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Emonts J, Buyel J. An overview of descriptors to capture protein properties - Tools and perspectives in the context of QSAR modeling. Comput Struct Biotechnol J 2023; 21:3234-3247. [PMID: 38213891 PMCID: PMC10781719 DOI: 10.1016/j.csbj.2023.05.022] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 05/23/2023] [Accepted: 05/23/2023] [Indexed: 01/13/2024] Open
Abstract
Proteins are important ingredients in food and feed, they are the active components of many pharmaceutical products, and they are necessary, in the form of enzymes, for the success of many technical processes. However, production can be challenging, especially when using heterologous host cells such as bacteria to express and assemble recombinant mammalian proteins. The manufacturability of proteins can be hindered by low solubility, a tendency to aggregate, or inefficient purification. Tools such as in silico protein engineering and models that predict separation criteria can overcome these issues but usually require the complex shape and surface properties of proteins to be represented by a small number of quantitative numeric values known as descriptors, as similarly used to capture the features of small molecules. Here, we review the current status of protein descriptors, especially for application in quantitative structure activity relationship (QSAR) models. First, we describe the complexity of proteins and the properties that descriptors must accommodate. Then we introduce descriptors of shape and surface properties that quantify the global and local features of proteins. Finally, we highlight the current limitations of protein descriptors and propose strategies for the derivation of novel protein descriptors that are more informative.
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Affiliation(s)
- J. Emonts
- Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Germany
| | - J.F. Buyel
- University of Natural Resources and Life Sciences, Vienna (BOKU), Department of Biotechnology (DBT), Institute of Bioprocess Science and Engineering (IBSE), Muthgasse 18, 1190 Vienna, Austria
- Institute for Molecular Biotechnology, Worringerweg 1, RWTH Aachen University, 52074 Aachen, Germany
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2
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Contreras-Torres E, Marrero-Ponce Y, Terán JE, Agüero-Chapin G, Antunes A, García-Jacas CR. Fuzzy spherical truncation-based multi-linear protein descriptors: From their definition to application in structural-related predictions. Front Chem 2022; 10:959143. [PMID: 36277354 PMCID: PMC9585278 DOI: 10.3389/fchem.2022.959143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 08/15/2022] [Indexed: 11/13/2022] Open
Abstract
This study introduces a set of fuzzy spherically truncated three-dimensional (3D) multi-linear descriptors for proteins. These indices codify geometric structural information from kth spherically truncated spatial-(dis)similarity two-tuple and three-tuple tensors. The coefficients of these truncated tensors are calculated by applying a smoothing value to the 3D structural encoding based on the relationships between two and three amino acids of a protein embedded into a sphere. At considering, the geometrical center of the protein matches with center of the sphere, the distance between each amino acid involved in any specific interaction and the geometrical center of the protein can be computed. Then, the fuzzy membership degree of each amino acid from an spherical region of interest is computed by fuzzy membership functions (FMFs). The truncation value is finally a combination of the membership degrees from interacting amino acids, by applying the arithmetic mean as fusion rule. Several fuzzy membership functions with diverse biases on the calculation of amino acids memberships (e.g., Z-shaped (close to the center), PI-shaped (middle region), and A-Gaussian (far from the center)) were considered as well as traditional truncation functions (e.g., Switching). Such truncation functions were comparatively evaluated by exploring: 1) the frequency of membership degrees, 2) the variability and orthogonality analyses among them based on the Shannon Entropy’s and Principal Component’s methods, respectively, and 3) the prediction performance of alignment-free prediction of protein folding rates and structural classes. These analyses unraveled the singularity of the proposed fuzzy spherically truncated MDs with respect to the classical (non-truncated) ones and respect to the MDs truncated with traditional functions. They also showed an improved prediction power by attaining an external correlation coefficient of 95.82% in the folding rate modelling and an accuracy of 100% in distinguishing structural protein classes. These outcomes are better than the ones attained by existing approaches, justifying the theoretical contribution of this report. Thus, the fuzzy spherically truncated-based protein descriptors from MuLiMs-MCoMPAs (http://tomocomd.com/mulims-mcompas) are promising alignment-free predictors for modeling protein functions and properties.
