Impact of DNA ligase 1 and IIIα interactions with APE1 and polß on the efficiency of base excision repair pathway at the downstream steps.

Base excision repair (BER) requires a tight coordination between the repair enzymes through protein-protein interactions and involves gap filling by DNA polymerase (pol) ß and subsequent nick sealing by DNA ligase (LIG) 1 or LIGIIIα at the downstream steps. Apurinic/apyrimidinic-endonuclease 1 (APE1), by its exonuclease activity, proofreads 3' mismatches incorporated by polß during BER. We previously reported that the interruptions in the functional interplay between polß and the BER ligases result in faulty repair events. Yet, how the protein interactions of LIG1 and LIGIIIα could affect the repair pathway coordination during nick sealing at the final steps remains unknown. Here, we demonstrate that LIGIIIα interacts more tightly with polß and APE1 than LIG1, and the N-terminal noncatalytic region of LIG1 as well as the catalytic core and BRCT domain of LIGIIIα mediate interactions with both proteins. Our results demonstrated less efficient nick sealing of polß nucleotide insertion products in the absence of LIGIIIα zinc-finger domain and LIG1 N-terminal region. Furthermore, we showed a coordination between APE1 and LIG1/LIGIIIα during the removal of 3' mismatches from the nick repair intermediate on which both BER ligases can seal noncanonical ends or gap repair intermediate leading to products of single deletion mutagenesis. Overall results demonstrate the importance of functional coordination from gap filling by polß coupled to nick sealing by LIG1/LIGIIIα in the presence of proofreading by APE1, which is mainly governed by protein-protein interactions and protein-DNA intermediate communications, to maintain repair efficiency at the downstream steps of the BER pathway.

Cancer pharmacoinformatics: Databases and analytical tools.

Cancer is a subject of extensive investigation, and the utilization of omics technology has resulted in the generation of substantial volumes of big data in cancer research. Numerous databases are being developed to manage and organize this data effectively. These databases encompass various domains such as genomics, transcriptomics, proteomics, metabolomics, immunology, and drug discovery. The application of computational tools into various core components of pharmaceutical sciences constitutes "Pharmacoinformatics", an emerging paradigm in rational drug discovery. The three major features of pharmacoinformatics include (i) Structure modelling of putative drugs and targets, (ii) Compilation of databases and analysis using statistical approaches, and (iii) Employing artificial intelligence/machine learning algorithms for the discovery of novel therapeutic molecules. The development, updating, and analysis of databases using statistical approaches play a pivotal role in pharmacoinformatics. Multiple software tools are associated with oncoinformatics research. This review catalogs the databases and computational tools related to cancer drug discovery and highlights their potential implications in the pharmacoinformatics of cancer.

Impact of DNA ligase inhibition on the nick sealing of polß nucleotide insertion products at the downstream steps of base excision repair pathway.

DNA ligase (LIG) I and IIIα finalize base excision repair (BER) by sealing a nick product after nucleotide insertion by DNA polymerase (pol) ß at the downstream steps. We previously demonstrated that a functional interplay between polß and BER ligases is critical for efficient repair, and polß mismatch or oxidized nucleotide insertions confound final ligation step. Yet, how targeting downstream enzymes with small molecule inhibitors could affect this coordination remains unknown. Here, we report that DNA ligase inhibitors, L67 and L82-G17, slightly enhance hypersensitivity to oxidative stress-inducing agent, KBrO3, in polß+/+ cells more than polß-/- null cells. We showed less efficient ligation after polß nucleotide insertions in the presence of the DNA ligase inhibitors. Furthermore, the mutations at the ligase inhibitor binding sites (G448, R451, A455) of LIG1 significantly affect nick DNA binding affinity and nick sealing efficiency. Finally, our results demonstrated that the BER ligases seal a gap repair intermediate by the effect of polß inhibitor that diminishes gap filling activity. Overall, our results contribute to understand how the BER inhibitors against downstream enzymes, polß, LIG1, and LIGIIIα, could impact the efficiency of gap filling and subsequent nick sealing at the final steps leading to the formation of deleterious repair intermediates.

Prediction of Mycobacterium tuberculosis cell wall permeability using machine learning methods.

