1
|
Péczka N, Ranđelović I, Orgován Z, Csorba N, Egyed A, Petri L, Ábrányi-Balogh P, Gadanecz M, Perczel A, Tóvári J, Schlosser G, Takács T, Mihalovits LM, Ferenczy G, Buday L, Keserű GM. Contribution of Noncovalent Recognition and Reactivity to the Optimization of Covalent Inhibitors: A Case Study on KRas G12C. ACS Chem Biol 2024; 19:1743-1756. [PMID: 38991015 PMCID: PMC11334105 DOI: 10.1021/acschembio.4c00217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Revised: 06/23/2024] [Accepted: 07/01/2024] [Indexed: 07/13/2024]
Abstract
Covalent drugs might bear electrophiles to chemically modify their targets and have the potential to target previously undruggable proteins with high potency. Covalent binding of drug-size molecules includes a noncovalent recognition provided by secondary interactions and a chemical reaction leading to covalent complex formation. Optimization of their covalent mechanism of action should involve both types of interactions. Noncovalent and covalent binding steps can be characterized by an equilibrium dissociation constant (KI) and a reaction rate constant (kinact), respectively, and they are affected by both the warhead and the scaffold of the ligand. The relative contribution of these two steps was investigated on a prototypic drug target KRASG12C, an oncogenic mutant of KRAS. We used a synthetically more accessible nonchiral core derived from ARS-1620 that was equipped with four different warheads and a previously described KRAS-specific basic side chain. Combining these structural changes, we have synthesized novel covalent KRASG12C inhibitors and tested their binding and biological effect on KRASG12C by various biophysical and biochemical assays. These data allowed us to dissect the effect of scaffold and warhead on the noncovalent and covalent binding event. Our results revealed that the atropisomeric core of ARS-1620 is not indispensable for KRASG12C inhibition, the basic side chain has little effect on either binding step, and warheads affect the covalent reactivity but not the noncovalent binding. This type of analysis helps identify structural determinants of efficient covalent inhibition and may find use in the design of covalent agents.
Collapse
Affiliation(s)
- Nikolett Péczka
- Medicinal
Chemistry Research Group and National Drug Discovery and Development
Laboratory, HUN-REN Research Centre for
Natural Sciences, Budapest 1117, Hungary
- Department
of Organic Chemistry and Technology, Budapest
University of Technology and Economics, Budapest 1111, Hungary
| | - Ivan Ranđelović
- Department
of Experimental Pharmacology and the National Tumor Biology Laboratory, National Institute of Oncology, Budapest 1122, Hungary
| | - Zoltán Orgován
- Medicinal
Chemistry Research Group and National Drug Discovery and Development
Laboratory, HUN-REN Research Centre for
Natural Sciences, Budapest 1117, Hungary
| | - Noémi Csorba
- Medicinal
Chemistry Research Group and National Drug Discovery and Development
Laboratory, HUN-REN Research Centre for
Natural Sciences, Budapest 1117, Hungary
- Department
of Organic Chemistry and Technology, Budapest
University of Technology and Economics, Budapest 1111, Hungary
| | - Attila Egyed
- Medicinal
Chemistry Research Group and National Drug Discovery and Development
Laboratory, HUN-REN Research Centre for
Natural Sciences, Budapest 1117, Hungary
| | - László Petri
- Medicinal
Chemistry Research Group and National Drug Discovery and Development
Laboratory, HUN-REN Research Centre for
Natural Sciences, Budapest 1117, Hungary
| | - Péter Ábrányi-Balogh
- Medicinal
Chemistry Research Group and National Drug Discovery and Development
Laboratory, HUN-REN Research Centre for
Natural Sciences, Budapest 1117, Hungary
| | - Márton Gadanecz
- Protein
Modeling Research Group, Laboratory of Structural Chemistry and Biology, ELTE Institute of Chemistry, Budapest 1117, Hungary
- Hevesy
György PhD School of Chemistry, Eötvös
Loránd University, Pázmány Péter sétány. 1/A, Budapest 1117, Hungary
| | - András Perczel
- Protein
Modeling Research Group, Laboratory of Structural Chemistry and Biology, ELTE Institute of Chemistry, Budapest 1117, Hungary
| | - József Tóvári
- Department
of Experimental Pharmacology and the National Tumor Biology Laboratory, National Institute of Oncology, Budapest 1122, Hungary
| | - Gitta Schlosser
- MTA-ELTE
“Lendület”, Ion Mobility
Mass Spectrometry Research Group, Budapest 1117, Hungary
| | - Tamás Takács
- HUN-REN
Research Centre for Natural Sciences, Signal
Transduction and Functional Genomics Research Group, Budapest 1117, Hungary
- Doctoral
School of Biology, Institute of Biology, ELTE Eötvös Loránd University, Budapest 1117, Hungary
| | - Levente M. Mihalovits
- Medicinal
Chemistry Research Group and National Drug Discovery and Development
Laboratory, HUN-REN Research Centre for
Natural Sciences, Budapest 1117, Hungary
| | - György
G. Ferenczy
- Medicinal
Chemistry Research Group and National Drug Discovery and Development
Laboratory, HUN-REN Research Centre for
Natural Sciences, Budapest 1117, Hungary
| | - László Buday
- HUN-REN
Research Centre for Natural Sciences, Signal
Transduction and Functional Genomics Research Group, Budapest 1117, Hungary
| | - György M. Keserű
- Medicinal
Chemistry Research Group and National Drug Discovery and Development
Laboratory, HUN-REN Research Centre for
Natural Sciences, Budapest 1117, Hungary
- Department
of Organic Chemistry and Technology, Budapest
University of Technology and Economics, Budapest 1111, Hungary
| |
Collapse
|
2
|
Zagórska A, Czopek A, Fryc M, Jończyk J. Inhibitors of SARS-CoV-2 Main Protease (Mpro) as Anti-Coronavirus Agents. Biomolecules 2024; 14:797. [PMID: 39062511 PMCID: PMC11275247 DOI: 10.3390/biom14070797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 07/01/2024] [Accepted: 07/03/2024] [Indexed: 07/28/2024] Open
Abstract
The main protease (Mpro) of SARS-CoV-2 is an essential enzyme that plays a critical part in the virus's life cycle, making it a significant target for developing antiviral drugs. The inhibition of SARS-CoV-2 Mpro has emerged as a promising approach for developing therapeutic agents to treat COVID-19. This review explores the structure of the Mpro protein and analyzes the progress made in understanding protein-ligand interactions of Mpro inhibitors. It focuses on binding kinetics, origin, and the chemical structure of these inhibitors. The review provides an in-depth analysis of recent clinical trials involving covalent and non-covalent inhibitors and emerging dual inhibitors targeting SARS-CoV-2 Mpro. By integrating findings from the literature and ongoing clinical trials, this review captures the current state of research into Mpro inhibitors, offering a comprehensive understanding of challenges and directions in their future development as anti-coronavirus agents. This information provides new insights and inspiration for medicinal chemists, paving the way for developing more effective Mpro inhibitors as novel COVID-19 therapies.
