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Yan Z, Wang J. Evolution shapes interaction patterns for epistasis and specific protein binding in a two-component signaling system. Commun Chem 2024; 7:13. [PMID: 38233668 PMCID: PMC10794238 DOI: 10.1038/s42004-024-01098-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 01/05/2024] [Indexed: 01/19/2024] Open
Abstract
The elegant design of protein sequence/structure/function relationships arises from the interaction patterns between amino acid positions. A central question is how evolutionary forces shape the interaction patterns that encode long-range epistasis and binding specificity. Here, we combined family-wide evolutionary analysis of natural homologous sequences and structure-oriented evolution simulation for two-component signaling (TCS) system. The magnitude-frequency relationship of coupling conservation between positions manifests a power-law-like distribution and the positions with highly coupling conservation are sparse but distributed intensely on the binding surfaces and hydrophobic core. The structure-specific interaction pattern involves further optimization of local frustrations at or near the binding surface to adapt the binding partner. The construction of family-wide conserved interaction patterns and structure-specific ones demonstrates that binding specificity is modulated by both direct intermolecular interactions and long-range epistasis across the binding complex. Evolution sculpts the interaction patterns via sequence variations at both family-wide and structure-specific levels for TCS system.
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Affiliation(s)
- Zhiqiang Yan
- Center for Theoretical Interdisciplinary Sciences, Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang, 325001, PR China
| | - Jin Wang
- Department of Chemistry and Physics, State University of New York at Stony Brook, Stony Brook, NY, 11790, USA.
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2
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González-Paz L, Lossada C, Hurtado-León ML, Fernández-Materán FV, Paz JL, Parvizi S, Cardenas Castillo RE, Romero F, Alvarado YJ. Intrinsic Dynamics of the ClpXP Proteolytic Machine Using Elastic Network Models. ACS OMEGA 2023; 8:7302-7318. [PMID: 36873006 PMCID: PMC9979342 DOI: 10.1021/acsomega.2c04347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 10/25/2022] [Indexed: 06/18/2023]
Abstract
ClpXP complex is an ATP-dependent mitochondrial matrix protease that binds, unfolds, translocates, and subsequently degrades specific protein substrates. Its mechanisms of operation are still being debated, and several have been proposed, including the sequential translocation of two residues (SC/2R), six residues (SC/6R), and even long-pass probabilistic models. Therefore, it has been suggested to employ biophysical-computational approaches that can determine the kinetics and thermodynamics of the translocation. In this sense, and based on the apparent inconsistency between structural and functional studies, we propose to apply biophysical approaches based on elastic network models (ENM) to study the intrinsic dynamics of the theoretically most probable hydrolysis mechanism. The proposed models ENM suggest that the ClpP region is decisive for the stabilization of the ClpXP complex, contributing to the flexibility of the residues adjacent to the pore, favoring the increase in pore size and, therefore, with the energy of interaction of its residues with a larger portion of the substrate. It is predicted that the complex may undergo a stable configurational change once assembled and that the deformability of the system once assembled is oriented, to increase the rigidity of the domains of each region (ClpP and ClpX) and to gain flexibility of the pore. Our predictions could suggest under the conditions of this study the mechanism of the interaction of the system, of which the substrate passes through the unfolding of the pore in parallel with a folding of the bottleneck. The variations in the distance calculated by molecular dynamics could allow the passage of a substrate with a size equivalent to ∼3 residues. The theoretical behavior of the pore and the stability and energy of binding to the substrate based on ENM models suggest that in this system, there are thermodynamic, structural, and configurational conditions that allow a possible translocation mechanism that is not strictly sequential.
