Structure-Based Reverse Vaccinology Failed in the Case of HIV Because it Disregarded Accepted Immunological Theory

Reverse engineering protection: A comprehensive survey of reverse vaccinology-based vaccines targeting viral pathogens

Vaccines have significantly reduced the impact of numerous deadly viral infections. However, there is an increasing need to expedite vaccine development in light of the recurrent pandemics and epidemics. Also, identifying vaccines against certain viruses is challenging due to various factors, notably the inability to culture certain viruses in cell cultures and the wide-ranging diversity of MHC profiles in humans. Fortunately, reverse vaccinology (RV) efficiently overcomes these limitations and has simplified the identification of epitopes from antigenic proteins across the entire proteome, streamlining the vaccine development process. Furthermore, it enables the creation of multiepitope vaccines that can effectively account for the variations in MHC profiles within the human population. The RV approach offers numerous advantages in developing precise and effective vaccines against viral pathogens, including extensive proteome coverage, accurate epitope identification, cross-protection capabilities, and MHC compatibility. With the introduction of RV, there is a growing emphasis among researchers on creating multiepitope-based vaccines aiming to stimulate the host's immune responses against multiple serotypes, as opposed to single-component monovalent alternatives. Regardless of how promising the RV-based vaccine candidates may appear, they must undergo experimental validation to probe their protection efficacy for real-world applications. The time, effort, and resources allocated to the laborious epitope identification process can now be redirected toward validating vaccine candidates identified through the RV approach. However, to overcome failures in the RV-based approach, efforts must be made to incorporate immunological principles and consider targeting the epitope regions involved in disease pathogenesis, immune responses, and neutralizing antibody maturation. Integrating multi-omics and incorporating artificial intelligence and machine learning-based tools and techniques in RV would increase the chances of developing an effective vaccine. This review thoroughly explains the RV approach, ideal RV-based vaccine construct components, RV-based vaccines designed to combat viral pathogens, its challenges, and future perspectives.

Computational identification of antibody-binding epitopes from mimotope datasets

Introduction: A fundamental challenge in computational vaccinology is that most B-cell epitopes are conformational and therefore hard to predict from sequence alone. Another significant challenge is that a great deal of the amino acid sequence of a viral surface protein might not in fact be antigenic. Thus, identifying the regions of a protein that are most promising for vaccine design based on the degree of surface exposure may not lead to a clinically relevant immune response. Methods: Linear peptides selected by phage display experiments that have high affinity to the monoclonal antibody of interest ("mimotopes") usually have similar physicochemical properties to the antigen epitope corresponding to that antibody. The sequences of these linear peptides can be used to find possible epitopes on the surface of the antigen structure or a homology model of the antigen in the absence of an antigen-antibody complex structure. Results and Discussion: Herein we describe two novel methods for mapping mimotopes to epitopes. The first is a novel algorithm named MimoTree that allows for gaps in the mimotopes and epitopes on the antigen. More specifically, a mimotope may have a gap that does not match to the epitope to allow it to adopt a conformation relevant for binding to an antibody, and residues may similarly be discontinuous in conformational epitopes. MimoTree is a fully automated epitope detection algorithm suitable for the identification of conformational as well as linear epitopes. The second is an ensemble approach, which combines the prediction results from MimoTree and two existing methods.

Quantum vaccinomics platforms to advance in vaccinology

The opinion flows from Introduction to the immunological quantum that requires a historical perspective, to Quantum vaccine algorithms supported by a bibliometric analysis, to Quantum vaccinomics describing from our perspective the different vaccinomics and quantum vaccinomics algorithms. Finally, in the Discussion and conclusions we propose novel platforms and algorithms developed to further advance on quantum vaccinomics. In the paper we refer to protective epitopes or immunological quantum for the design of candidate vaccine antigens, which may elicit a protective response through both cellular and antibody mediated mechanisms of the host immune system. Vaccines are key interventions for the prevention and control of infectious diseases affecting humans and animals worldwide. Biophysics led to quantum biology and quantum immunology reflecting quantum dynamics within living systems and their evolution. In analogy to quantum of light, immune protective epitopes were proposed as the immunological quantum. Multiple quantum vaccine algorithms were developed based on omics and other technologies. Quantum vaccinomics is the methodological approach with different platforms used for the identification and combination of immunological quantum for vaccine development. Current quantum vaccinomics platforms include in vitro, in music and in silico algorithms and top trends in biotechnology for the identification, characterization and combination of candidate protective epitopes. These platforms have been applied to different infectious diseases and in the future should target prevalent and emerging infectious diseases with novel algorithms.

