scholarly journals Drug design and repurposing with DockThor-VS web server focusing on SARS-CoV-2 therapeutic targets and their non-synonym variants

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Isabella A. Guedes ◽  
Leon S. C. Costa ◽  
Karina B. dos Santos ◽  
Ana L. M. Karl ◽  
Gregório K. Rocha ◽  
...  
Keyword(s):  
Drug Design ◽  
Therapeutic Targets ◽  
Web Server ◽  
Drug Repurposing ◽  
World Health ◽  
Design Strategies ◽  
Structure Based Drug Design ◽  
N Protein ◽  
The Impact ◽  
The Web

AbstractThe COVID-19 caused by the SARS-CoV-2 virus was declared a pandemic disease in March 2020 by the World Health Organization (WHO). Structure-Based Drug Design strategies based on docking methodologies have been widely used for both new drug development and drug repurposing to find effective treatments against this disease. In this work, we present the developments implemented in the DockThor-VS web server to provide a virtual screening (VS) platform with curated structures of potential therapeutic targets from SARS-CoV-2 incorporating genetic information regarding relevant non-synonymous variations. The web server facilitates repurposing VS experiments providing curated libraries of currently available drugs on the market. At present, DockThor-VS provides ready-for-docking 3D structures for wild type and selected mutations for Nsp3 (papain-like, PLpro domain), Nsp5 (Mpro, 3CLpro), Nsp12 (RdRp), Nsp15 (NendoU), N protein, and Spike. We performed VS experiments of FDA-approved drugs considering the therapeutic targets available at the web server to assess the impact of considering different structures and mutations to identify possible new treatments of SARS-CoV-2 infections. The DockThor-VS is freely available at www.dockthor.lncc.br.

scholarly journals Drug Design and Repurposing with DockThor-VS Web Server: Virtual Screening focusing on SARS-CoV-2 Therapeutic Targets and their Non-Synonym Variants

2020 ◽  
Author(s):  
Isabella A. Guedes ◽  
Leon S. C. Costa ◽  
Karina B. dos Santos ◽  
Ana L. M. Karl ◽  
Gregório K. Rocha ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Drug Design ◽  
Therapeutic Targets ◽  
Web Server ◽  
Drug Repurposing ◽  
World Health ◽  
Design Strategies ◽  
Structure Based Drug Design ◽  
The Impact ◽  
The Web

Abstract The COVID-19 caused by the SARS-CoV-2 virus was declared as a pandemic disease in March 2020 by the World Health Organization (WHO). Structure-Based Drug Design strategies based on docking methodologies have been widely used for both new drug development and drug repurposing to find effective treatments against this disease. In this work, we present the developments implemented in the DockThor-VS web server to provide a virtual screening (VS) platform with curated structures of potential therapeutic targets from SARS-CoV-2 incorporating genetic information regarding relevant non-synonymous variations. The web server facilitates repurposing VS experiments providing curated libraries of currently available drugs on the market. Currently, DockThor-VS provides ready-for-docking 3D structures for wild type and selected mutations for Nsp3 (papain-like, PLpro domain), Nsp5 (Mpro, 3CLpro), Nsp12 (RdRp), Nsp15 (NendoU), N protein and Spike. We performed VS experiments of FDA-approved drugs considering the therapeutic targets available at the web server to assess the impact of considering different structures and mutations in the identification of possible new treatments of SARS-CoV-2 infections. The DockThor-VS is freely available at www.dockthor.lncc.br.

scholarly journals The critical role of QM/MM X-ray refinement and accurate tautomer/protomer determination in structure-based drug design

2020 ◽  
Author(s):  
Oleg Y. Borbulevych ◽  
Roger I. Martin ◽  
Lance M. Westerhoff
Keyword(s):  
Drug Design ◽  
Critical Role ◽  
Pharmaceutical Research ◽  
Energy Functional ◽  
Structural Refinement ◽  
Structure Based Drug Design ◽  
X Ray ◽  
X Ray Crystallography ◽  
Refinement Method ◽  
The Impact

