions highlighted in red correspond to important structural elements involved in protein activation. Credit: CNIO Researchers from the Structural Biology Computational Group of the Spanish National Cancer Research Centre (CNIO), led by Alfonso Valencia, in collaboration with a group headed by Francesco Gervasio at the University College London (UK), have developed the first computational method based on evolutionary principles to predict protein dynamics, which explains the changes in the shape or dimensional structure that they experience in order to interact with other compounds or speed up chemical reactions. The study constitutes a major step forward in the computational study of protein dynamics (i.e. their movement), which is crucial for the design of drugs and for the research on genetic diseases, such as cancer, resulting in higher levels of complexity than allowed by current methods. The results have been published this week in the journal Proceedings of the National Academy of Sciences (PNAS). Proteins are macromolecules that are key to the thousands of cellular functions that take place in a living organism. They are formed by chains of smaller molecules called amino acids that fold forming a three-dimensional structure. It has recently been discovered that by studying the co-evolution of amino acids we can reconstruct the form or structure of these biological compounds in their natural surroundings. "A protein's amino acids can co-evolve, i.e. change in a coordinated way," says Alfonso Valencia. "By analysing the sequences of a given family of proteins, we can predict physical contacts between amino acids with great precision, in sufficient number to reconstruct the folding of a protein accurately and, therefore, its structure or form." However, this structure does not remain static; it goes through changes in such a way that, similar to a dance in which each of the dancers adapts to their partner, it interacts with other biological compounds or with drugs. This is known as protein dynamics, the study of which has proven to be very difficult both with experimental observations and using computational tools. The question addressed by the researchers at the beginning of the study, when Francesco Gervasio headed the Computational Biophysics Group at the CNIO, was more complex: can we use co-evolutionary studies to predict changes in the shape of proteins and, consequently, the language they establish with their environment? "We developed a model in which the amino acids that have a strong co-evolutionary relationship attracted each other, without further additional data," says Simone Marsili, researcher who has also participated in the project. "First, we simulate the folding process and then we can see how the simulations were able to predict the changes in shape of the proteins at different levels of complexity, including those required for kinases to function [these are key proteins in metabolic and cell signalling processes as well as in cell transport, amongst others]." This new computational method easily integrates experimental and genomic data through the use of the latest sequence analysis and 3D modelling technology. In addition, it demonstrates that genomic data can be a source of useful information to supplement the current tools used to study the structure and dynamics of proteins. "The ability to predict key features of proteins at this level of complexity will help to understand how the sequence of a protein determines its dynamics and, therefore, its functions," concludes Valencia. This field of knowledge is key to the study of genetic diseases, such as cancer, or the design of drugs, amongst other uses. More information: Ludovico Sutto et al. From residue coevolution to protein conformational ensembles and functional dynamics, Proceedings of the National Academy of Sciences (2015). DOI: 10.1073/pnas.1508584112
De Vivo M.,Italian Institute of Technology |
Bottegoni G.,Italian Institute of Technology |
Berteotti A.,Italian Institute of Technology |
Recanatini M.,University of Bologna |
And 3 more authors.
Future Medicinal Chemistry | Year: 2011
Cyclin-dependent kinases (CDKs) are one of the most promising target families for drug discovery for several diseases, such as cancer and neurodegenerative disorders. Over the years, structural insights on CDKs have demonstrated high protein plasticity, with several cases where two or more structures of the same protein adopt different conformations. This has generated a great deal of interest in understanding the relationship between CDK structure and function. Here, we highlight how computer simulations have recently contributed in characterizing some key rare and transient events in CDKs, such as the reaction transition state and activation loop movement. Although not yet fully defined, we can now portray the enzymatic mechanism and plasticity of CDKs at high spatial and temporal resolution. These theoretical studies bridge with experiments and highlight structural determinants that could help in designing specific CDK inhibitors. © 2011 Future Science Ltd.
D'Abramo M.,University of Barcelona |
D'Abramo M.,Computational Biophysics Group |
Orozco M.,University of Barcelona |
Amadei A.,University of Rome Tor Vergata
Chemical Communications | Year: 2011
Influence of external electric field as well as base substitution effects on the reduction/oxidation free energies of single stranded DNA suggest that base sequencing via measuring redox properties might be feasible under the conditions that (i) a difference of ∼ 230 kJ mol-1 in the oxidation potentials is enough to discriminate between nucleobases conductance signals and (ii) the strand is long enough to reduce end effects. © 2011 The Royal Society of Chemistry.
Zenn R.K.,University of Stuttgart |
Abad E.,University of Stuttgart |
Abad E.,Computational Biophysics Group |
Kastner J.,University of Stuttgart
Journal of Physical Chemistry B | Year: 2015
The flavin-containing enzyme monoamine oxidase (MAO) is essential for the enzymatic decomposition of amine neurotransmitters. The exact mechanism of the oxidative deamination of amines to aldehydes by the enzyme has not yet been fully understood despite extensive research on the area. The rate limiting step is the reductive half-reaction where the Hα together with two electrons of the amine substrate is transferred to the flavin cofactor. However, it is still not known whether the hydrogen is transferred as a proton or a hydride. Experimental results cannot be fully explained by either of those mechanisms. In our previous work, theoretical results based on QM/MM calculations of the full enzyme show an intermediate situation between these two cases. In this paper, we report on an in-depth computational analysis concerning the role of the enzymatic environment for the reaction mechanism of human MAO-B with different p-substituted benzylamines as substrates. Our results show that steric and electrostatic effects from the active site environment turn the mechanism closer to an asynchronous polar nucleophilic mechanism. We found indications that the protein environment of MAO-A enhances the polar nucleophilic character of the mechanism compared to that of MAO-B. © 2015 American Chemical Society.
Fidelak J.,Sanofi S.A. |
Juraszek J.,Computational Biophysics Group |
Branduardi D.,Italian Institute of Technology |
Bianciotto M.,Sanofi S.A. |
Gervasio F.L.,Computational Biophysics Group
Journal of Physical Chemistry B | Year: 2010
Free-energy pathway methods show great promise in computing the mode of action and the free energy profile associated with the binding of small molecules with proteins, but are generally very computationally demanding. Here we apply a novel approach based on metadynamics and path collective variables. We show that this combination is able to find an optimal reaction coordinate and the free energy profile of binding with explicit solvent and full flexibility, while minimizing human intervention and computational costs. We apply it to predict the binding affinity of a congeneric series of 5 CDK2 inhibitors. The predicted binding free energy profiles are in accordance with experiment. © 2010 American Chemical Society.
Kappel C.,Theoretical and Computational Biophysics |
Dolker N.,Theoretical and Computational Biophysics |
Dolker N.,Computational Biophysics Group |
Kumar R.,Theoretical and Computational Biophysics |
And 5 more authors.
Physical Review Letters | Year: 2012
Experimental and computational dynamic force spectroscopy is widely used to determine the mechanical properties of single biomolecules. Whereas so far the focus has mainly been on rupture or unfolding forces, recent force-probe molecular dynamics simulations have revealed a strong loading rate dependence of biomolecular elasticities, which cannot be explained by the established one-dimensional transition-state treatments. We show that this nonequilibrium behavior can be explained by a theory that includes relaxation effects. For three structurally and mechanically quite diverse systems, a single relaxation mode suffices to quantitatively describe their loading-rate-dependent elastic behavior. Atomistic simulations of these systems revealed the microscopic nature of the respective relaxation modes. This result suggests a new type of "elasticity spectroscopy" experiment, which should render nonequilibrium properties of structured macromolecules accessible to single-molecule force spectroscopy. © 2012 American Physical Society.