A new protocol to improve the predictive power of molecular docking

Quantitative understanding of molecular recognition is key for basic research and computer-aided drug design projects. Docking mimics ligand-receptor association in silico, providing an atomic-level model structure of their complex. Unfortunately most docking algorithms underestimate receptor flexibility, reducing the rate of success when binding induces large structural changes of partners. Ensembledocking, where a set of receptor structures (e.g. from MD simulations) is considered, was implemented to overcome this limitation. Clearly, ensemble structures should include conformations prone to host ligands (holo form), which is usually not the case when apo and holo forms are separated by high free energy barriers. To improve generation of holo-like receptor conformations starting only from its apo form, we implemented a computational protocol based on enhancedsampling MD simulations. We validated our method on proteins whose apo and holo structures were available and previous efforts to generate holo-like structures and native-like docking poses failed. Receptor structures obtained with our method were comparable to those extracted from MD trajectories of the complex. Furthermore, the docking poses generated by using these structures were native-like and topranked in score

Elucidating efflux inhibition and avoidance in Pseudomonas aeruginosa

Antibiotic resistance is a major threat to public health. Gramnegative pathogens, such as Pseudomonas aeruginosa, are of particular concern. One of the first bacterial defence mechanisms is the active export of drugs out of the cell, mainly mediated by resistance-nodulation-division (RND) efflux pumps. The major RND efflux pump of P. aeruginosa is MexAB-OprM, in which the inner membrane transporter MexB is responsible for the recognition and binding of compounds. Due to the difficulty of producing co-crystals,computational methods are crucial to gaining insights into the interactions between compounds and MexB. We exploited multi-copy molecular dynamics simulations to investigate the binding of peptidomimetics compounds to MexB. Based on microbiology studies, this series was shown to include efflux substrates, inhibitors, and avoiders. The detailed analysis of protein-ligand interactions (both direct and water-mediated) revealed characteristic patterns for each class of compounds, highlighting significant differences. Our results outline molecular-level information that could help the rational design of new inhibitors and new antibiotics less susceptible to the efflux mechanism

A new protocol to improve the predictive power of molecular docking

Quantitative understanding of molecular recognition is key for basic research and computer-aided drug design projects. Docking mimics ligand-receptor association in silico, providing an atomic-level model structure of their complex. Unfortunately most docking algorithms underestimate receptor flexibility, reducing the rate of success when binding induces large structural changes of partners. Ensembledocking, where a set of receptor structures (e.g. from MD simulations) is considered, was implemented to overcome this limitation. Clearly, ensemble structures should include conformations prone to host ligands (holo form), which is usually not the case when apo and holo forms are separated by high free energy barriers. To improve generation of holo-like receptor conformations starting only from its apo form, we implemented a computational protocol based on enhancedsampling MD simulations. We validated our method on proteins whose apo and holo structures were available and previous efforts to generate holo-like structures and native-like docking poses failed. Receptor structures obtained with our method were comparable to those extracted from MD trajectories of the complex. Furthermore, the docking poses generated by using these structures were native-like and topranked in score

Multi-messenger Observations of a Binary Neutron Star Merger

International audienceOn 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of $\sim 1.7\,{\rm{s}}$ with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg(2) at a luminosity distance of ${40}_{-8}^{+8}$ Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 $\,{M}_{\odot }$. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at $\sim 40\,{\rm{Mpc}}$) less than 11 hours after the merger by the One-Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ∼10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position $\sim 9$ and $\sim 16$ days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC 4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta