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Stainbrook SC, Yu JS, Reddick MP, Bagheri N, Tyo KEJ. Modulating and evaluating receptor promiscuity through directed evolution and modeling. Protein Eng Des Sel 2017; 30:455-465. [PMID: 28453776 DOI: 10.1093/protein/gzx018] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2016] [Accepted: 04/17/2017] [Indexed: 11/13/2022] Open
Abstract
The promiscuity of G-protein-coupled receptors (GPCRs) has broad implications in disease, pharmacology and biosensing. Promiscuity is a particularly crucial consideration for protein engineering, where the ability to modulate and model promiscuity is essential for developing desirable proteins. Here, we present methodologies for (i) modifying GPCR promiscuity using directed evolution and (ii) predicting receptor response and identifying important peptide features using quantitative structure-activity relationship models and grouping-exhaustive feature selection. We apply these methodologies to the yeast pheromone receptor Ste2 and its native ligand α-factor. Using directed evolution, we created Ste2 mutants with altered specificity toward a library of α-factor variants. We then used the Vectors of Hydrophobic, Steric, and Electronic properties and partial least squares regression to characterize receptor-ligand interactions, identify important ligand positions and properties, and predict receptor response to novel ligands. Together, directed evolution and computational analysis enable the control and evaluation of GPCR promiscuity. These approaches should be broadly useful for the study and engineering of GPCRs and other protein-small molecule interactions.
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Affiliation(s)
- Sarah C Stainbrook
- Interdisciplinary Biological Sciences Program, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA
| | - Jessica S Yu
- Chemical and Biological Engineering, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA
| | - Michael P Reddick
- Chemical and Biological Engineering, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA
| | - Neda Bagheri
- Interdisciplinary Biological Sciences Program, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA.,Chemical and Biological Engineering, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA
| | - Keith E J Tyo
- Interdisciplinary Biological Sciences Program, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA.,Chemical and Biological Engineering, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA
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Fuchs JE, Wellenzohn B, Weskamp N, Liedl KR. Matched Peptides: Tuning Matched Molecular Pair Analysis for Biopharmaceutical Applications. J Chem Inf Model 2015; 55:2315-23. [PMID: 26501781 PMCID: PMC4658635 DOI: 10.1021/acs.jcim.5b00476] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
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Biopharmaceuticals hold great promise
for the future of drug discovery.
Nevertheless, rational drug design strategies are mainly focused on
the discovery of small synthetic molecules. Herein we present matched
peptides, an innovative analysis technique for biological data related
to peptide and protein sequences. It represents an extension of matched
molecular pair analysis toward macromolecular sequence data and allows
quantitative predictions of the effect of single amino acid substitutions
on the basis of statistical data on known transformations. We demonstrate
the application of matched peptides to a data set of major histocompatibility
complex class II peptide ligands and discuss the trends captured with
respect to classical quantitative structure–activity relationship
approaches as well as structural aspects of the investigated protein–peptide
interface. We expect our novel readily interpretable tool at the interface
of cheminformatics and bioinformatics to support the rational design
of biopharmaceuticals and give directions for further development
of the presented methodology.
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Affiliation(s)
- Julian E Fuchs
- Theoretical Chemistry, Faculty of Chemistry and Pharmacy, University of Innsbruck , Innrain 82, 6020 Innsbruck, Austria
| | - Bernd Wellenzohn
- Research Germany/Lead Identification and Optimization Support, Boehringer Ingelheim Pharma GmbH & Co. KG , Birkendorfer Straße 65, 88397 Biberach an der Riss, Germany
| | - Nils Weskamp
- Research Germany/Lead Identification and Optimization Support, Boehringer Ingelheim Pharma GmbH & Co. KG , Birkendorfer Straße 65, 88397 Biberach an der Riss, Germany
| | - Klaus R Liedl
- Theoretical Chemistry, Faculty of Chemistry and Pharmacy, University of Innsbruck , Innrain 82, 6020 Innsbruck, Austria
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Di Luca M, Maccari G, Nifosì R. Treatment of microbial biofilms in the post-antibiotic era: prophylactic and therapeutic use of antimicrobial peptides and their design by bioinformatics tools. Pathog Dis 2014; 70:257-70. [PMID: 24515391 DOI: 10.1111/2049-632x.12151] [Citation(s) in RCA: 65] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2013] [Revised: 01/22/2014] [Accepted: 01/30/2014] [Indexed: 12/14/2022] Open
Abstract
The treatment for biofilm infections is particularly challenging because bacteria in these conditions become refractory to antibiotic drugs. The reduced effectiveness of current therapies spurs research for the identification of novel molecules endowed with antimicrobial activities and new mechanisms of antibiofilm action. Antimicrobial peptides (AMPs) have been receiving increasing attention as potential therapeutic agents, because they represent a novel class of antibiotics with a wide spectrum of activity and a low rate in inducing bacterial resistance. Over the past decades, a large number of naturally occurring AMPs have been identified or predicted from various organisms as effector molecules of the innate immune system playing a crucial role in the first line of defense. Recent studies have shown the ability of some AMPs to act against microbial biofilms, in particular during early phases of biofilm development. Here, we provide a review of the antimicrobial peptides tested on biofilms, highlighting their advantages and disadvantages for prophylactic and therapeutic applications. In addition, we describe the strategies and methods for de novo design of potentially active AMPs and discuss how informatics and computational tools may be exploited to improve antibiofilm effectiveness.
