A novel thiazolopyrimidinone series of PI3K-beta selective inhibitors has been identified. This c... more A novel thiazolopyrimidinone series of PI3K-beta selective inhibitors has been identified. This chemotype has provided an excellent tool compound, 18, that showed potent growth inhibition in the PTEN-deficient breast cancer cell line MDA-MB-468 under anchorage-independent conditions, and it also demonstrated pharmacodynamic effects and efficacy in a PTEN-deficient prostate cancer PC-3 xenograft mouse model.
It is difficult to properly validate algorithms that dock a small molecule ligand into its protei... more It is difficult to properly validate algorithms that dock a small molecule ligand into its protein receptor using data from the public domain: the predictions are not blind because the correct binding mode is already known, and public test cases may not be representative of compounds of interest such as drug leads. Here, we use private data from a real drug discovery program to carry out a blind evaluation of the RosettaLigand docking methodology and find that its performance is on average comparable with that of the best commercially available current small molecule docking programs. The strength of RosettaLigand is the use of the Rosetta sampling methodology to simultaneously optimize protein sidechain, protein backbone and ligand degrees of freedom; the extensive benchmark test described here identifies shortcomings in other aspects of the protocol and suggests clear routes to improving the method.
Synthesis and Reactivity in Inorganic Metal-organic and Nano-metal Chemistry, 2008
Interest in developing a nano‐oxidizer matrix for reaction with nano Al for energetic application... more Interest in developing a nano‐oxidizer matrix for reaction with nano Al for energetic applications led to the development of nanometric Fe2O3. We have reported a synthetic procedure for nano‐iron oxide using starch as the capping agent. Here, aqueous solution of ferric chloride was added into starch solution and after stirring it was basified by triethyl amine to get colloidal precipitate
Phosphoinositide 3-kinase α (PI3Kα) is a critical regulator of cell growth and transformation, an... more Phosphoinositide 3-kinase α (PI3Kα) is a critical regulator of cell growth and transformation, and its signaling pathway is the most commonly mutated pathway in human cancers. The mammalian target of rapamycin (mTOR), a class IV PI3K protein kinase, is also a central regulator of cell growth, and mTOR inhibitors are believed to augment the antiproliferative efficacy of PI3K/AKT pathway inhibition. 2,4-Difluoro-N-{2-(methyloxy)-5-[4-(4-pyridazinyl)-6-quinolinyl]-3-pyridinyl}benzenesulfonamide (GSK2126458, 1) has been identified as a highly potent, orally bioavailable inhibitor of PI3Kα and mTOR with in vivo activity in both pharmacodynamic and tumor growth efficacy models. Compound 1 is currently being evaluated in human clinical trials for the treatment of cancer.
A novel series of potent and selective hexokinase 2 (HK2) inhibitors, 2,6-disubstituted glucosami... more A novel series of potent and selective hexokinase 2 (HK2) inhibitors, 2,6-disubstituted glucosamines, has been identified based on HTS hits, exemplified by compound 1. Inhibitor-bound crystal structures revealed that the HK2 enzyme could adopt an "induced-fit" conformation. The SAR study led to the identification of potent HK2 inhibitors, such as compound 34 with greater than 100-fold selectivity over HK1. Compound 25 inhibits in situ glycolysis in a UM-UC-3 bladder tumor cell line via (13)CNMR measurement of [3-(13)C]lactate produced from [1,6-(13)C2]glucose added to the cell culture.
Current opinion in drug discovery & development, 2006
In principle, quantum mechanics provides a more accurate representation of molecular systems than... more In principle, quantum mechanics provides a more accurate representation of molecular systems than other modeling approaches. While this notion is not a matter of dispute, it has not yet been definitively demonstrated within the realm of structure-based drug design that the use of quantum mechanical methods over the use of classical modeling approaches is justified in consideration of the increase in expense associated with quantum mechanical methods. Demonstrating that quantum mechanics-based methods can be superior to simpler models, and resolving problems relating to estimating the effects of conformational entropy, will provide key areas of interest in the coming years for in silico structure-based drug design. Recent applications using quantum mechanical methods in structure-based drug design are reviewed herein, and applications ranging from scoring receptor-ligand interactions using quantum mechanics to the generation of quantitative structure-activity relationships using quan...