Abstract Conventional protein:ligand crystallographic refinement uses stereochemistry restraints coupled with a rudimentary energy functional to ensure the correct geometry of the model of the macromolecule—along with any bound ligand(s)—within the context of the experimental, X-ray density. These methods generally lack explicit terms for electrostatics, polarization, dispersion, hydrogen bonds, and other key interactions, and instead they use pre-determined parameters (e.g. bond lengths, angles, and torsions) to drive structural refinement. In order to address this deficiency and obtain a more complete and ultimately more accurate structure, we have developed an automated approach for macromolecular refinement based on a two layer, QM/MM (ONIOM) scheme as implemented within our DivCon Discovery Suite and "plugged in" to two mainstream crystallographic packages: PHENIX and BUSTER. This implementation is able to use one or more region layer(s), which is(are) characterized using linear-scaling, semi-empirical quantum mechanics, followed by a system layer which includes the balance of the model and which is described using a molecular mechanics functional. In this work, we applied our Phenix/DivCon refinement method—coupled with our XModeScore method for experimental tautomer/protomer state determination—to the characterization of structure sets relevant to structure-based drug design (SBDD). We then use these newly refined structures to show the impact of QM/MM X-ray refined structure on our understanding of function by exploring the influence of these improved structures on protein:ligand binding affinity prediction (and we likewise show how we use post-refinement scoring outliers to inform subsequent X-ray crystallographic efforts). Through this endeavor, we demonstrate a computational chemistry ↔ structural biology (X-ray crystallography) "feedback loop" which has utility in industrial and academic pharmaceutical research as well as other allied fields.

Structure-based Drug Design Strategies in the Development of Small Molecule Inhibitors Targeting Bcl-2 Family Proteins

2020 ◽  
Vol 17 (8) ◽  
pp. 943-953
Author(s):  
Zhe Yin ◽  
Donglin Yang ◽  
Jun Wang ◽  
Yuequan Jiang
Keyword(s):  
Clinical Trials ◽  
Drug Design ◽  
B Cell ◽  
Cancer Cells ◽  
Small Molecule ◽  
Small Molecule Inhibitors ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Design Strategies ◽  
Structure Based Drug Design

Proteins of B-cell lymphoma (Bcl-2) family are key regulators of apoptosis and are involved in the pathogenesis of various cancers. Disrupting the interactions between the antiapoptotic and proapoptotic Bcl-2 members is an attractive strategy to reactivate the apoptosis of cancer cells. Structure-based drug design (SBDD) has been successfully applied to the discovery of small molecule inhibitors targeting Bcl-2 proteins in past decades. Up to now, many Bcl-2 inhibitors with different paralogue selectivity profiles have been developed and some were used in clinical trials. This review focused on the recent applications of SBDD strategies in the development of small molecule inhibitors targeting Bcl-2 family proteins.

Structure-based inhibitor design and repurposing clinical drugs to target SARS-CoV-2 proteases

2022 ◽  
Author(s):  
Anoop Narayanan ◽  
Shay A. Toner ◽  
Joyce Jose
Keyword(s):  
Drug Design ◽  
Protease Inhibitors ◽  
Drug Repurposing ◽  
Inhibitor Design ◽  
Rational Structure ◽  
Structure Based Drug Design ◽  
Drug Designing ◽  
Clinical Drugs

SARS-CoV-2, the coronavirus responsible for the current COVID-19 pandemic, encodes two proteases, 3CLpro and PLpro, two of the main antiviral research targets. Here we provide an overview of the structures and functions of 3CLpro and PLpro and examine strategies of structure-based drug designing and drug repurposing against these proteases. Rational structure-based drug design enables the generation of potent and target-specific antivirals. Drug repurposing offers an attractive prospect with an accelerated turnaround. Thus far, several protease inhibitors have been identified, and some candidates are undergoing trials that may well prove to be effective antivirals against SARS-CoV-2.

Design of Novel Phosphopantetheine Adenylyltransferase Inhibitors: a Potential New Approach to Tackle Mycobacterium tuberculosis

2021 ◽  
Vol 21 ◽  
Author(s):  
Marina C. Primi ◽  
Maurício T. Tavares ◽  
Larry L. Klein ◽  
Tina Izard ◽  
Carlos M. R. Sant'Anna ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Drug Design ◽  
Rational Design ◽  
Multi Drug Resistance ◽  
Design Strategies ◽  
Structure Based Drug Design ◽  
New Approach ◽  
Docking Simulations ◽  
Structure Activity ◽  
The World

