相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。EnzyHTP: A High-Throughput Computational Platform for Enzyme Modeling
Qianzhen Shao et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2022)
Learning protein fitness models from evolutionary and assay-labeled data
Chloe Hsu et al.
NATURE BIOTECHNOLOGY (2022)
Therapeutic enzyme engineering using a generative neural network
Andrew Giessel et al.
SCIENTIFIC REPORTS (2022)
Machine learning modeling of family wide enzyme-substrate specificity screens
Samuel Goldman et al.
PLOS COMPUTATIONAL BIOLOGY (2022)
Deep learning-based kcat prediction enables improved enzyme-constrained model reconstruction
Feiran Li et al.
NATURE CATALYSIS (2022)
ProThermDB: thermodynamic database for proteins and mutants revisited after 15 years
Rahul Nikam et al.
NUCLEIC ACIDS RESEARCH (2021)
Anomalous collapses of Nares Strait ice arches leads to enhanced export of Arctic sea ice
G. W. K. Moore et al.
NATURE COMMUNICATIONS (2021)
Machine-Learning-Guided Library Design Cycle for Directed Evolution of Enzymes: The Effects of Training Data Composition on Sequence Space Exploration
Yutaka Saito et al.
ACS CATALYSIS (2021)
Ancestral lysosomal enzymes with increased activity harbor therapeutic potential for treatment of Hunter syndrome
Natalie M. Hendrikse et al.
ISCIENCE (2021)
Deep learning allows genome-scale prediction of Michaelis constants from structural features
Alexander Kroll et al.
PLOS BIOLOGY (2021)
Rational Enzyme Design without Structural Knowledge: A Sequence-Based Approach for Efficient Generation of Transglycosylases
David Teze et al.
CHEMISTRY-A EUROPEAN JOURNAL (2021)
Near-complete depolymerization of polyesters with nano-dispersed enzymes
Christopher Delre et al.
NATURE (2021)
Low-N protein engineering with data-efficient deep learning
Surojit Biswas et al.
NATURE METHODS (2021)
Advances in machine learning for directed evolution
Bruce J. Wittmann et al.
CURRENT OPINION IN STRUCTURAL BIOLOGY (2021)
Machine-Learning-Assisted Free Energy Simulation of Solution-Phase and Enzyme Reactions
Xiaoliang Pan et al.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION (2021)
Rate-Perturbing Single Amino Acid Mutation for Hydrolases: A Statistical Profiling
Bailu Yan et al.
JOURNAL OF PHYSICAL CHEMISTRY B (2021)
Highly accurate protein structure prediction with AlphaFold
John Jumper et al.
NATURE (2021)
Revealing enzyme functional architecture via high-throughput microfluidic enzyme kinetics
C. J. Markin et al.
SCIENCE (2021)
Spectroscopically Guided Simulations Reveal Distinct Strategies for Positioning Substrates to Achieve Selectivity in Nonheme Fe(II)/α-Ketoglutarate-Dependent Halogenases
Rimsha Mehmood et al.
ACS CATALYSIS (2021)
Informed training set design enables efficient machine learning-assisted directed protein evolution
Bruce J. Wittmann et al.
CELL SYSTEMS (2021)
Recent trends in biocatalysis
Dong Yi et al.
CHEMICAL SOCIETY REVIEWS (2021)
Revolutionizing enzyme engineering through artificial intelligence and machine learning
Nitu Singh et al.
EMERGING TOPICS IN LIFE SCIENCES (2021)
Multistable inflatable origami structures at the metre scale
Christopher Delre et al.
NATURE (2021)
Expanding functional protein sequence spaces using generative adversarial networks
Donatas Repecka et al.
NATURE MACHINE INTELLIGENCE (2021)
Machine learning-based prediction of enzyme substrate scope: Application to bacterial nitrilases
Zhongyu Mou et al.
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS (2021)
Directed Evolution of a Halide Methyltransferase Enables Biocatalytic Synthesis of Diverse SAM Analogs
M. Eng. Qingyun Tang et al.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION (2021)
Kemp Elimination Reaction Catalyzed by Electric Fields
Carles Acosta-Silva et al.
CHEMPHYSCHEM (2020)
Machine Learning in Enzyme Engineering
Stanislav Mazurenko et al.
ACS CATALYSIS (2020)
Enzyme engineering: Reshaping the biocatalytic functions
Misha Ali et al.
BIOTECHNOLOGY AND BIOENGINEERING (2020)
Deep Dive into Machine Learning Models for Protein Engineering
Yuting Xu et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2020)
An engineered PET depolymerase to break down and recycle plastic bottles
V. Tournier et al.
NATURE (2020)
EnzymeMiner: automated mining of soluble enzymes with diverse structures, catalytic properties and stabilities
Jiri Hon et al.
NUCLEIC ACIDS RESEARCH (2020)
Characterization and engineering of a two-enzyme system for plastics depolymerization
Brandon C. Knott et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2020)
Discovery of Novel Gain-of-Function Mutations Guided by Structure-Based Deep Learning
Raghav Shroff et al.
