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Bach K, Dohnálek J, Škerlová J, Kuzmík J, Poláchová E, Stanchev S, Majer P, Fanfrlík J, Pecina A, Řezáč J, Lepšík M, Borshchevskiy V, Polovinkin V, Strisovsky K. Extensive targeting of chemical space at the prime side of ketoamide inhibitors of rhomboid proteases by branched substituents empowers their selectivity and potency. Eur J Med Chem 2024; 275:116606. [PMID: 38901105 DOI: 10.1016/j.ejmech.2024.116606] [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: 04/04/2024] [Revised: 06/10/2024] [Accepted: 06/14/2024] [Indexed: 06/22/2024]
Abstract
Rhomboid intramembrane serine proteases have been implicated in several pathologies, and emerge as attractive pharmacological target candidates. The most potent and selective rhomboid inhibitors available to date are peptidyl α-ketoamides, but their selectivity for diverse rhomboid proteases and strategies to modulate it in relevant contexts are poorly understood. This gap, together with the lack of suitable in vitro models, hinders ketoamide development for relevant eukaryotic rhomboid enzymes. Here we explore the structure-activity relationship principles of rhomboid inhibiting ketoamides by medicinal chemistry and enzymatic in vitro and in-cell assays with recombinant rhomboid proteases GlpG, human mitochondrial rhomboid PARL and human RHBDL2. We use X-ray crystallography in lipidic cubic phase to understand the binding mode of one of the best ketoamide inhibitors synthesized here containing a branched terminal substituent bound to GlpG. In addition, to extend the interpretation of the co-crystal structure, we use quantum mechanical calculations and quantify the relative importance of interactions along the inhibitor molecule. These combined experimental analyses implicates that more extensive exploration of chemical space at the prime side is unexpectedly powerful for the selectivity of rhomboid inhibiting ketoamides. Together with variations in the peptide sequence at the non-prime side, or its non-peptidic alternatives, this strategy enables targeted tailoring of potent and selective ketoamides towards diverse rhomboid proteases including disease-relevant ones such as PARL and RHBDL2.
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Affiliation(s)
- Kathrin Bach
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Science, Flemingovo n. 2, Prague, 160 00, Czech Republic; Department of Molecular Genetics, Faculty of Science, Charles University, Viničná 5, Prague, 128 44, Czech Republic
| | - Jan Dohnálek
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Science, Flemingovo n. 2, Prague, 160 00, Czech Republic; University of Chemistry and Technology, Technická 5, Prague, 166 28, Czech Republic
| | - Jana Škerlová
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Science, Flemingovo n. 2, Prague, 160 00, Czech Republic
| | - Ján Kuzmík
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Science, Flemingovo n. 2, Prague, 160 00, Czech Republic
| | - Edita Poláchová
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Science, Flemingovo n. 2, Prague, 160 00, Czech Republic; First Faculty of Medicine, Charles University, Kateřinská 32, Prague, 121 08, Czech Republic
| | - Stancho Stanchev
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Science, Flemingovo n. 2, Prague, 160 00, Czech Republic
| | - Pavel Majer
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Science, Flemingovo n. 2, Prague, 160 00, Czech Republic
| | - Jindřich Fanfrlík
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Science, Flemingovo n. 2, Prague, 160 00, Czech Republic
| | - Adam Pecina
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Science, Flemingovo n. 2, Prague, 160 00, Czech Republic
| | - Jan Řezáč
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Science, Flemingovo n. 2, Prague, 160 00, Czech Republic
| | - Martin Lepšík
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Science, Flemingovo n. 2, Prague, 160 00, Czech Republic
| | - Valentin Borshchevskiy
- Institute of Biological Information Processing 7, IBI-7 (Structural Biochemistry) Forschungszentrum Jülich 52428 Jülich, Germany
| | - Vitaly Polovinkin
- ELI Beamlines Centre, ELI ERIC, Za Radnicí 835, 252 41, Dolní Břežany, Czech Republic
| | - Kvido Strisovsky
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Science, Flemingovo n. 2, Prague, 160 00, Czech Republic.
