Knowledge based structure modeling of the third hypervariable region of antibodies

Protein structure prediction has gained increased attention over the past decades in a wide range of biological disciplines. Creating an accurate visual model of a protein can aid in protein engineering; which has implications in the creation of therapeutic molecules as is the case with antibodies. The third complementarity determining region of the heavy chain of antibodies (CDR-H3) is known to show a large degree of variation in sequence and in length, and therefore has provided difficulties for structure prediction. By separating the CDR-H3 into two logical sections, the apex and base, and using a homology modeling techniques for each section, this study attempts to predict structure for this important region of antibodies. This method also accounts for certain interactions proven to be relevant in CDR-H3 structure to select a suitable parent for modeling an unknown CDR-H3. The selection algorithm was tested using a test set of proteins, selected based on base type, length and diversity. Overall, there seemed to be a slight improvement in the prediction of CDR-H3 by this method when compared with traditional homology methods; although both drastic improvements and evident decreases in accuracy of predictions from individual molecules can be observed

abYsis: Integrated Antibody Sequence and Structure-Management, Analysis, and Prediction

abYsis is a web-based antibody research system that includes an integrated database of antibody sequence and structure data. The system can be interrogated in numerous ways-from simple text and sequence searches to sophisticated queries that apply 3D structural constraints. The publicly available version includes pre-analyzed sequence data from the European Molecular Biology Laboratory European Nucleotide Archive (EMBL-ENA) and Kabat as well as structure data from the Protein Data Bank. A researcher's own sequences can also be analyzed through the web interface. A defining characteristic of abYsis is that the sequences are automatically numbered with a series of popular schemes such as Kabat and Chothia and then annotated with key information such as complementarity-determining regions and potential post-translational modifications. A unique aspect of abYsis is a set of residue frequency tables for each position in an antibody, allowing "unusual residues" (those rarely seen at a particular position) to be highlighted and decisions to be made on which mutations may be acceptable. This is especially useful when comparing antibodies from different species. abYsis is useful for any researcher specializing in antibody engineering, especially those developing antibodies as drugs. abYsis is available at www.abysis.org

AbDb: Antibody structure database - A database of PDB derived antibody structures

In order to analyse structures of proteins of a particular class, these need to be extracted from Protein Data Bank (PDB) files. In the case of antibodies, there are a number of special considerations: (i) identifying antibodies in the PDB is not trivial, (ii) they may be crystallized with or without antigen, (iii) for analysis purposes, one is normally only interested in the Fv region of the antibody, (iv) structural analysis of epitopes, in particular, requires individual antibody–antigen complexes from a PDB file which may contain multiple copies of the same, or different, antibodies and (v) standard numbering schemes should be applied. Consequently, there is a need for a specialist resource containing pre-numbered non-redundant antibody Fv structures with their cognate antigens. We have created an automatically updated resource, AbDb, which collects the Fv regions from antibody structures using information from our SACS database which summarizes antibody structures from the PDB. PDB files containing multiple structures are split and numbered and each antibody structure is associated with its antigen where available. Antibody structures with only light or heavy chains have also been processed and sequences of antibodies are compared to identify multiple structures of the same antibody. The data may be queried on the basis of PDB code, or the name or species of the antibody or antigen, and the complete datasets may be downloaded. Database URL: www.bioinf.org.uk/abs/abdb

Updates to the Integrated Protein–Protein Interaction Benchmarks: Docking Benchmark Version 5 and Affinity Benchmark Version 2

We present an updated and integrated version of our widely used protein–protein docking and binding affinity benchmarks. The benchmarks consist of non-redundant, high-quality structures of protein–protein complexes along with the unbound structures of their components. Fifty-five new complexes were added to the docking benchmark, 35 of which have experimentally measured binding affinities. These updated docking and affinity benchmarks now contain 230 and 179 entries, respectively. In particular, the number of antibody–antigen complexes has increased significantly, by 67% and 74% in the docking and affinity benchmarks, respectively. We tested previously developed docking and affinity prediction algorithms on the new cases. Considering only the top 10 docking predictions per benchmark case, a prediction accuracy of 38% is achieved on all 55 cases and up to 50% for the 32 rigid-body cases only. Predicted affinity scores are found to correlate with experimental binding energies up to r = 0.52 overall and r = 0.72 for the rigid complexes.Peer ReviewedPostprint (author's final draft

