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Nguyen TTD, Ho QT, Le NQK, Phan VD, Ou YY. Use Chou's 5-Steps Rule With Different Word Embedding Types to Boost Performance of Electron Transport Protein Prediction Model. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2022; 19:1235-1244. [PMID: 32750894 DOI: 10.1109/tcbb.2020.3010975] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Living organisms receive necessary energy substances directly from cellular respiration. The completion of electron storage and transportation requires the process of cellular respiration with the aid of electron transport chains. Therefore, the work of deciphering electron transport proteins is inevitably needed. The identification of these proteins with high performance has a prompt dependence on the choice of methods for feature extraction and machine learning algorithm. In this study, protein sequences served as natural language sentences comprising words. The nominated word embedding-based feature sets, hinged on the word embedding modulation and protein motif frequencies, were useful for feature choosing. Five word embedding types and a variety of conjoint features were examined for such feature selection. The support vector machine algorithm consequentially was employed to perform classification. The performance statistics within the 5-fold cross-validation including average accuracy, specificity, sensitivity, as well as MCC rates surpass 0.95. Such metrics in the independent test are 96.82, 97.16, 95.76 percent, and 0.9, respectively. Compared to state-of-the-art predictors, the proposed method can generate more preferable performance above all metrics indicating the effectiveness of the proposed method in determining electron transport proteins. Furthermore, this study reveals insights about the applicability of various word embeddings for understanding surveyed sequences.
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2
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Abstract
During the last three decades or so, many efforts have been made to study the protein cleavage
sites by some disease-causing enzyme, such as HIV (Human Immunodeficiency Virus) protease
and SARS (Severe Acute Respiratory Syndrome) coronavirus main proteinase. It has become increasingly
clear <i>via</i> this mini-review that the motivation driving the aforementioned studies is quite wise,
and that the results acquired through these studies are very rewarding, particularly for developing peptide
drugs.
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Affiliation(s)
- Kuo-Chen Chou
- Gordon Life Science Institute, Boston, MA 02478, United States
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3
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Chou KC. An Insightful 10-year Recollection Since the Emergence of the 5-steps Rule. Curr Pharm Des 2020; 25:4223-4234. [PMID: 31782354 DOI: 10.2174/1381612825666191129164042] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Accepted: 11/25/2019] [Indexed: 11/22/2022]
Abstract
OBJECTIVE One of the most challenging and also the most difficult problems is how to formulate a biological sequence with a vector but considerably keep its sequence order information. METHODS To address such a problem, the approach of Pseudo Amino Acid Components or PseAAC has been developed. RESULTS AND CONCLUSION It has become increasingly clear via the 10-year recollection that the aforementioned proposal has been indeed very powerful.
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Affiliation(s)
- Kuo-Chen Chou
- Gordon Life Science Institute, Boston, Massachusetts 02478, United States.,Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China
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6
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Identifying FL11 subtype by characterizing tumor immune microenvironment in prostate adenocarcinoma via Chou's 5-steps rule. Genomics 2020; 112:1500-1515. [DOI: 10.1016/j.ygeno.2019.08.021] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Revised: 08/03/2019] [Accepted: 08/26/2019] [Indexed: 12/14/2022]
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7
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Zheng H, Yang H, Gong D, Mai L, Qiu X, Chen L, Su X, Wei R, Zeng Z. Progress in the Mechanism and Clinical Application of Cilostazol. Curr Top Med Chem 2020; 19:2919-2936. [PMID: 31763974 DOI: 10.2174/1568026619666191122123855] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Revised: 07/27/2019] [Accepted: 08/02/2019] [Indexed: 12/20/2022]
Abstract
Cilostazol is a unique platelet inhibitor that has been used clinically for more than 20 years. As a phosphodiesterase type III inhibitor, cilostazol is capable of reversible inhibition of platelet aggregation and vasodilation, has antiproliferative effects, and is widely used in the treatment of peripheral arterial disease, cerebrovascular disease, percutaneous coronary intervention, etc. This article briefly reviews the pharmacological mechanisms and clinical application of cilostazol.
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Affiliation(s)
- Huilei Zheng
- Department of Medical Examination & Health Management, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.,Guangxi Key Laboratory of Precision Medicine in Cardio-cerebrovascular Diseases Control and Prevention,Nanning, Guangxi, China.,Guangxi Clinical Research Center for Cardio-cerebrovascular Diseases, Nanning, Guangxi, China
| | - Hua Yang
- Guangxi Key Laboratory of Precision Medicine in Cardio-cerebrovascular Diseases Control and Prevention,Nanning, Guangxi, China.,Guangxi Clinical Research Center for Cardio-cerebrovascular Diseases, Nanning, Guangxi, China.,Department of Critical Care Medicine, Second People's Hospital of Nanning, Nanning, Guangxi, China
| | - Danping Gong
- Guangxi Key Laboratory of Precision Medicine in Cardio-cerebrovascular Diseases Control and Prevention,Nanning, Guangxi, China.,Guangxi Clinical Research Center for Cardio-cerebrovascular Diseases, Nanning, Guangxi, China.,Elderly Cardiology Ward, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Lanxian Mai
- Guangxi Key Laboratory of Precision Medicine in Cardio-cerebrovascular Diseases Control and Prevention,Nanning, Guangxi, China.,Guangxi Clinical Research Center for Cardio-cerebrovascular Diseases, Nanning, Guangxi, China.,Disciplinary Construction Office, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Xiaoling Qiu
- Guangxi Key Laboratory of Precision Medicine in Cardio-cerebrovascular Diseases Control and Prevention,Nanning, Guangxi, China.,Guangxi Clinical Research Center for Cardio-cerebrovascular Diseases, Nanning, Guangxi, China
| | - Lidai Chen
- Guangxi Key Laboratory of Precision Medicine in Cardio-cerebrovascular Diseases Control and Prevention,Nanning, Guangxi, China.,Guangxi Clinical Research Center for Cardio-cerebrovascular Diseases, Nanning, Guangxi, China
| | - Xiaozhou Su
- Guangxi Key Laboratory of Precision Medicine in Cardio-cerebrovascular Diseases Control and Prevention,Nanning, Guangxi, China.,Guangxi Clinical Research Center for Cardio-cerebrovascular Diseases, Nanning, Guangxi, China
| | - Ruoqi Wei
- Department of Computer Science and Engineering, University of Bridgeport,126 Park Ave, BRIDGEPORT, CT 06604, United States
| | - Zhiyu Zeng
- Guangxi Key Laboratory of Precision Medicine in Cardio-cerebrovascular Diseases Control and Prevention,Nanning, Guangxi, China.,Guangxi Clinical Research Center for Cardio-cerebrovascular Diseases, Nanning, Guangxi, China.,Elderly Cardiology Ward, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
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8
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Chou KC. Impacts of Pseudo Amino Acid Components and 5-steps Rule to Proteomics and Proteome Analysis. Curr Top Med Chem 2019; 19:2283-2300. [DOI: 10.2174/1568026619666191018100141] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Revised: 08/18/2019] [Accepted: 08/26/2019] [Indexed: 01/27/2023]
Abstract
Stimulated by the 5-steps rule during the last decade or so, computational proteomics has achieved remarkable progresses in the following three areas: (1) protein structural class prediction; (2) protein subcellular location prediction; (3) post-translational modification (PTM) site prediction. The results obtained by these predictions are very useful not only for an in-depth study of the functions of proteins and their biological processes in a cell, but also for developing novel drugs against major diseases such as cancers, Alzheimer’s, and Parkinson’s. Moreover, since the targets to be predicted may have the multi-label feature, two sets of metrics are introduced: one is for inspecting the global prediction quality, while the other for the local prediction quality. All the predictors covered in this review have a userfriendly web-server, through which the majority of experimental scientists can easily obtain their desired data without the need to go through the complicated mathematics.
