Analysis and application of evolutionary processes to tackle HIV-1 entry

Im Laufe der Jahrmillionen hat die Evolution durch einige einfache Mechanismen wie Mutation, Selektion oder auch Vererbung eine erstaunliche Artenvielfalt hervorgebracht. Diese Prinzipien können auch beim computergestützten Entwurf von Proteinen und/oder Proteinsequenzen mit gewünschten Eigenschaften, wie z.B. Stabilität oder Funktionalität einer Proteinstruktur, angewandt werden. Da jedoch der mögliche Konformations- und Sequenzraum für bereits kleine Proteine immens groß wird, werden hier vereinfachte Gitterproteinmodelle verwendet. Im ersten Teil der Promotionsarbeit werden evolutionäre Algorithmen, im Besonderen S Metric Selection - Evolutionary Multi-objective Optimisation Algorithm (SMS-EMOA), implementiert und angewandt um möglichst optimale evolutionäre Parameter zu identifizieren, z.B. Populationsgröße oder Mutationsrate. Interessanterweise spielt die richtige Auswahl der evolutionären Parameter eine entscheidende Rolle bezüglich der Effizienz der Algorithmen. Im zweiten Teil der Arbeit wird die Evolution von Proteinen beobachtet und analysiert. Ein besonderes Augenmerk wird dabei auf Positionen gelegt, die nicht konserviert sind. Gleichwohl können diese mit kompensatorischen Mutationen an anderen Stellen im Protein strukturell wichtige Funktionen einnehmen. Hierbei werden verschiedene Koevolutionsmethoden, wie z.B. die Mutual Information (MI) oder die Direct Coupling Analysis (DCA), weiterentwickelt und verglichen. Anschließend wird die DCA-Methode mit einer neu verbesserten Gewichtung angewandt um koevolvierende Positionen im Humanen Immundefizienz-Virus (HIV) Hüllprotein-Komplex (Env) vorherzusagen. Bemerkenswerterweise wurden dabei sowohl bereits in der Literatur beschriebene als auch noch unbekannte Positionen identifiziert, die eine entscheidende Rolle im Eintritt des Viruses in die humane Wirtszelle spielen können. Schließlich wurden die koevolvierenden Positionen bei der Erstellung eines Homologiemodells des Protein-Komplexes verwendet

Coevolution Analysis of HIV-1 Envelope Glycoprotein Complex

The HIV-1 Env spike is the main protein complex that facilitates HIV-1 entry into CD4+ host cells. HIV-1 entry is a multistep process that is not yet completely understood. This process involves several protein-protein interactions between HIV-1 Env and a variety of host cell receptors along with many conformational changes within the spike. HIV-1 Env developed due to high mutation rates and plasticity escape strategies from immense immune pressure and entry inhibitors. We applied a coevolution and residue-residue contact detecting method to identify coevolution patterns within HIV-1 Env protein sequences representing all group M subtypes. We identified 424 coevolving residue pairs within HIV-1 Env. The majority of predicted pairs are residue-residue contacts and are proximal in 3D structure. Furthermore, many of the detected pairs have functional implications due to contributions in either CD4 or coreceptor binding, or variable loop, gp120-gp41, and interdomain interactions. This study provides a new dimension of information in HIV research. The identified residue couplings may not only be important in assisting gp120 and gp41 coordinate structure prediction, but also in designing new and effective entry inhibitors that incorporate mutation patterns of HIV-1 Env

Sequence-Signature Optimization Enables Improved Identification of Human HV6-1-Derived Class Antibodies That Neutralize Diverse Influenza A Viruses

Sequence signatures of multidonor broadly neutralizing influenza antibodies can be used to quantify the prevalence of B cells with virus-neutralizing potential to accelerate development of broadly protective vaccine strategies. Antibodies of the same class share similar recognition modes and developmental pathways, and several antibody classes have been identified that neutralize diverse group 1- and group 2-influenza A viruses and have been observed in multiple human donors. One such multidonor antibody class, the HV6-1-derived class, targets the stem region of hemagglutinin with extraordinary neutralization breadth. Here, we use an iterative process to combine informatics, biochemical, and structural analyses to delineate an improved sequence signature for HV6-1-class antibodies. Based on sequence and structure analyses of known HV6-1 class antibodies, we derived a more inclusive signature (version 1), which we used to search for matching B-cell transcripts from published next-generation sequencing datasets of influenza vaccination studies. We expressed selected antibodies, evaluated their function, and identified amino acid-level requirements from which to refine the sequence signature (version 2). The cryo-electron microscopy structure for one of the signature-identified antibodies in complex with hemagglutinin confirmed motif recognition to be similar to known HV6-1-class members, MEDI8852 and 56.a.09, despite differences in recognition-loop length. Threading indicated the refined signature to have increased accuracy, and signature-identified heavy chains, when paired with the light chain of MEDI8852, showed neutralization comparable to the most potent members of the class. Incorporating sequences of additional class members thus enables an improved sequence signature for HV6-1-class antibodies, which can identify class members with increased accuracy

Structural survey of HIV-1-neutralizing antibodies targeting Env trimer delineates epitope categories and suggests vaccine templates

