Electrostatic complementarity at the interface drives transient protein-protein interactions

Exploration of dynamic interaction between β-lactoglobulin and casein micelles during UHT milk process

The protein aggregation induced by UHT treatment shortens the shelf life of UHT milk. However, the mechanism of β-Lg induced casein micelle aggregation remains unclear. Herein, the dynamic interaction between β-Lg and casein micelles during UHT processing was investigated by experimental techniques and molecular dynamics simulations. Results showed that β-Lg decreased the stability of casein micelles, increased their size and zeta potential. Raman and FTIR spectra analysis suggested that hydrogen and disulfide bonds facilitated their interaction. Cryo-TEM showed that the formation of the casein micelle/β-Lg complex involved rigid binding, flexible linking, and severe cross-linking aggregation during UHT processing. SAXS and MST demonstrated β-Lg bound to κ-casein on micelle surfaces with a dissociation constant (Kd) of 3.84 ± 1.14 μm. Molecular docking and dynamic simulations identified the interacting amino acid residues and clarified that electrostatic and van der Waals forces drove the interaction. UHT treatment increased hydrogen bonds and decreased total binding energy. The non-covalent binding promoted the formation of disulfide bonds between β-Lg and casein micelles under heat treatment. Ultimately, it was concluded that non-covalent interaction and disulfide bonding resulted in casein micelle/β-Lg aggregates. These findings provided scientific insights into protein aggregation in UHT milk.

Computational evidences of a misfolding event in an aggregation-prone light chain preceding the formation of the non-native pathogenic dimer

Antibody light chain amyloidosis is a disorder in which protein aggregates, mainly composed of immunoglobulin light chains, deposit in diverse tissues impairing the correct functioning of organs. Interestingly, due to the high susceptibility of antibodies to mutations, AL amyloidosis appears to be strongly patient-specific. Indeed, every patient will display their own mutations that will make the proteins involved prone to aggregation thus hindering the study of this disease on a wide scale. In this framework, determining the molecular mechanisms that drive the aggregation could pave the way to the development of patient-specific therapeutics. Here, we focus on a particular patient-derived light chain, which has been experimentally characterized. We investigated the early phases of the aggregation pathway through extensive full-atom molecular dynamics simulations, highlighting a structural rearrangement and the exposure of two hydrophobic regions in the aggregation-prone species. Next, we moved to consider the pathological dimerization process through docking and molecular dynamics simulations, proposing a dimeric structure as a candidate pathological first assembly. Overall, our results shed light on the first phases of the aggregation pathway for a light chain at an atomic level detail, offering new structural insights into the corresponding aggregation process.

Investigation of the MDM2-binding potential of de novo designed peptides using enhanced sampling simulations

The tumor suppressor p53 plays a crucial role in cellular responses to various stresses, regulating key processes such as apoptosis, senescence, and DNA repair. Dysfunctional p53, prevalent in approximately 50 % of human cancers, contributes to tumor development and resistance to treatment. This study employed deep learning-based protein design and structure prediction methods to identify novel high-affinity peptide binders (Pep1 and Pep2) targeting MDM2, with the aim of disrupting its interaction with p53. Extensive all-atom molecular dynamics simulations highlighted the stability of the designed peptide in complex with the target, supported by several structural analyses, including RMSD, RMSF, Rg, SASA, PCA, and free energy landscapes. Using the steered molecular dynamics and umbrella sampling simulations, we elucidate the dissociation dynamics of p53, Pep1, and Pep2 from MDM2. Notable differences in interaction profiles were observed, emphasizing the distinct dissociation patterns of each peptide. In conclusion, the results of our umbrella sampling simulations suggest Pep1 as a higher-affinity MDM2 binder compared to p53 and Pep2, positioning it as a potential inhibitor of the MDM2-p53 interaction. Using state-of-the-art protein design tools and advanced MD simulations, this study provides a comprehensive framework for rational in silico design of peptide binders with therapeutic implications in disrupting MDM2-p53 interactions for anticancer interventions.

Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments

Investigating protein-protein interactions is crucial for understanding cellular biological processes because proteins often function within molecular complexes rather than in isolation. While experimental and computational methods have provided valuable insights into these interactions, they often overlook a critical factor: the crowded cellular environment. This environment significantly impacts protein behavior, including structural stability, diffusion, and ultimately the nature of binding. In this review, we discuss theoretical and computational approaches that allow the modeling of biological systems to guide and complement experiments and can thus significantly advance the investigation, and possibly the predictions, of protein-protein interactions in the crowded environment of cell cytoplasm. We explore topics such as statistical mechanics for lattice simulations, hydrodynamic interactions, diffusion processes in high-viscosity environments, and several methods based on molecular dynamics simulations. By synergistically leveraging methods from biophysics and computational biology, we review the state of the art of computational methods to study the impact of molecular crowding on protein-protein interactions and discuss its potential revolutionizing effects on the characterization of the human interactome.

High-Throughput Interactome Determination via Sulfur Anomalous Scattering

We propose a novel approach for detecting the binding between proteins making use of the anomalous diffraction of natively present heavy elements, e.g., sulfurs, inside molecular three-dimensional structures. In particular, we analytically and numerically show that the diffraction patterns produced by the anomalous scattering of the sulfur atoms in a given direction depend additively on the relative distances between all couples of sulfur atoms. Thus, the differences in the patterns produced by bound proteins with respect to their nonbonded states can be exploited to rapidly assess protein complex formation. On the basis of our results, we suggest a possible experimental procedure for detecting protein-protein binding. Overall, the completely label-free and rapid method we propose may be readily extended to probe interactions on a large scale, thus paving the way for the development of a novel field of research based on a synchrotron light source.

