scholarly journals Combined Ligand and Structure Based Approaches Towards Developing Novel Renin Inhibitors for the Treatment of Hypertension

2021 ◽  
Author(s):  
P Ambili Unni ◽  
S Sajitha Lulu ◽  
Girinath G Pillai
Keyword(s):  
Chemical Space ◽  
Binding Free Energy ◽  
Chemical Species ◽  
Molecular Size ◽  
Central Component ◽  
Geriatric Population ◽  
Structure Based Drug Design ◽  
Renin Inhibitors ◽  
Treatment Of Hypertension ◽  
Renin Inhibition

<p>Hypertension is considered as the predominant risk factor for the onset of Cardiovascular disease (CVD) in the elder population. The chronic activation of Renin Angiotensin System (RAS) is considered as the primary causative factor for the inception of hypertension in geriatric population. Angiotensin Converting Enzyme (ACE) is a highly explored druggable target in the context of hypertension since this enzyme catalyses the conversion of angiotensin I to angiotensin II, a potent vasoconstrictor. But clinical trials conducted on ACE inhibitors reported their incompetence in the effective treatment of hypertension. Hence, recent studies are focussing on renin, which is a central component of RAS in the regulation of blood pressure. The present study focuses on the elucidation of physicochemical properties of chemical compounds essential for renin inhibition and identification of novel renin inhibitors possessing enhanced potency as well as bioavailability. We have employed Molecular Field Topology Analysis (MFTA) as well as Structure Based Drug Design (SBDD) approaches for the accomplishment of above-mentioned objectives. MFTA approach were piloted on 45 indole-3-carboxamide derivatives by elucidating the significance of charge distribution as well as molecular size of chemical species in eliciting renin inhibition. Optimal model was obtained with Nf = 3, r<sup>2 </sup>= 0.81 , Q<sup>2</sup> = 0.65. Molecular docking, atom-based binding free energy contributions and bioavailability assessments were carried out to identify most potent lead molecule among 45 compounds reported for renin inhibition. Further, new derivative molecules were predicted for the best lead molecule by employing chemical space exploration. All datasets, descriptor values, QSAR models for predictions usage and plots will be available in <a href="https://github.com/giribio/agingdata">https://github.com/giribio/agingdata</a></p><p></p>

scholarly journals Combined Ligand and Structure Based Approaches Towards Developing Novel Renin Inhibitors for the Treatment of Hypertension

2021 ◽  
Author(s):  
P Ambili Unni ◽  
S Sajitha Lulu ◽  
Girinath G Pillai
Keyword(s):  
Chemical Space ◽  
Binding Free Energy ◽  
Chemical Species ◽  
Molecular Size ◽  
Central Component ◽  
Geriatric Population ◽  
Structure Based Drug Design ◽  
Renin Inhibitors ◽  
Treatment Of Hypertension ◽  
Renin Inhibition

<p>Hypertension is considered as the predominant risk factor for the onset of Cardiovascular disease (CVD) in the elder population. The chronic activation of Renin Angiotensin System (RAS) is considered as the primary causative factor for the inception of hypertension in geriatric population. Angiotensin Converting Enzyme (ACE) is a highly explored druggable target in the context of hypertension since this enzyme catalyses the conversion of angiotensin I to angiotensin II, a potent vasoconstrictor. But clinical trials conducted on ACE inhibitors reported their incompetence in the effective treatment of hypertension. Hence, recent studies are focussing on renin, which is a central component of RAS in the regulation of blood pressure. The present study focuses on the elucidation of physicochemical properties of chemical compounds essential for renin inhibition and identification of novel renin inhibitors possessing enhanced potency as well as bioavailability. We have employed Molecular Field Topology Analysis (MFTA) as well as Structure Based Drug Design (SBDD) approaches for the accomplishment of above-mentioned objectives. MFTA approach were piloted on 45 indole-3-carboxamide derivatives by elucidating the significance of charge distribution as well as molecular size of chemical species in eliciting renin inhibition. Optimal model was obtained with Nf = 3, r<sup>2 </sup>= 0.81 , Q<sup>2</sup> = 0.65. Molecular docking, atom-based binding free energy contributions and bioavailability assessments were carried out to identify most potent lead molecule among 45 compounds reported for renin inhibition. Further, new derivative molecules were predicted for the best lead molecule by employing chemical space exploration. All datasets, descriptor values, QSAR models for predictions usage and plots will be available in <a href="https://github.com/giribio/agingdata">https://github.com/giribio/agingdata</a></p><p></p>

