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Asim A. Approaches to Backbone Flexibility in Protein-Protein Docking. Methods Mol Biol 2024; 2780:45-68. [PMID: 38987463 DOI: 10.1007/978-1-0716-3985-6_4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2024]
Abstract
Proteins are the fundamental organic macromolecules in living systems that play a key role in a variety of biological functions including immunological detection, intracellular trafficking, and signal transduction. The docking of proteins has greatly advanced during recent decades and has become a crucial complement to experimental methods. Protein-protein docking is a helpful method for simulating protein complexes whose structures have not yet been solved experimentally. This chapter focuses on major search tactics along with various docking programs used in protein-protein docking algorithms, which include: direct search, exhaustive global search, local shape feature matching, randomized search, and broad category of post-docking approaches. As backbone flexibility predictions and interactions in high-resolution protein-protein docking remain important issues in the overall optimization context, we have put forward several methods and solutions used to handle backbone flexibility. In addition, various docking methods that are utilized for flexible backbone docking, including ATTRACT, FlexDock, FLIPDock, HADDOCK, RosettaDock, FiberDock, etc., along with their scoring functions, algorithms, advantages, and limitations are discussed. Moreover, what progress in search technology is expected, including not only the creation of new search algorithms but also the enhancement of existing ones, has been debated. As conformational flexibility is one of the most crucial factors affecting docking success, more work should be put into evaluating the conformational flexibility upon binding for a particular case in addition to developing new algorithms to replace the rigid body docking and scoring approach.
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Affiliation(s)
- Ayesha Asim
- Department of Synthesis and Chemical Technology of Pharmaceutical Substances with Computer Modeling Laboratory, Faculty of Pharmacy, Medical University of Lublin, Lublin, Poland
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2
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Hacisuleyman A, Erman B. Fine tuning rigid body docking results using the Dreiding force field: A computational study of 36 known nanobody-protein complexes. Proteins 2023; 91:1417-1426. [PMID: 37232507 DOI: 10.1002/prot.26529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 05/03/2023] [Accepted: 05/08/2023] [Indexed: 05/27/2023]
Abstract
This paper aims to understand the binding strategies of a nanobody-protein pair by studying known complexes. Rigid body protein-ligand docking programs produce several complexes, called decoys, which are good candidates with high scores of shape complementarity, electrostatic interactions, desolvation, buried surface area, and Lennard-Jones potentials. However, the decoy that corresponds to the native structure is not known. We studied 36 nanobody-protein complexes from the single domain antibody database, sd-Ab DB, http://www.sdab-db.ca/. For each structure, a large number of decoys are generated using the Fast Fourier Transform algorithm of the software ZDOCK. The decoys were ranked according to their target protein-nanobody interaction energies, calculated by using the Dreiding Force Field, with rank 1 having the lowest interaction energy. Out of 36 protein data bank (PDB) structures, 25 true structures were predicted as rank 1. Eleven of the remaining structures required Ångstrom size rigid body translations of the nanobody relative to the protein to match the given PDB structure. After the translation, the Dreiding interaction (DI) energies of all complexes decreased and became rank 1. In one case, rigid body rotations as well as translations of the nanobody were required for matching the crystal structure. We used a Monte Carlo algorithm that randomly translates and rotates the nanobody of a decoy and calculates the DI energy. Results show that rigid body translations and the DI energy are sufficient for determining the correct binding location and pose of ZDOCK created decoys. A survey of the sd-Ab DB showed that each nanobody makes at least one salt bridge with its partner protein, indicating that salt bridge formation is an essential strategy in nanobody-protein recognition. Based on the analysis of the 36 crystal structures and evidence from existing literature, we propose a set of principles that could be used in the design of nanobodies.
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Affiliation(s)
- Aysima Hacisuleyman
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Burak Erman
- Chemical and Biological Engineering, Koc University, Istanbul, Turkey
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3
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Moura JJG. The History of Desulfovibrio gigas Aldehyde Oxidoreductase-A Personal View. Molecules 2023; 28:4229. [PMID: 37241969 PMCID: PMC10223205 DOI: 10.3390/molecules28104229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 05/17/2023] [Accepted: 05/19/2023] [Indexed: 05/28/2023] Open
Abstract
A story going back almost 40 years is presented in this manuscript. This is a different and more challenging way of reporting my research and I hope it will be useful to and target a wide-ranging audience. When preparing the manuscript and collecting references on the subject of this paper-aldehyde oxidoreductase from Desulfovibrio gigas-I felt like I was travelling back in time (and space), bringing together the people that have contributed most to this area of research. I sincerely hope that I can give my collaborators the credit they deserve. This study is not presented as a chronologic narrative but as a grouping of topics, the development of which occurred over many years.
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Affiliation(s)
- José J G Moura
- LAQV, NOVA School of Science and Technology|FCT NOVA, 2829-516 Caparica, Portugal
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4
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Rui H, Ashton KS, Min J, Wang C, Potts PR. Protein-protein interfaces in molecular glue-induced ternary complexes: classification, characterization, and prediction. RSC Chem Biol 2023; 4:192-215. [PMID: 36908699 PMCID: PMC9994104 DOI: 10.1039/d2cb00207h] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 01/02/2023] [Indexed: 01/04/2023] Open
Abstract
Molecular glues are a class of small molecules that stabilize the interactions between proteins. Naturally occurring molecular glues are present in many areas of biology where they serve as central regulators of signaling pathways. Importantly, several clinical compounds act as molecular glue degraders that stabilize interactions between E3 ubiquitin ligases and target proteins, leading to their degradation. Molecular glues hold promise as a new generation of therapeutic agents, including those molecular glue degraders that can redirect the protein degradation machinery in a precise way. However, rational discovery of molecular glues is difficult in part due to the lack of understanding of the protein-protein interactions they stabilize. In this review, we summarize the structures of known molecular glue-induced ternary complexes and the interface properties. Detailed analysis shows different mechanisms of ternary structure formation. Additionally, we also review computational approaches for predicting protein-protein interfaces and highlight the promises and challenges. This information will ultimately help inform future approaches for rational molecular glue discovery.
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Affiliation(s)
- Huan Rui
- Center for Research Acceleration by Digital Innovation, Amgen Research Thousand Oaks CA 91320 USA
| | - Kate S Ashton
- Medicinal Chemistry, Amgen Research Thousand Oaks CA 91320 USA
| | - Jaeki Min
- Induced Proximity Platform, Amgen Research Thousand Oaks CA 91320 USA
| | - Connie Wang
- Digital, Technology & Innovation, Amgen Thousand Oaks CA 91320 USA
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5
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Chang Y, Hawkins BA, Du JJ, Groundwater PW, Hibbs DE, Lai F. A Guide to In Silico Drug Design. Pharmaceutics 2022; 15:pharmaceutics15010049. [PMID: 36678678 PMCID: PMC9867171 DOI: 10.3390/pharmaceutics15010049] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 12/16/2022] [Accepted: 12/17/2022] [Indexed: 12/28/2022] Open
Abstract
The drug discovery process is a rocky path that is full of challenges, with the result that very few candidates progress from hit compound to a commercially available product, often due to factors, such as poor binding affinity, off-target effects, or physicochemical properties, such as solubility or stability. This process is further complicated by high research and development costs and time requirements. It is thus important to optimise every step of the process in order to maximise the chances of success. As a result of the recent advancements in computer power and technology, computer-aided drug design (CADD) has become an integral part of modern drug discovery to guide and accelerate the process. In this review, we present an overview of the important CADD methods and applications, such as in silico structure prediction, refinement, modelling and target validation, that are commonly used in this area.
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Affiliation(s)
- Yiqun Chang
- Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia
| | - Bryson A. Hawkins
- Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia
| | - Jonathan J. Du
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Paul W. Groundwater
- Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia
| | - David E. Hibbs
- Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia
| | - Felcia Lai
- Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia
- Correspondence:
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Nucleus-translocated mitochondrial cytochrome c liberates nucleophosmin-sequestered ARF tumor suppressor by changing nucleolar liquid–liquid phase separation. Nat Struct Mol Biol 2022; 29:1024-1036. [DOI: 10.1038/s41594-022-00842-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 08/30/2022] [Indexed: 11/07/2022]
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7
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Das S, Chakrabarti S. Classification and prediction of protein-protein interaction interface using machine learning algorithm. Sci Rep 2021; 11:1761. [PMID: 33469042 PMCID: PMC7815773 DOI: 10.1038/s41598-020-80900-2] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Accepted: 12/15/2020] [Indexed: 01/29/2023] Open
Abstract
Structural insight of the protein-protein interaction (PPI) interface can provide knowledge about the kinetics, thermodynamics and molecular functions of the complex while elucidating its role in diseases and further enabling it as a potential therapeutic target. However, owing to experimental lag in solving protein-protein complex structures, three-dimensional (3D) knowledge of the PPI interfaces can be gained via computational approaches like molecular docking and post-docking analyses. Despite development of numerous docking tools and techniques, success in identification of native like interfaces based on docking score functions is limited. Hence, we employed an in-depth investigation of the structural features of the interface that might successfully delineate native complexes from non-native ones. We identify interface properties, which show statistically significant difference between native and non-native interfaces belonging to homo and hetero, protein-protein complexes. Utilizing these properties, a support vector machine (SVM) based classification scheme has been implemented to differentiate native and non-native like complexes generated using docking decoys. Benchmarking and comparative analyses suggest very good performance of our SVM classifiers. Further, protein interactions, which are proven via experimental findings but not resolved structurally, were subjected to this approach where 3D-models of the complexes were generated and most likely interfaces were predicted. A web server called Protein Complex Prediction by Interface Properties (PCPIP) is developed to predict whether interface of a given protein-protein dimer complex resembles known protein interfaces. The server is freely available at http://www.hpppi.iicb.res.in/pcpip/ .