Tuberculosis (TB) caused by the bacteria Mycobacterium tuberculosis (M. tb), continues to pose a significant worldwide health threat. The advent of drug-resistant strains of the disease highlights the critical need for novel treatments. The unique cell wall of M. tb provides an extra layer of protection for the bacteria and hence only compounds that can penetrate this barrier can reach their targets within the bacterial cell wall. The creation of a reliable machine learning (ML) model to predict the mycobacterial cell wall permeability of small molecules is presented in this work and four ML algorithms, including Random Forest, Support Vector Machines (SVM), k-nearest Neighbour (k-NN) and Logistic Regression were trained on a dataset of 5368 compounds. RDKit and Mordred toolkits were used to calculate features. To determine the most effective model, various performance metrics were used such as accuracy, precision, recall, F1 score, and area under the receiver operating characteristic curve. The best-performing model was further refined with hyperparameter tuning and tenfold cross-validation. The SVM model with filtering outperformed the other machine learning models and demonstrated 80.26% and 81.13% accuracy on the test and validation datasets, respectively. The study also provided insights into the molecular descriptors that play the most important role in predicting the ability of a molecule to pass the M. tb cell wall, which could guide future compound design. The model is available at https://github.com/PGlab-NIPER/MTB_Permeability .

DNA ligase I fidelity mediates the mutagenic ligation of pol ß oxidized and mismatch nucleotide insertion products in base excision repair.

DNA ligase I (LIG1) completes the base excision repair (BER) pathway at the last nick-sealing step after DNA polymerase (pol) ß gap-filling DNA synthesis. However, the mechanism by which LIG1 fidelity mediates the faithful substrate-product channeling and ligation of repair intermediates at the final steps of the BER pathway remains unclear. We previously reported that pol ß 8-oxo-2'-deoxyribonucleoside 5'-triphosphate insertion confounds LIG1, leading to the formation of ligation failure products with a 5'-adenylate block. Here, using reconstituted BER assays in vitro, we report the mutagenic ligation of pol ß 8-oxo-2'-deoxyribonucleoside 5'-triphosphate insertion products and an inefficient ligation of pol ß Watson-Crick-like dG:T mismatch insertion by the LIG1 mutant with a perturbed fidelity (E346A/E592A). Moreover, our results reveal that the substrate discrimination of LIG1 for the nicked repair intermediates with preinserted 3'-8-oxodG or mismatches is governed by mutations at both E346 and E592 residues. Finally, we found that aprataxin and flap endonuclease 1, as compensatory DNA-end processing enzymes, can remove the 5'-adenylate block from the abortive ligation products harboring 3'-8-oxodG or the 12 possible noncanonical base pairs. These findings contribute to the understanding of the role of LIG1 as an important determinant in faithful BER and how a multiprotein complex (LIG1, pol ß, aprataxin, and flap endonuclease 1) can coordinate to prevent the formation of mutagenic repair intermediates with damaged or mismatched ends at the downstream steps of the BER pathway.

Prognostic utility of the ovarian cancer secretome: a systematic investigation.

BACKGROUND: Ovarian cancer is usually detected at an advanced stage with frequent recurrence. The recurrence-free survival and overall survival is influenced by the age at diagnosis, tumor stage and histological subtype. Nonetheless, quantifiable prognostic biomarkers are needed for early identification of the high-risk patients and for personalized medicine. Several studies link tumor-specific dysregulated expression of certain proteins with ovarian cancer prognosis. However, careful investigation of presence of these prognostically relevant proteins in ovarian cancer secretome is lacking. OBJECTIVE: To critically analyze the recent published data on prognostically relevant proteins for ovarian cancer and to carefully search how many of them are reported in the published ovarian cancer secretome datasets. DESIGN: A search for relevant studies in the past 2 years was conducted in PubMed and a comprehensive list of proteins associated with the ovarian cancer prognosis was prepared. These were cross-referred to the published ovarian cancer secretome profiles. The proteins identified in the secretome were further shortlisted based on a scoring strategy employing stringent criteria. RESULTS: A panel of seven promising secretory biomarkers associated with ovarian cancer prognosis is proposed. CONCLUSION: Scanning the ovarian cancer secretome datasets provides the opportunity to identify if tumor-specific biomarkers could be tested as secretory biomarkers. Detecting their levels in the body fluid would be more advantageous than evaluating the expression in the tissue, since it could be monitored multiple times over the course of the disease to have a better judgment of the prognosis and response to therapy.

N-glycosylation status of Trop2 impacts its surface density, interaction with claudin-7 and exosomal release.

