Multicomplex-based pharmacophore modeling in conjunction with multi-target docking and molecular dynamics simulations for the identification of PfDHFR inhibitors

Analysis of the interaction of antimalarial agents with Plasmodium falciparum glutathione reductase through molecular mechanical calculations

CONTEXT

Malaria remains a significant global health challenge with emerging resistance to current treatments. Plasmodium falciparum glutathione reductase (PfGR) plays a critical role in the defense mechanisms of malaria parasites against oxidative stress. In this study, we investigate the potential of targeting PfGR with conventional antimalarials and dual drugs combining aminoquinoline derivatives with GR inhibitors, which reveal promising interactions between PfGR and studied drugs. The naphthoquinone Atovaquone demonstrated particularly high affinity and potential dual-mode binding with the enzyme active site and cavity. Furthermore, dual drugs exhibit enhanced binding affinity, suggesting their efficacy in inhibiting PfGR, where the aliphatic ester bond (linker) is essential for effective binding with the enzyme's active site. Overall, this research provides important insights into the interactions between antimalarial agents and PfGR and encourages further exploration of its role in the mechanisms of action of antimalarials, including dual drugs, to enhance antiparasitic efficacy.

METHODS

The drugs were tested as PfGR potential inhibitors via molecular docking on AutoDock 4, which was performed based on the preoptimized structures in HF/3-21G-PCM level of theory on ORCA 5. Drug-receptor systems with the most promising binding affinities were then studied with a molecular dynamic's simulation on AMBER 16. The molecular dynamics simulations were performed with a 100 ns NPT ensemble employing GAFF2 forcefield in the temperature of 310 K, integration time step of 2 fs, and non-bond cutoff distance of 6.0 Å.

Structure- and ligand-based drug design methods for the modeling of antimalarial agents: a review of updates from 2012 onwards

Malaria still persists as one of the deadliest infectious disease having a huge morbidity and mortality affecting the higher population of the world. Structure and ligand-based drug design methods like molecular docking and MD simulations, pharmacophore modeling, QSAR and virtual screening are widely used to perceive the accordant correlation between the antimalarial activity and property of the compounds to design novel dominant and discriminant molecules. These modeling methods will speed-up antimalarial drug discovery, selection of better drug candidates for synthesis and to achieve potent and safer drugs. In this work, we have extensively reviewed the literature pertaining to the use and applications of various ligand and structure-based computational methods for the design of antimalarial agents. Different classes of molecules are discussed along with their target interactions pattern, which is responsible for antimalarial activity. Communicated by Ramaswamy H. Sarma.

An insight into the recent development of the clinical candidates for the treatment of malaria and their target proteins

Malaria is an endemic disease, prevalent in tropical and subtropical regions which cost half of million deaths annually. The eradication of malaria is one of the global health priority nevertheless, current therapeutic efforts seem to be insufficient due to the emergence of drug resistance towards most of the available drugs, even first-line treatment ACT, unavailability of the vaccine, and lack of drugs with a new mechanism of action. Intensification of antimalarial research in recent years has resulted into the development of single dose multistage therapeutic agents which has advantage of overcoming the antimalarial drug resistance. The present review explored the current progress in the development of new promising antimalarials against prominent target proteins that have the potential to be a clinical candidate. Here, we also reviewed different aspects of drug resistance and highlighted new drug candidates that are currently in a clinical trial or clinical development, along with a few other molecules with excellent antimalarial activity overs ACTs. The summarized scientific value of previous approaches and structural features of antimalarials related to the activity are highlighted that will be helpful for the development of next-generation antimalarials.

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.

Halogenated derivatives of methotrexate as human dihydrofolate reductase inhibitors in cancer chemotherapy

Methotrexate is a widely used anti-metabolite in cancer chemotherapy. A series of halogenated drugs is designed from Methotrexate to assess their interactions with human dihydrofolate reductase. The aim of this study is to evaluate the performance of the modified drugs compared to the parent Methotrexate. Density Functional Theory is employed to optimize these drugs. Molecular docking calculation of these optimized drugs against dihydrofolate reductase is performed to find out binding affinity. In addition, molecular dynamics simulation is considered for the complexes of best two modified drugs with their receptors. Modifications by the halogens show significant changes in the charge distribution, dipole moment, thermodynamic stability, enthalpy and free energy. The highest binding affinity value (-36.401 KJ/mol) was obtained for M14. Hybrid quantum mechanics/molecular mechanics calculation shows a binding energy of -255.140 KJ/mol. Modified drugs have significant hydrogen and non-covalent bonding interactions with amino acids of the receptor. Molecular dynamics simulation disclosed that the root-mean-square-deviation of the alpha carbon associated with M6-1KMV and M14-1KMV complexes is 2.367 Å and 2.622 Å, respectively. Moreover, the interactions between modified drugs and receptor are mostly persevered in 25 nanosecond molecular dynamics simulation. Ensemble-based docking also confirmed that modified drugs show strong non-bonding interactions with different crystallographic and molecular dynamics based conformers. The best scored drugs show considerable pharmacokinetic properties. Modified derivatives M5, M6, M8, M10, M13 and M14 show the better binding affinity and a good number of hydrogen and other non-bonding interactions with the target protein which are similar to other anticancer drugs.Communicated by Ramaswamy H. Sarma.