Molecular dynamics simulations reveal canonical conformations in different pMHC/TCR interactions

The major defense system against microbial pathogens in vertebrates is the adaptive immune response and represents an effective mechanism in cancer surveillance. T cells represent an essential component of this complex system. They can recognize myriads of antigens as short peptides (p) originated from the intracellular degradation of foreign proteins presented by major histocompatibility complex (MHC) proteins. The clonotypic T-cell antigen receptor (TCR) is specialized in recognizing pMHC and triggering T cells immune response. It is still unclear how TCR engagement to pMHC is translated into the intracellular signal that initiates T-cell immune response. Some work has suggested the possibility that pMHC binding induces in the TCR conformational changes transmitted to its companion CD3 subunits that govern signaling. The conformational changes would promote phosphorylation of the CD3 complex ζ chain that initiates signal propagation intracellularly. Here, we used all-atom molecular dynamics simulations (MDs) of 500 ns to analyze the conformational behavior of three TCRs (1G4, ILA1 and ILA1α1β1) interacting with the same MHC class I (HLA-A*02:01) bound to different peptides, and modelled in the presence of a lipid bilayer. Our data suggest a correlation between the conformations explored by the β-chain constant regions and the T-cell response experimentally determined. In particular, independently by the TCR type involved in the interaction, the TCR activation seems to be linked to a specific zone of the conformational space explored by the β-chain constant region. Moreover, TCR ligation restricts the conformational space the MHC class I groove

Does blood type affect the COVID-19 infection pattern?

Among the many aspects that characterize the COVID-19 pandemic, two seem particularly challenging to understand: (i) the great geographical differences in the degree of virus contagiousness and lethality which were found in the different phases of the epidemic progression, and (ii) the potential role of the infected people's blood type in both the virus infectivity and the progression of the disease. A recent hypothesis could shed some light on both aspects. Specifically, it has been proposed that in the subject-to-subject transfer SARS-CoV-2 conserves on its capsid the erythrocytes' antigens of the source subject. Thus these conserved antigens can potentially cause an immune reaction in a receiving subject that has previously acquired specific antibodies for the source subject antigens. This hypothesis implies a blood type-dependent infection rate. The strong geographical dependence of the blood type distribution could be, therefore, one of the factors at the origin of the observed heterogeneity in the epidemics spread. Here, we present an epidemiological deterministic model where the infection rules based on blood types are taken into account and compare our model outcomes with the exiting worldwide infection progression data. We found an overall good agreement, which strengthens the hypothesis that blood types do play a role in the COVID-19 infection.Comment: 6 figures, 4 table

Exploring the Association Between Sialic Acid and SARS-CoV-2 Spike Protein Through a Molecular Dynamics-Based Approach

Recent experimental evidence demonstrated the capability of SARS-CoV-2 Spike protein to bind sialic acid molecules, which was a trait not present in SARS-CoV and could shed light on the molecular mechanism used by the virus for the cell invasion. This peculiar feature has been successfully predicted by in-silico studies comparing the sequence and structural characteristics that SARS-CoV-2 shares with other sialic acid-binding viruses, like MERS-CoV. Even if the region of the binding has been identified in the N-terminal domain of Spike protein, so far no comprehensive analyses have been carried out on the spike-sialic acid conformations once in the complex. Here, we addressed this aspect performing an extensive molecular dynamics simulation of a system composed of the N-terminal domain of the spike protein and a sialic acid molecule. We observed several short-lived binding events, reconnecting to the avidic nature of the binding, interestingly occurring in the surface Spike region where several insertions are present with respect to the SARS-CoV sequence. Characterizing the bound configurations via a clustering analysis on the Principal Component of the motion, we identified different possible binding conformations and discussed their dynamic and structural properties. In particular, we analyze the correlated motion between the binding residues and the binding effect on the stability of atomic fluctuation, thus proposing regions with high binding propensity with sialic acid