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2
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Ginex T, Vázquez J, Estarellas C, Luque FJ. Quantum mechanical-based strategies in drug discovery: Finding the pace to new challenges in drug design. Curr Opin Struct Biol 2024; 87:102870. [PMID: 38914031 DOI: 10.1016/j.sbi.2024.102870] [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: 04/21/2024] [Revised: 06/02/2024] [Accepted: 06/04/2024] [Indexed: 06/26/2024]
Abstract
The expansion of the chemical space to tangible libraries containing billions of synthesizable molecules opens exciting opportunities for drug discovery, but also challenges the power of computer-aided drug design to prioritize the best candidates. This directly hits quantum mechanics (QM) methods, which provide chemically accurate properties, but subject to small-sized systems. Preserving accuracy while optimizing the computational cost is at the heart of many efforts to develop high-quality, efficient QM-based strategies, reflected in refined algorithms and computational approaches. The design of QM-tailored physics-based force fields and the coupling of QM with machine learning, in conjunction with the computing performance of supercomputing resources, will enhance the ability to use these methods in drug discovery. The challenge is formidable, but we will undoubtedly see impressive advances that will define a new era.
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Affiliation(s)
- Tiziana Ginex
- Pharmacelera, Parc Científic de Barcelona (PCB), Baldiri Reixac 4-8, 08028 Barcelona, Spain
| | - Javier Vázquez
- Pharmacelera, Parc Científic de Barcelona (PCB), Baldiri Reixac 4-8, 08028 Barcelona, Spain; Departament de Nutrició, Ciències de l'Alimentació i Gastronomia, Universitat de Barcelona, Institut de Biomedicina (IBUB), 08921 Santa Coloma de Gramenet, Spain; Institut de Biomedicina (IBUB), 08921 Santa Coloma de Gramenet, Spain
| | - Carolina Estarellas
- Departament de Nutrició, Ciències de l'Alimentació i Gastronomia, Universitat de Barcelona, Institut de Biomedicina (IBUB), 08921 Santa Coloma de Gramenet, Spain; Institut de Química Teòrica i Computacional (IQTCUB), 08921 Santa Coloma de Gramenet, Spain
| | - F Javier Luque
- Departament de Nutrició, Ciències de l'Alimentació i Gastronomia, Universitat de Barcelona, Institut de Biomedicina (IBUB), 08921 Santa Coloma de Gramenet, Spain; Institut de Biomedicina (IBUB), 08921 Santa Coloma de Gramenet, Spain; Institut de Química Teòrica i Computacional (IQTCUB), 08921 Santa Coloma de Gramenet, Spain.
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3
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Paciotti R, Re N, Storchi L. Combining the Fragment Molecular Orbital and GRID Approaches for the Prediction of Ligand-Metalloenzyme Binding Affinity: The Case Study of hCA II Inhibitors. Molecules 2024; 29:3600. [PMID: 39125005 PMCID: PMC11313991 DOI: 10.3390/molecules29153600] [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: 06/27/2024] [Revised: 07/18/2024] [Accepted: 07/29/2024] [Indexed: 08/12/2024] Open
Abstract
Polarization and charge-transfer interactions play an important role in ligand-receptor complexes containing metals, and only quantum mechanics methods can adequately describe their contribution to the binding energy. In this work, we selected a set of benzenesulfonamide ligands of human Carbonic Anhydrase II (hCA II)-an important druggable target containing a Zn2+ ion in the active site-as a case study to predict the binding free energy in metalloprotein-ligand complexes and designed specialized computational methods that combine the ab initio fragment molecular orbital (FMO) method and GRID approach. To reproduce the experimental binding free energy in these systems, we adopted a machine-learning approach, here named formula generator (FG), considering different FMO energy terms, the hydrophobic interaction energy (computed by GRID) and logP. The main advantage of the FG approach is that it can find nonlinear relations between the energy terms used to predict the binding free energy, explicitly showing their mathematical relation. This work showed the effectiveness of the FG approach, and therefore, it might represent an important tool for the development of new scoring functions. Indeed, our scoring function showed a high correlation with the experimental binding free energy (R2 = 0.76-0.95, RMSE = 0.34-0.18), revealing a nonlinear relation between energy terms and highlighting the relevant role played by hydrophobic contacts. These results, along with the FMO characterization of ligand-receptor interactions, represent important information to support the design of new and potent hCA II inhibitors.
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Affiliation(s)
- Roberto Paciotti
- Department of Pharmacy, Università “G. D’Annunzio” Di Chieti-Pescara, 66100 Chieti, Italy; (N.R.); (L.S.)
