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 Crystallographic and electrophilic fragment screening of the SARS-CoV-2 main protease

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Alice Douangamath ◽  
Daren Fearon ◽  
Paul Gehrtz ◽  
Tobias Krojer ◽  
Petra Lukacik ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Drug Design ◽  
Active Site ◽  
Large Scale ◽  
Structure Based Drug Design ◽  
Dimer Interface ◽  
X Ray ◽  
Fragment Screening ◽  
Viral Proteases ◽  
Main Protease

Abstract COVID-19, caused by SARS-CoV-2, lacks effective therapeutics. Additionally, no antiviral drugs or vaccines were developed against the closely related coronavirus, SARS-CoV-1 or MERS-CoV, despite previous zoonotic outbreaks. To identify starting points for such therapeutics, we performed a large-scale screen of electrophile and non-covalent fragments through a combined mass spectrometry and X-ray approach against the SARS-CoV-2 main protease, one of two cysteine viral proteases essential for viral replication. Our crystallographic screen identified 71 hits that span the entire active site, as well as 3 hits at the dimer interface. These structures reveal routes to rapidly develop more potent inhibitors through merging of covalent and non-covalent fragment hits; one series of low-reactivity, tractable covalent fragments were progressed to discover improved binders. These combined hits offer unprecedented structural and reactivity information for on-going structure-based drug design against SARS-CoV-2 main protease.

scholarly journals Covalent and Non-Covalent Binding Free Energy Calculations for Peptidomimetic Inhibitors of SARS-CoV-2 Main Protease

2020 ◽  
Author(s):  
Ernest Awoonor-Williams ◽  
Abd Al-Aziz A. Abu-Saleh
Keyword(s):  
Free Energy ◽  
Drug Design ◽  
Binding Free Energy ◽  
Covalent Binding ◽  
Free Energy Calculations ◽  
Total Binding Energy ◽  
Structure Based Drug Design ◽  
Main Protease ◽  
Covalent Adduct ◽  
Binding Free Energy Calculations

COVID-19, the disease caused by the newly discovered coronavirus — SARS-CoV-2, has created global health, social, and economic crisis. At the time of writing (November 12, 2020), there are over 50 million confirmed cases and more than 1 million reported deaths due to COVID-19. Currently, there are no approved vaccines, and recently Veklury (remdesivir) was approved for the treatment of COVID-19 requiring hospitalization. The main protease (M<sup>pro</sup>) of the virus is an attractive target for the development of effective antiviral therapeutics because it is required for proteolytic cleavage of viral polyproteins. Furthermore, the M<sup>pro</sup> has no human homologues, so drugs designed to bind to this target directly have less risk for off-target reactivity. Recently, several high-resolution crystallographic structures of the M<sup>pro</sup> in complex with inhibitors have been determined — to guide drug development and to spur efforts in structure-based drug design. One of the primary objectives of modern structure-based drug design is the accurate prediction of receptor­-ligand binding affinities for rational drug design and discovery. Here, we perform rigorous alchemical absolute binding free energy calculations and QM/MM calculations to give insight into the total binding energy of two recently crystallized inhibitors of SARS-CoV-2 M<sup>pro</sup>, namely, N3 and α-ketoamide 13b. The total binding energy consists of both covalent and non-covalent binding components since both compounds are covalent inhibitors of the M<sup>pro</sup>. Our results indicate that the covalent and non-covalent binding free energy contributions of both inhibitors to the M<sup>pro</sup> target differ significantly. The N3 inhibitor has more favourable non-covalent interactions, particularly hydrogen bonding, in the binding site of the M<sup>pro</sup> than the α-ketoamide inhibitor. But the Gibbs energy of reaction for the M<sup>pro</sup>–α-ketoamide covalent adduct is greater than the Gibbs reaction energy for the M<sup>pro</sup>–N3 covalent adduct. These differences in the covalent and non-covalent binding free energy contributions for both inhibitors could be a plausible explanation for their in vitro differences in antiviral activity. Our findings highlight the importance of both covalent and non-covalent binding free energy contributions to the absolute binding affinity of a covalent inhibitor towards its target.

