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Kalmer TL, Ancajas CMF, Cohen CI, McDaniel JM, Oyedele AS, Thirman HL, Walker AS. Statistical Coupling Analysis Predicts Correlated Motions in Dihydrofolate Reductase. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.18.599103. [PMID: 38948820 PMCID: PMC11213021 DOI: 10.1101/2024.06.18.599103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
The role of dynamics in enzymatic function is a highly debated topic. Dihydrofolate reductase (DHFR), due to its universality and the depth with which it has been studied, is a model system in this debate. Myriad previous works have identified networks of residues in positions near to and remote from the active site that are involved in dynamics and others that are important for catalysis. For example, specific mutations on the Met20 loop in E. coli DHFR (N23PP/S148A) are known to disrupt millisecond-timescale motions and reduce catalytic activity. However, how and if networks of dynamically coupled residues influence the evolution of DHFR is still an unanswered question. In this study, we first identify, by statistical coupling analysis and molecular dynamic simulations, a network of coevolving residues, which possess increased correlated motions. We then go on to show that allosteric communication in this network is selectively knocked down in N23PP/S148A mutant E. coli DHFR. Finally, we identify two sites in the human DHFR sector which may accommodate the Met20 loop double proline mutation while preserving dynamics. These findings strongly implicate protein dynamics as a driving force for evolution.
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Han ISM, Thayer KM. Reconnaissance of Allostery via the Restoration of Native p53 DNA-Binding Domain Dynamics in Y220C Mutant p53 Tumor Suppressor Protein. ACS OMEGA 2024; 9:19837-19847. [PMID: 38737036 PMCID: PMC11079909 DOI: 10.1021/acsomega.3c08509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 03/30/2024] [Accepted: 04/03/2024] [Indexed: 05/14/2024]
Abstract
Allosteric regulation of protein dynamics infers a long-range deliberate propagation of information via micro- and macroscale interactions. The Y220C structural mutant is one of the most frequent cancerous p53 mutants. The mutation is distally located from the DNA-binding site of the p53 DNA-binding domain yet causes changes in DNA recognition. This system presents a unique opportunity to examine the allosteric control of mutated proteins under a drug design paradigm. We focus on the key case study of p53 Y220C mutation restoration by a series of new compounds suggested to have Y220C reactivation properties in comparison to our previous findings on the restorative potential of PK11000, a compound studied extensively for reactivation in vitro and in vivo. Previously, we implemented all-atom molecular dynamics (MD) simulations and our lab's techniques of MD-Sectors and MD-Markov state models on the wild type, the Y220C mutant, and Y220C with PK11000 to characterize the effector's restorative properties in terms of conformational dynamics and hydrogen bonding. In this study, we turn to probing the effects made by docking the battery of a new but less well-tested set of aminobenzothiazole derivative compounds reported by Baud et al., which show promise of Y220C rescue. We find that while complete and precise reconstitution of p53 WT molecular dynamics may not be observed as was the case with PK11000, dispersed local reconstitution of loop dynamics provides evidence of rescuing effects by aminobenzothiazole derivative N,2-dihydroxy-3,5-diiodo-4-(1H-pyrrol-1-yl)benzamide, Effector 22, like what we observed for PK11000. Generalizable insights into the mutation and allosteric reactivation of p53 by various effectors by reconstitution of WT dynamics observed in statistical conformational ensemble analysis and network inference are discussed, considering the development of allosteric drug design rooted in first principles.
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Affiliation(s)
- In Sub M. Han
- College of Integrated Sciences, Wesleyan University, Hall-Atwater Laboratories, Middletown, Connecticut 06459-0180, United States
| | - Kelly M. Thayer
- College of Integrated Sciences, Wesleyan University, Hall-Atwater Laboratories, Middletown, Connecticut 06459-0180, United States
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3
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Cowan B, Beveridge DL, Thayer KM. Allosteric Signaling in PDZ Energetic Networks: Embedding Error Analysis. J Phys Chem B 2023; 127:623-633. [PMID: 36626697 PMCID: PMC9884075 DOI: 10.1021/acs.jpcb.2c06546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 12/23/2022] [Indexed: 01/12/2023]
Abstract
Allosteric signaling in proteins has been known for some half a century, yet how the signal traverses the protein remains an active area of research. Recently, the importance of electrostatics to achieve long-range signaling has become increasingly appreciated. Our laboratory has been working on developing network approaches to capture such interactions. In this study, we turn our attention to the well-studied allosteric model protein, PDZ. We study the allosteric dynamics on a per-residue basis in key constructs involving the PDZ domain, its allosteric effector, and its peptide ligand. We utilize molecular dynamics trajectories to create the networks for the constructs to explore the allosteric effect by plotting the heat kernel results onto axes defined by principal components. We introduce a new metric to quantitate the volume sampled by a residue in the latent space. We relate our findings to PDZ and the greater field of allostery.