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Singh K, Bhushan B, Singh B. Advances in Drug Discovery and Design using Computer-aided Molecular Modeling. Curr Comput Aided Drug Des 2024; 20:697-710. [PMID: 37711101 DOI: 10.2174/1573409920666230914123005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 08/09/2023] [Accepted: 08/15/2023] [Indexed: 09/16/2023]
Abstract
Computer-aided molecular modeling is a rapidly emerging technology that is being used to accelerate the discovery and design of new drug therapies. It involves the use of computer algorithms and 3D structures of molecules to predict interactions between molecules and their behavior in the body. This has drastically improved the speed and accuracy of drug discovery and design. Additionally, computer-aided molecular modeling has the potential to reduce costs, increase the quality of data, and identify promising targets for drug development. Through the use of sophisticated methods, such as virtual screening, molecular docking, pharmacophore modeling, and quantitative structure-activity relationships, scientists can achieve higher levels of efficacy and safety for new drugs. Moreover, it can be used to understand the activity of known drugs and simplify the process of formulating, optimizing, and predicting the pharmacokinetics of new and existing drugs. In conclusion, computer-aided molecular modeling is an effective tool to rapidly progress drug discovery and design by predicting the interactions between molecules and anticipating the behavior of new drugs in the body.
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Affiliation(s)
- Kuldeep Singh
- Department of Pharmacology, Rajiv Academy for Pharmacy, Mathura Uttar Pradesh, India
| | - Bharat Bhushan
- Department of Pharmacology, Institute of Pharmaceutical Research, GLA University, Mathura Uttar Pradesh, India
| | - Bhoopendra Singh
- Department of Pharmacy, B.S.A. College of Engineering & Technology, Mathura Uttar Pradesh India
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Stylianakis I, Zervos N, Lii JH, Pantazis DA, Kolocouris A. Conformational energies of reference organic molecules: benchmarking of common efficient computational methods against coupled cluster theory. J Comput Aided Mol Des 2023; 37:607-656. [PMID: 37597063 PMCID: PMC10618395 DOI: 10.1007/s10822-023-00513-5] [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: 05/09/2023] [Accepted: 06/03/2023] [Indexed: 08/21/2023]
Abstract
We selected 145 reference organic molecules that include model fragments used in computer-aided drug design. We calculated 158 conformational energies and barriers using force fields, with wide applicability in commercial and free softwares and extensive application on the calculation of conformational energies of organic molecules, e.g. the UFF and DREIDING force fields, the Allinger's force fields MM3-96, MM3-00, MM4-8, the MM2-91 clones MMX and MM+, the MMFF94 force field, MM4, ab initio Hartree-Fock (HF) theory with different basis sets, the standard density functional theory B3LYP, the second-order post-HF MP2 theory and the Domain-based Local Pair Natural Orbital Coupled Cluster DLPNO-CCSD(T) theory, with the latter used for accurate reference values. The data set of the organic molecules includes hydrocarbons, haloalkanes, conjugated compounds, and oxygen-, nitrogen-, phosphorus- and sulphur-containing compounds. We reviewed in detail the conformational aspects of these model organic molecules providing the current understanding of the steric and electronic factors that determine the stability of low energy conformers and the literature including previous experimental observations and calculated findings. While progress on the computer hardware allows the calculations of thousands of conformations for later use in drug design projects, this study is an update from previous classical studies that used, as reference values, experimental ones using a variety of methods and different environments. The lowest mean error against the DLPNO-CCSD(T) reference was calculated for MP2 (0.35 kcal mol-1), followed by B3LYP (0.69 kcal mol-1) and the HF theories (0.81-1.0 kcal mol-1). As regards the force fields, the lowest errors were observed for the Allinger's force fields MM3-00 (1.28 kcal mol-1), ΜΜ3-96 (1.40 kcal mol-1) and the Halgren's MMFF94 force field (1.30 kcal mol-1) and then for the MM2-91 clones MMX (1.77 kcal mol-1) and MM+ (2.01 kcal mol-1) and MM4 (2.05 kcal mol-1). The DREIDING (3.63 kcal mol-1) and UFF (3.77 kcal mol-1) force fields have the lowest performance. These model organic molecules we used are often present as fragments in drug-like molecules. The values calculated using DLPNO-CCSD(T) make up a valuable data set for further comparisons and for improved force field parameterization.
