Computational multi-target approach to target essential enzymes of Leishmania donovani using comparative molecular dynamic simulations and MMPBSA analysis.

INTRODUCTION: Visceral leishmaniasis (VL) is caused by Leishmania donovani. The purine and pyrimidine pathways are essential for L. donovani. Simultaneously inhibiting multiple targets could be an effective strategy to eliminate the pathogen and treat VL. OBJECTIVE: We aimed to target the essential enzymes of L. donovani and inhibit them using a multi-target approach. MATERIALS AND METHODS: A systematic analytical method was followed, in which first reported inhibitors of two essential enzymes (adenine phosphoribosyl-transferase [APRT] and dihydroorotate dehydrogenase [DHODH]) were collected and then ADMET and PASS analyses were conducted using the Lipinski rule and Veber's rule. Additionally, molecular docking between screened ligands and proteins were performed. The stability of complexes was analyzed using molecular dynamics (MD) simulations and MMPBSA analysis. RESULTS: Initially, 6,220 unique molecules were collected from the PubChem database, and then the Lipinski rule and Veber's rule were used for screening. In total, 203 compounds passed the ADMET test; their antileishmanial properties were tested by PASS analysis. As a result, 15 ligands were identified. Molecular docking simulations between APRT or DHODH and these 15 ligands were performed. Four molecules were found to be plant-derived compounds. Lig_2 and Lig_3 had good docking scores with both proteins. MD simulations were performed to determine the dynamic behavior and binding patterns of complexes. Both MD simulations and MMPBSA analysis showed Lig_3 is a promising antileishmanial inhibitor of both targets. CONCLUSION: Promising plant-derived compounds that might be used to combat VL were obtained through a multi-target approach.

Leishmaniasis: Omics Approaches to Understand its Biology from Molecule to Cell Level.

Leishmaniasis is the second deadliest vector-borne, neglected tropical zoonotic disease and is found in a variety of clinical forms based on genetic background. Its endemic type is present in tropical, sub-tropical and Mediterranean areas around the world which accounts for a lot of deaths every year. Currently, a variety of techniques are available for detection of leishmaniasis each technique having it's own pros and cons. The advancing next-generation sequencing (NGS) techniques are employed to find out novel diagnostic markers based on single nucleotide variants. A total of 274 NGS studies are available in European Nucleotide Archive (ENA) portal (https://www.ebi.ac.uk/ena/browser/home) that focused on wild-type and mutated Leishmania, differential gene expression, miRNA expression, and detection of aneuploidy mosaicism by omics approaches. These studies have provided insights into the population structure, virulence, and extensive structural variation, including known and suspected drug resistance loci, mosaic aneuploidy and hybrid formation under stressed conditions and inside the midgut of the sandfly. The complex interactions occurring within the parasite-host-vector triangle can be better understood by omics approaches. Further, advanced CRISPR technology allows researchers to delete and modify each gene individually to know the importance of genes in the virulence and survival of the disease-causing protozoa. In vitro generation of Leishmania hybrids are helping to understand the mechanism of disease progression in its different stages of infection. This review will give a comprehensive picture of the available omics data of various Leishmania spp. which helped to reveal the effect of climate change on the spread of its vector, the pathogen survival strategies, emerging antimicrobial resistance and its clinical importance.

Deciphering antiviral efficacy of malaria box compounds against malaria exacerbating viral pathogens- Epstein Barr virus and SARS-CoV-2, an in silico study.

In malaria endemic countries, coinfections and cotransmissions of different viral pathogens are widely reported. Prior studies have shown that malaria can trigger the Epstein-Barr virus (EBV) reactivation in the body. Besides, the altered immunity due to malaria could increase susceptibility to acquire co-circulating viruses like SARS-CoV-2 or vice versa during pandemic times. The dual burden of pathogens can deteriorate health by inducing disease severity. There are no or limited antiviral therapies available against EBV and SARS-CoV-2. Exploring the novel antimalarials for checking antiviral efficacy and using them in such cases could be the efficient approach of 'hitting two birds with one stone'. We investigated the antiviral potency of medicine for a malaria venture's malaria box containing 400 drug-like or probe-like compounds with experimentally proven antimalarial activity. We utilized a molecular docking approach to screen these compounds against crucial proteins- EBNA1 of EBV and RdRp of SARS-CoV-2 respectively. Based on binding affinity we shortlisted the top three compounds for each protein. Further, for validation of complex stability and binding, the protein-ligand complex is subjected to 100 ns molecular dynamic simulation. All the compounds showed stable binding with respective proteins. Based on binding free energies, involvement of important residues from target sites, and ADMET properties of compounds, the top ligand for each protein is selected. Ligand B (MMV665879) for EBNA1 (ΔGbind = -183.54 kJ/mol) and Ligand E (MMV665918) for RdRp (ΔGbind = -172.23 kJ/mol) could act as potential potent inhibitors. These antimalarial compounds can hence be utilized for further experimental investigation as antivirals against EBV and SARS-CoV-2.

An integrative approach using systems biology, mutational analysis with molecular dynamics simulation to challenge the functionality of a target protein.

Visceral leishmaniasis affects millions of people worldwide in areas where Leishmania donovani is endemic. The protozoan species serves a greater threat as it has gradually evolved drug resistance whereby requiring newer approaches to treat the infection. State-of-art techniques are mostly directed toward finding better targets extracted from the available proteome data. In light of recent computational advancements, we ascertain and validate one such target, adenylosuccinate lyase (ADSL) by implementation of in-silico methods which led to the identification of critical amino acid residues that affects its functional attributes. Our target selection was based on comprehensive topological analysis of a knowledge-based protein-protein interaction network. Subsequently, mutations were incorporated and the dynamic behavior of mutated and native proteins was traced using MD simulations for a total time span of 600 ns. Comparative analysis of the native and mutated structures exhibited perceptible changes in the ligand-bound catalytic region with respect to time. The unfavorable changes in the orientations of specific catalytic residues, His118 and His196, induced by generated mutations reduce the enzyme specificity. In summary, this integrative approach is able to select a target against pathogen, identify crucial residues, and challenge its functionality through the selected mutations.