Prediction of Human Papillomavirus-Host Oncoprotein Interactions Using Deep Learning.

Background: Human papillomavirus (HPV) causes disease through complex interactions between viral and host proteins, with the PI3K signaling pathway playing a key role. Proteins like AKT, IQGAP1, and MMP16 are involved in HPV-related cancer development. Traditional methods for studying protein-protein interactions (PPIs) are labor-intensive and time-consuming.

Design of Inhibitors That Target the Menin-Mixed-Lineage Leukemia Interaction.

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.

In Silico Discovery of Potential Inhibitors Targeting the RNA Binding Loop of ADAR2 and 5-HT2CR from Traditional Chinese Natural Compounds.

Adenosine deaminase acting on RNA 2 (ADAR2) is an important enzyme involved in RNA editing processes, particularly in the conversion of adenosine to inosine in RNA molecules. Dysregulation of ADAR2 activity has been implicated in various diseases, including neurological disorders (including schizophrenia), inflammatory disorders, viral infections, and cancers. Therefore, targeting ADAR2 with small molecules presents a promising therapeutic strategy for modulating RNA editing and potentially treating associated pathologies.

Investigating Environmental Determinants of Soil-Transmitted Helminths Transmission using GPS Tracking and Metagenomics Technologies.

Background: The Global Health community aims to eliminate soil-transmitted helminth (STH) infections by 2030. Current preventive methods such as Mass Drug Administration, WASH practices, and health education needs to be complimented to halt transmission. We tracked the movement of hookworm-infected and non-infected persons and investigated soil factors in the places they frequented within an endemic community to further understand the role of human movement and sources of infections.

Molecular Docking and Dynamics Simulation Studies Predict Potential Anti-ADAR2 Inhibitors: Implications for the Treatment of Cancer, Neurological, Immunological and Infectious Diseases.

Altered RNA editing has been linked to several neurodevelopmental disorders, including autism spectrum disorder (ASD) and intellectual disability, in addition to depression, schizophrenia, some cancers, viral infections and autoimmune disorders. The human ADAR2 is a potential therapeutic target for managing these various disorders due to its crucial role in adenosine to inosine editing. This study applied consensus scoring to rank potential ADAR2 inhibitors after performing molecular docking with AutoDock Vina and Glide (Maestro), using a library of 35,161 compounds obtained from traditional Chinese medicine.

Cheminformatics-Based Study Identifies Potential Ebola VP40 Inhibitors.

The Ebola virus (EBOV) is still highly infectious and causes severe hemorrhagic fevers in primates. However, there are no regulatorily approved drugs against the Ebola virus disease (EVD). The highly virulent and lethal nature of EVD highlights the need to develop therapeutic agents.

Multi-dimensional structural footprint identification for the design of potential scaffolds targeting METTL3 in cancer treatment from natural compounds.

Context: [Formula: see text]-adenosine-methyltransferase (METTL3) is the catalytic domain of the 'writer' proteins which is involved in the post modifications of [Formula: see text]-methyladinosine ([Formula: see text]). Though its activities are essential in many biological processes, it has been implicated in several types of cancer. Thus, drug developers and researchers are relentlessly in search of small molecule inhibitors that can ameliorate the oncogenic activities of METTL3.

Artificial Intelligence, Machine Learning, and Big Data for Ebola Virus Drug Discovery.

The effect of Ebola virus disease (EVD) is fatal and devastating, necessitating several efforts to identify potent biotherapeutic molecules. This review seeks to provide perspectives on complementing existing work on Ebola virus (EBOV) by discussing the role of machine learning (ML) techniques in the prediction of small molecule inhibitors of EBOV. Different ML algorithms have been used to predict anti-EBOV compounds, including Bayesian, support vector machine, and random forest algorithms, which present strong models with credible outcomes.

Inhibiting Sterol Methyltransferase to Identify Lead Compounds Using Molecular Modelling.

