1
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Galantamine Based Novel Acetylcholinesterase Enzyme Inhibitors: A Molecular Modeling Design Approach. Molecules 2023; 28:molecules28031035. [PMID: 36770702 PMCID: PMC9919016 DOI: 10.3390/molecules28031035] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 12/31/2022] [Accepted: 01/09/2023] [Indexed: 01/22/2023] Open
Abstract
Acetylcholinesterase (AChE) enzymes play an essential role in the development of Alzheimer's disease (AD). Its excessive activity causes several neuronal problems, particularly psychopathies and neuronal cell death. A bioactive pose on the hAChE B site of the human acetylcholinesterase (hAChE) enzyme employed in this investigation, which was obtained from the Protein Data Bank (PDB ID 4EY6), allowed for the prediction of the binding affinity and free binding energy between the protein and the ligand. Virtual screening was performed to obtain structures similar to Galantamine (GNT) with potential hAChE activity. The top 200 hit compounds were prioritized through the use of filters in ZincPharmer, with special features related to the pharmacophore. Critical analyses were carried out, such as hierarchical clustering analysis (HCA), ADME/Tox predictions, molecular docking, molecular simulation studies, synthetic accessibility (SA), lipophilicity, water solubility, and hot spots to confirm the stable binding of the two promising molecules (ZINC16951574-LMQC2, and ZINC08342556-LMQC5). The metabolism prediction, with metabolites M3-2, which is formed by Glutathionation reaction (Phase II), M1-2, and M2-2 formed from the reaction of S-oxidation and Aliphatic hydroxylation (Phase I), were both reactive but with no side effects. Theoretical synthetic routes and prediction of synthetic accessibility for the most promising compounds are also proposed. In conclusion, this study shows that in silico modeling can be used to create new drug candidate inhibitors for hAChE. The compounds ZINC16951574-LMQC2, and ZINC08342556-LMQC5 are particularly promising for oral administration because they have a favorable drug-likeness profile, excellent lipid solubility, high bioavailability, and adequate pharmacokinetics.
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2
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Kumar P, Mohanty D. Development of a Novel Pharmacophore Model Guided by the Ensemble of Waters and Small Molecule Fragments Bound to SARS-CoV-2 Main Protease. Mol Inform 2021; 41:e2100178. [PMID: 34633768 PMCID: PMC8646684 DOI: 10.1002/minf.202100178] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 09/20/2021] [Indexed: 11/17/2022]
Abstract
Recent fragment‐based drug design efforts have generated huge amounts of information on water and small molecule fragment binding sites on SARS‐CoV‐2 Mpro and preference of the sites for various types of chemical moieties. However, this information has not been effectively utilized to develop automated tools for in silico drug discovery which are routinely used for screening large compound libraries. Utilization of this information in the development of pharmacophore models can help in bridging this gap. In this study, information on water and small molecule fragments bound to Mpro has been utilized to develop a novel Water Pharmacophore (Waterphore) model. The Waterphore model can also implicitly represent the conformational flexibilities of binding pockets in terms of pharmacophore features. The Waterphore model derived from 173 apo‐ or small molecule fragment‐bound structures of Mpro has been validated by using a dataset of 68 known bioactive inhibitors and 78 crystal structure bound inhibitors of SARS‐CoV‐2 Mpro. It is encouraging to note that, even though no inhibitor data has been used in developing the Waterphore model, it could successfully identify the known inhibitors from a library of decoys with a ROC‐AUC of 0.81 and active hit rate (AHR) of 70 %. The Waterphore model is also general enough for potential applications for other drug targets.
