Exploring the Therapeutic Ability of Fenugreek against Type 2 Diabetes and Breast Cancer Employing Molecular Docking and Molecular Dynamics Simulations

Rampogu, Shailima,Parameswaran, Saravanan,Lemuel, Mary Rampogu,Lee, Keun Woo Hindawi 2018 Evidence-based Complementary and Alternative Medic Vol.2018 No.-

<P>Fenugreek (Trigonella foenum-graecum) is used as a spice throughout the world. It is known for its medicinal properties such as antidiabetic, anticarcinogenic, and immunological activities. The present study shows the properties and the nutritional quality of fenugreek seed extract and focuses on screening of active compounds in drug designing for type 2 diabetes and breast cancer. Quantitative analysis was used to calculate the percentages of protein, carbohydrates moisture, fatty acid, galactomannan, oil, and amino acid. Phytochemical analysis revealed the presence of flavonoids, terpenoids, phenols, proteins, saponins, and tannins in fenugreek seed extracts. Molecular docking and molecular dynamics simulation-based computational drug discovery methods were employed to address the role of fenugreek seed constituents against type 2 diabetes and breast cancer. The computational results reveal that the compound galactomannan can be ascribed as potential drug candidate against breast cancer and type 2 diabetes rendered by higher molecular dock scores, stable molecular dynamics (MD) simulations results, and lower binding energy calculations.</P>

Natural compounds as potential Hsp90 inhibitors for breast cancer-Pharmacophore guided molecular modelling studies

Rampogu, Shailima,Parate, Shraddha,Parameswaran, Saravanan,Park, Chanin,Baek, Ayoung,Son, Minky,Park, Yohan,Park, Seok Ju,Lee, Keun Woo Elsevier 2019 Computational biology and chemistry Vol.83 No.-

<P><B>Abstract</B></P> <P>Breast cancer is one of the major impediments affecting women globally. The ATP-dependant heat shock protein 90 (Hsp90) forms the central component of molecular chaperone machinery that predominantly governs the folding of newly synthesized peptides and their conformational maturation. It regulates the stability and function of numerous client proteins that are frequently upregulated and/or mutated in cancer cells, therefore, making Hsp90 inhibition a promising therapeutic strategy for the development of new efficacious drugs to treat breast cancer. In the present <I>in silico</I> investigation, a structure-based pharmacophore model was generated with hydrogen bond donor, hydrogen bond acceptor and hydrophobic features complementary to crucial residues Ala55, Lys58, Asp93, Ile96, Met98 and Thr184 directed at inhibiting the ATP-binding activity of Hsp90. Subsequently, the phytochemical dataset of 3210 natural compounds was screened to retrieve the prospective inhibitors after rigorous validation of the model pharmacophore. The retrieved 135 phytocompounds were further filtered by drug-likeness parameters including Lipinski’s rule of five and ADMET properties, then investigated via molecular docking-based scoring. Molecular interactions were assessed using Genetic Optimisation for Ligand Docking program for 95 drug-like natural compounds against Hsp90 along with two clinical drugs as reference compounds – Geldanamycin and Radicicol. Docking studies revealed three phytochemicals are better than the investigated clinical drugs. The reference and hit compounds with dock scores of 48.27 (Geldanamycin), 40.90 (Radicicol), 73.04 (Hit1), 72.92 (Hit2) and 68.12 (Hit3) were further validated for their binding stability through molecular dynamics simulations. We propose that the non-macrocyclic scaffolds of three identified phytochemicals might aid in the development of novel therapeutic candidates against Hsp90-driven cancers.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Natural compounds are identified as Hsp90 inhibitors. </LI> <LI> These compounds show stable interactions with key residues. </LI> <LI> Non-quinone containing compounds were discovered by structure based pharmacophore modelling. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

Computational Exploration for Lead Compounds That Can Reverse the Nuclear Morphology in Progeria

Rampogu, Shailima,Baek, Ayoung,Son, Minky,Zeb, Amir,Park, Chanin,Kumar, Raj,Lee, Gihwan,Kim, Donghwan,Choi, Yeonuk,Cho, Yeongrae,Park, Yohan,Park, Seok Ju,Lee, Keun Woo Hindawi 2017 BioMed research international Vol.2017 No.-

<P>Progeria is a rare genetic disorder characterized by premature aging that eventually leads to death and is noticed globally. Despite alarming conditions, this disease lacks effective medications; however, the farnesyltransferase inhibitors (FTIs) are a hope in the dark. Therefore, the objective of the present article is to identify new compounds from the databases employing pharmacophore based virtual screening. Utilizing nine training set compounds along with lonafarnib, a common feature pharmacophore was constructed consisting of four features. The validated Hypo1 was subsequently allowed to screen Maybridge, Chembridge, and Asinex databases to retrieve the novel lead candidates, which were then subjected to Lipinski's rule of 5 and ADMET for drug-like assessment. The obtained 3,372 compounds were forwarded to docking simulations and were manually examined for the key interactions with the crucial residues. Two compounds that have demonstrated a higher dock score than the reference compounds and showed interactions with the crucial residues were subjected to MD simulations and binding free energy calculations to assess the stability of docked conformation and to investigate the binding interactions in detail. Furthermore, this study suggests that the Hits may be more effective against progeria and further the DFT studies were executed to understand their orbital energies.</P>