A comprehensive insight on the challenges for COVID-19 vaccine: A lesson learnt from other viral vaccines

The aim of this study is to comprehensively analyze previous viral vaccine programs and identify potential challenges and effective measures for the COVID-19 vaccine program. Previous viral vaccine programs, such as those for HIV, Zika, Influenza, Ebola, Dengue, SARS, and MERS, were evaluated. Paramount challenges were identified, including quasi-species, cross-reactivity, duration of immunity, revaccination, mutation, immunosenescence, and adverse events related to viral vaccines. Although a large population has been vaccinated, mutations in SARS-CoV-2 and adverse events related to vaccines pose significant challenges. Previous vaccine programs have taught us that predicting the final outcome of the current vaccine program for COVID-19 cannot be determined at a given state. Long-term follow-up studies are essential. Validated preclinical studies, long-term follow-up studies, alternative therapeutic approaches, and alternative vaccines are necessary.

Design peptide and multi-epitope protein vaccine candidates against monkeypox virus using reverse vaccinology approach: an in-silico study

Monkeypox is a zoonotic virus that has recently affected different countries worldwide. On July 23, 2022, the WHO declared the outbreak of monkeypox as a public health emergency of international concern. Surveillance studies conducted in Central Africa in the 1980s and later during outbreaks in the same region showed smallpox vaccines to be clinically somewhat effective against Monkeypox virus. However, there is no specific vaccine against this virus. This research used bioinformatics techniques to establish a novel multi-epitope vaccine candidate against Monkeypox that can induce a strong immune response. Five well-known antigenic proteins (E8L, A30L, A35R, A29L, and B21R) of the virus were picked and assessed as possible immunogenic peptides. Two suitable peptide candidates were selected according to bio-informatics analysis. Based upon in silico evaluation, two multi-epitope vaccine candidates (ALALAR and ALAL) were built with rich-epitope domains consisting of high-ranking T and B-cell epitopes. After predicting and evaluating the 3D structure of the protein candidates, the most efficient 3D models were considered for docking studies with Toll-like receptor 4 (TLR4) and the HLA-A * 11:01, HLA-A*01:01, HLA-A*02:01, HLA-A*03:01, HLA-A*07:02, HLA-A*15:01, HLA-A*30:01 receptors. Subsequently, molecular dynamics (MD) simulation of up to 150 nanoseconds was employed to assess the durability of the interaction of the vaccine candidates with immune receptors. MD studies showed that M5-HLA-A*11:01, ALAL-TLR4, and ALALAR-TLR4 complexes were stable during simulation. Analysis of the in silico outcomes indicates that the M5 peptide and ALAL and ALALAR proteins may be suitable vaccine candidates against the Monkeypox virus.Communicated by Ramaswamy H. Sarma.

Multi-Cellular Immunological Interactions Associated With COVID-19 Infections

To rapidly prognosticate and generate hypotheses on pathogenesis, leukocyte multi-cellularity was evaluated in SARS-CoV-2 infected patients treated in India or the United States (152 individuals, 384 temporal observations). Within hospital (<90-day) death or discharge were retrospectively predicted based on the admission complete blood cell counts (CBC). Two methods were applied: (i) a "reductionist" one, which analyzes each cell type separately, and (ii) a "non-reductionist" method, which estimates multi-cellularity. The second approach uses a proprietary software package that detects distinct data patterns generated by complex and hypothetical indicators and reveals each data pattern's immunological content and associated outcome(s). In the Indian population, the analysis of isolated cell types did not separate survivors from non-survivors. In contrast, multi-cellular data patterns differentiated six groups of patients, including, in two groups, 95.5% of all survivors. Some data structures revealed one data point-wide line of observations, which informed at a personalized level and identified 97.8% of all non-survivors. Discovery was also fostered: some non-survivors were characterized by low monocyte/lymphocyte ratio levels. When both populations were analyzed with the non-reductionist method, they displayed results that suggested survivors and non-survivors differed immunologically as early as hospitalization day 1.

