scholarly journals Drug repurposing studies targeting SARS-CoV-2: an ensemble docking approach on drug target 3C-like protease (3CLpro)

2020 ◽  
pp. 1-21 ◽  
Author(s):  
Shruti Koulgi ◽  
Vinod Jani ◽  
Mallikarjunachari Uppuladinne ◽  
Uddhavesh Sonavane ◽  
Asheet Kumar Nath ◽  
...  
Keyword(s):  
Drug Target ◽  
Drug Repurposing ◽  
Ensemble Docking ◽  
Docking Approach

Drug Repurposing Studies Targeting SARS-nCoV2: An Ensemble Docking Approach on Drug Target 3C-like Protease (3CLpro)

2020 ◽  
Author(s):  
Shruti Koulgi ◽  
Vinod Jani ◽  
Mallikarjunachari Uppuladinne ◽  
Uddhavesh Sonavane ◽  
Asheet Kumar Nath ◽  
...  
Keyword(s):  
Drug Repurposing ◽  
Drug Binding ◽  
Ensemble Docking ◽  
Drug Molecules ◽  
Drug Binding Site ◽  
Main Protease ◽  
Docking Approach ◽  
Novel Coronavirus ◽  
Markov State Modeling ◽  
Viral Polyprotein

<p>The COVID-19 pandemic has been responsible for several deaths worldwide. The causative agent behind this disease is the Severe Acute Respiratory Syndrome – novel Coronavirus 2 (SARS-nCoV2). SARS-nCoV2 belongs to the category of RNA viruses. The main protease, responsible for the cleavage of the viral polyprotein is considered as one of the hot targets for treating COVID-19. Earlier reports suggest the use of HIV anti-viral drugs for targeting the main protease of SARS-CoV, which caused SARS in the year 2002-03. Hence, drug repurposing approach may prove to be useful in targeting the main protease of SARS-nCoV2. The high-resolution crystal structure of 3CL<sup>pro</sup> (main protease) of SARS-nCoV2 (PDB ID: 6LU7) was used as the target. The Food and Drug Administration (FDA) approved and SWEETLEAD database of drug molecules were screened. The apo form of the main protease was simulated for a cumulative of 150 ns and 10 μs open source simulation data was used, to obtain conformations for ensemble docking. The representative structures for docking were selected using RMSD-based clustering and Markov State Modeling analysis. This ensemble docking approach for main protease helped in exploring the conformational variation in the drug binding site of the main protease leading to efficient binding of more relevant drug molecules. The drugs obtained as best hits from the ensemble docking possessed anti-bacterial and anti-viral properties. Small molecules with these properties may prove to be useful to treat symptoms exhibited in COVID-19. This <i>in-silico</i> ensemble docking approach would support identification of potential candidates for repurposing against COVID-19.</p>

Drug Repurposing Studies Targeting SARS-nCoV2: An Ensemble Docking Approach on Drug Target 3C-like Protease (3CLpro)

2020 ◽  
Author(s):  
Shruti Koulgi ◽  
Vinod Jani ◽  
Mallikarjunachari Uppuladinne ◽  
Uddhavesh Sonavane ◽  
Asheet Kumar Nath ◽  
...  
Keyword(s):  
Drug Repurposing ◽  
Drug Binding ◽  
Ensemble Docking ◽  
Drug Molecules ◽  
Drug Binding Site ◽  
Main Protease ◽  
Docking Approach ◽  
Novel Coronavirus ◽  
Markov State Modeling ◽  
Viral Polyprotein

