Efficient Method To Count and Generate Compact Protein Lattice Conformations

Kloczkowski, Andrzej; Jernigan, Robert L.

doi:10.1021/ma970662h

Cited by 19 publications

(10 citation statements)

References 13 publications

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“…14 Network representations of protein structures have been employed in the past. [15][16][17][18][19] Brinda et al represented each amino acid in a protein structure by a node and the noncovalent interaction strength between two amino acids was considered in the determination of edges. 20 The constructed representations were called protein structure graphs (PSGs).…”

Section: Introductionmentioning

confidence: 99%

Exploration of the relationship between topology and designability of conformations

Leelananda

Towfic

Jernigan

et al. 2011

The Journal of Chemical Physics

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Protein structures are evolutionarily more conserved than sequences, and sequences with very low sequence identity frequently share the same fold. This leads to the concept of protein designability. Some folds are more designable and lots of sequences can assume that fold. Elucidating the relationship between protein sequence and the three-dimensional (3D) structure that the sequence folds into is an important problem in computational structural biology. Lattice models have been utilized in numerous studies to model protein folds and predict the designability of certain folds. In this study, all possible compact conformations within a set of two-dimensional and 3D lattice spaces are explored. Complementary interaction graphs are then generated for each conformation and are described using a set of graph features. The full HP sequence space for each lattice model is generated and contact energies are calculated by threading each sequence onto all the possible conformations. Unique conformation giving minimum energy is identified for each sequence and the number of sequences folding to each conformation (designability) is obtained. Machine learning algorithms are used to predict the designability of each conformation. We find that the highly designable structures can be distinguished from other non-designable conformations based on certain graphical geometric features of the interactions. This finding confirms the fact that the topology of a conformation is an important determinant of the extent of its designability and suggests that the interactions themselves are important for determining the designability.

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Section: Introductionmentioning

confidence: 99%

Exploration of the relationship between topology and designability of conformations

Leelananda

Towfic

Jernigan

et al. 2011

The Journal of Chemical Physics

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“…Additionally, amino acids in proteins are covalently linked, forming sequences usually containing between tens to hundreds of residues. The simplest mathematical models that mimic the linear nature of the protein sequence, its tight packing in the native state and the exclusion volume effect are compact self-avoiding walks on lattices (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18). The compact self-avoiding walk requires that each of the lattice points must be visited once and only once.…”

Section: Introductionmentioning

confidence: 99%

Shape-dependent designability studies of lattice proteins

Peto¹,

Kloczkowski²,

Jernigan³

2007

J. Phys.: Condens. Matter

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One important problem in computational structural biology is protein designability, that is, why protein sequences are not random strings of amino acids but instead show regular patterns that encode protein structures. Many previous studies that have attempted to solve the problem have relied upon reduced models of proteins. In particular, the 2D square and the 3D cubic lattices together with reduced amino acid alphabet models have been examined extensively and have lead to interesting results that shed some light on evolutionary relationship among proteins. Here we perform designability studies on the 2D square lattice and explore the effects of variable overall shapes on protein designability using a binary hydrophobic-polar (HP) amino acid alphabet. Because we rely on a simple energy function that counts the total number of H-H interactions between non-sequential residues, we restrict our studies to protein shapes that have the same number of residues and also a constant number of non-bonded contacts. We have found that there is a marked difference in the designability between various protein shapes, with some of them accounting for a significantly larger share of the total foldable sequences.

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“…For very simple discrete models, all conformations could be enumerated [20,76,96,141,[255][256][257][258][259][260] and an exact analysis of the model thermodynamics performed [20,261]. Structure and thermodynamics of more complex models are studied via classical molecular dynamics [262 -267] (MD), Monte Carlo (MC) methods [26,109,129,158 -160,167,168, 237,239,268-274], genetic algorithms and hybrid combinations of these methods [275].…”

Section: Sampling Conformational Space Of Reduced Modelsmentioning

confidence: 99%

Reduced models of proteins and their applications

Koliński

Skolnick

2004

Polymer

174

143

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Reduced computer modeling of proteins now has a history of about 30 years. In spite of the enormous increase in computing abilities, reduced models are still very important tools for theoretical studies of protein structure, dynamics and thermodynamics. Very simple, highly idealized lattice (and recently also off-lattice) models could be studied in great detail, providing valuable insight into the most general factors governing structure stability, folding kinetics and interactions responsible for characteristic two-state behavior near the folding temperature. More complex models now enable modeling of real proteins on the level of low to moderate resolution, allowing us to address more detailed questions. Ab initio protein structure predictions, still being far from a routine task, have become feasible. When supported by evolutionary information from multiple sequence alignments and potential local and/or global structural similarity to known structures, reduced modeling opens up new areas of comparative modeling, thereby complementing contemporary structural genomics. q

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Efficient Method To Count and Generate Compact Protein Lattice Conformations

Cited by 19 publications

References 13 publications

Exploration of the relationship between topology and designability of conformations

Exploration of the relationship between topology and designability of conformations

Shape-dependent designability studies of lattice proteins

Reduced models of proteins and their applications

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