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Affiliation(s)
- Lenin González-Paz
- Facultad
Experimental de Ciencias (FEC), Departamento de Biología, Laboratorio
de Genética y Biología Molecular (LGBM), Universidad del Zulia (LUZ), 4001 Maracaibo, Zulia, República Bolivariana
de Venezuela
- Centro
de Biomedicina Molecular (CBM). Laboratorio de Biocomputación
(LB), Instituto Venezolano de Investigaciones
Científicas (IVIC), 4001 Maracaibo, Zulia, República Bolivariana de Venezuela
| | - Carla Lossada
- Centro
de Biomedicina Molecular (CBM). Laboratorio de Biocomputación
(LB), Instituto Venezolano de Investigaciones
Científicas (IVIC), 4001 Maracaibo, Zulia, República Bolivariana de Venezuela
| | - Maria Laura Hurtado-León
- Facultad
Experimental de Ciencias (FEC), Departamento de Biología, Laboratorio
de Genética y Biología Molecular (LGBM), Universidad del Zulia (LUZ), 4001 Maracaibo, Zulia, República Bolivariana
de Venezuela
| | - Francelys V. Fernández-Materán
- Centro
de Biomedicina Molecular (CBM). Laboratorio de Biocomputación
(LB), Instituto Venezolano de Investigaciones
Científicas (IVIC), 4001 Maracaibo, Zulia, República Bolivariana de Venezuela
| | - José Luis Paz
- Departamento
Académico de Química Inorgánica, Facultad de
Química e Ingeniería Química, Universidad Nacional Mayor de San Marcos, 15081 Lima, Perú
| | - Shayan Parvizi
- Pulmonary,
Critical Care and Sleep Medicine, Baylor
College of Medicine, Houston, Texas 77030, United States
| | | | - Freddy Romero
- Pulmonary,
Critical Care and Sleep Medicine, Baylor
College of Medicine, Houston, Texas 77030, United States
| | - Ysaias J. Alvarado
- Centro
de Biomedicina Molecular (CBM), Laboratorio de Química Biofísica
Teórica y Experimental (LQBTE), Instituto
Venezolano de Investigaciones Cientificas (IVIC), 4001 Maracaibo, Zulia, República Bolivariana de Venezuela
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3
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Bryan JS, Pressé S. Learning continuous potentials from smFRET. Biophys J 2023; 122:433-441. [PMID: 36463404 PMCID: PMC9892619 DOI: 10.1016/j.bpj.2022.11.2947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 11/08/2022] [Accepted: 11/29/2022] [Indexed: 12/07/2022] Open
Abstract
Potential energy landscapes are useful models in describing events such as protein folding and binding. While single-molecule fluorescence resonance energy transfer (smFRET) experiments encode information on continuous potentials for the system probed, including rarely visited barriers between putative potential minima, this information is rarely decoded from the data. This is because existing analysis methods often model smFRET output assuming, from the onset, that the system probed evolves in a discretized state space to be analyzed within a hidden Markov model (HMM) paradigm. By contrast, here, we infer continuous potentials from smFRET data without discretely approximating the state space. We do so by operating within a Bayesian nonparametric paradigm by placing priors on the family of all possible potential curves. As our inference accounts for a number of required experimental features raising computational cost (such as incorporating discrete photon shot noise), the framework leverages a structured-kernel-interpolation Gaussian process prior to help curtail computational cost. We show that our structured-kernel-interpolation priors for potential energy reconstruction from smFRET analysis accurately infers the potential energy landscape from a smFRET binding experiment. We then illustrate advantages of structured-kernel-interpolation priors for potential energy reconstruction from smFRET over standard HMM approaches by providing information, such as barrier heights and friction coefficients, that is otherwise inaccessible to HMMs.
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Affiliation(s)
- J Shepard Bryan
- Center for Biological Physics, Arizona State University, Tempe, Arizona; Department of Physics, Arizona State University, Tempe, Arizona
| | - Steve Pressé
- Center for Biological Physics, Arizona State University, Tempe, Arizona; Department of Physics, Arizona State University, Tempe, Arizona; School of Molecular Sciences, Arizona State University, Tempe, Arizona.
