Mapping Function from Dynamics: Future Challenges for Network-Based Models of Protein Structures

Proteins fulfill complex and diverse biological functions through the controlled atomic motions of their structures (functional dynamics). The protein composition is given by its amino-acid sequence, which was assumed to encode the function. However, the discovery of functional sequence variants proved that the functional encoding does not come down to the sequence, otherwise a change in the sequence would mean a change of function. Likewise, the discovery that function is fulfilled by a set of structures and not by a unique structure showed that the functional encoding does not come down to the structure either. That leaves us with the possibility that a set of atomic motions, achievable by different sequences and different structures, encodes a specific function. Thanks to the exponential growth in annual depositions in the Protein Data Bank of protein tridimensional structures at atomic resolutions, network models using the Cartesian coordinates of atoms of a protein structure as input have been used over 20 years to investigate protein features. Combining networks with experimental measures or with Molecular Dynamics (MD) simulations and using typical or ad-hoc network measures is well suited to decipher the link between protein dynamics and function. One perspective is to consider static structures alone as alternatives to address the question and find network measures relevant to dynamics that can be subsequently used for mining and classification of dynamic sequence changes functionally robust, adaptable or faulty. This way the set of dynamics that fulfill a function over a diversity of sequences and structures will be determined.

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Wavelet transformed Gaussian network model

Journal of Theoretical and Computational Chemistry ◽

10.1142/s0219633614500539 ◽

2014 ◽

Vol 13 (06) ◽

pp. 1450053 ◽

Cited By ~ 1

Author(s):

Meng Zhan ◽

Suhong Li ◽

Fan Li

Keyword(s):

Protein Dynamics ◽

Network Model ◽

Protein Structures ◽

Network Models ◽

Experimental Results ◽

Gaussian Network Model ◽

The Mean ◽

Dynamics And Function ◽

And Function ◽

Gaussian Network

Accurate prediction of the Debye–Waller temperature factor of proteins is of significant importance in the study of protein dynamics and function. This work explores the utility of wavelets for improving the performance of Gaussian network model (GNM). We propose two wavelet transformed Gaussian network models (wtGNM), namely a scale-one wtGNM and a scale-two wtGNM. Based on a set of 113 protein structures, it shows that the mean correlation with experimental results for the scale-one wtGNM is 0.714 and that for the scale-two wtGNM is 0.738. In contrast, the mean correlation for the original GNM is 0.594. Therefore, the wtGNM is a potential algorithm for improving the GNM prediction of protein B-factors.

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Matching of PDB chain sequences to information in public databases as a prerequisite for 3D functional site visualization

Journal of Integrative Bioinformatics ◽

10.1515/jib-2004-7 ◽

2004 ◽

Vol 1 (1) ◽

pp. 80-89

Author(s):

Guido Dieterich ◽

Dirk W. Heinz ◽

Joachim Reichelt

Keyword(s):

Genetic Disorders ◽

Protein Structures ◽

3D Structure ◽

Data Bank ◽

Mendelian Inheritance ◽

Biological Information ◽

Structure Comparison ◽

3D Structures ◽

Functional Sites ◽

And Function

Abstract The 3D structures of biomacromolecules stored in the Protein Data Bank [1] were correlated with different external, biological information from public databases. We have matched the feature table of SWISS-PROT [2] entries as well InterPro [3] domains and function sites with the corresponding 3D-structures. OMIM [4] (Online Mendelian Inheritance in Man) records, containing information of genetic disorders, were extracted and linked to the structures. The exhaustive all-against-all 3D structure comparison of protein structures stored in DALI [5] was condensed into single files for each PDB entry. Results are stored in XML format facilitating its incorporation into related software. The resulting annotation of the protein structures allows functional sites to be identified upon visualization.

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MIPS: metal interactions in protein structures

Journal of Applied Crystallography ◽

10.1107/s002188980903982x ◽

2009 ◽

Vol 43 (1) ◽

pp. 196-199 ◽

Cited By ~ 19

Author(s):

K. Hemavathi ◽

M. Kalaivani ◽

A. Udayakumar ◽

G. Sowmiya ◽

J. Jeyakanthan ◽

...