Antisense Peptide Technology for Diagnostic Tests and Bioengineering Research

Antisense peptide technology (APT) is based on a useful heuristic algorithm for rational peptide design. It was deduced from empirical observations that peptides consisting of complementary (sense and antisense) amino acids interact with higher probability and affinity than the randomly selected ones. This phenomenon is closely related to the structure of the standard genetic code table, and at the same time, is unrelated to the direction of its codon sequence translation. The concept of complementary peptide interaction is discussed, and its possible applications to diagnostic tests and bioengineering research are summarized. Problems and difficulties that may arise using APT are discussed, and possible solutions are proposed. The methodology was tested on the example of SARS-CoV-2. It is shown that the CABS-dock server accurately predicts the binding of antisense peptides to the SARS-CoV-2 receptor binding domain without requiring predefinition of the binding site. It is concluded that the benefits of APT outweigh the costs of random peptide screening and could lead to considerable savings in time and resources, especially if combined with other computational and immunochemical methods.

Design in biology and rational design in vaccinology: A conceptual analysis

This review discusses the philosophical foundations of what used to be called "the scientific method" and is nowadays often known as the scientific attitude. It used to be believed that scientific theories and methods aimed at the truth especially in the case of physics, chemistry and astronomy because these sciences were able to develop numerous scientific laws that made it possible to understand and predict many physical phenomena. The situation is different in the case of the biological sciences which deal with highly complex living organisms made up of huge numbers of constituents that undergo continuous dynamic processes; this leads to novel emergent properties in organisms that cannot be predicted because they are not present in the constituents before they have interacted with each other. This is one of the reasons why there are no universal scientific laws in biology. Furthermore, all scientific theories can only achieve a restricted level of predictive success because they remain valid only under the limited range of conditions that were used for establishing the theory' in the first place. Many theories that used to be accepted were subsequently shown to be false, demonstrating that scientific theories always remain tentative and can never be proven beyond and doubt. It is ironical that as scientists have finally accepted that approximate truths are perfectly adequate and that absolute truth is an illusion, a new irrational sociological phenomenon called Post-Truth conveyed by social media, the Internet and fake news has developed in the Western world that is convincing millions of people that truth simply does not exist. Misleading information is circulated with the intention to deceive and science denialism is promoted by denying the remarkable achievements of science and technology during the last centuries. Although the concept of intentional design is widely used to describe the methods that biologists use to make discoveries and inventions, it will be argued that the term is not appropriate for explaining the appearance of life on our planet nor for describing the scientific creativity of scientific investigators. The term rational for describing the development of new vaccines is also unjustified. Because the analysis of the COVID-19 pandemic requires contributions from biomedical and psycho-socioeconomic sciences, one scientific method alone would be insufficient for combatting the pandemic.

The Relevance of Bioinformatics Applications in the Discovery of Vaccine Candidates and Potential Drugs for COVID-19 Treatment

The application of bioinformatics to vaccine research and drug discovery has never been so essential in the fight against infectious diseases. The greatest combat of the 21st century against a debilitating disease agent SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) virus discovered in Wuhan, China, December 2019, has piqued an unprecedented usage of bioinformatics tools in deciphering the molecular characterizations of infectious pathogens. With the viral genome data of SARS-COV-2 been made available barely weeks after the reported outbreak, bioinformatics platforms have become an all-time critical tool to gain time in the fight against the disease pandemic. Before the outbreak, different platforms have been developed to explore antigenic epitopes, predict peptide-protein docking and antibody structures, and simulate antigen-antibody reactions and lots more. However, the advent of the pandemic witnessed an upsurge in the application of these pipelines with the development of newer ones such as the Coronavirus Explorer in the development of efficacious vaccines, drug repurposing, and/or discovery. In this review, we have explored the various pipelines available for use, their relevance, and limitations in the timely development of useful therapeutic candidates from genomic data knowledge to clinical therapy.