Influence of N-protonation on electronic properties of acridine derivatives by quantum crystallography

Applications of 9-aminoacridine (9aa) and its derivatives span fields such as chemistry, biology, and medicine, including anticancer and antimicrobial activities. Protonation of such molecules can alter their bioavailability as weakly basic drugs like aminoacridines exhibit reduced solubility at high pH levels potentially limiting their effectiveness in patients with elevated gastric pH. In this study, we analyse the influence of protonation on the electronic characteristics of the molecular organic crystals of 9-aminoacridine. The application of quantum crystallography, including aspherical atom refinement, has enriched the depiction of electron density in the studied systems and non-covalent interactions, providing more details than previous studies. Our experimental results, combined with a topological analysis of the electron density and its Laplacian, provided detailed descriptions of how protonation changes the electron density distribution around the amine group and water molecule, concurrently decreasing the electron density at bond critical points of N/O-H bonds. Protonation also alters the molecular architecture of the systems under investigation. This is reflected in different proportions of the N⋯H and O⋯H intermolecular contacts for the neutral and protonated forms. Periodic DFT calculations of the cohesive energies of the crystal lattice, as well as computed interaction energies between molecules in the crystal, confirm that protonation stabilises the crystal structure due to a positive synergy between strong halogen and hydrogen bonds. Our findings highlight the potential of quantum crystallography in predicting crystal structure properties and point to its possible applications in developing new formulations for poorly soluble drugs.

Design of protein-binding peptides with controlled binding affinity: the case of SARS-CoV-2 receptor binding domain and angiotensin-converting enzyme 2 derived peptides

The development of methods able to modulate the binding affinity between proteins and peptides is of paramount biotechnological interest in view of a vast range of applications that imply designed polypeptides capable to impair or favour Protein-Protein Interactions. Here, we applied a peptide design algorithm based on shape complementarity optimization and electrostatic compatibility and provided the first experimental in vitro proof of the efficacy of the design algorithm. Focusing on the interaction between the SARS-CoV-2 Spike Receptor-Binding Domain (RBD) and the human angiotensin-converting enzyme 2 (ACE2) receptor, we extracted a 23-residues long peptide that structurally mimics the major interacting portion of the ACE2 receptor and designed in silico five mutants of such a peptide with a modulated affinity. Remarkably, experimental KD measurements, conducted using biolayer interferometry, matched the in silico predictions. Moreover, we investigated the molecular determinants that govern the variation in binding affinity through molecular dynamics simulation, by identifying the mechanisms driving the different values of binding affinity at a single residue level. Finally, the peptide sequence with the highest affinity, in comparison with the wild type peptide, was expressed as a fusion protein with human H ferritin (HFt) 24-mer. Solution measurements performed on the latter constructs confirmed that peptides still exhibited the expected trend, thereby enhancing their efficacy in RBD binding. Altogether, these results indicate the high potentiality of this general method in developing potent high-affinity vectors for hindering/enhancing protein-protein associations.

From haemadin to haemanorm: Synthesis and characterization of full-length haemadin from the leech Haemadipsa sylvestris and of a novel bivalent, highly potent thrombin inhibitor (haemanorm)

Hirudin from Hirudo medicinalis is a bivalent α-Thrombin (αT) inhibitor, targeting the enzyme active site and exosite-I, and is currently used in anticoagulant therapy along with its simplified analogue hirulog. Haemadin, a small protein (57 amino acids) isolated from the land-living leech Haemadipsa sylvestris, selectively inhibits αT with a potency identical to that of recombinant hirudin (KI  = 0.2 pM), with which it shares a common disulfide topology and overall fold. At variance with hirudin, haemadin targets exosite-II and therefore (besides the free protease) it also blocks thrombomodulin-bound αT without inhibiting the active intermediate meizothrombin, thus offering potential advantages over hirudin. Here, we produced in reasonably high yields and pharmaceutical purity (>98%) wild-type haemadin and the oxidation resistant Met5 → nor-Leucine analogue, both inhibiting αT with a KI of 0.2 pM. Thereafter, we used site-directed mutagenesis, spectroscopic, ligand-displacement, and Hydrogen/Deuterium Exchange-Mass Spectrometry techniques to map the αT regions relevant for the interaction with full-length haemadin and with the synthetic N- and C-terminal peptides Haem(1-10) and Haem(45-57). Haem(1-10) competitively binds to/inhibits αT active site (KI  = 1.9 μM) and its potency was enhanced by 10-fold after Phe3 → β-Naphthylalanine exchange. Conversely to full-length haemadin, haem(45-57) displays intrinsic affinity for exosite-I (KD  = 1.6 μM). Hence, we synthesized a peptide in which the sequences 1-9 and 45-57 were joined together through a 3-Glycine spacer to yield haemanorm, a highly potent (KI  = 0.8 nM) inhibitor targeting αT active site and exosite-I. Haemanorm can be regarded as a novel class of hirulog-like αT inhibitors with potential pharmacological applications.