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Affiliation(s)
- Pawan Kumar
- National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi, 110067, India
| | - Debasisa Mohanty
- National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi, 110067, India
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3
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Egbert M, Ghani U, Ashizawa R, Kotelnikov S, Nguyen T, Desta I, Hashemi N, Padhorny D, Kozakov D, Vajda S. Assessing the binding properties of CASP14 targets and models. Proteins 2021; 89:1922-1939. [PMID: 34368994 DOI: 10.1002/prot.26209] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 07/22/2021] [Accepted: 08/04/2021] [Indexed: 12/27/2022]
Abstract
An important question is how well the models submitted to CASP retain the properties of target structures. We investigate several properties related to binding. First we explore the binding of small molecules as probes, and count the number of interactions between each residue and such probes, resulting in a binding fingerprint. The similarity between two fingerprints, one for the X-ray structure and the other for a model, is determined by calculating their correlation coefficient. The fingerprint similarity weakly correlates with global measures of accuracy, and GDT_TS higher than 80 is a necessary but not sufficient condition for the conservation of surface binding properties. The advantage of this approach is that it can be carried out without information on potential ligands and their binding sites. The latter information was available for a few targets, and we explored whether the CASP14 models can be used to predict binding sites and to dock small ligands. Finally, we tested the ability of models to reproduce protein-protein interactions by docking both the X-ray structures and the models to their interaction partners in complexes. The analysis showed that in CASP14 the quality of individual domain models is approaching that offered by X-ray crystallography, and hence such models can be successfully used for the identification of binding and regulatory sites, as well as for assembling obligatory protein-protein complexes. Success of ligand docking, however, often depends on fine details of the binding interface, and thus may require accounting for conformational changes by simulation methods.
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Affiliation(s)
- Megan Egbert
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - Usman Ghani
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - Ryota Ashizawa
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA.,Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, USA
| | - Sergei Kotelnikov
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA.,Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, USA
| | - Thu Nguyen
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, USA
| | - Israel Desta
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - Nasser Hashemi
- Division of Systems Engineering, Boston University, Boston, Massachusetts, USA
| | - Dzmitry Padhorny
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA
| | - Dima Kozakov
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA.,Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, USA
| | - Sandor Vajda
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA.,Department of Chemistry, Boston University, Boston, Massachusetts, USA
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4
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Development of a fast screening method for selecting excipients in formulations using MD simulations, NMR and microscale thermophoresis. Eur J Pharm Biopharm 2021; 158:11-20. [DOI: 10.1016/j.ejpb.2020.10.015] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 10/22/2020] [Accepted: 10/24/2020] [Indexed: 12/31/2022]
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5
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6
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Abstract
Molecular dynamics (MD) simulations of proteins reveal the existence of many transient surface pockets; however, the factors determining what small subset of these represent druggable or functionally relevant ligand binding sites, called "cryptic sites," are not understood. Here, we examine multiple X-ray structures for a set of proteins with validated cryptic sites, using the computational hot spot identification tool FTMap. The results show that cryptic sites in ligand-free structures generally have a strong binding energy hot spot very close by. As expected, regions around cryptic sites exhibit above-average flexibility, and close to 50% of the proteins studied here have unbound structures that could accommodate the ligand without clashes. Nevertheless, the strong hot spot neighboring each cryptic site is almost always exploited by the bound ligand, suggesting that binding may frequently involve an induced fit component. We additionally evaluated the structural basis for cryptic site formation, by comparing unbound to bound structures. Cryptic sites are most frequently occluded in the unbound structure by intrusion of loops (22.5%), side chains (19.4%), or in some cases entire helices (5.4%), but motions that create sites that are too open can also eliminate pockets (19.4%). The flexibility of cryptic sites frequently leads to missing side chains or loops (12%) that are particularly evident in low resolution crystal structures. An interesting observation is that cryptic sites formed solely by the movement of side chains, or of backbone segments with fewer than five residues, result only in low affinity binding sites with limited use for drug discovery.
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7
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Kulp JL, Cloudsdale IS, Kulp JL, Guarnieri F. Hot-spot identification on a broad class of proteins and RNA suggest unifying principles of molecular recognition. PLoS One 2017; 12:e0183327. [PMID: 28837642 PMCID: PMC5570288 DOI: 10.1371/journal.pone.0183327] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Accepted: 08/02/2017] [Indexed: 01/03/2023] Open
Abstract
Chemically diverse fragments tend to collectively bind at localized sites on proteins, which is a cornerstone of fragment-based techniques. A central question is how general are these strategies for predicting a wide variety of molecular interactions such as small molecule-protein, protein-protein and protein-nucleic acid for both experimental and computational methods. To address this issue, we recently proposed three governing principles, (1) accurate prediction of fragment-macromolecule binding free energy, (2) accurate prediction of water-macromolecule binding free energy, and (3) locating sites on a macromolecule that have high affinity for a diversity of fragments and low affinity for water. To test the generality of these concepts we used the computational technique of Simulated Annealing of Chemical Potential to design one small fragment to break the RecA-RecA protein-protein interaction and three fragments that inhibit peptide-deformylase via water-mediated multi-body interactions. Experiments confirm the predictions that 6-hydroxydopamine potently inhibits RecA and that PDF inhibition quantitatively tracks the water-mediated binding predictions. Additionally, the principles correctly predict the essential bound waters in HIV Protease, the surprisingly extensive binding site of elastase, the pinpoint location of electron transfer in dihydrofolate reductase, the HIV TAT-TAR protein-RNA interactions, and the MDM2-MDM4 differential binding to p53. The experimental confirmations of highly non-obvious predictions combined with the precise characterization of a broad range of known phenomena lend strong support to the generality of fragment-based methods for characterizing molecular recognition.
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Affiliation(s)
- John L. Kulp
- Conifer Point Pharmaceuticals, Doylestown, Pennsylvania, United States of America
- Department of Chemistry, Baruch S. Blumberg Institute, Doylestown, Pennsylvania, United States of America
| | - Ian S. Cloudsdale
- Conifer Point Pharmaceuticals, Doylestown, Pennsylvania, United States of America
| | - John L. Kulp
- Conifer Point Pharmaceuticals, Doylestown, Pennsylvania, United States of America
| | - Frank Guarnieri
- PAKA Pulmonary Pharmaceuticals, Acton, Massachusetts, United States of America
- * E-mail:
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8
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Ghanakota P, Carlson HA. Driving Structure-Based Drug Discovery through Cosolvent Molecular Dynamics. J Med Chem 2016; 59:10383-10399. [PMID: 27486927 DOI: 10.1021/acs.jmedchem.6b00399] [Citation(s) in RCA: 65] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Identifying binding hotspots on protein surfaces is of prime interest in structure-based drug discovery, either to assess the tractability of pursuing a protein target or to drive improved potency of lead compounds. Computational approaches to detect such regions have traditionally relied on energy minimization of probe molecules onto static protein conformations in the absence of the natural aqueous environment. Advances in high performance computing now allow us to assess hotspots using molecular dynamics (MD) simulations. MD simulations integrate protein flexibility and the complicated role of water, thereby providing a more realistic assessment of the complex kinetics and thermodynamics at play. In this review, we describe the evolution of various cosolvent-based MD techniques and highlight a myriad of potential applications for such technologies in computational drug development.
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Affiliation(s)
- Phani Ghanakota
- Department of Medicinal Chemistry, College of Pharmacy, University of Michigan , 428 Church Street, Ann Arbor, Michigan 48109-1065, United States
| | - Heather A Carlson
- Department of Medicinal Chemistry, College of Pharmacy, University of Michigan , 428 Church Street, Ann Arbor, Michigan 48109-1065, United States
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9
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Mamonov AB, Moghadasi M, Mirzaei H, Zarbafian S, Grove LE, Bohnuud T, Vakili P, Paschalidis IC, Vajda S, Kozakov D. Focused grid-based resampling for protein docking and mapping. J Comput Chem 2016; 37:961-70. [PMID: 26837000 PMCID: PMC4814242 DOI: 10.1002/jcc.24273] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2015] [Revised: 08/31/2015] [Accepted: 09/26/2015] [Indexed: 12/27/2022]
Abstract
The fast Fourier transform (FFT) sampling algorithm has been used with success in application to protein-protein docking and for protein mapping, the latter docking a variety of small organic molecules for the identification of binding hot spots on the target protein. Here we explore the local rather than global usage of the FFT sampling approach in docking applications. If the global FFT based search yields a near-native cluster of docked structures for a protein complex, then focused resampling of the cluster generally leads to a substantial increase in the number of conformations close to the native structure. In protein mapping, focused resampling of the selected hot spot regions generally reveals further hot spots that, while not as strong as the primary hot spots, also contribute to ligand binding. The detection of additional ligand binding regions is shown by the improved overlap between hot spots and bound ligands.