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Affiliation(s)
- Kuo-Chen Chou
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, 610054, China
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9
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Xie NZ, Li JX, Huang RB. Biological Production of (S)-acetoin: A State-of-the-Art Review. Curr Top Med Chem 2019; 19:2348-2356. [PMID: 31648637 DOI: 10.2174/1568026619666191018111424] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 08/28/2019] [Accepted: 09/02/2019] [Indexed: 12/24/2022]
Abstract
Acetoin is an important four-carbon compound that has many applications in foods, chemical synthesis, cosmetics, cigarettes, soaps, and detergents. Its stereoisomer (S)-acetoin, a high-value chiral compound, can also be used to synthesize optically active drugs, which could enhance targeting properties and reduce side effects. Recently, considerable progress has been made in the development of biotechnological routes for (S)-acetoin production. In this review, various strategies for biological (S)- acetoin production are summarized, and their constraints and possible solutions are described. Furthermore, future prospects of biological production of (S)-acetoin are discussed.
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Affiliation(s)
- Neng-Zhong Xie
- National Engineering Research Center for Non-Food Biorefinery, State Key Laboratory of Non-Food Biomass and Enzyme Technology, Guangxi Key Laboratory of Bio-refinery, Guangxi Biomass Engineering Technology Research Center, Guangxi Academy of Sciences, 98 Daling Road, Nanning, 530007, China
| | - Jian-Xiu Li
- National Engineering Research Center for Non-Food Biorefinery, State Key Laboratory of Non-Food Biomass and Enzyme Technology, Guangxi Key Laboratory of Bio-refinery, Guangxi Biomass Engineering Technology Research Center, Guangxi Academy of Sciences, 98 Daling Road, Nanning, 530007, China
| | - Ri-Bo Huang
- National Engineering Research Center for Non-Food Biorefinery, State Key Laboratory of Non-Food Biomass and Enzyme Technology, Guangxi Key Laboratory of Bio-refinery, Guangxi Biomass Engineering Technology Research Center, Guangxi Academy of Sciences, 98 Daling Road, Nanning, 530007, China.,State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Life Science and Technology, Guangxi University, 100 Daxue Road, Nanning, 530004, China
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10
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Chou KC. Proposing Pseudo Amino Acid Components is an Important Milestone for Proteome and Genome Analyses. Int J Pept Res Ther 2019. [DOI: 10.1007/s10989-019-09910-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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11
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12
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Khan S, Khan M, Iqbal N, Hussain T, Khan SA, Chou KC. A Two-Level Computation Model Based on Deep Learning Algorithm for Identification of piRNA and Their Functions via Chou’s 5-Steps Rule. Int J Pept Res Ther 2019. [DOI: 10.1007/s10989-019-09887-3] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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13
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Pan Q, Guo Y, Guo L, Liao S, Zhao C, Wang S, Liu HF. Mechanistic Insights of Chemicals and Drugs as Risk Factors for Systemic Lupus Erythematosus. Curr Med Chem 2019; 27:5175-5188. [PMID: 30947650 DOI: 10.2174/0929867326666190404140658] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Revised: 03/25/2019] [Accepted: 03/27/2019] [Indexed: 12/21/2022]
Abstract
Systemic Lupus Erythematosus (SLE) is a chronic and relapsing heterogenous autoimmune disease that primarily affects women of reproductive age. Genetic and environmental risk factors are involved in the pathogenesis of SLE, and susceptibility genes have recently been identified. However, as gene therapy is far from clinical application, further investigation of environmental risk factors could reveal important therapeutic approaches. We systematically explored two groups of environmental risk factors: chemicals (including silica, solvents, pesticides, hydrocarbons, heavy metals, and particulate matter) and drugs (including procainamide, hydralazine, quinidine, Dpenicillamine, isoniazid, and methyldopa). Furthermore, the mechanisms underlying risk factors, such as genetic factors, epigenetic change, and disrupted immune tolerance, were explored. This review identifies novel risk factors and their underlying mechanisms. Practicable measures for the management of these risk factors will benefit SLE patients and provide potential therapeutic strategies.