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Affiliation(s)
- Subhrangshu Das
- grid.417635.20000 0001 2216 5074Structural Biology and Bioinformatics Division, CSIR-Indian Institute of Chemical Biology, Kolkata, WB India
| | - Saikat Chakrabarti
- grid.417635.20000 0001 2216 5074Structural Biology and Bioinformatics Division, CSIR-Indian Institute of Chemical Biology, Kolkata, WB India
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8
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Chen G, Seukep AJ, Guo M. Recent Advances in Molecular Docking for the Research and Discovery of Potential Marine Drugs. Mar Drugs 2020; 18:md18110545. [PMID: 33143025 PMCID: PMC7692358 DOI: 10.3390/md18110545] [Citation(s) in RCA: 69] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 10/27/2020] [Accepted: 10/28/2020] [Indexed: 12/28/2022] Open
Abstract
Marine drugs have long been used and exhibit unique advantages in clinical practices. Among the marine drugs that have been approved by the Food and Drug Administration (FDA), the protein–ligand interactions, such as cytarabine–DNA polymerase, vidarabine–adenylyl cyclase, and eribulin–tubulin complexes, are the important mechanisms of action for their efficacy. However, the complex and multi-targeted components in marine medicinal resources, their bio-active chemical basis, and mechanisms of action have posed huge challenges in the discovery and development of marine drugs so far, which need to be systematically investigated in-depth. Molecular docking could effectively predict the binding mode and binding energy of the protein–ligand complexes and has become a major method of computer-aided drug design (CADD), hence this powerful tool has been widely used in many aspects of the research on marine drugs. This review introduces the basic principles and software of the molecular docking and further summarizes the applications of this method in marine drug discovery and design, including the early virtual screening in the drug discovery stage, drug target discovery, potential mechanisms of action, and the prediction of drug metabolism. In addition, this review would also discuss and prospect the problems of molecular docking, in order to provide more theoretical basis for clinical practices and new marine drug research and development.
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Affiliation(s)
- Guilin Chen
- Key Laboratory of Plant Germplasm Enhancement & Specialty Agriculture, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074, China; (G.C.); (A.J.S.)
- Sino-Africa Joint Research Center, Chinese Academy of Sciences, Wuhan 430074, China
- Innovation Academy for Drug Discovery and Development, Chinese Academy of Sciences, Shanghai 201203, China
| | - Armel Jackson Seukep
- Key Laboratory of Plant Germplasm Enhancement & Specialty Agriculture, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074, China; (G.C.); (A.J.S.)
- Sino-Africa Joint Research Center, Chinese Academy of Sciences, Wuhan 430074, China
- Innovation Academy for Drug Discovery and Development, Chinese Academy of Sciences, Shanghai 201203, China
- Department of Biomedical Sciences, Faculty of Health Sciences, University of Buea, P.O. Box 63 Buea, Cameroon
| | - Mingquan Guo
- Key Laboratory of Plant Germplasm Enhancement & Specialty Agriculture, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074, China; (G.C.); (A.J.S.)
- Sino-Africa Joint Research Center, Chinese Academy of Sciences, Wuhan 430074, China
- Innovation Academy for Drug Discovery and Development, Chinese Academy of Sciences, Shanghai 201203, China
- Correspondence: ; Tel.: +86-27-8770-0850
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9
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Yang L, Han Y, Zhang H, Li W, Dai Y. Prediction of Protein-Protein Interactions with Local Weight-Sharing Mechanism in Deep Learning. BIOMED RESEARCH INTERNATIONAL 2020; 2020:5072520. [PMID: 32626745 PMCID: PMC7312734 DOI: 10.1155/2020/5072520] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 03/04/2020] [Accepted: 05/21/2020] [Indexed: 12/30/2022]
Abstract
Protein-protein interactions (PPIs) are important for almost all cellular processes, including metabolic cycles, DNA transcription and replication, and signaling cascades. The experimental methods for identifying PPIs are always time-consuming and expensive. Therefore, it is important to develop computational approaches for predicting PPIs. In this paper, an improved model is proposed to use a machine learning method in the study of protein-protein interactions. With the consideration of the factors affecting the prediction of the PPIs, a method of feature extraction and fusion is proposed to improve the variety of the features to be considered in the prediction. Besides, with the consideration of the effect affected by the different input order of the two proteins, we propose a "Y-type" Bi-RNN model and train the network by using a method which both needs backward and forward training. In order to insure the training time caused on the extra training either a backward one or a forward one, this paper proposes a weight-sharing policy to minimize the parameters in the training. The experimental results show that the proposed method can achieve an accuracy of 99.57%, recall of 99.36%, sensitivity of 99.76%, precision of 99.74%, MCC of 99.14%, and AUC of 99.56% under the benchmark dataset.
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Affiliation(s)
- Lei Yang
- College of Computer Science and Engineering, Northeastern University, Shenyang, China
- Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, China
| | - Yukun Han
- College of Computer Science and Engineering, Northeastern University, Shenyang, China
| | - Huixue Zhang
- College of Computer Science and Engineering, Northeastern University, Shenyang, China
| | - Wenlong Li
- College of Software, Northeastern University, Shenyang, China
| | - Yu Dai
- College of Software, Northeastern University, Shenyang, China
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10
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Sahoo L, Sahoo S, Mohanty M, Sankar M, Dixit S, Das P, Rasal KD, Rather MA, Sundaray JK. Molecular characterization, computational analysis and expression profiling of Dmrt1 gene in Indian major carp, Labeo rohita (Hamilton 1822). Anim Biotechnol 2019; 32:413-426. [PMID: 31880491 DOI: 10.1080/10495398.2019.1707683] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Sexual dimorphism of fish morphology, physiology and behavior is diverse and complex in nature. Doublesex and mab-3 related transcription factor (Dmrt) is a large protein family whose function is sexual development and differentiation in vertebrates. Here, we report a full-length cDNA sequence of Labeo rohita (rohu) Dmrt1 of 907 bp length having 798 bp of open reading frame encoding 265 amino acids. The molecular weight of rohu DMRT1 protein was found to be 28.74 KDa and isoelectric point was 7.53. DMRT1 protein contains 23 positively and 24 negatively charged amino acids with a GRAVY score of -0.618. A characteristic DM domain was found in DMRT1 protein, which is a novel DNA-binding domain. Phylogenetic analysis showed maximum similarity with Cyprinus carpio when compared with DMRT1 of other vertebrates. Molecular docking study identified active sites to be targeted for drug designing. Rohu DMRT1 was observed to interact with other proteins such as FOXL2, CYP19a1a, AMH and SOX9a. Differential expression study revealed higher expression in testis tissue implying its role in male sex differentiation and testicular development. The information generated in the present work could facilitate further research to resolve the issues related to gonadal maturation and reproduction of commercially important aquaculture species.
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Affiliation(s)
- L Sahoo
- Fish Genetics and Biotechnology Division, ICAR-Central Institute of Freshwater Aquaculture, Bhubaneswar, Odisha, India
| | - S Sahoo
- Fish Genetics and Biotechnology Division, ICAR-Central Institute of Freshwater Aquaculture, Bhubaneswar, Odisha, India
| | - M Mohanty
- Fish Genetics and Biotechnology Division, ICAR-Central Institute of Freshwater Aquaculture, Bhubaneswar, Odisha, India
| | - M Sankar
- ICAR-Central Marine Research Institute, Mandapam Regional Centre, Tamil Nadu, India
| | - S Dixit
- Fish Genetics and Biotechnology Division, ICAR-Central Institute of Freshwater Aquaculture, Bhubaneswar, Odisha, India
| | - P Das
- Fish Genetics and Biotechnology Division, ICAR-Central Institute of Freshwater Aquaculture, Bhubaneswar, Odisha, India
| | - K D Rasal
- Fish Genetics and Biotechnology Division, ICAR-Central Institute of Freshwater Aquaculture, Bhubaneswar, Odisha, India
| | - M A Rather
- Division of Fish genetics and Biotechnology, Faculty of Fisheries, Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir, Srinagar, Jammu and Kashmir, India
| | - J K Sundaray
- Fish Genetics and Biotechnology Division, ICAR-Central Institute of Freshwater Aquaculture, Bhubaneswar, Odisha, India
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Abstract
Background Protein-protein docking is a valuable computational approach for investigating protein-protein interactions. Shape complementarity is the most basic component of a scoring function and plays an important role in protein-protein docking. Despite significant progresses, shape representation remains an open question in the development of protein-protein docking algorithms, especially for grid-based docking approaches. Results We have proposed a new pairwise shape-based scoring function (LSC) for protein-protein docking which adopts an exponential form to take into account long-range interactions between protein atoms. The LSC scoring function was incorporated into our FFT-based docking program and evaluated for both bound and unbound docking on the protein docking benchmark 4.0. It was shown that our LSC achieved a significantly better performance than four other similar docking methods, ZDOCK 2.1, MolFit/G, GRAMM, and FTDock/G, in both success rate and number of hits. When considering the top 10 predictions, LSC obtained a success rate of 51.71% and 6.82% for bound and unbound docking, respectively, compared to 42.61% and 4.55% for the second-best program ZDOCK 2.1. LSC also yielded an average of 8.38 and 3.94 hits per complex in the top 1000 predictions for bound and unbound docking, respectively, followed by 6.38 and 2.96 hits for the second-best ZDOCK 2.1. Conclusions The present LSC method will not only provide an initial-stage docking approach for post-docking processes but also have a general implementation for accurate representation of other energy terms on grids in protein-protein docking. The software has been implemented in our HDOCK web server at http://hdock.phys.hust.edu.cn/.