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Affiliation(s)
- Artem B. Mamonov
- Department of Biomedical Engineering, Boston University, Boston MA 02215
| | - Mohammad Moghadasi
- Center for Information and Systems Engineering, Boston University, Boston, MA 02215
| | - Hanieh Mirzaei
- Center for Information and Systems Engineering, Boston University, Boston, MA 02215
| | - Shahrooz Zarbafian
- Department of Mechanical Engineering, Boston University, Boston MA 02215
| | - Laurie E. Grove
- Department of Sciences, Wentworth Institute of Technology, Boston, MA 02115, USA
| | - Tanggis Bohnuud
- Department of Biomedical Engineering, Boston University, Boston MA 02215
| | - Pirooz Vakili
- Center for Information and Systems Engineering, Boston University, Boston, MA 02215
- Department of Mechanical Engineering, Boston University, Boston MA 02215
| | - Ioannis Ch. Paschalidis
- Center for Information and Systems Engineering, Boston University, Boston, MA 02215
- Department of Electrical and Computer Engineering, Boston University, Boston MA 02215
| | - Sandor Vajda
- Department of Biomedical Engineering, Boston University, Boston MA 02215
- Center for Information and Systems Engineering, Boston University, Boston, MA 02215
- Department of Chemistry, Boston University, Boston MA 02215
| | - Dima Kozakov
- Department of Biomedical Engineering, Boston University, Boston MA 02215
- Departemnt of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, 11790
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10
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Radoux CJ, Olsson TSG, Pitt WR, Groom CR, Blundell TL. Identifying Interactions that Determine Fragment Binding at Protein Hotspots. J Med Chem 2016; 59:4314-25. [PMID: 27043011 DOI: 10.1021/acs.jmedchem.5b01980] [Citation(s) in RCA: 73] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Locating a ligand-binding site is an important first step in structure-guided drug discovery, but current methods do little to suggest which interactions within a pocket are the most important for binding. Here we illustrate a method that samples atomic hotspots with simple molecular probes to produce fragment hotspot maps. These maps specifically highlight fragment-binding sites and their corresponding pharmacophores. For ligand-bound structures, they provide an intuitive visual guide within the binding site, directing medicinal chemists where to grow the molecule and alerting them to suboptimal interactions within the original hit. The fragment hotspot map calculation is validated using experimental binding positions of 21 fragments and subsequent lead molecules. The ligands are found in high scoring areas of the fragment hotspot maps, with fragment atoms having a median percentage rank of 97%. Protein kinase B and pantothenate synthetase are examined in detail. In each case, the fragment hotspot maps are able to rationalize a Free-Wilson analysis of SAR data from a fragment-based drug design project.
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Affiliation(s)
- Chris J Radoux
- Cambridge Crystallographic Data Centre , 12 Union Road, Cambridge, CB2 1EZ, United Kingdom.,Department of Biochemistry, University of Cambridge , Sanger Building, 80 Tennis Court Road, Cambridge CB2 1GA, United Kingdom
| | - Tjelvar S G Olsson
- Cambridge Crystallographic Data Centre , 12 Union Road, Cambridge, CB2 1EZ, United Kingdom.,John Innes Centre, Norwich Research Park , Colney Lane, Norwich, Norfolk NR4 7UH, United Kingdom
| | - Will R Pitt
- UCB , 208 Bath Road, Slough, West Berkshire SL1 3WE, United Kingdom
| | - Colin R Groom
- Cambridge Crystallographic Data Centre , 12 Union Road, Cambridge, CB2 1EZ, United Kingdom
| | - Tom L Blundell
- Department of Biochemistry, University of Cambridge , Sanger Building, 80 Tennis Court Road, Cambridge CB2 1GA, United Kingdom
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11
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Abstract
Over the past two decades, solvent mapping has emerged as a useful tool for identifying hot spots within binding sites on proteins for drug-like molecules and suggesting properties of potential binders. While the experimental technique requires solving multiple crystal structures of a protein in different solvents, computational solvent mapping allows for fast analysis of a protein for potential binding sites and their druggability. Recent advances in genomics, systems biology and interactomics provide a multitude of potential targets for drug development and solvent mapping can provide useful information to help prioritize targets for drug discovery projects. Here, we review various approaches to computational solvent mapping, highlight some key advances and provide our opinion on future directions in the field.
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12
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Abstract
A powerful early approach to evaluating the druggability of proteins involved determining the hit rate in NMR-based screening of a library of small compounds. Here, we show that a computational analog of this method, based on mapping proteins using small molecules as probes, can reliably reproduce druggability results from NMR-based screening and can provide a more meaningful assessment in cases where the two approaches disagree. We apply the method to a large set of proteins. The results show that, because the method is based on the biophysics of binding rather than on empirical parametrization, meaningful information can be gained about classes of proteins and classes of compounds beyond those resembling validated targets and conventionally druglike ligands. In particular, the method identifies targets that, while not druggable by druglike compounds, may become druggable using compound classes such as macrocycles or other large molecules beyond the rule-of-five limit.