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Affiliation(s)
- Qingjun Pan
- Key Laboratory of Prevention and Management of Chronic Kidney Disease of Zhanjiang City, Affiliated Hospital of Guangdong Medical University, 57th South Renmin Road, Zhanjiang 524001, Guangdong, China
| | - Yun Guo
- Key Laboratory of Prevention and Management of Chronic Kidney Disease of Zhanjiang City, Affiliated Hospital of Guangdong Medical University, 57th South Renmin Road, Zhanjiang 524001, Guangdong, China
| | - Linjie Guo
- Key Laboratory of Prevention and Management of Chronic Kidney Disease of Zhanjiang City, Affiliated Hospital of Guangdong Medical University, 57th South Renmin Road, Zhanjiang 524001, Guangdong, China
| | - Shuzhen Liao
- Key Laboratory of Prevention and Management of Chronic Kidney Disease of Zhanjiang City, Affiliated Hospital of Guangdong Medical University, 57th South Renmin Road, Zhanjiang 524001, Guangdong, China
| | - Chunfei Zhao
- Key Laboratory of Prevention and Management of Chronic Kidney Disease of Zhanjiang City, Affiliated Hospital of Guangdong Medical University, 57th South Renmin Road, Zhanjiang 524001, Guangdong, China
| | - Sijie Wang
- Key Laboratory of Prevention and Management of Chronic Kidney Disease of Zhanjiang City, Affiliated Hospital of Guangdong Medical University, 57th South Renmin Road, Zhanjiang 524001, Guangdong, China
| | - Hua-Feng Liu
- Key Laboratory of Prevention and Management of Chronic Kidney Disease of Zhanjiang City, Affiliated Hospital of Guangdong Medical University, 57th South Renmin Road, Zhanjiang 524001, Guangdong, China
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14
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Jiang QX. Structural Variability in the RLR-MAVS Pathway and Sensitive Detection of Viral RNAs. Med Chem 2019; 15:443-458. [PMID: 30569868 PMCID: PMC6858087 DOI: 10.2174/1573406415666181219101613] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Revised: 10/23/2018] [Accepted: 12/12/2018] [Indexed: 12/25/2022]
Abstract
Cells need high-sensitivity detection of non-self molecules in order to fight against pathogens. These cellular sensors are thus of significant importance to medicinal purposes, especially for treating novel emerging pathogens. RIG-I-like receptors (RLRs) are intracellular sensors for viral RNAs (vRNAs). Their active forms activate mitochondrial antiviral signaling protein (MAVS) and trigger downstream immune responses against viral infection. Functional and structural studies of the RLR-MAVS signaling pathway have revealed significant supramolecular variability in the past few years, which revealed different aspects of the functional signaling pathway. Here I will discuss the molecular events of RLR-MAVS pathway from the angle of detecting single copy or a very low copy number of vRNAs in the presence of non-specific competition from cytosolic RNAs, and review key structural variability in the RLR / vRNA complexes, the MAVS helical polymers, and the adapter-mediated interactions between the active RLR / vRNA complex and the inactive MAVS in triggering the initiation of the MAVS filaments. These structural variations may not be exclusive to each other, but instead may reflect the adaptation of the signaling pathways to different conditions or reach different levels of sensitivity in its response to exogenous vRNAs.
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Affiliation(s)
- Qiu-Xing Jiang
- Department of Microbiology and Cell Science, University of Florida, Gainesville, FL 32611, United States
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15
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Qiu WR, Sun BQ, Xiao X, Xu ZC, Chou KC. iHyd-PseCp: Identify hydroxyproline and hydroxylysine in proteins by incorporating sequence-coupled effects into general PseAAC. Oncotarget 2018; 7:44310-44321. [PMID: 27322424 PMCID: PMC5190098 DOI: 10.18632/oncotarget.10027] [Citation(s) in RCA: 141] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2016] [Accepted: 05/29/2016] [Indexed: 12/30/2022] Open
Abstract
Protein hydroxylation is a posttranslational modification (PTM), in which a CH group in Pro (P) or Lys (K) residue has been converted into a COH group, or a hydroxyl group (−OH) is converted into an organic compound. Closely associated with cellular signaling activities, this type of PTM is also involved in some major diseases, such as stomach cancer and lung cancer. Therefore, from the angles of both basic research and drug development, we are facing a challenging problem: for an uncharacterized protein sequence containing many residues of P or K, which ones can be hydroxylated, and which ones cannot? With the explosive growth of protein sequences in the post-genomic age, the problem has become even more urgent. To address such a problem, we have developed a predictor called iHyd-PseCp by incorporating the sequence-coupled information into the general pseudo amino acid composition (PseAAC) and introducing the “Random Forest” algorithm to operate the calculation. Rigorous jackknife tests indicated that the new predictor remarkably outperformed the existing state-of-the-art prediction method for the same purpose. For the convenience of most experimental scientists, a user-friendly web-server for iHyd-PseCp has been established at http://www.jci-bioinfo.cn/iHyd-PseCp, by which users can easily obtain their desired results without the need to go through the complicated mathematical equations involved.
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Affiliation(s)
- Wang-Ren Qiu
- Computer Department, Jingdezhen Ceramic Institute, Jingdezhen, China.,Department of Computer Science and Bond Life Science Center, University of Missouri, Columbia, MO, USA
| | - Bi-Qian Sun
- Computer Department, Jingdezhen Ceramic Institute, Jingdezhen, China
| | - Xuan Xiao
- Computer Department, Jingdezhen Ceramic Institute, Jingdezhen, China.,Gordon Life Science Institute, Boston, MA, USA
| | - Zhao-Chun Xu
- Computer Department, Jingdezhen Ceramic Institute, Jingdezhen, China
| | - Kuo-Chen Chou
- Gordon Life Science Institute, Boston, MA, USA.,Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia.,Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
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16
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Fernández-Blanco E, Aguiar-Pulido V, Munteanu CR, Dorado J. Random Forest classification based on star graph topological indices for antioxidant proteins. J Theor Biol 2013; 317:331-7. [DOI: 10.1016/j.jtbi.2012.10.006] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2012] [Revised: 09/17/2012] [Accepted: 10/02/2012] [Indexed: 10/27/2022]
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17
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Aguiar-Pulido V, Munteanu CR, Seoane JA, Fernández-Blanco E, Pérez-Montoto LG, González-Díaz H, Dorado J. Naïve Bayes QSDR classification based on spiral-graph Shannon entropies for protein biomarkers in human colon cancer. MOLECULAR BIOSYSTEMS 2012; 8:1716-22. [PMID: 22466084 DOI: 10.1039/c2mb25039j] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Fast cancer diagnosis represents a real necessity in applied medicine due to the importance of this disease. Thus, theoretical models can help as prediction tools. Graph theory representation is one option because it permits us to numerically describe any real system such as the protein macromolecules by transforming real properties into molecular graph topological indices. This study proposes a new classification model for proteins linked with human colon cancer by using spiral graph topological indices of protein amino acid sequences. The best quantitative structure-disease relationship model is based on eleven Shannon entropy indices. It was obtained with the Naïve Bayes method and shows excellent predictive ability (90.92%) for new proteins linked with this type of cancer. The statistical analysis confirms that this model allows diagnosing the absence of human colon cancer obtaining an area under receiver operating characteristic of 0.91. The methodology presented can be used for any type of sequential information such as any protein and nucleic acid sequence.