Sequence and structural analysis of antibodies

The work presented in this thesis focusses on the sequence and structural analysis of antibodies and has fallen into three main areas. First I developed a method to assess how typical an antibody sequence is of the expressed human antibody repertoire. My hypothesis was that the more \humanlike" an antibody sequence is (in other words how typical it is of the expressed human repertoire), the less likely it is to elicit an immune response when used in vivo in humans. In practice, I found that, while the most and least-human sequences generated the lowest and highest anti-antibody reponses in the small available dataset, there was little correlation in between these extremes. Second, I examined the distribution of the packing angles between VH and VL domains of antibodies and whether residues in the interface in uence the packing angle angle. This is an important factor which has essentially been ignored in modelling antibody structures since the packing angle can have a signi�cant e�ect on the topography of the combining site. Finding out which interface residues have the greatest in uence is also important in protocols for `humanizing' mouse antibodies to make them more suitable for use in therapy in humans. Third, I developed a method to apply standard Kabat or Chothia numbering schemes to an antibody sequence automatically. In brief, the method uses pro�les to identify the ends of the framework regions and then �lls in the numbers for each section. Benchmarking the performance of this algorithm against annotations in the Kabat database highlighted several errors in the manual annotations in the Kabat database. Based on structural analysis of insertions and deletions in the framework regions of antibodies, I have extended the Chothia numbering scheme to identify the structurally correct positions of insertions and deletions in the framework regions

Structural and Conformational Analysis of B-cell Epitopes − component to guide peptide vaccine design

Peptide vaccines have many potential advantages including low cost, lack of need for cold-chain storage and safety. However, it is well known that approximately 90% of B-cell Epitopes (BCEs) are discontinuous in nature making it difficult to mimic them for creating vaccines. To perform a detailed structural analysis of these epitopes, they needs to be mapped onto antigen structures that are complexed with antibody. In order to obtain a clean dataset of antibody-antigen complex crystal structures, a pipeline was designed to process automatically and clean the antibody related structures from the PDB. To store this processed antibody structural data, a database (AbDb) was built and made available online. The degree of discontinuity in B-cell epitopes and their conformational nature was studied by mapping epitopes in the antibody-antigen dataset. The discontinuity of B-cell epitopes was analysed by defining extended ‘regions’ (R, consisting of at least 3 antibody-contacting residues each separated by ≤ 3 residues) and small fragments (F, antibody-contacting residues that do not satisfy the requirements for a region). Secondly, an algorithm was developed to classify region shape as linear, curved or folded. Molecular dynamics simulations were carried out on isolated epitope regions (wild type and mutant peptides). The mutant peptides have been designed by mutating non-contacting and hydrophobic residues in epitopes. Two types of mutations (hy- drophobic to alanine and hydrophobic to glutamine) have been studied using molec- ular dynamics simulations. Furthermore, the effect of end-capping on wild type and mutant epitope regions has been studied. Simulation studies were carried out on 5 linear and 5 folded shape regions. Out of these, 2 epitopes (one linear and one folded), along with their mutants and derivatives, were tested experimentally for conformational stability by CD spectroscopy and NMR. The binding of isolated epitopes with antibody was also validated by ELISA and SPR

Novel pharmacophore clustering methods for protein binding site comparison

Proteins perform diverse functions within cells. Some of the functions depend on the protein being involved in a protein complex, interacting with other proteins or with other entities (ligands) through specific binding sites on their surface. Comparison of protein binding sites has potential benefits in many research fields, including drug promiscuity studies, polypharmacology and immunology. While multiple methods have been proposed for comparing binding sites, they tend to focus on comparing very similar proteins and have only been developed for small specific datasets or very targeted applications. None of these methods make use of the powerful representation afforded by 3D complex-based pharmacophores. A pharmacophore model provides a description of a binding site, consisting of a group of chemical features arranged in three-dimensional space, that can be used to represent biological activities. Two different pharmacophore comparison and clustering methods based on the Iterative Closest Point (ICP) algorithm are proposed: a 3-dimensional ICP pharmacophore clustering method, and an N-dimensional ICP pharmacophore clustering method. These methods are complemented by a series of data pre-processing methods for input data preparation. The implementation of the methods takes computational representations (pharmacophores) of single molecule or protein complexes as input and produces distance matrices that can be visualised as dendrograms. The methods integrate both alignment-dependent and alignment-independent concepts. Both clustering methods were successfully evaluated using a 31 globulin-binding steroid dataset and a 41 antibody-antigen dataset, and were able to handle a larger dataset of 159 protein homodimers. For the steroid dataset, the resulting classification of ligands shows good correspondence with a classification based on binding affinity. For the antibody-antigen dataset, the classification of antigens reflected both antigen type and binding antibody. The applications to homodimers demonstrated the ability of both clustering methods to handle a larger dataset, and the possibility to visualise N-D pairwise comparisons using structural superposition of binding sites