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12
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Wang H, Li H. Research on theoretical analysis of human capital of labor economics based on artificial intelligence. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2019. [DOI: 10.3233/jifs-179127] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Haibo Wang
- Economics School, Dongbei University of Finance and Economics, Dalian, China
| | - Hua Li
- Economics School, Dongbei University of Finance and Economics, Dalian, China
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13
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Zhang C, Guan Y. Research on related technologies of vision target tracking based on discrete differential algorithm for deep learning. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2019. [DOI: 10.3233/jifs-179128] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Changqi Zhang
- School of Communication and Information Engineering, Shanghai University, Shanghai, China
| | - Yepeng Guan
- School of Communication and Information Engineering, Shanghai University, Shanghai, China
- Key Laboratory of Advanced Displays and System Application, Ministry of Education, Shanghai, China
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14
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Ding B, Chen W, Huang Y. The construction of internet data mining model based on cloud computing. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2019. [DOI: 10.3233/jifs-179129] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Bangxu Ding
- Department of Mathematics and Computer Science, Tongling University, Tongling, Anhui, China
| | - Wen Chen
- Department of Mathematics and Computer Science, Tongling University, Tongling, Anhui, China
| | - Yongqing Huang
- Department of Mathematics and Computer Science, Tongling University, Tongling, Anhui, China
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15
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Lyu X, Gong E. Intelligent clustering analysis model for mining area mineral resource prediction. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2019. [DOI: 10.3233/jifs-179110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Xiaodong Lyu
- School of Resources and Civil Engineering, Northeastern University, Shenyang, China
| | - Enpu Gong
- School of Resources and Civil Engineering, Northeastern University, Shenyang, China
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Neveu E, Popov P, Hoffmann A, Migliosi A, Besseron X, Danoy G, Bouvry P, Grudinin S. RapidRMSD: rapid determination of RMSDs corresponding to motions of flexible molecules. Bioinformatics 2019; 34:2757-2765. [PMID: 29554205 DOI: 10.1093/bioinformatics/bty160] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2017] [Accepted: 03/13/2018] [Indexed: 12/27/2022] Open
Abstract
Motivation The root mean square deviation (RMSD) is one of the most used similarity criteria in structural biology and bioinformatics. Standard computation of the RMSD has a linear complexity with respect to the number of atoms in a molecule, making RMSD calculations time-consuming for the large-scale modeling applications, such as assessment of molecular docking predictions or clustering of spatially proximate molecular conformations. Previously, we introduced the RigidRMSD algorithm to compute the RMSD corresponding to the rigid-body motion of a molecule. In this study, we go beyond the limits of the rigid-body approximation by taking into account conformational flexibility of the molecule. We model the flexibility with a reduced set of collective motions computed with e.g. normal modes or principal component analysis. Results The initialization of our algorithm is linear in the number of atoms and all the subsequent evaluations of RMSD values between flexible molecular conformations depend only on the number of collective motions that are selected to model the flexibility. Therefore, our algorithm is much faster compared to the standard RMSD computation for large-scale modeling applications. We demonstrate the efficiency of our method on several clustering examples, including clustering of flexible docking results and molecular dynamics (MD) trajectories. We also demonstrate how to use the presented formalism to generate pseudo-random constant-RMSD structural molecular ensembles and how to use these in cross-docking. Availability and implementation We provide the algorithm written in C++ as the open-source RapidRMSD library governed by the BSD-compatible license, which is available at http://team.inria.fr/nano-d/software/RapidRMSD/. The constant-RMSD structural ensemble application and clustering of MD trajectories is available at http://team.inria.fr/nano-d/software/nolb-normal-modes/. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Emilie Neveu
- Inria/Univ. Grenoble Alpes/LJK-CNRS, Grenoble, France.,Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Petr Popov
- Inria/Univ. Grenoble Alpes/LJK-CNRS, Grenoble, France.,Moscow Institute of Physics and Technology, Dolgoprudniy, Russia
| | | | - Angelo Migliosi
- Faculté des Sciences, de la Technologie et de la Communication, University of Luxembourg, Luxembourg, Luxembourg
| | - Xavier Besseron
- Faculté des Sciences, de la Technologie et de la Communication, University of Luxembourg, Luxembourg, Luxembourg
| | - Grégoire Danoy
- Faculté des Sciences, de la Technologie et de la Communication, University of Luxembourg, Luxembourg, Luxembourg
| | - Pascal Bouvry
- Faculté des Sciences, de la Technologie et de la Communication, University of Luxembourg, Luxembourg, Luxembourg
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Geng C, Xue LC, Roel‐Touris J, Bonvin AMJJ. Finding the ΔΔ
G
spot: Are predictors of binding affinity changes upon mutations in protein–protein interactions ready for it? WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2019. [DOI: 10.1002/wcms.1410] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- Cunliang Geng
- Bijvoet Center for Biomolecular Research, Faculty of Science—Chemistry Utrecht University Utrecht The Netherlands
| | - Li C. Xue
- Bijvoet Center for Biomolecular Research, Faculty of Science—Chemistry Utrecht University Utrecht The Netherlands
| | - Jorge Roel‐Touris
- Bijvoet Center for Biomolecular Research, Faculty of Science—Chemistry Utrecht University Utrecht The Netherlands
| | - Alexandre M. J. J. Bonvin
- Bijvoet Center for Biomolecular Research, Faculty of Science—Chemistry Utrecht University Utrecht The Netherlands
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18
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Gupta M, Sharma R, Kumar A. Docking techniques in pharmacology: How much promising? Comput Biol Chem 2018; 76:210-217. [PMID: 30067954 DOI: 10.1016/j.compbiolchem.2018.06.005] [Citation(s) in RCA: 88] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2017] [Revised: 02/21/2018] [Accepted: 06/30/2018] [Indexed: 01/01/2023]
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19
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20
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Macalino SJY, Basith S, Clavio NAB, Chang H, Kang S, Choi S. Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery. Molecules 2018; 23:E1963. [PMID: 30082644 PMCID: PMC6222862 DOI: 10.3390/molecules23081963] [Citation(s) in RCA: 62] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2018] [Revised: 08/03/2018] [Accepted: 08/04/2018] [Indexed: 12/14/2022] Open
Abstract
The advent of advanced molecular modeling software, big data analytics, and high-speed processing units has led to the exponential evolution of modern drug discovery and better insights into complex biological processes and disease networks. This has progressively steered current research interests to understanding protein-protein interaction (PPI) systems that are related to a number of relevant diseases, such as cancer, neurological illnesses, metabolic disorders, etc. However, targeting PPIs are challenging due to their "undruggable" binding interfaces. In this review, we focus on the current obstacles that impede PPI drug discovery, and how recent discoveries and advances in in silico approaches can alleviate these barriers to expedite the search for potential leads, as shown in several exemplary studies. We will also discuss about currently available information on PPI compounds and systems, along with their usefulness in molecular modeling. Finally, we conclude by presenting the limits of in silico application in drug discovery and offer a perspective in the field of computer-aided PPI drug discovery.
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Affiliation(s)
- Stephani Joy Y Macalino
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea.
| | - Shaherin Basith
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea.
| | - Nina Abigail B Clavio
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea.
| | - Hyerim Chang
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea.
| | - Soosung Kang
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea.
| | - Sun Choi
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea.
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21
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Nóbrega CS, Pauleta SR. Interaction between Neisseria gonorrhoeae bacterial peroxidase and its electron donor, the lipid-modified azurin. FEBS Lett 2018; 592:1473-1483. [PMID: 29665008 DOI: 10.1002/1873-3468.13053] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Revised: 04/04/2018] [Accepted: 04/06/2018] [Indexed: 11/05/2022]
Abstract
The Neisseria gonorrhoeae bacterial cytochrome c peroxidase plays a key role in detoxifying the cells from H2 O2 by reducing it to water using the lipid-modified azurin, LAz, a small type 1 copper protein, as electron donor. Here, the interaction between these two proteins was characterized by steady-state kinetics, two-dimensional NMR and molecular docking simulations. LAz is an efficient electron donor capable of activating this enzyme. This electron transfer complex is weak with a hydrophobic character, with LAz binding close to the electron transferring heme of the enzyme. The high catalytic rate (39 ± 0.03 s-1 ) is explained by the LAz pre-orientation, due to a positive dipole moment, and by the fast-dynamic ensemble of orientations, suggested by the small chemical shifts.
