Evolutionary Multi-Objective Design of SARS-CoV-2 Protease Inhibitor Candidates

Computational drug design based on artificial intelligence is an emerging research area. At the time of writing this paper, the world suffers from an outbreak of the coronavirus SARS-CoV-2. A promising way to stop the virus replication is via protease inhibition. We propose an evolutionary multi-objective algorithm (EMOA) to design potential protease inhibitors for SARS-CoV-2's main protease. Based on the SELFIES representation the EMOA maximizes the binding of candidate ligands to the protein using the docking tool QuickVina 2, while at the same time taking into account further objectives like drug-likeliness or the fulfillment of filter constraints. The experimental part analyzes the evolutionary process and discusses the inhibitor candidates.Comment: 15 pages, 7 figures, submitted to PPSN 202

Probing electron-phonon interactions away from the Fermi level with resonant inelastic x-ray scattering

Interactions between electrons and lattice vibrations are responsible for a wide range of material properties and applications. Recently, there has been considerable interest in the development of resonant inelastic x-ray scattering (RIXS) as a tool for measuring electron-phonon ( e -ph) interactions. Here, we demonstrate the ability of RIXS to probe the interaction between phonons and specific electronic states both near to, and away from, the Fermi level. We perform carbon K -edge RIXS measurements on graphite, tuning the incident x-ray energy to separately probe the interactions of the π ∗ and σ ∗ electronic states. Our high-resolution data reveal detailed structure in the multiphonon RIXS features that directly encodes the momentum dependence of the e -ph interaction strength. We develop a Green’s-function method to model this structure, which naturally accounts for the phonon and interaction-strength dispersions, as well as the mixing of phonon momenta in the intermediate state. This model shows that the differences between the spectra can be fully explained by contrasting trends of the e -ph interaction through the Brillouin zone, being concentrated at the Γ and K points for the π ∗ states while being significant at all momenta for the σ ∗ states. Our results advance the interpretation of phonon excitations in RIXS and extend its applicability as a probe of e -ph interactions to a new range of out-of-equilibrium situations

Atropselective syntheses of (-) and (+) rugulotrosin A utilizing point-to-axial chirality transfer

Chiral, dimeric natural products containing complex structures and interesting biological properties have inspired chemists and biologists for decades. A seven-step total synthesis of the axially chiral, dimeric tetrahydroxanthone natural product rugulotrosin A is described. The synthesis employs a one-pot Suzuki coupling/dimerization to generate the requisite 2,2'-biaryl linkage. Highly selective point-to-axial chirality transfer was achieved using palladium catalysis with achiral phosphine ligands. Single X-ray crystal diffraction data were obtained to confirm both the atropisomeric configuration and absolute stereochemistry of rugulotrosin A. Computational studies are described to rationalize the atropselectivity observed in the key dimerization step. Comparison of the crude fungal extract with synthetic rugulotrosin A and its atropisomer verified that nature generates a single atropisomer of the natural product.P50 GM067041 - NIGMS NIH HHS; R01 GM099920 - NIGMS NIH HHS; GM-067041 - NIGMS NIH HHS; GM-099920 - NIGMS NIH HH

Social and cultural factors underlying generational differences in overweight: a cross-sectional study among ethnic minorities in the Netherlands

<p>Abstract</p> <p>Background</p> <p>The prevalence of overweight appears to vary in people of first and second generation ethnic minority groups. Insight into the factors that underlie these weight differences might help in understanding the health transition that is taking place across generations following migration. We studied the role of social and cultural factors associated with generational differences in overweight among young Turkish and Moroccan men and women in the Netherlands.</p> <p>Methods</p> <p>Cross-sectional data were derived from the LASER-study in which information on health-related behaviour and socio-demographic factors, level of education, occupational status, acculturation (cultural orientation and social contacts), religious and migration-related factors was gathered among Turkish and Moroccan men (n = 334) and women (n = 339) aged 15-30 years. Participants were interviewed during a home visit. Overweight was defined as a Body Mass Index ≥ 25 kg/m². Using logistic regression analyses, we tested whether the measured social and cultural factors could explain differences in overweight between first and second generation ethnic groups.</p> <p>Results</p> <p>Second generation women were less often overweight than first generation women (21.8% and 45.0% respectively), but this association was no longer significant when adjusting for the socioeconomic position (i.e. higher level of education) of second generation women (Odds Ratio (OR) = 0.77, 95%, Confidence Interval (CI) 0.40-1.46). In men, we observed a reversed pattern: second generation men were more often overweight than first generation men (32.7% and 27.8%). This association (OR = 1.89, 95% CI 1.09-3.24) could not be explained by the social and cultural factors because none of these factors were associated with overweight among men.</p> <p>Conclusions</p> <p>The higher socio-economic position of second generation Turkish and Moroccan women may partly account for the lower prevalence of overweight in this group compared to first generation women. Further research is necessary to elucidate whether any postulated socio-biological or other processes are relevant to the opposite pattern of overweight among men.</p

Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as asthma endotypes. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies

Functional Group and Substructure Searching as a Tool in Metabolomics

BACKGROUND: A direct link between the names and structures of compounds and the functional groups contained within them is important, not only because biochemists frequently rely on literature that uses a free-text format to describe functional groups, but also because metabolic models depend upon the connections between enzymes and substrates being known and appropriately stored in databases. METHODOLOGY: We have developed a database named "Biochemical Substructure Search Catalogue" (BiSSCat), which contains 489 functional groups, >200,000 compounds and >1,000,000 different computationally constructed substructures, to allow identification of chemical compounds of biological interest. CONCLUSIONS: This database and its associated web-based search program (http://bisscat.org/) can be used to find compounds containing selected combinations of substructures and functional groups. It can be used to determine possible additional substrates for known enzymes and for putative enzymes found in genome projects. Its applications to enzyme inhibitor design are also discussed

Identification and Characterization of Two Functionally Unknown Genes Involved in Butanol Tolerance of Clostridium acetobutylicum

Solvents toxicity is a major limiting factor hampering the cost-effective biotechnological production of chemicals. In Clostridium acetobutylicum, a functionally unknown protein (encoded by SMB_G1518) with a hypothetical alcohol interacting domain was identified. Disruption of SMB_G1518 and/or its downstream gene SMB_G1519 resulted in increased butanol tolerance, while overexpression of SMB_G1518-1519 decreased butanol tolerance. In addition, SMB_G1518-1519 also influences the production of pyruvate:ferredoxin oxidoreductase (PFOR) and flagellar protein hag, the maintenance of cell motility. We conclude that the system of SMB_G1518-1519 protein plays a role in the butanol sensitivity/tolerance phenotype of C. acetobutylicum, and can be considered as potential targets for engineering alcohol tolerance

Measurement of the t(t)over-bar production cross section in the dilepton channel in pp collisions at √s=8 TeV

The top-antitop quark (t (t) over bar) production cross section is measured in proton-proton collisions at root s = 8 TeV with the CMS experiment at the LHC, using a data sample corresponding to an integrated luminosity of 5.3 fb(-1). The measurement is performed by analysing events with a pair of electrons or muons, or one electron and one muon, and at least two jets, one of which is identified as originating from hadronisation of a bottom quark. The measured cross section is 239 +/- 2 (stat.) +/- 11 (syst.) +/- 6 (lum.) pb, for an assumed top-quark mass of 172.5 GeV, in agreement with the prediction of the standard model

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO