Computational vaccinology and the ICoVax 2012 workshop

Abstract Computational vaccinology or vaccine informatics is an interdisciplinary field that addresses scientific and clinical questions in vaccinology using computational and informatics approaches. Computational vaccinology overlaps with many other fields such as immunoinformatics, reverse vaccinology, postlicensure vaccine research, vaccinomics, literature mining, and systems vaccinology. The second ISV Pre-conference Computational Vaccinology Workshop (ICoVax 2012) was held on October 13, 2013 in Shanghai, China. A number of topics were presented in the workshop, including allergen predictions, prediction of linear T cell epitopes and functional conformational epitopes, prediction of protein-ligand binding regions, vaccine design using reverse vaccinology, and case studies in computational vaccinology. Although a significant progress has been made to date, a number of challenges still exist in the field. This Editorial provides a list of major challenges for the future of computational vaccinology and identifies developing themes that will expand and evolve over the next few years.http://deepblue.lib.umich.edu/bitstream/2027.42/112516/1/12859_2013_Article_5721.pd

Computational Vaccinology and the ICoVax 2012 Workshop

Computational vaccinology or vaccine informatics is an interdisciplinary field that addresses scientific and clinical questions in vaccinology using computational and informatics approaches. Computational vaccinology overlaps with many other fields such as immunoinformatics, reverse vaccinology, postlicensure vaccine research, vaccinomics, literature mining, and systems vaccinology. The second ISV Pre-conference Computational Vaccinology Workshop (ICoVax 2012) was held on October 13, 2013 in Shanghai, China. A number of topics were presented in the workshop, including allergen predictions, prediction of linear T cell epitopes and functional conformational epitopes, prediction of protein-ligand binding regions, vaccine design using reverse vaccinology, and case studies in computational vaccinology. Although a significant progress has been made to date, a number of challenges still exist in the field. This Editorial provides a list of major challenges for the future of computational vaccinology and identifies developing themes that will expand and evolve over the next few years

Computational approaches in antibody-drug conjugate optimization for targeted cancer therapy

WOS: 000444683500007PubMed ID: 30068276Cancer has become one of the main leading causes of morbidity and mortality worldwide. One of the critical drawbacks of current cancer therapeutics has been the lack of the target-selectivity, as these drugs should have an effect exclusively on cancer cells while not perturbing healthy ones. In addition, their mechanism of action should be sufficiently fast to avoid the invasion of neighbouring healthy tissues by cancer cells. The use of conventional chemotherapeutic agents and other traditional therapies, such as surgery and radiotherapy, leads to off-target interactions with serious side effects. In this respect, recently developed target-selective Antibody-Drug Conjugates (ADCs) are more effective than traditional therapies, presumably due to their modular structures that combine many chemical properties simultaneously. In particular, ADCs are made up of three different units: a highly selective Monoclonal antibody (Mab) which is developed against a tumour-associated antigen, the payload (cytotoxic agent), and the linker. The latter should be stable in circulation while allowing the release of the cytotoxic agent in target cells. The modular nature of these drugs provides a platform to manipulate and improve selectivity and the toxicity of these molecules independently from each other. This in turn leads to generation of second-and third-generation ADCs, which have been more effective than the previous ones in terms of either selectivity or toxicity or both. Development of ADCs with improved efficacy requires knowledge at the atomic level regarding the structure and dynamics of the molecule. As such, we reviewed all the most recent computational methods used to attain all-atom description of the structure, energetics and dynamics of these systems. In particular, this includes homology modelling, molecular docking and refinement, atomistic and coarse-grained molecular dynamics simulations, principal component and cross-correlation analysis. The full characterization of the structure-activity relationship devoted to ADCs is critical for antibody-drug conjugate research and development.Fundacao para a Ciencia e a Tecnologia (FCT) Investigator programme [IF/00578/2014]; European Social Fund; Programa Operacional Potencial Humano; Marie Sklodowska-Curie Individual Fellowship MSCA-IF-2015 [MEMBRANEPROT 659826]; European Regional Development Fund (ERDF), through the Centro 2020 Regional Operational Programme [CENTRO-01-0145-FEDER-000008]; European Regional Development Fund (ERDF), COMPETE 2020 - Operational Programme for Competitiveness and Internationalisation; Portuguese national funds via FCT [POCI-01-0145-FEDER-007440]; FCT [FCT-SFRH/BPD/97650/2013]; Fundacao para a Ciencia e Tecnologia (FCT), Portugal [UID/Multi/04349/2013]Irina S. Moreira acknowledges support by the Fundacao para a Ciencia e a Tecnologia (FCT) Investigator programme - IF/00578/2014 (co-financed by European Social Fund and Programa Operacional Potencial Humano), and a Marie Sklodowska-Curie Individual Fellowship MSCA-IF-2015 [MEMBRANEPROT 659826]. This work was also financed by the European Regional Development Fund (ERDF), through the Centro 2020 Regional Operational Programme under project CENTRO-01-0145-FEDER-000008: Brain-Health 2020, and through the COMPETE 2020 - Operational Programme for Competitiveness and Internationalisation and Portuguese national funds via FCT, under project POCI-01-0145-FEDER-007440. Rita Melo acknowledges support from the FCT (FCT-SFRH/BPD/97650/2013). This work has been partially supported by the Fundacao para a Ciencia e Tecnologia (FCT), Portugal, through the UID/Multi/04349/2013 project in Centre for Nuclear Sciences and Technologies (C2TN)

The in silico prediction of foot-and-mouth disease virus (FMDV) epitopes on the South African territories (SAT)1, SAT2 and SAT3 serotypes

Foot-and-mouth disease (FMD) is a highly contagious and economically important disease that affects even-toed hoofed mammals. The FMD virus (FMDV) is the causative agent of FMD, of which there are seven clinically indistinguishable serotypes. Three serotypes, namely, South African Territories (SAT)1, SAT2 and SAT3 are endemic to southern Africa and are the most antigenically diverse among the FMDV serotypes. A negative consequence of this antigenic variation is that infection or vaccination with one virus may not provide immune protection from other strains or it may only confer partial protection. The identification of B-cell epitopes is therefore key to rationally designing cross-reactive vaccines that recognize the immunologically distinct serotypes present within the population. Computational epitope prediction methods that exploit the inherent physicochemical properties of epitopes in their algorithms have been proposed as a cost and time-effective alternative to the classical experimental methods. The aim of this project is to employ in silico epitope prediction programmes to predict B-cell epitopes on the capsids of the SAT serotypes. Sequence data for 18 immunologically distinct SAT1, SAT2 and SAT3 strains from across southern Africa were collated. Since, only one SAT1 virus has had its structure elucidated by X-ray crystallography (PDB ID: 2WZR), homology models of the 18 virus capsids were built computationally using Modeller v9.12. They were then subjected to energy minimizations using the AMBER force field. The quality of the models was evaluated and validated stereochemically and energetically using the PROMOTIF and ANOLEA servers respectively. The homology models were subsequently used as input to two different epitope prediction servers, namely Discotope1.0 and Ellipro. Only those epitopes predicted by both programmes were defined as epitopes. Both previously characterised and novel epitopes were predicted on the SAT strains. Some of the novel epitopes are located on the same loops as experimentally derived epitopes, while others are located on a putative novel antigenic site, which is located close to the five-fold axis of symmetry. A consensus set of 11 epitopes that are common on at least 15 out of 18 SAT strains was collated. In future work, the epitopes predicted in this study will be experimentally validated using mutagenesis studies. Those found to be true epitopes may be used in the rational design of broadly reactive SAT vaccinesLife and Consumer SciencesM. Sc. (Life Sciences

Navigating the Extremes of Biological Datasets for Reliable Structural Inference and Design

Structural biologists currently confront serious challenges in the effective interpretation of experimental data due to two contradictory situations: a severe lack of structural data for certain classes of proteins, and an incredible abundance of data for other classes. The challenge with small data sets is how to extract sufficient information to draw meaningful conclusions, while the challenge with large data sets is how to curate, categorize, and search the data to allow for its meaningful interpretation and application to scientific problems. Here, we develop computational strategies to address both sparse and abundant data sets. In the category of sparse data sets, we focus our attention on the problem of transmembrane (TM) protein structure determination. As X-ray crystallography and NMR data is notoriously difficult to obtain for TM proteins, we develop a novel algorithm which uses low-resolution data from protein cross-linking or scanning mutagenesis studies to produce models of TM helix oligomers and show that our method produces models with an accuracy on par with X-ray crystallography or NMR for a test set of known TM proteins. Turning to instances of data abundance, we examine how to mine the vast stores of protein structural data in the Protein Data Bank (PDB) to aid in the design of proteins with novel binding properties. We show how the identification of an anion binding motif in an antibody structure allowed us to develop a phosphate binding module that can be used to produce novel antibodies to phosphorylated peptides - creating antibodies to 7 novel phospho-peptides to illustrate the utility of our approach. We then describe a general strategy for designing binders to a target protein epitope based upon recapitulating protein interaction geometries which are over-represented in the PDB. We follow this by using data describing the transition probabilities of amino acids to develop a novel set of degenerate codons to create more efficient gene libraries. We conclude by describing a novel, real-time, all-atom structural search engine, giving researchers the ability to quickly search known protein structures for a motif of interest and providing a new interactive paradigm of protein design

Combining computer simulations and deep learning to understand and predict protein structural dynamics

Molecular dynamics simulations provide a means to characterize the ensemble of structures that a protein adopts in solution. These structural ensembles provide crucial information about how proteins function, and these ensembles also reveal potential drug binding sites that are not observable from static protein structures (i.e. cryptic pockets). However, analyzing these high- dimensional datasets to understand protein function remains challenging. Additionally, finding cryptic pockets using simulation data is slow and expensive, which makes the appeal of computationally screening for cryptic pockets limited to a narrow set of circumstances. In this thesis, I develop deep learning based methods to overcome these challenges. First, I develop a deep learning algorithm, called DiffNets, to deal with the high-dimensionality of structural ensembles. DiffNets takes structural ensembles from similar systems with different biochemical properties and learns to highlight structural features that distinguish the systems, ultimately connecting structural signatures to their associated biochemical properties. Using DiffNets, I provide structural insights that explain how naturally occurring genetic variants of the oxytocin receptor alter signaling. Additionally, DiffNets help reveal how a SARS-CoV-2 protein involved in immune evasion becomes activated. Next, I use MD simulations to hunt for cryptic pockets across the SARS-CoV-2 proteome, which led to the discovery of more than 50 new potential druggable sites. Because this effort required an extraordinary amount of resources, I developed a deep learning approach to predict sites of cryptic pockets from single protein structures. This approach reduces the time to identify if a protein has a cryptic pocket by ~10,000-fold compared to the next best method

The Conformational Universe of Proteins and Peptides: Tales of Order and Disorder

Proteins represent one of the most abundant classes of biological macromolecules and play crucial roles in a vast array of physiological and pathological processes. The knowledge of the 3D structure of a protein, as well as the possible conformational transitions occurring upon interaction with diverse ligands, are essential to fully comprehend its biological function.In addition to globular, well-folded proteins, over the past few years, intrinsically disordered proteins (IDPs) have received a lot of attention. IDPs are usually aggregation-prone and may form toxic amyloid fibers and oligomers associated with several human pathologies. Peptides are smaller in size than proteins but similarly represent key elements of cells. A few peptides are able to work as tumor markers and find applications in the diagnostic and therapeutic fields. The conformational analysis of bioactive peptides is important to design novel potential drugs acting as selective modulators of specific receptors or enzymes. Nevertheless, synthetic peptides reproducing different protein fragments have frequently been implemented as model systems in folding studies relying on structural investigations in water and/or other environments.This book contains contributions (seven original research articles and five reviews published in the journal Molecules) on the above-described topics and, in detail, it includes structural studies on globular folded proteins, IDPs and bioactive peptides. These works were conducted usingdifferent experimental methods

Determination of the spatial structure and comparative analysis of selected inhaled allergens and their complexes with antibodies

