Targeting the dengue β-OG with serotype-specific alkaloid virtual leads

Application of Machine Learning Techniques to Predict Binding Affinity for Drug Targets: A Study of Cyclin-Dependent Kinase 2

BACKGROUND

The elucidation of the structure of cyclin-dependent kinase 2 (CDK2) made it possible to develop targeted scoring functions for virtual screening aimed to identify new inhibitors for this enzyme. CDK2 is a protein target for the development of drugs intended to modulate cellcycle progression and control. Such drugs have potential anticancer activities.

OBJECTIVE

Our goal here is to review recent applications of machine learning methods to predict ligand- binding affinity for protein targets. To assess the predictive performance of classical scoring functions and targeted scoring functions, we focused our analysis on CDK2 structures.

METHODS

We have experimental structural data for hundreds of binary complexes of CDK2 with different ligands, many of them with inhibition constant information. We investigate here computational methods to calculate the binding affinity of CDK2 through classical scoring functions and machine- learning models.

RESULTS

Analysis of the predictive performance of classical scoring functions available in docking programs such as Molegro Virtual Docker, AutoDock4, and Autodock Vina indicated that these methods failed to predict binding affinity with significant correlation with experimental data. Targeted scoring functions developed through supervised machine learning techniques showed a significant correlation with experimental data.

CONCLUSION

Here, we described the application of supervised machine learning techniques to generate a scoring function to predict binding affinity. Machine learning models showed superior predictive performance when compared with classical scoring functions. Analysis of the computational models obtained through machine learning could capture essential structural features responsible for binding affinity against CDK2.

Cytotoxicity Activity and Druggability Studies of Sigmasterol Isolated from Marine Sponge Dysidea avara Against Oral Epithelial Cancer Cell (KB/C152) and T-Lymphocytic Leukemia Cell Line (Jurkat/ E6-1)

Background:

Marine sponge is a rich natural resource of many pharmacological compounds and various bioactive anticancer agents are derived from marine organisms like sponges.

Methods:

studying the anticancer activity and Drug ability of marine sponge Dysidea avara using Cell lines oral epithelial cancer cell (KB/C152) and T-lymphocytic leukemia cell line (Jurkat/ E6-1). Marine sponge was collected from Persian Gulf. Several analytical techniques have been used to obtain and recognize stigmasterol, including column chromatography, thin layer chromatography, and gas chromatography-mass spectrometry. The PASS Prediction Activity was used to investigate the apoptosis-inducing effect of stigmasterol. The cytotoxic activity of stigmasterol was examined using yellow tetrazolium salt XTT (sodium 2, 3,-bis (2methoxy-4-nitro-5-sulfophenyl)-5-[(phenylamino) carbonyl]-2H-tetrazolium) assay. The stigmasterol were docked within the protein tyrosine kinase (PTKs) (PDB code: 1t46) and epidermal growth factor receptor (EGFRK) (PDB code: 1M17). Also, the pharmacological characteristics of stigmasterol were predicted using PerADME, SwissADME, and Molinspi ration tools. Apoptosis-inducing effect of stigmasterol indicate the stigmasterol in terms of the possibility of apoptosis in cells.

Results:

The apoptosis inducement results of known stigmasterol were determined by PASS on-line prediction. The compound exhibit potent cytotoxic properties against KB/C152 cell compared to Jurkat/ E6-1 cell. The stigmasterol showed the cytotoxicity effects on KB/C152 and HUT78 with IC50 ranges of 81.18 and 103.03 μg/ml, respectively. Molecular docking showed that, stigmasterol bound stably to the active sites of the protein tyrosine kinase (PTKs) (PDB code: 1t46) and epidermal growth factor receptor (EGFRK) (PDB code: 1M17).

Conclusion:

The compound showed desirable pharmacokinetic properties (ADME). This provided direct evidence of how a prospective anti-cancer agent can be stigmasterol. The preclinical studies paved the way for a potential new compound of anti-cancer.