ACS SYNTHETIC BIOLOGY (2020)
Machine learning-based prediction of activity and substrate specificity for OleA enzymes in the thiolase superfamily
Serina L. Robinson et al.
SYNTHETIC BIOLOGY (2020)
Hydrogen-Deuterium Exchange within Adenosine Deaminase, a TIM Barrel Hydrolase, Identifies Networks for Thermal Activation of Catalysis
Shuaihua Gao et al.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY (2020)
Substrate specificity of 2-deoxy-D-ribose 5-phosphate aldolase (DERA) assessed by different protein engineering and machine learning methods
Sanni Voutilainen et al.
APPLIED MICROBIOLOGY AND BIOTECHNOLOGY (2020)
An evolution-based model for designing chorismate mutase enzymes
William P. Russ et al.
SCIENCE (2020)
Machine Learning Identifies Chemical Characteristics That Promote Enzyme Catalysis
Brian M. Bonk et al.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY (2019)
Machine learning-assisted directed protein evolution with combinatorial libraries
Zachary Wu et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2019)
Enzyme-Catalysed Synthesis of Secondary and Tertiary Amides
Mark R. Petchey et al.
ADVANCED SYNTHESIS & CATALYSIS (2019)
Quantum Mechanical Description of Electrostatics Provides a Unified Picture of Catalytic Action Across Methyltransferases
Zhongyue Yang et al.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS (2019)
Finding Reactive Configurations: A Machine Learning Approach for Estimating Energy Barriers Applied to Sirtuin 5
Beatriz von der Esch et al.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION (2019)
Unified rational protein engineering with sequence-based deep representation learning
Ethan C. Alley et al.
NATURE METHODS (2019)
Engineering CRISPR/ Lb Cas12a for highly efficient, temperature‐tolerant plant gene editing
Patrick Schindele et al.
PLANT BIOTECHNOLOGY JOURNAL (2019)
Evolutionary redesign of the lysosomal enzyme arylsulfatase A increases efficacy of enzyme replacement therapy for metachromatic leukodystrophy
Heidi Simonis et al.
HUMAN MOLECULAR GENETICS (2019)
UniProt: a worldwide hub of protein knowledge
Alex Bateman et al.
NUCLEIC ACIDS RESEARCH (2019)
BRENDA in 2019: a European ELIXIR core data resource
Lisa Jeske et al.
NUCLEIC ACIDS RESEARCH (2019)
Revealing quantum mechanical effects in enzyme catalysis with large-scale electronic structure simulation
Zhongyue Yang et al.
REACTION CHEMISTRY & ENGINEERING (2019)
Combining Reclaimed PET with Bio-based Monomers Enables Plastics Upcycling
Nicholas A. Rorrer et al.
JOULE (2019)
Mechanism and Catalytic Site Atlas (M-CSA): a database of enzyme reaction mechanisms and active sites
Antonio J. M. Ribeiro et al.
NUCLEIC ACIDS RESEARCH (2018)
Speeding up enzyme discovery and engineering with ultrahigh-throughput methods
Hans Adrian Bunzel et al.
CURRENT OPINION IN STRUCTURAL BIOLOGY (2018)
Advances in the Engineering of the Gene Editing Enzymes and the Genomes: Understanding and Handling the Off-Target Effects of CRISPR/Cas9
Yufang Yin et al.
JOURNAL OF BIOMEDICAL NANOTECHNOLOGY (2018)
ProtaBank: A repository for protein design and engineering data
Connie Y. Wang et al.
PROTEIN SCIENCE (2018)
Directed Evolution of Protein Catalysts
Cathleen Zeymer et al.
ANNUAL REVIEW OF BIOCHEMISTRY, VOL 87 (2018)
Directed evolution of the bacterial endo-β-1,4-glucanase from Streptomyces sp G12 towards improved catalysts for lignocellulose conversion
Davide Agostino Cecchini et al.
AMB EXPRESS (2018)
Automated Design of Efficient and Functionally Diverse Enzyme Repertoires
Olga Khersonsky et al.
MOLECULAR CELL (2018)
Deep generative models of genetic variation capture the effects of mutations
Adam J. Riesselman et al.
NATURE METHODS (2018)
Large-scale QM/MM free energy simulations of enzyme catalysis reveal the influence of charge transfer
Heather J. Kulik
PHYSICAL CHEMISTRY CHEMICAL PHYSICS (2018)
Functional and informatics analysis enables glycosyltransferase activity prediction
Min Yang et al.
NATURE CHEMICAL BIOLOGY (2018)
Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models
David Heckmann et al.
NATURE COMMUNICATIONS (2018)
A machine learning approach for reliable prediction of amino acid interactions and its application in the directed evolution of enantioselective enzymes
Frederic Cadet et al.
SCIENTIFIC REPORTS (2018)
Predicting novel substrates for enzymes with minimal experimental effort with active learning
Dante A. Pertusi et al.