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Affiliation(s)
- Ernesto Contreras-Torres
- Grupo de Medicina Molecular y Traslacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina, Universidad San Francisco de Quito (USFQ), Quito, Pichincha, Ecuador
- Instituto de Simulación Computacional (ISC-USFQ), Quito, Pichincha, Ecuador
- BCAM—Basque Center for Applied Mathematics, Bilbao, Spain
| | - Yovani Marrero-Ponce
- Grupo de Medicina Molecular y Traslacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina, Universidad San Francisco de Quito (USFQ), Quito, Pichincha, Ecuador
- Instituto de Simulación Computacional (ISC-USFQ), Quito, Pichincha, Ecuador
- Computer-Aided Molecular “Biosilico” Discovery and Bioinformatics Research International Network (CAMD-BIR IN), Quito, Ecuador
- *Correspondence: Yovani Marrero-Ponce, , , César R. García-Jacas, , ,
| | - Julio E. Terán
- Grupo de Medicina Molecular y Traslacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina, Universidad San Francisco de Quito (USFQ), Quito, Pichincha, Ecuador
- Instituto de Simulación Computacional (ISC-USFQ), Quito, Pichincha, Ecuador
- Department of Textile Engineering, Chemistry and Science, College of Textiles, North Carolina State University, Raleigh, NC, United States
| | - Guillermin Agüero-Chapin
- CIIMAR—Centro Interdisciplinar de Investigação Marinha e Ambiental, Universidade do Porto, Porto, Portugal
- Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto, Portugal
| | - Agostinho Antunes
- CIIMAR—Centro Interdisciplinar de Investigação Marinha e Ambiental, Universidade do Porto, Porto, Portugal
- Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto, Portugal
| | - César R. García-Jacas
- Cátedras Conacyt—Departamento de Ciencias de la Computación, Centro de Investigación Científica y de Educación Superior de Ensenada (CICESE), Ensenada, Baja California, Mexico
- *Correspondence: Yovani Marrero-Ponce, , , César R. García-Jacas, , ,
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3
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Contreras-Torres E, Marrero-Ponce Y, Terán JE, García-Jacas CR, Brizuela CA, Sánchez-Rodríguez JC. MuLiMs-MCoMPAs: A Novel Multiplatform Framework to Compute Tensor Algebra-Based Three-Dimensional Protein Descriptors. J Chem Inf Model 2020; 60:1042-1059. [PMID: 31663741 DOI: 10.1021/acs.jcim.9b00629] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
This report introduces the MuLiMs-MCoMPAs software (acronym for Multi-Linear Maps based on N-Metric and Contact Matrices of 3D Protein and Amino-acid weightings), designed to compute tensor-based 3D protein structural descriptors by applying two- and three-linear algebraic forms. Moreover, these descriptors contemplate generalizing components such as novel 3D protein structural representations, (dis)similarity metrics, and multimetrics to extract geometrical related information between two and three amino acids, weighting schemes based on amino acid properties, matrix normalization procedures that consider simple-stochastic and mutual probability transformations, topological and geometrical cutoffs, amino acid, and group-based MD calculations, and aggregation operators for merging amino acidic and group MDs. The MuLiMs-MCoMPAs software, which belongs to the ToMoCoMD-CAMPS suite, was developed in Java (version 1.8) using the Chemistry Development Kit (CDK) (version 1.4.19) and the Jmol libraries. This software implemented a divide-and-conquer strategy to parallelize the computation of the indices as well as modules for data preprocessing and batch computing functionalities. Furthermore, it consists of two components: (i) a desktop-graphical user interface (GUI) and (ii) an API library. The relevance of this novel approach is demonstrated through two analyses that considered Shannon's entropy-based variability and a principal component analysis. These studies showed that the MuLiMs-MCoMPAs' three-linear descriptor family contains higher informational entropy than several other descriptors generated with available computation tools. Moreover, the MuLiMs-MCoMPAs indices capture additional orthogonal information to the one codified by the available calculation approaches. As a result, two sets of suggested theoretical configurations that contain 13648 two-linear indices and 20263 three-linear indices are available for download at tomocomd.com . Furthermore, as a demonstration of the applicability and easy integration of the MuLiMs library into a QSAR-based expert system, a software application (ProStAF) was generated to predict SCOP protein structural classes and folding rate. It can thus be anticipated that the MuLiMs-MCoMPAs framework will turn into a valuable contribution to the chem- and bioinformatics research fields.
