The center piece of this thesis is the key-lock metaphor, specifically in the context of computer-aided drug design. This concept was introduced in chapter 1 where the process of drug discovery... Show moreThe center piece of this thesis is the key-lock metaphor, specifically in the context of computer-aided drug design. This concept was introduced in chapter 1 where the process of drug discovery and lead optimization is discussed. Due to the fact that there are many locks (proteins) and even more keys (ligands), computational research can provide an interesting opportunity to aid and speedup drug discovery. Different methods are introduced in chapter 1, which were used throughout this thesis. In chapter 2 an overview is provided of the different methods of docking and Virtual Screening in the context of GPCRs. Chapter 3 demonstrates the importance of including water molecules in Virtual Screening. In Chapter 4 a Virtual Screen is applied with explicit water molecules on the Adenosine A2A receptor. Chapter 5 presents and discusses an alternative method of analyzing Virtual Screens, Interaction Fingerprints. In Chapter 6 it is demonstrated that more recent statistical methods like deep neural networks are able to outperform other methods, like naïve bayes and random forests. Chapter 7 introduces a method of calculating relative binding energy differences, Free Energy Perturbation (FEP). In Chapter 8 we conclude the thesis with general conclusions and an outlook of the field. Show less
The structure of the human A(2A) adenosine receptor has been elucidated by X-ray crystallography with a high affinity non-xanthine antagonist, ZM241385, bound to it. This template molecule served... Show moreThe structure of the human A(2A) adenosine receptor has been elucidated by X-ray crystallography with a high affinity non-xanthine antagonist, ZM241385, bound to it. This template molecule served as a starting point for the incorporation of reactive moieties that cause the ligand to covalently bind to the receptor. In particular, we incorporated a fluorosulfonyl moiety onto ZM241385, which yielded LUF7445 (4-((3-((7-amino-2-(furan-2-yl)-[1, 2, 4]triazolo[1,5-a][1, 3, 5]triazin-5-yl)amino)propyl)carbamoyl)benzene sulfonyl fluoride). In a radioligand binding assay, LUF7445 acted as a potent antagonist, with an apparent affinity for the hA(2A) receptor in the nanomolar range. Its apparent affinity increased with longer incubation time, suggesting an increasing level of covalent binding over time. An in silico A(2A)-structure-based docking model was used to study the binding mode of LUF7445. This led us to perform site-directed mutagenesis of the A(2A) receptor to probe and validate the target lysine amino acid K153 for covalent binding. Meanwhile, a functional assay combined with wash-out experiments was set up to investigate the efficacy of covalent binding of LUF7445. All these experiments led us to conclude LUF7445 is a valuable molecular tool for further investigating covalent interactions at this receptor. It may also serve as a prototype for a therapeutic approach in which a covalent antagonist may be needed to counteract prolonged and persistent presence of the endogenous ligand adenosine. Show less
Alachouzos, G.; Lenselink, E.B.; Mulder-Krieger, T.; Vries, H. de; IJzerman, A.P.; Louvel, J. 2017
We report the synthesis and biological evaluation of new 2-amino-4,5-diarylpyrimidines as selective antagonists at the adenosine A(1) receptor. The scaffold they are based upon is a deaza variation... Show moreWe report the synthesis and biological evaluation of new 2-amino-4,5-diarylpyrimidines as selective antagonists at the adenosine A(1) receptor. The scaffold they are based upon is a deaza variation of a previously reported collection of 3-amino-5,6-diaryl-1,2,4-triazines, members of which had a sub-nanomolar affinity but limited selectivity over the A(2A) subtype. Initially, similar structure-affinity relationships at the 5-aryl ring were established, and then emphasis was put on increasing selectivity at the hA(1)AR by introducing substituents on the N-2-position, all the while maintaining a nanomolar affinity. Compound 3z, bearing a trans 4-hydroxycyclohexyl substituent, was identified as a potent (K-i(hA(1)AR) = 7.7 nM) and selective (K-i(hA(2)AAR) = 1389 nM) antagonist at the human adenosine A(1) receptor. Computational docking was effected at the A(1) and A(2A) subtypes, rationalizing the effect of the 4-hydroxycyclohexyl substituent on selectivity, in relation with the nature of the substituent on the 5-position of the pyrimidine. (C) 2016 Elsevier Masson SAS. All rights reserved. Show less