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Affiliation(s)
- Cláudia S Nóbrega
- Microbial Stress Lab, UCIBIO, REQUIMTE, Department of Química, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal
| | - Sofia R Pauleta
- Microbial Stress Lab, UCIBIO, REQUIMTE, Department of Química, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal
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22
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The NMR2 Method to Determine Rapidly the Structure of the Binding Pocket of a Protein–Ligand Complex with High Accuracy. MAGNETOCHEMISTRY 2018. [DOI: 10.3390/magnetochemistry4010012] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Structural characterization of complexes is crucial for a better understanding of biological processes and structure-based drug design. However, many protein–ligand structures are not solvable by X-ray crystallography, for example those with low affinity binders or dynamic binding sites. Such complexes are usually targeted by solution-state NMR spectroscopy. Unfortunately, structure calculation by NMR is very time consuming since all atoms in the complex need to be assigned to their respective chemical shifts. To circumvent this problem, we recently developed the Nuclear Magnetic Resonance Molecular Replacement (NMR2) method. NMR2 very quickly provides the complex structure of a binding pocket as measured by solution-state NMR. NMR2 circumvents the assignment of the protein by using previously determined structures and therefore speeds up the whole process from a couple of months to a couple of days. Here, we recall the main aspects of the method, show how to apply it, discuss its advantages over other methods and outline its limitations and future directions.
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23
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Samhan-Arias AK, Almeida RM, Ramos S, Cordas CM, Moura I, Gutierrez-Merino C, Moura JJG. Topography of human cytochrome b 5/cytochrome b 5 reductase interacting domain and redox alterations upon complex formation. BIOCHIMICA ET BIOPHYSICA ACTA-BIOENERGETICS 2017; 1859:78-87. [PMID: 28958890 DOI: 10.1016/j.bbabio.2017.10.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 08/17/2017] [Revised: 10/23/2017] [Accepted: 10/27/2017] [Indexed: 10/18/2022]
Abstract
Cytochrome b5 is the main electron acceptor of cytochrome b5 reductase. The interacting domain between both human proteins has been unidentified up to date and very little is known about its redox properties modulation upon complex formation. In this article, we characterized the protein/protein interacting interface by solution NMR and molecular docking. In addition, upon complex formation, we measured an increase of cytochrome b5 reductase flavin autofluorescence that was dependent upon the presence of cytochrome b5. Data analysis of these results allowed us to calculate a dissociation constant value between proteins of 0.5±0.1μM and a 1:1 stoichiometry for the complex formation. In addition, a 30mV negative shift of cytochrome b5 reductase redox potential in presence of cytochrome b5 was also measured. These experiments suggest that the FAD group of cytochrome b5 reductase increase its solvent exposition upon complex formation promoting an efficient electron transfer between the proteins.
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Affiliation(s)
- Alejandro K Samhan-Arias
- UCIBIO, REQUIMTE, Departamento de Química, Faculdade de Ciências e Tecnologia, NOVA, 2829-516 Caparica, Portugal.
| | - Rui M Almeida
- UCIBIO, REQUIMTE, Departamento de Química, Faculdade de Ciências e Tecnologia, NOVA, 2829-516 Caparica, Portugal
| | - Susana Ramos
- UCIBIO, REQUIMTE, Departamento de Química, Faculdade de Ciências e Tecnologia, NOVA, 2829-516 Caparica, Portugal
| | - Cristina M Cordas
- UCIBIO, REQUIMTE, Departamento de Química, Faculdade de Ciências e Tecnologia, NOVA, 2829-516 Caparica, Portugal
| | - Isabel Moura
- UCIBIO, REQUIMTE, Departamento de Química, Faculdade de Ciências e Tecnologia, NOVA, 2829-516 Caparica, Portugal
| | - Carlos Gutierrez-Merino
- Department of Biochemistry and Molecular Biology, Faculty of Sciences, Institute of Molecular Pathology Biomarkers, University of Extremadura, 06006 Badajoz, Spain
| | - José J G Moura
- UCIBIO, REQUIMTE, Departamento de Química, Faculdade de Ciências e Tecnologia, NOVA, 2829-516 Caparica, Portugal.
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24
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González-Arzola K, Díaz-Quintana A, Rivero-Rodríguez F, Velázquez-Campoy A, De la Rosa MA, Díaz-Moreno I. Histone chaperone activity of Arabidopsis thaliana NRP1 is blocked by cytochrome c. Nucleic Acids Res 2017; 45:2150-2165. [PMID: 27924001 PMCID: PMC5389710 DOI: 10.1093/nar/gkw1215] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2016] [Accepted: 11/22/2016] [Indexed: 12/21/2022] Open
Abstract
Higher-order plants and mammals use similar mechanisms to repair and tolerate oxidative DNA damage. Most studies on the DNA repair process have focused on yeast and mammals, in which histone chaperone-mediated nucleosome disassembly/reassembly is essential for DNA to be accessible to repair machinery. However, little is known about the specific role and modulation of histone chaperones in the context of DNA damage in plants. Here, the histone chaperone NRP1, which is closely related to human SET/TAF-Iβ, was found to exhibit nucleosome assembly activity in vitro and to accumulate in the chromatin of Arabidopsis thaliana after DNA breaks. In addition, this work establishes that NRP1 binds to cytochrome c, thereby preventing the former from binding to histones. Since NRP1 interacts with cytochrome c at its earmuff domain, that is, its histone-binding domain, cytochrome c thus competes with core histones and hampers the activity of NRP1 as a histone chaperone. Altogether, the results obtained indicate that the underlying molecular mechanisms in nucleosome disassembly/reassembly are highly conserved throughout evolution, as inferred from the similar inhibition of plant NRP1 and human SET/TAF-Iβ by cytochrome c during DNA damage response.
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Affiliation(s)
- Katiuska González-Arzola
- Institute for Chemical Research (IIQ), Isla de la Cartuja Scientific Research Centre (cicCartuja), University of Seville-Spanish National Research Council (CSIC), Avda. Américo Vespucio 49, 41092 Sevilla, Spain
| | - Antonio Díaz-Quintana
- Institute for Chemical Research (IIQ), Isla de la Cartuja Scientific Research Centre (cicCartuja), University of Seville-Spanish National Research Council (CSIC), Avda. Américo Vespucio 49, 41092 Sevilla, Spain
| | - Francisco Rivero-Rodríguez
- Institute for Chemical Research (IIQ), Isla de la Cartuja Scientific Research Centre (cicCartuja), University of Seville-Spanish National Research Council (CSIC), Avda. Américo Vespucio 49, 41092 Sevilla, Spain
| | - Adrián Velázquez-Campoy
- Institute for Biocomputation and Physics of Complex Systems (BIFI), Joint Unit Institute of Physical Chemistry Rocasolano (IQFR)-BIFI-Spanish National Research Council (CSIC), University of Zaragoza, Mariano Esquillor s/n, 50018 Zaragoza, Spain.,Department of Biochemistry and Molecular and Cellular Biology, University of Zaragoza, Pedro Cerbuna 12, 50009 Zaragoza (Spain); and Aragon Agency for Research and Development (ARAID), Regional Government of Aragon, Maria de Luna 11, 50018 Zaragoza, Spain
| | - Miguel A De la Rosa
- Institute for Chemical Research (IIQ), Isla de la Cartuja Scientific Research Centre (cicCartuja), University of Seville-Spanish National Research Council (CSIC), Avda. Américo Vespucio 49, 41092 Sevilla, Spain
| | - Irene Díaz-Moreno
- Institute for Chemical Research (IIQ), Isla de la Cartuja Scientific Research Centre (cicCartuja), University of Seville-Spanish National Research Council (CSIC), Avda. Américo Vespucio 49, 41092 Sevilla, Spain
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25
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Yu Z, Li P, Merz KM. Using Ligand-Induced Protein Chemical Shift Perturbations To Determine Protein–Ligand Structures. Biochemistry 2017; 56:2349-2362. [DOI: 10.1021/acs.biochem.7b00170] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Affiliation(s)
- Zhuoqin Yu
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824-1322, United States
| | - Pengfei Li
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824-1322, United States
| | - Kenneth M. Merz
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824-1322, United States
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26
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Molecular Simulations of Disulfide-Rich Venom Peptides with Ion Channels and Membranes. Molecules 2017; 22:molecules22030362. [PMID: 28264446 PMCID: PMC6155311 DOI: 10.3390/molecules22030362] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2017] [Revised: 02/23/2017] [Accepted: 02/24/2017] [Indexed: 12/12/2022] Open
Abstract
Disulfide-rich peptides isolated from the venom of arthropods and marine animals are a rich source of potent and selective modulators of ion channels. This makes these peptides valuable lead molecules for the development of new drugs to treat neurological disorders. Consequently, much effort goes into understanding their mechanism of action. This paper presents an overview of how molecular simulations have been used to study the interactions of disulfide-rich venom peptides with ion channels and membranes. The review is focused on the use of docking, molecular dynamics simulations, and free energy calculations to (i) predict the structure of peptide-channel complexes; (ii) calculate binding free energies including the effect of peptide modifications; and (iii) study the membrane-binding properties of disulfide-rich venom peptides. The review concludes with a summary and outlook.