The vaccinologist's "dirty little secret": a better understanding of structure-function relationships of viral immunogens might advance rational HIV vaccine design

I will offer a conceptual analysis of different notions of structure and function of viral immunogens and of different structure-function relationships. My focus will then be on the mechanisms by which the desired immune response is induced and why strategies based on three-dimensional molecular antigen structures and their rational design are limited in their ability to induce the desired immunogenicity. I will look at the mechanisms of action of adjuvants (thus the wordplay with Janeway’s “immunologist’s dirty little secret”). Strategies involving adjuvants and other (more successful) vaccination strategies rely on taking into account activities and functions (“what is going on”), and not just the structures involved (“who is there”), in binding in a “lock and key” fashion. Functional patterns as well as other organizational and temporal patterns, I will argue, are crucial for inducing the desired immune response and immunogenicity. The 3D structural approach by itself has its benefits – and its limits, which I want to highlight by this philosophical analysis, pointing out the importance of structure-function relationships. Different functional aspects such as antigenicity, immunogenicity, and immunity need to be kept separate and cannot be reduced to three-dimensional structures of vaccines. Taking into account different notions of structure and function and their relationships might thus advance our understanding of the immune system and rational HIV vaccine design, to which end philosophy can provide useful tools.

Mobility and disorder in antibody and antigen binding sites do not prevent immunochemical recognition

The known polyspecificity of antibodies, which is crucial for efficient immune response, is determined by the conformational flexibility and intrinsic disorder encoded in local peculiarities of the amino acid sequence of antibodies within or in the vicinity of their complementarity determining regions. Similarly, epitopes represent fuzzy binding sites, which are also characterized by local structural flexibility. Existing data suggest that the efficient interactions between antigens and antibodies rely on the conformational mobility and some disorder of their binding sites and therefore can be relatively well described by the "flexible lock - adjustable key" model, whereas both, extreme order (rigid lock-and-key) and extreme disorder (viral shape-shifters) are not compatible with the efficient antigen-antibody interactions and are not present in immune interactions.

Design and Characterization of a Novel Tool for the Antigenic Enrichment of Actinobacillus pleuropneumoniae Outer Membrane

Production and isolation of recombinant proteins are costly and work-intensive processes, especially in immunology when tens or hundreds of potential immunogens need to be purified for testing. Here we propose an alternative method for fast screening of immunogen candidates, based on genetic engineering of recombinant bacterial strains able to express and expose selected antigens on their outer membrane. In Actinobacillus pleuropneumoniae, a Gram-negative porcine pathogen responsible for extensive economic losses worldwide, we identified a conserved general secretion pathway (GSP) domain in the N-terminal part of the outer membrane protein ApfA (ApfA stem: ApfAs). ApfAs was used as an outer membrane anchor, to which potential immunogens can be attached. To enable confirmation of correct positioning, ApfAs, was cloned in combination with the modified acyl carrier protein (ACP) fluorescent tag ACP mini (ACPm) and the putative immunogen VacJ. The chimeric construct was inserted in the pMK-express vector, subsequently transformed into A. pleuropneumoniae for expression. Flow cytometry, fluorescence imaging and mass spectrometry analysis were employed to demonstrate that the outer membrane of the transformed strain was enriched with the chimeric ApfAs-ACPm-VacJ antigen. Our results confirmed correct positioning of the chimeric ApfAs-ACPm-VacJ antigen and supported this system's potential as platform technology enabling antigenic enrichment of the outer membrane of A. pleuropneumoniae.

Not by structures alone: Can the immune system recognize microbial functions?

