Selective cytotoxicity of a novel immunotoxin based on pulchellin A chain for cells expressing HIV envelope.

Immunotoxins (ITs), which consist of antibodies conjugated to toxins, have been proposed as a treatment for cancer and chronic infections. To develop and improve the ITs, different toxins such as ricin, have been used, aiming for higher efficacy against target cells. The toxin pulchellin, isolated from the Abrus pulchellus plant, has similar structure and function as ricin. Here we have compared two plant toxins, recombinant A chains from ricin (RAC) and pulchellin (PAC) toxins, for their ability to kill HIV Env-expressing cells. In this study, RAC and PAC were produced in E. coli, and chromatographically purified, then chemically conjugated to two different anti-HIV monoclonal antibodies (MAbs), anti-gp120 MAb 924 or anti-gp41 MAb 7B2. These conjugates were characterized biochemically and immunologically. Cell internalization was studied by flow cytometry and confocal microscopy. Results showed that PAC can function within an effective IT. The ITs demonstrated specific binding against native antigens on persistently HIV-infected cells and recombinant antigens on Env-transfected cells. PAC cytotoxicity appears somewhat less than RAC, the standard for comparison. This is the first report that PAC may have utility for the design and construction of therapeutic ITs, highlighting the potential role for specific cell targeting

Structure of a Novel Shoulder-to-Shoulder p24 Dimer in Complex with the Broad-Spectrum Antibody A10F9 and Its Implication in Capsid Assembly

10.1371/journal.pone.0061314PLoS ONE84

Improved Bevirimat resistance prediction by combination of structural and sequence-based classifiers

<p>Abstract</p> <p>Background</p> <p>Maturation inhibitors such as Bevirimat are a new class of antiretroviral drugs that hamper the cleavage of HIV-1 proteins into their functional active forms. They bind to these preproteins and inhibit their cleavage by the HIV-1 protease, resulting in non-functional virus particles. Nevertheless, there exist mutations in this region leading to resistance against Bevirimat. Highly specific and accurate tools to predict resistance to maturation inhibitors can help to identify patients, who might benefit from the usage of these new drugs.</p> <p>Results</p> <p>We tested several methods to improve Bevirimat resistance prediction in HIV-1. It turned out that combining structural and sequence-based information in classifier ensembles led to accurate and reliable predictions. Moreover, we were able to identify the most crucial regions for Bevirimat resistance computationally, which are in line with experimental results from other studies.</p> <p>Conclusions</p> <p>Our analysis demonstrated the use of machine learning techniques to predict HIV-1 resistance against maturation inhibitors such as Bevirimat. New maturation inhibitors are already under development and might enlarge the arsenal of antiretroviral drugs in the future. Thus, accurate prediction tools are very useful to enable a personalized therapy.</p

Predicting Bevirimat resistance of HIV-1 from genotype

<p>Abstract</p> <p>Background</p> <p>Maturation inhibitors are a new class of antiretroviral drugs. Bevirimat (BVM) was the first substance in this class of inhibitors entering clinical trials. While the inhibitory function of BVM is well established, the molecular mechanisms of action and resistance are not well understood. It is known that mutations in the regions CS p24/p2 and p2 can cause phenotypic resistance to BVM. We have investigated a set of p24/p2 sequences of HIV-1 of known phenotypic resistance to BVM to test whether BVM resistance can be predicted from sequence, and to identify possible molecular mechanisms of BVM resistance in HIV-1.</p> <p>Results</p> <p>We used artificial neural networks and random forests with different descriptors for the prediction of BVM resistance. Random forests with hydrophobicity as descriptor performed best and classified the sequences with an area under the Receiver Operating Characteristics (ROC) curve of 0.93 ± 0.001. For the collected data we find that p2 sequence positions 369 to 376 have the highest impact on resistance, with positions 370 and 372 being particularly important. These findings are in partial agreement with other recent studies. Apart from the complex machine learning models we derived a number of simple rules that predict BVM resistance from sequence with surprising accuracy. According to computational predictions based on the data set used, cleavage sites are usually not shifted by resistance mutations. However, we found that resistance mutations could shorten and weaken the <it>α</it>-helix in p2, which hints at a possible resistance mechanism.</p> <p>Conclusions</p> <p>We found that BVM resistance of HIV-1 can be predicted well from the sequence of the p2 peptide, which may prove useful for personalized therapy if maturation inhibitors reach clinical practice. Results of secondary structure analysis are compatible with a possible route to BVM resistance in which mutations weaken a six-helix bundle discovered in recent experiments, and thus ease Gag cleavage by the retroviral protease.</p