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Borkar MR, Pissurlenkar RRS, Coutinho EC. HomoSAR: Bridging comparative protein modeling with quantitative structural activity relationship to design new peptides. J Comput Chem 2013; 34:2635-46. [DOI: 10.1002/jcc.23436] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2013] [Revised: 08/17/2013] [Accepted: 08/21/2013] [Indexed: 12/19/2022]
Affiliation(s)
- Mahesh R. Borkar
- Department of Pharmaceutical Chemistry; Bombay College of Pharmacy; Kalina, Santacruz (East) Mumbai 400098 India
| | - Raghuvir R. S. Pissurlenkar
- Department of Pharmaceutical Chemistry; Bombay College of Pharmacy; Kalina, Santacruz (East) Mumbai 400098 India
| | - Evans C. Coutinho
- Department of Pharmaceutical Chemistry; Bombay College of Pharmacy; Kalina, Santacruz (East) Mumbai 400098 India
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Pissurlenkar RRS, Khedkar VM, Iyer RP, Coutinho EC. Ensemble QSAR: a QSAR method based on conformational ensembles and metric descriptors. J Comput Chem 2011; 32:2204-18. [PMID: 21509786 DOI: 10.1002/jcc.21804] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2011] [Revised: 02/24/2011] [Accepted: 03/06/2011] [Indexed: 11/06/2022]
Abstract
Quantitative structure-activity relationship (QSAR) is the most versatile tool in computer-assisted molecular design. One conceptual drawback seen in QSAR approaches is the "one chemical-one structure-one parameter value" dogma where the model development is based on physicochemical description for a single molecular conformation, while ignoring the rest of the conformational space. It is well known that molecules have several low-energy conformations populated at physiological temperature, and each conformer makes a significant impact on associated properties such as biological activity. At the level of molecular interaction, the dynamics around the molecular structure is of prime essence rather than the average structure. As a step toward understanding the role of these discrete microscopic states in biological activity, we have put together a theoretically rigorous and computationally tractable formalism coined as eQSAR. In this approach, the biological activity is modeled as a function of physicochemical description for a selected set of low-energy conformers, rather than that's for a single lowest energy conformation. Eigenvalues derived from the "Physicochemical property integrated distance matrices" (PD-matrices) that encompass both 3D structure and physicochemical properties, have been used as descriptors; is a novel addition. eQSAR is validated on three peptide datasets and explicitly elaborated for bradykinin-potentiating peptides. The conformational ensembles were generated by a simple molecular dynamics and consensus dynamics approaches. The eQSAR models are statistically significant and possess the ability to select the most biologically relevant conformation(s) with the relevant physicochemical attributes that have the greatest meaning for description of the biological activity.
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Affiliation(s)
- Raghuvir R S Pissurlenkar
- Department of Pharmaceutical Chemistry, Bombay College of Pharmacy, Kalina, Santacruz (E), Mumbai 400098, India
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Computational medicinal chemistry in fragment-based drug discovery: what, how and when. Future Med Chem 2011; 3:95-134. [DOI: 10.4155/fmc.10.277] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
The use of fragment-based drug discovery (FBDD) has increased in the last decade due to the encouraging results obtained to date. In this scenario, computational approaches, together with experimental information, play an important role to guide and speed up the process. By default, FBDD is generally considered as a constructive approach. However, such additive behavior is not always present, therefore, simple fragment maturation will not always deliver the expected results. In this review, computational approaches utilized in FBDD are reported together with real case studies, where applicability domains are exemplified, in order to analyze them, and then, maximize their performance and reliability. Thus, a proper use of these computational tools can minimize misleading conclusions, keeping the credit on FBDD strategy, as well as achieve higher impact in the drug-discovery process. FBDD goes one step beyond a simple constructive approach. A broad set of computational tools: docking, R group quantitative structure–activity relationship, fragmentation tools, fragments management tools, patents analysis and fragment-hopping, for example, can be utilized in FBDD, providing a clear positive impact if they are utilized in the proper scenario – what, how and when. An initial assessment of additive/non-additive behavior is a critical point to define the most convenient approach for fragments elaboration.
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Zhou X, Li Z, Dai Z, Zou X. QSAR modeling of peptide biological activity by coupling support vector machine with particle swarm optimization algorithm and genetic algorithm. J Mol Graph Model 2010; 29:188-96. [DOI: 10.1016/j.jmgm.2010.06.002] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2010] [Revised: 05/26/2010] [Accepted: 06/13/2010] [Indexed: 01/04/2023]
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Padrón-García JA, Alonso-Tarajano M, Alonso-Becerra E, Winterburn TJ, Ruiz Y, Kay J, Berry C. Quantitative structure activity relationship of IA3-like peptides as aspartic proteinase inhibitors. Proteins 2009; 75:859-69. [DOI: 10.1002/prot.22295] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Assessment of Additive/Nonadditive Effects in Structure−Activity Relationships: Implications for Iterative Drug Design. J Med Chem 2008; 51:7552-62. [DOI: 10.1021/jm801070q] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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A comprehensive analysis of the thermodynamic events involved in ligand–receptor binding using CoRIA and its variants. J Comput Aided Mol Des 2008; 22:91-104. [DOI: 10.1007/s10822-008-9172-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2007] [Accepted: 01/05/2008] [Indexed: 10/22/2022]
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