Keyword(s):

Protein Structures ◽

Three Dimensional ◽

Data Bank ◽

Metal Interactions ◽

Structural Functions ◽

Protein Molecules ◽

Macromolecular Protein ◽

And Function ◽

Nucleic Acid Structures ◽

User Friendly

MIPS (metal interactions in protein structures) is a database of metals in the three-dimensional macromolecular structures available in the Protein Data Bank. Bound metal ions in proteins have both catalytic and structural functions. The proposed database serves as an open resource for the analysis and visualization of all metals and their interactions with macromolecular (protein and nucleic acid) structures. MIPS can be searchedviaa user-friendly interface, and the interactions between metals and protein molecules, and the geometric parameters, can be viewed in both textual and graphical format using the freely available graphics plug-inJmol. MIPS is updated regularly, by means of programmed scripts to find metal-containing proteins from newly released protein structures. The database is useful for studying the properties of coordination between metals and protein molecules. It also helps to improve understanding of the relationship between macromolecular structure and function. This database is intended to serve the scientific community working in the areas of chemical and structural biology, and is freely available to all users, around the clock, at http://dicsoft2.physics.iisc.ernet.in/mips/.

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Learning structural motif representations for efficient protein structure search

10.1101/137828 ◽

2017 ◽

Cited By ~ 2

Author(s):

Yang Liu ◽

Qing Ye ◽

Liwei Wang ◽

Jian Peng

Keyword(s):

Protein Structure ◽

Fundamental Problem ◽

Sequence Similarity ◽

Structural Alignment ◽

Protein Structures ◽

Computational Cost ◽

Data Bank ◽

Hierarchical Organization ◽

Structural Motif ◽

And Function

AbstractMotivationUnderstanding the relationship between protein structure and function is a fundamental problem in protein science. Given a protein of unknown function, fast identification of similar protein structures from the Protein Data Bank (PDB) is a critical step for inferring its biological function. Such structural neighbors can provide evolutionary insights into protein conformation, interfaces and binding sites that are not detectable from sequence similarity. However, the computational cost of performing pairwise structural alignment against all structures in PDB is prohibitively expensive. Alignment-free approaches have been introduced to enable fast but coarse comparisons by representing each protein as a vector of structure features or fingerprints and only computing similarity between vectors. As a notable example, FragBag represents each protein by a “bag of fragments”, which is a vector of frequencies of contiguous short backbone fragments from a predetermined library.ResultsHere we present a new approach to learning effective structural motif presentations using deep learning. We develop DeepFold, a deep convolutional neural network model to extract structural motif features of a protein structure. Similar to FragBag, DeepFold represents each protein structure or fold using a vector of learned structural motif features. We demonstrate that DeepFold substantially outperforms FragBag on protein structural search on a non-redundant protein structure database and a set of newly released structures. Remarkably, DeepFold not only extracts meaningful backbone segments but also finds important long-range interacting motifs for structural comparison. We expect that DeepFold will provide new insights into the evolution and hierarchical organization of protein structural motifs.Availabilityhttps://github.com/largelymfs/[email protected]

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Probing the effects of nonannular lipid binding on the stability of the calcium pump SERCA

10.1101/470948 ◽

2018 ◽

Author(s):

L. Michel Espinoza-Fonseca

Keyword(s):

Structural Integrity ◽

Transmembrane Protein ◽

Md Simulations ◽

Lipid Binding ◽

Calcium Pump ◽

Lipid Molecule ◽

Allosteric Control ◽

Functional Dynamics ◽

The Stability ◽

And Function

AbstractThe calcium pump SERCA is a transmembrane protein that is critical for calcium transport in cells. SERCA resides in an environment made up largely by the lipid bilayer, so lipids play a central role on its stability and function. Studies have provided insights into the effects of annular and bulk lipids on SERCA activation, but the role of a nonannular lipid site in the E2 intermediate state remains elusive. Here, we have performed microsecond molecular dynamics (MD) simulations to probe the effects of nonannular lipid binding on the stability and structural dynamics of the E2 state of SERCA. We found that the structural integrity and stability of the E2 state is independent of nonannular lipid binding, and that occupancy of a lipid molecule at this site does not modulate destabilization of the E2 state, a step required to initiate the transition toward the competent E1 state. We also found that binding of the nonannular lipid does not induce direct allosteric control of the intrinsic functional dynamics the E2 state. We conclude that nonannular lipid binding is not necessary for the stability of the E2 state, but we speculate that it becomes functionally significant during the E2-to-E1 transition of the pump.