Computational methods to calculate binding affinity in protein-ligand interaction are of immense ... more Computational methods to calculate binding affinity in protein-ligand interaction are of immense interest because of obvious practical applications in structure-based drug design. Scoring functions attempt to calculate the variation in binding affinity of ligands-inhibitors bound to protein targets at various levels of theory. In this study we use semiempirical quantum mechanics to design a scoring function that can calculate the electrostatic interactions and solvation free energy expected during complexation. This physically based approach has the ability to capture binding affinity trends in a diverse range of protein-ligand complexes. We also show the predictive power of this scoring function within protein targets and its ability to score ligand poses docked to a protein target. We also demonstrate the ability of this scoring function to discriminate between native and decoy poses and highlight the crucial role played by electrostatic interactions in molecular recognition. Fina...
Journal of the American Chemical Society, Jan 4, 2004
In this communication, we report the development of a novel quantum mechanics-based scoring funct... more In this communication, we report the development of a novel quantum mechanics-based scoring function to predict free energy of ligand binding in the zinc metalloenzymes carbonic anhydrase (CA) and carboxypeptidase A (CPA). In particular, the AM1 method is used in conjunction with solvation modeling to predict the relative binding affinities of 18 CA and 5 CPA inhibitors. The effect of metal-ligand charge transfer is also discussed and shown to be different in CPA and CA, providing a further challenge to computing metalloenzyme binding affinities.
In the search of PI3K p110α wild type and H1047R mutant selective small molecule leads, an encode... more In the search of PI3K p110α wild type and H1047R mutant selective small molecule leads, an encoded library technology (ELT) campaign against the desired target proteins was performed which led to the discovery of a selective chemotype for PI3K isoforms from a three-cycle DNA encoded library. An X-ray crystal structure of a representative inhibitor from this chemotype demonstrated a unique binding mode in the p110α protein.
Bioorganic & medicinal chemistry letters, Jan 15, 2012
A series of PI3K-beta selective inhibitors, imidazo[1,2-a]-pyrimidin-5(1H)-ones, has been rationa... more A series of PI3K-beta selective inhibitors, imidazo[1,2-a]-pyrimidin-5(1H)-ones, has been rationally designed based on the docking model of the more potent R enantiomer of TGX-221, identified by a chiral separation, in a PI3K-beta homology model. Synthesis and SAR of this novel chemotype are described. Several compounds in the series demonstrated potent growth inhibition in a PTEN-deficient breast cancer cell line MDA-MB-468 under anchorage independent conditions.
We have developed a method for the prediction of an amino acid sequence that is compatible with a... more We have developed a method for the prediction of an amino acid sequence that is compatible with a three-dimensional backbone structure. Using only a backbone structure of a protein as input, the algorithm is capable of designing sequences that closely resemble natural members of the protein family to which the template structure belongs. In general, the predicted sequences are shown to have multiple sequence profile scores that are dramatically higher than those of random sequences, and sometimes better than some of the natural sequences that make up the superfamily. As anticipated, highly conserved but poorly predicted residues are often those that contribute to the functional rather than structural properties of the protein. Overall, our analysis suggests that statistical profile scores of designed sequences are a novel and valuable figure of merit for assessing and improving protein design algorithms.
Pairwise decomposition of the interaction energy between molecules is shown to be a powerful tool... more Pairwise decomposition of the interaction energy between molecules is shown to be a powerful tool that can increase our understanding of macromolecular recognition processes. Herein we calculate the pairwise decomposition of the interaction energy between the protein human carbonic anhydrase II (HCAII) and the fluorine-substituted ligand N-(4-sulfamylbenzoyl)benzylamine (SBB) using semiempirical quantum mechanics based methods. We dissect the interaction between the ligand and the protein by dividing the ligand and the protein into subsystems to understand the structure-activity relationships as a result of fluorine substitution. In particular, the off-diagonal elements of the Fock matrix that is composed of the interaction between the ionic core and the valence electrons and the exchange energy between the subsystems or atoms of interest is examined in detail. Our analysis reveals that the fluorine-substituted benzylamine group of SBB does not directly affect the binding energy. Rather, we find that the strength of the interaction between Thr199 of HCAII and the sulfamylbenzoyl group of SBB affects the binding affinity between the protein and the ligand. These observations underline the importance of the sulfonamide group in binding affinity as shown by previous experiments (Maren, T. H.; Wiley: C. E. J. Med. Chem. 1968, 11, 228-232). Moreover, our calculations qualitatively agree with the structural aspects of these proteinligand complexes as determined by X-ray crystallography.
In this communication, we report the development of a novel quantum mechanics-based scoring funct... more In this communication, we report the development of a novel quantum mechanics-based scoring function to predict free energy of ligand binding in the zinc metalloenzymes carbonic anhydrase (CA) and carboxypeptidase A (CPA). In particular, the AM1 method is used in conjunction with solvation modeling to predict the relative binding affinities of 18 CA and 5 CPA inhibitors. The effect of metal-ligand charge transfer is also discussed and shown to be different in CPA and CA, providing a further challenge to computing metalloenzyme binding affinities.