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27
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Zhang Z, Ehmann U, Zacharias M. Monte Carlo replica-exchange based ensemble docking of protein conformations. Proteins 2017; 85:924-937. [DOI: 10.1002/prot.25262] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2016] [Revised: 01/11/2017] [Accepted: 01/19/2017] [Indexed: 12/14/2022]
Affiliation(s)
- Zhe Zhang
- Physik-Department T38; Technische Universität München; Garching 85748 Germany
- Department Chemie; Technische Universität München, Biomolecular NMR and Munich Center for Integrated Protein Science; Garching 85747 Germany
- College of Life and Health Sciences; Northeast University; Shenyang P.R. China
| | - Uwe Ehmann
- Physik-Department T38; Technische Universität München; Garching 85748 Germany
| | - Martin Zacharias
- Physik-Department T38; Technische Universität München; Garching 85748 Germany
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28
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Pagadala NS, Syed K, Tuszynski J. Software for molecular docking: a review. Biophys Rev 2017; 9:91-102. [PMID: 28510083 DOI: 10.1007/s12551-016-0247-1] [Citation(s) in RCA: 654] [Impact Index Per Article: 93.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2016] [Accepted: 12/27/2016] [Indexed: 11/26/2022] Open
Abstract
Molecular docking methodology explores the behavior of small molecules in the binding site of a target protein. As more protein structures are determined experimentally using X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy, molecular docking is increasingly used as a tool in drug discovery. Docking against homology-modeled targets also becomes possible for proteins whose structures are not known. With the docking strategies, the druggability of the compounds and their specificity against a particular target can be calculated for further lead optimization processes. Molecular docking programs perform a search algorithm in which the conformation of the ligand is evaluated recursively until the convergence to the minimum energy is reached. Finally, an affinity scoring function, ΔG [U total in kcal/mol], is employed to rank the candidate poses as the sum of the electrostatic and van der Waals energies. The driving forces for these specific interactions in biological systems aim toward complementarities between the shape and electrostatics of the binding site surfaces and the ligand or substrate.
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Affiliation(s)
- Nataraj S Pagadala
- Department of Medical Microbiology and Immunology, Li Ka Shing Institute of Virology, 6-020 Katz Group Centre, University of Alberta, Edmonton, Alberta, T6G 2E1, Canada.
| | - Khajamohiddin Syed
- Unit for Drug Discovery Research, Department of Health Sciences, Faculty of Health and Environmental Sciences, Central University of Technology, Bloemfontein, 9300, Free State, South Africa
| | - Jack Tuszynski
- Department of Experimental Oncology, Cross Cancer Institute, Edmonton, Alberta, Canada
- Department of Physics, University of Alberta, Edmonton, Alberta, Canada
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29
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Vishwanath S, Sukhwal A, Sowdhamini R, Srinivasan N. Specificity and stability of transient protein-protein interactions. Curr Opin Struct Biol 2017; 44:77-86. [PMID: 28088083 DOI: 10.1016/j.sbi.2016.12.010] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2016] [Revised: 11/03/2016] [Accepted: 12/19/2016] [Indexed: 11/18/2022]
Abstract
Remarkable features that are achieved in a protein-protein complex to precise levels are stability and specificity. Deviation from the normal levels of specificity and stability, which is often caused by mutations, could result in disease conditions. Chemical nature, 3-D arrangement and dynamics of interface residues code for both specificity and stability. This article reviews roles of interfacial residues in transient protein-protein complexes. It is proposed that aside from hotspot residues conferring stability to the complex, a small set of 'rigid' residues at the interface that maintain conformation between complexed and uncomplexed forms, play a major role in conferring specificity. Exceptionally, 'super hotspot' residues, which confer both stability and specificity, are attractive sites for interaction with small molecule inhibitors.
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Affiliation(s)
- Sneha Vishwanath
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560012, India
| | - Anshul Sukhwal
- National Centre for Biological Sciences, TIFR, UAS-GKVK Campus, Bellary road, Bangalore 560065, India; SASTRA Deemed University, Tirumalai Samudram, Thanjavur 613402, India
| | - Ramanathan Sowdhamini
- National Centre for Biological Sciences, TIFR, UAS-GKVK Campus, Bellary road, Bangalore 560065, India
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30
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Abstract
Today, the development of new drugs is a challenging task of science. Researchers already applied molecular docking in the drug design field to simulate ligand- receptor interactions. Docking is a term used for computational schemes that attempt to find the “best” matching between two molecules in a complex formed from constituent molecules. It has a wide range of uses and applications in drug discovery. However, some defects still exist; the accuracy and speed of docking calculation is a challenge to explore and these methods can be enhanced as a solution to docking problem. The molecular docking problem can be defined as follows: Given the atomic coordinates of two molecules, predict their “correct” bound association. The chapter discusses common challenges critical aspects of docking method such as ligand- and receptor- conformation, flexibility and cavity detection, etc. It emphasis to the challenges and inadequacies with the theories behind as well as the examples.
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31
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Hasani HJ, Barakat KH. Protein-Protein Docking. PHARMACEUTICAL SCIENCES 2017. [DOI: 10.4018/978-1-5225-1762-7.ch042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Protein-protein docking algorithms are powerful computational tools, capable of analyzing the protein-protein interactions at the atomic-level. In this chapter, we will review the theoretical concepts behind different protein-protein docking algorithms, highlighting their strengths as well as their limitations and pointing to important case studies for each method. The methods we intend to cover in this chapter include various search strategies and scoring techniques. This includes exhaustive global search, fast Fourier transform search, spherical Fourier transform-based search, direct search in Cartesian space, local shape feature matching, geometric hashing, genetic algorithm, randomized search, and Monte Carlo search. We will also discuss the different ways that have been used to incorporate protein flexibility within the docking procedure and some other future directions in this field, suggesting possible ways to improve the different methods.
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32
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Trana EN, Nocek JM, Woude JV, Span I, Smith SM, Rosenzweig AC, Hoffman BM. Charge-Disproportionation Symmetry Breaking Creates a Heterodimeric Myoglobin Complex with Enhanced Affinity and Rapid Intracomplex Electron Transfer. J Am Chem Soc 2016; 138:12615-28. [PMID: 27646786 DOI: 10.1021/jacs.6b07672] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
We report rapid photoinitiated intracomplex electron transfer (ET) within a "charge-disproportionated" myoglobin (Mb) dimer with greatly enhanced affinity. Two mutually supportive Brownian Dynamics (BD) interface redesign strategies, one a new "heme-filtering" approach, were employed to "break the symmetry" of a Mb homodimer by pairing Mb constructs with complementary highly positive and highly negative net surface charges, introduced through D/E → K and K → E mutations, respectively. BD simulations using a previously developed positive mutant, Mb(+6) = Mb(D44K/D60K/E85K), led to construction of the complementary negative mutant Mb(-6) = Mb(K45E, K63E, K95E). Simulations predict the pair will form a well-defined complex comprising a tight ensemble of conformations with nearly parallel hemes, at a metal-metal distance ∼18-19 Å. Upon expression and X-ray characterization of the partners, BD predictions were verified through ET photocycle measurements enabled by Zn-deuteroporphyrin substitution, forming the [ZnMb(-6), Fe(3+)Mb(+6)] complex. Triplet ET quenching shows charge disproportionation increases the binding constant by no less than ∼5 orders of magnitude relative to wild-type Mb values. All progress curves for charge separation (CS) and charge recombination (CR) are reproduced by a generalized kinetic model for the interprotein ET photocycle. The intracomplex ET rate constants for both CS and CR are increased by over 5 orders of magnitude, and their viscosity independence is indicative of true interprotein ET, rather than dynamic gating as seen in previous studies. The complex displays an unprecedented timecourse for CR of the CS intermediate I. After a laser flash, I forms through photoinduced CS, accumulates to a maximum concentration, then dies away through CR. However, before completely disappearing, I reappears without another flash and reaches a second maximum before disappearing completely.