Structural similarity-based predictions of protein interactions between HIV-1 and Homo sapiens

Abstract Background In the course of infection, viruses such as HIV-1 must enter a cell, travel to sites where they can hijack host machinery to transcribe their genes and translate their proteins, assemble, and then leave the cell again, all while evading the host immune system. Thus, successful infection depends on the pathogen's ability to manipulate the biological pathways and processes of the organism it infects. Interactions between HIV-encoded and human proteins provide one means by which HIV-1 can connect into cellular pathways to carry out these survival processes. Results We developed and applied a computational approach to predict interactions between HIV and human proteins based on structural similarity of 9 HIV-1 proteins to human proteins having known interactions. Using functional data from RNAi studies as a filter, we generated over 2000 interaction predictions between HIV proteins and 406 unique human proteins. Additional filtering based on Gene Ontology cellular component annotation reduced the number of predictions to 502 interactions involving 137 human proteins. We find numerous known interactions as well as novel interactions showing significant functional relevance based on supporting Gene Ontology and literature evidence. Conclusions Understanding the interplay between HIV-1 and its human host will help in understanding the viral lifecycle and the ways in which this virus is able to manipulate its host. The results shown here provide a potential set of interactions that are amenable to further experimental manipulation as well as potential targets for therapeutic intervention

Rationally Designed Interfacial Peptides Are Efficient In Vitro Inhibitors of HIV-1 Capsid Assembly with Antiviral Activity

Virus capsid assembly constitutes an attractive target for the development of antiviral therapies; a few experimental inhibitors of this process for HIV-1 and other viruses have been identified by screening compounds or by selection from chemical libraries. As a different, novel approach we have undertaken the rational design of peptides that could act as competitive assembly inhibitors by mimicking capsid structural elements involved in intersubunit interfaces. Several discrete interfaces involved in formation of the mature HIV-1 capsid through polymerization of the capsid protein CA were targeted. We had previously designed a peptide, CAC1, that represents CA helix 9 (a major part of the dimerization interface) and binds the CA C-terminal domain in solution. Here we have mapped the binding site of CAC1, and shown that it substantially overlaps with the CA dimerization interface. We have also rationally modified CAC1 to increase its solubility and CA-binding affinity, and designed four additional peptides that represent CA helical segments involved in other CA interfaces. We found that peptides CAC1, its derivative CAC1M, and H8 (representing CA helix 8) were able to efficiently inhibit the in vitro assembly of the mature HIV-1 capsid. Cocktails of several peptides, including CAC1 or CAC1M plus H8 or CAI (a previously discovered inhibitor of CA polymerization), or CAC1M+H8+CAI, also abolished capsid assembly, even when every peptide was used at lower, sub-inhibitory doses. To provide a preliminary proof that these designed capsid assembly inhibitors could eventually serve as lead compounds for development of anti-HIV-1 agents, they were transported into cultured cells using a cell-penetrating peptide, and tested for antiviral activity. Peptide cocktails that drastically inhibited capsid assembly in vitro were also able to efficiently inhibit HIV-1 infection ex vivo. This study validates a novel, entirely rational approach for the design of capsid assembly interfacial inhibitors that show antiviral activity

The Minimal Autoinhibited Unit of the Guanine Nucleotide Exchange Factor Intersectin