<p>The COVID-19 pandemic has been responsible for several deaths worldwide. The causative agent behind this disease is the Severe Acute Respiratory Syndrome – novel Coronavirus 2 (SARS-nCoV2). SARS-nCoV2 belongs to the category of RNA viruses. The main protease, responsible for the cleavage of the viral polyprotein is considered as one of the hot targets for treating COVID-19. Earlier reports suggest the use of HIV anti-viral drugs for targeting the main protease of SARS-CoV, which caused SARS in the year 2002-03. Hence, drug repurposing approach may prove to be useful in targeting the main protease of SARS-nCoV2. The high-resolution crystal structure of 3CL<sup>pro</sup> (main protease) of SARS-nCoV2 (PDB ID: 6LU7) was used as the target. The Food and Drug Administration (FDA) approved and SWEETLEAD database of drug molecules were screened. The apo form of the main protease was simulated for a cumulative of 150 ns and 10 μs open source simulation data was used, to obtain conformations for ensemble docking. The representative structures for docking were selected using RMSD-based clustering and Markov State Modeling analysis. This ensemble docking approach for main protease helped in exploring the conformational variation in the drug binding site of the main protease leading to efficient binding of more relevant drug molecules. The drugs obtained as best hits from the ensemble docking possessed anti-bacterial and anti-viral properties. Small molecules with these properties may prove to be useful to treat symptoms exhibited in COVID-19. This <i>in-silico</i> ensemble docking approach would support identification of potential candidates for repurposing against COVID-19.</p>

scholarly journals Translational and Clinical Pharmacology Considerations in Drug Repurposing for X-linked Adrenoleukodystrophy-A Rare Peroxisomal Disorder

2021 ◽  
Author(s):  
Julianne Tieu ◽  
Siddhee Sahasrabudhe ◽  
Paul Orchard ◽  
James Cloyd ◽  
Reena Kartha
Keyword(s):  
Drug Target ◽  
Drug Targets ◽  
Drug Repurposing ◽  
Pharmacokinetics And Pharmacodynamics ◽  
Drug Candidates ◽  
Target Patient Population ◽  
Site Of Action ◽  
Repurposed Drugs ◽  
Gait Disturbances ◽  
Spastic Quadriparesis

X-linked adrenoleukodystrophy (X-ALD) is an inherited, neurodegenerative rare disease that can result in devastating symptoms of blindness, gait disturbances, and spastic quadriparesis due to progressive demyelination. Typically, the disease progresses rapidly, causing death within the first decade of life. With limited treatments available, efforts to determine an effective therapy that can alter disease progression or mitigate symptoms have been undertaken for many years, particularly through drug repurposing. Repurposing has generally been guided through clinical experience and small trials. At this time, none of the drug candidates have been approved for use, which may be due, in part, to the lack of pharmacokinetic/pharmacodynamic (PK/PD) information on the repurposed medications in the target patient population. Greater consideration for the disease pathophysiology, drug pharmacology, and potential drug-target interactions, specifically at the site of action, would improve drug repurposing and facilitate development. Although there is a good understanding of X-ALD pathophysiology, the absence of information on drug targets, pharmacokinetics, and pharmacodynamics hinders the repurposing of drugs for this condition. Incorporating advanced translational and clinical pharmacological approaches in preclinical studies and early stages clinical trials will improve the success of repurposed drugs for X-ALD as well as other rare diseases.

scholarly journals Drug Repurposing for Candidate SARS-CoV-2 Main Protease Inhibitors by a Novel in Silico Method

2020 ◽  
Author(s):  
Milan Sencanski ◽  
Vladimir Perovic ◽  
Snezana Pajovic ◽  
Miroslav Adzic ◽  
Slobodan Paessler ◽  
...  
Keyword(s):  
Protease Inhibitors ◽  
In Silico ◽  
Drug Target ◽  
Transmission Rate ◽  
Experimental Testing ◽  
Drug Repurposing ◽  
Global Public Health ◽  
Main Protease ◽  
Additional Approach ◽  
Drugbank Database

<p>The SARS-CoV-2 outbreak caused an unprecedented global public health threat, having a high transmission rate with currently no drugs or vaccines approved. An alternative powerful additional approach to counteract COVID-19 is <em>in silico</em> drug repurposing. The SARS-CoV-2 main protease is essential for viral replication and an attractive drug target. In this study, we used the virtual screening (VS) protocol with both long-range and short-range interactions to select candidate SARS-CoV-2 main protease inhibitors. First, the ISM applied for Small Molecules was used for searching the Drugbank database and further followed by molecular docking. After <em>in silico</em> screening of drug space, we identified 57 drugs as potential SARS-CoV-2 main protease inhibitors that we propose for further experimental testing.</p>

The Screening of phytochemicals against NS5 Polymerase to treat Zika Virus infection: Integrated computational based approach

