Machine Learning-Enhanced Quantum Chemistry-Assisted Refinement of the Active Site Structure of Metalloproteins.

Understanding the fine structural details of inhibitor binding at the active site of metalloenzymes can have a profound impact on the rational drug design targeted to this broad class of biomolecules. Structural techniques such as NMR, cryo-EM, and X-ray crystallography can provide bond lengths and angles, but the uncertainties in these measurements can be as large as the range of values that have been observed for these quantities in all the published structures. This uncertainty is far too large to allow for reliable calculations at the quantum chemical (QC) levels for developing precise structure-activity relationships or for improving the energetic considerations in protein-inhibitor studies. Therefore, the need arises to rely upon computational methods to refine the active site structures well beyond the resolution obtained with routine application of structural methods. In a recent paper, we have shown that it is possible to refine the active site of cobalt(II)-substituted MMP12, a metalloprotein that is a relevant drug target, by matching to the experimental pseudocontact shifts (PCS) those calculated using multireference ab initio QC methods. The computational cost of this methodology becomes a significant bottleneck when the starting structure is not sufficiently close to the final one, which is often the case with biomolecular structures. To tackle this problem, we have developed an approach based on a neural network (NN) and a support vector regression (SVR) and applied it to the refinement of the active site structure of oxalate-inhibited human carbonic anhydrase 2 (hCAII), another prototypical metalloprotein target. The refined structure gives a remarkably good agreement between the QC-calculated and the experimental PCS. This study not only contributes to the knowledge of CAII but also demonstrates the utility of combining machine learning (ML) algorithms with QC calculations, offering a promising avenue for investigating other drug targets and complex biological systems in general.

Modular, multi-robot integration of laboratories: an autonomous workflow for solid-state chemistry.

Automation can transform productivity in research activities that use liquid handling, such as organic synthesis, but it has made less impact in materials laboratories, which require sample preparation steps and a range of solid-state characterization techniques. For example, powder X-ray diffraction (PXRD) is a key method in materials and pharmaceutical chemistry, but its end-to-end automation is challenging because it involves solid powder handling and sample processing. Here we present a fully autonomous solid-state workflow for PXRD experiments that can match or even surpass manual data quality, encompassing crystal growth, sample preparation, and automated data capture. The workflow involves 12 steps performed by a team of three multipurpose robots, illustrating the power of flexible, modular automation to integrate complex, multitask laboratories.

Label-Free Analysis of Urine Samples with In-Flow Digital Holographic Microscopy.

Urinary tract infections are among the most frequent infectious diseases and require screening a great amount of urine samples from patients. However, a high percentage of samples result as negative after urine culture plate tests (CPTs), demanding a simple and fast preliminary technique to screen out the negative samples. We propose a digital holographic microscopy (DHM) method to inspect fresh urine samples flowing in a glass capillary for 3 min, recording holograms at 2 frames per second. After digital reconstruction, bacteria, white and red blood cells, epithelial cells and crystals were identified and counted, and the samples were classified as negative or positive according to clinical cutoff values. Taking the CPT as reference, we processed 180 urine samples and compared the results with those of urine flow cytometry (UFC). Using standard evaluation metrics for our screening test, we found a similar performance for DHM and UFC, indicating DHM as a suitable and fast screening technique retaining several advantages. As a benefit of DHM, the technique is label-free and does not require sample preparation. Moreover, the phase and amplitude images of the cells and other particles present in urine are digitally recorded and can serve for further investigation afterwards.

The evolution of paramagnetic NMR as a tool in structural biology.