Os efeitos dos polímeros piezoeléctricos na diferenciação neuronal

Mestrado em Biomedicina MolecularO crescimento de neurites é crucial para o desenvolvimento neuronal, bem como para a plasticidade e reparação na fase adulta. Após uma lesão neuronal, o sucesso da reparação é determinando pelas propriedades plásticas constitutivas dos neurónios afetados e pelo seu potencial de regeneração, que é influenciado por sinais externos físicos (ex.: cicatriz glial) e químicos (ex.: moléculas inibitórias). Recentemente, o desenvolvimento de materiais à nano-escala, que interagem com os sistemas biológicos a nível molecular, prometem revolucionar o tratamento das lesões do Sistema Nervoso Central e Periférico. Os scaffolds de nanomateriais podem suportar e promover o crescimento de neurites e consequentemente, intervir nas complexas interações moleculares que ocorrem a após o dano neuronal, entre as células e o seu ambiente extracelular. Vários estudos têm demonstrado que os materiais piezoeléctricos, que geram carga elétrica em resposta ao stress mecânico, podem ser usados para a preparação de scaffolds eletricamente carregados que devem influenciar o comportamento celular. Este estudo centrou-se nos efeitos dos materiais baseados em PLLA (ácido poli (L – láctico)) sob a forma de filmes, nanofibras orientadas aleatória e alinhadamente, e da sua polarização, na diferenciação neuronal. A linha celular de neuroblastoma (SH-SY5Y) foi utilizada para avaliar o efeito dos materiais-baseados em PLLA na adesão, viabilidade, morfologia celular, bem como na diferenciação tipo-neuronal. A análise proteómica baseada em espectrometria de massa das células cultivadas em nanofibras de PLLA foi também efetuada. Os neurónios corticais embriónicos foram seguidamente utilizados para avaliar os efeitos das nanofibras de PLLA alinhadas e da sua polarização no crescimento de neurites. Nesta análise, descobrimos que os materiais de PLLA parecem inibir parcialmente a proliferação celular, enquanto promovem a diferenciação, alterando os níveis das proteínas que intervêm nestes processos. Ocorrem alterações significativas do citoesqueleto, particularmente ao nível do citoesqueleto de actina, que não induzem mas parecem potenciar o crescimento de neurites sob exposição a um sinal extracelular como o ácido retinóico. Este efeito parece ser particularmente evidente para as nanofibras de PLLA alinhadas, que induzem efeitos intermédios na restruturação do citoesqueleto. Em geral, a polarização das amostras de PLLA tem efeitos benéficos na proliferação celular e potencia o crescimento de neurites, particularmente nos neurónios. Acreditamos que as nanofibras de PLLA alinhadas serão um bom scaffold para regeneração neuronal, uma vez que mimetiza o ambiente mecânico natural das células. Contudo, futuras experiências in vitro e in vivo são necessárias para comprovar a eficácia deste potencial scaffold.Neuritic growth is crucial for neural development, as well as for adaptation and repair in adulthood. Upon neuronal injury, the successful neuritic regrowth is determined by the constitutive plastic properties of neurons and by their regenerative potential, which is influenced by physical (e.g. glial scar) and chemical (e.g. inhibitory molecules) extrinsic cues. Recently, the development of nanometer-scale materials, which can interact with biological systems at a molecular level, provide hope to revolutionize the treatment of central and peripheral nervous system injuries. Nanomaterial scaffolds can support and promote neuritic outgrowth and consequently, take part in the complex molecular interactions between cells and their extracellular environment after neuronal injury. Several studies have shown that piezoelectric materials, which generate electrical charge in response to mechanical strain, may be used to prepare bioactive electrically charged scaffolds that may influence cell behavior. This study focused on the effects of PLLA (poly-L-lactic acid) – based materials in the form of films, random and aligned nanofibers, and of their polarization, on neuronal-like and neuronal differentiation. The neuroblastoma SH-SY5Y cell line was used to evaluate the effect of PLLA – based materials on cellular adhesion, viability, morphology and neuron-like differentiation. Mass spectrometry-based proteomic analysis of cells grown on PLLA nanofibers was also conducted. Primary embryonic cortical neurons were further used to evaluate the effect of PLLA aligned nanofibers and their polarization on neuritic outgrowth. In this analysis, we found that PLLA materials seem to partially inhibit cell proliferation, while promoting neuronal differentiation, altering the levels of proteins that intervene in these processes. Dramatic cytoskeleton remodeling occurs, particularly at the actin cytoskeleton level, which does not induce but may potentiate neuritic outgrowth upon exposure to an extracellular cue, such as Retinoic Acid. This effect seems to be particularly evident for PLLA aligned nanofibers, which induce intermediate effects in the cytoskeleton remodeling. In general, polarization of the PLLA polymers has beneficial effects on cell proliferation and potentiates the neuritic outgrowth, particularly in neurons. We believe that polarized PLLA aligned nanofibers would be a good scaffold for neuronal regeneration, since it mimics the natural mechanical cell environment and enhances neuritic outgrowth. However, further in vitro and in vivo investigations are required to prove the efficacy of this potential scaffold