Collapse
Affiliation(s)
- Agnieszka Zagórska
- Department of Medicinal Chemistry, Jagiellonian University Medical College, Medyczna 9, 30-688 Kraków, Poland; (A.C.); (M.F.); (J.J.)
| | | | | | | |
Collapse
|
3
|
Rossetti G, Mandelli D. How exascale computing can shape drug design: A perspective from multiscale QM/MM molecular dynamics simulations and machine learning-aided enhanced sampling algorithms. Curr Opin Struct Biol 2024; 86:102814. [PMID: 38631106 DOI: 10.1016/j.sbi.2024.102814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 03/11/2024] [Accepted: 03/25/2024] [Indexed: 04/19/2024]
Abstract
Molecular simulations are an essential asset in the first steps of drug design campaigns. However, the requirement of high-throughput limits applications mainly to qualitative approaches with low computational cost, but also low accuracy. Unlocking the potential of more rigorous quantum mechanical/molecular mechanics (QM/MM) models combined with molecular dynamics-based free energy techniques could have a tremendous impact. Indeed, these two relatively old techniques are emerging as promising methods in the field. This has been favored by the exponential growth of computer power and the proliferation of powerful data-driven methods. Here, we briefly review recent advances and applications, and give our perspective on the impact that QM/MM and free-energy methods combined with machine learning-aided algorithms can have on drug design.
Collapse
Affiliation(s)
- Giulia Rossetti
- Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany; Department of Neurology, University Hospital Aachen (UKA), RWTH Aachen University, Aachen, Germany; Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich GmbH, Jülich 52428, Germany. https://twitter.com/G_Rossetti_
| | - Davide Mandelli
- Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany.
| |
Collapse
|
4
|
Nam K, Shao Y, Major DT, Wolf-Watz M. Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development. ACS OMEGA 2024; 9:7393-7412. [PMID: 38405524 PMCID: PMC10883025 DOI: 10.1021/acsomega.3c09084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 01/15/2024] [Accepted: 01/19/2024] [Indexed: 02/27/2024]
Abstract
Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.
Collapse
Affiliation(s)
- Kwangho Nam
- Department
of Chemistry and Biochemistry, University
of Texas at Arlington, Arlington, Texas 76019, United States
| | - Yihan Shao
- Department
of Chemistry and Biochemistry, University
of Oklahoma, Norman, Oklahoma 73019-5251, United States
| | - Dan T. Major
- Department
of Chemistry and Institute for Nanotechnology & Advanced Materials, Bar-Ilan University, Ramat-Gan 52900, Israel
| | | |
Collapse
|
5
|
Medrano FJ, de la Hoz-Rodríguez S, Martí S, Arafet K, Schirmeister T, Hammerschmidt SJ, Müller C, González-Martínez Á, Santillana E, Ziebuhr J, Romero A, Zimmer C, Weldert A, Zimmermann R, Lodola A, Świderek K, Moliner V, González FV. Peptidyl nitroalkene inhibitors of main protease rationalized by computational and crystallographic investigations as antivirals against SARS-CoV-2. Commun Chem 2024; 7:15. [PMID: 38238420 PMCID: PMC10796436 DOI: 10.1038/s42004-024-01104-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 01/09/2024] [Indexed: 01/22/2024] Open
Abstract
The coronavirus disease 2019 (COVID-19) pandemic continues to represent a global public health issue. The viral main protease (Mpro) represents one of the most attractive targets for the development of antiviral drugs. Herein we report peptidyl nitroalkenes exhibiting enzyme inhibitory activity against Mpro (Ki: 1-10 μM) good anti-SARS-CoV-2 infection activity in the low micromolar range (EC50: 1-12 μM) without significant toxicity. Additional kinetic studies of compounds FGA145, FGA146 and FGA147 show that all three compounds inhibit cathepsin L, denoting a possible multitarget effect of these compounds in the antiviral activity. Structural analysis shows the binding mode of FGA146 and FGA147 to the active site of the protein. Furthermore, our results illustrate that peptidyl nitroalkenes are effective covalent reversible inhibitors of the Mpro and cathepsin L, and that inhibitors FGA145, FGA146 and FGA147 prevent infection against SARS-CoV-2.