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Affiliation(s)
- Dima Kozakov
- Department of Applied Mathematics & Statistics, Stony Brook University , Stony Brook, New York 11794, United States
| | - David R Hall
- Acpharis Inc. , Holliston, Massachusetts 01746, United States
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13
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Ligand deconstruction: Why some fragment binding positions are conserved and others are not. Proc Natl Acad Sci U S A 2015; 112:E2585-94. [PMID: 25918377 DOI: 10.1073/pnas.1501567112] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Fragment-based drug discovery (FBDD) relies on the premise that the fragment binding mode will be conserved on subsequent expansion to a larger ligand. However, no general condition has been established to explain when fragment binding modes will be conserved. We show that a remarkably simple condition can be developed in terms of how fragments coincide with binding energy hot spots--regions of the protein where interactions with a ligand contribute substantial binding free energy--the locations of which can easily be determined computationally. Because a substantial fraction of the free energy of ligand binding comes from interacting with the residues in the energetically most important hot spot, a ligand moiety that sufficiently overlaps with this region will retain its location even when other parts of the ligand are removed. This hypothesis is supported by eight case studies. The condition helps identify whether a protein is suitable for FBDD, predicts the size of fragments required for screening, and determines whether a fragment hit can be extended into a higher affinity ligand. Our results show that ligand binding sites can usefully be thought of in terms of an anchor site, which is the top-ranked hot spot and dominates the free energy of binding, surrounded by a number of weaker satellite sites that confer improved affinity and selectivity for a particular ligand and that it is the intrinsic binding potential of the protein surface that determines whether it can serve as a robust binding site for a suitably optimized ligand.
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14
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The FTMap family of web servers for determining and characterizing ligand-binding hot spots of proteins. Nat Protoc 2015; 10:733-55. [PMID: 25855957 DOI: 10.1038/nprot.2015.043] [Citation(s) in RCA: 411] [Impact Index Per Article: 45.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
FTMap is a computational mapping server that identifies binding hot spots of macromolecules-i.e., regions of the surface with major contributions to the ligand-binding free energy. To use FTMap, users submit a protein, DNA or RNA structure in PDB (Protein Data Bank) format. FTMap samples billions of positions of small organic molecules used as probes, and it scores the probe poses using a detailed energy expression. Regions that bind clusters of multiple probe types identify the binding hot spots in good agreement with experimental data. FTMap serves as the basis for other servers, namely FTSite, which is used to predict ligand-binding sites, FTFlex, which is used to account for side chain flexibility, FTMap/param, used to parameterize additional probes and FTDyn, for mapping ensembles of protein structures. Applications include determining the druggability of proteins, identifying ligand moieties that are most important for binding, finding the most bound-like conformation in ensembles of unliganded protein structures and providing input for fragment-based drug design. FTMap is more accurate than classical mapping methods such as GRID and MCSS, and it is much faster than the more-recent approaches to protein mapping based on mixed molecular dynamics. By using 16 probe molecules, the FTMap server finds the hot spots of an average-size protein in <1 h. As FTFlex performs mapping for all low-energy conformers of side chains in the binding site, its completion time is proportionately longer.
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15
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Abstract
The potential utility of synthetic macrocycles as drugs, particularly against low
druggability targets such as protein-protein interactions, has been widely discussed.
There is little information, however, to guide the design of macrocycles for good target
protein-binding activity or bioavailability. To address this knowledge gap we analyze the
binding modes of a representative set of macrocycle-protein complexes. The results,
combined with consideration of the physicochemical properties of approved macrocyclic
drugs, allow us to propose specific guidelines for the design of synthetic macrocycles
libraries possessing structural and physicochemical features likely to favor strong
binding to protein targets and also good bioavailability. We additionally provide evidence
that large, natural product derived macrocycles can bind to targets that are not druggable
by conventional, drug-like compounds, supporting the notion that natural product inspired
synthetic macrocycles can expand the number of proteins that are druggable by synthetic
small molecules.