scholarly journals Covalent and Non-Covalent Binding Free Energy Calculations for Peptidomimetic Inhibitors of SARS-CoV-2 Main Protease

2020 ◽  
Author(s):  
Ernest Awoonor-Williams ◽  
Abd Al-Aziz A. Abu-Saleh
Keyword(s):  
Free Energy ◽  
Drug Design ◽  
Binding Free Energy ◽  
Covalent Binding ◽  
Free Energy Calculations ◽  
Total Binding Energy ◽  
Structure Based Drug Design ◽  
Main Protease ◽  
Covalent Adduct ◽  
Binding Free Energy Calculations

COVID-19, the disease caused by the newly discovered coronavirus — SARS-CoV-2, has created global health, social, and economic crisis. At the time of writing (November 12, 2020), there are over 50 million confirmed cases and more than 1 million reported deaths due to COVID-19. Currently, there are no approved vaccines, and recently Veklury (remdesivir) was approved for the treatment of COVID-19 requiring hospitalization. The main protease (M<sup>pro</sup>) of the virus is an attractive target for the development of effective antiviral therapeutics because it is required for proteolytic cleavage of viral polyproteins. Furthermore, the M<sup>pro</sup> has no human homologues, so drugs designed to bind to this target directly have less risk for off-target reactivity. Recently, several high-resolution crystallographic structures of the M<sup>pro</sup> in complex with inhibitors have been determined — to guide drug development and to spur efforts in structure-based drug design. One of the primary objectives of modern structure-based drug design is the accurate prediction of receptor­-ligand binding affinities for rational drug design and discovery. Here, we perform rigorous alchemical absolute binding free energy calculations and QM/MM calculations to give insight into the total binding energy of two recently crystallized inhibitors of SARS-CoV-2 M<sup>pro</sup>, namely, N3 and α-ketoamide 13b. The total binding energy consists of both covalent and non-covalent binding components since both compounds are covalent inhibitors of the M<sup>pro</sup>. Our results indicate that the covalent and non-covalent binding free energy contributions of both inhibitors to the M<sup>pro</sup> target differ significantly. The N3 inhibitor has more favourable non-covalent interactions, particularly hydrogen bonding, in the binding site of the M<sup>pro</sup> than the α-ketoamide inhibitor. But the Gibbs energy of reaction for the M<sup>pro</sup>–α-ketoamide covalent adduct is greater than the Gibbs reaction energy for the M<sup>pro</sup>–N3 covalent adduct. These differences in the covalent and non-covalent binding free energy contributions for both inhibitors could be a plausible explanation for their in vitro differences in antiviral activity. Our findings highlight the importance of both covalent and non-covalent binding free energy contributions to the absolute binding affinity of a covalent inhibitor towards its target.

scholarly journals Computational Discovery of Small Drug-like Compounds as Potential Inhibitors of SARS-CoV-2 Main Protease

2020 ◽  
Author(s):  
Alexander M. Andrianov ◽  
Yuri V. Kornoushenko ◽  
Anna D. Karpenko ◽  
Ivan P. Bosko ◽  
Alexander Tuzikov
Keyword(s):  
Active Site ◽  
Binding Free Energy ◽  
Antiviral Agents ◽  
Binding Pocket ◽  
Van Der Waals Interactions ◽  
Salt Bridges ◽  
Enzyme Active Site ◽  
High Affinity ◽  
Affinity Ligand ◽  
Main Protease

