Diffractive Dijet Production at s = 630 and 1800 GeV at the Fermilab Tevatron

We report a measurement of the diffractive structure function F-jj(D) of the antiproton obtained from a study of dijet events produced in association with a leading antiproton in (p) over barp collisions at roots = 630 GeV at the Fermilab Tevatron. The ratio of F-jj(D) at roots = 630 GeV to F-jj(D) obtained from a similar measurement at roots = 1800 GeV is compared with expectations from QCD factorization and other theoretical predictions. We also report a measurement of the xi (x-Pomeron) and beta (x of parton in Pomeron) dependence of F-jj(D) at roots = 1800 GeV . In the region 0.035 < &xi; < 0.095 , \t\ < 1 GeV2 , and &beta; < 0.5 , F-jj(D)(beta, xi) is found to be of the form beta(-1.0+/-0.1) xi(-0.9+/-0. 1) , which obeys beta-xi factorization

Measurement of the average time-integrated mixing probability of b-flavored hadrons produced at the Fermilab Tevatron

We have measured the number of like-sign (LS) and opposite-sign (OS) lepton pairs arising from double semileptonic decays of b and (b) over bar hadrons, pair produced at the Fermilab Tevatron collider. The data samples were collected with the Collider Detector at Fermilab during the 1992-1995 collider run by triggering on the existence of mumu or emu candidates in an event. The observed ratio of LS to OS dileptons leads to a measurement of the average time-integrated mixing probability of all produced b-flavored hadrons which decay weakly, (χ) over bar =0.152+/-0.007 (stat)+/-0.011 (syst), that is significantly larger than the world average (χ) over bar =0.118+/-0.005

Measurement of the Ratio of b Quark Production Cross Sections in Antiproton-Proton Collisions at 630 GeV and 1800 GeV

We report a measurement of the ratio of the bottom quark production cross section in antiproton-proton collisions at 630 GeV to 1800 GeV using bottom quarks with transverse momenta greater than 10.75 GeV identified through their semileptonic decays and long lifetimes. The measured ratio sigma(630)/sigma(1800) = 0.171 +/- .024 +/- .012 is in good agreement with next-to-leading order (NLO) quantum chromodynamics (QCD)

Observation of the narrow state X(3872)-\u3e J/psi pi(+)pi(-) in (p)over-barp collisions at root s=1.96 TeV

We report the observation of a narrow state decaying into J/psipi(+)pi(-) and produced in 220 pb(-1) of (p) over barp collisions at roots=1.96 TeV in the CDF II experiment. We observe 730+/-90 decays. The mass is measured to be 3871.3+/-0.7(stat)+/-0.4(syst) MeV/c(2), with an observed width consistent with the detector resolution. This is in agreement with the recent observation by the Belle Collaboration of the X(3872) meson

Recent Advancements in Computing Reliable Binding Free Energies in Drug Discovery Projects

In recent times, our healthcare system is being challenged by many drug-resistant microorganisms and ageing-associated diseases for which we do not have any drugs or drugs with poor therapeutic profile. With pharmaceutical technological advancements, increasing computational power and growth of related biomedical fields, there have been dramatic increase in the number of drugs approved in general, but still way behind in drug discovery for certain class of diseases. Now, we have access to bigger genomics database, better biophysical methods, and knowledge about chemical space with which we should be able to easily explore and predict synthetically feasible compounds for the lead optimization process. In this chapter, we discuss the limitations and highlights of currently available computational methods used for protein–ligand binding affinities estimation and this includes force-field, ab initio electronic structure theory and machine learning approaches. Since the electronic structure-based approach cannot be applied to systems of larger length scale, the free energy methods based on this employ certain approximations, and these have been discussed in detail in this chapter. Recently, the methods based on electronic structure theory and machine learning approaches also are successfully being used to compute protein–ligand binding affinities and other pharmacokinetic and pharmacodynamic properties and so have greater potential to take forward computer-aided drug discovery to newer heights.</p

Extending the application of biocatalysis to meet the challenges of drug development

The pharmaceutical industry, driven by an increasing need to deliver new and more effective medicines to patients, is increasingly turning to the use of engineered biocatalysts for both lead generation of active compounds and the sustainable manufacture of active pharmaceutical ingredients. Advances in enzyme discovery, high-throughput screening and protein engineering have substantially expanded the available biocatalysts, and consequently, many more synthetic transformations are now possible. Enzymes can be fine-tuned for practical applications with greater speed and likelihood of success than before, thereby leading to greater predictability and confidence when scaling up these processes. Coupled with a greater awareness of which reactions are suitable for biocatalysis (for example, biocatalytic retrosynthesis), new chemoenzymatic and multi-enzyme processes have been designed and applied to the synthesis of a range of important pharmaceutical target molecules. Increasingly, researchers are exploring opportunities for using immobilized biocatalysts in flow conditions. In this Review, we discuss some of the key drivers and scientific developments that are expanding the application of biocatalysis in the pharmaceutical industry and highlight potential future developments that likely will continue to increase the impact of biocatalysis in drug development