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Cervical cancer is the fourth most diagnosed cancer and the fourth leading cause of cancer death in women globally. Its onset and progression have been attributed to high-risk human papillomavirus (HPV) types, especially 16 and 18, while the Epstein–Barr virus (EBV) is believed to also significantly contribute to cervical cancer growth. The E6 protein associated with high-risk HPV strains, such as HPV16 and HPV18, is known for its role in promoting cervical cancer and other anogenital cancers. E6 proteins contribute to the malignant transformation of infected cells by targeting and degrading tumor suppressor proteins, especially p53. On the other hand, EBV nuclear antigen 1 (EBNA1) plays a crucial role in the maintenance and replication of the EBV genome in infected cells. EBNA1 is believed to increase HPV E6 and E7 levels, as well as c-MYC, and BIRC5 cellular genes in the HeLa cell line, implying that HPV/EBV co-infection accelerates cervical cancer onset and growth. Thus, the E6 and EBNA1 antigens of HPV and EBV, respectively, are attractive targets for cervical cancer immunotherapy. This study, therefore, virtually screened for potential drug candidates with good binding affinity to all three oncoviral proteins, HPV16 E6, HPV18 E6, and EBNA1. The compounds were further subjected to ADMET profiling, biological activity predictions, molecular dynamics (MD) simulations, and molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) calculations. A total of six compounds comprising ZINC000013380012, ZINC000070454124, ZINC000014588133, ZINC000085568136, ZINC000095909247, and ZINC000085597263 demonstrated very strong affinity (≤−60 kJ/mol) to the three oncoviral proteins (EBNA1, HPV16 E6, and HPV18 E6) after being subjected to docking, MD, and MM/PBSA. These compounds demonstrated relatively stronger binding than the controls used, inhibitors of EBNA1 (VK-1727) and HPV E6 (baicalein and gossypetin). Biological activity predictions also corroborated their antineoplastic, p53-enhancing, Pin1 inhibitory, and JAK2 inhibitory activities. Further experimental testing is required to validate the ability of the shortlisted compounds to silence the insidious effects of HPV E6 and EBNA1 proteins in cervical cancers. [ABSTRACT FROM AUTHOR]

The prognosis of mixed-lineage leukemia (MLL) has remained a significant health concern, especially for infants. The minimal treatments available for this aggressive type of leukemia has been an ongoing problem. Chromosomal translocations of the KMT2A gene are known as MLL, which expresses MLL fusion proteins. A protein called menin is an important oncogenic cofactor for these MLL fusion proteins, thus providing a new avenue for treatments against this subset of acute leukemias. In this study, we report results using the structure-based drug design (SBDD) approach to discover potential novel MLL-mediated leukemia inhibitors from natural products against menin. The three-dimensional (3D) protein model was derived from Protein Databank (Protein ID: 4GQ4), and EasyModeller 4.0 and I-TASSER were used to fix missing residues during rebuilding. Out of the ten protein models generated (five from EasyModeller and I-TASSER each), one model was selected. The selected model demonstrated the most reasonable quality and had 75.5% of residues in the most favored regions, 18.3% of residues in additionally allowed regions, 3.3% of residues in generously allowed regions, and 2.9% of residues in disallowed regions. A ligand library containing 25,131 ligands from a Chinese database was virtually screened using AutoDock Vina, in addition to three known menin inhibitors. The top 10 compounds including ZINC000103526876, ZINC000095913861, ZINC000095912705, ZINC000085530497, ZINC000095912718, ZINC000070451048, ZINC000085530488, ZINC000095912706, ZINC000103580868, and ZINC000103584057 had binding energies of −11.0, −10.7, −10.6, −10.2, −10.2, −9.9, −9.9, −9.9, −9.9, and −9.9 kcal/mol, respectively. To confirm the stability of the menin–ligand complexes and the binding mechanisms, molecular dynamics simulations including molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) computations were performed. The amino acid residues that were found to be potentially crucial in ligand binding included Phe243, Met283, Cys246, Tyr281, Ala247, Ser160, Asn287, Asp185, Ser183, Tyr328, Asn249, His186, Leu182, Ile248, and Pro250. MI-2-2 and PubChem CIDs 71777742 and 36294 were shown to possess anti-menin properties; thus, this justifies a need to experimentally determine the activity of the identified compounds. The compounds identified herein were found to have good pharmacological profiles and had negligible toxicity. Additionally, these compounds were predicted as antileukemic, antineoplastic, chemopreventive, and apoptotic agents. The 10 natural compounds can be further explored as potential novel agents for the effective treatment of MLL-mediated leukemia. [ABSTRACT FROM AUTHOR]

Buruli ulcer (BU), a severe skin disease is caused by Mycobacterium ulcerans. There are concerns of therapeutic inefficacy of existing drugs coupled with chemoresistance. Databases have been shown to augment data mining and integrative systems pharmacology approaches towards the search for novel therapeutic moieties. So far, there is no known integrated database solely dedicated to BU drug discovery. In this work, Buruli ulcer database (BuDb) is a "one-stop-shop" knowledgebase for supporting BU drug discovery. It contains both manually verified literature and database-curated data on BU. The BuDb provides comprehensive information on the various drug targets, tested compounds, existing drugs, ethnopharmacological plants and information on the genome of M. ulcerans. It also contains cross-referenced links to databases including PubMed, PubChem, DrugBank, NCBI, Gene Ontology (GO), UniProt, Prota4u, String database, KEGG Pathway and KEGG genome database. The BuDb has been implemented with accessibility features such as keyword and specific searches as well as browsing. BuDb is the first useful online repository of its kind integrated with enriched datasets that can aid in the discovery of new biotherapeutic entities for BU. BuDb can be freely accessed at http://197.255.126.13:3000/. BuDb is the first online database that support the discovery of new biotherapeutic entities for Buruli ulcer. BuDb provides comprehensive information on the various drug targets, tested compounds, existing drugs and ethnopharmacological plants. BuDb is cross-referenced to functional genomic data, pathways and gene ontologies relating to Mycobacterium ulcerans. [ABSTRACT FROM AUTHOR]

