A nontoxic pain killer designed by modeling of pathological receptor conformations

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Canonical sampling through velocity-rescaling

Giovanni Bussi, Michele Parrinello, Davide Donadio (2008)

We present a new molecular dynamics algorithm for sampling the canonical distribution. In this approach the velocities of all the particles are rescaled by a properly chosen random factor. The algorithm is formally justified and it is shown that, in spite of its stochastic nature, a quantity can still be defined that remains constant during the evolution. In numerical applications this quantity can be used to measure the accuracy of the sampling. We illustrate the properties of this new method on Lennard-Jones and TIP4P water models in the solid and liquid phases. Its performance is excellent and largely independent on the thermostat parameter also with regard to the dynamic properties.

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Crystal structure of the μ-opioid receptor bound to a morphinan antagonist

Aashish Manglik, Andrew C. Kruse, Tong Kobilka … (2012)

Summary Opium is one of the world’s oldest drugs, and its derivatives morphine and codeine are among the most used clinical drugs to relieve severe pain. These prototypical opioids produce analgesia as well as many of their undesirable side effects (sedation, apnea and dependence) by binding to and activating the G-protein-coupled μ-opioid receptor (μOR) in the central nervous system. Here we describe the 2.8 Å crystal structure of the μOR in complex with an irreversible morphinan antagonist. Compared to the buried binding pocket observed in most GPCRs published to date, the morphinan ligand binds deeply within a large solvent-exposed pocket. Of particular interest, the μOR crystallizes as a two-fold symmetric dimer through a four-helix bundle motif formed by transmembrane segments 5 and 6. These high-resolution insights into opioid receptor structure will enable the application of structure-based approaches to develop better drugs for the management of pain and addiction.

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Anti-inflammatory therapy in chronic disease: challenges and opportunities.

Ira Tabas, Christopher K. Glass (2013)

A number of widespread and devastating chronic diseases, including atherosclerosis, type 2 diabetes, and Alzheimer's disease, have a pathophysiologically important inflammatory component. In these diseases, the precise identity of the inflammatory stimulus is often unknown and, if known, is difficult to remove. Thus, there is interest in therapeutically targeting the inflammatory response. Although there has been success with anti-inflammatory therapy in chronic diseases triggered by primary inflammation dysregulation or autoimmunity, there are considerable limitations. In particular, the inflammatory response is critical for survival. As a result, redundancy, compensatory pathways, and necessity narrow the risk:benefit ratio of anti-inflammatory drugs. However, new advances in understanding inflammatory signaling and its links to resolution pathways, together with new drug development, offer promise in this area of translational biomedical research.