Collapse
Affiliation(s)
- Francisco J Medrano
- Centro de Investigaciones Biológicas Margarita Salas (CSIC), Ramiro de Maeztu 9, 28040, Madrid, Spain.
| | | | - Sergio Martí
- Departament de Química Física i Analítica, Universitat Jaume I, 12071, Castelló, Spain
| | - Kemel Arafet
- Departament de Química Física i Analítica, Universitat Jaume I, 12071, Castelló, Spain
| | - Tanja Schirmeister
- Institute of Pharmaceutical and BiomedicalSciences, Johannes Gutenberg-University Mainz, Staudinger Weg 5, 55128, Mainz, Germany
| | - Stefan J Hammerschmidt
- Institute of Pharmaceutical and BiomedicalSciences, Johannes Gutenberg-University Mainz, Staudinger Weg 5, 55128, Mainz, Germany
| | - Christin Müller
- Institute of Medical Virology, Justus Liebig University Giessen, Schubertstrasse 81, 35392, Giessen, Germany
| | - Águeda González-Martínez
- Centro de Investigaciones Biológicas Margarita Salas (CSIC), Ramiro de Maeztu 9, 28040, Madrid, Spain
| | - Elena Santillana
- Centro de Investigaciones Biológicas Margarita Salas (CSIC), Ramiro de Maeztu 9, 28040, Madrid, Spain
| | - John Ziebuhr
- Institute of Medical Virology, Justus Liebig University Giessen, Schubertstrasse 81, 35392, Giessen, Germany
| | - Antonio Romero
- Centro de Investigaciones Biológicas Margarita Salas (CSIC), Ramiro de Maeztu 9, 28040, Madrid, Spain
| | - Collin Zimmer
- Institute of Pharmaceutical and BiomedicalSciences, Johannes Gutenberg-University Mainz, Staudinger Weg 5, 55128, Mainz, Germany
| | - Annabelle Weldert
- Institute of Pharmaceutical and BiomedicalSciences, Johannes Gutenberg-University Mainz, Staudinger Weg 5, 55128, Mainz, Germany
| | - Robert Zimmermann
- Institute of Pharmaceutical and BiomedicalSciences, Johannes Gutenberg-University Mainz, Staudinger Weg 5, 55128, Mainz, Germany
| | - Alessio Lodola
- Dipartimento di Scienze degli Alimenti e del Farmaco, Università degli Studi di Parma, Parma, Italy
| | - Katarzyna Świderek
- Departament de Química Física i Analítica, Universitat Jaume I, 12071, Castelló, Spain
| | - Vicent Moliner
- Departament de Química Física i Analítica, Universitat Jaume I, 12071, Castelló, Spain.
| | - Florenci V González
- Departament de Química Inorgànica i Orgànica, Universitat Jaume I, 12071, Castelló, Spain.
| |
Collapse
|
6
|
Hasan MN, Ray M, Saha A. Landscape of In Silico Tools for Modeling Covalent Modification of Proteins: A Review on Computational Covalent Drug Discovery. J Phys Chem B 2023; 127:9663-9684. [PMID: 37921534 DOI: 10.1021/acs.jpcb.3c04710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2023]
Abstract
Covalent drug discovery has been a challenging research area given the struggle of finding a sweet balance between selectivity and reactivity for these drugs, the lack of which often leads to off-target activities and hence undesirable side effects. However, there has been a resurgence in covalent drug design following the success of several covalent drugs such as boceprevir (2011), ibrutinib (2013), neratinib (2017), dacomitinib (2018), zanubrutinib (2019), and many others. Design of covalent drugs includes many crucial factors, where "evaluation of the binding affinity" and "a detailed mechanistic understanding on covalent inhibition" are at the top of the list. Well-defined experimental techniques are available to elucidate these factors; however, often they are expensive and/or time-consuming and hence not suitable for high throughput screens. Recent developments in in silico methods provide promise in this direction. In this report, we review a set of recent publications that focused on developing and/or implementing novel in silico techniques in "Computational Covalent Drug Discovery (CCDD)". We also discuss the advantages and disadvantages of these approaches along with what improvements are required to make it a great tool in medicinal chemistry in the near future.
Collapse
Affiliation(s)
- Md Nazmul Hasan
- Department of Chemistry and Biochemistry, University of Wisconsin─Milwaukee, Milwaukee, Wisconsin 53211, United States
| | - Manisha Ray
- Department of Chemistry and Biochemistry, Loyola University Chicago, Chicago, Illinois 60660, United States
| | - Arjun Saha
- Department of Chemistry and Biochemistry, University of Wisconsin─Milwaukee, Milwaukee, Wisconsin 53211, United States
| |
Collapse
|
7
|
Zaman N, Azam SS. Discrete Dynamics of Warhead Modulation on Covalent Inhibition of Oxyr: A QM/MM Study. J Phys Chem B 2023. [PMID: 37377002 DOI: 10.1021/acs.jpcb.2c07376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2023]
Abstract
The bacterial transcriptional factor OxyR, a peroxide sensor conserved in bacterial virulence pathways, has the capability to exhibit exceptional reactivity toward hydrogen peroxide (H2O2). H2O2 is essential for oxidizing cysteine thiolates to maintain cellular redox homeostasis and is dispensable for bacterial growth that can potentially mitigate drug resistance, thus underlining OxyR as a valuable target. We employ quantum mechanics/molecular mechanics (QM/MM) umbrella sampling (US) simulations at the DFTB3/MM level of theory and propose a reaction mechanism with four potential covalent inhibitors. The potential of mean force reveals the direct role of intrinsic reactivity of inhibitors, for instance, benzothiophenes and modified experimental inhibitors with methyl oxo-enoate warhead-activated carbonyl samples in the first step of reaction, which shed light on the significance of proton transfer indispensable for full inhibition, whereas the nitrile inhibitor undergoes a stepwise mechanism with a small proton-transfer energy barrier and lower imaginary frequencies that materialize instantly after nucleophilic attack. To unveil the molecular determinants of respective binding affinities, transition states along the reaction path are optimized and characterized with B3LYP 6-31+G(d,p). Furthermore, the post-simulation analysis indicates the catalytic triad (His130/Cys199/Thr129), thermodynamically favored for inhibition, which restricts water molecules from acting as the potential source of protonation/deprotonation. This study thus serves as a preamble to add variation in the proposed structures and unveils the impact of functional groups lying in warheads that modulate the kinetics of proton transfer, which will certainly aid to design more selective and efficient irreversible inhibitors of OxyR.
