1
|
Grigas AT, Fisher A, Shattuck MD, O'Hern CS. Connecting polymer collapse and the onset of jamming. Phys Rev E 2024; 109:034406. [PMID: 38632799 DOI: 10.1103/physreve.109.034406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Accepted: 02/13/2024] [Indexed: 04/19/2024]
Abstract
Previous studies have shown that the interiors of proteins are densely packed, reaching packing fractions that are as large as those found for static packings of individual amino-acid-shaped particles. How can the interiors of proteins take on such high packing fractions given that amino acids are connected by peptide bonds and many amino acids are hydrophobic with attractive interactions? We investigate this question by comparing the structural and mechanical properties of collapsed attractive disk-shaped bead-spring polymers to those of three reference systems: static packings of repulsive disks, of attractive disks, and of repulsive disk-shaped bead-spring polymers. We show that the attractive systems quenched to temperatures below the glass transition T≪T_{g} and static packings of both repulsive disks and bead-spring polymers possess similar interior packing fractions. Previous studies have shown that static packings of repulsive disks are isostatic at jamming onset, i.e., the number of interparticle contacts N_{c} matches the number of degrees of freedom, which strongly influences their mechanical properties. We find that repulsive polymer packings are hypostatic at jamming onset (i.e., with fewer contacts than degrees of freedom) but are effectively isostatic when including stabilizing quartic modes, which give rise to quartic scaling of the potential energy with displacements along these modes. While attractive disk and polymer packings are often considered hyperstatic with excess contacts over the isostatic number, we identify a definition for interparticle contacts for which they can also be considered as effectively isostatic. As a result, we show that the mechanical properties (e.g., scaling of the potential energy with excess contact number and low-frequency contribution to the density of vibrational modes) of weakly attractive disk and polymer packings are similar to those of isostatic repulsive disk and polymer packings. Our results demonstrate that static packings generated via attractive collapse or compression of repulsive particles possess similar structural and mechanical properties.
Collapse
Affiliation(s)
- Alex T Grigas
- Graduate Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520, USA
- Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut 06520, USA
| | - Aliza Fisher
- Department of Mechanical Engineering and Materials Science, Yale University, New Haven, Connecticut 06520, USA
| | - Mark D Shattuck
- Benjamin Levich Institute and Physics Department, The City College of New York, New York, New York 10031, USA
| | - Corey S O'Hern
- Graduate Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520, USA
- Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut 06520, USA
- Department of Mechanical Engineering and Materials Science, Yale University, New Haven, Connecticut 06520, USA
- Department of Physics, Yale University, New Haven, Connecticut 06520, USA
- Department of Applied Physics, Yale University, New Haven, Connecticut 06520, USA
| |
Collapse
|
2
|
Grigas AT, Liu Z, Regan L, O'Hern CS. Core packing of well-defined X-ray and NMR structures is the same. Protein Sci 2022; 31:e4373. [PMID: 35900019 PMCID: PMC9277709 DOI: 10.1002/pro.4373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 05/06/2022] [Accepted: 06/02/2022] [Indexed: 11/10/2022]
Abstract
Numerous studies have investigated the differences and similarities between protein structures determined by solution NMR spectroscopy and those determined by X-ray crystallography. A fundamental question is whether any observed differences are due to differing methodologies or to differences in the behavior of proteins in solution versus in the crystalline state. Here, we compare the properties of the hydrophobic cores of high-resolution protein crystal structures and those in NMR structures, determined using increasing numbers and types of restraints. Prior studies have reported that many NMR structures have denser cores compared with those of high-resolution X-ray crystal structures. Our current work investigates this result in more detail and finds that these NMR structures tend to violate basic features of protein stereochemistry, such as small non-bonded atomic overlaps and few Ramachandran and sidechain dihedral angle outliers. We find that NMR structures solved with more restraints, and which do not significantly violate stereochemistry, have hydrophobic cores that have a similar size and packing fraction as their counterparts determined by X-ray crystallography at high resolution. These results lead us to conclude that, at least regarding the core packing properties, high-quality structures determined by NMR and X-ray crystallography are the same, and the differences reported earlier are most likely a consequence of methodology, rather than fundamental differences between the protein in the two different environments.
