1
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Nottoli M, Vanich E, Cupellini L, Scalmani G, Pelosi C, Lipparini F. Importance of Polarizable Embedding for Computing Optical Rotation: The Case of Camphor in Ethanol. J Phys Chem Lett 2024:7992-7999. [PMID: 39078659 DOI: 10.1021/acs.jpclett.4c01550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/31/2024]
Abstract
Solvation effects on optical rotation are notoriously challenging to model for computational chemistry, as the specific rotatory power of a molecule can vary wildly going from apolar to polar or even protic solvents. To address such a problem, we present a polarizable embedding implementation of an electric and magnetic response property based on density functional theory and the AMOEBA polarizable force field, and apply such an implementation to the study of the optical rotation of camphor in ethanol. By comparing a continuum model, and electrostatic and polarizable embedding QM/MM models, we observe that accounting for the environment's polarization gives rise to not only a different quantitative prediction, in very good agreement with experiments for the QM/AMOEBA model, but also to a very different qualitative picture, with the values of the optical rotation computed along a classical molecular dynamics trajectory with electrostatic embedding being statistically uncorrelated to the ones obtained with the polarizable description.
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Affiliation(s)
- Michele Nottoli
- Institute of Applied Analysis and Numerical Simulation, Universität Stuttgart, Pfaffenwaldring 57, D-70569, Stuttgart, Germany
| | - Edoardo Vanich
- Dipartimento di Chimica e Chimica Industriale, Università di Pisa, Via G. Moruzzi 13, I-56124 Pisa, Italy
| | - Lorenzo Cupellini
- Dipartimento di Chimica e Chimica Industriale, Università di Pisa, Via G. Moruzzi 13, I-56124 Pisa, Italy
| | - Giovanni Scalmani
- Gaussian, Inc., 340 Quinnipiac Street Building 40, Wallingford, Connecticut 06492, United States
| | - Chiara Pelosi
- Dipartimento di Chimica e Chimica Industriale, Università di Pisa, Via G. Moruzzi 13, I-56124 Pisa, Italy
| | - Filippo Lipparini
- Dipartimento di Chimica e Chimica Industriale, Università di Pisa, Via G. Moruzzi 13, I-56124 Pisa, Italy
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2
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Gutermuth T, Sieg J, Stohn T, Rarey M. Modeling with Alternate Locations in X-ray Protein Structures. J Chem Inf Model 2023; 63:2573-2585. [PMID: 37018549 DOI: 10.1021/acs.jcim.3c00100] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/07/2023]
Abstract
In many molecular modeling applications, the standard procedure is still to handle proteins as single, rigid structures. While the importance of conformational flexibility is widely known, handling it remains challenging. Even the crystal structure of a protein usually contains variability exemplified in alternate side chain orientations or backbone segments. This conformational variability is encoded in PDB structure files by so-called alternate locations (AltLocs). Most modeling approaches either ignore AltLocs or resolve them with simple heuristics early on during structure import. We analyzed the occurrence and usage of AltLocs in the PDB and developed an algorithm to automatically handle AltLocs in PDB files enabling all structure-based methods using rigid structures to take the alternative protein conformations described by AltLocs into consideration. A respective software tool named AltLocEnumerator can be used as a structure preprocessor to easily exploit AltLocs. While the amount of data makes it difficult to show impact on a statistical level, handling AltLocs has a substantial impact on a case-by-case basis. We believe that the inspection and consideration of AltLocs is a very valuable approach in many modeling scenarios.
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Affiliation(s)
- Torben Gutermuth
- Universität Hamburg, ZBH - Center for Bioinformatics, Bundesstraße 43, 20146 Hamburg, Germany
| | - Jochen Sieg
- Universität Hamburg, ZBH - Center for Bioinformatics, Bundesstraße 43, 20146 Hamburg, Germany
| | - Tim Stohn
- Universität Hamburg, ZBH - Center for Bioinformatics, Bundesstraße 43, 20146 Hamburg, Germany
| | - Matthias Rarey
- Universität Hamburg, ZBH - Center for Bioinformatics, Bundesstraße 43, 20146 Hamburg, Germany
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3
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Burastero O, Defelipe LA, Gola G, Tateosian NL, Lopez ED, Martinena CB, Arcon JP, Traian MD, Wetzler DE, Bento I, Barril X, Ramirez J, Marti MA, Garcia-Alai MM, Turjanski AG. Cosolvent Sites-Based Discovery of Mycobacterium Tuberculosis Protein Kinase G Inhibitors. J Med Chem 2022; 65:9691-9705. [PMID: 35737472 PMCID: PMC9344462 DOI: 10.1021/acs.jmedchem.1c02012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
![]()
Computer-aided
drug discovery methods play a major role in the
development of therapeutically important small molecules, but their
performance needs to be improved. Molecular dynamics simulations in
mixed solvents are useful in understanding protein–ligand recognition
and improving molecular docking predictions. In this work, we used
ethanol as a cosolvent to find relevant interactions for ligands toward
protein kinase G, an essential protein of Mycobacterium
tuberculosis (Mtb).
We validated the hot spots by screening a database of fragment-like
compounds and another one of known kinase inhibitors. Next, we performed
a pharmacophore-guided docking simulation and found three low micromolar
inhibitors, including one with a novel chemical scaffold that we expanded
to four derivative compounds. Binding affinities were characterized
by intrinsic fluorescence quenching assays, isothermal titration calorimetry,
and the analysis of melting curves. The predicted binding mode was
confirmed by X-ray crystallography. Finally, the compounds significantly
inhibited the viability of Mtb in infected
THP-1 macrophages.
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Affiliation(s)
- Osvaldo Burastero
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina.,Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina.,European Molecular Biology Laboratory Hamburg, Notkestrasse 85, Hamburg D-22607, Germany
| | - Lucas A Defelipe
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina.,Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina.,European Molecular Biology Laboratory Hamburg, Notkestrasse 85, Hamburg D-22607, Germany
| | - Gabriel Gola
- Departamento de Química Orgánica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina.,Unidad de Microanálisis y Métodos Físicos Aplicados a Química Orgánica (UMYMFOR), Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires. CONICET, Buenos Aires C1428EGA, Argentina
| | - Nancy L Tateosian
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina.,Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina
| | - Elias D Lopez
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina.,Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina
| | - Camila Belen Martinena
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina.,Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina
| | - Juan Pablo Arcon
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina.,Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina
| | - Martín Dodes Traian
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina.,Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina
| | - Diana E Wetzler
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina.,Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina
| | - Isabel Bento
- European Molecular Biology Laboratory Hamburg, Notkestrasse 85, Hamburg D-22607, Germany
| | - Xavier Barril
- Catalan Institution for Research and Advanced Studies (ICREA), Passeig Lluís Companys 23, Barcelona 08010, Spain.,Faculty of Pharmacy and Institute of Biomedicine (IBUB), University of Barcelona, Av.Joan XXIII 27-31, Barcelona 08028, Spain
| | - Javier Ramirez
- Departamento de Química Orgánica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina.,Unidad de Microanálisis y Métodos Físicos Aplicados a Química Orgánica (UMYMFOR), Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires. CONICET, Buenos Aires C1428EGA, Argentina
| | - Marcelo A Marti
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina.,Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina
| | - Maria M Garcia-Alai
- European Molecular Biology Laboratory Hamburg, Notkestrasse 85, Hamburg D-22607, Germany
| | - Adrián G Turjanski
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina.,Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires C1428EGA, Argentina
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4
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Miñarro-Lleonar M, Ruiz-Carmona S, Alvarez-Garcia D, Schmidtke P, Barril X. Development of an Automatic Pipeline for Participation in the CELPP Challenge. Int J Mol Sci 2022; 23:ijms23094756. [PMID: 35563148 PMCID: PMC9105952 DOI: 10.3390/ijms23094756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 04/20/2022] [Accepted: 04/21/2022] [Indexed: 12/01/2022] Open
Abstract
The prediction of how a ligand binds to its target is an essential step for Structure-Based Drug Design (SBDD) methods. Molecular docking is a standard tool to predict the binding mode of a ligand to its macromolecular receptor and to quantify their mutual complementarity, with multiple applications in drug design. However, docking programs do not always find correct solutions, either because they are not sampled or due to inaccuracies in the scoring functions. Quantifying the docking performance in real scenarios is essential to understanding their limitations, managing expectations and guiding future developments. Here, we present a fully automated pipeline for pose prediction validated by participating in the Continuous Evaluation of Ligand Pose Prediction (CELPP) Challenge. Acknowledging the intrinsic limitations of the docking method, we devised a strategy to automatically mine and exploit pre-existing data, defining—whenever possible—empirical restraints to guide the docking process. We prove that the pipeline is able to generate predictions for most of the proposed targets as well as obtain poses with low RMSD values when compared to the crystal structure. All things considered, our pipeline highlights some major challenges in the automatic prediction of protein–ligand complexes, which will be addressed in future versions of the pipeline.
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Affiliation(s)
- Marina Miñarro-Lleonar
- Pharmacy Faculty, University of Barcelona, Av. de Joan XXIII 27-31, 08028 Barcelona, Spain;
| | | | - Daniel Alvarez-Garcia
- GAIN Therapeutics, Parc Cientific de Barcelona, Baldiri i Reixac 10, 08029 Barcelona, Spain;
| | - Peter Schmidtke
- Discngine S.A.S., 79 Avenue Ledru Rollin, 75012 Paris, France;
| | - Xavier Barril
- Pharmacy Faculty, University of Barcelona, Av. de Joan XXIII 27-31, 08028 Barcelona, Spain;
- GAIN Therapeutics, Parc Cientific de Barcelona, Baldiri i Reixac 10, 08029 Barcelona, Spain;
- Catalan Institute for Research and Advanced Studies (ICREA), Passeig de Lluis Companys 23, 08010 Barcelona, Spain
- Correspondence:
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5
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Computational Design of Inhibitors Targeting the Catalytic β Subunit of Escherichia coli FOF1-ATP Synthase. Antibiotics (Basel) 2022; 11:antibiotics11050557. [PMID: 35625201 PMCID: PMC9138118 DOI: 10.3390/antibiotics11050557] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 03/22/2022] [Accepted: 03/25/2022] [Indexed: 01/27/2023] Open
Abstract
With the uncontrolled growth of multidrug-resistant bacteria, there is an urgent need to search for new therapeutic targets, to develop drugs with novel modes of bactericidal action. FoF1-ATP synthase plays a crucial role in bacterial bioenergetic processes, and it has emerged as an attractive antimicrobial target, validated by the pharmaceutical approval of an inhibitor to treat multidrug-resistant tuberculosis. In this work, we aimed to design, through two types of in silico strategies, new allosteric inhibitors of the ATP synthase, by targeting the catalytic β subunit, a centerpiece in communication between rotor subunits and catalytic sites, to drive the rotary mechanism. As a model system, we used the F1 sector of Escherichia coli, a bacterium included in the priority list of multidrug-resistant pathogens. Drug-like molecules and an IF1-derived peptide, designed through molecular dynamics simulations and sequence mining approaches, respectively, exhibited in vitro micromolar inhibitor potency against F1. An analysis of bacterial and Mammalia sequences of the key structural helix-turn-turn motif of the C-terminal domain of the β subunit revealed highly and moderately conserved positions that could be exploited for the development of new species-specific allosteric inhibitors. To our knowledge, these inhibitors are the first binders computationally designed against the catalytic subunit of FOF1-ATP synthase.
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6
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Alvarez-Garcia D, Schmidtke P, Cubero E, Barril X. Extracting Atomic Contributions to Binding Free Energy Using Molecular Dynamics Simulations with Mixed Solvents (MDmix). Curr Drug Discov Technol 2022; 19:62-68. [PMID: 34951392 PMCID: PMC9906626 DOI: 10.2174/1570163819666211223162829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 09/28/2021] [Accepted: 10/05/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND Mixed solvents MD (MDmix) simulations have proved to be a useful and increasingly accepted technique with several applications in structure-based drug discovery. One of the assumptions behind the methodology is the transferability of free energy values from the simulated cosolvent molecules to larger drug-like molecules. However, the binding free energy maps (ΔGbind) calculated for the different moieties of the cosolvent molecules (e.g. a hydroxyl map for the ethanol) are largely influenced by the rest of the solvent molecule and do not reflect the intrinsic affinity of the moiety in question. As such, they are hardly transferable to different molecules. METHOD To achieve transferable energies, we present here a method for decomposing the molecular binding free energy into accurate atomic contributions. RESULT We demonstrate with two qualitative visual examples how the corrected energy maps better match known binding hotspots and how they can reveal hidden hotspots with actual drug design potential. CONCLUSION Atomic decomposition of binding free energies derived from MDmix simulations provides transferable and quantitative binding free energy maps.
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Affiliation(s)
- Daniel Alvarez-Garcia
- Gain Therapeutics, Parc Cientific de Barcelona, Baldiri Reixac 10, 08029 Barcelona, Spain
| | - Peter Schmidtke
- Facultat de Farmacia, Universitat de Barcelona, Av. Joan XXIII 27-31, 08028 Barcelona, Spain;,Current address: Discngine, 79 Avenue Ledru Rollin, 75012 Paris, France;
| | - Elena Cubero
- Gain Therapeutics, Parc Cientific de Barcelona, Baldiri Reixac 10, 08029 Barcelona, Spain
| | - Xavier Barril
- Gain Therapeutics, Parc Cientific de Barcelona, Baldiri Reixac 10, 08029 Barcelona, Spain;,Facultat de Farmacia, Universitat de Barcelona, Av. Joan XXIII 27-31, 08028 Barcelona, Spain;,Catalan Institution for Research and Advanced Studies (ICREA), Passeig Lluis Companys 23, 08010 Barcelona, Spain,Address correspondence to this author at the Gain Therapeutics, Parc Cientific de Barcelona, Baldiri Reixac 10, 08029 Barcelona, Spain; E-mail:
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7
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Maiangwa J, Hamdan SH, Mohamad Ali MS, Salleh AB, Zaliha Raja Abd Rahman RN, Shariff FM, Leow TC. Enhancing the stability of Geobacillus zalihae T1 lipase in organic solvents and insights into the structural stability of its variants. J Mol Graph Model 2021; 105:107897. [PMID: 33770705 DOI: 10.1016/j.jmgm.2021.107897] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 03/04/2021] [Accepted: 03/04/2021] [Indexed: 11/28/2022]
Abstract
Critical to the applications of proteins in non-aqueous enzymatic processes is their structural dynamics in relation to solvent polarity. A pool of mutants derived from Geobacillus zalihae T1 lipase was screened in organic solvents (methanol, ethanol, propanol, butanol and pentanol) resulting in the selection of six mutants at initial screening (A83D/K251E, R21C, G35D/S195 N, K84R/R103C/M121I/T272 M and R106H/G327S). Site-directed mutagenesis further yielded quadruple mutants A83D/M121I/K251E/G327S and A83D/M121I/S195 N/T272 M, both of which had improved activity after incubation in methanol. The km and kcat values of these mutants vary marginally with the wild-type enzyme in the methanol/substrate mixture. Thermally induced unfolding of mutants was accompanied with some loss of secondary structure content. The root mean square deviations (RMSD) and B-factors revealed that changes in the structural organization are intertwined with an interplay of the protein backbone with organic solvents. Spatially exposed charged residues showed correlations between the solvation dynamics of the methanol solvent and the hydrophobicity of the residues. The short distances of the radial distribution function provided the required distances for hydrogen bond formation and hydrophobic interactions. These dynamic changes demonstrate newly formed structural interactions could be targeted and incorporated experimentally on the basis of solvent mobility and mutant residues.
