Background/Objectives: Pteridine reductase 1 (PTR1) has been one of the prime targets for discovering novel antileishmanial therapeutics in the fight against Leishmaniasis. This enzyme catalyzes the NADPH-dependent reduction of pterins to their tetrahydro forms. While chemotherapy remains the primary treatment, its effectiveness is constrained by drug resistance, unfavorable side effects, and substantial associated costs. Methods: This study addresses the urgent need for novel, cost-effective drugs by employing in silico techniques to identify potential lead compounds targeting the PTR1 enzyme. A library of 1463 natural compounds from AfroDb and NANPDB, prefiltered based on Lipinski’s rules, was used to screen against the LmPTR1 target. The X-ray structure of LmPTR1 complexed with NADP and dihydrobiopterin (Protein Data Bank ID: 1E92) was identified to contain the critical residues Arg17, Leu18, Ser111, Phe113, Pro224, Gly225, Ser227, Leu229, and Val230 including the triad of residues Asp181-Tyr194-Lys198, which are critical for the catalytic process involving the reduction of dihydrofolate to tetrahydrofolate. Results: The docking yielded 155 compounds meeting the stringent criteria of −8.9 kcal/mol instead of the widely used −7.0 kcal/mol. These compounds demonstrated binding affinities comparable to the known inhibitors; methotrexate (−9.5 kcal/mol), jatrorrhizine (−9.0 kcal/mol), pyrimethamine (−7.3 kcal/mol), hardwickiic acid (−8.1 kcal/mol), and columbamine (−8.6 kcal/mol). Protein–ligand interactions and molecular dynamics (MD) simulation revealed favorable hydrophobic and hydrogen bonding with critical residues, such as Lys198, Arg17, Ser111, Tyr194, Asp181, and Gly225. Crucial to the drug development, the compounds were physiochemically and pharmacologically profiled, narrowing the selection to eight compounds, excluding those with potential toxicities. The five selected compounds ZINC000095486253, ZINC000095486221, ZINC000095486249, 8alpha-hydroxy-13-epi-pimar-16-en-6,18-olide, and pachycladin D were predicted to be antiprotozoal (Leishmania) with Pa values of 0.642, 0.297, 0.543, 0.431, and 0.350, respectively. Conclusions: This study identified five lead compounds that showed substantial binding affinity against LmPTR1 as well as critical residue interactions. A 100 ns MD combined with molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) calculations confirmed the robust binding interactions and provided insights into the dynamics and stability of the protein–ligand complexes.

Objective: Falciparum malaria is a major global health concern, affecting more than half of the world’s population and causing over half a million deaths annually. Red cell invasion is a crucial step in the parasite’s life cycle, where the parasite invade human erythrocytes to sustain infection and ensure survival. Two parasite proteins, Apical Membrane Antigen 1 (AMA-1) and Rhoptry Neck Protein 2 (RON2), are involved in tight junction formation, which is an essential step in parasite invasion of the red blood cell. Targeting the AMA-1 and RON2 interaction with inhibitors halts the formation of the tight junction, thereby preventing parasite invasion, which is detrimental to parasite survival. This study leverages machine learning (ML) to predict potential small molecule inhibitors of the AMA-1–RON2 interaction, providing putative antimalaria compounds for further chemotherapeutic exploration. Method: Data was retrieved from the PubChem database (AID 720542), comprising 364,447 inhibitors and non-inhibitors of the AMA-1–RON2 interaction. The data was processed by computing Morgan fingerprints and divided into training and testing with an 80:20 ratio, and the classes in the training data were balanced using the Synthetic Minority Oversampling Technique. Five ML models developed comprised Random Forest (RF), Gradient Boost Machines (GBMs), CatBoost (CB), AdaBoost (AB) and Support Vector Machine (SVM). The performances of the models were evaluated using accuracy, F1 score, and receiver operating characteristic—area under the curve (ROC-AUC) and validated using held-out data and a y-randomization test. An applicability domain analysis was carried out using the Tanimoto distance with a threshold set at 0.04 to ascertain the sample space where the models predict with confidence. Results: The GBMs model emerged as the best, achieving 89% accuracy and a ROC-AUC of 92%. CB and RF had accuracies of 88% and 87%, and ROC-AUC scores of 93% and 91%, respectively. Conclusions: Experimentally validated inhibitors of the AMA-1–RON2 interaction could serve as starting blocks for the next-generation antimalarial drugs. The models were deployed as a web-based application, known as PLASMOpred.

The Marburg virus (MARV), responsible for severe hemorrhagic fevers with mortality rates as high as 90%, remains a significant public health threat. This s

Buruli ulcer (BU) is a necrotizing skin disease caused by Mycobacterium ulcerans that produces a virulent lipid toxin, mycolactone, which is detectable in urine. Current diagnostics are time-consuming and require specialized expertise, often leading to delayed diagnosis. This makes it difficult to understand the disease’s spread and plan effective interventions. To facilitate early diagnostic biomarker identification, we used computational methods to identify proteins to the antigen lactone, a product of mycolactone hydrolysis, that could be used to develop rapid diagnostic tests (RDTs). Using AutoDock Vina, we performed a virtual screening of 6 proteins against lactone. Four proteins – N-Acyl homoserine lactonases (4G5X), hyperthermophilic Sulfolobus islandicus PLL SisLac (4G2D), phosphotriesterase (2VC5) and quorum-quenching lactonase (6N9I) – showed strong interactions with lactone, with binding energies ranging from −8.9 to −6.0 kcal/mol. Molecular dynamic simulations used to assess the stability of these protein-lactone complexes showed that natural lactonase and promiscuous phosphotriesterase activities (2VC5) and quorum-quenching lactonase GcL (6N9I) were the most stable. In addition, 2VC5 and 4G5X demonstrated the most flexibility. Overall, the proteins 2VC5, 4G2D and 4G5X showed a strong binding affinity, good stability and favourable interactions with lactone. These findings suggest that these proteins could serve as the basis for developing rapid, noninvasive RDTs for BU disease.