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Related Concept Videos

Protein-protein Interfaces02:04

Protein-protein Interfaces

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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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Conserved Binding Sites01:49

Conserved Binding Sites

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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
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Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

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Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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Protein Families02:47

Protein Families

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Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key...
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Protein Organization01:24

Protein Organization

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Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....
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Ligand Binding Sites02:40

Ligand Binding Sites

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Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
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Deterministic Search Methods for Computational Protein Design.

Seydou Traoré1,2,3, David Allouche4, Isabelle André1,2,3

  • 1INSA, UPS, INP, Université de Toulouse, 135 Avenue de Rangueil, 31077, Toulouse, France.

Methods in Molecular Biology (Clifton, N.J.)
|December 4, 2016
PubMed
Summary
This summary is machine-generated.

Computational Protein Design (CPD) faces challenges in exploring sequence space. Exact deterministic methods efficiently identify optimal protein models, unlike stochastic approaches.

Keywords:
Cost function networkDead-end-eliminationExact combinatorial optimizationGlobal minimum energy conformationInteger linear programmingMarkov random fieldNear-optimal solutions

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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Area of Science:

  • Computational Biology
  • Protein Engineering
  • Bioinformatics

Background:

  • Computational Protein Design (CPD) struggles with the vast amino-acid sequence space and side chain flexibility.
  • Efficient search methods are crucial for identifying low-energy sequence-conformation models.

Purpose of the Study:

  • To review exact deterministic search methods for Computational Protein Design.
  • To compare these methods against stochastic approaches for finding global minimum energy conformations (GMEC).

Main Methods:

  • Overview of exact deterministic methods: Dead-End-Elimination with A* (DEE/A*), Cost Function Networks (CFN), Integer Linear Programming (ILP), and Markov Random Fields (MRF).
  • Detailed explanation of DEE/A* and CFN for identifying low-energy models from pairwise energy matrices.

Main Results:

  • Deterministic methods guarantee identification of the GMEC, unlike stochastic methods.
  • Four distinct deterministic approaches (DEE/A*, CFN, ILP, MRF) are discussed for their application in CPD.

Conclusions:

  • Exact deterministic methods offer a robust solution for exploring protein sequence space in CPD.
  • DEE/A* and CFN are practical tools for finding optimal protein sequence-conformation models.