Investigating the side-chain structural organization behind the stability of protein folding and binding

What are the molecular mechanisms that dictate protein-protein binding stability and whether those are related to the ones behind protein fold stability are still largely open questions. Indeed, despite many past efforts, we still lack definitive models to account for experimental quantities like protein melting temperature or complex binding affinity. Here, we investigate and compare chemical and physical features on a dataset of protein with known melting temperature as well as a large dataset of protein-protein complexes with reliable experimental binding affinity. In particular, we probed the aminoacid composition and the organization of the network of intramolecular and intermolecular interaction energies among residues. We found that hydrophobic residues present on the protein surfaces are preferentially located in the binding regions, while charged residues behave oppositely. In addition, the abundance of polar amino acid like Serine and Proline correlates with the binding affinity of the complexes. Analysing the interaction energies we found that distant Coulombic interactions are responsible for thermal stability while the total inter-molecular van der Waals energy correlates with protein-protein binding affinity.Comment: 8 pages, 3 figure

Shape Complementarity Optimization of Antibody-Antigen Interfaces: the Application to SARS-CoV-2 Spike Protein

Many factors influence biomolecules binding, and its assessment constitutes an elusive challenge in computational structural biology. In this respect, the evaluation of shape complementarity at molecular interfaces is one of the main factors to be considered. We focus on the particular case of antibody-antigen complexes to quantify the complementarities occurring at molecular interfaces. We relied on a method we recently developed, which employs the 2D Zernike descriptors, to characterize investigated regions with an ordered set of numbers summarizing the local shape properties. Collected a structural dataset of antibody-antigen complexes, we applied this method and we statistically distinguished, in terms of shape complementarity, pairs of interacting regions from non-interacting ones. Thus, we set up a novel computational strategy based on \textit{in-silico} mutagenesis of antibody binding site residues. We developed a Monte Carlo procedure to increase the shape complementarity between the antibody paratope and a given epitope on a target protein surface. We applied our protocol against several molecular targets in SARS-CoV-2 spike protein, known to be indispensable for viral cell invasion. We, therefore, optimized the shape of template antibodies for the interaction with such regions. As the last step of our procedure, we performed an independent molecular docking validation of the results of our Monte Carlo simulations.Comment: 13 pages, 4 figure

A computational approach to investigate TDP-43 C-terminal fragments aggregation in Amyotrophic Lateral Sclerosis

Many of the molecular mechanisms underlying the pathological aggregation of proteins observed in neurodegenerative diseases are still not fully understood. Among the diseases associated with protein aggregates, for example, Amyotrophic Lateral Sclerosis (ALS) is of relevant importance. Although understanding the processes that cause the disease is still an open challenge, its relationship with protein aggregation is widely known. In particular, human TDP-43, an RNA/DNA binding protein, is a major component of pathological cytoplasmic inclusions described in ALS patients. The deposition of the phosphorylated full-length TDP-43 in spinal cord cells has been widely studied, and it has been shown that the brain cortex presents an accumulation of phosphorylated C-terminal fragments (CTFs). Even if it is debated whether CTFs represent a primary cause of ALS, they are a hallmark of TDP-43 related neurodegeneration in the brain. Here, we investigate the CTFs aggregation process, providing a possible computational model of interaction based on the evaluation of shape complementarity at the interfaces. To this end, extensive Molecular Dynamics (MD) simulations were conducted for different types of fragments with the aim of exploring the equilibrium configurations. Adopting a newly developed approach based on Zernike polynomials, for finding complementary regions of the molecular surface, we sampled a large set of exposed portions of the molecular surface of CTFs structures as obtained from MD simulations. The analysis proposes a set of possible associations between the CTFs, which could drive the aggregation process of the CTFs.Comment: 9 pages, 4 figures, 1 tabl

Exploiting Reaction-Diffusion Conditions to Trigger Pathway Complexity in the Growth of a MOF