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Affiliation(s)
- Ernesto Contreras-Torres
- Computer-Aided Molecular "Biosilico" Discovery and Bioinformatics Research International Network (CAMD-BIR IN) , Cumbayá, Quito , Ecuador.,Grupo de Medicina Molecular y Traslacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina, Edificio de Especialidades Médicas; and Instituto de Simulación Computacional (ISC-USFQ) , Universidad San Francisco de Quito (USFQ) , Diego de Robles y vía Interoceánica , Quito 170157 , Pichincha , Ecuador
| | - Yovani Marrero-Ponce
- Grupo de Medicina Molecular y Traslacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina, Edificio de Especialidades Médicas; and Instituto de Simulación Computacional (ISC-USFQ) , Universidad San Francisco de Quito (USFQ) , Diego de Robles y vía Interoceánica , Quito 170157 , Pichincha , Ecuador.,Grupo GINUMED, Facultad de Salud, Programa de Medicina , Corporacion Universitaria Rafal Nuñez , Cartagena , Colombia.,Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Departamento de Química Física, Facultad de Farmacia , Universitat de València , 46010 Valéncia , Spain
| | - Julio E Terán
- Grupo de Medicina Molecular y Traslacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina, Edificio de Especialidades Médicas; and Instituto de Simulación Computacional (ISC-USFQ) , Universidad San Francisco de Quito (USFQ) , Diego de Robles y vía Interoceánica , Quito 170157 , Pichincha , Ecuador.,Grupo de Química Computacional y Teórica, Departamento de Ingeniería Química , Universidad San Francisco de Quito (USFQ) , Diego de Robles y vía Interoceánica , Quito 170157 , Pichincha Ecuador
| | - César R García-Jacas
- Cátedras Conacyt-Departamento de Ciencias de la Computación , Centro de Investigación Científica y de Educación Superior de Ensenada (CICESE) , Ensenada , Baja California , México
| | - Carlos A Brizuela
- Departamento de Ciencias de la Computación , Centro de Investigación Científica y de Educación Superior de Ensenada (CICESE) , Ensenada , Baja California , México
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4
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Marrero-Ponce Y, Teran JE, Contreras-Torres E, García-Jacas CR, Perez-Castillo Y, Cubillan N, Peréz-Giménez F, Valdés-Martini JR. LEGO-based generalized set of two linear algebraic 3D bio-macro-molecular descriptors: Theory and validation by QSARs. J Theor Biol 2020; 485:110039. [DOI: 10.1016/j.jtbi.2019.110039] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2019] [Revised: 09/11/2019] [Accepted: 10/02/2019] [Indexed: 11/28/2022]
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5
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Agüero-Chapin G, Galpert D, Molina-Ruiz R, Ancede-Gallardo E, Pérez-Machado G, De la Riva GA, Antunes A. Graph Theory-Based Sequence Descriptors as Remote Homology Predictors. Biomolecules 2019; 10:E26. [PMID: 31878100 PMCID: PMC7022958 DOI: 10.3390/biom10010026] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 12/16/2019] [Accepted: 12/18/2019] [Indexed: 12/23/2022] Open
Abstract
Alignment-free (AF) methodologies have increased in popularity in the last decades as alternative tools to alignment-based (AB) algorithms for performing comparative sequence analyses. They have been especially useful to detect remote homologs within the twilight zone of highly diverse gene/protein families and superfamilies. The most popular alignment-free methodologies, as well as their applications to classification problems, have been described in previous reviews. Despite a new set of graph theory-derived sequence/structural descriptors that have been gaining relevance in the detection of remote homology, they have been omitted as AF predictors when the topic is addressed. Here, we first go over the most popular AF approaches used for detecting homology signals within the twilight zone and then bring out the state-of-the-art tools encoding graph theory-derived sequence/structure descriptors and their success for identifying remote homologs. We also highlight the tendency of integrating AF features/measures with the AB ones, either into the same prediction model or by assembling the predictions from different algorithms using voting/weighting strategies, for improving the detection of remote signals. Lastly, we briefly discuss the efforts made to scale up AB and AF features/measures for the comparison of multiple genomes and proteomes. Alongside the achieved experiences in remote homology detection by both the most popular AF tools and other less known ones, we provide our own using the graphical-numerical methodologies, MARCH-INSIDE, TI2BioP, and ProtDCal. We also present a new Python-based tool (SeqDivA) with a friendly graphical user interface (GUI) for delimiting the twilight zone by using several similar criteria.