Wydział BiologiiAlergie towarzyszą człowiekowi niemal od zarania dziejów. Już w starożytnym Egipcie, Mezopotamii i Grecji znano reakcje alergiczne na pewne substancje. Alergią nazywamy stan, w którym organizm reaguje na substancję niegroźną w sposób gwałtowny i nieadekwatny do poziomu rzeczywistego zagrożenia. Reakcja alergiczna może występować pod wpływem różnych czynników i pod różnymi postaciami. Astma, wysięk z nosa, wysypka, problemy pokarmowe to tylko główne schorzenia związane z alergią. Astma jest jedną z najczęstszych (Masoli et al., 2004) i jedną z najpoważniejszych chorób dróg oddechowych, która może być powodowana przez alergeny wziewne (Busse and Lemanske, 2001). Przebieg astmy może być ostry lub chroniczny i ekspozycja na pyłek, ślinę i naskórek zwierzęcy, odchody roztoczy kurzu domowego, różne substancje karalusze, a także substancje niebędące alergenami mogą spowodować atak astmy. Poznanie struktury pneumoalergenów oraz próba zrozumienia molekularnych podstaw oddziaływań pomiędzy badanymi alergenami i przeciwciałami może przyczynić się do opracowania w przyszłości odpowiedniej terapii immunologicznej a tym samym zmniejszenia objawów astmy u osób nią dotkniętych. Głównym elementem tezy doktorskiej było zbadanie molekularnych podstaw oddziaływania głównego alergenu Grupy 1 z roztocza kurzu domowego pochodzącymi z Europy Der p 1 (skórożarłoczek skryty - Dermatophagoides pteronyssinus) oraz roztoczy kurzu domowego pochodzącymi z Ameryki (Dermatophagoides farinae) Der f 1 z przeciwciałami monoklonalnymi 4C1, 5H8 oraz 10B9. Została przeprowadzona szczegółowa analiza powierzchni oddziaływania epitopu oraz paratopu w otrzymanych kompleksach alergenu z przeciwciałami. Zbadanie alergenu Bla g 4 pochodzącego z karaczana prusaka (Blatella germanica) było kolejną częścią projektu poznania pneumoalergenów. Alergen ten należy do lipokalin – rodziny białek wiążących małe cząsteczki. Lipokaliny charakteryzują się stosunkowo niewielkim zachowaniem ewolucyjnym na poziomie sekwencji, ale silnym na poziomie struktury. Funkcja Bla g 4 oraz ligand wiązany przez to białko są nieznane. Rozwiązanie struktury Bla g 4 umożliwiło identyfikację ligandu, a przeprowadzenie analiz strukturalnych, sekwencyjnych oraz filogenetycznych najbliższego homologa – Per a 4 oraz innych spokrewnionych alergenów umożliwi w nieodległej przyszłości poznanie ich wzajemnych relacji. Poznanie struktury oraz zbadanie homologów alergenu Alt a 1 było ostatnią częścią projektu. Alergen Alt a 1 pochodzi z pleśni Alternaria alternata występującej powszechnie w klimacie umiarkowanym. Alt a 1 jest alergenem o nieznanej strukturze i funkcji. Rozwiązanie struktury, oraz analizy sekwencyjne i filogenetyczne będą pierwszym krokiem do przyszłych badań nad tym alergenem. Kompleksy alergenu Der p 1 z przeciwciałami 10B9 oraz 5H8, a także przeciwciała 10B9 w niezwiązanej formie dostarczyły unikatowej okazji do przeanalizowania sposobu wiązania regionów determinujących komplementarność przeciwciał do epitopów. Bardzo bliskie pokrewieństwo Der p 1 oraz Der f 1 oraz różnorodność otrzymanych struktur umożliwiła porównanie zmian zachodzących podczas wiązania przeciwciał, a także rodzajów uwarunkowań molekularnych do ich wystąpienia. Umożliwiło to porównanie zmian zachodzących podczas wiązania przeciwciała 10B9 do Der p 1 w kontekście otrzymanej uprzednio struktury alergenów Der p 1 i Der f 1 z podwójnie swoistym przeciwciałem 4C1. Otrzymane wyniki prowadzą do wniosku, że nawet takie same lub prawie identyczne epitopy mogą zachowywać się zgodnie zarówno z modelem „klucza i zamka” jak i modelem indukowanego dopasowania Identyfikacja reszt aminokwasowych odgrywających znaczącą rolę w oddziaływaniach alergenu z przeciwciałami oraz zrozumienie strukturalnych podstaw komplementarności między nimi może zostać wykorzystane w projektowaniu alergenów o epitopach charakteryzujących się obniżoną siłą wiązania przeciwciał do celów immunoterapii alergenowej. Dzięki krystalografii rentgenowskiej możliwe było poznanie szczegółów oddziaływania alergenu Bla g 4 z tyraminą, a dzięki analizie struktur oraz sekwencji białek homologicznych, będących także alergenami, poznanie zachowanego ewolucyjnie miejsca i sposobu wiązania tego ligandu wśród pokrewnych alergenów. Okazuje się, że nawet najbliższy homolog Bla g 4 - Per a 4 pochodzący z karalucha amerykańskiego (Periplaneta americana) nie ma zachowanych kluczowych aminokwasów odpowiedzialnych za wiązanie tyraminy i oktopaminy, więc najprawdopodobniej wiąże inne ligandy oraz pełni inną funkcję. Poznanie struktury alergenu Alt a 1, jako unikalnej dimerycznej β-baryłki, a także jako pierwszej z całej rodziny białek z grzybów o nieznanej funkcji jest pierwszym krokiem w celu dalszych badań nad funkcją oraz powiazaniem struktury z funkcja, co może doprowadzić do opracowania nowych form immunoterapii dla osób uczulonych na ten alergen. Uzyskanie struktur krystalicznych za pomocą rentgenografii krystalograficznej oraz analizy molekularnych podstaw oddziaływania alergenów z przeciwciałami; analizy strukturalnej wraz z sekwencyjną między homologicznymi alergenami może w przyszłości zostać wykorzystana do celów farmaceutycznych. Wyniki tych badań pokazują, że zastosowanie połączenia różnych technik umożliwia otrzymanie optymalnych rezultatów.Human kind has been troubled by allergies since the beginning of written history. Allergic reactions to certain substances have