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Affiliation(s)
- Ethan N Trana
- Department of Chemistry, Northwestern University , Evanston, Illinois 60208, United States
| | - Judith M Nocek
- Department of Chemistry, Northwestern University , Evanston, Illinois 60208, United States
| | - Jon Vander Woude
- Department of Chemistry, Northwestern University , Evanston, Illinois 60208, United States
| | - Ingrid Span
- Department of Molecular Biosciences, Northwestern University , Evanston, Illinois 60208, United States
| | - Stephen M Smith
- Department of Molecular Biosciences, Northwestern University , Evanston, Illinois 60208, United States
| | - Amy C Rosenzweig
- Department of Chemistry, Northwestern University , Evanston, Illinois 60208, United States.,Department of Molecular Biosciences, Northwestern University , Evanston, Illinois 60208, United States
| | - Brian M Hoffman
- Department of Chemistry, Northwestern University , Evanston, Illinois 60208, United States.,Department of Molecular Biosciences, Northwestern University , Evanston, Illinois 60208, United States
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33
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Electron transfer and docking between cytochrome cd 1 nitrite reductase and different redox partners — A comparative study. BIOCHIMICA ET BIOPHYSICA ACTA-BIOENERGETICS 2016; 1857:1412-1421. [DOI: 10.1016/j.bbabio.2016.04.279] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2016] [Revised: 03/30/2016] [Accepted: 04/27/2016] [Indexed: 11/21/2022]
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34
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Almeida RM, Dell'Acqua S, Krippahl L, Moura JJG, Pauleta SR. Predicting Protein-Protein Interactions Using BiGGER: Case Studies. Molecules 2016; 21:E1037. [PMID: 27517887 PMCID: PMC6274584 DOI: 10.3390/molecules21081037] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2016] [Revised: 08/03/2016] [Accepted: 08/04/2016] [Indexed: 11/29/2022] Open
Abstract
The importance of understanding interactomes makes preeminent the study of protein interactions and protein complexes. Traditionally, protein interactions have been elucidated by experimental methods or, with lower impact, by simulation with protein docking algorithms. This article describes features and applications of the BiGGER docking algorithm, which stands at the interface of these two approaches. BiGGER is a user-friendly docking algorithm that was specifically designed to incorporate experimental data at different stages of the simulation, to either guide the search for correct structures or help evaluate the results, in order to combine the reliability of hard data with the convenience of simulations. Herein, the applications of BiGGER are described by illustrative applications divided in three Case Studies: (Case Study A) in which no specific contact data is available; (Case Study B) when different experimental data (e.g., site-directed mutagenesis, properties of the complex, NMR chemical shift perturbation mapping, electron tunneling) on one of the partners is available; and (Case Study C) when experimental data are available for both interacting surfaces, which are used during the search and/or evaluation stage of the docking. This algorithm has been extensively used, evidencing its usefulness in a wide range of different biological research fields.
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Affiliation(s)
- Rui M Almeida
- UCIBIO, REQUIMTE, Departamento de Química, Faculdade de Ciências e Tecnologia, NOVA, 2829-516 Caparica, Portugal.
| | - Simone Dell'Acqua
- Department of Chemistry, University of Pavia, Via Taramelli 12, 27100 Pavia, Italy.
| | - Ludwig Krippahl
- CENTRIA, Departamento de Informática, Faculdade de Ciências e Tecnologia, NOVA, 2829-516 Caparica, Portugal.
| | - José J G Moura
- UCIBIO, REQUIMTE, Departamento de Química, Faculdade de Ciências e Tecnologia, NOVA, 2829-516 Caparica, Portugal.
| | - Sofia R Pauleta
- UCIBIO, REQUIMTE, Departamento de Química, Faculdade de Ciências e Tecnologia, NOVA, 2829-516 Caparica, Portugal.
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35
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Sarti E, Gladich I, Zamuner S, Correia BE, Laio A. Protein-protein structure prediction by scoring molecular dynamics trajectories of putative poses. Proteins 2016; 84:1312-20. [DOI: 10.1002/prot.25079] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2016] [Revised: 04/27/2016] [Accepted: 05/19/2016] [Indexed: 12/28/2022]
Affiliation(s)
| | | | | | - Bruno E. Correia
- Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale De Lausanne; Lausanne Switzerland
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36
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Ghasemi JB, Abdolmaleki A, Shiri F. Molecular Docking Challenges and Limitations. ADVANCES IN MEDICAL TECHNOLOGIES AND CLINICAL PRACTICE 2016. [DOI: 10.4018/978-1-5225-0362-0.ch003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Today, the development of new drugs is a challenging task of science. Researchers already applied molecular docking in the drug design field to simulate ligand- receptor interactions. Docking is a term used for computational schemes that attempt to find the “best” matching between two molecules in a complex formed from constituent molecules. It has a wide range of uses and applications in drug discovery. However, some defects still exist; the accuracy and speed of docking calculation is a challenge to explore and these methods can be enhanced as a solution to docking problem. The molecular docking problem can be defined as follows: Given the atomic coordinates of two molecules, predict their “correct” bound association. The chapter discusses common challenges critical aspects of docking method such as ligand- and receptor- conformation, flexibility and cavity detection, etc. It emphasis to the challenges and inadequacies with the theories behind as well as the examples.
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Surfing the Protein-Protein Interaction Surface Using Docking Methods: Application to the Design of PPI Inhibitors. Molecules 2015; 20:11569-603. [PMID: 26111183 PMCID: PMC6272567 DOI: 10.3390/molecules200611569] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2015] [Revised: 06/02/2015] [Accepted: 06/15/2015] [Indexed: 02/06/2023] Open
Abstract
Blocking protein-protein interactions (PPI) using small molecules or peptides modulates biochemical pathways and has therapeutic significance. PPI inhibition for designing drug-like molecules is a new area that has been explored extensively during the last decade. Considering the number of available PPI inhibitor databases and the limited number of 3D structures available for proteins, docking and scoring methods play a major role in designing PPI inhibitors as well as stabilizers. Docking methods are used in the design of PPI inhibitors at several stages of finding a lead compound, including modeling the protein complex, screening for hot spots on the protein-protein interaction interface and screening small molecules or peptides that bind to the PPI interface. There are three major challenges to the use of docking on the relatively flat surfaces of PPI. In this review we will provide some examples of the use of docking in PPI inhibitor design as well as its limitations. The combination of experimental and docking methods with improved scoring function has thus far resulted in few success stories of PPI inhibitors for therapeutic purposes. Docking algorithms used for PPI are in the early stages, however, and as more data are available docking will become a highly promising area in the design of PPI inhibitors or stabilizers.
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Sturlese M, Bellanda M, Moro S. NMR-Assisted Molecular Docking Methodologies. Mol Inform 2015; 34:513-25. [DOI: 10.1002/minf.201500012] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2015] [Accepted: 04/24/2015] [Indexed: 11/11/2022]
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Krippahl L, Barahona P. Protein docking with predicted constraints. Algorithms Mol Biol 2015; 10:9. [PMID: 25722738 PMCID: PMC4340843 DOI: 10.1186/s13015-015-0036-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2014] [Accepted: 01/29/2015] [Indexed: 11/30/2022] Open
Abstract
This paper presents a constraint-based method for improving protein docking results. Efficient constraint propagation cuts over 95% of the search time for finding the configurations with the largest contact surface, provided a contact is specified between two amino acid residues. This makes it possible to scan a large number of potentially correct constraints, lowering the requirements for useful contact predictions. While other approaches are very dependent on accurate contact predictions, ours requires only that at least one correct contact be retained in a set of, for example, one hundred constraints to test. It is this feature that makes it feasible to use readily available sequence data to predict specific potential contacts. Although such prediction is too inaccurate for most purposes, we demonstrate with a Naïve Bayes Classifier that it is accurate enough to more than double the average number of acceptable models retained during the crucial filtering stage of protein docking when combined with our constrained docking algorithm. All software developed in this work is freely available as part of the Open Chemera Library.
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Huang SY. Search strategies and evaluation in protein–protein docking: principles, advances and challenges. Drug Discov Today 2014; 19:1081-96. [DOI: 10.1016/j.drudis.2014.02.005] [Citation(s) in RCA: 87] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2013] [Revised: 01/04/2014] [Accepted: 02/24/2014] [Indexed: 01/10/2023]
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Martínez-Fábregas J, Díaz-Moreno I, González-Arzola K, Janocha S, Navarro JA, Hervás M, Bernhardt R, Velázquez-Campoy A, Díaz-Quintana A, De la Rosa MA. Structural and functional analysis of novel human cytochrome C targets in apoptosis. Mol Cell Proteomics 2014; 13:1439-56. [PMID: 24643968 DOI: 10.1074/mcp.m113.034322] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Since the first description of apoptosis four decades ago, great efforts have been made to elucidate, both in vivo and in vitro, the molecular mechanisms involved in its regulation. Although the role of cytochrome c during apoptosis is well established, relatively little is known about its participation in signaling pathways in vivo due to its essential role during respiration. To obtain a better understanding of the role of cytochrome c in the onset of apoptosis, we used a proteomic approach based on affinity chromatography with cytochrome c as bait in this study. In this approach, novel cytochrome c interaction partners were identified whose in vivo interaction and cellular localization were facilitated through bimolecular fluorescence complementation. Modeling of the complex interface between cytochrome c and its counterparts indicated the involvement of the surface surrounding the heme crevice of cytochrome c, in agreement with the vast majority of known redox adducts of cytochrome c. However, in contrast to the high turnover rate of the mitochondrial cytochrome c redox adducts, those occurring under apoptosis led to the formation of stable nucleo-cytoplasmic ensembles, as inferred mainly from surface plasmon resonance and nuclear magnetic resonance measurements, which permitted us to corroborate the formation of such complexes in vitro. The results obtained suggest that human cytochrome c interacts with pro-survival, anti-apoptotic proteins following its release into the cytoplasm. Thus, cytochrome c may interfere with cell survival pathways and unlock apoptosis in order to prevent the spatial and temporal coexistence of antagonist signals.