2021 ◽  
Vol 24 ◽  
Author(s):  
Abdur Rehman ◽  
Usman Ali Ashfaq ◽  
Farah Shahid ◽  
Fatima Noor ◽  
Sidra Aslam
Keyword(s):  
Zika Virus ◽  
Drug Target ◽  
Md Simulation ◽  
Cost Effective ◽  
Structural Proteins ◽  
Rna Dependent Rna Polymerase ◽  
Drug Effectiveness ◽  
Bonding Interaction ◽  
Ligand Interactions ◽  
Docking Approach

Background: The recent Zika virus (ZIKV) outbreak provides a spur for new, efficient, and safe anti-Zika Virus agents. RNA-dependent RNA polymerase (RdRp) is critical amongst the seven non-structural proteins for viral replication and is considered an attractive drug target. Methods: In this study, a molecular docking approach was used to rationally screen the library of 5000 phytochemicals to find inhibitors against NS5 RdRp. LigX tool was used to analyze the 2D plots of receptor-ligand interactions. The top-ranked compounds were then subjected to in-silico pharmacokinetic study. Results: The compounds, namely Polydatin, Dihydrogenistin, Liquiritin, Rhapontin, and Cichoriin, successfully bind inside the pocket of NS5 RdRp. Polydatin was the leading phytochemical that showed high docking score of -18.71 (kcal/mol) and bonding interaction at the active site of NS5 RdRp. They were subjected to analysis for drug-like properties that further reinforced their validation and showed that they could attach with the receptor more than SOFOSBUVIR control drugs. MD simulation of the top two complexes was performed, and the simulated complexes showed stability, and ligands were kept within the bonding pocket. Conclusion: The study might facilitate the development of a natural and cost-effective drug against ZIKV. Further validation, however, is necessary to confirm its drug effectiveness and its biocompatibility.

scholarly journals Target-Centered Drug Repurposing Predictions of Human Angiotensin-Converting Enzyme 2 (ACE2) and Transmembrane Protease Serine Subtype 2 (TMPRSS2) Interacting Approved Drugs for Coronavirus Disease 2019 (COVID-19) Treatment through a Drug-Target Interaction Deep Learning Model

Viruses ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1325
Author(s):  
Yoonjung Choi ◽  
Bonggun Shin ◽  
Keunsoo Kang ◽  
Sungsoo Park ◽  
Bo Ram Beck
Keyword(s):  
Deep Learning ◽  
Angiotensin Converting Enzyme ◽  
Drug Target ◽  
Expression Profiles ◽  
Drug Repurposing ◽  
Converting Enzyme ◽  
Angiotensin Converting Enzyme 2 ◽  
Target Interaction ◽  
Approved Drugs ◽  
Fda Approved Drugs

Previously, our group predicted commercially available Food and Drug Administration (FDA) approved drugs that can inhibit each step of the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using a deep learning-based drug-target interaction model called Molecule Transformer-Drug Target Interaction (MT-DTI). Unfortunately, additional clinically significant treatment options since the approval of remdesivir are scarce. To overcome the current coronavirus disease 2019 (COVID-19) more efficiently, a treatment strategy that controls not only SARS-CoV-2 replication but also the host entry step should be considered. In this study, we used MT-DTI to predict FDA approved drugs that may have strong affinities for the angiotensin-converting enzyme 2 (ACE2) receptor and the transmembrane protease serine 2 (TMPRSS2) which are essential for viral entry to the host cell. Of the 460 drugs with Kd of less than 100 nM for the ACE2 receptor, 17 drugs overlapped with drugs that inhibit the interaction of ACE2 and SARS-CoV-2 spike reported in the NCATS OpenData portal. Among them, enalaprilat, an ACE inhibitor, showed a Kd value of 1.5 nM against the ACE2. Furthermore, three of the top 30 drugs with strong affinity prediction for the TMPRSS2 are anti-hepatitis C virus (HCV) drugs, including ombitasvir, daclatasvir, and paritaprevir. Notably, of the top 30 drugs, AT1R blocker eprosartan and neuropsychiatric drug lisuride showed similar gene expression profiles to potential TMPRSS2 inhibitors. Collectively, we suggest that drugs predicted to have strong inhibitory potencies to ACE2 and TMPRSS2 through the DTI model should be considered as potential drug repurposing candidates for COVID-19.

