Combinatorial in-silico modeling and bioinformatics analysis of immune proteins and small-molecular weight inhibitors: a potential for cancer chemotherapy.

Doctoral Degree. University of KwaZulu-Natal, Durban.The immune system carries out pivotal functions in the protection of the body from damaging substances, microbes, and cellular alteration that could affect the health of an individual. The component of the immune system comprises of proteins, cells, and diverse organs. Individuals remain in a good state of health and wholeness if the immune system is working optimally, but if it becomes incapacitated toward fighting off germs or other harmful foreign substances, a diseased state set in. The innate and adaptive systems are the two sub-categories of the immune system. They work synergistically in the defence of the body and fighting off germs that triggered an immune response. Several proteins have been discovered to play pivotal roles in immune evasion and have therefore become attractive targets. Three of these proteins form the core of this thesis. Programmed death-ligand 1 (PD-L1), is an immune checkpoint protein which upon binding with another inhibitory checkpoint protein programmed cell death protein 1 (PD-1), elicit a cascade of reaction that leads to the reduction of proliferating antigen-specific T cells. The upregulation of PD-L1 can therefore, lead to evasion of the immune system by cancer cells. Cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) is made up of three parts (a transmembrane part, extracellular part, and a cytoplasmic part). CTLA-4 has been implicated in the downregulation of immune response and blocking CTLA-4 activity results in a surge in immune functions. It has also been found that CTLA-4 negatively controls the T-cells. Natural killer group 2, member D (NKG2D) is located on the surface of immune cells where it acts as an activating receptor and regulator of the adaptive and innate immune system upon binding to its constitutive ligands such as UL16-binding protein (ULBP6). ULBP6 is a highly polymorphic protein, hence, the interaction between NKGD2 and ULBP6 is often altered. This effect has a great impact on the function of NKGD2 as a regulator of the immune system. Various humanized antibodies have been developed to specifically target PD-L1 and CTLA4. Some have been approved while others are at different phases of clinical trial. Ipilimumab and tremelimumab are designed as CTLA-4 inhibitors. Durvalumab and atezolimab are designed as anti-PD-L1 inhibitor. However, due to the limitations that have characterized the use of humanized antibodies inhibitors such as production cost, instability, and low tumour penetration, etc, small molecule inhibitors have been considered as a better alternative to humanized antibodies inhibitors. This thesis explored the mechanism of inhibition of newly synthesised PD-L1 inhibitors (BMS- 1166 and BMS-1001). Also, per-residue based virtual screening was employed to predict potential CTLA-4 inhibitors. Computational methods such as molecular docking, molecular dynamic simulation, virtual screening, and SNPinformatics were employed. These computational techniques revealed that BMS-1166 and BMS-1001 caused a motional movement in the monomers of PD-L1 to form a dimer, thereby preventing PD-L1-PD-1 interaction. Although the PD-L1 monomers have the same residues, their affinity for the BMS compounds differ. Two compounds ZINC04515726 and ZINC08985213 were identified as possible targets of CTLA-4. These two compounds elicited favourable interaction with CTLA- 4 facilitated by some crucial residues. Furthermore, the non-synonymous Single Nucleotide Polymorphism (nsSNPs) associated with ULBP6 were identified, and the effect of these nsSNPs on the interaction between NKGD2 and ULBP6 was also investigated. The first study (Chapter 4) investigates the structural dynamics and also provides insights into the mechanism of inhibition of BMS-1166 and BMS-1001 on PD-L1. The second study (Chapter 5) determines the binding site landscape of CTLA-4 and also employs binding site similarities between unrelated proteins to repurpose an inhibitor to target CTLA-4. The third study (Chapter 6) identifies deleterious polymorphisms associated with ULBP6. The effect of these polymorphisms on NKGD2-ULBP6 binding as a consequent on immune response is also explored in this chapter. Chapter 7 gives a detailed report on how the use of bioinformatics tools and strategies have aided and advanced the field of cancer immunotherapy. This study provides a thorough insight into the in-silico design, development and mechanism of action of small molecule inhibitors of PD-L1 and CTLA-4. Furthermore, this study gives insight into the polymorphic nature of ULBP6. Thence, the work presented in this study would serve a s a platform towards the design of small molecule inhibitors of CTLA-4 and PD-L1 with high therapeutic and less toxicity

Transcription-translation error: In-silico investigation of the structural and functional impact of deleterious single nucleotide polymorphisms in GULP1 gene