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Affiliation(s)
- Jonathan Martínez-Fábregas
- From the ‡Instituto de Bioquímica Vegetal y Fotosíntesis, cicCartuja, Universidad de Sevilla-CSIC, Avda. Américo Vespucio 49, Sevilla 41092, Spain
| | - Irene Díaz-Moreno
- From the ‡Instituto de Bioquímica Vegetal y Fotosíntesis, cicCartuja, Universidad de Sevilla-CSIC, Avda. Américo Vespucio 49, Sevilla 41092, Spain
| | - Katiuska González-Arzola
- From the ‡Instituto de Bioquímica Vegetal y Fotosíntesis, cicCartuja, Universidad de Sevilla-CSIC, Avda. Américo Vespucio 49, Sevilla 41092, Spain
| | - Simon Janocha
- §Institut für Biochemie, Universität des Saarlandes, Campus B2.2, D-66123 Saarbrücken, Germany
| | - José A Navarro
- From the ‡Instituto de Bioquímica Vegetal y Fotosíntesis, cicCartuja, Universidad de Sevilla-CSIC, Avda. Américo Vespucio 49, Sevilla 41092, Spain
| | - Manuel Hervás
- From the ‡Instituto de Bioquímica Vegetal y Fotosíntesis, cicCartuja, Universidad de Sevilla-CSIC, Avda. Américo Vespucio 49, Sevilla 41092, Spain
| | - Rita Bernhardt
- §Institut für Biochemie, Universität des Saarlandes, Campus B2.2, D-66123 Saarbrücken, Germany
| | - Adrián Velázquez-Campoy
- ¶Institute of Biocomputation and Physics of Complex Systems (BIFI), Joint-Unit IQFR-CSIC-BIFI, Department of Biochemistry and Molecular and Cell Biology, University of Zaragoza, Zaragoza, Spain, and Fundacion ARAID, Government of Aragon, Zaragoza, Spain
| | - Antonio Díaz-Quintana
- From the ‡Instituto de Bioquímica Vegetal y Fotosíntesis, cicCartuja, Universidad de Sevilla-CSIC, Avda. Américo Vespucio 49, Sevilla 41092, Spain
| | - Miguel A De la Rosa
- From the ‡Instituto de Bioquímica Vegetal y Fotosíntesis, cicCartuja, Universidad de Sevilla-CSIC, Avda. Américo Vespucio 49, Sevilla 41092, Spain;
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Huang SY, Zou X. A knowledge-based scoring function for protein-RNA interactions derived from a statistical mechanics-based iterative method. Nucleic Acids Res 2014; 42:e55. [PMID: 24476917 PMCID: PMC3985650 DOI: 10.1093/nar/gku077] [Citation(s) in RCA: 94] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
Protein-RNA interactions play important roles in many biological processes. Given the high cost and technique difficulties in experimental methods, computationally predicting the binding complexes from individual protein and RNA structures is pressingly needed, in which a reliable scoring function is one of the critical components. Here, we have developed a knowledge-based scoring function, referred to as ITScore-PR, for protein-RNA binding mode prediction by using a statistical mechanics-based iterative method. The pairwise distance-dependent atomic interaction potentials of ITScore-PR were derived from experimentally determined protein–RNA complex structures. For validation, we have compared ITScore-PR with 10 other scoring methods on four diverse test sets. For bound docking, ITScore-PR achieved a success rate of up to 86% if the top prediction was considered and up to 94% if the top 10 predictions were considered, respectively. For truly unbound docking, the respective success rates of ITScore-PR were up to 24 and 46%. ITScore-PR can be used stand-alone or easily implemented in other docking programs for protein–RNA recognition.
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Affiliation(s)
- Sheng-You Huang
- Department of Physics and Astronomy, Department of Biochemistry, Dalton Cardiovascular Research Center, and Informatics Institute, University of Missouri, Columbia, MO 65211, USA
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43
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Parikh HI, Kellogg GE. Intuitive, but not simple: including explicit water molecules in protein-protein docking simulations improves model quality. Proteins 2013; 82:916-32. [PMID: 24214407 DOI: 10.1002/prot.24466] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2013] [Revised: 10/18/2013] [Accepted: 10/22/2013] [Indexed: 11/06/2022]
Abstract
Characterizing the nature of interaction between proteins that have not been experimentally cocrystallized requires a computational docking approach that can successfully predict the spatial conformation adopted in the complex. In this work, the Hydropathic INTeractions (HINT) force field model was used for scoring docked models in a data set of 30 high-resolution crystallographically characterized "dry" protein-protein complexes and was shown to reliably identify native-like models. However, most current protein-protein docking algorithms fail to explicitly account for water molecules involved in bridging interactions that mediate and stabilize the association of the protein partners, so we used HINT to illuminate the physical and chemical properties of bridging waters and account for their energetic stabilizing contributions. The HINT water Relevance metric identified the "truly" bridging waters at the 30 protein-protein interfaces and we utilized them in "solvated" docking by manually inserting them into the input files for the rigid body ZDOCK program. By accounting for these interfacial waters, a statistically significant improvement of ∼24% in the average hit-count within the top-10 predictions the protein-protein dataset was seen, compared to standard "dry" docking. The results also show scoring improvement, with medium and high accuracy models ranking much better than incorrect ones. These improvements can be attributed to the physical presence of water molecules that alter surface properties and better represent native shape and hydropathic complementarity between interacting partners, with concomitantly more accurate native-like structure predictions.
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Affiliation(s)
- Hardik I Parikh
- Department of Medicinal Chemistry and Institute for Structural Biology and Drug Discovery, Virginia Commonwealth University, Richmond, Virginia, 23298-0540
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Molecular docking of heparin oligosaccharides with Hep-II heparin-binding domain of fibronectin reveals an interplay between the different positions of sulfate groups. Glycoconj J 2013; 31:161-9. [DOI: 10.1007/s10719-013-9512-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2013] [Revised: 11/04/2013] [Accepted: 11/05/2013] [Indexed: 12/20/2022]
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Li L, Huang Y, Xiao Y. How to use not-always-reliable binding site information in protein-protein docking prediction. PLoS One 2013; 8:e75936. [PMID: 24124522 PMCID: PMC3790831 DOI: 10.1371/journal.pone.0075936] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2013] [Accepted: 08/22/2013] [Indexed: 11/19/2022] Open
Abstract
In many protein-protein docking algorithms, binding site information is used to help predicting the protein complex structures. Using correct and accurate binding site information can increase protein-protein docking success rate significantly. On the other hand, using wrong binding sites information should lead to a failed prediction, or, at least decrease the success rate. Recently, various successful theoretical methods have been proposed to predict the binding sites of proteins. However, the predicted binding site information is not always reliable, sometimes wrong binding site information could be given. Hence there is a high risk to use the predicted binding site information in current docking algorithms. In this paper, a softly restricting method (SRM) is developed to solve this problem. By utilizing predicted binding site information in a proper way, the SRM algorithm is sensitive to the correct binding site information but insensitive to wrong information, which decreases the risk of using predicted binding site information. This SRM is tested on benchmark 3.0 using purely predicted binding site information. The result shows that when the predicted information is correct, SRM increases the success rate significantly; however, even if the predicted information is completely wrong, SRM only decreases success rate slightly, which indicates that the SRM is suitable for utilizing predicted binding site information.
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Affiliation(s)
- Lin Li
- Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, South Carolina, United States of America
| | - Yanzhao Huang
- Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan, Hubei, China
- * E-mail: (YH); (YX)
| | - Yi Xiao
- Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan, Hubei, China
- * E-mail: (YH); (YX)
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Moal IH, Torchala M, Bates PA, Fernández-Recio J. The scoring of poses in protein-protein docking: current capabilities and future directions. BMC Bioinformatics 2013; 14:286. [PMID: 24079540 PMCID: PMC3850738 DOI: 10.1186/1471-2105-14-286] [Citation(s) in RCA: 76] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2013] [Accepted: 09/25/2013] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Protein-protein docking, which aims to predict the structure of a protein-protein complex from its unbound components, remains an unresolved challenge in structural bioinformatics. An important step is the ranking of docked poses using a scoring function, for which many methods have been developed. There is a need to explore the differences and commonalities of these methods with each other, as well as with functions developed in the fields of molecular dynamics and homology modelling. RESULTS We present an evaluation of 115 scoring functions on an unbound docking decoy benchmark covering 118 complexes for which a near-native solution can be found, yielding top 10 success rates of up to 58%. Hierarchical clustering is performed, so as to group together functions which identify near-natives in similar subsets of complexes. Three set theoretic approaches are used to identify pairs of scoring functions capable of correctly scoring different complexes. This shows that functions in different clusters capture different aspects of binding and are likely to work together synergistically. CONCLUSIONS All functions designed specifically for docking perform well, indicating that functions are transferable between sampling methods. We also identify promising methods from the field of homology modelling. Further, differential success rates by docking difficulty and solution quality suggest a need for flexibility-dependent scoring. Investigating pairs of scoring functions, the set theoretic measures identify known scoring strategies as well as a number of novel approaches, indicating promising augmentations of traditional scoring methods. Such augmentation and parameter combination strategies are discussed in the context of the learning-to-rank paradigm.