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Affiliation(s)
- Ioannis Stylianakis
- Department of Medicinal Chemistry, Faculty of Pharmacy, National and Kapodistrian University of Athens, Panepistimioupolis Zografou, 15771, Athens, Greece
| | - Nikolaos Zervos
- Department of Medicinal Chemistry, Faculty of Pharmacy, National and Kapodistrian University of Athens, Panepistimioupolis Zografou, 15771, Athens, Greece
| | - Jenn-Huei Lii
- Department of Chemistry, National Changhua University of Education, Changhua City, Taiwan
| | - Dimitrios A Pantazis
- Max-Planck-Institut für Kohlenforschung, Kaiser-Wilhelm-Platz 1, 45470, Mülheim an der Ruhr, Germany
| | - Antonios Kolocouris
- Department of Medicinal Chemistry, Faculty of Pharmacy, National and Kapodistrian University of Athens, Panepistimioupolis Zografou, 15771, Athens, Greece.
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771, Athens, Greece.
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6
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Szél V, Zsidó BZ, Jeszenői N, Hetényi C. Target-ligand binding affinity from single point enthalpy calculation and elemental composition. Phys Chem Chem Phys 2023; 25:31714-31725. [PMID: 37964670 DOI: 10.1039/d3cp04483a] [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: 11/16/2023]
Abstract
Reliable target-ligand binding thermodynamics data are essential for successful drug design and molecular engineering projects. Besides experimental methods, a number of theoretical approaches have been introduced for the generation of binding thermodynamics data. However, available approaches often neglect electronic effects or explicit water molecules influencing target-ligand interactions. To handle electronic effects within a reasonable time frame, we introduce a fast calculator QMH-L using a single target-ligand complex structure pre-optimized at the molecular mechanics level. QMH-L is composed of the semi-empirical quantum mechanics calculation of binding enthalpy with predicted explicit water molecules at the complex interface, and a simple descriptor based on the elemental composition of the ligand. QMH-L estimates the target-ligand binding free energy with a root mean square error (RMSE) of 0.94 kcal mol-1. The calculations also provide binding enthalpy values and they were compared with experimental binding thermodynamics data collected from the most reliable isothermal titration calorimetry studies of systems including various protein targets and challenging, large peptide ligands with a molecular weight of up to 2-3 thousand. The single point enthalpy calculations of QMH-L require modest computational resources and are based on short runs with open source and/or free software like Gromacs, Mopac, MobyWat, and Fragmenter. QMH-L can be applied for fast, automated scoring of drug candidates during a virtual screen, enthalpic engineering of new ligands or thermodynamic explanation of complex interactions.
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Affiliation(s)
- Viktor Szél
- Pharmacoinformatics Unit, Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Szigeti út 12, 7624 Pécs, Hungary.
| | - Balázs Zoltán Zsidó
- Pharmacoinformatics Unit, Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Szigeti út 12, 7624 Pécs, Hungary.
| | - Norbert Jeszenői
- Pharmacoinformatics Unit, Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Szigeti út 12, 7624 Pécs, Hungary.
| | - Csaba Hetényi
- Pharmacoinformatics Unit, Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Szigeti út 12, 7624 Pécs, Hungary.
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7
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Řezáč J, Stewart JJP. How well do semiempirical QM methods describe the structure of proteins? J Chem Phys 2023; 158:044118. [PMID: 36725526 DOI: 10.1063/5.0135091] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Semiempirical quantum-mechanical (QM) computational methods are an increasingly popular tool for the study of biomolecular systems. They were, however, developed and tested mostly on small model molecules. In this work, we explore one topic fundamental to these applications: the ability of the methods to describe the structure of proteins. In a set of 19 proteins for which a crystal structure with very high resolution is available, we analyze the properties of the protein geometries optimized using several semiempirical QM methods including PM6-D3H4, PM7, and GFN2-xTB. Some of the methods provide a very good description of the general structural features of the protein, yielding results better than or comparable to the AMBER ff03 force field. However, PM7 and PM6-D3H4 optimizations introduce artificial close contacts in the structure, which is partially remediated by reparameterization.