Nonsynonymous single nucleotide polymorphisms (nsSNPs) are one of the most common forms of mutations known to disrupt the product of translation thereby altering the protein structure-function relationship. GULP1 (PTB domain-containing engulfment adaptor protein 1) is an evolutionarily conserved adaptor protein that has been associated with glycated hemoglobin (HbA1c) in Genome-Wide Association Studies (GWAS). In order to understand the role of GULP1 in the etiology of diabetes, it is important to study some functional nsSNPs present within the GULP1 protein. We, therefore, used a SNPinformatics approach to retrieve, classify, and determine the stability effect of some nsSNPs. Y27C, G142D, A144T, and Y149C were jointly predicted by the pathogenic-classifying tools to be disease-causing, however, only G142D, A144T, and Y149C had their structural architecture perturbed as predicted by I-MUTANT and MuPro. Interestingly, G142D and Y149C occur at positions 142 and 149 of GULP1 which coincidentally are found within the binding site of GULP1. Protein-Protein interaction analysis also revealed that GULP1 interacted with 10 proteins such as Cell division cycle 5-like protein (CDC5L), ADP-ribosylation factor 6 (ARF6), Arf-GAP with coiled-coil (ACAP1), and Multiple epidermal growth factor-like domains protein 10 (MEGF10), etc. Taken together, rs1357922096, rs1264999716, and rs128246649 could be used as genetic biomarkers for the diagnosis of diabetes. However, being a computational study, these nsSNPs require experimental validation to explore their metabolic involvement in the pathogenesis of diseases

Computational and drug target analysis of functional single nucleotide polymorphisms associated with Haemoglobin Subunit Beta (HBB) gene

There is overwhelming evidence implicating Haemoglobin Subunit Beta (HBB) protein in the onset of beta thalassaemia. In this study for the first time, we used a combined SNP informatics and computer algorithms such as Neural network, Bayesian network, and Support Vector Machine to identify deleterious non-synonymous Single Nucleotide Polymorphisms (nsSNPs) present in the HBB gene. Our findings highlight three major mutation points (R31G, W38S, and Q128P) within the HBB gene sequence that have significant statistical and computational associations with the onset of beta thalassaemia. The dynamic simulation study revealed that R31G, W38S, and Q128P elicited high structural perturbation and instability, however, the wild type protein was considerably stable. Ten compounds with therapeutic potential against HBB were also predicted by structure-based virtual screening. Interestingly, the instability caused by the mutations was reversed upon binding to a ligand. This study has been able to predict potential deleterious mutants that can be further explored in the understanding of the pathological basis of beta thalassaemia and the design of tailored inhibitors

Strengthening Bioinformatics and Genomics Analysis Skills in Africa for Attainment of the Sustainable Development Goals Report of the 2nd Conference of the Nigerian Bioinformatics and Genomics Network

The second conference of the Nigerian Bioinformatics and Genomics Network (NBGN21) was held from October 11 to October 13, 2021. The event was organized by the Nigerian Bioinformatics and Genomics Network. A 1-day genomic analysis workshop on genome-wide association study and polygenic risk score analysis was organized as part of the conference. It was organized primarily as a research capacity building initiative to empower Nigerian researchers to take a leading role in this cutting-edge field of genomic data science. The theme of the conference was “Leveraging Bioinformatics and Genomics for the attainments of the Sustainable Development Goals.” The conference used a hybrid approach—virtual and in-person. It served as a platform to bring together 235 registered participants mainly from Nigeria and virtually, from all over the world. NBGN21 had four keynote speakers and four leading Nigerian scientists received awards for their contributions to genomics and bioinformatics development in Nigeria. A total of 100 travel fellowships were awarded to delegates within Nigeria. A major topic of discussion was the application of bioinformatics and genomics in the achievement of the Sustainable Development Goals (SDG3—Good Health and Well-Being, SDG4—Quality Education, and SDG 15—Life on Land [Biodiversity]). In closing, most of the NBGN21 conference participants were interviewed and interestingly they agreed that bioinformatics and genomic analysis of African genomes are vital in identifying population-specific genetic variants that confer susceptibility to different diseases that are endemic in Africa. The knowledge of this can empower African healthcare systems and governments for timely intervention, thereby enhancing good health and well-bein

Meta-analysis of African ancestry genome-wide association studies identified novel locus and validates multiple loci associated with kidney function