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Affiliation(s)
- Vanessa Aguiar-Pulido
- Department of Information and Communications Technologies, University of A Coruña, A Coruña, Spain
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18
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Pérez-Montoto LG, Santana L, González-Díaz H. Scoring function for DNA-drug docking of anticancer and antiparasitic compounds based on spectral moments of 2D lattice graphs for molecular dynamics trajectories. Eur J Med Chem 2009; 44:4461-9. [PMID: 19604606 PMCID: PMC7127518 DOI: 10.1016/j.ejmech.2009.06.011] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2009] [Revised: 06/04/2009] [Accepted: 06/05/2009] [Indexed: 02/02/2023]
Abstract
We introduce here a new class of invariants for MD trajectories based on the spectral moments pi(k)(L) of the Markov matrix associated to lattice network-like (LN) graph representations of Molecular Dynamics (MD) trajectories. The procedure embeds the MD energy profiles on a 2D Cartesian coordinates system using simple heuristic rules. At the same time, we associate the LN with a Markov matrix that describes the probabilities of passing from one state to other in the new 2D space. We construct this type of LNs for 422 MD trajectories obtained in DNA-drug docking experiments of 57 furocoumarins. The combined use of psoralens+ultraviolet light (UVA) radiation is known as PUVA therapy. PUVA is effective in the treatment of skin diseases such as psoriasis and mycosis fungoides. PUVA is also useful to treat human platelet (PTL) concentrates in order to eliminate Leishmania spp. and Trypanosoma cruzi. Both are parasites that cause Leishmaniosis (a dangerous skin and visceral disease) and Chagas disease, respectively; and may circulate in blood products collected from infected donors. We included in this study both lineal (psoralens) and angular (angelicins) furocoumarins. In the study, we grouped the LNs on two sets; set1: DNA-drug complex MD trajectories for active compounds and set2: MD trajectories of non-active compounds or no-optimal MD trajectories of active compounds. We calculated the respective pi(k)(L) values for all these LNs and used them as inputs to train a new classifier that discriminate set1 from set2 cases. In training series the model correctly classifies 79 out of 80 (specificity=98.75%) set1 and 226 out of 238 (Sensitivity=94.96%) set2 trajectories. In independent validation series the model correctly classifies 26 out of 26 (specificity=100%) set1 and 75 out of 78 (sensitivity=96.15%) set2 trajectories. We propose this new model as a scoring function to guide DNA-docking studies in the drug design of new coumarins for anticancer or antiparasitic PUVA therapy.
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Affiliation(s)
- Lázaro G. Pérez-Montoto
- Department of Microbiology & Parasitology, and Department of Organic Chemistry
- Faculty of Pharmacy, University of Santiago de Compostela, 15782, Spain
| | - Lourdes Santana
- Faculty of Pharmacy, University of Santiago de Compostela, 15782, Spain
| | - Humberto González-Díaz
- Department of Microbiology & Parasitology, and Department of Organic Chemistry
- Faculty of Pharmacy, University of Santiago de Compostela, 15782, Spain
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19
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Munteanu CR, Vázquez JM, Dorado J, Sierra AP, Sánchez-González Á, Prado-Prado FJ, González-Díaz H. Complex Network Spectral Moments for ATCUN Motif DNA Cleavage: First Predictive Study on Proteins of Human Pathogen Parasites. J Proteome Res 2009; 8:5219-28. [DOI: 10.1021/pr900556g] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Cristian R. Munteanu
- Department of Information and Communication Technologies, Computer Science Faculty, University of A Coruña, Campus de Elviña, s/n 15071 A Coruña, Spain, Department of Inorganic Chemistry, Faculty of Pharmacy, University of Santiago de Compostela, Praza Seminario de Estudos Galegos, s/n. Campus sur, 15782 Santiago de Compostela, Spain, and Department of Microbiology & Parasitology, Faculty of Pharmacy, University of Santiago de Compostela, Praza Seminario de Estudos Galegos, s/n. Campus sur, 15782
| | - José M. Vázquez
- Department of Information and Communication Technologies, Computer Science Faculty, University of A Coruña, Campus de Elviña, s/n 15071 A Coruña, Spain, Department of Inorganic Chemistry, Faculty of Pharmacy, University of Santiago de Compostela, Praza Seminario de Estudos Galegos, s/n. Campus sur, 15782 Santiago de Compostela, Spain, and Department of Microbiology & Parasitology, Faculty of Pharmacy, University of Santiago de Compostela, Praza Seminario de Estudos Galegos, s/n. Campus sur, 15782
| | - Julián Dorado
- Department of Information and Communication Technologies, Computer Science Faculty, University of A Coruña, Campus de Elviña, s/n 15071 A Coruña, Spain, Department of Inorganic Chemistry, Faculty of Pharmacy, University of Santiago de Compostela, Praza Seminario de Estudos Galegos, s/n. Campus sur, 15782 Santiago de Compostela, Spain, and Department of Microbiology & Parasitology, Faculty of Pharmacy, University of Santiago de Compostela, Praza Seminario de Estudos Galegos, s/n. Campus sur, 15782
| | - Alejandro Pazos Sierra
- Department of Information and Communication Technologies, Computer Science Faculty, University of A Coruña, Campus de Elviña, s/n 15071 A Coruña, Spain, Department of Inorganic Chemistry, Faculty of Pharmacy, University of Santiago de Compostela, Praza Seminario de Estudos Galegos, s/n. Campus sur, 15782 Santiago de Compostela, Spain, and Department of Microbiology & Parasitology, Faculty of Pharmacy, University of Santiago de Compostela, Praza Seminario de Estudos Galegos, s/n. Campus sur, 15782