A central question for immunology is: what does the immune system recognize and according to which principles does this kind of recognition work? Immunology has been dominated by the idea of recognizing molecular structures and triggering an appropriate immune response when facing non-self or danger. Recently, characterizations in terms of function have turned out to be more conserved and explanatory in microbiota research than taxonomic composition for understanding microbiota-host interactions. Starting from a conceptual analysis of the notions of structure and function, I raise the title question whether it is possible for the immune system to recognize microbial functions. I argue that this is indeed the case, making the claim that some function-associated molecular patterns are not indicative of the presence of certain taxa (''who is there'') but of biochemical activities and effects (''what is going on''). In addition, I discuss case studies which show that there are immunological sensors that can directly detect microbial activities, irrespective of their specific structural manifestation. At the same time, the discussed account puts the causal role notions of function on a more realist and objective basis.

What does it mean to develop an HIV vaccine by rational design?

This review argues that the three popular concepts of design, rationality and reductionism, which guided vaccine research for many years, actually contributed to the inability of vaccinologists to develop an effective HIV vaccine. The strong goal-directed intentionality inherent in the concept of design together with excessive confidence in the power of rational thinking convinced investigators that the accumulated structural knowledge on HIV epitopes, derived from crystallographic studies of complexes of neutralizing antibodies bound to HIV Env epitopes, would allow them to rationally design complementary immunogens capable of inducing anti-HIV protective antibodies. This strategy failed because it was not appreciated that the structures observed in epitope-paratope crystallographic complexes result from mutually induced fit between the two partners and do not represent structures present in the free disordered molecules before they had interacted. In addition, reductionist thinking led investigators to accept that biology could be reduced to chemistry, and this made them neglect the fundamental difference between chemical antigenicity and biological immunogenicity. As a result, they did not investigate which inherent constituents of immune systems controlled the induction of protective antibodies and focused instead only on the steric complementarity that exists between bound epitopes and paratopes.

Nanosystems Applied to HIV Infection: Prevention and Treatments

Sexually-transmitted infections (STIs) are a global health concern worldwide as they cause acute diseases, infertility, and significant mortality. Among the bacterial, viral, and parasitic pathogens that can be sexually transmitted, human immunodeficiency virus (HIV) has caused one of the most important pandemic diseases, which is acquired immune deficiency syndrome (AIDS). 32.7 million people have died from AIDS-related illnesses since the start of the epidemic. Moreover, in 2019, 38 million people were living with HIV worldwide. The need to deal with this viral infection becomes more obvious, because it represents not only a problem for public health, but also a substantial economic problem. In this context, it is necessary to focus efforts on developing methods for prevention, detection and treatment of HIV infections that significantly reduce the number of newly infected people and provide a better quality of life for patients. For several decades, biomedical research has been developed allowing quick solutions through the contribution of effective tools. One of them is the use of polymers as vehicles, drug carrier agents, or as macromolecular prodrugs. Moreover, nanosystems (NSs) play an especially important role in the diagnosis, prevention, and therapy against HIV infection. The purpose of this work is to review recent research into diverse NSs as potential candidates for prevention and treatment of HIV infection. Firstly, this review highlights the advantages of using nanosized structures for these medical applications. Furthermore, we provide an overview of different types of NSs used for preventing or combating HIV infection. Then, we briefly evaluate the most recent developments associated with prevention and treatment alternatives. Additionally, the implications of using different NSs are also addressed.

Using Omics Technologies and Systems Biology to Identify Epitope Targets for the Development of Monoclonal Antibodies Against Antibiotic-Resistant Bacteria

Over the past few decades, antimicrobial resistance has emerged as an important threat to public health due to the global dissemination of multidrug-resistant strains from several bacterial species. This worrisome trend, in addition to the paucity of new antibiotics with novel mechanisms of action in the development pipeline, warrants the development of non-antimicrobial approaches to combating infection caused by these isolates. Monoclonal antibodies (mAbs) have emerged as highly effective molecules for the treatment of multiple diseases. However, in spite of the fact that antibodies play an important role in protective immunity against bacteria, only three mAb therapies have been approved for clinical use in the treatment of bacterial infections. In the present review, we briefly outline the therapeutic potential of mAbs in the treatment of bacterial diseases and discuss how their development can be facilitated when assisted by “omics” technologies and interpreted under a systems biology paradigm. Specifically, methods employing large genomic, transcriptomic, structural, and proteomic datasets allow for the rational identification of epitopes. Ideally, these include those that are present in the majority of circulating isolates, highly conserved at the amino acid level, surface-exposed, located on antigens essential for virulence, and expressed during critical stages of infection. Therefore, these knowledge-based approaches can contribute to the identification of high-value epitopes for the development of effective mAbs against challenging bacterial clones.