Recent reports of resistance to artemisinin-based combination drugs necessitate the need to discover novel antimalarial compounds. The present study was aimed at identifying novel antimalarial compounds from natural product libraries using computational methods. Plasmodium falciparum is highly dependent on the pyrimidine biosynthetic pathway, a de novo pathway responsible for the production of pyrimidines, and the parasite lacks the pyrimidine salvage enzymes. The P. falciparum thymidylate monophosphate kinase (Pf TMPK) is an important protein necessary for rapid DNA replication; however, due to its broad substrate specificity, the protein is distinguished from its homologs, making it a suitable drug target. Compounds from AfroDB, a database of natural products originating from Africa, were screened virtually against Pf TMPK after filtering the compounds for absorption, distribution, metabolism, excretion, and toxicity (ADMET)-acceptable compounds with FAF-Drugs4. Thirteen hits with lower binding energies than thymidine monophosphate were selected after docking. Among the thirteen compounds, ZINC13374323 and ZINC13365918 with binding energies of −9.4 and −8.9 kcal/mol, respectively, were selected as plausible lead compounds because they exhibited structural properties that ensure proper binding at the active site and inhibitory effect against Pf TMPK. ZINC13374323 (also called aurantiamide acetate) is known to exhibit anti-inflammatory and antiviral activities, and ZINC13365918 exhibits antileishmanial activity. Furthermore, aurantiamide acetate, which is commercially available, is a constituent of Artemisia annua , the herb from which artemisinin was derived. The compound also shares interactions with several residues with a potent thymidine analog inhibitor of Pf TMPK. The anti-plasmodial activity of aurantiamide acetate was evaluated in vitro , and the mean half-maximal inhibitory concentration (IC50) was 69.33 μM when synchronized P. falciparum 3D7 culture was used as compared to IC50 > 100 μM with asynchronized culture. The significance of our findings within the context of malaria treatment strategies and challenges is discussed. [ABSTRACT FROM AUTHOR]

Over 200 million people worldwide are affected annually by schistosomiasis with debilitating socio-economic effects. Praziquantel remains the main chemotherapy against this neglected tropical disease but there are reports of drug resistance. Therefore, necessitating the need to identify potential biotherapeutic molecules. The study describes the first deep learning (DL)-based computational models for predicting inhibitors of Schistosoma mansoni Thioredoxin glutathione reductase (SmTGR), which is an essential protein for the survival of the helminths in the host. The state-of-the-art performance of DL in similar applications makes it ideal to deploy on bioactive datasets of the SmTGR drug target. Cost-sensitive deep neural network classifiers were trained using the binary classification approach. Based on the area under curve (AUC) of the receiver operating characteristic (ROC) Curve scores (86.3–86.5%), the five best models generated were able to classify inhibitors with high accuracy (85–90%). Additionally, the DL classifier outperformed random forest by far. This is a proof of concept that deep neural networks can efficiently and robustly classify active schistosomal molecules from inactive. The generated models could be used to screen large-scale compound libraries to prioritize potential inhibitors for experimental characterization. The study developed cost-sensitive deep neural network (DNN) classifiers for predicting anti-schistosomal molecules. This is a plausible proof of concept since the DNNs outperformed other models including random forest. The DNNs can be deployed to screen large-scale compound libraries to identify potential biotherapeutic entities against Schistosoma mansoni thioredoxin glutathione reductase. [ABSTRACT FROM AUTHOR]

Calcium channels (CCs), a group of ubiquitously expressed membrane proteins, are involved in many pathophysiological processes of protozoan parasites. Our understanding of CCs in cell signaling, organelle function, cellular homeostasis, and cell cycle control has led to improved insights into their structure and functions. In this article, we discuss CCs characteristics of five major protozoan parasites Plasmodium, Leishmania, Toxoplasma, Trypanosoma, and Cryptosporidium. We provide a comprehensive review of current antiparasitic drugs and the potential of using CCs as new therapeutic targets. Interestingly, previous studies have demonstrated that human CC modulators can kill or sensitize parasites to antiparasitic drugs. Still, none of the parasite CCs, pumps, or transporters has been validated as drug targets. Information for this review draws from extensive data mining of genome sequences, chemical library screenings, and drug design studies. Parasitic resistance to currently approved therapeutics is a serious and emerging threat to both disease control and management efforts. In this article, we suggest that the disruption of calcium homeostasis may be an effective approach to develop new anti‐parasite drug candidates and reduce parasite resistance. Highlights: This article maps out known small molecule agents interfering with calcium as well as critical target gene sets which have been scantily explored. Calcium homeostasis is critical for agility, metamorphosis, intracellular survival, and host cell invasion and egress essential for Apicomplexan and Kinetoplexan parasite pathogenesis. The article explored calcium channels as a treasure trove for target based drug discovery, since ion channels are the most drugable class of proteins and these genes bear relatively low homology with the human host. [ABSTRACT FROM AUTHOR]