Protein folding: from the levinthal paradox to structure prediction

Honig, Barry

doi:10.1006/jmbi.1999.3006

Cited by 145 publications

(110 citation statements)

References 72 publications

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“…Trees with very short stems and many low-energy branches are characteristic of glassy potential energy surfaces, which are associated with Levinthals paradox [25,26] in the context of protein folding. Well structured trees with few terminal branches suggest the existence of a folding funnel [13], consistent with the "new" paradigm for protein folding [27].…”

Section: Modelmentioning

confidence: 99%

In SilicoFolding of a Three Helix Protein and Characterization of Its Free-Energy Landscape in an All-Atom Force Field

Herges

Wenzel

2005

Phys. Rev. Lett.

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We report the reproducible first-principles folding of the 40 amino acid, three-helix headpiece of the HIV accessory protein in a recently developed all-atom free-energy forcefield. Six of twenty simulations using an adapted basin-hopping method converged to better than 3Å backbone RMS deviation to the experimental structure. Using over 60,000 low-energy conformations of this protein, we constructed a decoy tree that completely characterizes its folding funnel.PACS numbers: 87.15. Cc,02.70.Ns,02.60.Pn Available genomic and sequence information for proteins contains a wealth of biomedical information that becomes accessible when translated into three-dimensional structure [1]. While theoretical models for protein structure prediction [2,3] that partially rely on experimental information have shown consistent progress [4], the assessment of de-novo strategies that rely on sequence information alone has been much less favorable [5]. The development of such techniques, in particular of transferable first-principle all-atom folding methods, would significantly benefit the understanding of protein families where little experimental information is available, the prediction of novel folds as well as the investigation of protein association and dynamics which are presently difficult to probe experimentally. Recent progress for small peptides [3,6,7,8] documents both the feasibility of this approach as well as its limitations [9,10], in particualr those associated with the direct simulation of the folding process through molecular dynamics [11].Overwhelming experimental evidence supports the thermodynamic hypothesis [12] that many proteins are in thermodynamic equilibrium with their environment: their native state thus corresponds to the global minimum of their free energy landscape [13]. The free energy of the system is accessible either indirectly by explicit ensemble averaging of the combined internal energy of protein and solvent, or directly in a free-energy forcefield where an implicit solvation model approximates direct interactions with the solvent as well as most of the entropic contributions. We developed an all-atom protein forcefield (PFF01) [8,14,15] with an area-based implicit solvent model that approximates the free energy of peptide conformations in the natural solvent. Using a rational decoy approach this forcefield was optimized to correctly predict the native structure of the 36-amino acid headgroup of villin [9,10,11]. Without further parameter adjustment we then simulated the structurally conserved 40 amino-acid headpiece of the autonomously folding HIV accessory protein (1F4I-40) [16] with a modified basin hopping technique [17,18]. Out of twenty simulations the five energetically lowest correctly reproduced the NMR structure of this three-helix protein with a backbone RMS deviation of less than 3Å. The combination of decoy based model development for the free energy with efficient stochastic optimization methods suggests a viable route for protein structure prediction at the all atom level with p...

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Section: Modelmentioning

confidence: 99%

In SilicoFolding of a Three Helix Protein and Characterization of Its Free-Energy Landscape in an All-Atom Force Field

Herges

Wenzel

2005

Phys. Rev. Lett.

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“…uch interest is currently focused on the rapid and faithful folding of proteins from a one-dimensional sequence of amino acids in a random coil, to a three-dimensional biologically functional structure in the native state (1)(2)(3)(4). Chemical and thermal denaturation of proteins are standard techniques in protein biochemistry to determine protein folding and unfolding equilibria and kinetics (3,5,6).…”

mentioning

confidence: 99%

Protein unfolding: Rigidity lost

Rader

Hespenheide

Kuhn

et al. 2002

Proc. Natl. Acad. Sci. U.S.A.