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Affiliation(s)
- Guillermin Agüero-Chapin
- CIIMAR/CIMAR, Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Terminal de Cruzeiros do Porto de Leixões, Av. General Norton de Matos s/n 4450-208 Porto, Portugal
- Department of Biology, Faculty of Sciences, University of Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal
| | - Deborah Galpert
- Departamento de Ciencia de la Computación. Universidad Central ¨Marta Abreu¨ de Las Villas (UCLV), Santa Clara 54830, Cuba;
| | - Reinaldo Molina-Ruiz
- Centro de Bioactivos Químicos (CBQ), Universidad Central ¨Marta Abreu¨ de Las Villas (UCLV), Santa Clara 54830, Cuba;
| | - Evys Ancede-Gallardo
- Programa de Doctorado en Fisicoquímica Molecular, Facultad de Ciencias Exactas, Universidad Andrés Bello, Av. República 239, Santiago 8370146, Chile;
| | - Gisselle Pérez-Machado
- EpiDisease S.L. Spin-Off of Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), 46980 Valencia, Spain;
| | - Gustavo A. De la Riva
- Laboratorio de Biotecnología Aplicada S. de R.L. de C.V., GRECA Inc., Carretera La Piedad-Carapán, km 3.5, La Piedad, Michoacán 59300, Mexico;
- Tecnológico Nacional de México, Instituto Tecnológico de la Piedad, Av. Ricardo Guzmán Romero, Santa Fe, La Piedad de Cavadas, Michoacán 59370, Mexico
| | - Agostinho Antunes
- CIIMAR/CIMAR, Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Terminal de Cruzeiros do Porto de Leixões, Av. General Norton de Matos s/n 4450-208 Porto, Portugal
- Department of Biology, Faculty of Sciences, University of Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal
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6
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Terán JE, Marrero-Ponce Y, Contreras-Torres E, García-Jacas CR, Vivas-Reyes R, Terán E, Torres FJ. Tensor Algebra-based Geometrical (3D) Biomacro-Molecular Descriptors for Protein Research: Theory, Applications and Comparison with other Methods. Sci Rep 2019; 9:11391. [PMID: 31388082 PMCID: PMC6684663 DOI: 10.1038/s41598-019-47858-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Accepted: 07/22/2019] [Indexed: 11/16/2022] Open
Abstract
In this report, a new type of tridimensional (3D) biomacro-molecular descriptors for proteins are proposed. These descriptors make use of multi-linear algebra concepts based on the application of 3-linear forms (i.e., Canonical Trilinear (Tr), Trilinear Cubic (TrC), Trilinear-Quadratic-Bilinear (TrQB) and so on) as a specific case of the N-linear algebraic forms. The definition of the kth 3-tuple similarity-dissimilarity spatial matrices (Tensor's Form) are used for the transformation and for the representation of the existing chemical information available in the relationships between three amino acids of a protein. Several metrics (Minkowski-type, wave-edge, etc) and multi-metrics (Triangle area, Bond-angle, etc) are proposed for the interaction information extraction, as well as probabilistic transformations (e.g., simple stochastic and mutual probability) to achieve matrix normalization. A generalized procedure considering amino acid level-based indices that can be fused together by using aggregator operators for descriptors calculations is proposed. The obtained results demonstrated that the new proposed 3D biomacro-molecular indices perform better than other approaches in the SCOP-based discrimination and the prediction of folding rate of proteins by using simple linear parametrical models. It can be concluded that the proposed method allows the definition of 3D biomacro-molecular descriptors that contain orthogonal information capable of providing better models for applications in protein science.
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Affiliation(s)
- Julio E Terán
- Universidad San Francisco de Quito (USFQ), Grupo de Medicina Molecular y Translacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina, Edificio de Especialidades Médicas, Quito, Pichincha, Ecuador
- Universidad San Francisco de Quito (USFQ), Grupo de Química Computacional y Teórica (QCT-USFQ), Departamento de Ingeniería Química, and Instituto de Simulación Computacional (ISC-USFQ), Quito, Pichincha, Ecuador
| | - Yovani Marrero-Ponce
- Universidad San Francisco de Quito (USFQ), Grupo de Medicina Molecular y Translacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina, Edificio de Especialidades Médicas, Quito, Pichincha, Ecuador.