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Affiliation(s)
- Jonathan Maiangwa
- Department of Cell and Molecular Biology, Enzyme Microbial Technology Research Center, Faculty of Biotechnology and Biomolecular Science, Universiti Putra Malaysia Serdang, 43400, UPM Serdang, Selangor, Malaysia; Department of Microbiology Kaduna State University, Nigeria; Enzyme Microbial Technology Research Centre, Faculty of Biotechnology and Biomolecular Science, Universiti Putra Malaysia Serdang, 43400, UPM Serdang, Selangor, Malaysia
| | - Siti Hajar Hamdan
- Department of Biochemistry, Enzyme Microbial Technology Research Centre, Faculty of Biotechnology and Biomolecular Science, Universiti Putra Malaysia Serdang, 43400, UPM Serdang, Selangor, Malaysia
| | - Mohd Shukuri Mohamad Ali
- Department of Biochemistry, Enzyme Microbial Technology Research Centre, Faculty of Biotechnology and Biomolecular Science, Universiti Putra Malaysia Serdang, 43400, UPM Serdang, Selangor, Malaysia
| | - Abu Bakar Salleh
- Enzyme Microbial Technology Research Centre, Faculty of Biotechnology and Biomolecular Science, Universiti Putra Malaysia Serdang, 43400, UPM Serdang, Selangor, Malaysia
| | - Raja Noor Zaliha Raja Abd Rahman
- Department of Microbiology, Enzyme Microbial Technology Research Centre, Faculty of Biotechnology and Biomolecular Science, Universiti Putra Malaysia, 43400, UPM Serdang, Selangor, Malaysia
| | - Fairolniza Mohd Shariff
- Institute of Bioscience, 43400, UPM Serdang, Universiti Putra Malaysia Serdang, Selangor, Malaysia
| | - Thean Chor Leow
- Department of Cell and Molecular Biology, Enzyme Microbial Technology Research Center, Faculty of Biotechnology and Biomolecular Science, Universiti Putra Malaysia Serdang, 43400, UPM Serdang, Selangor, Malaysia; Enzyme Microbial Technology Research Centre, Faculty of Biotechnology and Biomolecular Science, Universiti Putra Malaysia Serdang, 43400, UPM Serdang, Selangor, Malaysia; Institute of Bioscience, 43400, UPM Serdang, Universiti Putra Malaysia Serdang, Selangor, Malaysia.
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8
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Monoclonal antibody stability can be usefully monitored using the excitation-energy-dependent fluorescence edge-shift. Biochem J 2021; 477:3599-3612. [PMID: 32869839 PMCID: PMC7527260 DOI: 10.1042/bcj20200580] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 08/27/2020] [Accepted: 09/01/2020] [Indexed: 11/17/2022]
Abstract
Among the major challenges in the development of biopharmaceuticals are structural heterogeneity and aggregation. The development of a successful therapeutic monoclonal antibody (mAb) requires both a highly active and also stable molecule. Whilst a range of experimental (biophysical) approaches exist to track changes in stability of proteins, routine prediction of stability remains challenging. The fluorescence red edge excitation shift (REES) phenomenon is sensitive to a range of changes in protein structure. Based on recent work, we have found that quantifying the REES effect is extremely sensitive to changes in protein conformational state and dynamics. Given the extreme sensitivity, potentially this tool could provide a ‘fingerprint’ of the structure and stability of a protein. Such a tool would be useful in the discovery and development of biopharamceuticals and so we have explored our hypothesis with a panel of therapeutic mAbs. We demonstrate that the quantified REES data show remarkable sensitivity, being able to discern between structurally identical antibodies and showing sensitivity to unfolding and aggregation. The approach works across a broad concentration range (µg–mg/ml) and is highly consistent. We show that the approach can be applied alongside traditional characterisation testing within the context of a forced degradation study (FDS). Most importantly, we demonstrate the approach is able to predict the stability of mAbs both in the short (hours), medium (days) and long-term (months). The quantified REES data will find immediate use in the biopharmaceutical industry in quality assurance, formulation and development. The approach benefits from low technical complexity, is rapid and uses instrumentation which exists in most biochemistry laboratories without modification.
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9
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Smith RD, Carlson HA. Identification of Cryptic Binding Sites Using MixMD with Standard and Accelerated Molecular Dynamics. J Chem Inf Model 2021; 61:1287-1299. [PMID: 33599485 DOI: 10.1021/acs.jcim.0c01002] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Protein dynamics play an important role in small molecule binding and can pose a significant challenge in the identification of potential binding sites. Cryptic binding sites have been defined as sites which require significant rearrangement of the protein structure to become physically accessible to a ligand. Mixed-solvent MD (MixMD) is a computational protocol which maps the surface of the protein using molecular dynamics (MD) of the unbound protein solvated in a 5% box of probe molecules with explicit water. This method has successfully identified known active and allosteric sites which did not require reorganization. In this study, we apply the MixMD protocol to identify known cryptic sites of 12 proteins characterized by a wide range of conformational changes. Of these 12 proteins, three require reorganization of side chains, five require loop movements, and four require movement of more significant structures such as whole helices. In five cases, we find that standard MixMD simulations are able to map the cryptic binding sites with at least one probe type. In two cases (guanylate kinase and TIE-2), accelerated MD, which increases sampling of torsional angles, was necessary to achieve mapping of portions of the cryptic binding site missed by standard MixMD. For more complex systems where movement of a helix or domain is necessary, MixMD was unable to map the binding site even with accelerated dynamics, possibly due to the limited timescale (100 ns for individual simulations). In general, similar conformational dynamics are observed in water-only simulations and those with probe molecules. This could imply that the probes are not driving opening events but rather take advantage of mapping sites that spontaneously open as part of their inherent conformational behavior. Finally, we show that docking to an ensemble of conformations from the standard MixMD simulations performs better than docking the apo crystal structure in nine cases and even better than half of the bound crystal structures. Poorer performance was seen in docking to ensembles of conformations from the accelerated MixMD simulations.
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Affiliation(s)
- Richard D Smith
- Department of Medicinal Chemistry, University of Michigan, 428 Church Street, Ann Arbor, Michigan 48109-1056, United States
| | - Heather A Carlson
- Department of Medicinal Chemistry, University of Michigan, 428 Church Street, Ann Arbor, Michigan 48109-1056, United States
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10
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Wehrhan L, Hillisch A, Mundt S, Tersteegen A, Meier K. Druggability Assessment for Selected Serine Proteases in a Pharmaceutical Industry Setting. ChemMedChem 2020; 15:2010-2018. [PMID: 32776472 DOI: 10.1002/cmdc.202000425] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Indexed: 01/15/2023]
Abstract
Target druggability assessment is an integral part of the early target characterization and selection process in pharmaceutical industry. Here, we investigate a set of five different serine proteases from the blood coagulation cascade. The aim of this study is twofold. Firstly, leveraging the wealth of available in-house high-throughput screening (HTS) data, we analyze HTS hit rates and discuss their predictive value for the development of small molecule (SMOL) candidates. Purely structure-activity relationship (SAR) based druggability ratings are compared with computational protein-structure based druggability assessments. Secondly, we evaluate the impact of using conformational ensembles from molecular dynamics (MD) simulations instead of single static crystal structures as basis for computational druggability assessments. Based on this study, we recommend incorporating molecular dynamics routinely into the early target characterization process, especially if only a single X-ray structure is available.
