Virtual screening of p53 mutants reveals Y220S as an additional rescue drug target for PhiKan083 with higher binding characteristics

2019 ◽  
Vol 80 ◽  
pp. 398-408 ◽  
Author(s):  
Vaijayanthi Raghavan ◽  
Maulishree Agrahari ◽  
Dhananjaya Kale Gowda
Keyword(s):  
Virtual Screening ◽  
Drug Target ◽  
Binding Characteristics ◽  
Rescue Drug

Virtual Screening, Molecular Modelling and Biochemical Studies to Exploit PF14_0660 as a Target to Identify Novel Anti-malarials

2019 ◽  
Vol 16 (4) ◽  
pp. 417-426
Author(s):  
Vimee Raturi ◽  
Kumar Abhishek ◽  
Subhashis Jana ◽  
Subhendu Sekhar Bag ◽  
Vishal Trivedi
Keyword(s):  
Virtual Screening ◽  
Phosphatase Activity ◽  
Molecular Modelling ◽  
Drug Target ◽  
Antimalarial Activity ◽  
Biochemical Study ◽  
Tyrosine Phosphatase ◽  
Host Protein ◽  
Dependent Manner ◽  
Multiple Sequence

Background: Malaria Parasite relies heavily on signal transduction pathways to control growth, the progression of the life cycle and sustaining stress for its survival. Unlike kinases, Plasmodium's phosphatome is one of the smallest and least explored for identifying drug target for clinical intervention. PF14_0660 is a putative protein present on the chromosome 14 of Plasmodium falciparum genome. Methods: Multiple sequence alignment of PF14_0660 with other known protein phosphatase indicate the presence of phosphatase motif with specific residues essential for metal binding, catalysis and providing structural stability. PF14_0660 is a mixed α/β type of protein with several β -sheet and α-helix arranged to form βαβαβα sub-structure. The surface properties of PF14_0660 is conserved with another phosphate of this family, but it profoundly diverges from the host protein tyrosine phosphatase. PF14_0660 was cloned, over-expressed and protein is exhibiting phosphatase activity in a dose-dependent manner. Docking of Heterocyclic compounds from chemical libraries into the PF14_0660 active site found nice fitting of several candidate molecules. Results: Compound PPinh6, PPinh 7 and PPinh 5 are exhibiting antimalarial activity with an IC50 of 1.4 ± 0.2µM, 3.8 ± 0.3 µM and 9.4 ± 0.6&#181M respectively. Compound PPinh 6 and PPinh 7 are inhibiting intracellular PF14_0660 phosphatase activity and killing parasite through the generation of reactive oxygen species. Conclusion: Hence, a combination of molecular modelling, virtual screening and biochemical study allowed us to explore the potentials of PF14_0660 as a drug target to design anti-malarials.

scholarly journals Identification of inhibitors of SARS-CoV-2 3CL-Pro enzymatic activity using a small molecule in-vitro repurposing screen

2020 ◽  
Author(s):  
Maria Kuzikov ◽  
Elisa Costanzi ◽  
Jeanette Reinshagen ◽  
Francesca Esposito ◽  
Laura Vangeel ◽  
...  
Keyword(s):  
Enzymatic Activity ◽  
Small Molecules ◽  
Drug Target ◽  
Treatment Options ◽  
Cleavage Sites ◽  
X Ray ◽  
Binding Characteristics ◽  
Main Protease ◽  
Ic50 Values