- Universidad de San Buenaventura - Cartagena - Facultad de Ciencias de la Salud - Grupo de Investigación Microbiología & Ambiente (GIMA) - Calle Real de Ternera, Diagonal 32, No. 30-966, Cartagena, Código postal: 1300 10, Colombia.
| | - Ernesto Contreras-Torres
- Universidad San Francisco de Quito (USFQ), Grupo de Medicina Molecular y Translacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina, Edificio de Especialidades Médicas, Quito, Pichincha, Ecuador
| | - César R García-Jacas
- Cátedras CONACYT - Departamento de Ciencia de la Computación, Centro de Investigación Científica y de Educación Superior de Ensenada (CICESE), Ensenada, Baja California, Mexico
| | - Ricardo Vivas-Reyes
- Grupo de Química Cuántica y Teórica de la Universidad de Cartagena-Facultad de Ciencias Exactas y Naturales. Programa de Química. Campus de San Pablo and Grupo GINUMED Corporacion Universitaria Rafal Nuñez. Facultad de Salud. Programa de Medicina., Cartagena, Colombia
- Grupo CipTec, Facultad de Ingenierias. Fundacion Universitaria Tecnologico Comfenalco - Cartagena, Cartagena, Bolívar, Colombia
| | - Enrique Terán
- Universidad San Francisco de Quito (USFQ), Grupo de Medicina Molecular y Translacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina, Edificio de Especialidades Médicas, Quito, Pichincha, Ecuador
| | - F Javier Torres
- Universidad San Francisco de Quito (USFQ), Grupo de Química Computacional y Teórica (QCT-USFQ), Departamento de Ingeniería Química, and Instituto de Simulación Computacional (ISC-USFQ), Quito, Pichincha, Ecuador
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Hafezi Z, Arefi MM. Recursive generalized extended least squares and RML algorithms for identification of bilinear systems with ARMA noise. ISA TRANSACTIONS 2019; 88:50-61. [PMID: 30580882 DOI: 10.1016/j.isatra.2018.12.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2018] [Revised: 11/24/2018] [Accepted: 12/07/2018] [Indexed: 06/09/2023]
Abstract
Bilinear systems are considered as a particular class of nonlinear systems including the state variables which are typically used for online identification. By using a recursive identification method and the maximum likelihood principle, this paper presents two recursive-based algorithms to identify the parameters of bilinear in parameter systems with ARMA noise. In this regard, recursive generalized extended least squares (RGELS) and recursive Maximum Likelihood (RML) algorithms have been proposed for identification of bilinear systems. These algorithms can be used as an alternative choice in system identification with acceptable performance. The proposed algorithms estimate the correlated noise parameters with high accuracy by making full use of the measurement data. Simulation results indicate that the proposed algorithms are effective for online identification of bilinear in parameter systems with high convergence speed.
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Affiliation(s)
- Zahra Hafezi
- Department of Power and Control Engineering, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.
| | - Mohammad Mehdi Arefi
- Department of Power and Control Engineering, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.
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Grisoni F, Merk D, Byrne R, Schneider G. Scaffold-Hopping from Synthetic Drugs by Holistic Molecular Representation. Sci Rep 2018; 8:16469. [PMID: 30405170 PMCID: PMC6220272 DOI: 10.1038/s41598-018-34677-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Accepted: 10/16/2018] [Indexed: 12/31/2022] Open
Abstract
The discovery of novel ligand chemotypes allows to explore uncharted regions in chemical space, thereby potentially improving synthetic accessibility, potency, and the drug-likeness of molecules. Here, we demonstrate the scaffold-hopping ability of the new Weighted Holistic Atom Localization and Entity Shape (WHALES) molecular descriptors compared to seven state-of-the-art molecular representations on 30,000 compounds and 182 biological targets. In a prospective application, we apply WHALES to the discovery of novel retinoid X receptor (RXR) modulators. WHALES descriptors identified four agonists with innovative molecular scaffolds, populating uncharted regions of the chemical space. One of the agonists, possessing a rare non-acidic chemotype, revealed high selectivity on 12 nuclear receptors and comparable efficacy as bexarotene on induction of ATP-binding cassette transporter A1, angiopoietin like protein 4 and apolipoprotein E. The outcome of this research supports WHALES as an innovative tool to explore novel regions of the chemical space and to detect novel bioactive chemotypes by straightforward similarity searching.
