Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 83 for “"protein design"”.
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Protein Design at Library Scale
Recent advances in de novo protein design have made it increasingly feasibleto create proteins with novel functions, driven by rapid progress in both com- putational modeling and high-throughput experimentation. Modern tools can explore vast sequence-structure spaces and evaluate biomolecular …
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Protein design using artificial intelligence
… can be leveraged to accelerate the discovery and design of new pharmaceuticals. Each chapter addresses different aspects of the drug design process, proposing software solutions aimed at enhancing the productivity of researchers in the field. The contributions section of the thesis begins with the …
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De Novo Heme Protein Design
… way to explain this is that OR is a metalloprotein. We have found a consensus sequence ""HXXCE"" in the 4--5 loop of ORs, which not only binds strongly to Cu2+ and Zn2+, but also turns alpha helical after metal binding. Since the 4--5 loop is as hydrophobic as the fourth helix of OR, charge …
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Methods and applications in computational protein design
… on applications and methods for computational protein design. First, we apply computational protein design to address the problem of degradation in stored proteins. Specifically, we target cysteine, asparagine, glutamine, and methionine amino acid residues to reduce or eliminate a protein's …
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Exact rotamer optimization for computational protein design
… the global minimum energy conformation (GMEC) of protein side chains is an important computational challenge in protein structure prediction and design. Using rotamer models, the problem is formulated as a NP-hard optimization problem. Dead-end elimination (DEE) methods combined with systematic A* …
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Multistate Computational Protein Design: Theories, Methods, and Applications
Traditional computational protein design (CPD) calculations model sequence perturbations and evaluate their stabilities using a single fixed protein backbone template in an approach referred to as single‐state design (SSD). However, certain design objectives require the explicit consideration of …
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Computational tools for including specificity in protein design
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.
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Generative Diffusion Models Towards De Novo Protein Design
De novo protein design aims to generate proteins with desired functions by rationally engineering novel protein structures and sequences. The structure requires modeling continuous 3D coordinates of atoms with rigid biochemical constraints of the polymer chain while the sequence is a series of …
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Enhanced Potts Models for Improved Computational Protein Design
Proteins are the fundamental building blocks of life, contributing to the structure, function, and regulation of all living cells. The ability to computationally design proteins to serve specific functions is thus of particular interest to the bioengineering and biomedical fields. TERMinator is a …
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Protein design with hierarchical treatment of solvation and electrostatics
… numbers of states: multiple-site titration and protein design. The continuum electrostatic model is combined with covalent, van der Waals, and non-polar energy terms, and the statistical mechanical basis for this model is reviewed. Multiple-site titration is modeled with four titratable residues …
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Models for transition metal oxides and for protein design
A large number of properties of solid state materials can now be predicted with standard first-principles methods such as the Local Density (LDA) or Generalized Gradient Approximation (GGA). However, known problems exist when using these methods for predicting the electronic structure and total …
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Uncovering Biophysical Determinants Of Oxidoreductase Function Through De Novo Protein Design
… and cellular respiratory machinery, “redox proteins” and the catalysis they enable form the foundation biological energy transduction. Mastering the mechanisms by which these enzymes work is the key to understanding how life works and drives the improvement of an as of yet poorly developed …
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Distinct Functional Phases in Proteins: A Test by Large-Scale Protein Design
Note: The general metadata -- e.g., title, author, abstract, subject headings, etc. -- is publicly available, but access to the submitted files is restricted to UT Southwestern campus access only.
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Development of Neural Networks for Biomolecular Structure Prediction with Applications to Protein Design
… structure of biomolecular complexes including proteins, nucleic acids, and small molecules. First, we developed a general neural network architecture for the prediction of biomolecular complexes in the Protein Data Bank (PDB). We then demonstrated the ability of this model to predict the …
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MULTIPLE STRATEGIES IN COMPUTATIONAL PROTEIN DESIGN: STRUCTURAL INTUITION, PROBABILISTIC INVERSE FOLDING, AND GENERATIVE APPROACHES
Designing proteins with specific structural and functional features has become increasingly feasible through the integration of physics-based modeling, statistical inference, and generative algorithms. This work presents conceptual, methodological, and applied examples spanning multiple stages of …
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Efficient New Computational Protein Design Algorithms, with Applications to Drug Resistance Prediction and HIV Antibody Design
<p>Proteins are essential for myriad biological functions, including DNA replication, molecular transport, catalysis, and antigen recognition. Protein function is determined by three dimensional structure, which is largely determined by amino acid composition. The functional diversity of known …
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Engineering TEV Protease Specificity: An Exploration of Machine Learning and High-Throughput Experimentation for Protein Design
… learning (ML) methods for highly effective protein engineering. The first portion of this thesis focuses on generating fitness landscapes from high-throughput experiments. Most machine learning models do not account for experimental noise, harming model performance and changing model …
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Statistical physics and biological information : hydrophobicity patterns in protein design and differential motif finding in DNA
… that correlations in solvent accessibility along protein structures play a key role in the designability phenomenon, for both lattice and natural proteins. Without such correlations, as predicted by the Random Energy Model (REM), all structures will have almost equal values of designability. By …
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Toward a Database of Geometric Interrelationships of Protein Secondary Structure Elements for De Novo Protein Design, Prediction and Analysis
… methods of analyzing, simulating, and modeling proteins are essential towards understanding protein structure and its interactions. Computational methods are easier as not all protein structures can be determined experimentally due to the inherent difficultly of working with some proteins. In …
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