Despite recent efforts to increase diversity in genome-wide association studies (GWASs), most loci currently associated with kidney function are still limited to European ancestry due to the underlying sample selection bias in available GWASs. We set out to identify susceptibility loci associated with estimated glomerular filtration rate (eGFRcrea) in 80027 individuals of African-ancestry from the UK Biobank (UKBB), Million Veteran Program (MVP), and Chronic Kidney Disease genetics (CKDGen) consortia. We identified 8 lead SNPs, 7 of which were previously associated with eGFR in other populations. We identified one novel variant, rs77408001 which is an intronic variant mapped to the ELN gene. We validated three previously reported loci at GATM-SPATA5L1, SLC15A5 and AGPAT3. Fine-mapping analysis identified variants rs77121243 and rs201602445 as having a 99.9% posterior probability of being causal. Our results warrant designing bigger studies within individuals of African ancestry to gain new insights into the pathogenesis of Chronic Kidney Disease (CKD), and identify genomic variants unique to this ancestry that may influence renal function and disease

Molecular Dynamic Simulation Reveals Structure Differences in APOL1 Variants and Implication in Pathogenesis of Chronic Kidney Disease.

BACKGROUND: According to observational studies, two polymorphisms in the apolipoprotein L1 (APOL1) gene have been linked to an increased risk of chronic kidney disease (CKD) in Africans. One polymorphism involves the substitution of two amino-acid residues (S342G and I384M; known as G1), while the other involves the deletion of two amino-acid residues in a row (N388 and Y389; termed G2). Despite the strong link between APOL1 polymorphisms and kidney disease, the molecular mechanisms via which these APOL1 mutations influence the onset and progression of CKD remain unknown. METHODS: To predict the active site and allosteric site on the APOL1 protein, we used the Computed Atlas of Surface Topography of Proteins (CASTp) and the Protein Allosteric Sites Server (PASSer). Using an extended molecular dynamics simulation, we investigated the characteristic structural perturbations in the 3D structures of APOL1 variants. RESULTS: According to CASTp's active site characterization, the topmost predicted site had a surface area of 964.892 Å2 and a pocket volume of 900.792 Å3. For the top three allosteric pockets, the allostery probability was 52.44%, 46.30%, and 38.50%, respectively. The systems reached equilibrium in about 125 ns. From 0-100 ns, there was also significant structural instability. When compared to G1 and G2, the wildtype protein (G0) had overall high stability throughout the simulation. The root-mean-square fluctuation (RMSF) of wildtype and variant protein backbone Cα fluctuations revealed that the Cα of the variants had a large structural fluctuation when compared to the wildtype. CONCLUSION: Using a combination of different computational techniques, we identified binding sites within the APOL1 protein that could be an attractive site for potential inhibitors of APOL1. Furthermore, the G1 and G2 mutations reduced the structural stability of APOL1

Meta-Analysis and Multivariate GWAS Analyses in 77,850 Individuals of African Ancestry Identify Novel Variants Associated with Blood Pressure Traits

High blood pressure (HBP) has been implicated as a major risk factor for cardiovascular diseases in several populations, including individuals of African ancestry. Despite the elevated burden of HBP-induced cardiovascular diseases in Africa and other populations of African descent, limited genetic studies have been carried out to explore the genetic mechanism driving this phenomenon. We performed genome-wide association univariate and multivariate analyses of both systolic (SBP) and diastolic blood pressure (DBP) traits in 77, 850 individuals of African ancestry. We used summary statistics data from six independent cohorts, including the African Partnership for Chronic Disease Research (APCDR), the UK Biobank, and the Million Veteran Program (MVP). FUMA was used to annotate, prioritize, visualize, and interpret our findings to gain a better understanding of the molecular mechanism(s) underlying the genetics of BP traits. Finally, we undertook a Bayesian fine-mapping analysis to identify potential causal variants. Our meta-analysis identified 10 independent variants associated with SBP and 9 with DBP traits. Whilst our multivariate GWAS method identified 21 independent signals, 18 of these SNPs have been previously identified. SBP was linked to gene sets involved in biological processes such as synapse assembly and cell-cell adhesion via plasma membrane adhesion. Of the 19 independent SNPs identified in the BP meta-analysis, only 11 variants had posterior probability (PP) of > 50%, including one novel variant: rs562545 (MOBP, PP = 77%). To facilitate further research and fine-mapping of high-risk loci/variants in highly susceptible groups for cardiovascular disease and other related traits, large-scale genomic datasets are needed. Our findings highlight the importance of including ancestrally diverse populations in large GWASs and the need for diversity in genetic research