Accessible surface area from NMR chemical shifts

Investigating the electronic properties of edge glycine/biopolymer/graphene quantum dots

This study systematically investigated four types of graphene quantum dots (GQDs) AHEX, ZTRI, ZHEX, and ATRI, and their interactions with glycine to form GQD-glycine complexes. Utilizing density functional theory (DFT) and the PM6 semiempirical method, the study analyzed electronic properties and structure-activity relationships. Global reactivity indices were calculated using Koopmans' theorem, and quantitative structure-activity relationship (QSAR) parameters were assessed via SCIGRESS 0.3. The study further explored interactions using density of states (DOS) and quantum theory of atoms in molecules (QTAIM) analyses. Key findings revealed that glycine interaction significantly increased the total dipole moment (TDM) and decreased the HOMO/LUMO energy gap (ΔE) for the GQD-glycine complexes. Notably, ZTRI/glycine showed a TDM of 4.535 Debye and a reduced ΔE of 0.323 eV, indicating enhanced reactivity. Further interactions with cellulose, chitosan, and sodium alginate identified the ZTRI/glycine/sodium alginate composite as the most reactive, with a TDM of 8.020 Debye and the lowest ΔE of 0.200 eV. This composite also exhibited the highest electrophilicity index (56.421) and lowest chemical hardness (0.145 eV), underscoring its superior reactivity and stability. DOS analysis revealed that biomolecules contributed the most to molecular orbitals, with carbon atoms contributing the least. QTAIM analysis confirmed the greater stability of the ZTRI/glycine/sodium alginate complex compared to other studied composites. These results highlight the enhanced reactivity and stability of GQDs when interacting with glycine and sodium alginate.

Solution Structure, Dynamics, and New Antifungal Aspects of the Cysteine-Rich Miniprotein PAFC

The genome of Penicillium chrysogenum Q176 contains a gene coding for the 88-amino-acid (aa)-long glycine- and cysteine-rich P. chrysogenum antifungal protein C (PAFC). After maturation, the secreted antifungal miniprotein (MP) comprises 64 aa and shares 80% aa identity with the bubble protein (BP) from Penicillium brevicompactum, which has a published X-ray structure. Our team expressed isotope (15N, 13C)-labeled, recombinant PAFC in high yields, which allowed us to determine the solution structure and molecular dynamics by nuclear magnetic resonance (NMR) experiments. The primary structure of PAFC is dominated by 14 glycines, and therefore, whether the four disulfide bonds can stabilize the fold is challenging. Indeed, unlike the few published solution structures of other antifungal MPs from filamentous ascomycetes, the NMR data indicate that PAFC has shorter secondary structure elements and lacks the typical β-barrel structure, though it has a positively charged cavity and a hydrophobic core around the disulfide bonds. Some parts within the two putative γ-core motifs exhibited enhanced dynamics according to a new disorder index presentation of 15N-NMR relaxation data. Furthermore, we also provided a more detailed insight into the antifungal spectrum of PAFC, with specific emphasis on fungal plant pathogens. Our results suggest that PAFC could be an effective candidate for the development of new antifungal strategies in agriculture.

Auto-encoding NMR chemical shifts from their native vector space to a residue-level biophysical index

Chemical shifts (CS) are determined from NMR experiments and represent the resonance frequency of the spin of atoms in a magnetic field. They contain a mixture of information, encompassing the in-solution conformations a protein adopts, as well as the movements it performs. Due to their intrinsically multi-faceted nature, CS are difficult to interpret and visualize. Classical approaches for the analysis of CS aim to extract specific protein-related properties, thus discarding a large amount of information that cannot be directly linked to structural features of the protein. Here we propose an autoencoder-based method, called ShiftCrypt, that provides a way to analyze, compare and interpret CS in their native, multidimensional space. We show that ShiftCrypt conserves information about the most common structural features. In addition, it can be used to identify hidden similarities between diverse proteins and peptides, and differences between the same protein in two different binding states.

NMR chemical shift information is highly valuable in the investigation of small molecule and protein structure. Here, the authors developed a neural network approach to unify protein chemical shifts and their changes in response to changes in protein sequence, structure, and dimerization interactions.

Conformational dynamics study on human γS-crystallin as an efficient route to childhood blindness

Single point mutants of human γS-crystallin cause dominant congenital cataracts, a recent one of which involves the substitution of highly conserved glycine at 57th position with a bulkier tryptophan. Our high-resolution 3D structure of this G57W mutant (abbreviated hereafter as γS-G57W), reported recently revealed site-specific structural perturbations with higher aggregation and lower stability compared to its wild-type; a structural feature associated with important functional and therapeutic consequences. In this communication, we report for the first time, residue resolved conformational dynamics in both γS-WT and γS-G57W using solution NMR spectroscopy, and suggest how these differences could crucially affect the biochemistry of the mutant. Guided by our critical structural investigations, extensive conformational dynamics and biophysical studies presented here show that loss of structural stability arises from enhanced dynamics in Greek key motif 2 inducing flexibility in the N-terminal domain as opposed to its structurally unperturbed C-terminal counterpart. NMR spectral density correlations and internal dynamics comparisons with the wild-type suggest that the overall thermodynamic instability propagates from the mutated N-terminal β4-β5 loop providing a residue level understanding of the structural changes associated with this early onset of lens opacification. Our results highlight the vital role of conserved Greek key motifs in conferring structural stability to crystallins and provide crucial molecular insights into crystallin aggregation in the eye lens, which triggers cataract formation in children. Overall, this critical study provides a residue level understanding of how conformational changes affect the structure and function of crystallins in particular and proteins in general, during health and disease.