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Affiliation(s)
- Benjamin
S. Cowan
- Department
of Computer Science, Wesleyan University, Middletown, Connecticut06457, United States
- College
of Integrative Sciences, Wesleyan University, Middletown, Connecticut06457, United States
| | - David L. Beveridge
- Molecular
Biophysics Program, Wesleyan University, Middletown, Connecticut06457, United States
- Department
of Chemistry, Wesleyan University, Middletown, Connecticut06457, United States
| | - Kelly M. Thayer
- Department
of Computer Science, Wesleyan University, Middletown, Connecticut06457, United States
- Molecular
Biophysics Program, Wesleyan University, Middletown, Connecticut06457, United States
- Department
of Chemistry, Wesleyan University, Middletown, Connecticut06457, United States
- College
of Integrative Sciences, Wesleyan University, Middletown, Connecticut06457, United States
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4
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Fabry J, Thayer KM. Network Analysis of Molecular Dynamics Sectors in the p53 Protein. ACS OMEGA 2023; 8:571-587. [PMID: 36643471 PMCID: PMC9835189 DOI: 10.1021/acsomega.2c05635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 12/05/2022] [Indexed: 06/17/2023]
Abstract
Design of allosteric regulators is an emergent field in the area of drug discovery holding promise for currently untreated diseases. Allosteric regulators bind to a protein in one location and affect a distant site. The ubiquitous presence of allosteric effectors in biology and the success of serendipitously identified allosteric compounds point to the potential they hold. Although the mechanism of transmission of an allosteric signal is not unequivocally determined, one hypothesis suggests that groups of evolutionarily covarying residues within a protein, termed sectors, are conduits. A long-term goal of our lab is to allosterically modulate the activity of proteins by binding small molecules at points of allosteric control. However, methods to consistently identify such points remain unclear. Sector residues on the surfaces of proteins are a promising source of allosteric targets. Recently, we introduced molecular dynamics (MD)-based sectors; MD sectors capitalize on covariance of motion, in place of evolutionary covariance. By focusing on motional covariance, MD sectors tap into the framework of statistical mechanics afforded by the Boltzmann ensemble of structural conformations comprising the underlying data set. We hypothesized that the method of MD sectors can be used to identify a cohesive network of motionally covarying residues capable of transmitting an allosteric signal in a protein. While our initial qualitative results showed promise for the method to predict sectors, that a network of cohesively covarying residues had been produced remained an untested assumption. In this work, we apply network theory to rigorously analyze MD sectors, allowing us to quantitatively assess the biologically relevant property of network cohesiveness of sectors in the context of the tumor suppressor protein, p53. We revised the methodology for assessing and improving MD sectors. Specifically, we introduce a metric to calculate the cohesive properties of the network. Our new approach separates residues into two categories: sector residues and non-sector residues. The relatedness within each respective group is computed with a distance metric. Cohesive sector networks are identified as those that have high relatedness among the sector residues which exceeds the relatedness of the residues to the non-sector residues in terms of the correlation of motions. Our major finding was that the revised means of obtaining sectors was more efficacious than previous iterations, as evidenced by the greater cohesion of the networks. These results are discussed in the context of the development of allosteric regulators of p53 in particular and the expected applicability of the method to the drug design field in general.