A covalent antagonist for the human adenosine A2A receptor Xue Yang, Guo Dong, Thomas J.M. Michiels, Eelke B. Lenselink, Laura Heitman, Julien Louvel, Ad P. IJzerman Abstract The structure of the... Show moreA covalent antagonist for the human adenosine A2A receptor Xue Yang, Guo Dong, Thomas J.M. Michiels, Eelke B. Lenselink, Laura Heitman, Julien Louvel, Ad P. IJzerman Abstract The structure of the human A2A adenosine receptor has been elucidated by X-ray crystallography with a high affinity non-xanthine antagonist, ZM241385, bound to it. This template molecule served as a starting point for the incorporation of reactive moieties that cause the ligand to covalently bind to the receptor. In particular, we incorporated a fluorosulfonyl moiety onto ZM241385, which yielded LUF7445 (4-((3-((7-amino-2-(furan-2-yl)-[1, 2, 4]triazolo[1,5-a][1, 3, 5]triazin-5-yl)amino)propyl)carbamoyl)benzene sulfonyl fluoride). In a radioligand binding assay, LUF7445 acted as a potent antagonist, with an apparent affinity for the hA2A receptor in the nanomolar range. Its apparent affinity increased with longer incubation time, suggesting an increasing level of covalent binding over time. An in silico A2A-structure-based docking model was used to study the binding mode of LUF7445. This led us to perform site-directed mutagenesis of the A2A receptor to probe and validate the target lysine amino acid K153 for covalent binding. Meanwhile, a functional assay combined with wash-out experiments was set up to investigate the efficacy of covalent binding of LUF7445. All these experiments led us to conclude LUF7445 is a valuable molecular tool for further investigating covalent interactions at this receptor. It may also serve as a prototype for a therapeutic approach in which a covalent antagonist may be needed to counteract prolonged and persistent presence of the endogenous ligand adenosine. Show less
We expanded on a series of pyrido[2,1-f]purine-2,4-clione derivatives as human adenosine A(3) receptor (hA(3)R) antagonists to determine their kinetic profiles and affinities. Many compounds showed... Show moreWe expanded on a series of pyrido[2,1-f]purine-2,4-clione derivatives as human adenosine A(3) receptor (hA(3)R) antagonists to determine their kinetic profiles and affinities. Many compounds showed high affinities and a diverse range of kinetic profiles. We found hA(3)R antagonists with very short residence time (RT) at the receptor (2.2 min for 5) and much longer RTs (e.g., 376 min for 27 or 391 min for 31). Two representative antagonists (5 and 27) were tested in [S-35]GTP gamma S binding assays, and their RTs appeared correlated to their (in)surmountable antagonism. From a k(on)-k(off)-K-D kinetic map, we divided the antagonists into three subgroups, providing a possible direction for the further development of hA(3)R antagonists. Additionally, we performed a computational modeling study that sheds light on the crucial receptor interactions, dictating the compounds' binding kinetics. Knowledge of target binding kinetics appears useful for developing and triaging new hA(3)R antagonists in the early phase of drug discovery. Show less
We expanded on a series of pyrido[2,1-f]purine-2,4-clione derivatives as human adenosine A(3) receptor (hA(3)R) antagonists to determine their kinetic profiles and affinities. Many compounds showed... Show moreWe expanded on a series of pyrido[2,1-f]purine-2,4-clione derivatives as human adenosine A(3) receptor (hA(3)R) antagonists to determine their kinetic profiles and affinities. Many compounds showed high affinities and a diverse range of kinetic profiles. We found hA(3)R antagonists with very short residence time (RT) at the receptor (2.2 min for 5) and much longer RTs (e.g., 376 min for 27 or 391 min for 31). Two representative antagonists (5 and 27) were tested in [S-35]GTP gamma S binding assays, and their RTs appeared correlated to their (in)surmountable antagonism. From a k(on)-k(off)-K-D kinetic map, we divided the antagonists into three subgroups, providing a possible direction for the further development of hA(3)R antagonists. Additionally, we performed a computational modeling study that sheds light on the crucial receptor interactions, dictating the compounds' binding kinetics. Knowledge of target binding kinetics appears useful for developing and triaging new hA(3)R antagonists in the early phase of drug discovery. Show less
The structure of the human A(2A) adenosine receptor has been elucidated by X-ray crystallography with a high affinity non-xanthine antagonist, ZM241385, bound to it. This template molecule served... Show moreThe structure of the human A(2A) adenosine receptor has been elucidated by X-ray crystallography with a high affinity non-xanthine antagonist, ZM241385, bound to it. This template molecule served as a starting point for the incorporation of reactive moieties that cause the ligand to covalently bind to the receptor. In particular, we incorporated a fluorosulfonyl moiety onto ZM241385, which yielded LUF7445 (4-((3-((7-amino-2-(furan-2-yl)-[1, 2, 4]triazolo[1,5-a][1, 3, 5]triazin-5-yl)amino)propyl)carbamoyl)benzene sulfonyl fluoride). In a radioligand binding assay, LUF7445 acted as a potent antagonist, with an apparent affinity for the hA(2A) receptor in the nanomolar range. Its apparent affinity increased with longer incubation time, suggesting an increasing level of covalent binding over time. An in silico A(2A)-structure-based docking model was used to study the binding mode of LUF7445. This led us to perform site-directed mutagenesis of the A(2A) receptor to probe and validate the target lysine amino acid K153 for covalent binding. Meanwhile, a functional assay combined with wash-out experiments was set up to investigate the efficacy of covalent binding of LUF7445. All these experiments led us to conclude LUF7445 is a valuable molecular tool for further investigating covalent interactions at this receptor. It may also serve as a prototype for a therapeutic approach in which a covalent antagonist may be needed to counteract prolonged and persistent presence of the endogenous ligand adenosine. Show less