| | - Ángeles Sánchez-González
- Department of Information and Communication Technologies, Computer Science Faculty, University of A Coruña, Campus de Elviña, s/n 15071 A Coruña, Spain, Department of Inorganic Chemistry, Faculty of Pharmacy, University of Santiago de Compostela, Praza Seminario de Estudos Galegos, s/n. Campus sur, 15782 Santiago de Compostela, Spain, and Department of Microbiology & Parasitology, Faculty of Pharmacy, University of Santiago de Compostela, Praza Seminario de Estudos Galegos, s/n. Campus sur, 15782
| | - Francisco J. Prado-Prado
- Department of Information and Communication Technologies, Computer Science Faculty, University of A Coruña, Campus de Elviña, s/n 15071 A Coruña, Spain, Department of Inorganic Chemistry, Faculty of Pharmacy, University of Santiago de Compostela, Praza Seminario de Estudos Galegos, s/n. Campus sur, 15782 Santiago de Compostela, Spain, and Department of Microbiology & Parasitology, Faculty of Pharmacy, University of Santiago de Compostela, Praza Seminario de Estudos Galegos, s/n. Campus sur, 15782
| | - Humberto González-Díaz
- Department of Information and Communication Technologies, Computer Science Faculty, University of A Coruña, Campus de Elviña, s/n 15071 A Coruña, Spain, Department of Inorganic Chemistry, Faculty of Pharmacy, University of Santiago de Compostela, Praza Seminario de Estudos Galegos, s/n. Campus sur, 15782 Santiago de Compostela, Spain, and Department of Microbiology & Parasitology, Faculty of Pharmacy, University of Santiago de Compostela, Praza Seminario de Estudos Galegos, s/n. Campus sur, 15782
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Generalized lattice graphs for 2D-visualization of biological information. J Theor Biol 2009; 261:136-47. [PMID: 19646452 PMCID: PMC7094121 DOI: 10.1016/j.jtbi.2009.07.029] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2009] [Revised: 07/18/2009] [Accepted: 07/20/2009] [Indexed: 01/09/2023]
Abstract
Several graph representations have been introduced for different data in theoretical biology. For instance, complex networks based on Graph theory are used to represent the structure and/or dynamics of different large biological systems such as protein–protein interaction networks. In addition, Randic, Liao, Nandy, Basak, and many others developed some special types of graph-based representations. This special type of graph includes geometrical constrains to node positioning in space and adopts final geometrical shapes that resemble lattice-like patterns. Lattice networks have been used to visually depict DNA and protein sequences but they are very flexible. However, despite the proved efficacy of new lattice-like graph/networks to represent diverse systems, most works focus on only one specific type of biological data. This work proposes a generalized type of lattice and illustrates how to use it in order to represent and compare biological data from different sources. We exemplify the following cases: protein sequence; mass spectra (MS) of protein peptide mass fingerprints (PMF); molecular dynamic trajectory (MDTs) from structural studies; mRNA microarray data; single nucleotide polymorphisms (SNPs); 1D or 2D-Electrophoresis study of protein polymorphisms and protein-research patent and/or copyright information. We used data available from public sources for some examples but for other, we used experimental results reported herein for the first time. This work may break new ground for the application of Graph theory in theoretical biology and other areas of biomedical sciences.
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21
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Munteanu CR, Magalhães AL, Uriarte E, González-Díaz H. Multi-target QPDR classification model for human breast and colon cancer-related proteins using star graph topological indices. J Theor Biol 2008; 257:303-11. [PMID: 19111559 PMCID: PMC7094125 DOI: 10.1016/j.jtbi.2008.11.017] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2008] [Revised: 11/11/2008] [Accepted: 11/22/2008] [Indexed: 11/07/2022]
Abstract
The cancer diagnostic is a complex process and, sometimes, the specific markers can interfere or produce negative results. Thus, new simple and fast theoretical models are required. One option is the complex network graphs theory that permits us to describe any real system, from the small molecules to the complex genetic, neural or social networks by transforming real properties in topological indices. This work converts the protein primary structure data in specific Randic's star networks topological indices using the new sequence to star networks (S2SNet) application. A set of 1054 proteins were selected from previous works and contains proteins related or not with two types of cancer, human breast cancer (HBC) and human colon cancer (HCC). The general discriminant analysis method generates an input-coded multi-target classification model with the training/predicting set accuracies of 90.0% for the forward stepwise model type. In addition, a protein subset was modified by single amino acid mutations with higher log-odds PAM250 values and tested with the new classification if can be related with HBC or HCC. In conclusion, we shown that, using simple input data such is the primary protein sequence and the simples linear analysis, it is possible to obtain accurate classification models that can predict if a new protein related with two types of cancer. These results promote the use of the S2SNet in clinical proteomics.