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Affiliation(s)
- J Řezáč
- Institute of Organic Chemistry and Biochemistry, Czech Academy of Sciences, 16000 Prague, Czech Republic
| | - J J P Stewart
- Stewart Computational Chemistry, 15210 Paddington Circle, Colorado Springs, Colorado 80921, USA
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8
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Fanfrlík J, Brynda J, Kugler M, Lepšík M, Pospíšilová K, Holub J, Hnyk D, Nekvinda J, Grüner B, Řezáčová P. B-H⋯π and C-H⋯π interactions in protein-ligand complexes: carbonic anhydrase II inhibition by carborane sulfonamides. Phys Chem Chem Phys 2023; 25:1728-1733. [PMID: 36594655 DOI: 10.1039/d2cp04673c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Among non-covalent interactions, B-H⋯π and C-H⋯π hydrogen bonding is rather weak and less studied. Nevertheless, since both can affect the energetics of protein-ligand binding, their understanding is an important prerequisite for reliable predictions of affinities. Through a combination of high-resolution X-ray crystallography and quantum-chemical calculations on carbonic anhydrase II/carborane-based inhibitor systems, this paper provides the first example of B-H⋯π hydrogen bonding in a protein-ligand complex. It shows that the B-H⋯π interaction is stabilized by dispersion, followed by electrostatics. Furthermore, it demonstrates that the similar C-H⋯π interaction is twice as strong, with a slightly smaller contribution of dispersion and a slightly higher contribution of electrostatics. Such a detailed insight will facilitate the rational design of future protein ligands, controlling these types of non-covalent interactions.
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Affiliation(s)
- Jindřich Fanfrlík
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Flemingovo nam. 2, 166 10, Prague 6, Czech Republic.
| | - Jiří Brynda
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Flemingovo nam. 2, 166 10, Prague 6, Czech Republic.
| | - Michael Kugler
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Flemingovo nam. 2, 166 10, Prague 6, Czech Republic.
| | - Martin Lepšík
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Flemingovo nam. 2, 166 10, Prague 6, Czech Republic.
| | - Klára Pospíšilová
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Flemingovo nam. 2, 166 10, Prague 6, Czech Republic.
| | - Josef Holub
- Institute of Inorganic Chemistry of the Czech Academy of Sciences, 250 68 Husinec-Řež, Czech Republic
| | - Drahomír Hnyk
- Institute of Inorganic Chemistry of the Czech Academy of Sciences, 250 68 Husinec-Řež, Czech Republic
| | - Jan Nekvinda
- Institute of Inorganic Chemistry of the Czech Academy of Sciences, 250 68 Husinec-Řež, Czech Republic
| | - Bohumír Grüner
- Institute of Inorganic Chemistry of the Czech Academy of Sciences, 250 68 Husinec-Řež, Czech Republic
| | - Pavlína Řezáčová
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Flemingovo nam. 2, 166 10, Prague 6, Czech Republic.
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9
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Liu X, Zheng L, Cong Y, Gong Z, Yin Z, Zhang JZH, Liu Z, Sun Z. Comprehensive evaluation of end-point free energy techniques in carboxylated-pillar[6]arene host-guest binding: II. regression and dielectric constant. J Comput Aided Mol Des 2022; 36:879-894. [PMID: 36394776 DOI: 10.1007/s10822-022-00487-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 10/29/2022] [Indexed: 11/18/2022]
Abstract
End-point free energy calculations as a powerful tool have been widely applied in protein-ligand and protein-protein interactions. It is often recognized that these end-point techniques serve as an option of intermediate accuracy and computational cost compared with more rigorous statistical mechanic models (e.g., alchemical transformation) and coarser molecular docking. However, it is observed that this intermediate level of accuracy does not hold in relatively simple and prototypical host-guest systems. Specifically, in our previous work investigating a set of carboxylated-pillar[6]arene host-guest complexes, end-point methods provide free energy estimates deviating significantly from the experimental reference, and the rank of binding affinities is also incorrectly computed. These observations suggest the unsuitability and inapplicability of standard end-point free energy techniques in host-guest systems, and alteration and development are required to make them practically usable. In this work, we consider two ways to improve the performance of end-point techniques. The first one is the PBSA_E regression that varies the weights of different free energy terms in the end-point calculation procedure, while the second one is considering the interior dielectric constant as an additional variable in the end-point equation. By detailed investigation of the calculation procedure and the simulation outcome, we prove that these two treatments (i.e., regression and dielectric constant) are manipulating the end-point equation in a somehow similar way, i.e., weakening the electrostatic contribution and strengthening the non-polar terms, although there are still many detailed differences between these two methods. With the trained end-point scheme, the RMSE of the computed affinities is improved from the standard ~ 12 kcal/mol to ~ 2.4 kcal/mol, which is comparable to another altered end-point method (ELIE) trained with system-specific data. By tuning PBSA_E weighting factors with the host-specific data, it is possible to further decrease the prediction error to ~ 2.1 kcal/mol. These observations along with the extremely efficient optimized-structure computation procedure suggest the regression (i.e., PBSA_E as well as its GBSA_E extension) as a practically applicable solution that brings end-point methods back into the library of usable tools for host-guest binding. However, the dielectric-constant-variable scheme cannot effectively minimize the experiment-calculation discrepancy for absolute binding affinities, but is able to improve the calculation of affinity ranks. This phenomenon is somehow different from the protein-ligand case and suggests the difference between host-guest and biomacromolecular (protein-ligand and protein-protein) systems. Therefore, the spectrum of tools usable for protein-ligand complexes could be unsuitable for host-guest binding, and numerical validations are necessary to screen out really workable solutions in these 'prototypical' situations.