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16
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Koley Seth B, Ray A, Biswas S, Basu S. NiII–Schiff base complex as an enzyme inhibitor of hen egg white lysozyme: a crystallographic and spectroscopic study. Metallomics 2014; 6:1737-47. [DOI: 10.1039/c4mt00098f] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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17
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Alvarez-Garcia D, Barril X. Relationship between Protein Flexibility and Binding: Lessons for Structure-Based Drug Design. J Chem Theory Comput 2014; 10:2608-14. [DOI: 10.1021/ct500182z] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Daniel Alvarez-Garcia
- Departament
de Fisicoquímica, Facultat de Farmàcia, Universitat de Barcelona, Av. Joan XXIII s/n, 08028 Barcelona, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Spain
| | - Xavier Barril
- Departament
de Fisicoquímica, Facultat de Farmàcia, Universitat de Barcelona, Av. Joan XXIII s/n, 08028 Barcelona, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Passeig Lluís Companys 23, 08010 Barcelona, Spain
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18
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Guo W, Wisniewski JA, Ji H. Hot spot-based design of small-molecule inhibitors for protein-protein interactions. Bioorg Med Chem Lett 2014; 24:2546-54. [PMID: 24751445 DOI: 10.1016/j.bmcl.2014.03.095] [Citation(s) in RCA: 107] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2014] [Revised: 03/26/2014] [Accepted: 03/28/2014] [Indexed: 12/27/2022]
Abstract
Protein-protein interactions (PPIs) are important targets for the development of chemical probes and therapeutic agents. From the initial discovery of the existence of hot spots at PPI interfaces, it has been proposed that hot spots might provide the key for developing small-molecule PPI inhibitors. However, there has been no review on the ways in which the knowledge of hot spots can be used to achieve inhibitor design, nor critical examination of successful examples. This Digest discusses the characteristics of hot spots and the identification of druggable hot spot pockets. An analysis of four examples of hot spot-based design reveals the importance of this strategy in discovering potent and selective PPI inhibitors. A general procedure for hot spot-based design of PPI inhibitors is outlined.
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Affiliation(s)
- Wenxing Guo
- Department of Chemistry, Center for Cell and Genome Science, University of Utah, 315 South 1400 East, Salt Lake City, UT 84112-0850, USA
| | - John A Wisniewski
- Department of Chemistry, Center for Cell and Genome Science, University of Utah, 315 South 1400 East, Salt Lake City, UT 84112-0850, USA
| | - Haitao Ji
- Department of Chemistry, Center for Cell and Genome Science, University of Utah, 315 South 1400 East, Salt Lake City, UT 84112-0850, USA.
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19
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Cui G, Swails JM, Manas ES. SPAM: A Simple Approach for Profiling Bound Water Molecules. J Chem Theory Comput 2013; 9:5539-49. [DOI: 10.1021/ct400711g] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Affiliation(s)
- Guanglei Cui
- Computational Chemistry US, Platform Technology and Sciences, GlaxoSmithKline Pharmaceuticals, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Jason M. Swails
- Quantum
Theory Project, University of Florida, Gainesville, Florida 32611, United States
| | - Eric S. Manas
- Computational Chemistry US, Platform Technology and Sciences, GlaxoSmithKline Pharmaceuticals, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
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20
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Haider K, Huggins DJ. Combining solvent thermodynamic profiles with functionality maps of the Hsp90 binding site to predict the displacement of water molecules. J Chem Inf Model 2013; 53:2571-86. [PMID: 24070451 PMCID: PMC3840717 DOI: 10.1021/ci4003409] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Intermolecular interactions in the aqueous phase must compete with the interactions between the two binding partners and their solvating water molecules. In biological systems, water molecules in protein binding sites cluster at well-defined hydration sites and can form strong hydrogen-bonding interactions with backbone and side-chain atoms. Displacement of such water molecules is only favorable when the ligand can form strong compensating hydrogen bonds. Conversely, water molecules in hydrophobic regions of protein binding sites make only weak interactions, and the requirements for favorable displacement are less stringent. The propensity of water molecules for displacement can be identified using inhomogeneous fluid solvation theory (IFST), a statistical mechanical method that decomposes the solvation free energy of a solute into the contributions from different spatial regions and identifies potential binding hotspots. In this study, we employed IFST to study the displacement of water molecules from the ATP binding site of Hsp90, using a test set of 103 ligands. The predicted contribution of a hydration site to the hydration free energy was found to correlate well with the observed displacement. Additionally, we investigated if this correlation could be improved by using the energetic scores of favorable probe groups binding at the location of hydration sites, derived from a multiple copy simultaneous search (MCSS) method. The probe binding scores were not highly predictive of the observed displacement and did not improve the predictivity when used in combination with IFST-based hydration free energies. The results show that IFST alone can be used to reliably predict the observed displacement of water molecules in Hsp90. However, MCSS can augment IFST calculations by suggesting which functional groups should be used to replace highly displaceable water molecules. Such an approach could be very useful in improving the hit-to-lead process for new drug targets.