Paramagnetic NMR data contain extremely accurate long-range information on metalloprotein structures and, when used in the frame of integrative structural biology approaches, they allow for the retrieval of structural details to a resolution that is not achievable using other techniques. Paramagnetic data thus represent an extremely powerful tool to refine protein models in solution, especially when coupled to X-ray or cryoelectron microscopy data, to monitor the formation of complexes and determine the relative arrangements of their components, and to highlight the presence of conformational heterogeneity. More recently, theoretical and computational advancements in quantum chemical calculations of paramagnetic NMR observables are progressively opening new routes in structural biology, because they allow for the determination of the structure within the coordination sphere of the metal center, thus acting as a loupe on sites that are difficult to observe but very important for protein function.

Lysozyme is Sterically Trapped Within the Silica Cage in Bioinspired Silica-Lysozyme Composites: A Multi-Technique Understanding of Elusive Protein-Material Interactions.

Lysozyme is widely known to promote the formation of condensed silica networks from solutions containing silicic acid, in a reproducible and cost-effective way. However, little is known about the fate of the protein after the formation of the silica particles. Also, the relative arrangement of the different components in the resulting material is a matter of debate. In this study, we investigate the nature of the protein-silica interactions by means of solid-state nuclear magnetic resonance spectroscopy, small-angle X-ray scattering, and electron microscopy. We find that lysozyme and silica are in intimate contact and strongly interacting, but their interaction is neither covalent nor electrostatic: lysozyme is mostly trapped inside the silica by steric effects.

A High-Resolution View of the Coordination Environment in a Paramagnetic Metalloprotein from its Magnetic Properties.

Metalloproteins constitute a significant fraction of the proteome of all organisms and their characterization is critical for both basic sciences and biomedical applications. A large portion of metalloproteins bind paramagnetic metal ions, and paramagnetic NMR spectroscopy has been widely used in their structural characterization. However, the signals of nuclei in the immediate vicinity of the metal center are often broadened beyond detection. In this work, we show that it is possible to determine the coordination environment of the paramagnetic metal in the protein at a resolution inaccessible to other techniques. Taking the structure of a diamagnetic analogue as a starting point, a geometry optimization is carried out by fitting the pseudocontact shifts obtained from first principles quantum chemical calculations to the experimental ones.

A Quantum Chemistry View on Two Archetypical Paramagnetic Pentacoordinate Nickel(II) Complexes Offers a Fresh Look on Their NMR Spectra.

Quantum chemical methods for calculating paramagnetic NMR observables are becoming increasingly accessible and are being included in the inorganic chemistry practice. Here, we test the performance of these methods in the prediction of proton hyperfine shifts of two archetypical high-spin pentacoordinate nickel(II) complexes (NiSAL-MeDPT and NiSAL-HDPT), which, for a variety of reasons, turned out to be perfectly suited to challenge the predictions to the finest level of detail. For NiSAL-MeDPT, new NMR experiments yield an assignment that perfectly matches the calculations. The slightly different hyperfine shifts from the two "halves" of the molecules related by a pseudo-C2 axis, which are experimentally divided into two well-defined spin systems, are also straightforwardly distinguished by the calculations. In the case of NiSAL-HDPT, for which no X-ray structure is available, the quality of the calculations allowed us to refine its structure using as a starting template the structure of NiSAL-MeDPT.

Multivariate Curve Resolution for 2D Solid-State NMR spectra.

We present a processing method, based on the multivariate curve resolution approach (MCR), to denoise 2D solid-state NMR spectra, yielding a substantial S/N ratio increase while preserving the lineshapes and relative signal intensities. These spectral features are particularly important in the quantification of silicon species, where sensitivity is limited by the low natural abundance of the 29Si nuclei and by the dilution of the intrinsic protons of silica, but can be of interest also when dealing with other intermediate-to-low receptivity nuclei. This method also offers the possibility of coprocessing multiple 2D spectra that have the signals at the same frequencies but with different intensities (e.g.: as a result of a variation in the mixing time). The processing can be carried out on the time-domain data, thus preserving the possibility of applying further processing to the data. As a demonstration, we have applied Cadzow denoising on the MCR-processed FIDs, achieving a further increase in the S/N ratio and more effective denoising also on the transients at longer indirect evolution times. We have applied the combined denoising on a set of experimental data from a lysozyme-silica composite.

