Periodontitis, a chronic inflammatory oral condition triggered by bacteria, archaea, viruses, and eukaryotic organisms, is a well-known and widespread disease around the world. While there are effective treatments for periodontitis, there are also several shortcomings associated with its management, including limited treatment options, the risk of recurrence, and the high cost of treatment. Our goal is to develop a more efficient, systematic drug design for periodontitis before clinical trials. We work on systems drug discovery and design for periodontitis treatment via systems biology and deep learning methods. We first applied big database mining to build a candidate genome-wide genetic and epigenetic network (GWGEN), which includes a protein-protein interaction network (PPIN) and a gene regulatory network (GRN) for periodontitis and healthy control. Next, based on the unhealthy and healthy microarray data, we applied system identification and system order detection methods to remove false positives in candidate GWGENs to obtain real GWGENs for periodontitis and healthy control, respectively. After the real GWGENs were obtained, we picked out the core GWGENs based on how significant the proteins and genes were via the principal network projection (PNP) method. Finally, referring to the annotation of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, we built up the core signaling pathways of periodontitis and healthy control. Consequently, we investigated the pathogenic mechanism of periodontitis by comparing their core signaling pathways. By checking up on the downstream core signaling pathway and the corresponding cellular dysfunctions of periodontitis, we identified the fos proto-oncogene, AP-1 Transcription Factor Subunit (FOS), TSC Complex Subunit 2 (TSC2), Forkhead Box O1 (FOXO1), and nuclear factor kappa-light chain enhancer of activated B cells (NF-$\mathsf{\kappa }$B) as significant biomarkers on which we could find candidate molecular drugs to target. To achieve our ultimate goal of designing a combination of molecular drugs for periodontitis treatment, a deep neural network (DNN)-based drug-target interaction (DTI) model was employed. The model is trained with the existing drug-target interaction databases for the prediction of candidate molecular drugs for significant biomarkers. Finally, we filter out brucine, disulfiram, verapamil, and PK-11195 as potential molecular drugs to be combined as a multiple-molecular drug to target the significant biomarkers based on drug design specifications, i.e., adequate drug regulation ability, high sensitivity, and low toxicity. In conclusion, we investigated the pathogenic mechanism of periodontitis by leveraging systems biology methods and thoroughly developed a therapeutic option for periodontitis treatment via the prediction of a DNN-based DTI model and drug design specifications. Full article

Rheumatoid arthritis (RA) is one of the most common autoimmune diseases, affecting 0.5% to 1% of the population. It could ultimately result in joint destruction, functional decline, work disability, and enhanced mortality. Cyclic citrullinated peptide antibodies (CCP Abs) are useful biomarkers for the early detection and diagnosis of RA. In this study, we used plant viral-based expression vectors that produce rapidly large quantities of CCP-specific monoclonal antibodies. Heavy and light chain genes of a CCP monoclonal antibody (CCP mAb) were cloned from the hybridoma cell (12G1) and introduced into two separate plant viral-based expression vectors, TMV and PVX. A cyclic citrullinated peptide monoclonal antibody was produced in Nicotiana benthamiana through an Agrobacterium-mediated transient expression system. The expression of CCP mAb in tobacco plants was confirmed by dot blot, western blot analysis, and enzyme-linked immunosorbent assays (ELISA). It was shown that tobacco plants could accumulate CCP mAbs up to 0.35% of total soluble protein. Accumulated CCP mAb from infiltrated leaves was purified by protein G affinity chromatography. Immunoblot assays and ELISA showed plant-produced CCP mAbs successfully bound to a synthetic CCP peptide antigen. This system provides a fast strategy for the production of pharmaceutical CCP mAbs in tobacco plants. Full article

Serine integrases are emerging as one of the most powerful biological tools for biotechnology. Over the past decade, many research papers have been published on the use of serine integrases in synthetic biology. In this review, we aim to systematically summarize the various studies ranging from structure and the catalytic mechanism to genetic design and interdisciplinary applications. First, we introduce the classification, structure, and catalytic model of serine integrases. Second, we present a timeline with milestones that describes the representative achievements. Then, we summarize the applications of serine integrases in genome engineering, genetic design, and DNA assembly. Finally, we discuss the potential of serine integrases for advancing interdisciplinary research. We anticipate that serine integrases will be further expanded as a versatile genetic toolbox for synthetic biology applications. Full article

Even more than 60 years after its introduction into the clinic, cyclophosphamide (CP), which belongs to the group of alkylating cytostatics, is indispensable for the treatment of cancer. This is despite the fact that its exact mechanism of action was unknown until a few years ago, and therefore, all attempts to improve the effectiveness of CP failed. The reason for not knowing the mechanism of action was the uncritical transfer of the chemical processes that lead to the formation of the actual alkylating CP metabolite phosphoreamide mustard (PAM) in vitro to in vivo conditions. In vitro—e.g., in cell culture experiments—PAM is formed by β-elimination of acrolein from the pharmacologically active CP metabolite aldophosphamide (ALD). In vivo, on the other hand, it is formed by enzymatic cleavage of ALD by phosphodiesterases (PDE) with the formation of 3-hydroxypropanal (HPA). The discovery of HPA as a cyclophosphamide metabolite, together with the discovery that HPA is a proapoptotic aldehyde and the discovery that the cell death event in therapy with CP is DNA-alkylation-initiated p53-controlled apoptosis, led to the formulation of a mechanism of action of CP and other oxazaphosphorine cytostatics (OX). This mechanism of action is presented here and is confirmed by newly developed CP-like compounds with lower toxicity and an order of magnitude better effectiveness. Full article