Surfactant protein D inhibits HIV-1 infection of target cells via interference with gp120-CD4 interaction and modulates pro-inflammatory cytokine production

© 2014 Pandit et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Surfactant Protein SP-D, a member of the collectin family, is a pattern recognition protein, secreted by mucosal epithelial cells and has an important role in innate immunity against various pathogens. In this study, we confirm that native human SP-D and a recombinant fragment of human SP-D (rhSP-D) bind to gp120 of HIV-1 and significantly inhibit viral replication in vitro in a calcium and dose-dependent manner. We show, for the first time, that SP-D and rhSP-D act as potent inhibitors of HIV-1 entry in to target cells and block the interaction between CD4 and gp120 in a dose-dependent manner. The rhSP-D-mediated inhibition of viral replication was examined using three clinical isolates of HIV-1 and three target cells: Jurkat T cells, U937 monocytic cells and PBMCs. HIV-1 induced cytokine storm in the three target cells was significantly suppressed by rhSP-D. Phosphorylation of key kinases p38, Erk1/2 and AKT, which contribute to HIV-1 induced immune activation, was significantly reduced in vitro in the presence of rhSP-D. Notably, anti-HIV-1 activity of rhSP-D was retained in the presence of biological fluids such as cervico-vaginal lavage and seminal plasma. Our study illustrates the multi-faceted role of human SPD against HIV-1 and potential of rhSP-D for immunotherapy to inhibit viral entry and immune activation in acute HIV infection. © 2014 Pandit et al.The work (Project no. 2011-16850) was supported by Medical Innovation Fund of Indian Council of Medical Research, New Delhi, India (www.icmr.nic.in/)

Prediction of peptide and protein propensity for amyloid formation

Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo structural changes, which lead to amyloid formation, are quite diverse and share no obvious sequence or structural homology, despite the structural similarity found in the fibrils. To address these issues, a novel approach based on recursive feature selection and feed-forward neural networks was undertaken to identify key features highly correlated with the self-assembly problem. This approach allowed the identification of seven physicochemical and biochemical properties of the amino acids highly associated with the self-assembly of peptides and proteins into amyloid-like fibrils (normalized frequency of β-sheet, normalized frequency of β-sheet from LG, weights for β-sheet at the window position of 1, isoelectric point, atom-based hydrophobic moment, helix termination parameter at position j+1 and ΔGº values for peptides extrapolated in 0 M urea). Moreover, these features enabled the development of a new predictor (available at http://cran.r-project.org/web/packages/appnn/index.html) capable of accurately and reliably predicting the amyloidogenic propensity from the polypeptide sequence alone with a prediction accuracy of 84.9 % against an external validation dataset of sequences with experimental in vitro, evidence of amyloid formation

A recombinant fragment of Human surfactant protein D binds Spike protein and inhibits infectivity and replication of SARS-CoV-2 in clinical samples

COVID -19 is an acute infectious disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Human surfactant protein D (SP-D) is known to interact with spike protein of SARS-CoV, but its immune-surveillance against SARS-CoV-2 is not known. The study aimed to examine the potential of a recombinant fragment of human SP-D (rfhSP-D) as an inhibitor of replication and infection of SARS-CoV-2. The interaction of rfhSP-D with spike protein of SARS-CoV-2 and hACE-2 receptor was predicted via docking analysis. The inhibition of interaction between spike protein and ACE-2 by rfhSP-D was confirmed using direct and indirect ELISA. The effect of rfhSP-D on replication and infectivity of SARS-CoV-2 from clinical samples was studied by measuring the expression of RdRp gene of the virus using qPCR. In-silico interaction studies indicated that three amino acid residues in the RBD of spike of SARS-CoV-2 were commonly involved in interacting with rfhSP-D and ACE-2. Studies using clinical samples of SARS-CoV-2 positive cases (asymptomatic, n=7 and symptomatic, n=8 and negative controls n=15) demonstrated that treatment with 1.67 µM rfhSP-D inhibited viral replication by ~5.5 fold and was more efficient than Remdesivir (100 µM). Approximately, a 2-fold reduction in viral infectivity was also observed after treatment with 1.67 µM rfhSP-D. These results conclusively demonstrate that the calcium independent rfhSP-D mediated inhibition of binding between the receptor binding domain of the S1 subunit of the SARS-CoV-2 spike protein and human ACE-2, its host cell receptor, and a significant reduction in SARS-CoV-2 infection and replication in-vitro