Collapse
Affiliation(s)
- Naila Zaman
- Computational Biology Lab, National Center for Bioinformatics, Quaid-i-Azam University, Islamabad 45320, Pakistan
| | - Syed Sikander Azam
- Computational Biology Lab, National Center for Bioinformatics, Quaid-i-Azam University, Islamabad 45320, Pakistan
| |
Collapse
|
8
|
Chan HT, Oliveira ASF, Schofield CJ, Mulholland AJ, Duarte F. Dynamical Nonequilibrium Molecular Dynamics Simulations Identify Allosteric Sites and Positions Associated with Drug Resistance in the SARS-CoV-2 Main Protease. JACS AU 2023; 3:1767-1774. [PMID: 37384148 PMCID: PMC10262681 DOI: 10.1021/jacsau.3c00185] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 05/19/2023] [Accepted: 05/19/2023] [Indexed: 06/30/2023]
Abstract
The SARS-CoV-2 main protease (Mpro) plays an essential role in the coronavirus lifecycle by catalyzing hydrolysis of the viral polyproteins at specific sites. Mpro is the target of drugs, such as nirmatrelvir, though resistant mutants have emerged that threaten drug efficacy. Despite its importance, questions remain on the mechanism of how Mpro binds its substrates. Here, we apply dynamical nonequilibrium molecular dynamics (D-NEMD) simulations to evaluate structural and dynamical responses of Mpro to the presence and absence of a substrate. The results highlight communication between the Mpro dimer subunits and identify networks, including some far from the active site, that link the active site with a known allosteric inhibition site, or which are associated with nirmatrelvir resistance. They imply that some mutations enable resistance by altering the allosteric behavior of Mpro. More generally, the results show the utility of the D-NEMD technique for identifying functionally relevant allosteric sites and networks including those relevant to resistance.
Collapse
Affiliation(s)
- H. T.
Henry Chan
- Chemistry
Research Laboratory, Department of Chemistry and the Ineos Oxford
Institute for Antimicrobial Research, University
of Oxford, 12 Mansfield Road, Oxford OX1 3TA, UK
| | - A. Sofia F. Oliveira
- Centre
for Computational Chemistry, School of Chemistry, University of Bristol, Cantock’s Close, Bristol BS8 1TS, UK
- School
of Biochemistry, University of Bristol, Bristol BS8 1TD, UK
| | - Christopher J. Schofield
- Chemistry
Research Laboratory, Department of Chemistry and the Ineos Oxford
Institute for Antimicrobial Research, University
of Oxford, 12 Mansfield Road, Oxford OX1 3TA, UK
| | - Adrian J. Mulholland
- Centre
for Computational Chemistry, School of Chemistry, University of Bristol, Cantock’s Close, Bristol BS8 1TS, UK
| | - Fernanda Duarte
- Chemistry
Research Laboratory, Department of Chemistry and the Ineos Oxford
Institute for Antimicrobial Research, University
of Oxford, 12 Mansfield Road, Oxford OX1 3TA, UK
| |
Collapse
|
9
|
Arafet K, Royo S, Schirmeister T, Barthels F, González FV, Moliner V. Impact of the Recognition Part of Dipeptidyl Nitroalkene Compounds on the Inhibition Mechanism of Cysteine Proteases Cruzain and Cathepsin L. ACS Catal 2023; 13:6289-6300. [PMID: 37180968 PMCID: PMC10167892 DOI: 10.1021/acscatal.3c01035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 04/10/2023] [Indexed: 05/16/2023]
Abstract
Cysteine proteases (CPs) are an important class of enzymes, many of which are responsible for several human diseases. For instance, cruzain of protozoan parasite Trypanosoma cruzi is responsible for the Chagas disease, while the role of human cathepsin L is associated with some cancers or is a potential target for the treatment of COVID-19. However, despite paramount work carried out during the past years, the compounds that have been proposed so far show limited inhibitory action against these enzymes. We present a study of proposed covalent inhibitors of these two CPs, cruzain and cathepsin L, based on the design, synthesis, kinetic measurements, and QM/MM computational simulations on dipeptidyl nitroalkene compounds. The experimentally determined inhibition data, together with the analysis and the predicted inhibition constants derived from the free energy landscape of the full inhibition process, allowed describing the impact of the recognition part of these compounds and, in particular, the modifications on the P2 site. The designed compounds and, in particular, the one with a bulky group (Trp) at the P2 site show promising in vitro inhibition activities against cruzain and cathepsin L for use as a starting lead compound in the development of drugs with medical applications for the treatment of human diseases and future designs.