Computational methods for calculation of protein-ligand binding affinities in structure-based drug design

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Zbigniew Dutkiewicz
Keyword(s):  
Drug Design ◽  
Ligand Binding ◽  
Binding Free Energy ◽  
Development Project ◽  
Quantum Mechanical ◽  
Prediction Methods ◽  
Binding Affinities ◽  
Structure Based Drug Design ◽  
Quantum Mechanical Description ◽  
Optimization Stage

AbstractDrug design is an expensive and time-consuming process. Any method that allows reducing the time the costs of the drug development project can have great practical value for the pharmaceutical industry. In structure-based drug design, affinity prediction methods are of great importance. The majority of methods used to predict binding free energy in protein-ligand complexes use molecular mechanics methods. However, many limitations of these methods in describing interactions exist. An attempt to go beyond these limits is the application of quantum-mechanical description for all or only part of the analyzed system. However, the extensive use of quantum mechanical (QM) approaches in drug discovery is still a demanding challenge. This chapter briefly reviews selected methods used to calculate protein-ligand binding affinity applied in virtual screening (VS), rescoring of docked poses, and lead optimization stage, including QM methods based on molecular simulations.

scholarly journals Toward the Identification of Potential α-Ketoamide Covalent Inhibitors for SARS-CoV-2 Main Protease: Fragment-Based Drug Design and MM-PBSA Calculations

Processes ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 1004
Author(s):  
Mahmoud A. El Hassab ◽  
Mohamed Fares ◽  
Mohammed K. Abdel-Hamid Amin ◽  
Sara T. Al-Rashood ◽  
Amal Alharbi ◽  
...  
Keyword(s):  
Drug Design ◽  
Active Site ◽  
Binding Free Energy ◽  
Stable Complex ◽  
Active Site Residues ◽  
Structure Based Drug Design ◽  
Enzyme Active Site ◽  
Potential Inhibitor ◽  
Main Protease ◽  
Covalent Docking

Since December 2019, the world has been facing the outbreak of the SARS-CoV-2 pandemic that has infected more than 149 million and killed 3.1 million people by 27 April 2021, according to WHO statistics. Safety measures and precautions taken by many countries seem insufficient, especially with no specific approved drugs against the virus. This has created an urgent need to fast track the development of new medication against the virus in order to alleviate the problem and meet public expectations. The SARS-CoV-2 3CL main protease (Mpro) is one of the most attractive targets in the virus life cycle, which is responsible for the processing of the viral polyprotein and is a key for the ribosomal translation of the SARS-CoV-2 genome. In this work, we targeted this enzyme through a structure-based drug design (SBDD) protocol, which aimed at the design of a new potential inhibitor for Mpro. The protocol involves three major steps: fragment-based drug design (FBDD), covalent docking and molecular dynamics (MD) simulation with the calculation of the designed molecule binding free energy at a high level of theory. The FBDD step identified five molecular fragments, which were linked via a suitable carbon linker, to construct our designed compound RMH148. The mode of binding and initial interactions between RMH148 and the enzyme active site was established in the second step of our protocol via covalent docking. The final step involved the use of MD simulations to test for the stability of the docked RMH148 into the Mpro active site and included precise calculations for potential interactions with active site residues and binding free energies. The results introduced RMH148 as a potential inhibitor for the SARS-CoV-2 Mpro enzyme, which was able to achieve various interactions with the enzyme and forms a highly stable complex at the active site even better than the co-crystalized reference.

scholarly journals Chemical Space Mapping for Multicomponent Gas Mixtures

2021 ◽  
Author(s):  
Airat Kotliar-Shapirov ◽  
Fedor S. Fedorov ◽  
Henni Ouerdane ◽  
Stanislav Evlashin ◽  
Albert G. Nasibulin ◽  
...  
Keyword(s):  
Cyclic Voltammetry ◽  
Data Processing ◽  
Electrochemical Sensors ◽  
Chemical Space ◽  
Chemical Species ◽  
Single Species ◽  
Data Driven ◽  
Multicomponent Gas ◽  
Data Driven Approach ◽  
Cyclic Voltammetry Data

In our manuscript, we present our protocol for data processing to mitigate the effects of interfering analytes on the identification of the chemical species detected by sensors. Considering NO2 and CO2, we designed electrochemical sensors whose response yielded the cyclic voltammetry data that we analyzed to classify single-species components and their mixtures using a data-driven approach to generate a chemical space where their mixtures can be deconvoluted.<br>