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Affiliation(s)
- Leon Wehrhan
- Bayer AG, Research & Development, Pharmaceuticals, 42096, Wuppertal, Germany
| | - Alexander Hillisch
- Bayer AG, Research & Development, Pharmaceuticals, 42096, Wuppertal, Germany
| | - Stefan Mundt
- Bayer AG, Research & Development, Pharmaceuticals, 42096, Wuppertal, Germany
| | - Adrian Tersteegen
- Bayer AG, Research & Development, Pharmaceuticals, 42096, Wuppertal, Germany
| | - Katharina Meier
- Bayer AG, Research & Development, Pharmaceuticals, 42096, Wuppertal, Germany
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11
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Loeffler JR, Fernández-Quintero ML, Schauperl M, Liedl KR. STACKED - Solvation Theory of Aromatic Complexes as Key for Estimating Drug Binding. J Chem Inf Model 2020; 60:2304-2313. [PMID: 32142283 PMCID: PMC7189365 DOI: 10.1021/acs.jcim.9b01165] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
![]()
The
use of fragments to biophysically characterize a protein binding
pocket and determine the strengths of certain interactions is a computationally
and experimentally commonly applied approach. Almost all drug like
molecules contain at least one aromatic moiety forming stacking interactions
in the binding pocket. In computational drug design, the strength
of stacking and the resulting optimization of the aromatic core or
moiety is usually calculated using high level quantum mechanical approaches.
However, as these calculations are performed in a vacuum, solvation
properties are neglected. We close this gap by using Grid Inhomogeneous
Solvation Theory (GIST) to describe the properties of individual heteroaromatics
and complexes and thereby estimate the desolvation penalty. In our
study, we investigated the solvation free energies of heteroaromatics
frequently occurring in drug design projects in complex with truncated
side chains of phenylalanine, tyrosine, and tryptophan. Furthermore,
we investigated the properties of drug-fragments crystallized in a
fragment-based lead optimization approach investigating PDE-10-A.
We do not only find good correlation for the estimated desolvation
penalty and the experimental binding free energy, but our calculations
also allow us to predict prominent interaction sites. We highlight
the importance of including the desolvation penalty of the respective
heteroaromatics in stacked complexes to explain the gain or loss in
affinity of potential lead compounds.
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Affiliation(s)
- Johannes R Loeffler
- Institute of General, Inorganic and Theoretical Chemistry, and Center of Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80-82, A-6020 Innsbruck, Tyrol, Austria
| | - Monica L Fernández-Quintero
- Institute of General, Inorganic and Theoretical Chemistry, and Center of Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80-82, A-6020 Innsbruck, Tyrol, Austria
| | - Michael Schauperl
- Institute of General, Inorganic and Theoretical Chemistry, and Center of Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80-82, A-6020 Innsbruck, Tyrol, Austria
| | - Klaus R Liedl
- Institute of General, Inorganic and Theoretical Chemistry, and Center of Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80-82, A-6020 Innsbruck, Tyrol, Austria
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12
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Mannini B, Vecchi G, Labrador-Garrido A, Fabre B, Fani G, Franco JM, Lilley K, Pozo D, Vendruscolo M, Chiti F, Dobson CM, Roodveldt C. Differential Interactome and Innate Immune Response Activation of Two Structurally Distinct Misfolded Protein Oligomers. ACS Chem Neurosci 2019; 10:3464-3478. [PMID: 31313906 DOI: 10.1021/acschemneuro.9b00088] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
The formation of misfolded protein oligomers during early stages of amyloid aggregation and the activation of neuroinflammatory responses are two key events associated with neurodegenerative diseases. Although it has been established that misfolded oligomers are involved in the neuroinflammatory process, the links between their structural features and their functional effects on the immune response remain unknown. To explore such links, we took advantage of two structurally distinct soluble oligomers (type A and B) of protein HypF-N and compared the elicited microglial inflammatory responses. By using confocal microscopy, protein pull-down, and high-throughput mass spectrometry, we found that, even though both types bound to a common pool of microglial proteins, type B oligomers-with a lower solvent-exposed hydrophobicity-showed enhanced protein binding, correlating with the observed inflammatory response. Furthermore, the interactome associated with inflammatory-mediated neurodegeneration revealed previously unidentified receptors and signaling molecules likely to be involved in the oligomer-elicited innate immune response.
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Affiliation(s)
- Benedetta Mannini
- Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, CB2 1EW Cambridge, U.K
| | - Giulia Vecchi
- Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, CB2 1EW Cambridge, U.K
| | - Adahir Labrador-Garrido
- Andalusian Center for Molecular Biology and Regenerative Medicine (CABIMER) - Universidad de Sevilla, Consejo Superior de Investigaciones Científicas (CSIC), Universidad Pablo de Olavide, 41092 Seville, Spain
- Department of Medical Biochemistry, Molecular Biology and Immunology, University of Seville, 41092 Seville, Spain
| | - Bertrand Fabre
- Cambridge Centre for Proteomics, Systems Biology Centre, Department of Biochemistry, University of Cambridge, CB2 1GA Cambridge, U.K
| | - Giulia Fani
- Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, CB2 1EW Cambridge, U.K
- Department of Experimental and Clinical Biomedical Sciences, Section of Biochemistry, University of Florence, 50134 Florence, Italy
| | - Jaime M. Franco
- Andalusian Center for Molecular Biology and Regenerative Medicine (CABIMER) - Universidad de Sevilla, Consejo Superior de Investigaciones Científicas (CSIC), Universidad Pablo de Olavide, 41092 Seville, Spain
- Department of Medical Biochemistry, Molecular Biology and Immunology, University of Seville, 41092 Seville, Spain
| | - Kathryn Lilley
- Cambridge Centre for Proteomics, Systems Biology Centre, Department of Biochemistry, University of Cambridge, CB2 1GA Cambridge, U.K
| | - David Pozo
- Andalusian Center for Molecular Biology and Regenerative Medicine (CABIMER) - Universidad de Sevilla, Consejo Superior de Investigaciones Científicas (CSIC), Universidad Pablo de Olavide, 41092 Seville, Spain
- Department of Medical Biochemistry, Molecular Biology and Immunology, University of Seville, 41092 Seville, Spain
| | - Michele Vendruscolo
- Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, CB2 1EW Cambridge, U.K
| | - Fabrizio Chiti
- Department of Experimental and Clinical Biomedical Sciences, Section of Biochemistry, University of Florence, 50134 Florence, Italy
| | - Christopher M. Dobson
- Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, CB2 1EW Cambridge, U.K
| | - Cintia Roodveldt
- Andalusian Center for Molecular Biology and Regenerative Medicine (CABIMER) - Universidad de Sevilla, Consejo Superior de Investigaciones Científicas (CSIC), Universidad Pablo de Olavide, 41092 Seville, Spain
- Department of Medical Biochemistry, Molecular Biology and Immunology, University of Seville, 41092 Seville, Spain
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13
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Schmidt D, Boehm M, McClendon CL, Torella R, Gohlke H. Cosolvent-Enhanced Sampling and Unbiased Identification of Cryptic Pockets Suitable for Structure-Based Drug Design. J Chem Theory Comput 2019; 15:3331-3343. [PMID: 30998331 DOI: 10.1021/acs.jctc.8b01295] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Modulating protein activity with small-molecules binding to cryptic pockets offers great opportunities to overcome hurdles in drug design. Cryptic sites are atypical binding sites in proteins that are closed in the absence of a stabilizing ligand and are thus inherently difficult to identify. Many studies have proposed methods to predict cryptic sites. However, a general approach to prospectively sample open conformations of these sites and to identify cryptic pockets in an unbiased manner suitable for structure-based drug design remains elusive. Here, we describe an all-atom, explicit cosolvent, molecular dynamics (MD) simulations-based workflow to sample the open states of cryptic sites and identify opened pockets, in a manner that does not require a priori knowledge about these sites. Furthermore, the workflow relies on a target-independent parametrization that only distinguishes between binding pockets for peptides or small molecules. We validated our approach on a diverse test set of seven proteins with crystallographically determined cryptic sites. The known cryptic sites were found among the three highest-ranked predicted cryptic sites, and an open site conformation was sampled and selected for most of the systems. Crystallographic ligand poses were well reproduced by docking into these identified open conformations for five of the systems. When the fully open state could not be reproduced, we were still able to predict the location of the cryptic site, or identify other cryptic sites that could be retrospectively validated with knowledge of the protein target. These characteristics render our approach valuable for investigating novel protein targets without any prior information.