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Affiliation(s)
- Xiao Liu
- School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai, 201620, China.
| | - Lei Zheng
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai, 200062, China
| | - Yalong Cong
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200062, China
| | - Zhihao Gong
- School of Micro-Nano Electronics, Zhejiang University, Hangzhou, 310027, China.,Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 310027, China
| | - Zhixiang Yin
- School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai, 201620, China
| | - John Z H Zhang
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai, 200062, China. .,School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200062, China. .,Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China. .,Department of Chemistry, New York University, NY, NY, 10003, USA.
| | - Zhirong Liu
- College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
| | - Zhaoxi Sun
- College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China.
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10
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Liu X, Zheng L, Qin C, Zhang JZH, Sun Z. Comprehensive evaluation of end-point free energy techniques in carboxylated-pillar[6]arene host-guest binding: I. Standard procedure. J Comput Aided Mol Des 2022; 36:735-752. [PMID: 36136209 DOI: 10.1007/s10822-022-00475-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 09/06/2022] [Indexed: 10/14/2022]
Abstract
Despite the massive application of end-point free energy methods in protein-ligand and protein-protein interactions, computational understandings about their performance in relatively simple and prototypical host-guest systems are limited. In this work, we present a comprehensive benchmark calculation with standard end-point free energy techniques in a recent host-guest dataset containing 13 host-guest pairs involving the carboxylated-pillar[6]arene host. We first assess the charge schemes for solutes by comparing the charge-produced electrostatics with many ab initio references, in order to obtain a preliminary albeit detailed view of the charge quality. Then, we focus on four modelling details of end-point free energy calculations, including the docking procedure for the generation of initial condition, the charge scheme for host and guest molecules, the water model used in explicit-solvent sampling, and the end-point methods for free energy estimation. The binding thermodynamics obtained with different modelling schemes are compared with experimental references, and some practical guidelines on maximizing the performance of end-point methods in practical host-guest systems are summarized. Further, we compare our simulation outcome with predictions in the grand challenge and discuss further developments to improve the prediction quality of end-point free energy methods. Overall, unlike the widely acknowledged applicability in protein-ligand binding, the standard end-point calculations cannot produce useful outcomes in host-guest binding and thus are not recommended unless alterations are performed.
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Affiliation(s)
- Xiao Liu
- School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai, 201620, China.
| | - Lei Zheng
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai, 200062, China
| | - Chu Qin
- School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai, 201620, China
| | - John Z H Zhang
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai, 200062, China.,School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200062, China.,Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China.,Department of Chemistry, New York University, New York, NY, 10003, USA
| | - Zhaoxi Sun
- College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China.