On the Mechanism of Bioinspired Formation of Inorganic Oxides: Structural Evidence of the Electrostatic Nature of the Interaction between a Mononuclear Inorganic Precursor and Lysozyme.

Nature has evolved several molecular machineries to promote the formation at physiological conditions of inorganic materials, which would otherwise be formed in extreme conditions. The molecular determinants of this process have been established over the last decade, identifying a strong role of electrostatics in the first steps of the precipitation. However, no conclusive, structure-based evidence has been provided so far. In this manuscript, we test the binding of lysozyme with silica and titania potential precursors. In contrast with the absence of structural information about the interaction with the silica precursor, we observe the interaction with a mononuclear titanium(IV) species, which is found to occur in a region rich of positive charges.

Assessing Structural Preferences of Unstructured Protein Regions by NMR.

Biomacromolecules, such as proteins, often exhibit significant motions intimately associated with their function. Intrinsically disordered proteins and proteins with intrinsically disordered regions, although extremely important for a plethora of cellular functions, are difficult to structurally characterize at the atomic level because the experimental parameters report on ensemble and time averages. Here, we demonstrate for the C-terminal domain of the human immunodeficiency virus type 1 capsid protein that NMR and, in particular, residual dipolar couplings (RDCs) measured for the folded portion of the protein can inform on the structural preferences of the unstructured portion using RDC-prediction tools and the maximum occurrence approach.

Assessing protein conformational landscapes: integration of DEER data in Maximum Occurrence analysis.

The properties of the conformational landscape of a biomolecule are of capital importance to understand its function. It is widely accepted that a statistical ensemble is far more representative than a single structure, especially for proteins with disordered regions. While experimental data provide the most important handle on the conformational variability that the system is experiencing, they usually report on either time or ensemble averages. Since the available conformations largely outnumber the (independent) available experimental data, the latter can be equally well reproduced by a variety of ensembles. We have proposed the Maximum Occurrence (MaxOcc) approach to provide an upper bound of the statistical weight of each conformation. This method is expected to converge towards the true statistical weights by increasing the number of independent experimental datasets. In this paper we explore the ability of DEER (Double Electron Electron Resonance) data, which report on the distance distribution between two spin labels attached to a biomolecule, to restrain the MaxOcc values and its complementarity to previously introduced experimental techniques such as NMR and Small-Angle X-ray Scattering. We here present the case of Ca2+ bound calmodulin (CaM) as a test case and show that DEER data impose a sizeable reduction of the conformational space described by high MaxOcc conformations.

Effect of pH and Mg2+ on Amorphous Magnesium-Calcium Phosphate (AMCP) stability.

HYPOTHESIS: Amorphous Magnesium-Calcium Phosphate (AMCP) particles in the distal small intestine have been shown to have a fundamental role in mammals' immune-surveillance mechanisms. Their formation in the gut lumen and their stability against crystallization are expected to depend upon physiological conditions such as pH and [Mg2+]. Knowing the influence of these parameters on AMCP stability would allow to predict the presence and the activity of the particles in physiological or pathological conditions. EXPERIMENTS: We performed the synthesis of AMCP particles at physiological temperature, in phosphate buffer at variable pH from ∼7.0 to 7.4. The stability of the particles was then tested by dispersing them in different conditions of [Mg2+], pH and concentration, so to mimic different biological conditions. The particles were characterized in terms of morphology, crystallinity, chemical composition and porosity. FINDINGS: The characterization showed that we managed to prepare AMCPs with features matching those of the endogenous particles. Both the lifetime of the amorphous phase and the nature of the formed crystalline material were found to depend upon [Mg2+], pH and concentration. This article paves the way for the comprehension of possible dysfunctions of the gut immune-surveillance mechanisms due to imbalances of these physico-chemical parameters.