been known even in the ancient Egypt, Mesopotamia or Greece. What we call an allergy is a state when organism reacts to otherwise unharmful substance in the violent and inappropriate manner to real danger posed by the given substance. An allergic reaction can occur under the influence of different factors and different forms. Asthma, rhinitis, rash, digestive problems are the main ailments related to allergies. Asthma is one of the most common (Masoli et al., 2004) and one of the most serious diseases of the airways caused by inhaled allergens (Busse and Lemanske, 2001). The course of asthma may be acute or chronic, and asthma attacks may be caused by exposure to pollen, animal saliva, animal dander, feces of the house dust mites, cockroach particles, as well as certain non-allergenic. The elucidation of pneumoallergen structures and an attempt to understand the molecular basis of the interactions between analyzed allergens and antibodies may contribute to the development of the proper immunotherapy and thus reduce asthma symptoms in people affected by it. The main part of this project was to analyze the molecular basis of the interaction between Group 1 major allergens from house dust mites – Der p 1 coming from European house dust mite (Dermatophagoides pteronyssinus) and Der f 1 coming from American house dust mite (Dermatophagoides farinae) with 4C1, 5H8 and 10B9 monoclonal antibodies. A detailed analysis of the interaction surface between the epitopes and the paratopes of the obtained complexes has been conducted. The analysis of the Bla g 4 allergen coming from German cockroach (Blatella germanica) was another part of the project concerning pneumoallergens. This allergen belongs to lipocalin protein family, which usually bind small ligands. The lipocalins are characterized by their relatively low sequence conservation, but strong structural similarity. The function of Bla g 4 as well as the ligand it binds were previously unknown, but the structure determination of Bla g 4 presented herein allowed for the identification of the ligand. The analysis of the structure and sequence of the closest homolog – Per a 4 as well as other homologous allergens allow recognition of interrelationships. The elucidation of the structure of Alt a 1 was the last part of the project. The Alt a 1 allergen comes from black mold (Alternaria alternata), which is common in the outdoor environment in the mild climate zones and is a major health hazard for humans when . Both the structure and the function of the Alt a 1 allergen are unknown. The structure solution together with the analysis of its sequence is the first step for the future research. The Der p 1 allergen complexed with monoclonal antibodies 10B9 and 5H8, as well as 10B9 antibody in its uncomplexed form provided a unique opportunity to study the mechanics of the binding of the complementarity determining regions to the epitopes. A very close homology between the Der p 1 and Der f 1 allergens together with the variety of the obtained structures allowed for the comparison of the changes undergoing upon the binding of the antibodies, as well as the molecular determinants involved in this process. This includes the changes in the conformation of the 10B9 antibody and the comparison with the results of previous study on the binding of the cross-reactive antibody 4C1 by Der p 1 and Der f 1. The obtained results show that both “lock and key” and “induced fit” binding models can coexist even in the same area of the epitopes. The identification of the amino acid residues having important role in the allergen-antibody interactions and the understanding of the molecular basis of the complementarity between them can be used in the design of allergens with the epitopes of lesser affinity to the given antibodies that may be beneficial in immunotherapy. Thanks to x-ray crystallography, it was possible to study the details of the Bla g 4 allergen with tyramine, and as a result of the analysis of the structures together with the sequences of its homologs, it was possible to determine the conservation level of the binding site. This, in turn, provided clues to the ligand binding among homologs related to Bla g 4. It turned out that even the closest homolog to Bla g 4 – the Per a 4 allergen from the American cockroach (Periplaneta americana) does not have conserved key amino acids responsible for the binding of tyramine or octopamine, thus most likely it binds to other ligands and serves a different purpose. Revealing the Alt a 1 allergen structure as a unique dimeric β-barrel protein, as well as solving it as a first structure of the whole protein family of unknown function and exclusive to fungi, is the first step for further research and identifying structure-function relationship, which can lead to the development of the new forms of immunotherapy for Alt a 1 sensitive patients. The knowledge gained by the elucidation of the crystal structures with x-ray crystallography methods, together with the result of the analysis of the molecular basis of allergen-antibody interactions as well as the structure and sequence analysis between the homologous allergens, may be used in the future for the pharmaceutical purposes. The outcome of the experimental and theoretical approach presented herein shows that the combination of different techniques provides more information than just the sum of the individual results