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Affiliation(s)
- Iain H Moal
- Joint BSC-IRB Research Program in Computational Biology, Life Science Department, Barcelona Super computing Center, Barcelona 08034, Spain
| | - Mieczyslaw Torchala
- Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London WC2A 3LY, UK
| | - Paul A Bates
- Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London WC2A 3LY, UK
| | - Juan Fernández-Recio
- Joint BSC-IRB Research Program in Computational Biology, Life Science Department, Barcelona Super computing Center, Barcelona 08034, Spain
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Ali SA, Alam M, Abbasi A, Kalbacher H, Schaechinger TJ, Hu Y, Zhijian C, Li W, Voelter W. Structure–Activity Relationship of a Highly Selective Peptidyl Inhibitor of Kv1.3 Voltage-Gated K+-Channel from Scorpion (B. sindicus) Venom. Int J Pept Res Ther 2013. [DOI: 10.1007/s10989-013-9362-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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Smith JA, Edwards SJ, Moth CW, Lybrand TP. TagDock: an efficient rigid body docking algorithm for oligomeric protein complex model construction and experiment planning. Biochemistry 2013; 52:5577-84. [PMID: 23875708 DOI: 10.1021/bi400158k] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We report here new computational tools and strategies to efficiently generate three-dimensional models for oligomeric biomolecular complexes in cases where there is limited experimental restraint data to guide the docking calculations. Our computational tools are designed to rapidly and exhaustively enumerate all geometrically possible docking poses for an oligomeric complex, rather than generate detailed, atomic-resolution models. Experimental data, such as interatomic distance measurements, are then used to select and refine docking poses that are consistent with the experimental restraints. Our computational toolkit is designed for use with sparse data sets to generate intermediate-resolution docking models, and utilizes distance difference matrix analysis to identify further restraint measurements that will provide maximum additional structural refinement. Thus, these tools can be used to help plan optimal residue positions for probe incorporation in labor-intensive biophysical experiments such as chemical cross-linking, electron paramagnetic resonance, or Förster resonance energy transfer spectroscopy studies. We present benchmark results for docking the collection of all 176 heterodimer protein complexes from the ZDOCK database, as well as a protein homodimer with recently collected experimental distance restraints, to illustrate the toolkit's capabilities and performance, and to demonstrate how distance difference matrix analysis can automatically identify and prioritize additional restraint measurements that allow us to rapidly optimize docking poses.
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Affiliation(s)
- Jarrod A Smith
- Department of Biochemistry, Vanderbilt University, Box 351822, Nashville, TN 37235-1822, USA
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Williamson MP. Using chemical shift perturbation to characterise ligand binding. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2013; 73:1-16. [PMID: 23962882 DOI: 10.1016/j.pnmrs.2013.02.001] [Citation(s) in RCA: 956] [Impact Index Per Article: 86.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2013] [Revised: 02/12/2013] [Accepted: 02/18/2013] [Indexed: 05/05/2023]
Abstract
Chemical shift perturbation (CSP, chemical shift mapping or complexation-induced changes in chemical shift, CIS) follows changes in the chemical shifts of a protein when a ligand is added, and uses these to determine the location of the binding site, the affinity of the ligand, and/or possibly the structure of the complex. A key factor in determining the appearance of spectra during a titration is the exchange rate between free and bound, or more specifically the off-rate koff. When koff is greater than the chemical shift difference between free and bound, which typically equates to an affinity Kd weaker than about 3μM, then exchange is fast on the chemical shift timescale. Under these circumstances, the observed shift is the population-weighted average of free and bound, which allows Kd to be determined from measurement of peak positions, provided the measurements are made appropriately. (1)H shifts are influenced to a large extent by through-space interactions, whereas (13)Cα and (13)Cβ shifts are influenced more by through-bond effects. (15)N and (13)C' shifts are influenced both by through-bond and by through-space (hydrogen bonding) interactions. For determining the location of a bound ligand on the basis of shift change, the most appropriate method is therefore usually to measure (15)N HSQC spectra, calculate the geometrical distance moved by the peak, weighting (15)N shifts by a factor of about 0.14 compared to (1)H shifts, and select those residues for which the weighted shift change is larger than the standard deviation of the shift for all residues. Other methods are discussed, in particular the measurement of (13)CH3 signals. Slow to intermediate exchange rates lead to line broadening, and make Kd values very difficult to obtain. There is no good way to distinguish changes in chemical shift due to direct binding of the ligand from changes in chemical shift due to allosteric change. Ligand binding at multiple sites can often be characterised, by simultaneous fitting of many measured shift changes, or more simply by adding substoichiometric amounts of ligand. The chemical shift changes can be used as restraints for docking ligand onto protein. By use of quantitative calculations of ligand-induced chemical shift changes, it is becoming possible to determine not just the position but also the orientation of ligands.
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Affiliation(s)
- Mike P Williamson
- Department of Molecular Biology and Biotechnology, University of Sheffield, Firth Court, Western Bank, Sheffield S10 2TN, UK.
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50
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Cruz-Gallardo I, Díaz-Moreno I, Díaz-Quintana A, Donaire A, Velázquez-Campoy A, Curd RD, Rangachari K, Birdsall B, Ramos A, Holder AA, De la Rosa MA. Antimalarial activity of cupredoxins: the interaction of Plasmodium merozoite surface protein 119 (MSP119) and rusticyanin. J Biol Chem 2013; 288:20896-20907. [PMID: 23749994 PMCID: PMC3774360 DOI: 10.1074/jbc.m113.460162] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2013] [Revised: 06/07/2013] [Indexed: 11/06/2022] Open
Abstract
The discovery of effective new antimalarial agents is urgently needed. One of the most frequently studied molecules anchored to the parasite surface is the merozoite surface protein-1 (MSP1). At red blood cell invasion MSP1 is proteolytically processed, and the 19-kDa C-terminal fragment (MSP119) remains on the surface and is taken into the red blood cell, where it is transferred to the food vacuole and persists until the end of the intracellular cycle. Because a number of specific antibodies inhibit erythrocyte invasion and parasite growth, MSP119 is therefore a promising target against malaria. Given the structural homology of cupredoxins with the Fab domain of monoclonal antibodies, an approach combining NMR and isothermal titration calorimetry (ITC) measurements with docking calculations based on BiGGER is employed on MSP119-cupredoxin complexes. Among the cupredoxins tested, rusticyanin forms a well defined complex with MSP119 at a site that overlaps with the surface recognized by the inhibitory antibodies. The addition of holo-rusticyanin to infected cells results in parasitemia inhibition, but negligible effects on parasite growth can be observed for apo-rusticyanin and other proteins of the cupredoxin family. These findings point to rusticyanin as an excellent therapeutic tool for malaria treatment and provide valuable information for drug design.
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Affiliation(s)
- Isabel Cruz-Gallardo
- From the Instituto de Bioquímica Vegetal y Fotosíntesis (IBVF), cicCartuja, Universidad de Sevilla-CSIC, Avenida Américo Vespucio 49, Sevilla 41092, Spain
| | - Irene Díaz-Moreno
- From the Instituto de Bioquímica Vegetal y Fotosíntesis (IBVF), cicCartuja, Universidad de Sevilla-CSIC, Avenida Américo Vespucio 49, Sevilla 41092, Spain
| | - Antonio Díaz-Quintana
- From the Instituto de Bioquímica Vegetal y Fotosíntesis (IBVF), cicCartuja, Universidad de Sevilla-CSIC, Avenida Américo Vespucio 49, Sevilla 41092, Spain
| | - Antonio Donaire
- the Departamento de Química Inorgánica, Facultad de Química, Universidad de Murcia, Campus Universitario de Espinardo, Murcia 30100, Spain
| | - Adrián Velázquez-Campoy
- the Instituto de Biocomputación y Física de Sistemas complejos (BIFI), Universidad de Zaragoza, c/Mariano Esquillor, Zaragoza 50018, Spain
| | | | | | - Berry Birdsall
- Molecular Structure Division, Medical Research Council (MRC) National Institute for Medical Research, The Ridgeway, Mill Hill, London W7 1AA, United Kingdom
| | - Andres Ramos
- Molecular Structure Division, Medical Research Council (MRC) National Institute for Medical Research, The Ridgeway, Mill Hill, London W7 1AA, United Kingdom
| | | | - Miguel A De la Rosa
- From the Instituto de Bioquímica Vegetal y Fotosíntesis (IBVF), cicCartuja, Universidad de Sevilla-CSIC, Avenida Américo Vespucio 49, Sevilla 41092, Spain,.
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