A computational approach to in silico drug discovery was carried out to identify small druglike compounds able to show structural and functional mimicry of the high affinity ligand X77, potent non-covalent inhibitor of SARS-COV-2 main protease (MPro). In doing so, the X77-mimetic candidates were predicted based on the crystal X77-MPro structure by a public web-oriented virtual screening platform Pharmit. Models of these candidates bound to SARS-COV-2 MPro were generated by molecular docking and optimized by the quantum chemical method PM7. At the final point, analysis of the interaction modes of the identified compounds with MPro and prediction of their binding affinity were carried out. Calculation revealed 5 top-ranking compounds that exhibited a high affinity to the active site of SARS-CoV-2 MPro. Insights into the ligandMPro models indicate that all identified compounds may effectively block the binding pocket of SARS-CoV-2 MPro, in line with the low values of binding free energy and dissociation constant. Mechanism of binding of these compounds to MPro is generally provided by hydrogen bonds and van der Waals interactions with the functionally important residues of the enzyme active site, such as His-41, Leu-141, His-163, Met-165, and Glu166. In addition, individual ligands form salt bridges with the MPro residues His-163 or Glu-166 and participate in specific - interactions with the catalytic dyad residue His-41. The data obtained show that the identified X77-mimetic candidates may serve as good scaffolds for the design of novel antiviral agents able to target the active site of SARS-CoV-2 MPro.<br>

scholarly journals Crystallographic and electrophilic fragment screening of the SARS-CoV-2 main protease

2020 ◽  
Author(s):  
Alice Douangamath ◽  
Daren Fearon ◽  
Paul Gehrtz ◽  
Tobias Krojer ◽  
Petra Lukacik ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Drug Design ◽  
Active Site ◽  
Large Scale ◽  
Structure Based Drug Design ◽  
Dimer Interface ◽  
X Ray ◽  
Fragment Screening ◽  
Viral Proteases ◽  
Main Protease

SummaryCOVID-19, caused by SARS-CoV-2, lacks effective therapeutics. Additionally, no antiviral drugs or vaccines were developed against the closely related coronavirus, SARS-CoV-1 or MERS-CoV, despite previous zoonotic outbreaks. To identify starting points for such therapeutics, we performed a large-scale screen of electrophile and non-covalent fragments through a combined mass spectrometry and X-ray approach against the SARS-CoV-2 main protease, one of two cysteine viral proteases essential for viral replication. Our crystallographic screen identified 71 hits that span the entire active site, as well as 3 hits at the dimer interface. These structures reveal routes to rapidly develop more potent inhibitors through merging of covalent and non-covalent fragment hits; one series of low-reactivity, tractable covalent fragments was progressed to discover improved binders. These combined hits offer unprecedented structural and reactivity information for on-going structure-based drug design against SARS-CoV-2 main protease.

scholarly journals Computational Discovery of Small Drug-like Compounds as Potential Inhibitors of SARS-CoV-2 Main Protease

2020 ◽  
Author(s):  
Alexander M. Andrianov ◽  
Yuri V. Kornoushenko ◽  
Anna D. Karpenko ◽  
Ivan P. Bosko ◽  
Alexander Tuzikov
Keyword(s):  
Active Site ◽  
Binding Free Energy ◽  
Antiviral Agents ◽  
Binding Pocket ◽  
Van Der Waals Interactions ◽  
Salt Bridges ◽  
Enzyme Active Site ◽  
High Affinity ◽  
Affinity Ligand ◽  
Main Protease

A computational approach to in silico drug discovery was carried out to identify small druglike compounds able to show structural and functional mimicry of the high affinity ligand X77, potent non-covalent inhibitor of SARS-COV-2 main protease (MPro). In doing so, the X77-mimetic candidates were predicted based on the crystal X77-MPro structure by a public web-oriented virtual screening platform Pharmit. Models of these candidates bound to SARS-COV-2 MPro were generated by molecular docking and optimized by the quantum chemical method PM7. At the final point, analysis of the interaction modes of the identified compounds with MPro and prediction of their binding affinity were carried out. Calculation revealed 5 top-ranking compounds that exhibited a high affinity to the active site of SARS-CoV-2 MPro. Insights into the ligandMPro models indicate that all identified compounds may effectively block the binding pocket of SARS-CoV-2 MPro, in line with the low values of binding free energy and dissociation constant. Mechanism of binding of these compounds to MPro is generally provided by hydrogen bonds and van der Waals interactions with the functionally important residues of the enzyme active site, such as His-41, Leu-141, His-163, Met-165, and Glu166. In addition, individual ligands form salt bridges with the MPro residues His-163 or Glu-166 and participate in specific - interactions with the catalytic dyad residue His-41. The data obtained show that the identified X77-mimetic candidates may serve as good scaffolds for the design of novel antiviral agents able to target the active site of SARS-CoV-2 MPro.<br>