Recently, we have developed a fast approach to calculate NMR chemical shifts using the divide and... more Recently, we have developed a fast approach to calculate NMR chemical shifts using the divide and conquer method at the semiempirical level. To demonstrate the utility of this approach for characterizing protein-ligand interactions, we used the deviation of calculated chemical shift perturbations from experiment to determine the orientation of a ligand (GPI-1046) in the binding pocket of the FK506 binding protein (FKBP12). Moreover, we were able to select the native state of the ligand from a collection of decoy poses. A key hydrogen bond between O1 and HN in Ile56 was also identified. Our results suggest that ligand-induced chemical shift perturbations can be used to refine protein/ligand structures.
Computational methods to calculate binding affinity in protein-ligand interaction are of immense ... more Computational methods to calculate binding affinity in protein-ligand interaction are of immense interest because of obvious practical applications in structure-based drug design. Scoring functions attempt to calculate the variation in binding affinity of ligands-inhibitors bound to protein targets at various levels of theory. In this study we use semiempirical quantum mechanics to design a scoring function that can calculate the electrostatic interactions and solvation free energy expected during complexation. This physically based approach has the ability to capture binding affinity trends in a diverse range of protein-ligand complexes. We also show the predictive power of this scoring function within protein targets and its ability to score ligand poses docked to a protein target. We also demonstrate the ability of this scoring function to discriminate between native and decoy poses and highlight the crucial role played by electrostatic interactions in molecular recognition. Finally we compare the performance of our scoring function with other available scoring functions in the literature.
Herein we will focus on the use of quantum mechanics (QM) in drug design (DD) to solve disparate ... more Herein we will focus on the use of quantum mechanics (QM) in drug design (DD) to solve disparate problems from scoring protein-ligand poses to building QM QSAR models. Through the variational principle of QM we know that we can obtain a more accurate representation of molecular systems than classical models, and while this is not a matter of debate, it still has not been shown that the expense of QM approaches is offset by improved accuracy in DD applications. Objectively validating the improved applicability and performance of QM over classical-based models in DD will be the focus of research in the coming years along with research on the conformational sampling problem as it relates to proteinligand complexes.
A novel thiazolopyrimidinone series of PI3K-beta selective inhibitors has been identified. This c... more A novel thiazolopyrimidinone series of PI3K-beta selective inhibitors has been identified. This chemotype has provided an excellent tool compound, 18, that showed potent growth inhibition in the PTEN-deficient breast cancer cell line MDA-MB-468 under anchorage-independent conditions, and it also demonstrated pharmacodynamic effects and efficacy in a PTEN-deficient prostate cancer PC-3 xenograft mouse model.
It is difficult to properly validate algorithms that dock a small molecule ligand into its protei... more It is difficult to properly validate algorithms that dock a small molecule ligand into its protein receptor using data from the public domain: the predictions are not blind because the correct binding mode is already known, and public test cases may not be representative of compounds of interest such as drug leads. Here, we use private data from a real drug discovery program to carry out a blind evaluation of the RosettaLigand docking methodology and find that its performance is on average comparable with that of the best commercially available current small molecule docking programs. The strength of RosettaLigand is the use of the Rosetta sampling methodology to simultaneously optimize protein sidechain, protein backbone and ligand degrees of freedom; the extensive benchmark test described here identifies shortcomings in other aspects of the protocol and suggests clear routes to improving the method.
Synthesis and Reactivity in Inorganic Metal-organic and Nano-metal Chemistry, 2008
Interest in developing a nano‐oxidizer matrix for reaction with nano Al for energetic application... more Interest in developing a nano‐oxidizer matrix for reaction with nano Al for energetic applications led to the development of nanometric Fe2O3. We have reported a synthetic procedure for nano‐iron oxide using starch as the capping agent. Here, aqueous solution of ferric chloride was added into starch solution and after stirring it was basified by triethyl amine to get colloidal precipitate
Phosphoinositide 3-kinase α (PI3Kα) is a critical regulator of cell growth and transformation, an... more Phosphoinositide 3-kinase α (PI3Kα) is a critical regulator of cell growth and transformation, and its signaling pathway is the most commonly mutated pathway in human cancers. The mammalian target of rapamycin (mTOR), a class IV PI3K protein kinase, is also a central regulator of cell growth, and mTOR inhibitors are believed to augment the antiproliferative efficacy of PI3K/AKT pathway inhibition. 2,4-Difluoro-N-{2-(methyloxy)-5-[4-(4-pyridazinyl)-6-quinolinyl]-3-pyridinyl}benzenesulfonamide (GSK2126458, 1) has been identified as a highly potent, orally bioavailable inhibitor of PI3Kα and mTOR with in vivo activity in both pharmacodynamic and tumor growth efficacy models. Compound 1 is currently being evaluated in human clinical trials for the treatment of cancer.