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22
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Munteanu CR, González-Díaz H, Borges F, de Magalhães AL. Natural/random protein classification models based on star network topological indices. J Theor Biol 2008; 254:775-83. [PMID: 18692072 PMCID: PMC7094162 DOI: 10.1016/j.jtbi.2008.07.018] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2008] [Revised: 07/09/2008] [Accepted: 07/15/2008] [Indexed: 11/18/2022]
Abstract
The development of the complex network graphs permits us to describe any real system such as social, neural, computer or genetic networks by transforming real properties in topological indices (TIs). This work uses Randic's star networks in order to convert the protein primary structure data in specific topological indices that are used to construct a natural/random protein classification model. The set of natural proteins contains 1046 protein chains selected from the pre-compiled CulledPDB list from PISCES Dunbrack's Web Lab. This set is characterized by a protein homology of 20%, a structure resolution of 1.6 Å and R-factor lower than 25%. The set of random amino acid chains contains 1046 sequences which were generated by Python script according to the same type of residues and average chain length found in the natural set. A new Sequence to Star Networks (S2SNet) wxPython GUI application (with a Graphviz graphics back-end) was designed by our group in order to transform any character sequence in the following star network topological indices: Shannon entropy of Markov matrices, trace of connectivity matrices, Harary number, Wiener index, Gutman index, Schultz index, Moreau–Broto indices, Balaban distance connectivity index, Kier–Hall connectivity indices and Randic connectivity index. The model was constructed with the General Discriminant Analysis methods from STATISTICA package and gave training/predicting set accuracies of 90.77% for the forward stepwise model type. In conclusion, this study extends for the first time the classical TIs to protein star network TIs by proposing a model that can predict if a protein/fragment of protein is natural or random using only the amino acid sequence data. This classification can be used in the studies of the protein functions by changing some fragments with random amino acid sequences or to detect the fake amino acid sequences or the errors in proteins. These results promote the use of the S2SNet application not only for protein structure analysis but also for mass spectroscopy, clinical proteomics and imaging, or DNA/RNA structure analysis.
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Affiliation(s)
- Cristian Robert Munteanu
- REQUIMTE-University of Porto, Faculty of Science, Chemistry Department, University of Porto 4169-007, Portugal.
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23
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Using ensemble of classifiers for predicting HIV protease cleavage sites in proteins. Amino Acids 2008; 36:409-16. [DOI: 10.1007/s00726-008-0076-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2008] [Accepted: 03/27/2008] [Indexed: 10/22/2022]
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24
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Mechanisms of telomerase-dimer catalysis. J Theor Biol 2007; 250:512-23. [PMID: 18054367 DOI: 10.1016/j.jtbi.2007.10.028] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2007] [Revised: 10/20/2007] [Accepted: 10/25/2007] [Indexed: 11/22/2022]
Abstract
There is evidence that human telomerase acts as a dimer [Wenz, C., Enenkel, B., Amacker, M., Kelleher, C., Damm, K., Lingner, J., 2001. Human telomerase contains two cooperating telomerase RNA molecules. EMBO J. 20, 3526-3534]. Three possible mechanisms have been proposed. We translate those proposals into three detailed mechanistic models for telomerase action, also introducing optional isomerizations with equilibrium constants inversely related to the number of bound nucleotides. To distinguish between these models by in situ experiments we propose a microscopic system which uses two-photon excitation of fluorescence in a volume of about 0.5 microm(3). A variety of detection strategies and experimental designs are considered; we focus on those best suited to observation of a small volume under limitations imposed by diffusion to and from the reacting micro-volume, and consequently restrict ourselves to constant flow. Numerical simulation is used to help identify an optimal experimental design. The detection of mechanistic changes hinges on linking fluorescence reporters to selected reaction components, either directly (chemically) or indirectly (via an indicator reaction). We show that rapid mixing experiments are better than chemical relaxation experiments, as the statistics of single molecule kinetics affects the latter more than the former. However, some fast reaction steps can only be revealed by chemical relaxation coupled with mixing experiments. We explore connections between our methods and studies of HIV and other systems with RNA to DNA transcription.
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25
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Du Q, Huang R, Wei Y, Wang C, Chou K. Peptide reagent design based on physical and chemical properties of amino acid residues. J Comput Chem 2007; 28:2043-50. [PMID: 17450553 PMCID: PMC7166493 DOI: 10.1002/jcc.20732] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2007] [Revised: 02/18/2007] [Accepted: 02/19/2007] [Indexed: 11/30/2022]
Abstract
It has tremendous values for both drug discovery and basic research to develop a solid bioinformatical tool for guiding peptide reagent design. Based on the physical and chemical properties of amino acids, a new strategy for peptide reagent design, the so-called AABPD (amino acid based-peptide design), is proposed. The peptide samples in a training dataset are described by a series of HMLP (heuristic molecular lipophilicity potential) parameters and other physicochemical properties of amino acid residues that form a three-dimensional data matrix where each component is defined by three indexes: the first index refers to the peptide samples, the second to the amino acid positions, and the third to the amino acid parameters. The binding free energy between a peptide ligand and its protein receptor is calculated by a linear free energy equation through the physicochemical parameters, resulting in a set of simultaneous linear equations between the bioactivity of the peptides and the physicochemical properties of amino acids. An iterative double least square technique is developed for the solution of the three-dimensional simultaneous linear equation set to determine the amino acid position coefficients of peptide sequence and the physicochemical parameter coefficients of amino acid residues alternately. The two sets of coefficients thus obtained are used for predicting the bioactivity of other query peptide reagents. Two calculation examples, the peptide substrate specificity of the SARS coronavirus 3C-like proteinase and the affinity prediction for epitope-peptides with Class I MHC molecules are studied by using the peptide reagent design strategy.