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11
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Li J, Maravelias CT, Van Lehn RC. Adaptive Conformer Sampling for Property Prediction Using the Conductor-like Screening Model for Real Solvents. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c01163] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Jianping Li
- Department of Chemical and Biological Engineering and DOE Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Christos T. Maravelias
- Department of Chemical and Biological Engineering and Andlinger Center for Energy and the Environment, Princeton University, Princeton, New Jersey 08540, United States
| | - Reid C. Van Lehn
- Department of Chemical and Biological Engineering and DOE Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
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12
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Qu X, Dong L, Si Y, Zhao Y, Wang Q, Su P, Wang B. Reliable Prediction of the Protein-Ligand Binding Affinity Using a Charge Penetration Corrected AMOEBA Force Field: A Case Study of Drug Resistance Mutations in Abl Kinase. J Chem Theory Comput 2022; 18:1692-1700. [PMID: 35107298 DOI: 10.1021/acs.jctc.1c01005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Protein mutations that directly impair drug binding are related to therapeutic resistance, and accurate prediction of their impact on drug binding would benefit drug design and clinical practice. Here, we have developed a scoring strategy that predicts the effect of the mutations on the protein-ligand binding affinity. In view of the critical importance of electrostatics in protein-ligand interactions, the charge penetration corrected AMOEBA force field (AMOEBA_CP model) was employed to improve the accuracy of the calculated electrostatic energy. We calculated the electrostatic energy using an energy decomposition analysis scheme based on the generalized Kohn-Sham (GKS-EDA). The AMOEBA_CP model was validated by a protein-fragment-ligand complex data set (Abl236) constructed from the co-crystal structures of the cancer target Abl kinase with six inhibitors. To predict ligand binding affinity changes upon protein mutation of Abl kinase, we used sampling protocol with multistep simulated annealing to search conformations of mutant proteins. The scoring strategy based on AMOEBA_CP model has achieved considerable performance in predicting resistance for 8 kinase inhibitors across 144 clinically identified point mutations. Overall, this study illustrates that the AMOEBA_CP model, which accurately treats electrostatics through penetration correction, enables the accurate prediction of the mutation-induced variation of protein-ligand binding affinity.
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Affiliation(s)
- Xiaoyang Qu
- State Key Laboratory of Physical Chemistry of Solid Surfaces and Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - Lina Dong
- State Key Laboratory of Physical Chemistry of Solid Surfaces and Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - Yubing Si
- College of Chemistry, Zhengzhou University, Zhengzhou 450001, P. R. China
| | - Yuan Zhao
- The Key Laboratory of Natural Medicine and Immuno-Engineering, Henan University, Kaifeng 475004, P. R. China
| | - Qiantao Wang
- Key Laboratory of Drug-Targeting and Drug Delivery System of the Education Ministry and Sichuan Province, Sichuan Engineering Laboratory for Plant-Sourced Drug and Sichuan Research Center for Drug Precision Industrial Technology, West China School of Pharmacy, Sichuan University, Chengdu 610041, P. R. China
| | - Peifeng Su
- State Key Laboratory of Physical Chemistry of Solid Surfaces and Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - Binju Wang
- State Key Laboratory of Physical Chemistry of Solid Surfaces and Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
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13
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Manigrasso J, Marcia M, De Vivo M. Computer-aided design of RNA-targeted small molecules: A growing need in drug discovery. Chem 2021. [DOI: 10.1016/j.chempr.2021.05.021] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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14
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Dostál J, Brynda J, Vaňková L, Zia SR, Pichová I, Heidingsfeld O, Lepšík M. Structural determinants for subnanomolar inhibition of the secreted aspartic protease Sapp1p from Candida parapsilosis. J Enzyme Inhib Med Chem 2021; 36:914-921. [PMID: 33843395 PMCID: PMC8043539 DOI: 10.1080/14756366.2021.1906664] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Pathogenic Candida albicans yeasts frequently cause infections in hospitals. Antifungal drugs lose effectiveness due to other Candida species and resistance. New medications are thus required. Secreted aspartic protease of C. parapsilosis (Sapp1p) is a promising target. We have thus solved the crystal structures of Sapp1p complexed to four peptidomimetic inhibitors. Three potent inhibitors (Ki: 0.1, 0.4, 6.6 nM) resembled pepstatin A (Ki: 0.3 nM), a general aspartic protease inhibitor, in terms of their interactions with Sapp1p. However, the weaker inhibitor (Ki: 14.6 nM) formed fewer nonpolar contacts with Sapp1p, similarly to the smaller HIV protease inhibitor ritonavir (Ki: 1.9 µM), which, moreover, formed fewer H-bonds. The analyses have revealed the structural determinants of the subnanomolar inhibition of C. parapsilosis aspartic protease. Because of the high similarity between Saps from different Candida species, these results can further be used for the design of potent and specific Sap inhibitor-based antimycotic drugs.