The recent outlook of leishmaniasis as a global public health concern coupled with the reportage of resistance and lack of efficacy of most antileishmanial drugs calls for a concerted effort to find new leads. The study combined and in vitro approaches to identify novel potential synthetic small-molecule inhibitors targeting the sterol methyltransferase (SMT). The SMT enzyme in the ergosterol biosynthetic pathway is required for the parasite's membrane fluidity, distribution of membrane proteins, and control of the cell cycle.

Structure-Based Identification of Natural-Product-Derived Compounds with Potential to Inhibit HIV-1 Entry.

Broadly neutralizing antibodies (bNAbs) are potent in neutralizing a wide range of HIV strains. VRC01 is a CD4-binding-site (CD4-bs) class of bNAbs that binds to the conserved CD4-binding region of HIV-1 envelope (env) protein. Natural products that mimic VRC01 bNAbs by interacting with the conserved CD4-binding regions may serve as a new generation of HIV-1 entry inhibitors by being broadly reactive and potently neutralizing.

Computer-aided identification of potential inhibitors against glutathione -transferase 3.

Hookworm infection is caused by the blood-feeding hookworm gastrointestinal nematodes. Its harmful effects include anemia and retarded growth and are common in the tropics. A current control method involves the mass drug administration of synthetic drugs, mainly albendazole and mebendazole.

Consensus docking and MM-PBSA computations identify putative furin protease inhibitors for developing potential therapeutics against COVID-19.

Unlabelled: The coronavirus disease 2019 (COVID-19) is a pandemic that has severely posed substantial health challenges and claimed millions of lives. Though vaccines have been produced to stem the spread of this disease, the death rate remains high since drugs used for treatment have therapeutic challenges. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes the disease, has a slew of potential therapeutic targets.

EBOLApred: A machine learning-based web application for predicting cell entry inhibitors of the Ebola virus.

Ebola virus disease (EVD) is a highly virulent and often lethal illness that affects humans through contact with the body fluid of infected persons. Glycoprotein and matrix protein VP40 play essential roles in the virus life cycle within the host. Whilst glycoprotein mediates the entry and fusion of the virus with the host cell membrane, VP40 is also responsible for viral particle assembly and budding.

Molecular Modelling and Atomistic Insights into the Binding Mechanism of MmpL3 Mtb.

Mycobacterial membrane proteins Large (MmpLs), which belong to the resistance, nodulation, and division (RND) protein superfamily, play critical roles in transporting polymers, lipids, and immunomodulators. MmpLs have become one of the important therapeutic drug targets to emerge in recent times. In this study, two homology modelling techniques, Modeller and SWISS-MODEL, were used in modelling the three-dimensional protein structure of the MmpL3 of Mycobacterium tuberculosis using that of M.

Density Functional Theory-Based Studies Predict Carbon Nanotubes as Effective Mycolactone Inhibitors.

Fullerenes, boron nitride nanotubes (BNNTs), and carbon nanotubes (CNTs) have all been extensively explored for biomedical purposes. This work describes the use of BNNTs and CNTs as mycolactone inhibitors. Density functional theory (DFT) has been used to investigate the chemical properties and interaction mechanisms of mycolactone with armchair BNNTs (5,5) and armchair CNTs (5,5).

Therapeutic Anti-Depressant Potential of Microbial GABA Produced by Strains for GABAergic Signaling Restoration and Inhibition of Addiction-Induced HPA Axis Hyperactivity.

The role of the microbiota-gut-brain (MGB) axis in mood regulation and depression treatment has gained attention in recent years, as evidenced by the growing number of animal and human studies that have reported the anti-depressive and associated gamma-aminobutyric acid-ergic (GABAergic) effects of probiotics developed from bacterial strains in the gut microbiome. The depressive states attenuated by these probiotics in patients suffering from clinical depression also characterize the severe and relapse-inducing withdrawal phase of the addiction cycle, which has been found to arise from the intoxication-enabled hyperregulation of the hypothalamic-pituitary-adrenal (HPA) axis, the body's major stress response system, and a corresponding attenuation of its main inhibitory system, the gamma-aminobutyric acid (GABA) signaling system. Therefore, the use of probiotics in the treatment of general cases of depression provides hope for a novel therapeutic approach to withdrawal depression remediation.