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Protein-ensemble–RNA docking by efficient consideration of protein flexibility through homology models

Bioinformatics ◽

10.1093/bioinformatics/btz388 ◽

2019 ◽

Vol 35 (23) ◽

pp. 4994-5002 ◽

Cited By ~ 5

Author(s):

Jiahua He ◽

Huanyu Tao ◽

Sheng-You Huang

Keyword(s):

Complex Structure ◽

Protein Structures ◽

Protein Flexibility ◽

Md Simulations ◽

Homology Model ◽

Data Bank ◽

Supplementary Information ◽

Scoring Functions ◽

Ensemble Docking ◽

The Impact

AbstractMotivationGiven the importance of protein–ribonucleic acid (RNA) interactions in many biological processes, a variety of docking algorithms have been developed to predict the complex structure from individual protein and RNA partners in the past decade. However, due to the impact of molecular flexibility, the performance of current methods has hit a bottleneck in realistic unbound docking. Pushing the limit, we have proposed a protein-ensemble–RNA docking strategy to explicitly consider the protein flexibility in protein–RNA docking through an ensemble of multiple protein structures, which is referred to as MPRDock. Instead of taking conformations from MD simulations or experimental structures, we obtained the multiple structures of a protein by building models from its homologous templates in the Protein Data Bank (PDB).ResultsOur approach can not only avoid the reliability issue of structures from MD simulations but also circumvent the limited number of experimental structures for a target protein in the PDB. Tested on 68 unbound–bound and 18 unbound–unbound protein–RNA complexes, our MPRDock/DITScorePR considerably improved the docking performance and achieved a significantly higher success rate than single-protein rigid docking whether pseudo-unbound templates are included or not. Similar improvements were also observed when combining our ensemble docking strategy with other scoring functions. The present homology model-based ensemble docking approach will have a general application in molecular docking for other interactions.Availability and implementationhttp://huanglab.phys.hust.edu.cn/mprdock/Supplementary informationSupplementary data are available at Bioinformatics online.

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Analysis of Fluctuation in the Heme-Binding Pocket and Heme Distortion in Hemoglobin and Myoglobin

10.20944/preprints202112.0475.v1 ◽

2021 ◽

Author(s):

Hiroko X. Kondo ◽

Yu Takano

Keyword(s):

Physical Properties ◽

Protein Structures ◽

Oxygen Affinity ◽

Md Simulations ◽

Data Bank ◽

Binding Pocket ◽

Protein Functions ◽

Heme Distortion ◽

The Relationship ◽

Protein Environment

Heme is located in the active site of proteins and has diverse and important biological functions, such as electron transfer and oxygen transport and/or storage. The distortion of heme porphyrin is considered an important factor for the diverse functions of heme because it correlates with the physical properties of heme, such as oxygen affinity and redox potential. Therefore, clarification of the relationship between heme distortion and the protein environment is crucial in protein science. Here, we analyzed the fluctuation in heme distortion in the protein environment for hemoglobin and myoglobin using molecular dynamics (MD) simulations and quantum mechanical (QM) calculations. We also investigated the protein structures of hemoglobin and myoglobin stored in Protein Data Bank and found that heme is distorted along the doming mode, which correlates with its oxygen affinity, more prominently in the protein environment than in the isolated state, and the magnitude of distortion is different between hemoglobin and myoglobin. This tendency was also observed in the results of MD simulations and QM calculations. These results suggest that heme distortion is affected by its protein environment and fluctuates around its fitted conformation, leading to physical properties that are appropriate for protein functions.

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Correlation of membrane protein conformational and functional dynamics

Nature Communications ◽

10.1038/s41467-021-24660-1 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Raghavendar Reddy Sanganna Gari ◽

Joel José Montalvo‐Acosta ◽

George R. Heath ◽

Yining Jiang ◽

Xiaolong Gao ◽

...

