Modeling Loops in Protein Structures

Fernández-Fuentes, Narcís; Fiser, András

doi:10.1002/9780470882207.ch13

Cited by 7 publications

(7 citation statements)

References 156 publications

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“… 14 , 41 The missing residues in the PDB structures were reconstructed by Modeller. 42 The initial structure was solvated in a TIP3P water box. 43 The Amber ff99SB force field was used for the protein system.…”

Section: Methodsmentioning

confidence: 99%

Activation Pathways and Free Energy Landscapes of the SARS-CoV-2 Spike Protein

Qian

Yang

et al. 2021

ACS Omega

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uses a spike protein (S-protein) to recognize the receptor protein ACE2 of human cells and initiate infection, during which the conformational transition of the S-protein from inactive (down) state to active (up) state is one of the key molecular events determining the infectivity but the underlying mechanism remains poorly understood. In this work, we investigated the activation pathways and free energy landscape of the S-protein of SARS-CoV-2 and compared with those of the closely related counterpart SARS-CoV using molecular dynamics simulations. Our results revealed a large difference between the activation pathways of the two S-proteins. The transition from inactive to an active state for the S-protein of SARS-CoV-2 is more cooperative, involving simultaneous disruptions of several key interfacial hydrogen bonds, and the transition encounters a much higher free energy barrier. In addition, the conformational equilibrium of the SARS-CoV-2 S-protein is more biased to the inactive state compared to that of the SARS-CoV S-protein, suggesting the transient feature of the active state before binding to the receptor protein of the host cell. The key interactions contributing to the difference of the activation pathways and free energy landscapes were discussed. The results provide insights into the molecular mechanism involved in the initial stage of the SARS-CoV-2 infection.

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Section: Methodsmentioning

confidence: 99%

Activation Pathways and Free Energy Landscapes of the SARS-CoV-2 Spike Protein

Qian

Yang

et al. 2021

ACS Omega

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“…We utilized the MODELLER 34 homology modeling software to build 100 models of each of the acyl-thioester reductase domains of MA-ACR, MB-ACR, and MT-ACR using the following PDB entries as templates: 3M1A-A, 3RKR-A, 3RIH-A, 3AFM-B, 3AFN-B, and 4BMV-A. We built a contact map by determining which pairwise amino acid contacts (defined as two amino acids within a 4.5 Å radius based on any atoms in the amino acids) were present in each model, and weighted each contact by the percentage of models in which the contact was present.…”

Section: Structural Modeling and Schema Library Designmentioning

confidence: 99%

Machine learning-guided acyl-ACP reductase engineering for improved in vivo fatty alcohol production

Greenhalgh

Fahlberg

Pfleger

et al. 2021

Preprint

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Fatty acyl reductases (FARs) catalyze the reduction of thioesters to alcohols and are key enzymes for the microbial production of fatty alcohols. Many existing metabolic engineering strategies utilize these reductases to produce fatty alcohols from intracellular acyl-CoA pools; however, acting on acyl-ACPs from fatty acid biosynthesis has a lower energetic cost and could enable more efficient production of fatty alcohols. Here we engineer FARs to preferentially act on acyl-ACP substrates and produce fatty alcohols directly from the fatty acid biosynthesis pathway. We implemented a machine learning-driven approach to iteratively search the protein fitness landscape for enzymes that produce high titers of fatty alcohols in vivo. After ten design-test-learn rounds, our approach converged on engineered enzymes that produce over twofold more fatty alcohols than the starting natural sequences. We further characterized the top identified sequence and found its improved alcohol production was a result of an enhanced catalytic rate on acyl-ACP substrates, rather than enzyme expression or KM effects. Finally, we analyzed the sequence-function data generated during the enzyme engineering to identify sequence and structure features that influence fatty alcohol production. We found an enzyme's net charge near the substrate-binding site was strongly correlated with in vivo activity on acyl-ACP substrates. These findings suggest future rational design strategies to engineer highly active enzymes for fatty alcohol production.

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“…The combination of the two, or combined methods, usually implying a knowledge-based approach followed by an ab initio one, has been also proposed [71]. In this article, we focused on knowledge-based approaches.…”

Section: Loop Structure Predictionmentioning

confidence: 99%

“…In this article, we focused on knowledge-based approaches. A comprehensive review of loop prediction methods and theory behind can be found elsewhere [71]. stand for α-helix-α-helix, α-helix-3 10 helix, 3 10 helix-α-helix, α-helix-β-strand, β-strand-α-helix, 3 10 helix-3 10 helix, β-strand-3 10 helix, 3 10 helix-β-strand, β-hairpins, and β-links, respectively.…”

Section: Loop Structure Predictionmentioning

confidence: 99%

Smotifs as structural local descriptors of supersecondary elements: classification, completeness and applications

Bonet

Fiser

Oliva

et al. 2014

Bio-Algorithms and Med-Systems

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Protein structures are made up of periodic and aperiodic structural elements (i.e., α-helices, β-strands and loops). Despite the apparent lack of regular structure, loops have specific conformations and play a central role in the folding, dynamics, and function of proteins. In this article, we reviewed our previous works in the study of protein loops as local supersecondary structural motifs or Smotifs. We reexamined our works about the structural classification of loops (ArchDB) and its application to loop structure prediction (ArchPRED), including the assessment of the limits of knowledge-based loop structure prediction methods. We finalized this article by focusing on the modular nature of proteins and how the concept of Smotifs provides a convenient and practical approach to decompose proteins into strings of concatenated Smotifs and how can this be used in computational protein design and protein structure prediction.

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Modeling Loops in Protein Structures

Cited by 7 publications

References 156 publications

Activation Pathways and Free Energy Landscapes of the SARS-CoV-2 Spike Protein

Activation Pathways and Free Energy Landscapes of the SARS-CoV-2 Spike Protein

Machine learning-guided acyl-ACP reductase engineering for improved in vivo fatty alcohol production

Smotifs as structural local descriptors of supersecondary elements: classification, completeness and applications

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