Molecular technology: Designing proteins and peptides

By C. Pabo. 1983

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Citations in the corpus

ProDCoNN: Protein design using a convolutional neural network (2019, background): “The inverse protein folding (IPF) problem, which was raised in 1983 by Pabo, 11 is the problem of finding the amino acid sequences that fold into a known three-dimensional (3D) structure.”
Energy-based models for atomic-resolution protein conformations (2020, methodology): “The generalization of neural energy functions to harder problem settings used in the protein design community, e.g. combinatorial side chain optimization (Tuffery et al., 1991; Holm & Sander, 1992), and inverse-folding (Pabo, 1983), is a direction for future work.”
Computational design of water-soluble α-helical barrels (2014, background): “Defining protein sequences that fold into specified three-dimensional structures is called the ‘inverse protein-folding problem’ (1).”
High-resolution Structural and Thermodynamic Analysis of Extreme Stabilization of Human Procarboxypeptidase by Computational Protein Design (2007, background): “The most common is to hold the co-ordinates of protein backbone atoms fixed, and to select residues that stabilize this conformation; this is often referred to as the “inverse folding problem”.(27) Furthermore, side-chain torsional degrees of freedom are typically restricted to a discrete set of com”
AlphaDesign: A graph protein design method and benchmark on AlphaFoldDB (2022, background): “While AlphaFold2 (Jumper et al., 2021) has tentatively solved protein folding from 1D sequences to 3D structures, its reverse problem, i.e., protein design raised by (Pabo, 1983) that aims to predict amino acid sequences from known 3D structures, has fewer break-throughs in the ML community.”
De Novo Protein Design for Novel Folds using Guided Conditional Wasserstein Generative Adversarial Networks (gcWGAN) (2019, background): “Since then, the direct exploration of sequence–structure relationship has led to both the forward problem of structure prediction from sequence (Baker and Sali, 2001) as wellastheinverseproblemofsequencedesignfordesiredstructures(Pabo, 1983; Street and Mayo, 1999).”
Algorithms for Protein Design (2016, background): “This latter stage has been historically referred to as protein design [28].”
Automated design of specificity in molecular recognition (2003, background): “Most design studies follow the 'inverted-folding' strategy in which an optimal sequence for a preexisting backbone is selected by the design algorith”
Achievements and Challenges in Computational Protein Design. (2017, background): “In 1983 Pabo wrote about designing proteins and peptides concluding that it may be difficult to design proteins which carry out a particular function but the use of pre-folded backbone configuration may be useful at this stage [4].”