Lenselink, E.B.; Dijke, N. ten; Bongers, B.J.; Papadatos, G.; Vlijmen, H. van; Kowalczyk, W.J.; ... ; Westen, G.J.P. van 2017
The structure of the human A2A adenosine receptor has been elucidated by X-ray crystallography with a high affinity non-xanthine antagonist, ZM241385, bound to it. This template molecule served as... Show moreThe structure of the human A2A adenosine receptor has been elucidated by X-ray crystallography with a high affinity non-xanthine antagonist, ZM241385, bound to it. This template molecule served as a starting point for the incorporation of reactive moieties that cause the ligand to covalently bind to the receptor. In particular, we incorporated a fluorosulfonyl moiety onto ZM241385, which yielded LUF7445 (4-((3-((7-amino-2-(furan-2-yl)-[1, 2, 4]triazolo[1,5-a][1, 3, 5]triazin-5-yl)amino)propyl)carbamoyl)benzene sulfonyl fluoride). In a radioligand binding assay, LUF7445 acted as a potent antagonist, with an apparent affinity for the hA2A receptor in the nanomolar range. Its apparent affinity increased with longer incubation time, suggesting an increasing level of covalent binding over time. An in silico A2A-structure-based docking model was used to study the binding mode of LUF7445. This led us to perform site-directed mutagenesis of the A2A receptor to probe and validate the target lysine amino acid K153 for covalent binding. Meanwhile, a functional assay combined with wash-out experiments was set up to investigate the efficacy of covalent binding of LUF7445. All these experiments led us to conclude LUF7445 is a valuable molecular tool for further investigating covalent interactions at this receptor. It may also serve as a prototype for a therapeutic approach in which a covalent antagonist may be needed to counteract prolonged and persistent presence of the endogenous ligand adenosine.KEYWORDS: A2A adenosine receptor; Adenosine; Covalent antagonist; G protein-coupled receptors; Radioligand binding Show less
The adenosine receptor subfamily includes four subtypes: the A1, A2A, A2B and A3 receptors, which all belong to the superfamily of G protein-coupled receptors (GPCRs). The adenosine A2B receptor is... Show moreThe adenosine receptor subfamily includes four subtypes: the A1, A2A, A2B and A3 receptors, which all belong to the superfamily of G protein-coupled receptors (GPCRs). The adenosine A2B receptor is the least investigated of the adenosine receptors, and the molecular mechanisms of its activation have hardly been explored. We used a single-GPCR-one-G protein yeast screening method in combination with mutagenesis studies, molecular modeling and bio-informatics to investigate the importance of the different amino acid residues of the NPxxY(x)6F motif and helix 8 in the human adenosine A2B receptor (hA2BR) activation. A scanning mutagenesis protocol was employed, yielding 11 single mutations and one double mutation of the NPxxY(x)6F motif and 16 single mutations of helix 8. The amino acid residues P287(7.50), Y290(7.53), R293(7.56) and I304(8.57) were found to be essential, since mutation of these amino acid residues to alanine led to a complete loss of function. Western blot analysis showed that mutant receptor R293(7.56)A was not expressed, whereas the other proteins were. Amino acid residues that are also important in receptor activation are: N286(7.49), V289(7.52), Y292(7.55), N294(8.47), F297(8.50), R298(8.51), H302(8.55) and R307(8.60). The mutation Y290(7.53)F lost 50% of efficacy, while F297(8.50)A behaved similar to wild type receptor. The double mutation, Y290(7.53)F/F297(8.50)Y, lost around 70% of efficacy and displayed a lower potency for the reference agonist 5'-(N-ethylcarboxamido)adenosine (NECA). This study provides new insight into the molecular interplay and impact of TM7 and helix 8 for hA2B receptor activation, which may be extrapolated to other adenosine receptors and possibly to other GPCRs. Show less
Proteochemometric (PCM) modelling is a computational method to model the bioactivity of multiple ligands against multiple related protein targets simultaneously. Hence it has been found to be... Show moreProteochemometric (PCM) modelling is a computational method to model the bioactivity of multiple ligands against multiple related protein targets simultaneously. Hence it has been found to be particularly useful when exploring the selectivity and promiscuity of ligands on different proteins. In this review, we will firstly provide a brief introduction to the main concepts of PCM for readers new to the field. The next part focuses on recent technical advances, including the application of support vector machines (SVMs) using different kernel functions, random forests, Gaussian processes and collaborative filtering. The subsequent section will then describe some novel practical applications of PCM in the medicinal chemistry field, including studies on GPCRs, kinases, viral proteins (e.g.from HIV) and epigenetic targets such as histone deacetylases. Finally, we will conclude by summarizing novel developments in PCM, which we expect to gain further importance in the future. These developments include adding three-dimensional protein target information, application of PCM to the prediction of binding energies, and application of the concept in the fields of pharmacogenomics and toxicogenomics. This review is an update to a related publication in 2011 and it mainly focuses on developments in the field since then. Show less