Intersectin-1L is a member of the Dbl homology (DH) domain guanine nucleotide exchange factors (GEF) which control Rho-family GTPase signaling. Intersectin-1L is a GEF that is specific for Cdc42. It plays an important role in endocytosis, and is regulated by several partners including the actin regulator N-WASP. Intact intersectin-1L shows low Cdc42 exchange activity, although the isolated catalytic DH domain shows high activity. This finding suggests that the molecule is autoinhibited. To investigate the mechanism of autoinhibition we have constructed a series of domain deletions. We find that the five SH3 domains of intersectin are important for autoinhibition, with the fifth domain (SH3(E)) being sufficient for the bulk of the autoinhibitory effect. This SH3 domain appears to primarily interact with the DH domain. We have determined the crystal structure of the SH3(E)-DH domain construct, which shows a domain swapped arrangement in which the SH3 from one monomer interacts with the DH domain of the other monomer. Analytical ultracentrifugation and gel filtration, however, show that under biochemical concentrations, the construct is fully monomeric. Thus we propose that the actual autoinhibited structure contains the related intramolecular SH3(E)-DH interaction. We propose a model in which this intramolecular interaction may block or distort the GTPase binding region of the DH domain

Efficient Production of HIV-1 Virus-Like Particles from a Mammalian Expression Vector Requires the N-Terminal Capsid Domain

It is now well accepted that the structural protein Pr55Gag is sufficient by itself to produce HIV-1 virus-like particles (VLPs). This polyprotein precursor contains different domains including matrix, capsid, SP1, nucleocapsid, SP2 and p6. In the present study, we wanted to determine by mutagenesis which region(s) is essential to the production of VLPs when Pr55Gag is inserted in a mammalian expression vector, which allows studying the protein of interest in the absence of other viral proteins. To do so, we first studied a minimal Pr55Gag sequence called Gag min that was used previously. We found that Gag min fails to produce VLPs when expressed in an expression vector instead of within a molecular clone. This failure occurs early in the cell at the assembly of viral proteins. We then generated a series of deletion and substitution mutants, and examined their ability to produce VLPs by combining biochemical and microscopic approaches. We demonstrate that the matrix region is not necessary, but that the efficiency of VLP production depends strongly on the presence of its basic region. Moreover, the presence of the N-terminal domain of capsid is required for VLP production when Gag is expressed alone. These findings, combined with previous observations indicating that HIV-1 Pr55Gag-derived VLPs act as potent stimulators of innate and acquired immunity, make the use of this strategy worth considering for vaccine development

The Rac GTP Exchange Factor TIAM-1 Acts with CDC-42 and the Guidance Receptor UNC-40/DCC in Neuronal Protrusion and Axon Guidance

The mechanisms linking guidance receptors to cytoskeletal dynamics in the growth cone during axon extension remain mysterious. The Rho-family GTPases Rac and CDC-42 are key regulators of growth cone lamellipodia and filopodia formation, yet little is understood about how these molecules interact in growth cone outgrowth or how the activities of these molecules are regulated in distinct contexts. UNC-73/Trio is a well-characterized Rac GTP exchange factor in Caenorhabditis elegans axon pathfinding, yet UNC-73 does not control CED-10/Rac downstream of UNC-6/Netrin in attractive axon guidance. Here we show that C. elegans TIAM-1 is a Rac-specific GEF that links CDC-42 and Rac signaling in lamellipodia and filopodia formation downstream of UNC-40/DCC. We also show that TIAM-1 acts with UNC-40/DCC in axon guidance. Our results indicate that a CDC-42/TIAM-1/Rac GTPase signaling pathway drives lamellipodia and filopodia formation downstream of the UNC-40/DCC guidance receptor, a novel set of interactions between these molecules. Furthermore, we show that TIAM-1 acts with UNC-40/DCC in axon guidance, suggesting that TIAM-1 might regulate growth cone protrusion via Rac GTPases in response to UNC-40/DCC. Our results also suggest that Rac GTPase activity is controlled by different GEFs in distinct axon guidance contexts, explaining how Rac GTPases can specifically control multiple cellular functions