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We propose and discuss a novel strategy for protein design. The method is based on recent theoretical advancements which showed the importance to treat carefully the conformational free energy of designed sequences. In this work we show how…

Statistical Mechanics · Physics 2009-10-31 A. Rossi , A. Maritan , C. Micheletti

Protein design is the inverse approach of the three-dimensional (3D) structure prediction for elucidating the relationship between the 3D structures and amino acid sequences. In general, the computation of the protein design involves a…

Biological Physics · Physics 2021-07-14 Tomoei Takahashi , George Chikenji , Kei Tokita

Proteins are essential biological macromolecules that execute life functions. Local structural motifs, such as active sites, are the most critical components for linking structure to function and are key to understanding protein evolution…

Quantitative Methods · Quantitative Biology 2026-04-10 Zhiyu Wang , Bingxin Zhou , Jing Wang , Yang Tan , Weishu Zhao , Pietro Liò , Liang Hong

Recent studies have shown competitive performance in protein design that aims to find the amino acid sequence folding into the desired structure. However, most of them disregard the importance of predictive confidence, fail to cover the…

Biomolecules · Quantitative Biology 2023-05-31 Zhangyang Gao , Cheng Tan , Stan Z. Li

Deep learning in \emph{de novo} protein design has achieved atomic-level fidelity. However, existing models remain largely non-deliberative: they directly synthesize molecular geometries without explicitly reasoning about which residues or…

We present a model, based on symmetry and geometry, for proteins. Using elementary ideas from mathematics and physics, we derive the geometries of discrete helices and sheets. We postulate a compatible solvent-mediated emergent pairwise…

Soft Condensed Matter · Physics 2023-06-21 Jayanth R. Banavar , Achille Giacometti , Trinh X. Hoang , Amos Maritan , Tatjana Škrbić

Predicting protein secondary structure using lattice model is one of the most studied computational problem in bioinformatics. Here secondary structure or three dimensional structure of protein is predicted from its amino acid sequence.…

Computational Engineering, Finance, and Science · Computer Science 2014-07-18 Dipan Lal Shaw , M. Sohel Rahman , A. S. M. Sohidull Islam , Shuvasish Karmaker

Computational protein structure determination involves optimization in a problem space much too large to exhaustively search. Existing approaches include optimization algorithms such as gradient descent and simulated annealing, but these…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-08-04 Michael Bryson , Xijiang Miao , Homayoun Valafar

Changes in the extent of local concavity along with changes in surface roughness of binding sites of proteins have long been considered as useful markers to identify functional sites of proteins. However, an algorithm that describes the…

Biomolecules · Quantitative Biology 2011-11-29 Anirban Banerji

We present a novel statistical mechanics formalism for the theoretical description of the process of protein folding$\leftrightarrow$unfolding transition in water environment. The formalism is based on the construction of the partition…

Biological Physics · Physics 2010-05-20 A. V. Yakubovich , A. V. Solov'yov , W. Greiner

We discuss a stochastic approach for reconstructing the native structures of proteins from the knowledge of the "effective connectivity", which is a one-dimensional structural profile constructed as a linear combination of the eigenvectors…

Biological Physics · Physics 2009-01-20 Katrin Wolff , Michele Vendruscolo , Markus Porto

In spite of decades of research, much remains to be discovered about folding: the detailed structure of the initial (unfolded) state, vestigial folding instructions remaining only in the unfolded state, the interaction of the molecule with…

Biological Physics · Physics 2018-11-26 Walter A. Simmons

Proteins fold to a specific functional conformation with a densely packed hydrophobic core that controls their stability. We develop a geometric, yet all-atom model for proteins that explains the universal core packing fraction of…

Soft Condensed Matter · Physics 2025-03-28 Alex T. Grigas , Zhuoyi Liu , Jack A. Logan , Mark D. Shattuck , Corey S. O'Hern

The design and optimization of antibodies requires an intricate balance across multiple properties. Protein inverse folding models, capable of generating diverse sequences folding into the same structure, are promising tools for maintaining…

Protein-protein interactions (protein functionalities) are mediated by water, which compacts individual proteins and promotes close and temporarily stable large-area protein-protein interfaces. In their classic paper Kyte and Doolittle (KD)…

Soft Condensed Matter · Physics 2009-11-13 Alexander E. Kister , James C. Phillips

Revealing the structure of complex biological macromolecules, such as proteins, is an essential step for understanding the chemical mechanisms that determine the diversity of their functions. Synchrotron based x-ray crystallography and…

Proteins are essential for life, and their structure determines their function. The protein secondary structure is formed by the folding of the protein primary structure, and the protein tertiary structure is formed by the bending and…

Biomolecules · Quantitative Biology 2024-03-11 Yanlin Zhou , Kai Tan , Xinyu Shen , Zheng He , Haotian Zheng

Using an off-lattice model, we fully enumerate folded conformations of polypeptide chains of up to N = 19 monomers. Structures are found to differ markedly in designability, defined as the number of sequences with that structure as a unique…

Soft Condensed Matter · Physics 2007-05-23 Eldon G. Emberly , Jonathan Miller , Chen Zeng , Ned S. Wingreen , Chao Tang

Smooth and curved microstructural topologies found in nature - from soap films to trabecular bone - have inspired several mimetic design spaces for architected metamaterials and bio-scaffolds. However, the design approaches so far have been…

Computational Engineering, Finance, and Science · Computer Science 2024-04-17 Yaqi Guo , Saurav Sharma , Siddhant Kumar

Recent advances in protein structure prediction, such as AlphaFold, have demonstrated the power of deep neural architectures like the Evoformer for capturing complex spatial and evolutionary constraints on protein conformation. However, the…

Machine Learning · Computer Science 2026-05-14 Arielle Sanford , Shuo Sun , Christian B. Mendl
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