Sulfonanilide Derivatives in Identifying Novel Aromatase Inhibitors by Applying Docking, Virtual Screening, and MD Simulations Studies

Rampogu, Shailima,Son, Minky,Park, Chanin,Kim, Hyong-Ha,Suh, Jung-Keun,Lee, Keun Woo Hindawi 2017 BioMed research international Vol.2017 No.-

<P>Breast cancer is one of the leading causes of death noticed in women across the world. Of late the most successful treatments rendered are the use of aromatase inhibitors (AIs). In the current study, a two-way approach for the identification of novel leads has been adapted. 81 chemical compounds were assessed to understand their potentiality against aromatase along with the four known drugs. Docking was performed employing the CDOCKER protocol available on the Discovery Studio (DS v4.5). Exemestane has displayed a higher dock score among the known drug candidates and is labeled as reference. Out of 81 ligands 14 have exhibited higher dock scores than the reference. In the second approach, these 14 compounds were utilized for the generation of the pharmacophore. The validated four-featured pharmacophore was then allowed to screen Chembridge database and the potential Hits were obtained after subjecting them to Lipinski's rule of five and the ADMET properties. Subsequently, the acquired 3,050 Hits were escalated to molecular docking utilizing GOLD v5.0. Finally, the obtained Hits were consequently represented to be ideal lead candidates that were escalated to the MD simulations and binding free energy calculations. Additionally, the gene-disease association was performed to delineate the associated disease caused by CYP19A1.</P>

Old Drugs for New Purpose—Fast Pace Therapeutic Identification for SARS-CoV-2 Infections by Pharmacophore Guided Drug Repositioning Approach

Shailima Rampogu,Keun Woo Lee 대한화학회 2021 Bulletin of the Korean Chemical Society Vol.42 No.2

The recent outbreak, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a devastating effect globally with no effective treatment. A swift strategy to find effective therapeutics against coronavirus disease 2019 (COVID-19) is to repurpose the approved drugs with a blend of computational techniques. In this pursuit an exhaustive computational methods were applied on DrugBank compounds targeting SARS-CoV-2 main protease (Mpro). A structure-based pharmacophore model was generated considering the interactions between the target and the inhibitor N3. The validated model was subjected to screen DrugBank database yielding 35 compounds. Further, evaluating the binding affinity studies with reference drug Remdesivir has resulted six candidates with higher molecular dock scores than the reference compound. These compounds have demonstrated firm molecular dynamics simulation (MDS) results forming stable protein-drug complex demonstrating pharmacophore features. Taken together, our findings propose Viomycin, Enviomycin, Framycetin, Amikacin, Iopromide, and Paromomycin as potent putative inhibitors for COVID-19 therapeutics.

Investigation of non-hydroxamate scaffolds against HDAC6 inhibition: A pharmacophore modeling, molecular docking, and molecular dynamics simulation approach

Zeb, A.,Park, C.,Son, M.,Rampogu, S.,Alam, S. I.,Park, S. J.,Lee, K. W. Imperial College Press 2018 JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOG Vol.16 No.3

<P>Proteins deacetylation by Histone deacetylase 6 (HDAC6) has been shown in various human chronic diseases like neurodegenerative diseases and cancer, and hence is an important therapeutic target. Since, the existing inhibitors have hydroxamate group, and are not HDAC6-selective, therefore, this study has designed to investigate non-hydroxamate HDAC6 inhibitors. Ligand-based pharmacophore was generated from 26 training set compounds of HDAC6 inhibitors. The statistical parameters of pharmacophore (Hypo1) included lowest total cost of 115.63, highest cost difference of 135.00, lowest RMSD of 0.70 and the highest correlation of 0.98. The pharmacophore was validated by Fischer's Randomization and Test Set validation, and used as screening tool for chemical databases. The screened compounds were filtered by fit value (> 10.00), estimated Inhibitory Concentration (IC50) (<0.459), Lipinski's Rule of Five and Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) Descriptors to identify drug-like compounds. Furthermore, the drug-like compounds were docked into the active site of HDAC6. The best docked compounds were selected having gold fitness score > 66.46 and chemscore < -28.31, and hydrogen bond interaction with catalytic active residues. Finally, three inhibitors having sulfamoyl group were selected by Molecular Dynamic (MD) simulation, which showed stable root mean square deviation (RMSD) (1.6-1.9 angstrom), lowest potential energy (< -6.3 x 10(5) kJ/mol), and hydrogen bonding with catalytic active residues of HDAC6.</P>