Understanding the relationship between the primary structure of proteins and their amyloidogenic propensity: clues from inclusion body formation

Amyloid formation is dependent to a considerable extent on the amino acid sequence of the protein. The present study delineates certain sequence-dependent features that are correlated with amyloidogenic propensity. The analyses indicate that amyloid formation is favored by lower thermostability and increased half-life of the protein. There seems to be a certain degree of bias in the composition of order-promoting amino acids in the case of amyloidogenic proteins. Based on these parameters, a prediction function for the amyloidogenic propensity of proteins has been created. The prediction function has been found to rationalize the reported effect of certain mutations on amyloid formation. It seems that a higher sheet propensity of residues that constitute the first seven residues of a helical structure in a protein might increase the propensity for a helix to sheet transition in that region under denaturing conditions

Protein aggregation: a perspective from amyloid and inclusion-body formation

Over the past few decades, an overwhelmingly vast amount of research has been dedicated to understanding protein aggregation. This review summarizes the current understanding of protein aggregation from the viewpoint of its two important manifestations: formation of amyloid fibrils and inclusion bodies. The article summarizes the structure, mechanism of formation, predisposing factors and measures of overcoming inclusion body and amyloid formation. The protective role played by molecular evolution in curbing aggregation and results from recent studies on the prediction of aggregation rates based on primary structure have also been discussed

A support vector machine-based method for predicting the propensity of a protein to be soluble or to form inclusion body on overexpression in Escherichia coli

Motivation: Inclusion body formation has been a major deterrent for overexpression studies since a large number of proteins form insoluble inclusion bodies when overexpressed in Escherichia coli. The formation of inclusion bodies is known to be an outcome of improper protein folding; thus the composition and arrangement of amino acids in the proteins would be a major influencing factor in deciding its aggregation propensity. There is a significant need for a prediction algorithm that would enable the rational identification of both mutants and also the ideal protein candidates for mutations that would confer higher solubility-on-overexpression instead of the presently used trial-and-error procedures. Results: Six physicochemical properties together with residue and dipeptide-compositions have been used to develop a support vector machine-based classifier to predict the overexpression status in E.coli. The prediction accuracy is similar to 72% suggesting that it performs reasonably well in predicting the propensity of a protein to be soluble or to form inclusion bodies. The algorithm could also correctly predict the change in solubility for most of the point mutations reported in literature. This algorithm can be a useful tool in screening protein libraries to identify soluble variants of proteins

Discovery of small molecule binders of human FSHR(TMD) with novel structural scaffolds by integrating structural bioinformatics and machine learning algorithms

Background: The activation of follicle stimulating hormone receptor (FSHR) by FSH and the consequent downstream signaling activities are crucial for reproductive health. The role of FSHR in tumor progression as well as osteoporosis advancement has also been well established. Currently, steroid preparations of estrogen and progesterone are being used for managing fertility, in spite of the harmful side effects, as there has not been much success in identification of effective FSHR modulators. Structure-based drug design initiatives for identification of potent and specific FSHR modulators have been impeded due to the non-availability of the complete crystal structure of hFSHR complexed with FSH. Methods: In this study, we have modeled the 3D structure of transmembrane domain (TMD) of hFSHR and identified molecules that demonstrate good binding affinity by virtual screening of drug-like library of compounds. The 3D structural and pharmacophoric features of the binders and non-binders obtained from virtual screening were further used to develop Support Vector Machine based classifier for TMD binding. Based on the observations from docking and SVM classification, a small molecule was identified for extensive MD simulations and in vitro assays for FSHR modulatory activity. Results: The molecule selected based on docking score and SVM prediction was found to inhibit FSH-induced cAMP activity by 80% at 300 \u3bcM concentration. Conclusion: The study proposes 1,3-diphenyl-1H-pyrazole-5-carboxylate as a promising scaffold for the design of new and potent FSHR allosteric inhibitors