Compound repurposing is an important strategy for the identification of effective treatment options against SARS-CoV-2 infection and COVID-19 disease. In this regard, SARS-CoV-2 main protease (3CL-Pro), also termed M-Pro, is an attractive drug target as it plays a central role in viral replication by processing the viral polyproteins pp1a and pp1ab at multiple distinct cleavage sites. We here report the results of a repurposing program involving 8.7 K compounds containing marketed drugs, clinical and preclinical candidates, and small molecules regarded as safe in humans. We confirmed previously reported inhibitors of 3CL-Pro, and have identified 62 additional compounds with IC50 values below 1 uM and profiled their selectivity towards Chymotrypsin and 3CL-Pro from the MERS virus. A subset of 8 inhibitors showed anti-cytopathic effect in a Vero-E6 cell line and the compounds thioguanosine and MG-132 were analysed for their predicted binding characteristics to SARS-CoV-2 3CL-Pro. The X-ray crystal structure of the complex of myricetin and SARS-Cov-2 3CL-Pro was solved at a resolution of 1.77 Angs., showing that myricetin is covalently bound to the catalytic Cys145 and therefore inhibiting its enzymatic activity.

Virtual Screening Yields Inhibitors of Novel Antifungal Drug Target, Benzoate 4-Monooxygenase

2012 ◽  
Vol 52 (11) ◽  
pp. 3053-3063 ◽  
Author(s):  
Sabina Berne ◽  
Barbara Podobnik ◽  
Neja Zupanec ◽  
Metka Novak ◽  
Nada Kraševec ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Drug Target ◽  
Antifungal Drug

Targeting FGL2, a molecular drug target for glioblastoma, with natural compounds through virtual screening method

2021 ◽  
Author(s):  
Fahad Hassan Shah ◽  
Song Ja Kim
Keyword(s):  
Virtual Screening ◽  
Active Site ◽  
Drug Target ◽  
Screening Method ◽  
Tumor Development ◽  
Pharmacokinetic Profile ◽  
Natural Compounds ◽  
Screening Platform ◽  
Proliferation In Vitro

Background: Fibroleukin-2 protein (FGL2) causes redevelopment of brain tumors. Inhibition of these proteins has shown to improve glioblastoma prognosis and treatment efficacy. Aim: The current study gathered recently exploited natural compounds that suppress glioblastoma proliferation in vitro, tested against FGL2 protein. Method: Twenty-five compounds were explored through a virtual screening platform. Results: Three natural compounds (betanine, hesperetin and ovatodiolide) hit the active site of FGL2. Furthermore, the influence of these compounds was also assessed using in silico gene expression, and ADMET tools showed downregulation of some genes, which caused rapid tumor development while possessing a moderate acute toxicity and pharmacokinetic profile. Conclusion: Our study presents three compounds that are good candidates for evaluation in FGL2 mutated glioblastoma animal models.

scholarly journals wSDTNBI: a novel network-based inference method for virtual screening

2022 ◽  
Author(s):  
Zengrui Wu ◽  
Hui Ma ◽  
Zehui Liu ◽  
Lulu Zheng ◽  
Zhuohang Yu ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Drug Target ◽  
Rapid Development ◽  
Inference Method ◽  
New Type

In recent years, the rapid development of network-based methods for the prediction of drug-target interactions (DTIs) provides an opportunity for the emergence of a new type of virtual screening (VS),...

scholarly journals Natural Product Compounds in Alpinia officinarum and Ginger are Potent SARS-CoV-2 Papain-like Protease Inhibitors

2020 ◽  
Author(s):  
Dibakar Goswami ◽  
Mukesh Kumar ◽  
Sunil K. Ghosh ◽  
Amit Das
Keyword(s):  
Virtual Screening ◽  
Natural Product ◽  
Protease Inhibitors ◽  
In Silico ◽  
Drug Target ◽  
Homology Modelling ◽  
Protease Domain ◽  
Lead Compounds ◽  
Alpinia Officinarum ◽  
Natural Product Compounds