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Affiliation(s)
- Jiří Dostál
- Institute of Organic Chemistry and Biochemistry, Czech Academy of Sciences, Prague, Czech Republic
| | - Jiří Brynda
- Institute of Organic Chemistry and Biochemistry, Czech Academy of Sciences, Prague, Czech Republic
| | - Lucie Vaňková
- Laboratory of Ligand Engineering, Institute of Biotechnology, Czech Academy of Sciences, v.v.i., BIOCEV Research Center, Vestec, Czech Republic
| | - Syeda Rehana Zia
- Department of Chemistry, University of Karachi, Karachi, Pakistan
| | - Iva Pichová
- Institute of Organic Chemistry and Biochemistry, Czech Academy of Sciences, Prague, Czech Republic
| | - Olga Heidingsfeld
- Institute of Organic Chemistry and Biochemistry, Czech Academy of Sciences, Prague, Czech Republic.,Department of Biochemistry, Faculty of Science, Charles University in Prague, Prague, Czech Republic
| | - Martin Lepšík
- Institute of Organic Chemistry and Biochemistry, Czech Academy of Sciences, Prague, Czech Republic
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15
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Gregor J, Radilová K, Brynda J, Fanfrlík J, Konvalinka J, Kožíšek M. Structural and Thermodynamic Analysis of the Resistance Development to Pimodivir (VX-787), the Clinical Inhibitor of Cap Binding to PB2 Subunit of Influenza A Polymerase. Molecules 2021; 26:molecules26041007. [PMID: 33673017 PMCID: PMC7917969 DOI: 10.3390/molecules26041007] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 01/20/2021] [Accepted: 02/12/2021] [Indexed: 01/06/2023] Open
Abstract
Influenza A virus (IAV) encodes a polymerase composed of three subunits: PA, with endonuclease activity, PB1 with polymerase activity and PB2 with host RNA five-prime cap binding site. Their cooperation and stepwise activation include a process called cap-snatching, which is a crucial step in the IAV life cycle. Reproduction of IAV can be blocked by disrupting the interaction between the PB2 domain and the five-prime cap. An inhibitor of this interaction called pimodivir (VX-787) recently entered the third phase of clinical trial; however, several mutations in PB2 that cause resistance to pimodivir were observed. First major mutation, F404Y, causing resistance was identified during preclinical testing, next the mutation M431I was identified in patients during the second phase of clinical trials. The mutation H357N was identified during testing of IAV strains at Centers for Disease Control and Prevention. We set out to provide a structural and thermodynamic analysis of the interactions between cap-binding domain of PB2 wild-type and PB2 variants bearing these mutations and pimodivir. Here we present four crystal structures of PB2-WT, PB2-F404Y, PB2-M431I and PB2-H357N in complex with pimodivir. We have thermodynamically analysed all PB2 variants and proposed the effect of these mutations on thermodynamic parameters of these interactions and pimodivir resistance development. These data will contribute to understanding the effect of these missense mutations to the resistance development and help to design next generation inhibitors.
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Affiliation(s)
- Jiří Gregor
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Gilead Sciences and IOCB Research Center, Flemingovo n. 2, 16610 Prague 6, Czech Republic; (J.G.); (K.R.); (J.B.); (J.F.)
- First Faculty of Medicine, Charles University, Kateřinská 1660/32, 12108 Prague 2, Czech Republic
| | - Kateřina Radilová
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Gilead Sciences and IOCB Research Center, Flemingovo n. 2, 16610 Prague 6, Czech Republic; (J.G.); (K.R.); (J.B.); (J.F.)
- First Faculty of Medicine, Charles University, Kateřinská 1660/32, 12108 Prague 2, Czech Republic
| | - Jiří Brynda
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Gilead Sciences and IOCB Research Center, Flemingovo n. 2, 16610 Prague 6, Czech Republic; (J.G.); (K.R.); (J.B.); (J.F.)
| | - Jindřich Fanfrlík
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Gilead Sciences and IOCB Research Center, Flemingovo n. 2, 16610 Prague 6, Czech Republic; (J.G.); (K.R.); (J.B.); (J.F.)
| | - Jan Konvalinka
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Gilead Sciences and IOCB Research Center, Flemingovo n. 2, 16610 Prague 6, Czech Republic; (J.G.); (K.R.); (J.B.); (J.F.)
- Department of Biochemistry, Faculty of Science, Charles University, Hlavova 8, 12800 Prague 2, Czech Republic
- Correspondence: (J.K.); (M.K.); Tel.: +420-220-183-218 (J.K.)
| | - Milan Kožíšek
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Gilead Sciences and IOCB Research Center, Flemingovo n. 2, 16610 Prague 6, Czech Republic; (J.G.); (K.R.); (J.B.); (J.F.)
- Correspondence: (J.K.); (M.K.); Tel.: +420-220-183-218 (J.K.)
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