Quantitative Biology

Use of a combination of statistical thermodynamics and the Gershgorin theorem enable us to guess, in the thermodynamic limit, a plausible value for the upper bound free-energy difference between native-like structures of monomeric globular proteins. Support to our result in light of both the observed free-energy change between the native and denatured states and the microstability free-energy values obtained from the observed micro-unfolding tendency of nine globular proteins, will be here discussed.

Due to the low density of envelope (Env) spikes on the surface of HIV-1, neutralizing IgG antibodies rarely bind bivalently using both antigen-binding arms (Fabs) to crosslink between spikes (inter-spike crosslinking), instead resorting to weaker monovalent binding that is more sensitive to Env mutations. Synthetic antibodies designed to bivalently bind a single Env trimer (intra-spike crosslinking) were previously shown to exhibit increased neutralization potencies. In initial work, diFabs joined by varying lengths of rigid double-stranded DNA (dsDNA) were considered. Anticipating future experiments to improve synthetic antibodies, we investigate whether linkers with different rigidities could enhance diFab potency by modeling DNA-Fabs containing different combinations of rigid dsDNA and flexible single-stranded DNA (ssDNA) and characterizing their neutralization potential. Model predictions suggest that while a long flexible polymer may be capable of bivalent binding, it exhibits weak neutralization due to the large loss in entropic degrees of freedom when both Fabs are bound. In contrast, the strongest neutralization potencies are predicted to require a rigid linker that optimally spans the distance between two Fab binding sites on an Env trimer, and avidity can be further boosted by incorporating more Fabs into these constructs. These results inform the design of multivalent anti-HIV-1 therapeutics that utilize avidity effects to remain potent against HIV-1 in the face of the rapid mutation of Env spikes.

Abnormal hemoglobins can have major consequences for tissue delivery of oxygen. Correct diagnosis of hemoglobinopathies with altered oxygen affinity requires a determination of hemoglobin oxygen dissociation curve (ODC), which relates the hemoglobin oxygen saturation to the partial pressure of oxygen in the blood. Determination of the ODC of human hemoglobin is typically carried out under conditions in which hemoglobin is in equilibrium with O2 at each partial pressure. However, in the human body due to the fast transit of RBCs through tissues hemoglobin oxygen exchanges occur under non-equilibrium conditions. We describe the determination of non-equilibrium ODC, and show that under these conditions Hb cooperativity has two apparent components in the Adair, Perutz, and MWC models of Hb. The first component, which we call sequential cooperativity, accounts for ~70% of Hb cooperativity, and emerges from the constraint of sequential binding that is shared by the three models. The second component, which we call conformational cooperativity, accounts for ~30% of Hb cooperativity, and is due either to a conformational equilibrium between low affinity and high affinity tetramers (as in the MWC model), or to a conformational change from low to high affinity once two of the tetramer sites are occupied (Perutz model).

Predicting the structure of multi-protein complexes is a grand challenge in biochemistry, with major implications for basic science and drug discovery. Computational structure prediction methods generally leverage pre-defined structural features to distinguish accurate structural models from less accurate ones. This raises the question of whether it is possible to learn characteristics of accurate models directly from atomic coordinates of protein complexes, with no prior assumptions. Here we introduce a machine learning method that learns directly from the 3D positions of all atoms to identify accurate models of protein complexes, without using any pre-computed physics-inspired or statistical terms. Our neural network architecture combines multiple ingredients that together enable end-to-end learning from molecular structures containing tens of thousands of atoms: a point-based representation of atoms, equivariance with respect to rotation and translation, local convolutions, and hierarchical subsampling operations. When used in combination with previously developed scoring functions, our network substantially improves the identification of accurate structural models among a large set of possible models. Our network can also be used to predict the accuracy of a given structural model in absolute terms. The architecture we present is readily applicable to other tasks involving learning on 3D structures of large atomic systems.

COVID-19 presents a great threat to public health worldwide and the infectious agent SARS-CoV-2 is currently the target of much research aiming at inhibition. The virus' main protease is a dimeric enzyme that has only recently begun to be thoroughly described, opening the door for virtual screening more broadly. Here, a PAIN-filtered flavonoid database was screened against four sites of the protease: a free (normal) conformation of the Substrate Binding Site (NSBS), an induced-fit state of the SBS (ISBS), a Dimerization Site (DS) and a Cryptic Site (CS). The mean binding energies of the top five ligands from each site were -9.52, -11.512, -7.042 and -10.348 kcal/mol for the NSBS, the ISBS, the DS and the CS, respectively. For the DS and CS, these top five compounds were selected as candidates to bind their respective site. In the case of SBS, the top 30 ligands with the lowest binding energies from NSBS and ISBS were contrasted and the ones present in both lists were selected as the final candidates. The final list was: Dorsilurin E (FL3FQUNP0001), Euchrenone a11 (FL2FALNP0014), Kurziflavolactone C (FL2FA9NC0016), Licorice glycoside E (FL2F1AGSN001) and Taxifolin 3'- (6"-phenyl- acetylglucoside) (FL4DACGS0020) for the SBS; Sanggenol O (FL2FALNP0020), CHEMBL2171573, Kanzonol E (FL3F1ANP0001), CHEMBL2171584 and Abyssynoflavanone VI (FL2FACNP0014) for DS and CHEMBL2171598, CHEMBL2171577, Denticulaflavanol (FL5FAANR0001), Kurzichalcolactone (FL1CA9NC0001) and CHEMBL2171578 for CS. Virtual screening integrated several confirmation methods, including cross-docking assays and positive and negative controls. All 15 compounds are currently subjected to molecular dynamics so as to theoretically validate their binding to the protease.