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4
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Sánchez IE, Galpern EA, Garibaldi MM, Ferreiro DU. Molecular Information Theory Meets Protein Folding. J Phys Chem B 2022; 126:8655-8668. [PMID: 36282961 DOI: 10.1021/acs.jpcb.2c04532] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
We propose an application of molecular information theory to analyze the folding of single domain proteins. We analyze results from various areas of protein science, such as sequence-based potentials, reduced amino acid alphabets, backbone configurational entropy, secondary structure content, residue burial layers, and mutational studies of protein stability changes. We found that the average information contained in the sequences of evolved proteins is very close to the average information needed to specify a fold ∼2.2 ± 0.3 bits/(site·operation). The effective alphabet size in evolved proteins equals the effective number of conformations of a residue in the compact unfolded state at around 5. We calculated an energy-to-information conversion efficiency upon folding of around 50%, lower than the theoretical limit of 70%, but much higher than human-built macroscopic machines. We propose a simple mapping between molecular information theory and energy landscape theory and explore the connections between sequence evolution, configurational entropy, and the energetics of protein folding.
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Affiliation(s)
- Ignacio E Sánchez
- Facultad de Ciencias Exactas y Naturales, Laboratorio de Fisiología de Proteínas, Consejo Nacional de Investigaciones Científicas y Técnicas, Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Universidad de Buenos Aires, Buenos AiresCP1428, Argentina
| | - Ezequiel A Galpern
- Facultad de Ciencias Exactas y Naturales, Laboratorio de Fisiología de Proteínas, Consejo Nacional de Investigaciones Científicas y Técnicas, Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Universidad de Buenos Aires, Buenos AiresCP1428, Argentina
| | - Martín M Garibaldi
- Facultad de Ciencias Exactas y Naturales, Laboratorio de Fisiología de Proteínas, Consejo Nacional de Investigaciones Científicas y Técnicas, Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Universidad de Buenos Aires, Buenos AiresCP1428, Argentina
| | - Diego U Ferreiro
- Facultad de Ciencias Exactas y Naturales, Laboratorio de Fisiología de Proteínas, Consejo Nacional de Investigaciones Científicas y Técnicas, Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Universidad de Buenos Aires, Buenos AiresCP1428, Argentina
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5
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Abstract
Proteins have dynamic structures that undergo chain motions on time scales spanning from picoseconds to seconds. Resolving the resultant conformational heterogeneity is essential for gaining accurate insight into fundamental mechanistic aspects of the protein folding reaction. The use of high-resolution structural probes, sensitive to population distributions, has begun to enable the resolution of site-specific conformational heterogeneity at different stages of the folding reaction. Different states populated during protein folding, including the unfolded state, collapsed intermediate states, and even the native state, are found to possess significant conformational heterogeneity. Heterogeneity in protein folding and unfolding reactions originates from the reduced cooperativity of various kinds of physicochemical interactions between various structural elements of a protein, and between a protein and solvent. Heterogeneity may arise because of functional or evolutionary constraints. Conformational substates within the unfolded state and the collapsed intermediates that exchange at rates slower than the subsequent folding steps give rise to heterogeneity on the protein folding pathways. Multiple folding pathways are likely to represent distinct sequences of structure formation. Insight into the nature of the energy barriers separating different conformational states populated during (un)folding can also be obtained by resolving heterogeneity.
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Affiliation(s)
- Sandhya Bhatia
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bengaluru 560065, India.,Indian Institute of Science Education and Research, Pune 411008, India
| | - Jayant B Udgaonkar
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bengaluru 560065, India.,Indian Institute of Science Education and Research, Pune 411008, India
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Perspectives on the landscape and flux theory for describing emergent behaviors of the biological systems. J Biol Phys 2022; 48:1-36. [PMID: 34822073 PMCID: PMC8866630 DOI: 10.1007/s10867-021-09586-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 09/07/2021] [Indexed: 10/19/2022] Open
Abstract
We give a review on the landscape theory of the equilibrium biological systems and landscape-flux theory of the nonequilibrium biological systems as the global driving force. The emergences of the behaviors, the associated thermodynamics in terms of the entropy and free energy and dynamics in terms of the rate and paths have been quantitatively demonstrated. The hierarchical organization structures have been discussed. The biological applications ranging from protein folding, biomolecular recognition, specificity, biomolecular evolution and design for equilibrium systems as well as cell cycle, differentiation and development, cancer, neural networks and brain function, and evolution for nonequilibrium systems, cross-scale studies of genome structural dynamics and experimental quantifications/verifications of the landscape and flux are illustrated. Together, this gives an overall global physical and quantitative picture in terms of the landscape and flux for the behaviors, dynamics and functions of biological systems.