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Affiliation(s)
- Denis Schmidt
- Mathematisch-Naturwissenschaftliche Fakultät, Institut für Pharmazeutische und Medizinische Chemie , Heinrich-Heine-Universität Düsseldorf , 40225 Düsseldorf , Germany
| | - Markus Boehm
- Medicinal Sciences , Pfizer Inc. , Cambridge , Massachusetts 02139 , United States
| | | | - Rubben Torella
- Medicinal Sciences , Pfizer Inc. , Cambridge , Massachusetts 02139 , United States
| | - Holger Gohlke
- Mathematisch-Naturwissenschaftliche Fakultät, Institut für Pharmazeutische und Medizinische Chemie , Heinrich-Heine-Universität Düsseldorf , 40225 Düsseldorf , Germany.,John von Neumann Institute for Computing (NIC), Jülich Supercomputing Centre (JSC) & Institute for Complex Systems-Structural Biochemistry (ICS 6) , Forschungszentrum Jülich GmbH , 52425 Jülich , Germany
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14
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Ghanakota P, DasGupta D, Carlson HA. Free Energies and Entropies of Binding Sites Identified by MixMD Cosolvent Simulations. J Chem Inf Model 2019; 59:2035-2045. [PMID: 31017411 DOI: 10.1021/acs.jcim.8b00925] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
In our recent efforts to map protein surfaces using mixed-solvent molecular dynamics (MixMD) (Ghanakota, P.; Carlson, H. A. Moving Beyond Active-Site Detection: MixMD Applied to Allosteric Systems. J. Phys. Chem. B 2016, 120, 8685-8695), we were able to successfully capture active sites and allosteric sites within the top-four most occupied hotspots. In this study, we describe our approach for estimating the thermodynamic profile of the binding sites identified by MixMD. First, we establish a framework for calculating free energies from MixMD simulations, and we compare our approach to alternative methods. Second, we present a means to obtain a relative ranking of the binding sites by their configurational entropy. The theoretical maximum and minimum free energy and entropy values achievable under such a framework along with the limitations of the techniques are discussed. Using this approach, the free energy and relative entropy ranking of the top-four MixMD binding sites were computed and analyzed across our allosteric protein targets: Abl Kinase, Androgen Receptor, Pdk1 Kinase, Farnesyl Pyrophosphate Synthase, Chk1 Kinase, Glucokinase, and Protein Tyrosine Phosphatase 1B.
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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
| | - Debarati DasGupta
- 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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15
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Mahmoud AH, Yang Y, Lill MA. Improving Atom-Type Diversity and Sampling in Cosolvent Simulations Using λ-Dynamics. J Chem Theory Comput 2019; 15:3272-3287. [PMID: 30933496 DOI: 10.1021/acs.jctc.8b00940] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Amr H. Mahmoud
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, 575 Stadium Mall Drive, West Lafayette, Indiana 47906, United States
| | - Ying Yang
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, 575 Stadium Mall Drive, West Lafayette, Indiana 47906, United States
| | - Markus A. Lill
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, 575 Stadium Mall Drive, West Lafayette, Indiana 47906, United States
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16
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Sun Z, Liu Q, Qu G, Feng Y, Reetz MT. Utility of B-Factors in Protein Science: Interpreting Rigidity, Flexibility, and Internal Motion and Engineering Thermostability. Chem Rev 2019; 119:1626-1665. [PMID: 30698416 DOI: 10.1021/acs.chemrev.8b00290] [Citation(s) in RCA: 292] [Impact Index Per Article: 58.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Zhoutong Sun
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, 32 West Seventh Avenue, Tianjin Airport Economic Area, Tianjin 300308, China
| | - Qian Liu
- State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Ge Qu
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, 32 West Seventh Avenue, Tianjin Airport Economic Area, Tianjin 300308, China
| | - Yan Feng
- State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Manfred T. Reetz
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, 32 West Seventh Avenue, Tianjin Airport Economic Area, Tianjin 300308, China
- Max-Planck-Institut für Kohlenforschung, Kaiser-Wilhelm-Platz 1, 45470 Mülheim an der Ruhr, Germany
- Chemistry Department, Philipps-University, Hans-Meerwein-Strasse 4, 35032 Marburg, Germany
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17
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Solvents to Fragments to Drugs: MD Applications in Drug Design. Molecules 2018; 23:molecules23123269. [PMID: 30544890 PMCID: PMC6321499 DOI: 10.3390/molecules23123269] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Revised: 12/02/2018] [Accepted: 12/03/2018] [Indexed: 01/24/2023] Open
Abstract
Simulations of molecular dynamics (MD) are playing an increasingly important role in structure-based drug discovery (SBDD). Here we review the use of MD for proteins in aqueous solvation, organic/aqueous mixed solvents (MDmix) and with small ligands, to the classic SBDD problems: Binding mode and binding free energy predictions. The simulation of proteins in their condensed state reveals solvent structures and preferential interaction sites (hot spots) on the protein surface. The information provided by water and its cosolvents can be used very effectively to understand protein ligand recognition and to improve the predictive capability of well-established methods such as molecular docking. The application of MD simulations to the study of the association of proteins with drug-like compounds is currently only possible for specific cases, as it remains computationally very expensive and labor intensive. MDmix simulations on the other hand, can be used systematically to address some of the common tasks in SBDD. With the advent of new tools and faster computers we expect to see an increase in the application of mixed solvent MD simulations to a plethora of protein targets to identify new drug candidates.