Toward Structure Determination of Disulfide-Rich Peptides Using Chemical Shift-Based Methods

Disulfide-rich peptides are a class of molecules for which NMR spectroscopy has been the primary tool for structural characterization. Here, we explore whether the process can be achieved by using structural information encoded in chemical shifts. We examine (i) a representative set of five cyclic disulfide-rich peptides that have high-resolution NMR and X-ray structures and (ii) a larger set of 100 disulfide-rich peptides from the PDB. Accuracy of the calculated structures was dependent on the methods used for searching through conformational space and for identifying native conformations. Although Hα chemical shifts could be predicted reasonably well using SHIFTX, agreement between predicted and experimental chemical shifts was sufficient for identifying native conformations for only some peptides in the representative set. Combining chemical shift data with the secondary structure information and potential energy calculations improved the ability to identify native conformations. Additional use of sparse distance restraints or homology information to restrict the search space also improved the resolution of the calculated structures. This study demonstrates that abbreviated methods have potential for elucidation of peptide structures to high resolution and further optimization of these methods, e.g., improvement in chemical shift prediction accuracy, will likely help transition these methods into the mainstream of disulfide-rich peptide structural biology.

Solution structure and novel insights into phylogeny and mode of action of the Neosartorya (Aspergillus) fischeri antifungal protein (NFAP)

Small, cysteine-rich and cationic antifungal proteins from natural sources are promising candidates for the development of novel treatment strategies to prevent and combat infections caused by drug-resistant fungi. However, limited information about their structure and antifungal mechanism hampers their future applications. In the present study, we determined the solution structure, dynamics and associated solvent areas of the Neosartorya (Aspergillus) fischeri antifungal protein NFAP. Genome mining within the genus revealed the presence of orthologous genes in N. fischeri and Neosartorya spathulata, and genes encoding closely related proteins can be found in Penicillium brasiliensis and Penicillium oxalicum. We show that the tertiary structure of these putative proteins can be resolved using the structure of NFAP as reliable template for in silico prediction. Localization studies with fluorescence-labelled protein pointed at an energy-dependent uptake mechanism of NFAP in the sensitive model fungus Neurospora crassa and subsequent cytoplasmic localization coincided with cell-death induction. The presented results contribute to a better understanding of the structure/function relationship of NFAP and related proteins and pave the way towards future antifungal drug development.

Rapid and reliable protein structure determination via chemical shift threading

Protein structure determination using nuclear magnetic resonance (NMR) spectroscopy can be both time-consuming and labor intensive. Here we demonstrate how chemical shift threading can permit rapid, robust, and accurate protein structure determination using only chemical shift data. Threading is a relatively old bioinformatics technique that uses a combination of sequence information and predicted (or experimentally acquired) low-resolution structural data to generate high-resolution 3D protein structures. The key motivations behind using NMR chemical shifts for protein threading lie in the fact that they are easy to measure, they are available prior to 3D structure determination, and they contain vital structural information. The method we have developed uses not only sequence and chemical shift similarity but also chemical shift-derived secondary structure, shift-derived super-secondary structure, and shift-derived accessible surface area to generate a high quality protein structure regardless of the sequence similarity (or lack thereof) to a known structure already in the PDB. The method (called E-Thrifty) was found to be very fast (often < 10 min/structure) and to significantly outperform other shift-based or threading-based structure determination methods (in terms of top template model accuracy)-with an average TM-score performance of 0.68 (vs. 0.50-0.62 for other methods). Coupled with recent developments in chemical shift refinement, these results suggest that protein structure determination, using only NMR chemical shifts, is becoming increasingly practical and reliable. E-Thrifty is available as a web server at http://ethrifty.ca .

Unraveling the meaning of chemical shifts in protein NMR

Chemical shifts are among the most informative parameters in protein NMR. They provide wealth of information about protein secondary and tertiary structure, protein flexibility, and protein-ligand binding. In this report, we review the progress in interpreting and utilizing protein chemical shifts that has occurred over the past 25years, with a particular focus on the large body of work arising from our group and other Canadian NMR laboratories. More specifically, this review focuses on describing, assessing, and providing some historical context for various chemical shift-based methods to: (1) determine protein secondary and super-secondary structure; (2) derive protein torsion angles; (3) assess protein flexibility; (4) predict residue accessible surface area; (5) refine 3D protein structures; (6) determine 3D protein structures and (7) characterize intrinsically disordered proteins. This review also briefly covers some of the methods that we previously developed to predict chemical shifts from 3D protein structures and/or protein sequence data. It is hoped that this review will help to increase awareness of the considerable utility of NMR chemical shifts in structural biology and facilitate more widespread adoption of chemical-shift based methods by the NMR spectroscopists, structural biologists, protein biophysicists, and biochemists worldwide. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.