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Affiliation(s)
- Kamran Haider
- Department of Biology, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences , Lahore, 54792, Pakistan
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21
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Ozbek P, Soner S, Haliloglu T. Hot spots in a network of functional sites. PLoS One 2013; 8:e74320. [PMID: 24023934 PMCID: PMC3759471 DOI: 10.1371/journal.pone.0074320] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2012] [Accepted: 08/02/2013] [Indexed: 12/05/2022] Open
Abstract
It is of significant interest to understand how proteins interact, which holds the key phenomenon in biological functions. Using dynamic fluctuations in high frequency modes, we show that the Gaussian Network Model (GNM) predicts hot spot residues with success rates ranging between S 8–58%, C 84–95%, P 5–19% and A 81–92% on unbound structures and S 8–51%, C 97–99%, P 14–50%, A 94–97% on complex structures for sensitivity, specificity, precision and accuracy, respectively. High specificity and accuracy rates with a single property on unbound protein structures suggest that hot spots are predefined in the dynamics of unbound structures and forming the binding core of interfaces, whereas the prediction of other functional residues with similar dynamic behavior explains the lower precision values. The latter is demonstrated with the case studies; ubiquitin, hen egg-white lysozyme and M2 proton channel. The dynamic fluctuations suggest a pseudo network of residues with high frequency fluctuations, which could be plausible for the mechanism of biological interactions and allosteric regulation.
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Affiliation(s)
- Pemra Ozbek
- Department of Bioengineering, Marmara University, Goztepe, Istanbul, Turkey
| | - Seren Soner
- Department of Chemical Engineering and Polymer Research Center, Bogazici University, Bebek, Turkey
| | - Turkan Haliloglu
- Department of Chemical Engineering and Polymer Research Center, Bogazici University, Bebek, Turkey
- * E-mail:
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22
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Zerbe BS, Hall DR, Vajda S, Whitty A, Kozakov D. Relationship between hot spot residues and ligand binding hot spots in protein-protein interfaces. J Chem Inf Model 2012; 52:2236-44. [PMID: 22770357 DOI: 10.1021/ci300175u] [Citation(s) in RCA: 75] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
In the context of protein-protein interactions, the term "hot spot" refers to a residue or cluster of residues that makes a major contribution to the binding free energy, as determined by alanine scanning mutagenesis. In contrast, in pharmaceutical research, a hot spot is a site on a target protein that has high propensity for ligand binding and hence is potentially important for drug discovery. Here we examine the relationship between these two hot spot concepts by comparing alanine scanning data for a set of 15 proteins with results from mapping the protein surfaces for sites that can bind fragment-sized small molecules. We find the two types of hot spots are largely complementary; the residues protruding into hot spot regions identified by computational mapping or experimental fragment screening are almost always themselves hot spot residues as defined by alanine scanning experiments. Conversely, a residue that is found by alanine scanning to contribute little to binding rarely interacts with hot spot regions on the partner protein identified by fragment mapping. In spite of the strong correlation between the two hot spot concepts, they fundamentally differ, however. In particular, while identification of a hot spot by alanine scanning establishes the potential to generate substantial interaction energy with a binding partner, there are additional topological requirements to be a hot spot for small molecule binding. Hence, only a minority of hot spots identified by alanine scanning represent sites that are potentially useful for small inhibitor binding, and it is this subset that is identified by experimental or computational fragment screening.