Computational Approaches and Challenges to Developing Universal Influenza Vaccines

The traditional design of effective vaccines for rapidly-evolving pathogens, such as influenza A virus, has failed to provide broad spectrum and long-lasting protection. With low cost whole genome sequencing technology and powerful computing capabilities, novel computational approaches have demonstrated the potential to facilitate the design of a universal influenza vaccine. However, few studies have integrated computational optimization in the design and discovery of new vaccines. Understanding the potential of computational vaccine design is necessary before these approaches can be implemented on a broad scale. This review summarizes some promising computational approaches under current development, including computationally optimized broadly reactive antigens with consensus sequences, phylogenetic model-based ancestral sequence reconstruction, and immunomics to compute conserved cross-reactive T-cell epitopes. Interactions between virus-host-environment determine the evolvability of the influenza population. We propose that with the development of novel technologies that allow the integration of data sources such as protein structural modeling, host antibody repertoire analysis and advanced phylodynamic modeling, computational approaches will be crucial for the development of a long-lasting universal influenza vaccine. Taken together, computational approaches are powerful and promising tools for the development of a universal influenza vaccine with durable and broad protection.

Structural Vaccinology for Viral Vaccine Design

Although vaccines have proven pivotal against arrays of infectious viral diseases, there are still no effective vaccines against many viruses. New structural insights into the viral envelope, protein conformation, and antigenic epitopes can guide the design of novel vaccines against challenging viruses such as human immunodeficiency virus (HIV), hepatitis C virus, enterovirus A71, and dengue virus. Recent studies demonstrated that applications of this structural information can solve some of the vaccine conundrums. This review focuses on recent advances in structure-based vaccine design, or structural vaccinology, for novel and innovative viral vaccine design.

The Hard Way towards an Antibody-Based HIV-1 Env Vaccine: Lessons from Other Viruses

Although effective antibody-based vaccines have been developed against multiple viruses, such approaches have so far failed for the human immunodeficiency virus type 1 (HIV-1). Despite the success of anti-retroviral therapy (ART) that has turned HIV-1 infection into a chronic disease and has reduced the number of new infections worldwide, a vaccine against HIV-1 is still urgently needed. We discuss here the major reasons for the failure of “classical” vaccine approaches, which are mostly due to the biological properties of the virus itself. HIV-1 has developed multiple mechanisms of immune escape, which also account for vaccine failure. So far, no vaccine candidate has been able to induce broadly neutralizing antibodies (bnAbs) against primary patient viruses from different clades. However, such antibodies were identified in a subset of patients during chronic infection and were shown to protect from infection in animal models and to reduce viremia in first clinical trials. Their detailed characterization has guided structure-based reverse vaccinology approaches to design better HIV-1 envelope (Env) immunogens. Furthermore, conserved Env epitopes have been identified, which are promising candidates in view of clinical applications. Together with new vector-based technologies, considerable progress has been achieved in recent years towards the development of an effective antibody-based HIV-1 vaccine.

Fundamental challenges to the development of a preventive HIV vaccine

There is consensus that only a preventive vaccine can contain the HIV/AIDS pandemic. After 30 years still there is no preventive HIV vaccine. This article examines fundamental challenges to the development of a preventive HIV vaccine. They include the initially erroneous but powerful perception of the natural history of HIV disease, as an acute rather than a chronic illness even in the absence of therapy, the lack of appreciation of the quasispecies biology of HIV and the abandonment of principles of immunology theory caused by the allure of technological prowess. In addition two other important aspects are discussed: vaccines directed against transmitted/founder viruses (T/F) and the reconsideration of HIV inactivation as a viable means to obtain a preventive HIV vaccine using novel safe methods of inactivation not available during the early years of the pandemic.