Background: Tuberculosis (TB) has been a challenging disease worldwide, especially for the neglected poor populations. Presently, there are approximately 2 billion people infected with TB worldwide and 10 million people in the world fell ill with active TB, leading to 1.5 million deaths. Introduction: The classic treatment is extensive and the drug and multi drug resistance of Mycobacterium tuberculosis has been a threat to the efficacy of the drugs currently used. Therefore, the rational design of new anti TB candidates is urgently needed. Methods: With the aim of contributing to face this challenge, 78 compounds have been proposed based on SBDD (Structure Based Drug Design) strategies applied to target the M. tuberculosis phosphopantetheine adenylyltransferase (MtPPAT) enzyme. Ligand Based Drug Design (LBDD) strategies were also used for establishing structure activity relationships (SAR) and for optimizing the structures. MtPPAT is important for the biosynthesis of coenzyme A (CoA) and it has been studied recently toward the discovery of new inhibitors. Results : After docking simulations and enthalpy calculations, the interaction of selected compounds with MtPPAT was found to be energetically favorable. The most promising compounds were then synthesized and submitted to anti M. tuberculosis and MtPPAT inhibition assays. Conclusion: One of the compounds synthesized (MCP163), showed the highest activity in both of these assays.

scholarly journals COVID-19 Lockdown: Housing Built Environment’s Effects on Mental Health

2020 ◽  
Vol 17 (16) ◽  
pp. 5973 ◽  
Author(s):  
Andrea Amerio ◽  
Andrea Brambilla ◽  
Alessandro Morganti ◽  
Andrea Aguglia ◽  
Davide Bianchi ◽  
...  
Keyword(s):  
Mental Health ◽  
Depressive Symptoms ◽  
Public Mental Health ◽  
Interdisciplinary Approach ◽  
Well Being ◽  
World Health ◽  
Design Strategies ◽  
Housing Design ◽  
Increased Risk ◽  
The Impact

Since the World Health Organization (WHO) declared the coronavirus infectious disease 2019 (COVID-19) outbreak a pandemic on 11 March, severe lockdown measures have been adopted by the Italian Government. For over two months of stay-at-home orders, houses became the only place where people slept, ate, worked, practiced sports, and socialized. As consolidated evidence exists on housing as a determinant of health, it is of great interest to explore the impact that COVID-19 response-related lockdown measures have had on mental health and well-being. We conducted a large web-based survey on 8177 students from a university institute in Milan, Northern Italy, one of the regions most heavily hit by the pandemic in Europe. As emerged from our analysis, poor housing is associated with increased risk of depressive symptoms during lockdown. In particular, living in apartments <60 m2 with poor views and scarce indoor quality is associated with, respectively, 1.31 (95% CI: 1046–1637), 1.368 (95% CI: 1166–1605), and 2.253 (95% CI: 1918–2647) times the risk of moderate–severe and severe depressive symptoms. Subjects reporting worsened working performance from home were over four times more likely to also report depression (OR = 4.28, 95% CI: 3713–4924). Housing design strategies should focus on larger and more livable living spaces facing green areas. We argue that a strengthened multi-interdisciplinary approach, involving urban planning, public mental health, environmental health, epidemiology, and sociology, is needed to investigate the effects of the built environment on mental health, so as to inform welfare and housing policies centered on population well-being.

Structure-Based Drug Design Strategies and Challenges

2018 ◽  
Vol 18 (12) ◽  
pp. 998-1006 ◽  
Author(s):  
Xin Wang ◽  
Ke Song ◽  
Li Li ◽  
Lijiang Chen
Keyword(s):  
Drug Design ◽  
Protein Structures ◽  
Three Dimensional ◽  
Design Strategies ◽  
Structure Based Drug Design ◽  
The Past ◽  
Three Dimensional Representation ◽  
Potent Drug ◽  
The Cost ◽  
Gene Information

Over the past ten years, the number of three-dimensional protein structures identified by advanced science and technology increases, and the gene information becomes more available than ever before as well. The development of computing science becomes another driving force which makes it possible to use computational methods effectively in various phases of the drug design and research. Now Structure-Based Drug Design (SBDD) tools are widely used to help researchers to predict the position of small molecules within a three-dimensional representation of the protein structure and estimate the affinity of ligands to target protein with considerable accuracy and efficiency. They also accelerate discovery speed of potent drug and reduce the cost and times for drug research. Here we present an overview of SBDD used in drug discovery and highlight its recent successes and major challenges to current SBDD methodologies.

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