The second domain of gelsolin (G2) hosts mutations responsible for a hereditary form of amyloidosis. The active form of gelsolin is Ca2+-bound; it is also a dynamic protein, hence structural biologists often rely on the study of the isolated G2. However, the wild type G2 structure that have been used so far in comparative studies is bound to a crystallographic Cd2+, in lieu of the physiological calcium. Here, we report the wild type structure of G2 in complex with Ca2+ highlighting subtle ion-dependent differences. Previous findings on different G2 mutations are also briefly revised in light of these results.

Bacterial infectious diseases are a major threat to human health. Timely and sensitive pathogenic bacteria detection is crucial in identifying the bacterial contaminations and preventing the spread of infectious diseases. Due to limitations of conventional bacteria detection techniques there have been concerted research efforts towards development of new biosensors. Biosensors offering label free, whole bacteria detection are highly desirable over those relying on label based or pathogenic molecular components detection. The major advantage is eliminating the additional time and cost required for labeling or extracting the desired bacterial components. Here, we demonstrate rapid, sensitive and label free E. coli detection utilizing interferometric reflectance imaging enhancement allowing for visualizing individual pathogens captured on the surface. Enabled by our ability to count individual bacteria on a large sensor surface, we demonstrate a limit of detection of 2.2 CFU/ml from a buffer solution with no sample preparation. To the best of our knowledge, this high level of sensitivity for whole E. coli detection is unprecedented in label free biosensing. The specificity of our biosensor is validated by comparing the response to target bacteria E. coli and non target bacteria S. aureus, K. pneumonia and P. aeruginosa. The biosensor performance in tap water also proves that its detection capability is unaffected by the sample complexity. Furthermore, our sensor platform provides high optical magnification imaging and thus validation of recorded detection events as the target bacteria based on morphological characterization. Therefore, our sensitive and label free detection method offers new perspectives for direct bacterial detection in real matrices and clinical samples.

Metal nanoclusters (NCs), typically consisting of a few to tens of metal atoms, bridge the gap between organometallic compounds and crystalline metal nanoparticles. As their size approaches the Fermi wavelength of electrons, metal NCs exhibit discrete energy levels, which in turn results in the emergence of intriguing physical and chemical (or physicochemical) properties, especially strong fluorescence. In the past few decades, dramatic growth has been witnessed in the development of different types of noble metal NCs (mainly AuNCs and AgNCs). However, compared with noble metals, copper is a relatively earth-abundant and cost-effective metal. Theoretical and experimental studies have shown that copper NCs (CuNCs) possess unique catalytic and photoluminescent properties. In this context, CuNCs are emerging as a new class of nontoxic, economic, and effective phosphors and catalysts, drawing significant interest across the life and medical sciences. To highlight these achievements, this review begins by providing an overview of a multitude of factors that play central roles in the fluorescence of CuNCs. Additionally, a critical perspective of how the aggregation of CuNCs can efficiently improve the florescent stability, tunability, and intensity is also discussed. Following, we present representative applications of CuNCs in detection and bioimaging. Finally, we outline current challenges and our perspective on the development of CuNCs.

2019-nCoV is a novel coronavirus was isolated and identified in 2019 in Wuhan, China. On 17th February and according to world health organization, a number of 71 429 confirmed cases worldwide, among them 2162 new cases recorded in the last 24 hours. There is no drug or vaccine for human and animal coronavirus. The inhibition of 3CL hydrolase enzyme provides a promising therapeutic principle for developing treatments against CoViD-19. The 3CLpro (Mpro) known for involving in counteracting the host innate immune response. This work presents the inhibitory effect of some natural compounds against 3CL hydrolase enzyme, and explain the main interactions in inhibitor-enzyme complex. Molecular docking study carried out using Autodock Vina. By screening several molecules, we identified three candidate agents that inhibit the main protease of coronavirus. Hispidin, lepidine E, and folic acid bound tightly in the enzyme, strong hydrogen bonds have been formed (1.69-1.80&[Aring]) with the active site residues. This study provides a possible therapeutic strategy for CoViD-19.

Many of the building blocks of life such as amino acids and nucleotides are chiral, i.e., different from their mirror image. Contemporary life selects and synthesizes only one of two possible handednesses. In an abiotic environment, however, there are usually equally many left- and right-handed molecules. If homochirality was a prerequisite of life, there must have been physical or chemical circumstances that led to the selection of a certain preference. Conversely, if it was a consequence of life, we must identify possible pathways for accomplishing a transition from a racemic to a homochiral chemistry. After a discussion of the observational evidence, I will review ideas where homochirality of any handedness could emerge as a consequence of the first polymerization events of nucleotides in an emerging RNA world. These mechanisms are not limited to nucleotides, but can also occur for peptides, as a precursor to the RNA world. The question of homochirality is, in this sense, intimately tied to the origin of life. Future Mars missions may be able to detect biomolecules of extant or extinct life. We will therefore also discuss possible experimental setups for determining the chirality of primitive life forms in situ on Mars.