Development of a Preventive HIV Vaccine Requires Solving Inverse Problems Which Is Unattainable by Rational Vaccine Design

Hypotheses and theories are essential constituents of the scientific method. Many vaccinologists are unaware that the problems they try to solve are mostly inverse problems that consist in imagining what could bring about a desired outcome. An inverse problem starts with the result and tries to guess what are the multiple causes that could have produced it. Compared to the usual direct scientific problems that start with the causes and derive or calculate the results using deductive reasoning and known mechanisms, solving an inverse problem uses a less reliable inductive approach and requires the development of a theoretical model that may have different solutions or none at all. Unsuccessful attempts to solve inverse problems in HIV vaccinology by reductionist methods, systems biology and structure-based reverse vaccinology are described. The popular strategy known as rational vaccine design is unable to solve the multiple inverse problems faced by HIV vaccine developers. The term “rational” is derived from “rational drug design” which uses the 3D structure of a biological target for designing molecules that will selectively bind to it and inhibit its biological activity. In vaccine design, however, the word “rational” simply means that the investigator is concentrating on parts of the system for which molecular information is available. The economist and Nobel laureate Herbert Simon introduced the concept of “bounded rationality” to explain why the complexity of the world economic system makes it impossible, for instance, to predict an event like the financial crash of 2007–2008. Humans always operate under unavoidable constraints such as insufficient information, a limited capacity to process huge amounts of data and a limited amount of time available to reach a decision. Such limitations always prevent us from achieving the complete understanding and optimization of a complex system that would be needed to achieve a truly rational design process. This is why the complexity of the human immune system prevents us from rationally designing an HIV vaccine by solving inverse problems.

Nature and Consequences of Biological Reductionism for the Immunological Study of Infectious Diseases

Evolution has conserved "economic" systems that perform many functions, faster or better, with less. For example, three to five leukocyte types protect from thousands of pathogens. To achieve so much with so little, biological systems combine their limited elements, creating complex structures. Yet, the prevalent research paradigm is reductionist. Focusing on infectious diseases, reductionist and non-reductionist views are here described. The literature indicates that reductionism is associated with information loss and errors, while non-reductionist operations can extract more information from the same data. When designed to capture one-to-many/many-to-one interactions-including the use of arrows that connect pairs of consecutive observations-non-reductionist (spatial-temporal) constructs eliminate data variability from all dimensions, except along one line, while arrows describe the directionality of temporal changes that occur along the line. To validate the patterns detected by non-reductionist operations, reductionist procedures are needed. Integrated (non-reductionist and reductionist) methods can (i) distinguish data subsets that differ immunologically and statistically; (ii) differentiate false-negative from -positive errors; (iii) discriminate disease stages; (iv) capture in vivo, multilevel interactions that consider the patient, the microbe, and antibiotic-mediated responses; and (v) assess dynamics. Integrated methods provide repeatable and biologically interpretable information.

Current views on the potential for development of a HIV vaccine

INTRODUCTION

Despite many recent advances in the HIV prevention landscape, an effective vaccine remains the most promising tool to end the HIV-1 pandemic. Areas covered: This review summarizes past HIV vaccine efficacy trials and current vaccine strategies as well as new approaches about to move into first-in-human trials. Expert opinion: Despite many setbacks in early HIV vaccine efficacy trials, the success of RV144 has provided the glimmer of hope necessary to invigorate the vaccine field, and has led to the development of a large number of vaccine strategies aiming at inducing an array of different immune responses. The follow-up pox-protein trials, developed to replicate and enhance the polyfunctional antibody responses induced by the RV144 regimen, are already reaching efficacy trials, while a large body of work providing a more complete understanding of the development of broadly neutralizing antibodies is now being translated into immunogen design using several different strategies. T-cell based vaccines, fallen out of favor after Ad5-based trials showed increased infection rates in Ad5 seropositive vaccine recipients, are experiencing a comeback based in part on the promising results from non-human primate challenge studies using rhCMV-based immunogens. This diverse array of vaccine candidates may finally allow us to identify a broadly effective HIV vaccine able to contain the epidemic.