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18
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Yang Y, Mahmoud AH, Lill MA. Modeling of Halogen–Protein Interactions in Co-Solvent Molecular Dynamics Simulations. J Chem Inf Model 2018; 59:38-42. [PMID: 30525593 DOI: 10.1021/acs.jcim.8b00806] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Affiliation(s)
- Ying Yang
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, 575 Stadium Mall Drive, West Lafayette, Indiana 47906, United States
| | - Amr H. Mahmoud
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, 575 Stadium Mall Drive, West Lafayette, Indiana 47906, United States
| | - Markus A. Lill
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, 575 Stadium Mall Drive, West Lafayette, Indiana 47906, United States
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19
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Iglesias J, Saen‐oon S, Soliva R, Guallar V. Computational structure‐based drug design: Predicting target flexibility. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2018. [DOI: 10.1002/wcms.1367] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Affiliation(s)
| | | | | | - Victor Guallar
- Life Science DepartmentBarcelonaSpain
- ICREA, Passeig Lluís Companys 23BarcelonaSpain
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20
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Graham SE, Smith RD, Carlson HA. Predicting Displaceable Water Sites Using Mixed-Solvent Molecular Dynamics. J Chem Inf Model 2018; 58:305-314. [PMID: 29286658 PMCID: PMC6190669 DOI: 10.1021/acs.jcim.7b00268] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Water molecules are an important factor in protein-ligand binding. Upon binding of a ligand with a protein's surface, waters can either be displaced by the ligand or may be conserved and possibly bridge interactions between the protein and ligand. Depending on the specific interactions made by the ligand, displacing waters can yield a gain in binding affinity. The extent to which binding affinity may increase is difficult to predict, as the favorable displacement of a water molecule is dependent on the site-specific interactions made by the water and the potential ligand. Several methods have been developed to predict the location of water sites on a protein's surface, but the majority of methods are not able to take into account both protein dynamics and the interactions made by specific functional groups. Mixed-solvent molecular dynamics (MixMD) is a cosolvent simulation technique that explicitly accounts for the interaction of both water and small molecule probes with a protein's surface, allowing for their direct competition. This method has previously been shown to identify both active and allosteric sites on a protein's surface. Using a test set of eight systems, we have developed a method using MixMD to identify conserved and displaceable water sites. Conserved sites can be determined by an occupancy-based metric to identify sites which are consistently occupied by water even in the presence of probe molecules. Conversely, displaceable water sites can be found by considering the sites which preferentially bind probe molecules. Furthermore, the inclusion of six probe types allows the MixMD method to predict which functional groups are capable of displacing which water sites. The MixMD method consistently identifies sites which are likely to be nondisplaceable and predicts the favorable displacement of water sites that are known to be displaced upon ligand binding.
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Affiliation(s)
- Sarah E. Graham
- Department of Biophysics, College of Pharmacy, University of Michigan, 428 Church St., Ann Arbor, Michigan, 48109-1065
| | - Richard D. Smith
- Department of Medicinal Chemistry, College of Pharmacy, University of Michigan, 428 Church St., Ann Arbor, Michigan, 48109-1065
| | - Heather A. Carlson
- Department of Biophysics, College of Pharmacy, University of Michigan, 428 Church St., Ann Arbor, Michigan, 48109-1065
- Department of Medicinal Chemistry, College of Pharmacy, University of Michigan, 428 Church St., Ann Arbor, Michigan, 48109-1065
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21
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Gioia D, Bertazzo M, Recanatini M, Masetti M, Cavalli A. Dynamic Docking: A Paradigm Shift in Computational Drug Discovery. Molecules 2017; 22:molecules22112029. [PMID: 29165360 PMCID: PMC6150405 DOI: 10.3390/molecules22112029] [Citation(s) in RCA: 87] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Revised: 11/18/2017] [Accepted: 11/19/2017] [Indexed: 12/18/2022] Open
Abstract
Molecular docking is the methodology of choice for studying in silico protein-ligand binding and for prioritizing compounds to discover new lead candidates. Traditional docking simulations suffer from major limitations, mostly related to the static or semi-flexible treatment of ligands and targets. They also neglect solvation and entropic effects, which strongly limits their predictive power. During the last decade, methods based on full atomistic molecular dynamics (MD) have emerged as a valid alternative for simulating macromolecular complexes. In principle, compared to traditional docking, MD allows the full exploration of drug-target recognition and binding from both the mechanistic and energetic points of view (dynamic docking). Binding and unbinding kinetic constants can also be determined. While dynamic docking is still too computationally expensive to be routinely used in fast-paced drug discovery programs, the advent of faster computing architectures and advanced simulation methodologies are changing this scenario. It is feasible that dynamic docking will replace static docking approaches in the near future, leading to a major paradigm shift in in silico drug discovery. Against this background, we review the key achievements that have paved the way for this progress.
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Affiliation(s)
- Dario Gioia
- Department of Pharmacy and Biotechnology, Alma Mater Studiorum-Universita' di Bologna, via Belmeloro 6, I-40126 Bologna, Italy.
| | - Martina Bertazzo
- Department of Pharmacy and Biotechnology, Alma Mater Studiorum-Universita' di Bologna, via Belmeloro 6, I-40126 Bologna, Italy.
- Computational Sciences, Istituto Italiano di Tecnologia, via Morego 30, 16163 Genova, Italy.
| | - Maurizio Recanatini
- Department of Pharmacy and Biotechnology, Alma Mater Studiorum-Universita' di Bologna, via Belmeloro 6, I-40126 Bologna, Italy.
| | - Matteo Masetti
- Department of Pharmacy and Biotechnology, Alma Mater Studiorum-Universita' di Bologna, via Belmeloro 6, I-40126 Bologna, Italy.
| | - Andrea Cavalli
- Department of Pharmacy and Biotechnology, Alma Mater Studiorum-Universita' di Bologna, via Belmeloro 6, I-40126 Bologna, Italy.
- Computational Sciences, Istituto Italiano di Tecnologia, via Morego 30, 16163 Genova, Italy.
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22
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Plant-expressed cocaine hydrolase variants of butyrylcholinesterase exhibit altered allosteric effects of cholinesterase activity and increased inhibitor sensitivity. Sci Rep 2017; 7:10419. [PMID: 28874829 PMCID: PMC5585256 DOI: 10.1038/s41598-017-10571-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Accepted: 08/10/2017] [Indexed: 12/04/2022] Open
Abstract
Butyrylcholinesterase (BChE) is an enzyme with broad substrate and ligand specificities and may function as a generalized bioscavenger by binding and/or hydrolyzing various xenobiotic agents and toxicants, many of which target the central and peripheral nervous systems. Variants of BChE were rationally designed to increase the enzyme’s ability to hydrolyze the psychoactive enantiomer of cocaine. These variants were cloned, and then expressed using the magnICON transient expression system in plants and their enzymatic properties were investigated. In particular, we explored the effects that these site-directed mutations have over the enzyme kinetics with various substrates of BChE. We further compared the affinity of various anticholinesterases including organophosphorous nerve agents and pesticides toward these BChE variants relative to the wild type enzyme. In addition to serving as a therapy for cocaine addiction-related diseases, enhanced bioscavenging against other harmful agents could add to the practicality and versatility of the plant-derived recombinant enzyme as a multivalent therapeutic.
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23
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Uehara S, Tanaka S. Cosolvent-Based Molecular Dynamics for Ensemble Docking: Practical Method for Generating Druggable Protein Conformations. J Chem Inf Model 2017; 57:742-756. [PMID: 28388074 DOI: 10.1021/acs.jcim.6b00791] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Protein flexibility is a major hurdle in current structure-based virtual screening (VS). In spite of the recent advances in high-performance computing, protein-ligand docking methods still demand tremendous computational cost to take into account the full degree of protein flexibility. In this context, ensemble docking has proven its utility and efficiency for VS studies, but it still needs a rational and efficient method to select and/or generate multiple protein conformations. Molecular dynamics (MD) simulations are useful to produce distinct protein conformations without abundant experimental structures. In this study, we present a novel strategy that makes use of cosolvent-based molecular dynamics (CMD) simulations for ensemble docking. By mixing small organic molecules into a solvent, CMD can stimulate dynamic protein motions and induce partial conformational changes of binding pocket residues appropriate for the binding of diverse ligands. The present method has been applied to six diverse target proteins and assessed by VS experiments using many actives and decoys of DEKOIS 2.0. The simulation results have revealed that the CMD is beneficial for ensemble docking. Utilizing cosolvent simulation allows the generation of druggable protein conformations, improving the VS performance compared with the use of a single experimental structure or ensemble docking by standard MD with pure water as the solvent.