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Affiliation(s)
- Francesca Grisoni
- Swiss Federal Institute of Technology (ETH), Department of Chemistry and Applied Biosciences, Vladimir-Prelog-Weg 4, CH-8093, Zurich, Switzerland. .,Milano Chemometrics & QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, IT-20126, Milano, Italy.
| | - Daniel Merk
- Swiss Federal Institute of Technology (ETH), Department of Chemistry and Applied Biosciences, Vladimir-Prelog-Weg 4, CH-8093, Zurich, Switzerland
| | - Ryan Byrne
- Swiss Federal Institute of Technology (ETH), Department of Chemistry and Applied Biosciences, Vladimir-Prelog-Weg 4, CH-8093, Zurich, Switzerland
| | - Gisbert Schneider
- Swiss Federal Institute of Technology (ETH), Department of Chemistry and Applied Biosciences, Vladimir-Prelog-Weg 4, CH-8093, Zurich, Switzerland.
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9
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Contreras-Torres E. Predicting structural classes of proteins by incorporating their global and local physicochemical and conformational properties into general Chou's PseAAC. J Theor Biol 2018; 454:139-145. [DOI: 10.1016/j.jtbi.2018.05.033] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2018] [Revised: 05/23/2018] [Accepted: 05/28/2018] [Indexed: 11/24/2022]
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10
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García-Jacas CR, Cabrera-Leyva L, Marrero-Ponce Y, Suárez-Lezcano J, Cortés-Guzmán F, García-González LA. GOWAWA Aggregation Operator-based Global Molecular Characterizations: Weighting Atom/bond Contributions (LOVIs/LOEIs) According to their Influence in the Molecular Encoding. Mol Inform 2018; 37:e1800039. [PMID: 30070434 DOI: 10.1002/minf.201800039] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2018] [Accepted: 07/13/2018] [Indexed: 11/11/2022]
Abstract
A different perspective to compute global weighted definitions of molecular descriptors from the contributions of each atom (LOVIs) or covalent bond (LOEIs) within a molecule is presented, using the generalized ordered weighted averaging - weighted averaging (GOWAWA) aggregation operator. This operator is rather different from the other norm-, mean- and statistic-based operators used up to date for the descriptors calculation from LOVIs/LOEIs. GOWAWA unifies the generalized ordered weighted averaging (GOWA) and the weighted generalized mean (WGM) functions and, in addition, it uses a smoothing parameter to assign different importance values to both functions depending on the problem under study. With the GOWAWA operator, diversity of novel global aggregations of molecular descriptors can be determined, where the influence that each atom (or covalent bond) has on the molecular characterization is taken into account. Therefore, this approach is completely different from the ones reported in the literature, where the values of LOVIs/LOEIs are considered equally important. To demonstrate the feasibility of using this operator, the QuBiLS-MIDAS descriptors (http://tomocomd.com/qubils-midas) were used and, as a result, a module was built into the corresponding software to compute them, being thus the only software reported in the literature that can be employed to determine weighted descriptors. Moreover, several modeling studies were performed on eight chemical datasets, which demonstrated that, with the GOWAWA aggregation operator, weighted QuBiLS-MIDAS descriptors that contribute to develop models with greater predictive power can be computed, if compared to the models based on the non-weighted descriptors calculated from the other operators used up to date. A non-parametric statistical assessment confirmed that the GOWAWA-based predictions are significantly superior to the others obtained. Therefore, all in all, it can be concluded that, from the results achieved, the GOWAWA operator constitutes a prominent alternative to codify relevant chemical information of the molecules, ultimately useful in improving the modeling ability of several old and recent descriptors whose definition is based on the LOVIs/LOEIs calculation.