METABOLIC ENGINEERING (2017)
Mutation effects predicted from sequence co-variation
Thomas A. Hopf et al.
NATURE BIOTECHNOLOGY (2017)
Stereoselectivity-Tailored, Metal-Free Hydrolytic Dynamic Kinetic Resolution of Morita-Baylis-Hillman Acetates Using an Engineered Lipase-Organic Base Cocatalyst
Bo Xia et al.
ACS CATALYSIS (2017)
SANDPUMA: ensemble predictions of nonribosomal peptide chemistry reveal biosynthetic diversity across Actinobacteria
Marc G. Chevrette et al.
BIOINFORMATICS (2017)
An introduction to deep learning on biological sequence data: examples and solutions
Vanessa Isabell Jurtz et al.
BIOINFORMATICS (2017)
Coevolutionary Landscape Inference and the Context-Dependence of Mutations in Beta-Lactamase TEM-1
Matteo Figliuzzi et al.
MOLECULAR BIOLOGY AND EVOLUTION (2016)
Semisupervised Gaussian Process for Automated Enzyme Search
Joseph Mellor et al.
ACS SYNTHETIC BIOLOGY (2016)
Kinetic Characterization of 100 Glycoside Hydrolase Mutants Enables the Discovery of Structural Features Correlated with Kinetic Constants
Dylan Alexander Carlin et al.
PLOS ONE (2016)
Engineering of Kuma030: A Gliadin Peptidase That Rapidly Degrades Immunogenic Gliadin Peptides in Gastric Conditions
Clancey Wolf et al.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY (2015)
Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics
Ehsaneddin Asgari et al.
PLOS ONE (2015)
Deep mutational scanning: a new style of protein science
Douglas M. Fowler et al.
NATURE METHODS (2014)
Design of Protein Catalysts
Donald Hilvert
ANNUAL REVIEW OF BIOCHEMISTRY, VOL 82 (2013)
De novo enzymes by computational design
Hajo Kries et al.
CURRENT OPINION IN CHEMICAL BIOLOGY (2013)
Many Pathways in Laboratory Evolution Can Lead to Improved Enzymes: How to Escape from Local Minima
Yosephine Gumulya et al.
CHEMBIOCHEM (2012)
Computational Design of an α-Gliadin Peptidase
Sydney R. Gordon et al.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY (2012)
SABIO-RK-database for biochemical reaction kinetics
Ulrike Wittig et al.
NUCLEIC ACIDS RESEARCH (2012)
Bridging the gaps in design methodologies by evolutionary optimization of the stability and proficiency of designed Kemp eliminase KE59
Olga Khersonsky et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2012)
RosettaScripts: A Scripting Language Interface to the Rosetta Macromolecular Modeling Suite
Sarel J. Fleishman et al.
PLOS ONE (2011)
Direct-coupling analysis of residue coevolution captures native contacts across many protein families
Faruck Morcos et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2011)
Deep mutational scanning: assessing protein function on a massive scale
Carlos L. Araya et al.
TRENDS IN BIOTECHNOLOGY (2011)
Structural Fluctuations in Enzyme-Catalyzed Reactions: Determinants of Reactivity in Fatty Acid Amide Hydrolase from Multivariate Statistical Analysis of Quantum Mechanics/Molecular Mechanics Paths
Alessi Lodola et al.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION (2010)
An exciting but challenging road ahead for computational enzyme design
David Baker
PROTEIN SCIENCE (2010)
Combining Structure and Sequence Information Allows Automated Prediction of Substrate Specificities within Enzyme Families
Marc Roettig et al.
PLOS COMPUTATIONAL BIOLOGY (2010)
Exploring protein fitness landscapes by directed evolution
Philip A. Romero et al.
NATURE REVIEWS MOLECULAR CELL BIOLOGY (2009)
Bimodal protein solubility distribution revealed by an aggregation analysis of the entire ensemble of Escherichia coli proteins
Tatsuya Niwa et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2009)
Improving catalytic function by ProSAR-driven enzyme evolution
Richard J. Fox et al.
NATURE BIOTECHNOLOGY (2007)
A new set of amino acid descriptors and its application in peptide QSARs
H Mei et al.
BIOPOLYMERS (2005)
UniProt: the Universal Protein knowledgebase
R Apweiler et al.
NUCLEIC ACIDS RESEARCH (2004)
Concepts of nature in organic synthesis: Cascade catalysis and multistep conversions in concert
A Bruggink et al.
ORGANIC PROCESS RESEARCH & DEVELOPMENT (2003)
Optimizing the search algorithm for protein engineering by directed evolution
R Fox et al.
PROTEIN ENGINEERING (2003)
BRENDA, enzyme data and metabolic information
I Schomburg et al.
NUCLEIC ACIDS RESEARCH (2002)
Analysis and prediction of functional sub-types from protein sequence alignments
SS Hannenhalli et al.
JOURNAL OF MOLECULAR BIOLOGY (2000)
The Protein Data Bank
HM Berman et al.
NUCLEIC ACIDS RESEARCH (2000)