Collapse
Affiliation(s)
- Kemel Arafet
- Dipartimento
di Scienze degli Alimenti e del Farmaco, Università degli Studi di Parma, 43124 Parma, Italy
- BioComp
Group, Institute of Advanced Materials (INAM),
Universitat Jaume I, 12071 Castelló, Spain
| | - Santiago Royo
- Departament
de Química Inorgànica i Orgànica, Universitat Jaume I, 12071 Castelló, Spain
| | - Tanja Schirmeister
- Institute
of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-Universität, 55128 Mainz, Germany
| | - Fabian Barthels
- Institute
of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-Universität, 55128 Mainz, Germany
| | - Florenci V. González
- Departament
de Química Inorgànica i Orgànica, Universitat Jaume I, 12071 Castelló, Spain
| | - Vicent Moliner
- BioComp
Group, Institute of Advanced Materials (INAM),
Universitat Jaume I, 12071 Castelló, Spain
| |
Collapse
|
10
|
Ramos-Guzmán CA, Andjelkovic M, Zinovjev K, Ruiz-Pernía JJ, Tuñón I. The impact of SARS-CoV-2 3CL protease mutations on nirmatrelvir inhibitory efficiency. Computational insights into potential resistance mechanisms. Chem Sci 2023; 14:2686-2697. [PMID: 36908962 PMCID: PMC9993853 DOI: 10.1039/d2sc06584c] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 02/13/2023] [Indexed: 02/16/2023] Open
Abstract
The use of antiviral drugs can promote the appearance of mutations in the target protein that increase the resistance of the virus to the treatment. This is also the case of nirmatrelvir, a covalent inhibitor of the 3CL protease, or main protease, of SARS-CoV-2. In this work we show how the by-residue decomposition of noncovalent interactions established between the drug and the enzyme, in combination with an analysis of naturally occurring mutations, can be used to detect potential mutations in the 3CL protease conferring resistance to nirmatrelvir. We also investigate the consequences of these mutations on the reaction mechanism to form the covalent enzyme-inhibitor complex using QM/MM methods. In particular, we show that the E166V variant of the protease displays smaller binding affinity to nirmatrelvir and larger activation free energy for the formation of the covalent complex, both factors contributing to the observed resistance to the treatment with this drug. The conclusions derived from our work can be used to anticipate the consequences of the introduction of nirmatrelvir in the fitness landscape of the virus and to design new inhibitors adapted to some of the possible resistance mechanisms.
Collapse
Affiliation(s)
- Carlos A Ramos-Guzmán
- Departamento de Química Física, Universidad de Valencia 46100 Burjassot Spain
- Instituto de Materiales Avanzados, Universidad Jaume I 12071 Castelló Spain
| | - Milorad Andjelkovic
- Departamento de Química Física, Universidad de Valencia 46100 Burjassot Spain
| | - Kirill Zinovjev
- Departamento de Química Física, Universidad de Valencia 46100 Burjassot Spain
| | | | - Iñaki Tuñón
- Departamento de Química Física, Universidad de Valencia 46100 Burjassot Spain
| |
Collapse
|
11
|
Movilla S, Martí S, Roca M, Moliner V. Computational Study of the Inhibition of RgpB Gingipain, a Promising Target for the Treatment of Alzheimer's Disease. J Chem Inf Model 2023; 63:950-958. [PMID: 36648276 PMCID: PMC10882967 DOI: 10.1021/acs.jcim.2c01198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Alzheimer's disease represents one of the most ambitious challenges for biomedical sciences due to the growing number of cases worldwide in the elderly population and the lack of efficient treatments. One of the recent attempts to develop a treatment points to the cysteine protease RgpB as a promising drug target. In this attempt, several small-molecule covalent inhibitors of this enzyme have been proposed. Here, we report a computational study at the atomic level of the inhibition mechanism of the most promising reported compounds. Molecular dynamics simulations were performed on six of them, and their binding energies in the active site of the protein were computed. Contact maps and interaction energies were decomposed by residues to disclose those key interactions with the enzyme. Finally, quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations were performed to evaluate the reaction mechanism by which these drug candidates lead to covalently bound complexes, inhibiting the RgpB protease. The results provide a guide for future re-design of prospective and efficient inhibitors for the treatment of Alzheimer's disease.