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Affiliation(s)
- César R García-Jacas
- Instituto de Química, Universidad Nacional Autónoma de México (UNAM), Ciudad de México, México
| | - Lisset Cabrera-Leyva
- Grupo de Investigación de Inteligencia Artificial (AIRES), Facultad de Informática, Universidad de Camagüey, Camagüey, Cuba
| | - Yovani Marrero-Ponce
- Universidad San Francisco de Quito (USFQ), Grupo de Medicina Molecular y Traslacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina, Edificio de Especialidades Médicas, Quito, Pichincha, Ecuador.,Grupo de Investigación Ambiental (GIA), Programas Ambientales, Facultad de Ingenierías, Fundación Universitaria Tecnológico de Comfenalco (COMFENALCO), Cartagena de Indias, Bolívar, Colombia
| | - José Suárez-Lezcano
- Pontificia Universidad Católica del Ecuador Sede Esmeraldas (PUCESE), Esmeraldas, Ecuador
| | - Fernando Cortés-Guzmán
- Instituto de Química, Universidad Nacional Autónoma de México (UNAM), Ciudad de México, México
| | - Luis A García-González
- Grupo de Investigación de Bioinformática, Universidad de las Ciencias Informáticas (UCI), La Habana, Cuba
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Yu B, Lou L, Li S, Zhang Y, Qiu W, Wu X, Wang M, Tian B. Prediction of protein structural class for low-similarity sequences using Chou’s pseudo amino acid composition and wavelet denoising. J Mol Graph Model 2017; 76:260-273. [DOI: 10.1016/j.jmgm.2017.07.012] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2017] [Revised: 07/11/2017] [Accepted: 07/12/2017] [Indexed: 11/25/2022]
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12
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Simeon S, Li H, Win TS, Malik AA, Kandhro AH, Piacham T, Shoombuatong W, Nuchnoi P, Wikberg JES, Gleeson MP, Nantasenamat C. PepBio: predicting the bioactivity of host defense peptides. RSC Adv 2017. [DOI: 10.1039/c7ra01388d] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
A large-scale QSAR study of host defense peptides sheds light on the origin of their bioactivities (antibacterial, anticancer, antiviral and antifungal).
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13
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García-Jacas CR, Marrero-Ponce Y, Barigye SJ, Hernández-Ortega T, Cabrera-Leyva L, Fernández-Castillo A. N-tuple topological/geometric cutoffs for 3D N-linear algebraic molecular codifications: variability, linear independence and QSAR analysis. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2016; 27:949-975. [PMID: 27707004 DOI: 10.1080/1062936x.2016.1231714] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2016] [Accepted: 08/30/2016] [Indexed: 06/06/2023]
Abstract
Novel N-tuple topological/geometric cutoffs to consider specific inter-atomic relations in the QuBiLS-MIDAS framework are introduced in this manuscript. These molecular cutoffs permit the taking into account of relations between more than two atoms by using (dis-)similarity multi-metrics and the concepts related with topological and Euclidean-geometric distances. To this end, the kth two-, three- and four-tuple topological and geometric neighbourhood quotient (NQ) total (or local-fragment) spatial-(dis)similarity matrices are defined, to represent 3D information corresponding to the relations between two, three and four atoms of the molecular structures that satisfy certain cutoff criteria. First, an analysis of a diverse chemical space for the most common values of topological/Euclidean-geometric distances, bond/dihedral angles, triangle/quadrilateral perimeters, triangle area and volume was performed in order to determine the intervals to take into account in the cutoff procedures. A variability analysis based on Shannon's entropy reveals that better distribution patterns are attained with the descriptors based on the cutoffs proposed (QuBiLS-MIDAS NQ-MDs) with regard to the results obtained when all inter-atomic relations are considered (QuBiLS-MIDAS KA-MDs - 'Keep All'). A principal component analysis shows that the novel molecular cutoffs codify chemical information captured by the respective QuBiLS-MIDAS KA-MDs, as well as information not captured by the latter. Lastly, a QSAR study to obtain deeper knowledge of the contribution of the proposed methods was carried out, using four molecular datasets (steroids (STER), angiotensin converting enzyme (ACE), thermolysin inhibitors (THER) and thrombin inhibitors (THR)) widely used as benchmarks in the evaluation of several methodologies. One to four variable QSAR models based on multiple linear regression were developed for each compound dataset following the original division into training and test sets. The results obtained reveal that the novel cutoff procedures yield superior performances relative to those of the QuBiLS-MIDAS KA-MDs in the prediction of the biological activities considered. From the results achieved, it can be suggested that the proposed N-tuple topological/geometric cutoffs constitute a relevant criteria for generating MDs codifying particular atomic relations, ultimately useful in enhancing the modelling capacity of the QuBiLS-MIDAS 3D-MDs.