SARS-CoV-2 or COVID-19 has caused more than 10,00,000 infections and ~55,000 deaths worldwide spanning over 203 countries, and the numbers are exponentially increasing. Due to urgent need of treating the SARS infection, many approved, pre-clinical, anti-viral, anti-malarial and anti-SARS drugs are being administered to patients. SARS-CoV-2 papain-like protease (PLpro) has a protease domain which cleaves the viral polyproteins a/b, necessary for its survival and replication, and is one of the drug target against SARS-CoV-2. 3D structures of SARS-CoV-2 PLpro were built by homology modelling. Two models having partially open and closed conformations were used in our study. Virtual screening of natural product compounds was performed. We prepared an in house library of compounds found in rhizomes, Alpinia officinarum, ginger and curcuma, and docked them into the solvent accessible S3-S4 pocket of PLpro. Eight compounds from Alpinia officinarum and ginger bind with high in silico affinity to closed PLpro conformer, and hence are potential SARS-CoV-2 PLpro inhibitors. Our study reveal new lead compounds targeting SARS-CoV-2. Further structure based modifications or extract formulations of these compounds can lead to highly potent inhibitors to treat SARS-CoV-2 infections.<br>

scholarly journals Natural Product Compounds in Alpinia officinarum and Ginger are Potent SARS-CoV-2 Papain-like Protease Inhibitors

2020 ◽  
Author(s):  
Dibakar Goswami ◽  
Mukesh Kumar ◽  
Sunil K. Ghosh ◽  
Amit Das
Keyword(s):  
Virtual Screening ◽  
Natural Product ◽  
Protease Inhibitors ◽  
In Silico ◽  
Drug Target ◽  
Homology Modelling ◽  
Protease Domain ◽  
Lead Compounds ◽  
Alpinia Officinarum ◽  
Natural Product Compounds

SARS-CoV-2 or COVID-19 has caused more than 10,00,000 infections and ~55,000 deaths worldwide spanning over 203 countries, and the numbers are exponentially increasing. Due to urgent need of treating the SARS infection, many approved, pre-clinical, anti-viral, anti-malarial and anti-SARS drugs are being administered to patients. SARS-CoV-2 papain-like protease (PLpro) has a protease domain which cleaves the viral polyproteins a/b, necessary for its survival and replication, and is one of the drug target against SARS-CoV-2. 3D structures of SARS-CoV-2 PLpro were built by homology modelling. Two models having partially open and closed conformations were used in our study. Virtual screening of natural product compounds was performed. We prepared an in house library of compounds found in rhizomes, Alpinia officinarum, ginger and curcuma, and docked them into the solvent accessible S3-S4 pocket of PLpro. Eight compounds from Alpinia officinarum and ginger bind with high in silico affinity to closed PLpro conformer, and hence are potential SARS-CoV-2 PLpro inhibitors. Our study reveal new lead compounds targeting SARS-CoV-2. Further structure based modifications or extract formulations of these compounds can lead to highly potent inhibitors to treat SARS-CoV-2 infections.<br>

Structure-based Virtual Screening Approach for the Discovery of Potent Inhibitors of Aminoglycoside 6'-N-Acetyltransferase Type Ib [AAC(6')-Ib] against K. pneumoniae Infections

2020 ◽  
Vol 17 (8) ◽  
pp. 1027-1035
Author(s):  
Reaz Uddin ◽  
Bushra Siraj ◽  
Sidra Rafi ◽  
Syed Sikander Azam ◽  
Abdul Wadood
Keyword(s):  
Virtual Screening ◽  
Klebsiella Pneumoniae ◽  
Drug Target ◽  
Clinical Importance ◽  
Genomic Islands ◽  
Dimensional Structure ◽  
Binding Modes ◽  
Induced Fit ◽  
Substrate Analogs ◽  
Potential Inhibitors

