4.7 Article

AlphaFold 2: Why It Works and Its Implications for Understanding the Relationships of Protein Sequence, Structure, and Function

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。
Article Biochemistry & Molecular Biology

Improving protein tertiary structure prediction by deep learning and distance prediction in CASP14

Jian Liu et al.

Summary: Significant progress has been made in protein structure prediction by utilizing deep learning and residue-residue distance prediction since CASP13. The MULTICOM predictor in the 2020 CASP14 experiment ranked well in both tertiary structure prediction and inter-domain structure prediction, showing improvement in template-free modeling and overall performance.

PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS (2022)

Article Biochemistry & Molecular Biology

TheAutoDocksuite at 30

David S. Goodsell et al.

Summary: The AutoDock suite offers a comprehensive toolset for computational ligand docking and drug design, with specialized tools available for challenging systems. All methods in the suite are freely available, leading to the rapid growth of user and developer communities.

PROTEIN SCIENCE (2021)

Article Biochemical Research Methods

DeepDist: real-value inter-residue distance prediction with deep residual convolutional network

Tianqi Wu et al.

Summary: The study introduces a multi-task deep learning distance predictor (DeepDist) that can simultaneously predict real-value inter-residue distances and classify them into multiple distance intervals. Tested on 43 CASP13 hard domains, DeepDist achieves comparable performance in real-value distance prediction and multi-class distance prediction.

BMC BIOINFORMATICS (2021)

Article Biochemistry & Molecular Biology

Combination of deep neural network with attention mechanism enhances the explainability of protein contact prediction

Chen Chen et al.

Summary: Deep learning has made significant advancements in protein residue-residue contact prediction since the 2012 CASP10 competition, but little effort has been put into interpreting its black-box methods. This study introduces an attention-based convolutional neural network model for protein contact prediction, which adds attention modules on top of existing deep learning models to improve prediction accuracy and provide interpretable patterns.

PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS (2021)

Article Chemistry, Medicinal

FRAGSITE: A Fragment-Based Approach for Virtual Ligand Screening

Hongyi Zhou et al.

Summary: In modern drug discovery, virtual ligand screening (VLS) is commonly used to reduce time and cost before experimental ligand screening. A new approach called FRAGSITE improves VLS precision and recall by integrating ligand fragment scores with global ligand similarity scores, outperforming state-of-the-art methods and showing better performance on challenging sets.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2021)

Article Biology

Binding mechanism of inhibitors to p38α MAP kinase deciphered by using multiple replica Gaussian accelerated molecular dynamics and calculations of binding free energies

Jianzhong Chen et al.

Summary: The study utilized MR-GaMD simulations and MM-GBSA method to investigate the binding mechanisms of three inhibitors to p38α, showing significant conformational changes and suggesting potential efficient target residues for potent inhibitors towards p38α.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

Article Biochemistry & Molecular Biology

The role of local versus nonlocal physicochemical restraints in determining protein native structure

Jeffrey Skolnick et al.

Summary: The tertiary structure of a protein is determined by the interplay of local secondary structure propensities, hydrogen bonding, and tertiary interactions. The global structure of a protein sequence is collectively selected by the many-body, tertiary interactions among residues. Recent advances in deep-learning approaches have been successful in predicting protein side-chain contacts because they implicitly learned the many-body interactions among protein residues.

CURRENT OPINION IN STRUCTURAL BIOLOGY (2021)

Article Multidisciplinary Sciences

Highly accurate protein structure prediction with AlphaFold

John Jumper et al.

Summary: Proteins are essential for life, and accurate prediction of their structures is a crucial research problem. Current experimental methods are time-consuming, highlighting the need for accurate computational approaches to address the gap in structural coverage. Despite recent progress, existing methods fall short of atomic accuracy in protein structure prediction.

NATURE (2021)

Article Multidisciplinary Sciences

Highly accurate protein structure prediction for the human proteome

Kathryn Tunyasuvunakool et al.