Delineating Structural Characteristics of Viral Capsid Proteins Critical for Their Functional Assembly.

Viral capsids exhibit elaborate and symmetrical architectures of defined sizes and remarkable mechanical properties not seen with cellular macromolecular complexes. The limited coding capacity of viral genome necessitates economization upon one or a few identical gene products known as capsid proteins for shell assembly. The functional uniqueness of this class of proteins prompts questions on structural features critically important for their higher order organization. In this thesis, I develop the statistical framework and computational tools to pinpoint the structural characteristics of viral capsid proteins exclusive to the virosphere by testing a series of hypotheses, providing understanding of the physical principles governing molecular self-association that can inform rational design of nanomaterials and therapeutics. In the first chapter, I compare the folds of capsid proteins with those of generic proteins, and establish that capsid proteins are segregated in structural fold space, highlighting the geometric constraints of these building blocks for tiling into a closed shell. Second, I develop a software program, PCalign, for quantifying the physicochemical similarity between protein-protein interfaces. This tool overcomes the major limitation of current methods by using a reduced representation of structural information, greatly expanding the structural interface space that can be investigated through inclusion of large macromolecular assemblies that are often not amenable to high resolution experimental techniques. As an application of this method, I propose a computational framework for template-based protein inhibitor design, leading to the prediction of putative binders for a therapeutic target, the influenza hemagglutinin. In silico evaluations of these candidate drugs parallel those of known protein binders, offering great promise in expanding therapeutic options in the clinic. Lastly, I examine protein-protein interfaces using PCalign, and find strong statistical evidence for the disconnectivity between capsid proteins and cellular proteins in structural interface space. I thus conclude that the basic shape and the sticky edges of these Lego pieces act concertedly to create the sophisticated shell architecture. In summary, the novel tools contributed by this dissertation work lead to delineation of structural features of viral capsid proteins that make them functionally unique, providing an understanding that will serve as the basis for prediction and design.PHDBioinformaticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/110375/1/sscheng_1.pd