Crystal structure of the N-terminal domain of human Timeless and its interaction with Tipin

Human Timeless is involved in replication fork stabilization, S-phase checkpoint activation and establishment of sister chromatid cohesion. In the cell, Timeless forms a constitutive heterodimeric complex with Tipin. Here we present the 1.85 Å crystal structure of a large N-terminal segment of human Timeless, spanning amino acids 1-463, and we show that this region of human Timeless harbours a partial binding site for Tipin. Furthermore, we identify minimal regions of the two proteins that are required for the formation of a stable Timeless-Tipin complex and provide evidence that the Timeless-Tipin interaction is based on a composite binding interface comprising different domains of Timeless.Wellcome Trust Investigator Award [104641/Z/14/Z to L.P.]; Boehringer-Ingelheim Fonds PhD Fellowship; Janggen-Pöhn-Stiftung Awards; Swiss National Science Foundation (to S.H.). Funding for open access charge: Wellcome Trust

WISDOM-II: Screening against multiple targets implicated in malaria using computational grid infrastructures

<p>Abstract</p> <p>Background</p> <p>Despite continuous efforts of the international community to reduce the impact of malaria on developing countries, no significant progress has been made in the recent years and the discovery of new drugs is more than ever needed. Out of the many proteins involved in the metabolic activities of the <it>Plasmodium </it>parasite, some are promising targets to carry out rational drug discovery.</p> <p>Motivation</p> <p>Recent years have witnessed the emergence of grids, which are highly distributed computing infrastructures particularly well fitted for embarrassingly parallel computations like docking. In 2005, a first attempt at using grids for large-scale virtual screening focused on plasmepsins and ended up in the identification of previously unknown scaffolds, which were confirmed in vitro to be active plasmepsin inhibitors. Following this success, a second deployment took place in the fall of 2006 focussing on one well known target, dihydrofolate reductase (DHFR), and on a new promising one, glutathione-S-transferase.</p> <p>Methods</p> <p>In silico drug design, especially vHTS is a widely and well-accepted technology in lead identification and lead optimization. This approach, therefore builds, upon the progress made in computational chemistry to achieve more accurate <it>in silico </it>docking and in information technology to design and operate large scale grid infrastructures.</p> <p>Results</p> <p>On the computational side, a sustained infrastructure has been developed: docking at large scale, using different strategies in result analysis, storing of the results on the fly into MySQL databases and application of molecular dynamics refinement are MM-PBSA and MM-GBSA rescoring. The modeling results obtained are very promising. Based on the modeling results, <it>In vitro </it>results are underway for all the targets against which screening is performed.</p> <p>Conclusion</p> <p>The current paper describes the rational drug discovery activity at large scale, especially molecular docking using FlexX software on computational grids in finding hits against three different targets (PfGST, PfDHFR, PvDHFR (wild type and mutant forms) implicated in malaria. Grid-enabled virtual screening approach is proposed to produce focus compound libraries for other biological targets relevant to fight the infectious diseases of the developing world.</p

Is the astronomical forcing a reliable and unique pacemaker for climate? A conceptual model study

There is evidence that ice age cycles are paced by astronomical forcing, suggesting some kind of synchronisation phenomenon. Here, we identify the type of such synchronisation and explore systematically its uniqueness and robustness using a simple paleoclimate model akin to the van der Pol relaxation oscillator and dynamical system theory. As the insolation is quite a complex quasiperiodic signal involving different frequencies, the traditional concepts used to define synchronisation to periodic forcing are no longer applicable. Instead, we explore a different concept of generalised synchronisation in terms of (coexisting) synchronised solutions for the forced system, their basins of attraction and instabilities. We propose a clustering technique to compute the number of synchronised solutions, each of which corresponds to a different paleoclimate history. In this way, we uncover multistable synchronisation (reminiscent of phase- or frequency-locking to individual periodic components of astronomical forcing) at low forcing strength, and monostable or unique synchronisation at stronger forcing. In the multistable regime, different initial conditions may lead to different paleoclimate histories. To study their robustness, we analyse Lyapunov exponents that quantify the rate of convergence towards each synchronised solution (local stability), and basins of attraction that indicate critical levels of external perturbations (global stability). We find that even though synchronised solutions are stable on a long term, there exist short episodes of desynchronisation where nearby climate trajectories diverge temporarily (for about 50 kyr). (...)Comment: 22 pages, 18 figure