Summary: Using the AlphaFold method, the structural coverage of the proteome has been significantly expanded, covering 98.5% of human proteins with 58% of residues having confident predictions and 36% having very high confidence. Introducing new metrics to interpret the dataset and identify disordered regions, this study aims to provide high-quality predictions for generating biological hypotheses.

NATURE (2021)

Article Biochemistry & Molecular Biology

Protein tertiary structure prediction and refinement using deep learning and Rosetta in CASP14

Ivan Anishchenko et al.

Summary: The trRosetta structure prediction method utilizes deep learning to generate predicted residue-residue distance and orientation distributions to build 3D models. By incorporating language model embeddings and weighted template information based on sequence similarity, along with a refinement pipeline guided by DeepAccNet accuracy predictor, the new pipeline has shown considerable improvement over the original trRosetta in both benchmark tests and CASP results, completing the modeling process faster and with less computing resources.

PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS (2021)

Article Multidisciplinary Sciences

Accurate prediction of protein structures and interactions using a three-track neural network

Minkyung Baek et al.

Summary: Through the three-track network, we achieved accuracies approaching those of DeepMind in CASP14, enabling rapid solution of challenging x-ray crystallography and cryo-electron microscopy structure modeling problems, and providing insights into the functions of proteins with currently unknown structure.

SCIENCE (2021)

Article Biochemical Research Methods

A novel sequence alignment algorithm based on deep learning of the protein folding code

Mu Gao et al.

Summary: The SAdLSA algorithm effectively learns protein folding code from experimentally determined protein structures, improving structural relationships detection in sequence comparisons. It demonstrates significant improvement over established approaches on challenging datasets, with a time complexity of O(N) thanks to GPU acceleration.

BIOINFORMATICS (2021)

Article Computer Science, Artificial Intelligence

Improved protein structure prediction by deep learning irrespective of co-evolution information

Jinbo Xu et al.

Summary: Recent advances in computational protein structure prediction have shown significant improvements by integrating deep learning and co-evolutionary analysis. Using ResNet, predictions of correct protein folds have been successful even without co-evolution information, suggesting potential for learning important protein sequence-structure relationships.

NATURE MACHINE INTELLIGENCE (2021)

Article Multidisciplinary Sciences

Improved protein structure prediction using potentials from deep learning

Andrew W. Senior et al.

NATURE (2020)

Article Multidisciplinary Sciences

Improved protein structure prediction using predicted interresidue orientations

Jianyi Yang et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2020)

Review Biochemistry & Molecular Biology

How Do Molecular Dynamics Data Complement Static Structural Data of GPCRs

Mariona Torrens-Fontanals et al.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2020)

Article Multidisciplinary Sciences

Conformational states dynamically populated by a kinase determine its function

Tao Xie et al.

SCIENCE (2020)

Article Multidisciplinary Sciences

Predicting binding sites from unbound versus bound protein structures

Jordan J. Clark et al.

SCIENTIFIC REPORTS (2020)

Article Biochemical Research Methods

RCSB Protein Data Bank 1D tools and services

Joan Segura et al.

BIOINFORMATICS (2020)

Article Multidisciplinary Sciences

Defining a new nomenclature for the structures of active and inactive kinases

Vivek Modi et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2019)

Article Multidisciplinary Sciences

Distance-based protein folding powered by deep learning

Jinbo Xu

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2019)

Article Multidisciplinary Sciences

DESTINI: A deep-learning approach to contact-driven protein structure prediction

Mu Gao et al.

SCIENTIFIC REPORTS (2019)

Review Biochemistry & Molecular Biology

Cryptic binding sites on proteins: definition, detection, and druggability

Sandor Vajda et al.

CURRENT OPINION IN CHEMICAL BIOLOGY (2018)

Review Biochemistry & Molecular Biology

The Molecular Basis of G Protein-Coupled Receptor Activation

William I. Weis et al.