HIV-1 broadly neutralizing antibodies are desired for their therapeutic potential and as templates for vaccine design. Such antibodies target the HIV-1-envelope (Env) trimer, which is shielded from immune recognition by extraordinary glycosylation and sequence variability. Recognition by broadly neutralizing antibodies thus provides insight into how antibody can bypass these immune-evasion mechanisms. Remarkably, antibodies neutralizing >25% of HIV-1 strains have now been identified that recognize all major exposed surfaces of the prefusion-closed Env trimer. Here we analyzed all 206 broadly neutralizing antibody-HIV-1 Env complexes in the PDB with resolution suitable to define their interaction chemistries. These segregated into 20 antibody classes based on ontogeny and recognition, and into 6 epitope categories (V1V2, glycan-V3, CD4-binding site, silent face center, fusion peptide, and subunit interface) based on recognized Env residues. We measured antibody neutralization on a 208-isolate panel and analyzed features of paratope and B cell ontogeny. The number of protruding loops, CDR H3 length, and level of somatic hypermutation for broadly HIV-1 neutralizing antibodies were significantly higher than for a comparison set of non-HIV-1 antibodies. For epitope, the number of independent sequence segments was higher (P < 0.0001), as well as the glycan component surface area (P = 0.0005). Based on B cell ontogeny, paratope, and breadth, the CD4-binding site antibody IOMA appeared to be a promising candidate for lineage-based vaccine design. In terms of epitope-based vaccine design, antibody VRC34.01 had few epitope segments, low epitope-glycan content, and high epitope-conformational variability, which may explain why VRC34.01-based design is yielding promising vaccine results

Structural survey of HIV-1-neutralizing antibodies targeting Env trimer delineates epitope categories and suggests vaccine templates

HIV-1 broadly neutralizing antibodies are desired for their therapeutic potential and as templates for vaccine design. Such antibodies target the HIV-1-envelope (Env) trimer, which is shielded from immune recognition by extraordinary glycosylation and sequence variability. Recognition by broadly neutralizing antibodies thus provides insight into how antibody can bypass these immune-evasion mechanisms. Remarkably, antibodies neutralizing >25% of HIV-1 strains have now been identified that recognize all major exposed surfaces of the prefusion-closed Env trimer. Here we analyzed all 206 broadly neutralizing antibody-HIV-1 Env complexes in the PDB with resolution suitable to define their interaction chemistries. These segregated into 20 antibody classes based on ontogeny and recognition, and into 6 epitope categories (V1V2, glycan-V3, CD4-binding site, silent face center, fusion peptide, and subunit interface) based on recognized Env residues. We measured antibody neutralization on a 208-isolate panel and analyzed features of paratope and B cell ontogeny. The number of protruding loops, CDR H3 length, and level of somatic hypermutation for broadly HIV-1 neutralizing antibodies were significantly higher than for a comparison set of non-HIV-1 antibodies. For epitope, the number of independent sequence segments was higher (P < 0.0001), as well as the glycan component surface area (P = 0.0005). Based on B cell ontogeny, paratope, and breadth, the CD4-binding site antibody IOMA appeared to be a promising candidate for lineage-based vaccine design. In terms of epitope-based vaccine design, antibody VRC34.01 had few epitope segments, low epitope-glycan content, and high epitope-conformational variability, which may explain why VRC34.01-based design is yielding promising vaccine results

Model selection emphasises the importance of non-chromosomal information in genetic studies.

Ever since the case of the missing heritability was highlighted some years ago, scientists have been investigating various possible explanations for the issue. However, none of these explanations include non-chromosomal genetic information. Here we describe explicitly how chromosomal and non-chromosomal modifiers collectively influence the heritability of a trait, in this case, the growth rate of yeast. Our results show that the non-chromosomal contribution can be large, adding another dimension to the estimation of heritability. We also discovered, combining the strength of LASSO with model selection, that the interaction of chromosomal and non-chromosomal information is essential in describing phenotypes

Effect of Luminaries’ Arrangement and Type on Visual Comfort and Energy Consumption

The current study seeks to evaluate the effect of luminaries’ arrangement and type on visual comfort and energy consumption. Two identical classrooms with different luminaries’ arrangements were selected to evaluate the efficacy of the existing lighting system in terms of illuminance uniformity, unified glare rating, and installed load efficacy ratio. DIALux Evo software validated against measured illuminance then employed to assess other suggested luminaries’ arrangement and replacing the existing fluorescent lamp with LED type to recommend the best scenario. The findings of the study indicate that the Luminaries’ arrangement and type are decisive factors that affect visual comfort and save energy wastage. Accordingly, we recommend distributing the luminaries in a way that the number of rows equals the number of columns and consider the longitudinal length of the luminaire to be parallel to the longitudinal length of the illuminated space. Field measurements revealed that the existing lighting system does not offer visual comfort for occupants and simulation findings recommend using LED luminaries in classrooms to ensure visual comfort and save energy wastage up to 50%

Frequency of selected linear models according to their MSE within 1000 modelling repeats.

<p>Frequency of selected linear models according to their MSE within 1000 modelling repeats.</p

COVID-19 Impact on Education and Work in the Kingdom of Bahrain: Survey Study

The Coronavirus (COVID-19) pandemic has disrupted teaching and work in the entire world. The COVID-19 reshaped the management of education and work leading to a rethinking of new approaches in the education system or the business environment. A lot of studies and reports were published over the world analyzing and discussing the current situation and looking for solutions and alternatives to overcome this crisis. This paper discusses the impact of the COVID- 19 pandemic in education and work environments in the Kingdom of Bahrain using the survey method. Also, it reviewed the precautionary measures that were taken by the Kingdom to confront this dangerous pandemic. In addition, it discussed the use of digital tools and technology, which will help to overcome the problems initiated during the pandemic. An online survey was performed by distributing 12 research questions to different people in the Kingdom of Bahrain. 210 answered the questionnaire, and the data were analyzed with statistical software. Overall findings of this study indicated that the online learning transition in the Kingdom of Bahrain was successful because most of the respondents agreed with the use of online learning. Moreover, the respondents who had jobs revealed that COVID-19 affected their work