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Affiliation(s)
- Brandon S Zerbe
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, USA
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23
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White BR, Carlson JCT, Kerns JL, Wagner CR. Protein interface remodeling in a chemically induced protein dimer. J Mol Recognit 2012; 25:393-403. [DOI: 10.1002/jmr.2196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Brian R. White
- Department of Medicinal Chemistry, College of Pharmacy; University of Minnesota; Minneapolis; MN; 55455; USA
| | - Jonathan C. T. Carlson
- Department of Medicinal Chemistry, College of Pharmacy; University of Minnesota; Minneapolis; MN; 55455; USA
| | - Jessie L. Kerns
- Department of Medicinal Chemistry, College of Pharmacy; University of Minnesota; Minneapolis; MN; 55455; USA
| | - Carston R. Wagner
- Department of Medicinal Chemistry, College of Pharmacy; University of Minnesota; Minneapolis; MN; 55455; USA
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24
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Bohnuud T, Beglov D, Ngan CH, Zerbe B, Hall DR, Brenke R, Vajda S, Frank-Kamenetskii MD, Kozakov D. Computational mapping reveals dramatic effect of Hoogsteen breathing on duplex DNA reactivity with formaldehyde. Nucleic Acids Res 2012; 40:7644-52. [PMID: 22705795 PMCID: PMC3439909 DOI: 10.1093/nar/gks519] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
Formaldehyde has long been recognized as a hazardous environmental agent highly reactive with DNA. Recently, it has been realized that due to the activity of histone demethylation enzymes within the cell nucleus, formaldehyde is produced endogenously, in direct vicinity of genomic DNA. Should it lead to extensive DNA damage? We address this question with the aid of a computational mapping method, analogous to X-ray and nuclear magnetic resonance techniques for observing weakly specific interactions of small organic compounds with a macromolecule in order to establish important functional sites. We concentrate on the leading reaction of formaldehyde with free bases: hydroxymethylation of cytosine amino groups. Our results show that in B-DNA, cytosine amino groups are totally inaccessible for the formaldehyde attack. Then, we explore the effect of recently discovered transient flipping of Watson–Crick (WC) pairs into Hoogsteen (HG) pairs (HG breathing). Our results show that the HG base pair formation dramatically affects the accessibility for formaldehyde of cytosine amino nitrogens within WC base pairs adjacent to HG base pairs. The extensive literature on DNA interaction with formaldehyde is analyzed in light of the new findings. The obtained data emphasize the significance of DNA HG breathing.
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Affiliation(s)
- Tanggis Bohnuud
- Graduate program in Bioinformatics, Boston University, Boston, MA 02215, USA
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25
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Bakan A, Nevins N, Lakdawala AS, Bahar I. Druggability Assessment of Allosteric Proteins by Dynamics Simulations in the Presence of Probe Molecules. J Chem Theory Comput 2012; 8:2435-2447. [PMID: 22798729 PMCID: PMC3392909 DOI: 10.1021/ct300117j] [Citation(s) in RCA: 118] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2012] [Indexed: 12/14/2022]
Abstract
Druggability assessment of a target protein has emerged
in recent
years as an important concept in hit-to-lead optimization. A reliable
and physically relevant measure of druggability would allow informed
decisions on the risk of investing in a particular target. Here, we
define “druggability” as a quantitative estimate of
binding sites and affinities for a potential drug acting on a specific
protein target. In the present study, we describe a new methodology
that successfully predicts the druggability and maximal binding affinity
for a series of challenging targets, including those that function
through allosteric mechanisms. Two distinguishing features of the
methodology are (i) simulation of the binding dynamics of a diversity
of probe molecules selected on the basis of an analysis of approved
drugs and (ii) identification of druggable sites and estimation of
corresponding binding affinities on the basis of an evaluation of
the geometry and energetics of bound probe clusters. The use of the
methodology for a variety of targets such as murine double mutant-2,
protein tyrosine phosphatase 1B (PTP1B), lymphocyte function-associated
antigen 1, vertebrate kinesin-5 (Eg5), and p38 mitogen-activated protein
kinase provides examples for which the method correctly captures the
location and binding affinities of known drugs. It also provides insights
into novel druggable sites and the target’s structural changes
that would accommodate, if not promote and stabilize, drug binding.
Notably, the ability to identify high affinity spots even in challenging
cases such as PTP1B or Eg5 shows promise as a rational tool for assessing
the druggability of protein targets and identifying allosteric or
novel sites for drug binding.
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