Background: Aminoglycoside 6'-N-acetyltransferase type Ib (AAC(6')-Ib) from Klebsiella pneumoniae is an established drug target and has conferred insensitivity to aminoglycosides. Aminoglycosides are often inactivated by aminoglycoside modifying enzymes encoded by genes present in the chromosome, plasmids, and other genetic elements. The AAC(6′)- Ib is an enzyme of clinical importance found in a wide variety of gram-negative pathogens. The AAC(6′)-Ib enzyme is of interest not only because of its ubiquity but also because of other characteristics e.g., it presents significant microheterogeneity at the N-termini and the aac(6′)-Ib gene is often present in integrons, transposons, plasmids, genomic islands, and other genetic structures. The majority of the reported potent inhibitors against the target are substrate analogs. Therefore, there is a need to develop or discover new scaffolds other than substrate analogs as AAC(6')-Ib inhibitor. Objective: The objective of this study is to set optimum parameters for the structure-based virtual screening by multiple docking and scoring methods. The multiple scoring of each ligand also incorporates the ‘Induced Fit’ docking effect that helps to build further confidence in the shortlisted compounds. The method eventually is able to predict the potential inhibitors that bind to the active site and can potentially inhibit the activity of the Aminoglycoside 6′-N-acetyltransferase type Ib [AAC(6’)-Ib] from Klebsiella pneumoniae. Methods: Using the available three-dimensional structure of enzyme AAC(6')-Ib inhibitor complex, a structure-based virtual screening was performed with the hope of prioritizing the promising leads. In order to set up the protocol, 30,000 drug-like molecules were selected from the ChemBridge library. Multiple docking programs, i.e. UCSF DOCK6 and AutoDock Vina have been applied in the current study so that a consensus is developed to the predicted binding modes and thus the docking accuracy. The Amber scores of the Dock6 – a secondary scoring function was also used to perform the ‘Induced Fit’ effect and correspondingly re-rank the compounds. Results: The top 30 ranked compounds of the most frequent scored were selected from the histogram. The 2D interactions of those 30 compounds were drawn from the Ligplot+ tool. Six of the compounds were prioritized as potential inhibitors as they are representing the maximum number of interactions from the rest of the compounds and also possess the drug-likeness as predicted by the estimated ADMET properties. Conclusion: This study provided useful insight that the proposed compounds have the potential to bind to the aminoglycoside binding site of AAC(6′)-Ib that may eventually inhibit the Klebsiella pneumoniae. This study has the potential to propose putative new and novel inhibitors against a resistant drug target of Klebsiella pneumoniae.

Identification of Therapeutic drug Target of Stenotrophomonas maltophilia through subtractive genomic approach and in-silico screening based on 2D similarity filtration and Molecular Dynamic Simulation.

2020 ◽  
Vol 23 ◽  
Author(s):  
Rahul Chandela ◽  
Dhananjay Jade ◽  
Surender Mohan ◽  
Sugumar Shobana ◽  
Ridhi Sharma
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
Molecular Simulation ◽  
Drug Target ◽  
Stenotrophomonas Maltophilia ◽  
Opportunistic Infections ◽  
Therapeutic Drug ◽  
High Morbidity ◽  
The Novel ◽  
Genomic Approach

Background: Stenotrophomonas maltophilia is a multi-drug resistant, gram-negative bacterium that causes opportunistic infections and is associated with high morbidity and mortality in severely immunocompromised individuals. Aim: To find out the drug target and a novel inhibitor for Stenotrophomonas maltophilia. Objectives: Current study focused on the identification of specific drug target by subtractive genomes analysis and to find out the novel inhibitor for the identified target protein by virtual screening, molecular docking, and molecular simulation approach. Materials and Methods: In this study, we performed a subtractive genomics approach to identify the novel drug target for S.maltophilia. After obtaining the specific target, the next footstep was to identify inhibitors that include the calculation of 2D Similarity search, Molecular Docking, and Molecular Simulation for the drug development for the S.maltophilia. Results: With an efficient subtractive genomic approach, five unique targets as the impressive therapeutics founded out of 4386 protein genes. In which UDP-D-acetylmuramic (murF) was the most remarkable target. Further virtual screening, docking, and dynamics resulted in the identification of seven novel inhibitors. Conclusion: Further, in vitro and in vivo bioassay of the identified novel inhibitors could facilitate effective drug use against S.maltophilia.

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