In silico Design of APOBEC3G Inhibitors Through Site-Specific Fluorination of a ssDNA Oligonucleotide

Overview

The human protein APOBEC3G (A3G) deaminates single-stranded DNA (ssDNA) by mutating deoxycytidine (DC) to deoxyuridine (DU). A3G dysregulation induces DNA damage resulting in cancer evolution and reduced sensitivity to genotoxic treatments, thereby conferring drug resistance. To improve prognosis of cancer infections, A3G inhibitors were designed using deoxy-zebularine (DZ), a DC analog which inhibits cytidine deamination, substituted in ssDNA from an A3G-CTD2 crystal structure. To improve binding affinity of the DZ-ssDNA oligonucleotide to A3G, 2’-deoxy-2’-fluoro-arabino nucleic acids (2’FANA) were placed in varying sites on the strand due to fluorine’s high electronegativity and hydrophobicity: indicators of increased enthalpic interactions. 2’FANA oligonucleotides additionally experience high duplex stability through a C2’-endo DNA-like sugar pucker which stabilizes noncanonical nucleic acid structures. Molecular dynamics (MD), a computational method that simulates molecular systems over time, was applied to study protein-inhibitor interactions. Use of 2’FANA-DC in the -1’ position decreased binding affinity based on hydrogen bond formation data. This trend was observed for all modifications made involving 2’FANA-DC at -1’. Dual modification of 2’FANA-DT at the -3’ site and 2’FANA-DA at the 1’ site induced the largest increase in binding affinity compared to the unmodified control, based on hydrogen bond formation data. Increased enthalpic interactions with minimal structural impact indicate the inhibitor model with the dual -3’ and 1’ site modifications as a drug candidate for the treatment of drug resistance in cancer infections and a preventative therapeutic targeting cancer evolution. In vitro NMR deamination assays will be used in the future to test this inhibitor model. Computational Drug Discovery for Alzheimer’s Using Gene Expression Analysis and Network Pharmacology Raheel Sarwar Massachusetts Academy of Mathematics and Science at Worcester Polytechnic Institute, Worcester, MA Instructor: Kevin Crowthers, Ph.D. Alzheimer’s disease (AD) is a neurodegenerative disease that is currently incurable. Symptoms of Alzheimer’s include impairment of cognitive functions, such as memory and learning ability, that progressively worsen over time. The complex pathophysiology of Alzheimer’s has resulted in a lack of effective drugs that inhibit the disease progression, and there is a demand for more effective drug discovery as the affected population continues to grow. Multi-targeting computational approaches may allow for more effectiveness of intervention by targeting multiple causal genes and their pathways, contrary to many existing approaches that have only targeted beta-amyloid, a well-known protein linked to Alzheimer’s (AD), and failed. This study utilizes three microarray datasets from the Gene Expression Omnibus (GEO). Genes were ranked within each dataset based on |logFC|> 1.5, p-value <0.001, gene ontology processes, and pathway annotations from STRING. The alpha-synuclein gene (SNCA) was identified as the most statistically relevant gene based on these criteria, and pathway analysis in KEGG suggests that it plays a role in senile plaque formation in Alzheimer’s. Gene2Drug was used in this study to target four highly correlated genes with SNCA – CALM1, TUBB3, SNAP25, and MAPT – and identify the top 10 inhibitors for Alzheimer’s intervention. The identified inhibitors in this study were Fluvoxamine, Levobunolol, Arcaine, Sulfaquinoxaline, Cefuroxime, Chelidonine, Perhexiline, DL-thiorphan, Ramipril, and Diphemanil Metilsulfate. Future extensions of this project include analyses of drug efficacy and Blood-Brain-Barrier (BBB) permeability, to facilitate a higher chance of success in animal model trials, drug testing phases, and the finding of a possible cure.

Competition history

• JSHS 2022 Category not listed

Resources

• National JSHS abstract book ↗

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