The role of temperature in the binding of the disordered epitope region of human thrombopoietin to antibody: A molecular dynamics simulations study.

The N-terminal domain (163 residues) of Human thrombopoietin (hTPO) is highly conserved and responsible for the receptor-binding. The crystal structure of free hTPO is not yet available, but the crystal structure of its receptor-binding domain (hTPO163) is available in complex with the TN1-Fab antibody. According to a thermodynamic study of hTPO163 binding to TN1-Fab Ab, the ΔH value for binding becomes more negative with an increase in temperature from 283 K to 303 K. The objective of our study is to understand how the free hTPO163 behaves dynamically and to study the effect of temperature on the association of hTPO163 to TN1-Fab antibody through molecular dynamics simulations. We studied the Ag-Ab interactions at two different temperatures 298 K and 303 K. The discontinuous epitope region (residues 98-115) of free hTPO163 displays a conformational switch and it gets stabilized upon binding to the Ab at 303 K. Based on our results, it may be surmised that the epitope region 98-115 is behaving like a disordered epitope. The disordered epitopes are known to be more efficient in binding with the antibody. We also find that, there is an increase in number of hydrogen-bonding interactions and hydrophobic contacts with an increase in the temperature from 298 K to 303 K. Thus, this observation explains a possible reason behind the more negative value of ΔH at the higher temperature 303 K as compared to 298 K.

Proteomics and Machine Learning Approaches Reveal a Set of Prognostic Markers for COVID-19 Severity With Drug Repurposing Potential.

The pestilential pathogen SARS-CoV-2 has led to a seemingly ceaseless pandemic of COVID-19. The healthcare sector is under a tremendous burden, thus necessitating the prognosis of COVID-19 severity. This in-depth study of plasma proteome alteration provides insights into the host physiological response towards the infection and also reveals the potential prognostic markers of the disease. Using label-free quantitative proteomics, we performed deep plasma proteome analysis in a cohort of 71 patients (20 COVID-19 negative, 18 COVID-19 non-severe, and 33 severe) to understand the disease dynamics. Of the 1200 proteins detected in the patient plasma, 38 proteins were identified to be differentially expressed between non-severe and severe groups. The altered plasma proteome revealed significant dysregulation in the pathways related to peptidase activity, regulated exocytosis, blood coagulation, complement activation, leukocyte activation involved in immune response, and response to glucocorticoid biological processes in severe cases of SARS-CoV-2 infection. Furthermore, we employed supervised machine learning (ML) approaches using a linear support vector machine model to identify the classifiers of patients with non-severe and severe COVID-19. The model used a selected panel of 20 proteins and classified the samples based on the severity with a classification accuracy of 0.84. Putative biomarkers such as angiotensinogen and SERPING1 and ML-derived classifiers including the apolipoprotein B, SERPINA3, and fibrinogen gamma chain were validated by targeted mass spectrometry-based multiple reaction monitoring (MRM) assays. We also employed an in silico screening approach against the identified target proteins for the therapeutic management of COVID-19. We shortlisted two FDA-approved drugs, namely, selinexor and ponatinib, which showed the potential of being repurposed for COVID-19 therapeutics. Overall, this is the first most comprehensive plasma proteome investigation of COVID-19 patients from the Indian population, and provides a set of potential biomarkers for the disease severity progression and targets for therapeutic interventions.

Proteomic investigation reveals dominant alterations of neutrophil degranulation and mRNA translation pathways in patients with COVID-19.

The altered molecular proteins and pathways in response to COVID-19 infection are still unclear. Here, we performed a comprehensive proteomics-based investigation of nasopharyngeal swab samples from patients with COVID-19 to study the host response by employing simple extraction strategies. Few of the host proteins such as interleukin-6, L-lactate dehydrogenase, C-reactive protein, Ferritin, and aspartate aminotransferase were found to be upregulated only in COVID-19-positive patients using targeted multiple reaction monitoring studies. The most important pathways identified by enrichment analysis were neutrophil degranulation, interleukin-12 signaling pathways, and mRNA translation of proteins thus providing the detailed investigation of host response in COVID-19 infection. Thus, we conclude that mass spectrometry-detected host proteins have a potential for disease severity progression; however, suitable validation strategies should be deployed for the clinical translation. Furthermore, the in silico docking of potential drugs with host proteins involved in the interleukin-12 signaling pathway might aid in COVID-19 therapeutic interventions.

Inhibition of the activity of HIV-1 protease through antibody binding and mutations probed by molecular dynamics simulations.

HIV-1 protease is an essential enzyme in the life cycle of the HIV-1 virus. The conformational dynamics of the flap region of the protease is critical for the ligand binding mechanism, as well as for the catalytic activity. The monoclonal antibody F11.2.32 raised against HIV-1 protease inhibits its activity on binding. We have studied the conformational dynamics of protease in its free, inhibitor ritonavir and antibody bound forms using molecular dynamics simulations. We find that upon Ab binding to the epitope region (residues 36-46) of protease, the overall flexibility of the protease is decreased including the flap region and the active site, which is similar to the decrease in flexibility observed by inhibitor binding to the protease. This suggests an allosteric mechanism to inhibit protease activity. Further, the protease mutants G40E and G40R are known to have decreased activity and were also subjected to MD simulations. We find that the loss of flexibility in the mutants is similar to that observed in the protease bound to the Ab/inhibitor. These insights highlight the role played by dynamics in the function of the protease and how control of flexibility through Ab binding and site specific mutations can inhibit protease activity.

Conformational and dynamical basis for cross-reactivity observed between anti HIV-1 protease antibody with protease and an epitope peptide from it.

F11.2.32 is a monoclonal antibody raised against HIV-1 protease and it inhibits protease activity. While the structure of the epitope peptide in complex with the antibody is known, how protease interacts with the antibody is not known. In this study, we model the conformational features of the free and bound epitope peptide and protease-antibody interactions. We find through our simulations, that the free epitope peptide P36-46 samples conformations akin to the bound conformation of the peptide in complex with the Ab, with a ß-turn conformation sampled by the 38LPGR41 sequence highlighting the role of inherent conformational preferences of the peptide. Further, to determine the interactions present between the protease and antibody, we docked the protease in its conformation observed in the crystal structure, onto the antibody and simulated the dynamics of the complex in explicit water. We have identified the key residues involved in hydrogen-bond interactions and salt-bridges in Ag-Ab complex and examined the role of CDR flexibility in binding different conformations of the same epitope sequence in peptide and protein antigens. Thus, our results provide the basis for understanding the cross-reactivity observed between the antibody with protease and the epitope peptide from it.