261

298

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We relate the unfolding of a protein to its loss of structural stability or rigidity. Rigidity and flexibility are well defined concepts in mathematics and physics, with a body of theorems and algorithms that have been applied successfully to materials, allowing the constraints in a network to be related to its deformability. Here we simulate the weakening or dilution of the noncovalent bonds during protein unfolding, and identify the emergence of flexible regions as unfolding proceeds. The transition state is determined from the inflection point in the change in the number of independent bond-rotational degrees of freedom (floppy modes) of the protein as its mean atomic coordination decreases. The first derivative of the fraction of floppy modes as a function of mean coordination is similar to the fraction-folded curve for a protein as a function of denaturant concentration or temperature. The second derivative, a specific heat-like quantity, shows a peak around a mean coordination of ͗r͘ ‫؍‬ 2.41 for the 26 diverse proteins we have studied. As the protein denatures, it loses rigidity at the transition state, proceeds to a state where just the initial folding core remains stable, then becomes entirely denatured or flexible. This universal behavior for proteins of diverse architecture, including monomers and oligomers, is analogous to the rigid to floppy phase transition in network glasses. This approach provides a unifying view of the phase transitions of proteins and glasses, and identifies the mean coordination as the relevant structural variable, or reaction coordinate, along the unfolding pathway. Much interest is currently focused on the rapid and faithful folding of proteins from a one-dimensional sequence of amino acids in a random coil, to a three-dimensional biologically functional structure in the native state (1-4). Chemical and thermal denaturation of proteins are standard techniques in protein biochemistry to determine protein folding and unfolding equilibria and kinetics (3,5,6).A general view of protein folding is that it begins with hydrophobic collapse, in which the random coil changes to a compact state, with the hydrophobic groups in the interior region and polar groups at the surface interacting with the surrounding water. The packing is not yet optimal, with hydrophobic groups somewhat free to slide about in the interior of the globule, until residues are locked in place by the formation of specific hydrogen bonds. These hydrogen bonds can be regarded as a sort of Velcro that locks the various structural elements in the folded protein together. Once these interactions are optimized, the native state is predominantly rigid with flexible hinges or loops at the surface-the number and distribution of these depending on the particular protein.There have been many significant theoretical advances in understanding protein folding in recent years-including the concept of a funnel-shaped free-energy landscape (1, 7-9), simplified lattice models that are more tractable for simulations of folding (8, ...

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“…Bu duruma Levinthal Paradoksu denir [27]. Proteinler katlanırken büyük enerji engellerini aşmayacak şekilde ilerledikleri kabulü büyük enerji değişimleri olmadan sürecin modellenmesi genel kabulünü getirmiştir.…”

Section: Protein Yapı Tahmini (Protein Structure Prediction)unclassified

Ayrik Yapay Ari Koloni̇si̇ Algori̇tmasi İle Protei̇n Yapisi Tahmi̇ni̇

Batbat

Öztürk

2016

BTD

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Özet-Proteinlerin yerine getirdiği görevler üçüncül yapıları olarak adlandırılan doğal durumlarına doğrudan bağlıdır. Günümüzde birçok proteinin birincil yapı olarak adlandırılan dizilimleri bilinmekle beraber işlevlerini belirleyen üçüncül yapıları bilinmemektedir. Ele alınan dizide bulunan amino asitlerin üçüncül yapı oluşumuna yol açan özelliklerinin kullanılarak üçüncül yapılarının tahmin edilmesi proteinlerin gerçek doğasının tam anlaşılmasının önünü açacaktır. Proteinlerin üçüncül yapıları ile ilgili yapılan çalışmalarda en düşük serbest enerji düzeyinin elde edilmesi eğilimi tespit edilmiştir. Serbest enerji düzeylerini hesaplamada, sudan kaçma özelliği yoğun olarak kullanılmaktadır. Bu özelliğe göre sınıflandırılan amino asitleri temel alan HP modeli basitliği ve gerçekçiliği ile dikkat çekmektedir. Çalışmamızda HP modelinin doğadaki protein davranışı incelenerek geliştirilmiş bir türü olan Üç Boyutlu Hidrofobik Polar Yan Zincir modeli kullanılmıştır. Proteinlerin üçüncül yapı modellerinin bulunmasında arıların besin arama davranışlarını modelleyen Yapay Arı Kolonisi Algoritması temelli oluşturulan ayrık bir model önerilmiştir. Benzer çalışmalarda kullanılan başarımların test edildiği örnek dizilerde daha az maliyetle iyi sonuçlar alınmıştır. Abstract-Tasks that proteins perform are directly related to native conditions named their tertiary structure. Although arrays of numerous proteins' primary structure are known, tertiary structures those explain their functions are not well defined. Studies on translation of proteins to their tertiary structure found tendency of provision of minimal free energy level. HP model, used in calculation of free energy levels and based on the amino acids grouped by their hydrophobic characteristics, is standing out with its simplicity and authenticity. In this paper, three-dimensional hydrophobic side chain model that was developed by investigation of the protein behavior of HP model in nature was used. A new discrete model based on Artificial Bee Colony Algorithm that is simulating the foraging behaviors of bees is proposed to form the protein tertiary structures. The success of proposed model is tested on widely used benchmark protein arrays and compared with the results of similar methods from literature.

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Protein folding: from the levinthal paradox to structure prediction

Cited by 145 publications

References 72 publications

In SilicoFolding of a Three Helix Protein and Characterization of Its Free-Energy Landscape in an All-Atom Force Field

In SilicoFolding of a Three Helix Protein and Characterization of Its Free-Energy Landscape in an All-Atom Force Field

Protein unfolding: Rigidity lost

Ayrik Yapay Ari Koloni̇si̇ Algori̇tmasi İle Protei̇n Yapisi Tahmi̇ni̇

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