pyKVFinder: an efficient and integrable Python package for biomolecular cavity detection and characterization in data science

[1]  K. Kavukcuoglu,et al.  Highly accurate protein structure prediction for the human proteome , 2021, Nature.

[2]  O. Lichtarge,et al.  Targeting SARS-CoV-2 Nsp3 macrodomain structure with insights from human poly(ADP-ribose) glycohydrolase (PARG) structures with inhibitors , 2021, Progress in Biophysics and Molecular Biology.

[3]  Helder Veras Ribeiro Filho,et al.  Cryo-EM structure of the mature and infective Mayaro virus at 4.4 Å resolution reveals features of arthritogenic alphaviruses , 2020, Nature Communications.

[4]  B. Robson,et al.  The use of knowledge management tools in viroinformatics. Example study of a highly conserved sequence motif in Nsp3 of SARS-CoV-2 as a therapeutic target , 2020, Computers in Biology and Medicine.

[5]  A. Joachimiak,et al.  Crystal structures of SARS-CoV-2 ADP-ribose phosphatase: from the apo form to ligand complexes , 2020, IUCrJ.

[6]  João Victor da Silva Guerra,et al.  ParKVFinder: A thread-level parallel approach in biomolecular cavity detection , 2020, SoftwareX.

[7]  Nicholas R Silvaggi,et al.  Molecular Basis for ADP-Ribose Binding to the Mac1 Domain of SARS-CoV-2 nsp3 , 2020, Biochemistry.

[8]  Jaime Fern'andez del R'io,et al.  Array programming with NumPy , 2020, Nature.

[9]  J. Claverie A Putative Role of de-Mono-ADP-Ribosylation of STAT1 by the SARS-CoV-2 Nsp3 Protein in the Cytokine Storm Syndrome of COVID-19 , 2020, Viruses.

[10]  Corey J. Nolet,et al.  Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence , 2020, Inf..

[11]  Joel Nothman,et al.  SciPy 1.0-Fundamental Algorithms for Scientific Computing in Python , 2019, ArXiv.

[12]  Carole Goble,et al.  BioExcel Building Blocks, a software library for interoperable biomolecular simulation workflows , 2019, Scientific Data.

[13]  Tiago M C Simões,et al.  CavVis - A Field-of-View Geometric Algorithm for Protein Cavity Detection , 2019, J. Chem. Inf. Model..

[14]  David S. Goodsell,et al.  RCSB Protein Data Bank: biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy , 2018, Nucleic Acids Res..

[15]  Cole H. Christie,et al.  Protein Data Bank: the single global archive for 3D macromolecular structure data , 2018, Nucleic acids research.

[16]  Cameron Mura,et al.  Structural biology meets data science: does anything change? , 2018, Current opinion in structural biology.

[17]  Alexander S. Rose,et al.  NGLview–interactive molecular graphics for Jupyter notebooks , 2018, Bioinform..

[18]  Rommie E. Amaro,et al.  POVME 3.0: Software for Mapping Binding Pocket Flexibility. , 2017, Journal of chemical theory and computation.

[19]  Jincun Zhao,et al.  The Conserved Coronavirus Macrodomain Promotes Virulence and Suppresses the Innate Immune Response during Severe Acute Respiratory Syndrome Coronavirus Infection , 2016, mBio.

[20]  Gert Vriend,et al.  YASARA View—molecular graphics for all devices—from smartphones to workstations , 2014, Bioinform..

[21]  José Xavier-Neto,et al.  KVFinder: steered identification of protein cavities as a PyMOL plugin , 2014, BMC Bioinformatics.

[22]  K. G. Fleming,et al.  Side-chain hydrophobicity scale derived from transmembrane protein folding into lipid bilayers , 2011, Proceedings of the National Academy of Sciences.

[23]  Hongbo Zhu,et al.  MSPocket: an orientation-independent algorithm for the detection of ligand binding pockets , 2011, Bioinform..

[24]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[25]  T. Kawabata Detection of multiscale pockets on protein surfaces using mathematical morphology , 2010, Proteins.

[26]  R. Wade,et al.  Computational approaches to identifying and characterizing protein binding sites for ligand design , 2009, Journal of molecular recognition : JMR.

[27]  Mona Singh,et al.  Predicting Protein Ligand Binding Sites by Combining Evolutionary Sequence Conservation and 3D Structure , 2009, PLoS Comput. Biol..

[28]  Vincent Le Guilloux,et al.  Fpocket: An open source platform for ligand pocket detection , 2009, BMC Bioinformatics.

[29]  B. Ludewig,et al.  Mouse Hepatitis Virus Liver Pathology Is Dependent on ADP-Ribose-1″-Phosphatase, a Viral Function Conserved in the Alpha-Like Supergroup , 2008, Journal of Virology.

[30]  John D. Hunter,et al.  Matplotlib: A 2D Graphics Environment , 2007, Computing in Science & Engineering.

[31]  A. Konagurthu,et al.  MUSTANG: A multiple structural alignment algorithm , 2006, Proteins.

[32]  Gang Zhao,et al.  An amino acid “transmembrane tendency” scale that approaches the theoretical limit to accuracy for prediction of transmembrane helices: Relationship to biological hydrophobicity , 2006, Protein science : a publication of the Protein Society.

[33]  G. Heijne,et al.  Recognition of transmembrane helices by the endoplasmic reticulum translocon , 2005, Nature.

[34]  Frank H. Allen,et al.  Cambridge Structural Database , 2002 .

[35]  G. Klebe,et al.  Identification and mapping of small-molecule binding sites in proteins: computational tools for structure-based drug design. , 2002, Farmaco.

[36]  Junmei Wang,et al.  How well does a restrained electrostatic potential (RESP) model perform in calculating conformational energies of organic and biological molecules? , 2000, J. Comput. Chem..

[37]  H. Edelsbrunner,et al.  Anatomy of protein pockets and cavities: Measurement of binding site geometry and implications for ligand design , 1998, Protein science : a publication of the Protein Society.

[38]  M Hendlich,et al.  LIGSITE: automatic and efficient detection of potential small molecule-binding sites in proteins. , 1997, Journal of molecular graphics & modelling.

[39]  Stephen H. White,et al.  Experimentally determined hydrophobicity scale for proteins at membrane interfaces , 1996, Nature Structural Biology.

[40]  D. Eisenberg,et al.  The hydrophobic moment detects periodicity in protein hydrophobicity. , 1984, Proceedings of the National Academy of Sciences of the United States of America.

[41]  R. Doolittle,et al.  A simple method for displaying the hydropathic character of a protein. , 1982, Journal of molecular biology.