Collapse
Affiliation(s)
- Santiago Movilla
- BioComp Group, Institute of Advanced Materials (INAM), Universitat Jaume I, 12071 Castellón, Spain
| | - Sergio Martí
- BioComp Group, Institute of Advanced Materials (INAM), Universitat Jaume I, 12071 Castellón, Spain
| | - Maite Roca
- BioComp Group, Institute of Advanced Materials (INAM), Universitat Jaume I, 12071 Castellón, Spain
| | - Vicent Moliner
- BioComp Group, Institute of Advanced Materials (INAM), Universitat Jaume I, 12071 Castellón, Spain
| |
Collapse
|
12
|
Liu Y, Sulaiman HF, Johnson BR, Ma R, Gao Y, Fernando H, Amarasekara A, Ashley-Oyewole A, Fan H, Ingram HN, Briggs JM. QM/MM study of N501 involved intermolecular interaction between SARS-CoV-2 receptor binding domain and antibody of human origin. Comput Biol Chem 2023; 102:107810. [PMID: 36610304 PMCID: PMC9811887 DOI: 10.1016/j.compbiolchem.2023.107810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 01/02/2023] [Accepted: 01/03/2023] [Indexed: 01/06/2023]
Abstract
Intermolecular interaction between key residue N501 of the epitope on SARS-CoV-2 RBD and screening antibody B38 was studied using the QM/MM and QM approach. The QM/MM optimized geometry shows that angle X-H---Y is 165° for O-H---O between mAb light chain S30 and RBD N501. High level MP2 calculations indicated the interaction between RBD N501 and S30 of B38 Fab light chain provide a relatively strong attractive force of - 3.32 kcal/mol, whereas the hydrogen bond between RBD Q498 and S30 was quantified as 0.10 kcal/mol. The decrease in ESP partial charge on hydrogen atom of hydroxyl group on S30 drops from 0.38 a.u. to 0.31 a.u., exhibiting the sharing of 0.07 a.u. from the lone pair electron oxygen of N501 due to hydrogen bond formation. The NBO occupancy of hydrogen atom also decreases from 25.79 % to 22.93 % in the hydroxyl H-O NBO bond of S30. However, the minor change of NBO hybridization of hydroxyl oxygen of S30 from sp3.00 to sp3.05 implies the rigidity of hydrogen bond tetrahedral geometry in the relative dynamic protein complex. The O-H---O angle is 165° which is close but not exactly linear. The structural requirement for sp3 hybridization of oxygen for hydroxyl group on S30 and dimension of protein likely prevent O-H---O from adopting linear geometry. The hydrogen bond strengths were also calculated using a variety of DFT methods, and the result of - 3.33 kcal/mol from the M06L method is the closest to that of the MP2 calculation. Results of this work may aid in the COVID-19 vaccine and drug screening.
Collapse
Affiliation(s)
- Yuemin Liu
- Department of Chemistry, Prairie View A&M University, Prairie View, TX 77446, the United States of America,Department of Chemistry, Rice University, Houston, TX 77005, the United States of America,Corresponding author at: Department of Chemistry, Prairie View A&M University, Prairie View, TX 77446, the United States of America
| | - Hana F. Sulaiman
- Department of Chemistry, Prairie View A&M University, Prairie View, TX 77446, the United States of America
| | - Bruce R. Johnson
- Department of Chemistry, Rice University, Houston, TX 77005, the United States of America
| | - Rulong Ma
- Department of Biology and Biochemistry, University of Houston, Houston, TX 77004, the United States of America
| | - Yunxiang Gao
- Department of Chemistry, Prairie View A&M University, Prairie View, TX 77446, the United States of America
| | - Harshica Fernando
- Department of Chemistry, Prairie View A&M University, Prairie View, TX 77446, the United States of America
| | - Ananda Amarasekara
- Department of Chemistry, Prairie View A&M University, Prairie View, TX 77446, the United States of America
| | - Andrea Ashley-Oyewole
- Department of Chemistry, Prairie View A&M University, Prairie View, TX 77446, the United States of America
| | - Huajun Fan
- College of Chemical Engineering, Sichuan University Science and Engineering, Zigong, Sichuan 643000, PR China
| | - Heaven N. Ingram
- Department of Chemistry, Prairie View A&M University, Prairie View, TX 77446, the United States of America
| | - James M. Briggs
- Department of Biology and Biochemistry, University of Houston, Houston, TX 77004, the United States of America
| |
Collapse
|
13
|
La Monica G, Bono A, Lauria A, Martorana A. Targeting SARS-CoV-2 Main Protease for Treatment of COVID-19: Covalent Inhibitors Structure-Activity Relationship Insights and Evolution Perspectives. J Med Chem 2022; 65:12500-12534. [PMID: 36169610 PMCID: PMC9528073 DOI: 10.1021/acs.jmedchem.2c01005] [Citation(s) in RCA: 54] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Indexed: 02/07/2023]
Abstract
The viral main protease is one of the most attractive targets among all key enzymes involved in the SARS-CoV-2 life cycle. Covalent inhibition of the cysteine145 of SARS-CoV-2 MPRO with selective antiviral drugs will arrest the replication process of the virus without affecting human catalytic pathways. In this Perspective, we analyzed the in silico, in vitro, and in vivo data of the most representative examples of covalent SARS-CoV-2 MPRO inhibitors reported in the literature to date. In particular, the studied molecules were classified into eight different categories according to their reactive electrophilic warheads, highlighting the differences between their reversible/irreversible mechanism of inhibition. Furthermore, the analyses of the most recurrent pharmacophoric moieties and stereochemistry of chiral carbons were reported. The analyses of noncovalent and covalent in silico protocols, provided in this Perspective, would be useful for the scientific community to discover new and more efficient covalent SARS-CoV-2 MPRO inhibitors.