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Affiliation(s)
- Shota Uehara
- Department of Computational Science, Graduate School of System Informatics, Kobe University , 1-1 Rokkodai, Nada, Kobe, Hyogo 657-8501, Japan
| | - Shigenori Tanaka
- Department of Computational Science, Graduate School of System Informatics, Kobe University , 1-1 Rokkodai, Nada, Kobe, Hyogo 657-8501, Japan
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24
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Delcanale P, Rodríguez-Amigo B, Juárez-Jiménez J, Luque FJ, Abbruzzetti S, Agut M, Nonell S, Viappiani C. Tuning the local solvent composition at a drug carrier surface: the effect of dimethyl sulfoxide/water mixture on the photofunctional properties of hypericin-β-lactoglobulin complexes. J Mater Chem B 2017; 5:1633-1641. [PMID: 32263935 DOI: 10.1039/c7tb00081b] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Aggregation is a major problem for the anti-microbial photodynamic applications of hydrophobic photosensitizers since it strongly reduces the amount of singlet oxygen generated in aqueous solutions. Binding of hypericin (Hyp) to the milk whey protein β-lactoglobulin (βLG), occurring at the two hydrophobic cavities located at the interface of the protein homodimer, can be exploited to confer water-solubility and biocompatibility to the photosensitizer. The introduction of a small amount of the organic cosolvent dimethyl sulfoxide (DMSO) leads to a remarkable improvement of the photophysical properties of the complex Hyp-βLG by increasing its fluorescence emission and singlet oxygen photosensitization quantum yields. Surprisingly, the ability of the complex to photo-inactivate bacteria of the strain Staphylococcus aureus is strongly reduced in the presence of DMSO, despite the higher yield of photosensitization. The reasons for this apparently contradictory behavior are investigated, providing new insights into the use of carrier systems for hydrophobic photosensitizers.
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Affiliation(s)
- P Delcanale
- Dipartimento di Scienze Matematiche, Fisiche e Informatiche, Università di Parma, Parco Area delle Scienze 7A, 43124 Parma, Italy.
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25
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Marques SM, Daniel L, Buryska T, Prokop Z, Brezovsky J, Damborsky J. Enzyme Tunnels and Gates As Relevant Targets in Drug Design. Med Res Rev 2016; 37:1095-1139. [PMID: 27957758 DOI: 10.1002/med.21430] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2016] [Revised: 10/11/2016] [Accepted: 11/07/2016] [Indexed: 12/28/2022]
Abstract
Many enzymes contain tunnels and gates that are essential to their function. Gates reversibly switch between open and closed conformations and thereby control the traffic of small molecules-substrates, products, ions, and solvent molecules-into and out of the enzyme's structure via molecular tunnels. Many transient tunnels and gates undoubtedly remain to be identified, and their functional roles and utility as potential drug targets have received comparatively little attention. Here, we describe a set of general concepts relating to the structural properties, function, and classification of these interesting structural features. In addition, we highlight the potential of enzyme tunnels and gates as targets for the binding of small molecules. The different types of binding that are possible and the potential pharmacological benefits of such targeting are discussed. Twelve examples of ligands bound to the tunnels and/or gates of clinically relevant enzymes are used to illustrate the different binding modes and to explain some new strategies for drug design. Such strategies could potentially help to overcome some of the problems facing medicinal chemists and lead to the discovery of more effective drugs.
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Affiliation(s)
- Sergio M Marques
- Loschmidt Laboratories, Faculty of Science, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, RECETOX, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic
| | - Lukas Daniel
- Loschmidt Laboratories, Faculty of Science, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, RECETOX, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic.,International Centre for Clinical Research, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic
| | - Tomas Buryska
- Loschmidt Laboratories, Faculty of Science, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, RECETOX, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic.,International Centre for Clinical Research, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic
| | - Zbynek Prokop
- Loschmidt Laboratories, Faculty of Science, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, RECETOX, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic.,International Centre for Clinical Research, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic
| | - Jan Brezovsky
- Loschmidt Laboratories, Faculty of Science, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, RECETOX, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic.,International Centre for Clinical Research, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic
| | - Jiri Damborsky
- Loschmidt Laboratories, Faculty of Science, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, RECETOX, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic.,International Centre for Clinical Research, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic
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26
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Nguyen DD, Wei GW. The impact of surface area, volume, curvature, and Lennard-Jones potential to solvation modeling. J Comput Chem 2016; 38:24-36. [PMID: 27718270 DOI: 10.1002/jcc.24512] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2016] [Revised: 08/17/2016] [Accepted: 08/30/2016] [Indexed: 12/24/2022]
Abstract
This article explores the impact of surface area, volume, curvature, and Lennard-Jones (LJ) potential on solvation free energy predictions. Rigidity surfaces are utilized to generate robust analytical expressions for maximum, minimum, mean, and Gaussian curvatures of solvent-solute interfaces, and define a generalized Poisson-Boltzmann (GPB) equation with a smooth dielectric profile. Extensive correlation analysis is performed to examine the linear dependence of surface area, surface enclosed volume, maximum curvature, minimum curvature, mean curvature, and Gaussian curvature for solvation modeling. It is found that surface area and surfaces enclosed volumes are highly correlated to each other's, and poorly correlated to various curvatures for six test sets of molecules. Different curvatures are weakly correlated to each other for six test sets of molecules, but are strongly correlated to each other within each test set of molecules. Based on correlation analysis, we construct twenty six nontrivial nonpolar solvation models. Our numerical results reveal that the LJ potential plays a vital role in nonpolar solvation modeling, especially for molecules involving strong van der Waals interactions. It is found that curvatures are at least as important as surface area or surface enclosed volume in nonpolar solvation modeling. In conjugation with the GPB model, various curvature-based nonpolar solvation models are shown to offer some of the best solvation free energy predictions for a wide range of test sets. For example, root mean square errors from a model constituting surface area, volume, mean curvature, and LJ potential are less than 0.42 kcal/mol for all test sets. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Duc D Nguyen
- Department of Mathematics, Michigan State University, Michigan, 48824
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, Michigan, 48824.,Department of Electrical and Computer Engineering, Michigan State University, Michigan, 48824.,Department of Biochemistry and Molecular Biology, Michigan State University, Michigan, 48824
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27
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Xia K, Opron K, Wei GW. Multiscale Gaussian network model (mGNM) and multiscale anisotropic network model (mANM). J Chem Phys 2016; 143:204106. [PMID: 26627949 DOI: 10.1063/1.4936132] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Gaussian network model (GNM) and anisotropic network model (ANM) are some of the most popular methods for the study of protein flexibility and related functions. In this work, we propose generalized GNM (gGNM) and ANM methods and show that the GNM Kirchhoff matrix can be built from the ideal low-pass filter, which is a special case of a wide class of correlation functions underpinning the linear scaling flexibility-rigidity index (FRI) method. Based on the mathematical structure of correlation functions, we propose a unified framework to construct generalized Kirchhoff matrices whose matrix inverse leads to gGNMs, whereas, the direct inverse of its diagonal elements gives rise to FRI method. With this connection, we further introduce two multiscale elastic network models, namely, multiscale GNM (mGNM) and multiscale ANM (mANM), which are able to incorporate different scales into the generalized Kirchhoff matrices or generalized Hessian matrices. We validate our new multiscale methods with extensive numerical experiments. We illustrate that gGNMs outperform the original GNM method in the B-factor prediction of a set of 364 proteins. We demonstrate that for a given correlation function, FRI and gGNM methods provide essentially identical B-factor predictions when the scale value in the correlation function is sufficiently large. More importantly, we reveal intrinsic multiscale behavior in protein structures. The proposed mGNM and mANM are able to capture this multiscale behavior and thus give rise to a significant improvement of more than 11% in B-factor predictions over the original GNM and ANM methods. We further demonstrate the benefits of our mGNM through the B-factor predictions of many proteins that fail the original GNM method. We show that the proposed mGNM can also be used to analyze protein domain separations. Finally, we showcase the ability of our mANM for the analysis of protein collective motions.
