A profound computational study to prioritize the natural compound inhibitors against the P. falciparum orotidine-5-monophosphate decarboxylase enzyme

Identification of natural products against enoyl-acyl-carrier-protein reductase in malaria via combined pharmacophore modeling, molecular docking and simulations studies

Plasmodium falciparum is counted as one of the deadly species causing malaria. In that respect, enoyl acyl carrier protein reductase is recognized as one of the attractive druggable targets for the identification of antimalarials. Thus, from the structural proteome of ENR, common feature pharmacophores were constructed. To identify the representative models, all the hypotheses were subjected to validation methods, like, test set, enrichment factor, and Güner-Henry method, and the selected representative hypotheses were used to screen out the drug-like natural products. Further, the screened candidates were advanced to molecular docking calculations. Based on the docking score criteria and presence of essential interaction with Tyr277, seven candidates were shortlisted to conduct the HYDE and QSAR assessment. Further, the stability of these complexes was evaluated by employing molecular dynamics simulations, molecular mechanics-generalized born surface area approach-based free binding energy calculations with the residue-wise contribution of PfENR to the total binding free energy of the complex. On comparing the root mean square deviation, and fluctuation plots of the docked candidates with the reference, all the candidates displayed stable behavior, and the same outcome was depicted from the secondary structure element. However, from the free energy calculations, and residue-wise contribution conducted after dynamics, it was observed that out of seven, only five candidates sustain the binding with Tyr277 and cofactor of PfENR. Therefore, in the current work, the hybrid study of screening and stability lead to the identification of five structurally diverse candidates that can be employed for the design of novel antimalarials.Communicated by Ramaswamy H. Sarma.

In silico identification of angiotensin-1 converting enzyme inhibitors using text mining and virtual screening

Cardiovascular diseases are the world's leading cause of death. Hypertension is an important risk factor for cardiovascular and renal diseases. Angiotensin-converting enzyme (ACE) can be a possible therapeutic target for managing angiotensin I conversion to angiotensin II and ultimately controlling hypertension. Indole is an significant fragment used in many medicines approved by FDA. For this reason, the molecules in their fragments containing" indol" keywords were taken from the Specs-SC (small compound) database. The predicted therapeutc activity values (TAV) of these compounds against hypertension were evaluated using binary models of QSAR by MetaCore/MetaDrug. For the 26 separate QSAR models of toxicity, molecules with measured TAV greater than 0.5 were used. 3792 non-toxic compounds were investigated by molecular docking study and molecular dynamics simulations for their ACE inhibitory activity. Glide standard precision (SP) of Maestro Molecular Modeling pocket was used to perform molecular docking. Short molecular dynamics (MD) simulations (5-ns) were carried out by initiating the top docking poses of selected 40 molecules. To quantitatively evaluate the predicted binding affinity of a screened compound, average MM/GBSA scores of screened ligands were calculated and based on their binding free energy values, hit compounds were identified for the long (100-ns) MD simulations. Root mean square deviation and root mean square fluctuations were also calculated to assess the structural characteristics and observe fluctuations of the 100-ns time scale. Thus, with the application of text mining and integrated molecular modeling we reported novel indole-based hit inhibitors for ACE-1.Communicated by Ramaswamy H. Sarma.

Identification of the natural compound inhibitors against Plasmodium falciparum plasmepsin-II via common feature based screening and molecular dynamics simulations

Malaria is counted amongst the deadly disease caused by Plasmodium falciparum. Recently, plasmepsin-II enzyme has gained much importance as an attractive drug target for the exploration of antimalarials. Therefore, the common feature pharmacophore models were generated from the crystallized complexes of the plasmepsin-II proteome. These models were subjected to a series of validation procedures, i.e. test set and Güner Henry studies to enlist the representative models. The selected representative hypotheses incorporating the most essential chemical features (common ZHHA) were screened against the natural product database to retrieve the potential candidates. To ensure the selection of the drug-like candidates, prior to screening, filtering steps (Drug-likeness and ADMET filters) were employed on the selected database. To study the interaction pattern of the candidates within the protein, these molecules were advanced to the molecular docking studies. Subsequently, based on the selected cut-off criteria obtained via redocking of the reference (4Z22), 15 compounds showed higher docking score (> -16.05 kcal/mol), and displayed the presence of hydrogen bonding with the crucial amino acids, i.e. Asp34 and Asp214. Further, the stability of the docked molecules was scrutinized via molecular dynamics simulations, and the results were compared with the reference compound 4Z22. All the docked compounds showed stable dynamics behaviour. Thus, in the present contribution, the combination of screening and stability procedures resulted in the identification of 15 hits that can serve as a new chemical space in the designing of the novel antimalarials.Communicated by Ramaswamy H. Sarma.