Trophoblast antigen 2 (Trop2) is a type I transmembrane protein post-translationally modified by N-linked glycosylation. It was originally detected in trophoblasts but was later shown to be frequently overexpressed in many epithelial cancers. Recently, anti-Trop2 antibody-drug conjugate has been FDA approved for the treatment of metastatic triple-negative breast and urothelial carcinomas, making it an important tumor antigen. The current study explored the significance of N-glycosylation of Trop2 by substituting specific N-glycan addition sites by site-directed mutagenesis. The mutant proteins were characterized in transiently transfected HEK293 cells. The N-glycosylation mutants did not affect protein expression, stability, dimerization ability and matriptase mediated cleavage. However, N120A and N208A mutants showed decreased interaction with its binding partner claudin-7. Our earlier reported Trop2 mutant V194A, which shows aberrant glycosylation, also displayed hampered interaction with claudin-7. To further characterize the mutants, stable clones expressing wild type and mutant Trop2 were generated in OVCAR3 cell line. Interestingly, surface biotinylation assay showed significantly higher surface expression of N120A and N208A mutants whereas surface localization was drastically reduced for V194A Trop2 mutant. Though overexpression of wild type Trop2 did not cause any change in fibronectin-mediated FAK (Focal adhesion kinase) signaling; expression of N120A mutant, surprisingly downregulated FAK signaling. Furthermore, exosomal release of Trop2 was also decreased in N120A and N208A mutants. This data suggests that site-specific N-glycan addition determines Trop2 surface density, claudin-7 interaction and exosomal release.

DNA ligase I variants fail in the ligation of mutagenic repair intermediates with mismatches and oxidative DNA damage.

DNA ligase I (LIG1) joins DNA strand breaks during DNA replication and repair transactions and contributes to genome integrity. The mutations (P529L, E566K, R641L and R771W) in LIG1 gene are described in patients with LIG1-deficiency syndrome that exhibit immunodeficiency. LIG1 senses 3'-DNA ends with a mismatch or oxidative DNA base inserted by a repair DNA polymerase. However, the ligation efficiency of the LIG1 variants for DNA polymerase-promoted mutagenesis products with 3'-DNA mismatches or 8-oxo-2'-deoxyguanosine (8-oxodG) remains undefined. Here, we report that R641L and R771W fail in the ligation of nicked DNA with 3'-8-oxodG, leading to an accumulation of 5'-AMP-DNA intermediates in vitro. Moreover, we found that the presence of all possible 12 non-canonical base pairs variously impacts the ligation efficiency by P529L and R771W depending on the architecture at the DNA end, whereas E566K exhibits no activity against all substrates tested. Our results contribute to the understanding of the substrate specificity and mismatch discrimination of LIG1 for mutagenic repair intermediates and the effect of non-synonymous mutations on ligase fidelity.

Association of Serum Ferritin Levels with Hematological Manifestations in Systemic Lupus Erythematosus Patients from Western India.

OBJECTIVE: To identify the hematological manifestations and its association with serum ferritin levels in SLE patients from Western India. METHODS: Ninety clinically diagnosed SLE patients fulfilling ACR criteria were included. Disease activity was assessed at the time of evaluation using Systemic Lupus Erythematosus Disease Activity Index (SLEDAI). Sera were tested for serum ferritin levels by ELISA (Calbiotech, USA). Autoantibodies such as ANA, anti-dsDNA by indirect immunofluorescence test (IFA- Bio-Rad, USA) and anti-cardiolipin antibodies (ACA) to IgG and IgM isotypes and Anti-ß2 GP antibodies to IgG and IgM isotypes were detected by ELISA using commercially available kits (Euroimmun, Lubeck, Germany). RESULTS: Out of 90 SLE patients studied, 41 patients (45.6%) showed hematological abnormalities, where anemia (82.9%), leucopenia (26.8%), autoimmune hemolytic anemia (AIHA) (14.6%) and idiopathic thrombocytopenic purpura (ITP) were noted in (34.1%) patients. Mean±SD serum ferritin levels among SLE patients were 270.2±266.0 ng/ml as compared to 29.0±15.8 ng/ml healthy normal controls (p<0.0001). A positive correlation between serum ferritin levels and SLEDAI scores (r= 0.2640, p=0.0124) and anti-dsDNA positivity was noted (r=0.32, p<0.0001). Serum ferritin levels were negatively correlated with hemoglobin levels (r=-0.5964, p=0.0001), WBC count (r=-0.1705, p=0.2316), platelet count ((r=-0.1701, P=0.2375), C3 levels (r=-0.4417, p=0.0034) and C4 levels (r=-0.0363, p=0.8215). CONCLUSIONS: Serum ferritin is an excellent marker of SLE which can be used for an evaluation of disease activity particularly in active stage of the disease mainly in patients having hematological and renal manifestations.