Coordination polymers (CPs), including metal-organic frameworks (MOFs), are crystalline materials with promising applications in electronics, magnetism, catalysis, and gas storage/separation. However, the mechanisms and pathways underlying their formation remain largely undisclosed. Herein, we demonstrate that diffusion-controlled mixing of reagents at the very early stages of the crystallization process (i.e., within ≈40 ms), achieved by using continuous-flow microfluidic devices, can be used to enable novel crystallization pathways of a prototypical spin-crossover MOF towards its thermodynamic product. In particular, two distinct and unprecedented nucleation-growth pathways were experimentally observed when crystallization was triggered under microfluidic mixing. Full-atom molecular dynamics simulations also confirm the occurrence of these two distinct pathways during crystal growth. In sharp contrast, a crystallization by particle attachment was observed under bulk (turbulent) mixing. These unprecedented results provide a sound basis for understanding the growth of CPs and open up new avenues for the engineering of porous materials by using out-of-equilibrium conditions

Insights into the Interaction Mechanism of DTP3 with MKK7 by Using STD-NMR and Computational Approaches

GADD45β/MKK7 complex is a non-redundant, cancer cell-restricted survival module downstream of the NF-kB survival pathway, and it has a pathogenically critical role in multiple myeloma, an incurable malignancy of plasma cells. The first-in-class GADD45β/MKK7 inhibitor DTP3 effectively kills MM cells expressing its molecular target, both in vitro and in vivo, by inducing MKK7/JNK-dependent apoptosis with no apparent toxicity to normal cells. DTP3 combines favorable drug-like properties, with on-target-specific pharmacology, resulting in a safe and cancer-selective therapeutic effect; however, its mode of action is only partially understood. In this work, we have investigated the molecular determinants underlying the MKK7 interaction with DTP3 by combining computational, NMR, and spectroscopic methods. Data gathered by fluorescence quenching and computational approaches consistently indicate that the N-terminal region of MKK7 is the optimal binding site explored by DTP3. These findings further the understanding of the selective mode of action of GADD45β/MKK7 inhibitors and inform potential mechanisms of drug resistance. Notably, upon validation of the safety and efficacy of DTP3 in human trials, our results could also facilitate the development of novel DTP3-like therapeutics with improved bioavailability or the capacity to bypass drug resistance

Gender minorities in breast cancer – Clinical trials enrollment disparities: Focus on male, transgender and gender diverse patients

Background: The last years have seen unprecedented improvement in breast cancer (BC) survival rates. However, this entirely apply to female BC patients, since gender minorities (male, transgender/gender-diverse) are neglected in BC phase III registration clinical trials. Methods: We conducted a scoping review of phase III clinical trials of agents with a current positioning within the therapeutic algorithms of BC. Results: We selected 51 phase III trials. Men enrollment was allowed in 35.3% of trials. In none of the trial inclusion/exclusion criteria referred to transgender/gender-diverse people. A numerical higher rate of enrolled men was observed in the contemporary as compared to historical group. We found a statistically significant association between the drug class and the possibility of including men: 100%, 80%, 50%, 33.3%, 25%, 10% and 9.1% of trials testing ICI/PARP-i, ADCs, PI3K/AKT/mTOR-i, anti-HER2 therapy, CDK4/6-i, ET alone, and CT alone. Overall, 77409 patients were enrolled, including 112 men (0.2%). None of the trial reported transgender/gender-diverse people proportion. Studies investigating PARP-i were significantly associated with the highest rate of enrolled men (1.42%), while the lowest rates were observed for trials of CT (0.13%), ET alone (0.10%), and CDK 4/6-I (0.08%), p < 0.001. Conclusions: We confirmed that gender minorities are severely underrepresented among BC registration trials. We observed a lower rate of men in trials envisaging endocrine manipulation or in less contemporary trials. This work sought to urge the scientific community to increase the awareness level towards the issue of gender minorities and to endorse more inclusive criteria in clinical trials