Renin inhibitors for the treatment of hypertension: Design and optimization of a novel series of spirocyclic piperidines

2011 ◽  
Vol 21 (24) ◽  
pp. 7399-7404 ◽  
Author(s):  
Austin Chen ◽  
Renee Aspiotis ◽  
Louis-Charles Campeau ◽  
Elizabeth Cauchon ◽  
Amadine Chefson ◽  
...  
Keyword(s):  
Renin Inhibitors ◽  
Design And Optimization ◽  
Treatment Of Hypertension

Pharmacology of renin inhibitors and their application to the treatment of hypertension

1994 ◽  
Vol 61 (3) ◽  
pp. 325-344 ◽  
Author(s):  
Jeanette M. Wood ◽  
Frédéric Cumin ◽  
Jürgen Maibaum
Keyword(s):  
Renin Inhibitors ◽  
Treatment Of Hypertension

scholarly journals The tmQM Dataset - Quantum Geometries and Properties of 86k Transition Metal Complexes

2020 ◽  
Author(s):  
David Balcells ◽  
Bastian Bjerkem Skjelstad
Keyword(s):  
Transition Metal ◽  
Metal Complexes ◽  
Materials Science ◽  
Chemical Space ◽  
Molecular Size ◽  
Closed Shell ◽  
Organometallic Complexes ◽  
Node Degree ◽  
Strong Impact ◽  
Homo Lumo

<div>We report the transition metal quantum mechanics dataset (tmQM), which contains the geometries and properties of a large transition metal-organic compound space. tmQM is comprised of 86,665 mononuclear complexes extracted from the Cambridge Structural Database, including Werner, bioinorganic and organometallic complexes based on a large variety of organic ligands and 30 transition metals (the 3d, 4d and 5d from groups 3 to 12). All complexes are closed-shell, and with a formal charge in the range {+1, 0, -1}e. The tmQM dataset provides the Cartesian coordinates of all metal complexes optimized at the DFTB(GFN2-xTB) level, and their molecular size, stoichiometry, and metal node degree. The quantum properties were computed at the DFT(TPSSh-D3BJ/def2-SVP) level, and include the electronic and dispersion energies, HOMO and LUMO orbital energies, HOMO-LUMO gap, dipole moment, and natural charge of the metal center; DFTB(GFN2-xTB) polarizabilities are also provided. Pairwise representations showed the low correlation between these properties, providing nearly continuous maps with unusual regions of the chemical space; e.g. complexes combining large polarizabilities with wide HOMO-LUMO gaps, and complexes combining low-energy HOMO orbitals with electron-rich metal centers. The</div><div>tmQM dataset can be exploited in the data-driven discovery of new metal complexes, including predictive models based on machine learning. These models may have a strong impact on the fields in which transition metal chemistry plays a key role; e.g. catalysis, organic synthesis, and materials science. tmQM is an open dataset that can be downloaded free of charge from https://github.com/bbskjelstad/tmqm</div>

Transport of Gases in Porous Membranes

MRS Bulletin ◽  
1999 ◽  
Vol 24 (3) ◽  
pp. 41-45 ◽  
Author(s):  
Stratis V. Sotirchos ◽  
Vasilis N. Burganos
Keyword(s):  
Pore Space ◽  
Chemical Species ◽  
Molecular Size ◽  
Porous Membrane ◽  
Transport Processes ◽  
Porous Membranes ◽  
Gaseous Species ◽  
Interior Space ◽  
Separation Processes ◽  
Membrane Pore

The capability of membranes to affect differently, both qualitatively and quantitatively, the transport rates of chemical species of dissimilar chemical structure through their interior space renders them attractive for use in many separation problems. Extensive research efforts have thus been undertaken on the preparation and characterization of membrane materials and the study of the transport processes involved in their use in separation applications. The study of the transport of gaseous species through the pore space of porous membranes and the analysis and understanding of the mechanisms that are involved in this process are a very important, if not the most important, element in the development of membranebased separation processes.The resistance that a gaseous species encounters as it is transported through the pore space of a porous membrane is a function of its molecular properties, of its interaction with the material that makes up the walls of the pores, and of the membrane pore structure. Gaseous transport in pores can take place through various mechanisms, whose contribution to the overall transport rate of a particular species is, in general, determined by the strength of the interactions of the molecules of that species with the pore walls and by the relative magnitudes of three length scales that characterize the molecular size, the distance between pore walls, and the density of the fluid in the pore space.

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