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Affiliation(s)
- Qi‐Shi Du
- Guangxi Key Laboratory of Subtropical Bioresource Conservation and Utilization, Guangxi University, Nanning, Guangxi, 530004, China
- Institute of Bioinformatics and Drug Discovery, Tianjin Normal University, Tianjin, 300074, China
- Gordon Life Science Institute, San Diego, California 92130, USA
| | - Ri‐Bo Huang
- Guangxi Key Laboratory of Subtropical Bioresource Conservation and Utilization, Guangxi University, Nanning, Guangxi, 530004, China
- Guangxi Academy of Sciences, 98 Daling Road, Nanning, Guangxi 530004, China
| | - Yu‐Tuo Wei
- Guangxi Key Laboratory of Subtropical Bioresource Conservation and Utilization, Guangxi University, Nanning, Guangxi, 530004, China
| | - Cheng‐Hua Wang
- Guangxi Key Laboratory of Subtropical Bioresource Conservation and Utilization, Guangxi University, Nanning, Guangxi, 530004, China
| | - Kuo‐Chen Chou
- Gordon Life Science Institute, San Diego, California 92130, USA
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26
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Gao L, Ding YS, Dai H, Shao SH, Huang ZD, Chou KC. A novel fingerprint map for detecting SARS-CoV. J Pharm Biomed Anal 2005; 41:246-50. [PMID: 16289934 PMCID: PMC7127393 DOI: 10.1016/j.jpba.2005.09.031] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2005] [Revised: 09/20/2005] [Accepted: 09/24/2005] [Indexed: 01/15/2023]
Abstract
Spike (S) protein is the most important membrane protein on the surface of severe acute respiratory syndrome coronavirus (SARS-CoV). It associates with cellular receptors to mediate infection of their target cells. Inspired by such a mechanism, an in-depth investigation into the genome sequences of S protein of SARS-CoV and its receptor are conducted thru a mathematical transformation and graphic approach. As an outcome, a novel method for visualizing the characteristic of SARS-CoV is suggested. An extensive comparison among a large number of genome sequences has proved that the characteristic thus revealed is unique for SARS-CoV. As such, the characteristic can be regarded as the fingerprint map of SARS-CoV for diagnostic usage. Moreover, the conclusion has been further supported in a real case in Guangdong province of China. The fingerprint map proposed here has the merits of clear visibility and reliability that can serve as a complementary clinical tool for detecting SARS-CoV, particularly for the cases where the results obtained by the conventional methods are uncertain or conflicted with each other.
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Affiliation(s)
- Lei Gao
- Bio-Informatics Research Center, College of Information Sciences and Technology, Donghua University, Shanghai 200051, China
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27
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Du QS, Wang SQ, Zhu Y, Wei DQ, Guo H, Sirois S, Chou KC. Polyprotein cleavage mechanism of SARS CoV Mpro and chemical modification of the octapeptide. Peptides 2004; 25:1857-64. [PMID: 15501516 PMCID: PMC7115412 DOI: 10.1016/j.peptides.2004.06.018] [Citation(s) in RCA: 48] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2004] [Revised: 06/18/2004] [Accepted: 06/22/2004] [Indexed: 11/26/2022]
Abstract
The cleavage mechanism of severe acute respiratory syndrome (SARS) coronavirus main proteinase (M(pro) or 3CL(pro)) for the octapeptide AVLQSGFR is studied using molecular mechanics (MM) and quantum mechanics (QM). The catalytic dyad His-41 and Cys-145 in the active pocket between domain I and II seem to polarize the pi-electron density of the peptide bond between Gln and Ser in the octapeptide, leading to an increase of positive charge on C(CO) of Gln and negative charge on N(NH) of Ser. The possibility of enhancing the chemical bond between Gln and Ser based on the "distorted key" theory [Anal. Biochem. 233 (1996) 1] is examined. The scissile peptide bond between Gln and Ser is found to be solidified through "hybrid peptide bond" by changing the carbonyl group CO of Gln to CH(2) or CF(2). This leads to a break of the pi-bond system for the peptide bond, making the octapeptide (AVLQSGFR) a "distorted key" and a potential starting system for the design of anti SARS drugs.
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Affiliation(s)
- Qi-Shi Du
- Tianjin Normal University and Tianjin Institute of Bioinformatics and Drug Discovery (TIBDD), Tianjin 300074, China
- Institut Technologique de Montreal, Suite 168, 5253 Boul. Decarie, Montreal, Que., Canada H3W 3C3
| | - Shu-Qing Wang
- Tianjin Normal University and Tianjin Institute of Bioinformatics and Drug Discovery (TIBDD), Tianjin 300074, China
| | - Yu Zhu
- Tianjin Normal University and Tianjin Institute of Bioinformatics and Drug Discovery (TIBDD), Tianjin 300074, China
| | - Dong-Qing Wei
- Tianjin Normal University and Tianjin Institute of Bioinformatics and Drug Discovery (TIBDD), Tianjin 300074, China
- Institut Technologique de Montreal, Suite 168, 5253 Boul. Decarie, Montreal, Que., Canada H3W 3C3
- Center For Research in Molecular Modeling (CERMM), Concordia University, Montreal, Canada
| | - Hong Guo
- University of Tennessee, Department of Biochemistry, Cell and Molecular Biology, Knoxville, TN 37996-0840, USA
| | - Suzanne Sirois
- Institut Technologique de Montreal, Suite 168, 5253 Boul. Decarie, Montreal, Que., Canada H3W 3C3
| | - Kuo-Chen Chou
- Tianjin Normal University and Tianjin Institute of Bioinformatics and Drug Discovery (TIBDD), Tianjin 300074, China
- Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai 200030, China
- Gordon Life Science Institute, San Diego, CA 92130, USA
- Corresponding author.
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28
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Reinke RA, Lee DJ, McDougall BR, King PJ, Victoria J, Mao Y, Lei X, Reinecke MG, Robinson WE. L-chicoric acid inhibits human immunodeficiency virus type 1 integration in vivo and is a noncompetitive but reversible inhibitor of HIV-1 integrase in vitro. Virology 2004; 326:203-19. [PMID: 15302207 DOI: 10.1016/j.virol.2004.06.005] [Citation(s) in RCA: 38] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2004] [Revised: 02/17/2004] [Accepted: 06/01/2004] [Indexed: 11/22/2022]
Abstract
The human immunodeficiency virus (HIV) integrase (IN) must covalently join the viral cDNA into a host chromosome for productive HIV infection. l-Chicoric acid (l-CA) enters cells poorly but is a potent inhibitor of IN in vitro. Using quantitative real-time polymerase chain reaction (PCR), l-CA inhibits integration at concentrations from 500 nM to 10 microM but also inhibits entry at concentrations above 1 microM. Using recombinant HIV IN, steady-state kinetic analyses with l-CA were consistent with a noncompetitive or irreversible mechanism of inhibition. IN, in the presence or absence of l-CA, was successively washed. Inhibition of IN diminished, demonstrating that l-CA was reversibly bound to the protein. These data demonstrate that l-CA is a noncompetitive but reversible inhibitor of IN in vitro and of HIV integration in vivo. Thus, l-CA likely interacts with amino acids other than those which bind substrate.