Molecular Structure-Based Screening of the Constituents of Identifies Potential Inhibitors of Diabetes Mellitus Target Alpha Glucosidase.

Diabetes mellitus is a disorder characterized by higher levels of blood glucose due to impaired insulin mechanisms. Alpha glucosidase is a critical drug target implicated in the mechanisms of diabetes mellitus and its inhibition controls hyperglycemia. Since the existing standard synthetic drugs have therapeutic limitations, it is imperative to identify new potent inhibitors of natural product origin which may slow carbohydrate digestion and absorption via alpha glucosidase.

Homology Modeling, Design of Ligands, and Molecular Docking Identify Potential Inhibitors of 24-Sterol Methyltransferase.

The therapeutic challenges pertaining to leishmaniasis due to reported chemoresistance and toxicity necessitate the need to explore novel pathways to identify plausible inhibitory molecules. 24-sterol methyltransferase (SMT) is vital for the synthesis of ergosterols, the main constituents of cellular membranes. So far, mammals have not been shown to possess SMT or ergosterols, making the pathway a prime candidate for drug discovery.

Targeting the 's Thymidylate Monophosphate Kinase for the Identification of Novel Antimalarial Natural Compounds.

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. is highly dependent on the pyrimidine biosynthetic pathway, a pathway responsible for the production of pyrimidines, and the parasite lacks the pyrimidine salvage enzymes.

Computational Study on Potential Novel Anti-Ebola Virus Protein VP35 Natural Compounds.

Ebola virus (EBOV) is one of the most lethal pathogens that can infect humans. The Ebola viral protein VP35 (EBOV VP35) inhibits host IFN-α/β production by interfering with host immune responses to viral invasion and is thus considered as a plausible drug target. The aim of this study was to identify potential novel lead compounds against EBOV VP35 using computational techniques in drug discovery.

Dual-Inhibition of Human N-Myristoyltransferase Subtypes Halts Common Cold Pathogenesis: Atomistic Perspectives from the Case of IMP-1088.

The pharmacological inhibition of human N-myristoyltransferase (HsNMT) has emerged as an efficient strategy to completely prevent the replication process of rhinoviruses, a potential treatment for the common cold. This was corroborated by the recent discovery of compound IMP-1088, a novel inhibitor that demonstrated a dual-inhibitory activity against the two HsNMT subtypes 1 and 2 without inducing cytotoxicity. However, the molecular and structural basis for the dual-inhibitory potential of IMP-1088 has not been investigated.

Molecular modelling and fragment-based design of potential inhibitors of beta-tubulin gene of from natural products.

The emergence of drug resistance against the known hookworm drugs namely albendazole and mebendazole and their reduced efficacies necessitate the need for new drugs. Chemically diverse natural products present plausible templates to augment hookworm drug discovery. The present work utilized pharmacoinformatics techniques to predict African natural compounds ZINC95486082, ZINC95486052 and euphohelionon as potential inhibitory molecules of the hookworm β tubulin gene.

Molecular Docking Simulation Studies Identifies Potential Natural Product Derived-Antiwolbachial Compounds as Filaricides against Onchocerciasis.

Onchocerciasis is the leading cause of blindness and severe skin lesions which remain a major public health problem, especially in tropical areas. The widespread use of antibiotics and the long duration required for effective treatment continues to add to the increasing global menace of multi-resistant pathogens. harbors the endosymbiont bacteria , essential for the normal development of embryos, larvae and long-term survival of the adult worm, .