A novel series of potent and selective hexokinase 2 (HK2) inhibitors, 2,6-disubstituted glucosami... more A novel series of potent and selective hexokinase 2 (HK2) inhibitors, 2,6-disubstituted glucosamines, has been identified based on HTS hits, exemplified by compound 1. Inhibitor-bound crystal structures revealed that the HK2 enzyme could adopt an "induced-fit" conformation. The SAR study led to the identification of potent HK2 inhibitors, such as compound 34 with greater than 100-fold selectivity over HK1. Compound 25 inhibits in situ glycolysis in a UM-UC-3 bladder tumor cell line via (13)CNMR measurement of [3-(13)C]lactate produced from [1,6-(13)C2]glucose added to the cell culture.
Current opinion in drug discovery & development, 2006
In principle, quantum mechanics provides a more accurate representation of molecular systems than... more In principle, quantum mechanics provides a more accurate representation of molecular systems than other modeling approaches. While this notion is not a matter of dispute, it has not yet been definitively demonstrated within the realm of structure-based drug design that the use of quantum mechanical methods over the use of classical modeling approaches is justified in consideration of the increase in expense associated with quantum mechanical methods. Demonstrating that quantum mechanics-based methods can be superior to simpler models, and resolving problems relating to estimating the effects of conformational entropy, will provide key areas of interest in the coming years for in silico structure-based drug design. Recent applications using quantum mechanical methods in structure-based drug design are reviewed herein, and applications ranging from scoring receptor-ligand interactions using quantum mechanics to the generation of quantitative structure-activity relationships using quan...
Computational methods to calculate binding affinity in protein-ligand interaction are of immense ... more Computational methods to calculate binding affinity in protein-ligand interaction are of immense interest because of obvious practical applications in structure-based drug design. Scoring functions attempt to calculate the variation in binding affinity of ligands-inhibitors bound to protein targets at various levels of theory. In this study we use semiempirical quantum mechanics to design a scoring function that can calculate the electrostatic interactions and solvation free energy expected during complexation. This physically based approach has the ability to capture binding affinity trends in a diverse range of protein-ligand complexes. We also show the predictive power of this scoring function within protein targets and its ability to score ligand poses docked to a protein target. We also demonstrate the ability of this scoring function to discriminate between native and decoy poses and highlight the crucial role played by electrostatic interactions in molecular recognition. Fina...
Journal of the American Chemical Society, Jan 4, 2004
In this communication, we report the development of a novel quantum mechanics-based scoring funct... more In this communication, we report the development of a novel quantum mechanics-based scoring function to predict free energy of ligand binding in the zinc metalloenzymes carbonic anhydrase (CA) and carboxypeptidase A (CPA). In particular, the AM1 method is used in conjunction with solvation modeling to predict the relative binding affinities of 18 CA and 5 CPA inhibitors. The effect of metal-ligand charge transfer is also discussed and shown to be different in CPA and CA, providing a further challenge to computing metalloenzyme binding affinities.
In the search of PI3K p110α wild type and H1047R mutant selective small molecule leads, an encode... more In the search of PI3K p110α wild type and H1047R mutant selective small molecule leads, an encoded library technology (ELT) campaign against the desired target proteins was performed which led to the discovery of a selective chemotype for PI3K isoforms from a three-cycle DNA encoded library. An X-ray crystal structure of a representative inhibitor from this chemotype demonstrated a unique binding mode in the p110α protein.
Bioorganic & medicinal chemistry letters, Jan 15, 2012
A series of PI3K-beta selective inhibitors, imidazo[1,2-a]-pyrimidin-5(1H)-ones, has been rationa... more A series of PI3K-beta selective inhibitors, imidazo[1,2-a]-pyrimidin-5(1H)-ones, has been rationally designed based on the docking model of the more potent R enantiomer of TGX-221, identified by a chiral separation, in a PI3K-beta homology model. Synthesis and SAR of this novel chemotype are described. Several compounds in the series demonstrated potent growth inhibition in a PTEN-deficient breast cancer cell line MDA-MB-468 under anchorage independent conditions.