scholarly journals A review on drug repurposing applicable to COVID-19

2020 ◽  
Author(s):  
Serena Dotolo ◽  
Anna Marabotti ◽  
Angelo Facchiano ◽  
Roberto Tagliaferri
Keyword(s):  
Artificial Intelligence ◽  
Drug Target ◽  
Lower Cost ◽  
Drug Repositioning ◽  
Drug Repurposing ◽  
Chemical Compounds ◽  
The Moment ◽  
New Applications ◽  
Novel Drug ◽  
Small Chemical

Abstract Drug repurposing involves the identification of new applications for existing drugs at a lower cost and in a shorter time. There are different computational drug-repurposing strategies and some of these approaches have been applied to the coronavirus disease 2019 (COVID-19) pandemic. Computational drug-repositioning approaches applied to COVID-19 can be broadly categorized into (i) network-based models, (ii) structure-based approaches and (iii) artificial intelligence (AI) approaches. Network-based approaches are divided into two categories: network-based clustering approaches and network-based propagation approaches. Both of them allowed to annotate some important patterns, to identify proteins that are functionally associated with COVID-19 and to discover novel drug–disease or drug–target relationships useful for new therapies. Structure-based approaches allowed to identify small chemical compounds able to bind macromolecular targets to evaluate how a chemical compound can interact with the biological counterpart, trying to find new applications for existing drugs. AI-based networks appear, at the moment, less relevant since they need more data for their application.

scholarly journals Main Protease Inhibitors and Drug Surface Hotspot for the Treatment of COVID-19: Drug Repurposing and Molecular Docking Approach

2020 ◽  
Author(s):  
Mahmudul Hasan ◽  
Md Sorwer Alam Parvez ◽  
Kazi Faizul Azim ◽  
Abdus Shukur Imran ◽  
Topu Raihan ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Drug Repurposing ◽  
Pharmacokinetic Parameters ◽  
The Novel ◽  
Drug Candidates ◽  
Target Drug ◽  
Global Pandemic ◽  
Main Protease ◽  
Docking Approach ◽  
Repurposed Drugs

<div>The world is facing an unprecedented global pandemic caused by the novel SARS-CoV-2. In the absence</div><div>of a specific therapeutic agent to treat COVID-19 patients, the present study aimed to virtually screen out</div><div>the effective drug candidates from the approved main protease protein (MPP) inhibitors and their</div><div>derivatives for the treatment of SARS-CoV-2. Here, drug repurposing and molecular docking were</div><div>employed to screen approved MPP inhibitors and their derivatives. The approved MPP inhibitors against</div><div>HIV and HCV were prioritized, whilst hydroxychloroquine, favipiravir, remdesivir, and alpha-ketoamide</div><div>were studied as control. The target drug surface hotspot was also investigated through the molecular</div><div>docking technique. ADME analysis was conducted to understand the pharmacokinetics and drug-likeness</div><div>of the screened MPP inhibitors. The result of this study revealed that Paritaprevir (-10.9 kcal/mol), and its</div><div>analog (CID 131982844)(-16.3 kcal/mol) showed better binding affinity than the approved MPP inhibitor</div><div>compared in this study including favipiravir, remdesivir, and alpha-ketoamide. A comparative study among</div><div>the screened putative MPP inhibitors revealed that amino acids T25, T26, H41, M49, L141, N142, G143,</div><div>C145, H164, M165, E166, D187, R188, and Q189 are at critical positions for becoming the surface hotspot</div><div>in the MPP of SARS-CoV-2. The study also suggested that paritaprevir and its' analog (CID 131982844),</div><div>may be effective against SARS-CoV-2 as these molecules had the common drug-surface hotspots on the</div><div>main protease protein of SARS-CoV-2. Other pharmacokinetic parameters also indicate that paritaprevir</div><div>and its top analog (CID 131982844) will be either similar or better-repurposed drugs than already approved</div><div>MPP inhibitors. </div><div><br></div>

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