ANNUAL REVIEW OF BIOCHEMISTRY, VOL 87 (2018)

Article Chemistry, Medicinal

FINDSITEcomb2.0: A New Approach for Virtual Ligand Screening of Proteins and Virtual Target Screening of Biomolecules

Hongyi Zhou et al.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2018)

Article Biochemistry & Molecular Biology

Template-based protein structure prediction in CASP11 and retrospect of I-TASSER in the last decade

Jianyi Yang et al.

PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS (2016)

Article Chemistry, Medicinal

Mapping Functional Group Free Energy Patterns at Protein Occluded Sites: Nuclear Receptors and G-Protein Coupled Receptors

Sirish Kaushik Lakkaraju et al.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2015)

Article Chemistry, Physical

Are protein-protein interfaces special regions on a protein's surface?

Sam Tonddast-Navaei et al.

JOURNAL OF CHEMICAL PHYSICS (2015)

Article Biochemistry & Molecular Biology

ChSeq: A database of chameleon sequences

Wenlin Li et al.

PROTEIN SCIENCE (2015)

Article Multidisciplinary Sciences

Comprehensive prediction of drug-protein interactions and side effects for the human proteome

Hongyi Zhou et al.

SCIENTIFIC REPORTS (2015)

Review Chemistry, Multidisciplinary

Protein Conformational Populations and Functionally Relevant Substates

Arvind Ramanathan et al.

ACCOUNTS OF CHEMICAL RESEARCH (2014)

Article Chemistry, Physical

Further Evidence for the Likely Completeness of the Library of Solved Single Domain Protein Structures

Jeffrey Skolnick et al.

JOURNAL OF PHYSICAL CHEMISTRY B (2012)

Review Biotechnology & Applied Microbiology

Protein structure prediction from sequence variation

Debora S. Marks et al.

NATURE BIOTECHNOLOGY (2012)

Article Biochemistry & Molecular Biology

Template-based protein structure modeling using TASSERVMT

Hongyi Zhou et al.

PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS (2012)

Article Biochemical Research Methods

iAlign: a method for the structural comparison of protein-protein interfaces

Mu Gao et al.

BIOINFORMATICS (2010)

Article Biochemical Research Methods

I-TASSER: a unified platform for automated protein structure and function prediction

Ambrish Roy et al.

NATURE PROTOCOLS (2010)

Article Multidisciplinary Sciences

Recovering physical potentials from a model protein databank

J. W. Mullinax et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2010)

Article Multidisciplinary Sciences

Structural space of protein-protein interfaces is degenerate, close to complete, and highly connected

Mu Gao et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2010)

Article Biochemistry & Molecular Biology

Predicting the helix packing of globular proteins by self-correcting distance geometry

C.H. Mumenthaler et al.

PROTEIN SCIENCE (2010)

Article Biochemical Research Methods

Fr-TM-align: a new protein structural alignment method based on fragment alignments and the TM-score

Shashi Bhushan Pandit et al.

BMC BIOINFORMATICS (2008)

Article Biochemical Research Methods

I-TASSER server for protein 3D structure prediction

Yang Zhang

BMC BIOINFORMATICS (2008)

Article Multidisciplinary Sciences

A threading-based method (FINDSITE) for ligand-binding site prediction and functional annotation

Michal Brylinski et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2008)

Article Biophysics

Ab initio protein structure prediction using Chunk-TASSER

Hongyi Zhou et al.

BIOPHYSICAL JOURNAL (2007)

Article Multidisciplinary Sciences

On the origin and highly likely completeness of single-domain protein structures

Y Zhang et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2006)

Article Multidisciplinary Sciences

The protein structure prediction problem could be solved using the current PDB library

Y Zhang et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2005)

Article Biochemistry & Molecular Biology

TM-align: a protein structure alignment algorithm based on the TM-score

Y Zhang et al.

NUCLEIC ACIDS RESEARCH (2005)