First Community-Wide, Comparative Cross-Linking Mass Spectrometry Study

The number of publications in the field of chemical cross-linking combined with mass spectrometry (XL-MS) to derive constraints for protein three-dimensional structure modeling and to probe protein-protein interactions has increased during the last years. As the technique is now becoming routine for in vitro and in vivo applications in proteomics and structural biology there is a pressing need to define protocols as well as data analysis and reporting formats. Such consensus formats should become accepted in the field and be shown to lead to reproducible results. This first, community-based harmonization study on XL-MS is based on the results of 32 groups participating worldwide. The aim of this paper is to summarize the status quo of XL-MS and to compare and evaluate existing cross-linking strategies. Our study therefore builds the framework for establishing best practice guidelines to conduct cross-linking experiments, perform data analysis, and define reporting formats with the ultimate goal of assisting scientists to generate accurate and reproducible XL-MS results

Improving enrichment and hit rates in virtual screening.

Although molecular docking is a widely used technique in drug discovery for the identification of hits or lead molecules, the method still retains important weaknesses and limitations. We focused our efforts on the development, validation and application of a new post-docking tool aimed at overcoming some of these limitations. The method, named BEAR (Binding Estimation After Refinement), is a new automated post-docking procedure based on the conformational refinement of docking poses through molecular dynamics (MD) followed by accurate predictions of protein binding free energies using MM-PBSA and MM-GBSA. BEAR is fast, modular and automated, and can be applied to virtual screenings against any biological target with known structure and any database of compounds, regardless of the docking method used for generating the initial pose

Improving enrichment and hit rates in virtual screening.

The method, named BEAR (Binding Estimation After Refinement), is a new automated post-docking procedure based on the conformational refinement of docking poses through molecular dynamics (MD) followed by accurate predictions of protein binding free energies using MM-PBSA and MM-GBSA. BEAR post-processing yielded strikingly better enrichment factors than those obtained with docking, and demonstrated to be a reliable tool for drug discovery. The BEAR scoring functions resulted reliable and able to recognize and to discriminate known ligands among compounds with unknown activity

BEAR, a novel virtual screening methodology based on molecular dynamics refinement and accurate binding free Energy estimation.

The method, named BEAR (Binding Estimation After Refinement), is a new automated post-docking procedure based on the conformational refinement of docking poses through molecular dynamics (MD) followed by accurate predictions of protein binding free energies using MM-PBSA and MM-GBSA. When applied to a huge virtual screening campaign aimed at identifying new Plasmodium falciparum plasmepsin inhibitors, BEAR discovered 26 novel and potent (nM) inhibitors out of the 30 compounds tested in the wet lab, thereby giving an impressive hit rate.5 Importantly, BEAR allowed the discovery of two entirely new classes of inhibitors. These evidences strongly confirmed the potential of our virtual screening procedure for drug discovery. BEAR post-processing yielded strikingly better enrichment factors than those obtained with docking, and demonstrated to be a reliable tool for drug discovery. The BEAR scoring functions resulted reliable and able to recognize and to discriminate known ligands among compounds with unknown activity

Improving enrichment and hit rates in virtual screening.

Although molecular docking is a widely used technique in drug discovery for the identification of hits or lead molecules, the method still retains important weaknesses and limitations. For example, docking techniques still lack reliable simulation of the flexibility of both ligands and receptor, and scoring functions may fail to estimate ligand binding energies in reasonable agreement with experiment. In light of these observations, we focused our efforts on the development, validation and application of a new post-docking tool aimed at overcoming some of these limitations. The method, named BEAR (Binding Estimation After Refinement), is a new automated post-docking procedure based on the conformational refinement of docking poses through molecular dynamics (MD) followed by accurate predictions of protein binding free energies using MM-PBSA and MM-GBSA

Binding estimation after refinement: BEARing out an innovative virtual screening methodology.

In the drug discovery process, accurate methods of computing the affinity of small molecules with a desired biological target are strongly needed. To this end, we developed Binding Estimation After Refinement (BEAR), a new and automated post-docking procedure for the conformational refinement of docking poses through molecular dynamics (MD) followed by accurate prediction of binding free energies using MM-PBSA and MM-GBSA. The BEAR performance in virtual screening was evaluated on several macromolecular targets and related sets of known ligands, determining the enrichment factors and assessing the correlation between predicted and experimental binding affinities. Moreover, when applied in virtual screening campaigns, BEAR was able to discover novel and potent inhibitors of Plasmodium falciparum plasmepsin II with an impressive hit rate, and has been successful in identifying promising scaffolds for the design of irreversible protein kinase inhibitors. The BEAR virtual screening procedure is reliable and strongly automated, and can be tailored to the needs of the end-user in terms of computational time and the desired accuracy of the results