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 Modeling and synthesis of antiplasmodial chromones, chromanones and chalcones based on natural products of Kenya

2018 ◽  
Vol 16 (1) ◽  
pp. 8-21
Author(s):  
MANYIM SCOLASTICA ◽  
ALBERT J. NDAKALA ◽  
SOLOMON DERESE
Keyword(s):  
Natural Products ◽  
Drug Design ◽  
Active Site ◽  
Docking Studies ◽  
Moderate Activity ◽  
Vigorous Activity ◽  
Structure Based Drug Design ◽  
Web Based ◽  
Ic50 Values ◽  
Accessible Form

Scolastica M, Ndakala AJ, Derese S. 2018. Modeling and synthesis of antiplasmodial chromones, chromanones and chalcones based on natural products of Kenya. Biofarmasi J Nat Prod Biochem 16: 8-21. Despite numerous research that has been done on plants of Kenya resulting in the isolation of thousands of natural products, data on these natural products are not systematically organized in a readily accessible form. This has urged the construction of a web-based database of natural products of Kenya. The database is named Mitishamba and is hosted at http://mitishamba.uonbi.ac.ke. The Mitishamba database was queried for chromones, chromanones, and chalcones that were subjected to structure-based drug design using Fred (OpenEye) docking utility program with 1TV5 PDB structure of the PfDHODH receptor to identify complex of ligands that bind with the active site. Ligand-based drug design (Shape and electrostatics comparison) was also done on the ligands against query A77 1726 (38) (the ligand that co-crystallized with PfDHODH receptor) using ROCS and EON programs, respectively, of OpenEye suite. There was a substantial similarity among the top performing ligands in the docking studies with shape and electrostatic comparison that led to the identification of compounds of interest which were targeted for synthesis and antiplasmodial assay. In this study, a chromanone (7-hydroxy-2-(4-methoxyphenyl) chroman-4-one (48)) and two intermediate chalcones (2',4'-dihydroxy-4-methoxychalcone (45) and 2’,4’-dihydroxy-4-chlorochalcone (47)), were synthesized and subjected to antiplasmodial assay. Among these substances, 45 showed vigorous activity, whereas 47 and 48 had moderate activity against the chloroquine resistant K1 strain of P. falciparum with IC50 values of 4.56±1.66, 17.62 ± 5.94 and 18.01 ±1.66 µg/ml, respectively. Since the synthesized compounds showed antiplasmodial potential, there is a need for further computational refinement of these compounds to optimize their antiplasmodial activity.

Protein-Ligand Docking Methodologies and Its Application in Drug Discovery

2016 ◽  
pp. 196-219
Author(s):  
Sanchaita Rajkhowa ◽  
Ramesh C. Deka
Keyword(s):  
Molecular Docking ◽  
Drug Discovery ◽  
Drug Design ◽  
High Throughput Screening ◽  
Docking Studies ◽  
Stable Complex ◽  
Scoring Functions ◽  
Binding Modes ◽  
Structure Based Drug Design ◽  
Modern Drug

Molecular docking is a key tool in structural biology and computer-assisted drug design. Molecular docking is a method which predicts the preferred orientation of a ligand when bound in an active site to form a stable complex. It is the most common method used as a structure-based drug design. Here, the authors intend to discuss the various types of docking methods and their development and applications in modern drug discovery. The important basic theories such as sampling algorithm and scoring functions have been discussed briefly. The performances of the different available docking software have also been discussed. This chapter also includes some application examples of docking studies in modern drug discovery such as targeted drug delivery using carbon nanotubes, docking of nucleic acids to find the binding modes and a comparative study between high-throughput screening and structure-based virtual screening.

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