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Affiliation(s)
- C R García-Jacas
- a Escuela de Sistemas y Computación , Pontificia Universidad Católica del Ecuador Sede Esmeraldas (PUCESE) , Esmeraldas , Ecuador
- b Grupo de Investigación de Bioinformática , Instituto de Química, Universidad Nacional Autónoma de México (UNAM) , Ciudad de México , D.F, México
- c Grupo de Investigacion de Bioinformatica , Universidad de las Ciencias Informaticas (UCI) , La Habana , Cuba
| | - Y Marrero-Ponce
- d Grupo de Medicina Molecular y Traslacional (MeM&T) , Universidad San Francisco de Quito (USFQ) , Quito , Ecuador
- e Instituto de Simulación Computacional (ISC-USFQ), Universidad San Francisco de Quito (USFQ) , Quito , Ecuador
| | - S J Barigye
- g Department of Chemistry , McGill University , Montréal , Québec , Canada
| | - T Hernández-Ortega
- c Grupo de Investigacion de Bioinformatica , Universidad de las Ciencias Informaticas (UCI) , La Habana , Cuba
| | - L Cabrera-Leyva
- f Grupo de Investigación de Inteligencia Artificial (AIRES) , Universidad de Camagüey , Camagüey , Cuba
| | - A Fernández-Castillo
- c Grupo de Investigacion de Bioinformatica , Universidad de las Ciencias Informaticas (UCI) , La Habana , Cuba
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Muranyi IS, Volke D, Hoffmann R, Eisner P, Herfellner T, Brunnbauer M, Koehler P, Schweiggert-Weisz U. Protein distribution in lupin protein isolates from Lupinus angustifolius L. prepared by various isolation techniques. Food Chem 2016; 207:6-15. [PMID: 27080873 DOI: 10.1016/j.foodchem.2016.03.073] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2015] [Revised: 03/04/2016] [Accepted: 03/21/2016] [Indexed: 10/22/2022]
Abstract
Differences in the protein distribution of various protein isolates from Lupinus angustifolius L. Vitabor were identified as affected by the isolation procedure (alkaline and/or salt-induced extraction followed by isoelectric and/or dilutive precipitation). Protein isolates extracted in alkaline solution showed higher protein yields (26.4-31.7%) compared to salt-induced extraction (19.8-30.0%) or combined alkaline and salt-induced extraction (23.3-25.6%). Chemical variations among the protein isolates especially occurred within the albumins. Protein isolates precipitated isoelectrically showed the highest contents, whereas protein isolates precipitated by dilutive showed the lowest contents of conglutin δ. Furthermore, the alkaline subunits of conglutin α and conglutin γ decreased during alkaline extraction compared to salt-induced extraction. A decrease in protein-bound polar and basic amino acids was shown after protein isolation. In contrast, the amounts of nonpolar, aliphatic, aromatic, hydroxylated and sulfur-rich amino acids were higher in the lupin protein isolates compared to the lupin flakes. However, the functional side chains could not be related to the specific molecular arrangements of the protein isolates, as a similar amino acid composition was found among the protein isolates.
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Affiliation(s)
- Isabel S Muranyi
- Fraunhofer Institute for Process Engineering and Packaging (IVV), Giggenhauser Strasse 35, D-85354 Freising, Germany.
| | - Daniela Volke
- Center for Biotechnology and Biomedicine, Faculty of Chemistry and Mineralogy, University Leipzig, Deutscher Platz 5, D-04103 Leipzig, Germany
| | - Ralf Hoffmann
- Center for Biotechnology and Biomedicine, Faculty of Chemistry and Mineralogy, University Leipzig, Deutscher Platz 5, D-04103 Leipzig, Germany
| | - Peter Eisner
- Fraunhofer Institute for Process Engineering and Packaging (IVV), Giggenhauser Strasse 35, D-85354 Freising, Germany
| | - Thomas Herfellner
- Fraunhofer Institute for Process Engineering and Packaging (IVV), Giggenhauser Strasse 35, D-85354 Freising, Germany
| | - Markus Brunnbauer
- German Research Centre for Food Chemistry, Lise-Meitner-Strasse 34, D-85354 Freising, Germany
| | - Peter Koehler
- German Research Centre for Food Chemistry, Lise-Meitner-Strasse 34, D-85354 Freising, Germany
| | - Ute Schweiggert-Weisz
- Fraunhofer Institute for Process Engineering and Packaging (IVV), Giggenhauser Strasse 35, D-85354 Freising, Germany
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