Keyword(s):

Membrane Protein ◽

Conformational Changes ◽

Single Channel ◽

Conformational Dynamics ◽

Md Simulations ◽

High Temporal Resolution ◽

Dependent Manner ◽

Functional Dynamics ◽

Ph Dependent ◽

Open States

AbstractConformational changes in ion channels lead to gating of an ion-conductive pore. Ion flux has been measured with high temporal resolution by single-channel electrophysiology for decades. However, correlation between functional and conformational dynamics remained difficult, lacking experimental techniques to monitor sub-millisecond conformational changes. Here, we use the outer membrane protein G (OmpG) as a model system where loop-6 opens and closes the β-barrel pore like a lid in a pH-dependent manner. Functionally, single-channel electrophysiology shows that while closed states are favored at acidic pH and open states are favored at physiological pH, both states coexist and rapidly interchange in all conditions. Using HS-AFM height spectroscopy (HS-AFM-HS), we monitor sub-millisecond loop-6 conformational dynamics, and compare them to the functional dynamics from single-channel recordings, while MD simulations provide atomistic details and energy landscapes of the pH-dependent loop-6 fluctuations. HS-AFM-HS offers new opportunities to analyze conformational dynamics at timescales of domain and loop fluctuations.

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Ligand-induced structural changes analysis of ribose-binding protein as studied by molecular dynamics simulations

Technology and Health Care ◽

10.3233/thc-218011 ◽

2021 ◽

pp. 1-12

Author(s):

Haiyan Li ◽

Zanxia Cao ◽

Guodong Hu ◽

Liling Zhao ◽

Chunling Wang ◽

...

Keyword(s):

Molecular Dynamics ◽

Structural Changes ◽

Binding Protein ◽

Network Models ◽

Md Simulations ◽

Protein Domain ◽

Opening Angle ◽

Conformation Changes ◽

Wide Range ◽

Ribose Binding Protein

BACKGROUND: The ribose-binding protein (RBP) from Escherichia coli is one of the representative structures of periplasmic binding proteins. Binding of ribose at the cleft between two domains causes a conformational change corresponding to a closure of two domains around the ligand. The RBP has been crystallized in the open and closed conformations. OBJECTIVE: With the complex trajectory as a control, our goal was to study the conformation changes induced by the detachment of the ligand, and the results have been revealed from two computational tools, MD simulations and elastic network models. METHODS: Molecular dynamics (MD) simulations were performed to study the conformation changes of RBP starting from the open-apo, closed-holo and closed-apo conformations. RESULTS: The evolution of the domain opening angle θ clearly indicates large structural changes. The simulations indicate that the closed states in the absence of ribose are inclined to transition to the open states and that ribose-free RBP exists in a wide range of conformations. The first three dominant principal motions derived from the closed-apo trajectories, consisting of rotating, bending and twisting motions, account for the major rearrangement of the domains from the closed to the open conformation. CONCLUSIONS: The motions showed a strong one-to-one correspondence with the slowest modes from our previous study of RBP with the anisotropic network model (ANM). The results obtained for RBP contribute to the generalization of robustness for protein domain motion studies using either the ANM or PCA for trajectories obtained from MD.

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Macromolecular Structure Databases: Past Progress and Future Challenges

Acta Crystallographica Section D Biological Crystallography ◽

10.1107/s0907444998009846 ◽

1998 ◽

Vol 54 (6) ◽

pp. 1085-1094 ◽

Cited By ~ 2

Author(s):

Helge Weissig ◽

Ilya N. Shindyalov ◽

Philip E. Bourne

Keyword(s):

Management Practices ◽

Temporal Trends ◽

Protein Structures ◽

Data Bank ◽

Macromolecular Structure ◽

Paper Briefly ◽

Future Challenges ◽

Structure Databases ◽

Full Discussion ◽

Self Consistency

Databases containing macromolecular structure data provide a crystallographer with important tools for use in solving, refining and understanding the functional significance of their protein structures. Given this importance, this paper briefly summarizes past progress by outlining the features of the significant number of relevant databases developed to date. One recent database, PDB+, containing all current and obsolete structures deposited with the Protein Data Bank (PDB) is discussed in more detail. PDB+ has been used to analyze the self-consistency of the current (1 January 1998) corpus of over 7000 structures. A summary of those findings is presented (a full discussion will appear elsewhere) in the form of global and temporal trends within the data. These trends indicate that challenges exist if crystallographers are to provide the community with complete and consistent structural results in the future. It is argued that better information management practices are required to meet these challenges.

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