Results 31 to 40 of about 16,987,595 (305)
CoRR, 2018 We review algorithms for protein design in general. Although these algorithms have a rich combinatorial, geometric, and mathematical structure, they are almost never covered in computer science classes. Furthermore, many of these algorithms admit provable guarantees of accuracy, soundness, complexity, completeness, optimality, and approximation bounds.
Mark A. Hallen, Bruce Randall Donald
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Methods in Computational Protein Design [PDF]
, 2008 In silico design of protein has generated enormous interest with the rapid advances in computational power. Biological systems are known for their complexity, and we have made a series of computational developments that allow us to perform computational
Kam, Victor Wai Tak
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Machine Learning to Identify Flexibility Signatures of Class A GPCR Inhibition
Biomolecules, 2020 We show that machine learning can pinpoint features distinguishing inactive from active states in proteins, in particular identifying key ligand binding site flexibility transitions in GPCRs that are triggered by biologically active ligands. Our analysis
Joseph Bemister-Buffington +3 more
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Scientific Reports, 2022 We have recently developed a mouse monoclonal antibody (12–10H) binding to the head domain region in rat P2X4 receptor (rP2X4R, which is crucial for the pathogenesis of neuropathic pain) expressed on the cell with the highest binding affinity (K D = 20 ...
Chinatsu Shinozaki +11 more
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Tacit Learning in an Extended Interior Design Studio [PDF]
, 2019 5th DRS Learn X Design International Conference for Design Education Researchers: Insider Knowledge, 9-12 July 2019, METU, Ankara202403 bckwVersion of RecordSelf ...
Venkatesh, A +5 more
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Crystal structure correlations with the intrinsic thermodynamics of human carbonic anhydrase inhibitor binding [PDF]
PeerJ, 2018 The structure-thermodynamics correlation analysis was performed for a series of fluorine- and chlorine-substituted benzenesulfonamide inhibitors binding to several human carbonic anhydrase (CA) isoforms.
Alexey Smirnov +4 more
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De novo design of immunoglobulin-like domains
Nature Communications, 2022 The immunoglobulin domain framework of antibodies has been a long standing design challenge. Here, the authors describe design rules for tailoring these domains and show they can be accurately designed, de novo, with high stability and the ability to ...
Tamuka M. Chidyausiku +13 more
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Computational protein design [PDF]
Current Opinion in Chemical Biology, 2001 The field of computational protein design is reaching its adolescence. Protein design algorithms have been applied to design or engineer proteins that fold, fold faster, catalyze, catalyze faster, signal, and adopt preferred conformational states. Further developments of scoring functions, sampling strategies, and optimization methods will expand the ...
C M, Kraemer-Pecore +2 more
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Machine learning methods for protein-protein binding affinity prediction in protein design
Frontiers in Bioinformatics, 2022 Protein-protein interactions govern a wide range of biological activity. A proper estimation of the protein-protein binding affinity is vital to design proteins with high specificity and binding affinity toward a target protein, which has a variety of ...
Zhongliang Guo +2 more
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Algorithms for protein design [PDF]
Current Opinion in Structural Biology, 2016 Computational structure-based protein design programs are becoming an increasingly important tool in molecular biology. These programs compute protein sequences that are predicted to fold to a target structure and perform a desired function. The success of a program's predictions largely relies on two components: first, the input biophysical model, and
Pablo, Gainza +2 more
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