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Affiliation(s)
- Ryan A Reinke
- Department of Microbiology and Molecular Genetics, University of California, Irvine 92697-4800, USA
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29
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Kingston J, Sudheendra Rao M. High yield synthesis of cyclic phosphites, phosphates, sulphites and sulphates of catechol and glycol mediated by hypervalent silicon centres. Tetrahedron Lett 1997. [DOI: 10.1016/s0040-4039(97)01020-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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30
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Orlando P, Strazzullo G, Carretta F, De Falco M, Grippo P. Inhibition mechanisms of HIV-1, Mo-MuLV and AMV reverse transcriptases by Kelletinin A from Buccinulum corneum. EXPERIENTIA 1996; 52:812-7. [PMID: 8774754 DOI: 10.1007/bf01923995] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Kelletinin A [ribity pentakis (p-hydroxybenzoate)] (KA), an inhibitor of HTLV-1 replication isolated from Buccinulum corneum, showed a noncompetitive inhibitory activity with respect to the template primer and to dTTP in the poly(rA).oligo(dT)12-18-directed reaction of HIV-1, Mo-MuLV and AMV reverse transcriptases (RT). Analysis of natural and synthetic KA-related compounds showed that the inhibitory activity was strictly related to the structural peculiarities of the molecule. In the presence of DNA as template primer the inhibition mechanism was drastically modified: HIV-1 RT activity was stimulated by low concentrations of KA and was inhibited by increasing the concentration of the compound, while Mo-MuLV and AMV activities were irreversibly inhibited by the formation of a non-reactive complex. The RNase H activities of these RTs were not affected by KA. The results of this study suggest a different mechanism of interaction of Kelletinins with HIV-1 RT compared with other non-nucleoside inhibitors. A possible use of these drugs in combination therapy and in the design of structure-based reverse transcriptase inhibitors is discussed.
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Affiliation(s)
- P Orlando
- Istituto Biochimica delle Proteine ed Enzimologia, CNR, Arco Felice, Naples, Italy
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31
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Althaus IW, Chou KC, Lemay RJ, Franks KM, Deibel MR, Kezdy FJ, Resnick L, Busso ME, So AG, Downey KM, Romero DL, Thomas RC, Aristoff PA, Tarpley WG, Reusser F. The benzylthio-pyrimidine U-31,355, a potent inhibitor of HIV-1 reverse transcriptase. Biochem Pharmacol 1996; 51:743-50. [PMID: 8602869 DOI: 10.1016/0006-2952(95)02390-9] [Citation(s) in RCA: 67] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
U-31,355, or 4-amino-2-(benzylthio)-6-chloropyrimidine is an inhibitor of human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT) and possesses anti-HIV activity in HIV-1-infected lymphocytes grown in tissue culture. The compound acts as a specific inhibitor of the RNA-directed DNA polymerase function of HIV-1RT and does not impair the functions of the DNA-catalyzed DNA polymerase or the Rnase H of the enzyme. Kinetic studies were carried out to elucidate the mechanism of RT inhibition by U-31,355. The data were analyzed using Briggs-Haldane kinetics, assuming that the reaction is ordered in that the template:primer binds to the enzyme first, followed by the addition of dNTP, and that the polymerase is a processive enzyme. Based on these assumptions, a velocity equation was derived that allows the calculation of all the essential forward and backward rate constants for the reactions occurring between the enzyme, its substrates, and the inhibitor. The results obtained indicate that U-31,355 acts as a mixed inhibitor with respect to the template:primer and dNTP binding sites associated with the RNA-directed DNA polymerase domain of the enzyme. The inhibitor possessed a significantly higher binding affinity for the enzyme-substrate complexes, than for the free enzyme and consequently did not directly affect the functions of the substrate binding sites. Therefore, U-31,355 appears to impair an event occurring after the formation of the enzyme-substrate complexes, which involves either inhibition of the phosphoester bond formation or translocation of the enzyme relative to its template:primer following the formation of the ester bond. Moreover, the potency of U-31,355 depends on the base composition of the template:primer in that the inhibitor showed a much higher binding affinity for the enzyme-poly (rC):(dG)10 complexes than for the poly (rA):(dT)10 complexes.
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Affiliation(s)
- I W Althaus
- Upjohn Laboratories, Kalamazoo 49007-4940, MI USA
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32
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Althaus IW, Chou JJ, Gonzales AJ, Deibel MR, Chou KC, Kezdy FJ, Romero DL, Thomas RC, Aristoff PA, Tarpley WG. Kinetic studies with the non-nucleoside human immunodeficiency virus type-1 reverse transcriptase inhibitor U-90152E. Biochem Pharmacol 1994; 47:2017-28. [PMID: 7516658 DOI: 10.1016/0006-2952(94)90077-9] [Citation(s) in RCA: 59] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
The bisheteroarylpiperazine U-90152E is a potent inhibitor of human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT) and possesses excellent anti-HIV activity in HIV-1-infected lymphocytes grown in tissue culture. The compound inhibits both the RNA- and DNA-directed DNA polymerase functions of HIV-1 RT. Kinetic studies were carried out to elucidate the mechanism of RT inhibition by U-90152E. Michaelis-Menten kinetics, which are based on the establishment of a rapid equilibrium between the enzyme and its substrates, proved inadequate for the analysis of the experimental data. The data were thus analyzed using Briggs-Haldane kinetics, assuming that the reaction is ordered in that the template:primer binds to the enzyme first, followed by the addition of dNTP and that the polymerase is a processive enzyme. Based on these assumptions, a velocity equation was derived, which allows the calculation of all the essential forward and backward rate constants for the reactions occurring between the enzyme, its substrates and the inhibitor. The results obtained indicate that U-90152E acts exclusively as a mixed inhibitor with respect to the template: primer and dNTP binding sites for both the RNA- and DNA-directed DNA polymerase domains of the enzyme. The inhibitor shows a significantly higher binding affinity for the enzyme-substrate complexes than for the free enzyme and consequently does not directly impair the functions of the substrate binding sites. Therefore, U-90152E appears to impair an event occurring after the formation of the enzyme-substrate complexes, which involves either inhibition of the phosphoester bond formation or translocation of the enzyme relative to its template:primer following the formation of the ester bond.
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