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Affiliation(s)
- Kelin Xia
- Department of Mathematics, Michigan State University, East Lansing, Michigan 48824, USA
| | - Kristopher Opron
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824, USA
| | - Guo-Wei Wei
- Mathematical Biosciences Institute, The Ohio State University, Columbus, Ohio 43210, USA
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28
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Ferreira LG, Oliva G, Andricopulo AD. Protein-protein interaction inhibitors: advances in anticancer drug design. Expert Opin Drug Discov 2016; 11:957-68. [DOI: 10.1080/17460441.2016.1223038] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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29
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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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30
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Kmiecik S, Gront D, Kolinski M, Wieteska L, Dawid AE, Kolinski A. Coarse-Grained Protein Models and Their Applications. Chem Rev 2016; 116:7898-936. [DOI: 10.1021/acs.chemrev.6b00163] [Citation(s) in RCA: 555] [Impact Index Per Article: 69.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Sebastian Kmiecik
- Faculty
of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
| | - Dominik Gront
- Faculty
of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
| | - Michal Kolinski
- Bioinformatics
Laboratory, Mossakowski Medical Research Center of the Polish Academy of Sciences, Pawinskiego 5, 02-106 Warsaw, Poland
| | - Lukasz Wieteska
- Faculty
of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
- Department
of Medical Biochemistry, Medical University of Lodz, Mazowiecka 6/8, 92-215 Lodz, Poland
| | | | - Andrzej Kolinski
- Faculty
of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
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31
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Gagnon JK, Law SM, Brooks CL. Flexible CDOCKER: Development and application of a pseudo-explicit structure-based docking method within CHARMM. J Comput Chem 2016; 37:753-62. [PMID: 26691274 PMCID: PMC4776757 DOI: 10.1002/jcc.24259] [Citation(s) in RCA: 75] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2015] [Revised: 10/21/2015] [Accepted: 10/23/2015] [Indexed: 01/14/2023]
Abstract
Protein-ligand docking is a commonly used method for lead identification and refinement. While traditional structure-based docking methods represent the receptor as a rigid body, recent developments have been moving toward the inclusion of protein flexibility. Proteins exist in an interconverting ensemble of conformational states, but effectively and efficiently searching the conformational space available to both the receptor and ligand remains a well-appreciated computational challenge. To this end, we have developed the Flexible CDOCKER method as an extension of the family of complete docking solutions available within CHARMM. This method integrates atomically detailed side chain flexibility with grid-based docking methods, maintaining efficiency while allowing the protein and ligand configurations to explore their conformational space simultaneously. This is in contrast to existing approaches that use induced-fit like sampling, such as Glide or Autodock, where the protein or the ligand space is sampled independently in an iterative fashion. Presented here are developments to the CHARMM docking methodology to incorporate receptor flexibility and improvements to the sampling protocol as demonstrated with re-docking trials on a subset of the CCDC/Astex set. These developments within CDOCKER achieve docking accuracy competitive with or exceeding the performance of other widely utilized docking programs.
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Affiliation(s)
- Jessica K. Gagnon
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan
| | - Sean M. Law
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan
| | - Charles L. Brooks
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan, Fax: 734-647-1604
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32
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Mahita J, Harini K, Rao Pichika M, Sowdhamini R. An in silico approach towards the identification of novel inhibitors of the TLR-4 signaling pathway. J Biomol Struct Dyn 2015; 34:1345-62. [PMID: 26264972 DOI: 10.1080/07391102.2015.1079243] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Precise functioning and fine-tuning of Toll-like receptor 4 (TLR4) signaling is a critical requirement for the smooth functioning of the innate immune system, since aberrant TLR4 activation causes excessive production of pro-inflammatory cytokines and interferons. This can result in life threatening conditions such as septic shock and other inflammatory disorders. The TRIF-related adaptor molecule (TRAM) adaptor protein is unique to the TLR4 signaling pathway and abrogation of TRAM-mediated TLR4 signaling is a promising strategy for developing therapeutics aimed at disrupting TRAM interactions with other components of the TLR4 signaling complex. The VIPER motif from the vaccinia virus-producing protein, A46 has been reported to disrupt TRAM-TLR4 interactions. We have exploited this information, in combination with homology modeling and docking approaches, to identify a potential binding site on TRAM lined by the BB loop and αC helix. Virtual screening of commercially available small molecules targeting the binding site enabled to short-list 12 small molecules to abrogate TRAM-mediated TLR4 signaling. Molecular dynamics and molecular mechanics calculations have been performed for the analysis of these receptor-ligand interactions.
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Affiliation(s)
- Jarjapu Mahita
- a National Centre for Biological Sciences , GKVK Campus, Bangalore , India
| | - K Harini
- a National Centre for Biological Sciences , GKVK Campus, Bangalore , India
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33
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Nechay MR, Valdez CE, Alexandrova AN. Computational Treatment of Metalloproteins. J Phys Chem B 2015; 119:5945-56. [DOI: 10.1021/acs.jpcb.5b00028] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Michael R. Nechay
- Department
of Chemistry and Biochemistry and ‡California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Crystal E. Valdez
- Department
of Chemistry and Biochemistry and ‡California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Anastassia N. Alexandrova
- Department
of Chemistry and Biochemistry and ‡California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California 90095, United States
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34
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Gerogiokas G, Southey MWY, Mazanetz MP, Hefeitz A, Bodkin M, Law RJ, Michel J. Evaluation of water displacement energetics in protein binding sites with grid cell theory. Phys Chem Chem Phys 2015; 17:8416-26. [DOI: 10.1039/c4cp05572a] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
The grid cell theory method was used to elucidate perturbations in water network energetics in a range of protein–ligand complexes.
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Affiliation(s)
| | | | | | | | | | | | - J. Michel
- EaStCHEM School of Chemistry
- Edinburgh
- UK
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35
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Alvarez-Garcia D, Barril X. Molecular Simulations with Solvent Competition Quantify Water Displaceability and Provide Accurate Interaction Maps of Protein Binding Sites. J Med Chem 2014; 57:8530-9. [DOI: 10.1021/jm5010418] [Citation(s) in RCA: 74] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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), Gran Via de les Corts Catalanes,
585, 08007 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), Gran Via de les Corts Catalanes,
585, 08007 Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Passeig Lluís Companys 23, 08010 Barcelona, Spain
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36
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Affiliation(s)
- Bettina M. Nestl
- Institute
of Technical Biochemistry, University of Stuttgart, Allmandring
31, 70569 Stuttgart, Germany
| | - Bernhard Hauer
- Institute
of Technical Biochemistry, University of Stuttgart, Allmandring
31, 70569 Stuttgart, Germany
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