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Chu WT, Yan Z, Chu X, Zheng X, Liu Z, Xu L, Zhang K, Wang J. Physics of biomolecular recognition and conformational dynamics. REPORTS ON PROGRESS IN PHYSICS. PHYSICAL SOCIETY (GREAT BRITAIN) 2021; 84:126601. [PMID: 34753115 DOI: 10.1088/1361-6633/ac3800] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 11/09/2021] [Indexed: 06/13/2023]
Abstract
Biomolecular recognition usually leads to the formation of binding complexes, often accompanied by large-scale conformational changes. This process is fundamental to biological functions at the molecular and cellular levels. Uncovering the physical mechanisms of biomolecular recognition and quantifying the key biomolecular interactions are vital to understand these functions. The recently developed energy landscape theory has been successful in quantifying recognition processes and revealing the underlying mechanisms. Recent studies have shown that in addition to affinity, specificity is also crucial for biomolecular recognition. The proposed physical concept of intrinsic specificity based on the underlying energy landscape theory provides a practical way to quantify the specificity. Optimization of affinity and specificity can be adopted as a principle to guide the evolution and design of molecular recognition. This approach can also be used in practice for drug discovery using multidimensional screening to identify lead compounds. The energy landscape topography of molecular recognition is important for revealing the underlying flexible binding or binding-folding mechanisms. In this review, we first introduce the energy landscape theory for molecular recognition and then address four critical issues related to biomolecular recognition and conformational dynamics: (1) specificity quantification of molecular recognition; (2) evolution and design in molecular recognition; (3) flexible molecular recognition; (4) chromosome structural dynamics. The results described here and the discussions of the insights gained from the energy landscape topography can provide valuable guidance for further computational and experimental investigations of biomolecular recognition and conformational dynamics.
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Affiliation(s)
- Wen-Ting Chu
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, People's Republic of China
| | - Zhiqiang Yan
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, People's Republic of China
| | - Xiakun Chu
- Department of Chemistry & Physics, State University of New York at Stony Brook, Stony Brook, NY 11794, United States of America
| | - Xiliang Zheng
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, People's Republic of China
| | - Zuojia Liu
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, People's Republic of China
| | - Li Xu
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, People's Republic of China
| | - Kun Zhang
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, People's Republic of China
| | - Jin Wang
- Department of Chemistry & Physics, State University of New York at Stony Brook, Stony Brook, NY 11794, United States of America
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Trubiano A, Holmes-Cerfon M. Thermodynamic stability versus kinetic accessibility: Pareto fronts for programmable self-assembly. SOFT MATTER 2021; 17:6797-6807. [PMID: 34223604 DOI: 10.1039/d1sm00681a] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
A challenge in designing self-assembling building blocks is to ensure the target state is both thermodynamically stable and kinetically accessible. These two objectives are known to be typically in competition, but it is not known how to simultaneously optimize them. We consider this problem through the lens of multi-objective optimization theory: we develop a genetic algorithm to compute the Pareto fronts characterizing the tradeoff between equilibrium probability and folding rate, for a model system of small polymers of colloids with tunable short-ranged interaction energies. We use a coarse-grained model for the particles' dynamics that allows us to efficiently search over parameters, for systems small enough to be enumerated. For most target states there is a tradeoff when the number of types of particles is small, with medium-weak bonds favouring fast folding, and strong bonds favouring high equilibrium probability. The tradeoff disappears when the number of particle types reaches a value m*, that is usually much less than the total number of particles. This general approach of computing Pareto fronts allows one to identify the minimum number of design parameters to avoid a thermodynamic-kinetic tradeoff. However, we argue, by contrasting our coarse-grained model's predictions with those of Brownian dynamics simulations, that particles with short-ranged isotropic interactions should generically have a tradeoff, and avoiding it in larger systems will require orientation-dependent interactions.
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Affiliation(s)
- Anthony Trubiano
- Courant Institute of Mathematical Sciences, New York University, New York, New York 10012, USA.
| | - Miranda Holmes-Cerfon
- Courant Institute of Mathematical Sciences, New York University, New York, New York 10012, USA.
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