Collapse
Affiliation(s)
- Alex T. Grigas
- Graduate Program in Computational Biology and BioinformaticsYale UniversityNew HavenConnecticutUSA
- Integrated Graduate Program in Physical and Engineering BiologyYale UniversityNew HavenConnecticutUSA
| | - Zhuoyi Liu
- Integrated Graduate Program in Physical and Engineering BiologyYale UniversityNew HavenConnecticutUSA
- Department of Mechanical Engineering and Materials ScienceYale UniversityNew HavenConnecticutUSA
| | - Lynne Regan
- Institute of Quantitative Biology, Biochemistry and BiotechnologyCentre for Synthetic and Systems Biology, School of Biological Sciences, University of EdinburghEdinburghUK
| | - Corey S. O'Hern
- Graduate Program in Computational Biology and BioinformaticsYale UniversityNew HavenConnecticutUSA
- Integrated Graduate Program in Physical and Engineering BiologyYale UniversityNew HavenConnecticutUSA
- Department of Mechanical Engineering and Materials ScienceYale UniversityNew HavenConnecticutUSA
- Department of PhysicsYale UniversityNew HavenConnecticutUSA
- Department of Applied PhysicsYale UniversityNew HavenConnecticutUSA
| |
Collapse
|
3
|
Grigas AT, Mei Z, Treado JD, Levine ZA, Regan L, O'Hern CS. Using physical features of protein core packing to distinguish real proteins from decoys. Protein Sci 2020; 29:1931-1944. [PMID: 32710566 PMCID: PMC7454528 DOI: 10.1002/pro.3914] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Revised: 07/10/2020] [Accepted: 07/20/2020] [Indexed: 01/06/2023]
Abstract
The ability to consistently distinguish real protein structures from computationally generated model decoys is not yet a solved problem. One route to distinguish real protein structures from decoys is to delineate the important physical features that specify a real protein. For example, it has long been appreciated that the hydrophobic cores of proteins contribute significantly to their stability. We used two sources to obtain datasets of decoys to compare with real protein structures: submissions to the biennial Critical Assessment of protein Structure Prediction competition, in which researchers attempt to predict the structure of a protein only knowing its amino acid sequence, and also decoys generated by 3DRobot, which have user-specified global root-mean-squared deviations from experimentally determined structures. Our analysis revealed that both sets of decoys possess cores that do not recapitulate the key features that define real protein cores. In particular, the model structures appear more densely packed (because of energetically unfavorable atomic overlaps), contain too few residues in the core, and have improper distributions of hydrophobic residues throughout the structure. Based on these observations, we developed a feed-forward neural network, which incorporates key physical features of protein cores, to predict how well a computational model recapitulates the real protein structure without knowledge of the structure of the target sequence. By identifying the important features of protein structure, our method is able to rank decoy structures with similar accuracy to that obtained by state-of-the-art methods that incorporate many additional features. The small number of physical features makes our model interpretable, emphasizing the importance of protein packing and hydrophobicity in protein structure prediction.
Collapse
Affiliation(s)
- Alex T. Grigas
- Graduate Program in Computational Biology and BioinformaticsYale UniversityNew HavenConnecticutUSA
- Integrated Graduate Program in Physical and Engineering BiologyYale UniversityNew HavenConnecticutUSA
| | - Zhe Mei
- Integrated Graduate Program in Physical and Engineering BiologyYale UniversityNew HavenConnecticutUSA
- Department of ChemistryYale UniversityNew HavenConnecticutUSA
| | - John D. Treado
- Integrated Graduate Program in Physical and Engineering BiologyYale UniversityNew HavenConnecticutUSA
- Department of Mechanical Engineering and Materials ScienceYale UniversityNew HavenConnecticutUSA
| | - Zachary A. Levine
- Department of PathologyYale UniversityNew HavenConnecticutUSA
- Department of Molecular Biophysics and BiochemistryYale UniversityNew HavenConnecticutUSA
| | - Lynne Regan
- Institute of Quantitative Biology, Biochemistry and Biotechnology, Centre for Synthetic and Systems Biology, School of Biological SciencesUniversity of EdinburghEdinburghUK
| | - Corey S. O'Hern
- Graduate Program in Computational Biology and BioinformaticsYale UniversityNew HavenConnecticutUSA
- Integrated Graduate Program in Physical and Engineering BiologyYale UniversityNew HavenConnecticutUSA
- Department of Mechanical Engineering and Materials ScienceYale UniversityNew HavenConnecticutUSA
- Department of PhysicsYale UniversityNew HavenConnecticutUSA
- Department of Applied PhysicsYale UniversityNew HavenConnecticutUSA
| |
Collapse
|