DeepADRA2A: predicting adrenergic α2a inhibitors using deep learning.

Adrenergic α2a (ADRA2A) receptors play a crucial role in modulating various physiological actions, thereby influencing the proper functioning of different systems in the body. ADRA2A regulation is associated with a wide range of effects, including alterations in blood pressure, hypertension, heightened heart rate, etc. Inhibition of these receptors results in the release of noradrenaline, leading to heightened physiological activity, improved alertness, reduced blood pressure, and alleviation of hypertension. Conventional approaches for identifying ADRA2A inhibitors are burdened with high costs, labor-intensive procedures, and time-consuming processes. In light of these challenges, leveraging the power of artificial intelligence offers a promising solution for drug discovery and development. This study endeavors to harness the potential of artificial intelligence to develop robust models capable of accurately predicting ADRA2A inhibitors and non-inhibitors. By doing so, we aim to streamline and expedite the identification of potential drug candidates in this domain. In this study, we employed four different machine learning (ML) and deep learning (DL) algorithms to develop prediction models based on various molecular descriptors (1D, 2D, and molecular fingerprints). Among these models, the DL-based prediction model demonstrated superior performance, achieving accuracies of 98.25% and 97.23% on the training and test datasets, respectively. These results underscore the efficacy of DL-based model, as a highly effective tool for predicting ADRA2A inhibitors. The model is made available at https://github.com/PGlab-NIPER/DeepADRA2A.git.Communicated by Ramaswamy H. Sarma.

Comparison of Anti-Trop2 Extracellular Domain Antibodies Generated Against Peptide and Protein Immunogens for Targeting Trop2-Positive Tumour Cells.

Trophoblast antigen 2 (Trop2) is a transmembrane glycoprotein upregulated in multiple solid tumours. Trop2-based passive immunotherapies are in clinical trials, while Trop2 targeting CAR-T cell-based therapies are also reported. Information about its T- and B-cell epitopes is needed for it to be pursued as an active immunotherapeutic target. This study focused on identification of immunodominant epitopes in the Trop2 extracellular domain (ECD) that can mount an efficient anti-Trop2 antibody response. In silico analysis using various B-cell epitope prediction tools was carried out to identify linear and conformational B-cell epitopes in the ECD of Trop2. Three linear peptide immunogens were shortlisted and synthesized. Along with linear peptides, truncated Trop2 ECD that possesses combination of linear and conformational epitopes was also selected. Recombinant protein immunogen was produced in 293-F suspension culture system and affinity purified. Antisera against different immunogens were characterized by ELISA and Western blotting. Two anti-peptide antisera detected recombinant and ectopically expressed Trop2 protein; however, they were unable to recognize the endogenous Trop2 protein expressed by cancer cells. Antibodies against truncated Trop2 ECD could bind to the endogenous Trop2 expressed on the surface of cancer cells. In addition to their high avidity, these polyclonal anti-sera against truncated Trop2 protein also mediated antibody-dependent cell-mediated cytotoxicity (ADCC). In summary, our comparative analysis demonstrated the utility of truncated Trop2 ECD as a promising candidate to be pursued as an active immunotherapeutic molecule against Trop2-positive cancer cells.

Proteolytic cleavage of Trop2 at Arg87 is mediated by matriptase and regulated by Val194.

Proteolytic processing is an important post-translational modification affecting protein activity and stability. In the current study, we investigate the N-terminal cleavage of Trop2, a protein which is overexpressed in many cancers. We demonstrate that Trop2 is cleaved at Arg87 by a transmembrane serine protease, matriptase. Homology modeling and site-directed mutagenesis of amino acids in close proximity to the matriptase cleavage site reveal the importance of Val194 in regulating Trop2 cleavage. Co-immunoprecipitation studies confirm that amino acid substitutions at Arg87, Thr88, Lys189, Val194, and His195 do not affect Trop2 dimerization. However, cleavage of wild-type Trop2 by matriptase is inhibited when it is allowed to dimerize with a V194 A mutant monomer, further confirming the role of Val194 in matriptase-mediated N-terminal cleavage.