We have developed a method for the prediction of an amino acid sequence that is compatible with a... more We have developed a method for the prediction of an amino acid sequence that is compatible with a three-dimensional backbone structure. Using only a backbone structure of a protein as input, the algorithm is capable of designing sequences that closely resemble natural members of the protein family to which the template structure belongs. In general, the predicted sequences are shown to have multiple sequence profile scores that are dramatically higher than those of random sequences, and sometimes better than some of the natural sequences that make up the superfamily. As anticipated, highly conserved but poorly predicted residues are often those that contribute to the functional rather than structural properties of the protein. Overall, our analysis suggests that statistical profile scores of designed sequences are a novel and valuable figure of merit for assessing and improving protein design algorithms.
Pairwise decomposition of the interaction energy between molecules is shown to be a powerful tool... more Pairwise decomposition of the interaction energy between molecules is shown to be a powerful tool that can increase our understanding of macromolecular recognition processes. Herein we calculate the pairwise decomposition of the interaction energy between the protein human carbonic anhydrase II (HCAII) and the fluorine-substituted ligand N-(4-sulfamylbenzoyl)benzylamine (SBB) using semiempirical quantum mechanics based methods. We dissect the interaction between the ligand and the protein by dividing the ligand and the protein into subsystems to understand the structure-activity relationships as a result of fluorine substitution. In particular, the off-diagonal elements of the Fock matrix that is composed of the interaction between the ionic core and the valence electrons and the exchange energy between the subsystems or atoms of interest is examined in detail. Our analysis reveals that the fluorine-substituted benzylamine group of SBB does not directly affect the binding energy. Rather, we find that the strength of the interaction between Thr199 of HCAII and the sulfamylbenzoyl group of SBB affects the binding affinity between the protein and the ligand. These observations underline the importance of the sulfonamide group in binding affinity as shown by previous experiments (Maren, T. H.; Wiley: C. E. J. Med. Chem. 1968, 11, 228-232). Moreover, our calculations qualitatively agree with the structural aspects of these proteinligand complexes as determined by X-ray crystallography.
In this communication, we report the development of a novel quantum mechanics-based scoring funct... more In this communication, we report the development of a novel quantum mechanics-based scoring function to predict free energy of ligand binding in the zinc metalloenzymes carbonic anhydrase (CA) and carboxypeptidase A (CPA). In particular, the AM1 method is used in conjunction with solvation modeling to predict the relative binding affinities of 18 CA and 5 CPA inhibitors. The effect of metal-ligand charge transfer is also discussed and shown to be different in CPA and CA, providing a further challenge to computing metalloenzyme binding affinities.
Recently, we have developed a fast approach to calculate NMR chemical shifts using the divide and... more Recently, we have developed a fast approach to calculate NMR chemical shifts using the divide and conquer method at the semiempirical level. To demonstrate the utility of this approach for characterizing protein-ligand interactions, we used the deviation of calculated chemical shift perturbations from experiment to determine the orientation of a ligand (GPI-1046) in the binding pocket of the FK506 binding protein (FKBP12). Moreover, we were able to select the native state of the ligand from a collection of decoy poses. A key hydrogen bond between O1 and HN in Ile56 was also identified. Our results suggest that ligand-induced chemical shift perturbations can be used to refine protein/ligand structures.
Computational methods to calculate binding affinity in protein-ligand interaction are of immense ... more Computational methods to calculate binding affinity in protein-ligand interaction are of immense interest because of obvious practical applications in structure-based drug design. Scoring functions attempt to calculate the variation in binding affinity of ligands-inhibitors bound to protein targets at various levels of theory. In this study we use semiempirical quantum mechanics to design a scoring function that can calculate the electrostatic interactions and solvation free energy expected during complexation. This physically based approach has the ability to capture binding affinity trends in a diverse range of protein-ligand complexes. We also show the predictive power of this scoring function within protein targets and its ability to score ligand poses docked to a protein target. We also demonstrate the ability of this scoring function to discriminate between native and decoy poses and highlight the crucial role played by electrostatic interactions in molecular recognition. Finally we compare the performance of our scoring function with other available scoring functions in the literature.
Herein we will focus on the use of quantum mechanics (QM) in drug design (DD) to solve disparate ... more Herein we will focus on the use of quantum mechanics (QM) in drug design (DD) to solve disparate problems from scoring protein-ligand poses to building QM QSAR models. Through the variational principle of QM we know that we can obtain a more accurate representation of molecular systems than classical models, and while this is not a matter of debate, it still has not been shown that the expense of QM approaches is offset by improved accuracy in DD applications. Objectively validating the improved applicability and performance of QM over classical-based models in DD will be the focus of research in the coming years along with research on the conformational sampling problem as it relates to proteinligand complexes.
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Papers by Kaushik Raha