Collapse
Affiliation(s)
| | | | - Antonino Lauria
- Dipartimento di Scienze e
Tecnologie Biologiche Chimiche e Farmaceutiche, University of Palermo, Viale delle Scienze, Ed. 17, I-90128 Palermo, Italy
| | - Annamaria Martorana
- Dipartimento di Scienze e
Tecnologie Biologiche Chimiche e Farmaceutiche, University of Palermo, Viale delle Scienze, Ed. 17, I-90128 Palermo, Italy
| |
Collapse
|
14
|
Mazmanian K, Chen T, Sargsyan K, Lim C. From quantum-derived principles underlying cysteine reactivity to combating the COVID-19 pandemic. WILEY INTERDISCIPLINARY REVIEWS. COMPUTATIONAL MOLECULAR SCIENCE 2022; 12:e1607. [PMID: 35600063 PMCID: PMC9111396 DOI: 10.1002/wcms.1607] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 01/31/2022] [Accepted: 02/13/2022] [Indexed: 12/20/2022]
Abstract
The COVID-19 pandemic poses a challenge in coming up with quick and effective means to counter its cause, the SARS-CoV-2. Here, we show how the key factors governing cysteine reactivity in proteins derived from combined quantum mechanical/continuum calculations led to a novel multi-targeting strategy against SARS-CoV-2, in contrast to developing potent drugs/vaccines against a single viral target such as the spike protein. Specifically, they led to the discovery of reactive cysteines in evolutionary conserved Zn2+-sites in several SARS-CoV-2 proteins that are crucial for viral polypeptide proteolysis as well as viral RNA synthesis, proofreading, and modification. These conserved, reactive cysteines, both free and Zn2+-bound, can be targeted using the same Zn-ejector drug (disulfiram/ebselen), which enables the use of broad-spectrum anti-virals that would otherwise be removed by the virus's proofreading mechanism. Our strategy of targeting multiple, conserved viral proteins that operate at different stages of the virus life cycle using a Zn-ejector drug combined with other broad-spectrum anti-viral drug(s) could enhance the barrier to drug resistance and antiviral effects, as compared to each drug alone. Since these functionally important nonstructural proteins containing reactive cysteines are highly conserved among coronaviruses, our proposed strategy has the potential to tackle future coronaviruses. This article is categorized under:Structure and Mechanism > Reaction Mechanisms and CatalysisStructure and Mechanism > Computational Biochemistry and BiophysicsElectronic Structure Theory > Density Functional Theory.
Collapse
Affiliation(s)
| | - Ting Chen
- Institute of Biomedical Sciences Academia Sinica Taipei Taiwan
| | - Karen Sargsyan
- Institute of Biomedical Sciences Academia Sinica Taipei Taiwan
| | - Carmay Lim
- Institute of Biomedical Sciences Academia Sinica Taipei Taiwan
- Department of Chemistry National Tsing Hua University Hsinchu Taiwan
| |
Collapse
|
15
|
Ramos-Guzmán CA, Velázquez-Libera JL, Ruiz-Pernía JJ, Tuñón I. Testing Affordable Strategies for the Computational Study of Reactivity in Cysteine Proteases: The Case of SARS-CoV-2 3CL Protease Inhibition. J Chem Theory Comput 2022; 18:4005-4013. [PMID: 35549334 PMCID: PMC9115880 DOI: 10.1021/acs.jctc.2c00294] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
![]()
Cysteine proteases are an important target for the development of inhibitors that could
be used as drugs to regulate the activity of these kinds of enzymes involved in many
diseases, including COVID-19. For this reason, it is important to have methodological
tools that allow a detailed study of their activity and inhibition, combining
computational efficiency and accuracy. We here explore the performance of different
quantum mechanics/molecular mechanics methods to explore the inhibition reaction
mechanism of the SARS-CoV-2 3CL protease with a hydroxymethyl ketone derivative. We
selected two density functional theory (DFT) functionals (B3LYP and M06-2X), two
semiempirical Hamiltonians (AM1d and PM6), and two tight-binding DFT methods (DFTB3 and
GFN2-xTB) to explore the free energy landscape associated with this reaction. We show
that it is possible to obtain an accurate description combining molecular dynamics
simulations performed using tight-binding DFT methods and single-point energy
corrections at a higher QM description. The use of a computational strategy that
provides reliable results at a reasonable computational cost could assist the in silico
screening of possible candidates during the design of new drugs directed against
cysteine proteases.
Collapse
Affiliation(s)
- Carlos A Ramos-Guzmán
- Departamento de Química Física, Universitat de Valencia, Burjassot, Valencia 46100, Spain
| | - José Luis Velázquez-Libera
- Departamento de Química Física, Universitat de Valencia, Burjassot, Valencia 46100, Spain.,Departamento de Bioinformática, Facultad de Ingeniería, Centro de Bioinformática, Simulación y Modelado (CBSM), Universidad de Talca, Talca 3460000, Chile
| | - J Javier Ruiz-Pernía
- Departamento de Química Física, Universitat de Valencia, Burjassot, Valencia 46100, Spain
| | - Iñaki Tuñón
- Departamento de Química Física, Universitat de Valencia, Burjassot, Valencia 46100, Spain
| |
Collapse
|
16
|
El Khoury L, Jing Z, Cuzzolin A, Deplano A, Loco D, Sattarov B, Hédin F, Wendeborn S, Ho C, El Ahdab D, Jaffrelot Inizan T, Sturlese M, Sosic A, Volpiana M, Lugato A, Barone M, Gatto B, Macchia ML, Bellanda M, Battistutta R, Salata C, Kondratov I, Iminov R, Khairulin A, Mykhalonok Y, Pochepko A, Chashka-Ratushnyi V, Kos I, Moro S, Montes M, Ren P, Ponder JW, Lagardère L, Piquemal JP, Sabbadin D. Computationally driven discovery of SARS-CoV-2 M pro inhibitors: from design to experimental validation. Chem Sci 2022; 13:3674-3687. [PMID: 35432906 PMCID: PMC8966641 DOI: 10.1039/d1sc05892d] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 02/03/2022] [Indexed: 11/21/2022] Open
Abstract
We report a fast-track computationally driven discovery of new SARS-CoV-2 main protease (Mpro) inhibitors whose potency ranges from mM for the initial non-covalent ligands to sub-μM for the final covalent compound (IC50 = 830 ± 50 nM). The project extensively relied on high-resolution all-atom molecular dynamics simulations and absolute binding free energy calculations performed using the polarizable AMOEBA force field. The study is complemented by extensive adaptive sampling simulations that are used to rationalize the different ligand binding poses through the explicit reconstruction of the ligand-protein conformation space. Machine learning predictions are also performed to predict selected compound properties. While simulations extensively use high performance computing to strongly reduce the time-to-solution, they were systematically coupled to nuclear magnetic resonance experiments to drive synthesis and for in vitro characterization of compounds. Such a study highlights the power of in silico strategies that rely on structure-based approaches for drug design and allows the protein conformational multiplicity problem to be addressed. The proposed fluorinated tetrahydroquinolines open routes for further optimization of Mpro inhibitors towards low nM affinities.