Consensus Analyses in Molecular Docking Studies Applied to Medicinal Chemistry

The increasing number of computational studies in medicinal chemistry involving molecular docking has put the technique forward as promising in Computer-Aided Drug Design. Considering the main method in the virtual screening based on the structure, consensus analysis of docking has been applied in several studies to overcome limitations of algorithms of different programs and mainly to increase the reliability of the results and reduce the number of false positives. However, some consensus scoring strategies are difficult to apply and, in some cases, are not reliable due to the small number of datasets tested. Thus, for such a methodology to be successful, it is necessary to understand why, when and how to use consensus docking. Therefore, the present study aims to present different approaches to docking consensus, applications, and several scoring strategies that have been successful and can be applied in future studies.

Employing virtual screening and molecular dynamics simulations for identifying hits against the active cholera toxin

Cholera is a major global threat, affecting millions each year. The ADP ribosyltransferase activity of the active cholera toxin catalyses the massive loss of water and electrolytes during cholera infections. The active toxin heterodimer comprises the A1 subunit from Vibrio cholerae and ARF (ADP Ribosylation Factor) from the human host. Although the active toxin is a potential target for drug discovery against cholera, it has been scarcely targeted to date. The A1-ARF interface contains a potential druggable site for small molecule inhibitors. By combining a sequential docking and scoring strategy with molecular dynamics (MD) simulations, this study identified hits against the protein-protein interface (PPI) of the active cholera toxin from an in-house library of 9,175 ADMET-screened alkaloids. The docking algorithms and scoring functions of Glide SP, Glide XP, and AutoDock were employed for initial library screening. Three alkaloids were initially selected by docking-based virtual screening. The stability of the hit-toxin complexes was validated by MD simulations. Two of the three hits, namely, A6225 (7-formyldehydrothalicsimidine) and A16503 (1,2,7,8-tetrahydroxy dibenz[cd,f]indol-4(5H)-one), formed stable complexes with the toxin. Analyses of the hydrogen bond occupancies revealed that the hits formed stable hydrogen bonds with the toxin PPI. The hits identified herein can serve as reference compounds for drug discovery against cholera in the future.

Dengue Virus and Its Inhibitors: A Brief Review

The global occurrence of viral infectious diseases poses a significant threat to human health. Dengue virus (DENV) infection is one of the most noteworthy of these infections. According to a WHO survey, approximately 400 million people are infected annually; symptoms deteriorate in approximately one percent of cases. Numerous foundational and clinical investigations on viral epidemiology, structure and function analysis, infection source and route, therapeutic targets, vaccines, and therapeutic drugs have been conducted by both academic and industrial researchers. At present, CYD-TDV or Dengvaxia^® is the only approved vaccine, but potent inhibitors are currently under development. In this review, an overview of the viral life circle and the history of DENVs is presented, and the most recently reported antiviral candidates and newly discovered promising targets are focused and summarized. We believe that these successes and failures have enabled progress in anti-DENV drug discovery and hope that our review will stimulate further innovation in this area.

Druggability and Binding Site Interaction Studies of Potential Metabolites Isolated from Marine Sponge Aurora globostellata against Human Epidermal Growth Factor Receptor-2

To study the involvement of compounds stigmasterol and oleic acid isolated from marine sponge Aurora globostellata and docking against the Human Epidermal Growth Factor Receptor-2 in breast cancer. The comparative molecular docking was performed with the natural compounds from marine sponge and the synthetic drugs used in breast cancer treatment against the target HER2. The molecular docking analysis was done using GLIDE in Schrodinger software package. The ADME properties were calculated using the Qikprop. The observation of the common binding site for all the ligands confirms the binding pocket; where the isolated compound Stigmasterol agrees well with the binding residues and thus can be optimized further to arrive at a molecule that has a high binding affinity and low binding constant. The results of the docking studies carried out on HER2 provide an insight for the compound stigmasterol to have drug like properties than oleic acid. These results are supportive to confirm the marine sponges as a better lead for cancer therapeutics.