Proteochemometrics (PCM) is an approach for bioactivity predictive modeling which models the relationship between protein and chemical information. Gaussian Processes (GP), based on Bayesian... Show moreProteochemometrics (PCM) is an approach for bioactivity predictive modeling which models the relationship between protein and chemical information. Gaussian Processes (GP), based on Bayesian inference, provide the most objective estimation of the uncertainty of the predictions, thus permitting the evaluation of the applicability domain (AD) of the model. Furthermore, the experimental error on bioactivity measurements can be used as input for this probabilistic model. In this study, we apply GP implemented with a panel of kernels on three various (and multispecies) PCM datasets. The first dataset consisted of information from 8 human and rat adenosine receptors with 10,999 small molecule ligands and their binding affinity. The second consisted of the catalytic activity of four dengue virus NS3 proteases on 56 small peptides. Finally, we have gathered bioactivity information of small molecule ligands on 91 aminergic GPCRs from 9 different species, leading to a dataset of 24,593 datapoints with a matrix completeness of only 2.43%. GP models trained on these datasets are statistically sound, at the same level of statistical significance as Support Vector Machines (SVM), with R20R20R20 values on the external dataset ranging from 0.68 to 0.92, and RMSEP values close to the experimental error. Furthermore, the best GP models obtained with the normalized polynomial and radial kernels provide intervals of confidence for the predictions in agreement with the cumulative Gaussian distribution. GP models were also interpreted on the basis of individual targets and of ligand descriptors. In the dengue dataset, the model interpretation in terms of the amino-acid positions in the tetra-peptide ligands gave biologically meaningful results. Show less
Kufareva, I.; Katritch, V.; Westen, G.J.P. van; Lenselink, E.B.; Overington, J.P.; Participants, of GPCR Dock 2013; Stevens, RC Abagyan R 2014
Despite tremendous successes of GPCR crystallography, the receptors with available structures represent only a small fraction of human GPCRs. An important role of the modeling community is to... Show moreDespite tremendous successes of GPCR crystallography, the receptors with available structures represent only a small fraction of human GPCRs. An important role of the modeling community is to maximize structural insights for the remaining receptors and complexes. The community-wide GPCR Dock assessment was established to stimulate and monitor the progress in molecular modeling and ligand docking for GPCRs. The four targets in the present third assessment round presented new and diverse challenges for modelers, including prediction of allosteric ligand interaction and activation states in 5-hydroxytryptamine receptors 1B and 2B, and modeling by extremely distant homology for smoothened receptor. Forty-four modeling groups participated in the assessment. State-of-the-art modeling approaches achieved close-to-experimental accuracy for small rigid orthosteric ligands and models built by close homology, and they correctly predicted protein fold for distant homology targets. Predictions of long loops and GPCR activation states remain unsolved problems. Show less
Proteochemometric (PCM) modelling is a computational method to model the bioactivity of multiple ligands against multiple related protein targets simultaneously. Hence it has been found to be... Show moreProteochemometric (PCM) modelling is a computational method to model the bioactivity of multiple ligands against multiple related protein targets simultaneously. Hence it has been found to be particularly useful when exploring the selectivity and promiscuity of ligands on different proteins. In this review, we will firstly provide a brief introduction to the main concepts of PCM for readers new to the field. The next part focuses on recent technical advances, including the application of support vector machines (SVMs) using different kernel functions, random forests, Gaussian processes and collaborative filtering. The subsequent section will then describe some novel practical applications of PCM in the medicinal chemistry field, including studies on GPCRs, kinases, viral proteins (e.g.from HIV) and epigenetic targets such as histone deacetylases. Finally, we will conclude by summarizing novel developments in PCM, which we expect to gain further importance in the future. These developments include adding three-dimensional protein target information, application of PCM to the prediction of binding energies, and application of the concept in the fields of pharmacogenomics and toxicogenomics. This review is an update to a related publication in 2011 and it mainly focuses on developments in the field since then. Show less