Collapse
Affiliation(s)
- Léa El Khoury
- Qubit Pharmaceuticals, Incubateur Paris Biotech Santé 24 Rue du Faubourg Saint Jacques 75014 Paris France
| | - Zhifeng Jing
- Qubit Pharmaceuticals, Incubateur Paris Biotech Santé 24 Rue du Faubourg Saint Jacques 75014 Paris France
| | - Alberto Cuzzolin
- Chiesi Farmaceutici S.p.A, Nuovo Centro Ricerche Largo Belloli 11a 43122 Parma Italy
| | - Alessandro Deplano
- Pharmacelera, Torre R, 4a planta Despatx A05, Parc Cientific de Barcelona, Baldiri Reixac 8 08028 Barcelona Spain
| | - Daniele Loco
- Qubit Pharmaceuticals, Incubateur Paris Biotech Santé 24 Rue du Faubourg Saint Jacques 75014 Paris France
| | - Boris Sattarov
- Qubit Pharmaceuticals, Incubateur Paris Biotech Santé 24 Rue du Faubourg Saint Jacques 75014 Paris France
| | - Florent Hédin
- Qubit Pharmaceuticals, Incubateur Paris Biotech Santé 24 Rue du Faubourg Saint Jacques 75014 Paris France
| | - Sebastian Wendeborn
- University of Applied Sciences and Arts Northwestern Switzerland, School of LifeSciences Hofackerstrasse 30 CH-4132 Muttenz Switzerland
| | - Chris Ho
- Qubit Pharmaceuticals, Incubateur Paris Biotech Santé 24 Rue du Faubourg Saint Jacques 75014 Paris France
| | - Dina El Ahdab
- Sorbonne Université, Laboratoire de Chimie Théorique, UMR 7616 CNRS 75005 Paris France
| | - Theo Jaffrelot Inizan
- Sorbonne Université, Laboratoire de Chimie Théorique, UMR 7616 CNRS 75005 Paris France
| | - Mattia Sturlese
- Molecular Modeling Section, Department of Pharmaceutical and Pharmacological Sciences, University of Padua via F. Marzolo 5 35131 Padova Italy
| | - Alice Sosic
- Department of Pharmaceutical and Pharmacological Sciences, University of Padova via Marzolo 5 35131 Padova Italy
| | - Martina Volpiana
- Department of Pharmaceutical and Pharmacological Sciences, University of Padova via Marzolo 5 35131 Padova Italy
| | - Angela Lugato
- Department of Pharmaceutical and Pharmacological Sciences, University of Padova via Marzolo 5 35131 Padova Italy
| | - Marco Barone
- Department of Pharmaceutical and Pharmacological Sciences, University of Padova via Marzolo 5 35131 Padova Italy
| | - Barbara Gatto
- Department of Pharmaceutical and Pharmacological Sciences, University of Padova via Marzolo 5 35131 Padova Italy
| | - Maria Ludovica Macchia
- Department of Pharmaceutical and Pharmacological Sciences, University of Padova via Marzolo 5 35131 Padova Italy
| | - Massimo Bellanda
- Department of Chemistry, University of Padova via Marzolo 1 35131 Padova Italy
| | - Roberto Battistutta
- Department of Chemistry, University of Padova via Marzolo 1 35131 Padova Italy
| | - Cristiano Salata
- Department of Molecular Medicine, University of Padua via Gabelli 63 35121 Padova Italy
| | | | - Rustam Iminov
- Enamine Ltd 78 Chervonotkats'ka Str. Kyiv 02094 Ukraine
| | | | | | | | | | - Iaroslava Kos
- Enamine Ltd 78 Chervonotkats'ka Str. Kyiv 02094 Ukraine
| | - Stefano Moro
- Molecular Modeling Section, Department of Pharmaceutical and Pharmacological Sciences, University of Padua via F. Marzolo 5 35131 Padova Italy
| | - Matthieu Montes
- Laboratoire GBCM, EA7528, Conservatoire National des Arts et Métiers, Hesam Université 2 Rue Conte 75003 Paris France
| | - Pengyu Ren
- University of Texas at Austin, Department of Biomedical Engineering TX 78712 USA
| | - Jay W Ponder
- Department of Chemistry, Washington University in Saint Louis MO 63130 USA
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine MO 63110 USA
| | - Louis Lagardère
- Sorbonne Université, Laboratoire de Chimie Théorique, UMR 7616 CNRS 75005 Paris France
| | - Jean-Philip Piquemal
- Sorbonne Université, Laboratoire de Chimie Théorique, UMR 7616 CNRS 75005 Paris France
- Institut Universitaire de France 75005 Paris France
| | - Davide Sabbadin
- Qubit Pharmaceuticals, Incubateur Paris Biotech Santé 24 Rue du Faubourg Saint Jacques 75014 Paris France
| |
Collapse
|