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Affiliation(s)
- Jonathan
D. Fabry
- Department
of Mathematics and Computer Science, Wesleyan
University, Middletown, Connecticut06457United States
- Department
of Chemistry, Wesleyan University, Middletown, Connecticut06457, United States
| | - Kelly M. Thayer
- Department
of Mathematics and Computer Science, Wesleyan
University, Middletown, Connecticut06457United States
- Department
of Chemistry, Wesleyan University, Middletown, Connecticut06457, United States
- College
of Integrative Sciences, Wesleyan University, Middletown, Connecticut06457, United States
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5
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Armour-Garb I, Han ISM, Cowan BS, Thayer KM. Variable Regions of p53 Isoforms Allosterically Hard Code DNA Interaction. J Phys Chem B 2022; 126:8495-8507. [PMID: 36245142 PMCID: PMC9623584 DOI: 10.1021/acs.jpcb.2c06229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Allosteric regulation of protein activity pervades biology as the "second secret of life." We have been examining the allosteric regulation and mutant reactivation of the tumor suppressor protein p53. We have found that generalizing the definition of allosteric effector to include entire proteins and expanding the meaning of binding site to include the interface of a transcription factor with its DNA to be useful in understanding the modulation of protein activity. Here, we cast the variable regions of p53 isoforms as allosteric regulators of p53 interactions with its consensus DNA. We implemented molecular dynamics simulations and our lab's new techniques of molecular dynamics (MD) sectors and MD-Markov state models to investigate the effects of nine naturally occurring splice variant isoforms of p53. We find that all of the isoforms differ from wild type in their dynamic properties and how they interact with the DNA. We consider the implications of these findings on allostery and cancer treatment.
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Affiliation(s)
- Isabel Armour-Garb
- †Department
of Mathematics and Computer Science, ‡Department of Chemistry, and §College of Integrative
Sciences, Wesleyan University, Middletown, Connecticut 06457, United States
| | - In Sub Mark Han
- †Department
of Mathematics and Computer Science, ‡Department of Chemistry, and §College of Integrative
Sciences, Wesleyan University, Middletown, Connecticut 06457, United States
| | - Benjamin S. Cowan
- †Department
of Mathematics and Computer Science, ‡Department of Chemistry, and §College of Integrative
Sciences, Wesleyan University, Middletown, Connecticut 06457, United States
| | - Kelly M. Thayer
- †Department
of Mathematics and Computer Science, ‡Department of Chemistry, and §College of Integrative
Sciences, Wesleyan University, Middletown, Connecticut 06457, United States,
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6
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Domino effect in allosteric signaling of peptide binding. J Mol Biol 2022; 434:167661. [DOI: 10.1016/j.jmb.2022.167661] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 05/24/2022] [Accepted: 05/24/2022] [Indexed: 11/22/2022]
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Han ISM, Abramson D, Thayer KM. Insights into Rational Design of a New Class of Allosteric Effectors with Molecular Dynamics Markov State Models and Network Theory. ACS OMEGA 2022; 7:2831-2841. [PMID: 35097279 PMCID: PMC8792916 DOI: 10.1021/acsomega.1c05624] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 12/16/2021] [Indexed: 05/12/2023]
Abstract
The development of drugs to restore protein function has been a major advance facilitated by molecular medicine. Allosteric regulation, a phenomenon widely observed in nature, in which a molecule binds to control a distance active site, holds great promise for regulating proteins, yet how to rationally design such a molecule remains a mystery. Over the past few years, we and others have developed several techniques based on molecular dynamics (MD) simulations: MD-Markov state models to capture global conformational substates, and network theory approach utilizing the interaction energy within the protein to confer local allosteric control. We focus on the key case study of the p53 Y220C mutation restoration by PK11000, a compound experimentally shown to reactivate p53 native function in Y220C mutant present tumors. We gain insights into the mutation and allosteric reactivation of the protein, which we anticipate will be applicable to de novo design to engineer new compounds not only for this mutation, but in other macromolecular systems as well.
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González-Paz L, Hurtado-León ML, Lossada C, Fernández-Materán FV, Vera-Villalobos J, Loroño M, Paz JL, Jeffreys L, Alvarado YJ. Structural deformability induced in proteins of potential interest associated with COVID-19 by binding of homologues present in ivermectin: Comparative study based in elastic networks models. J Mol Liq 2021; 340:117284. [PMID: 34421159 PMCID: PMC8367659 DOI: 10.1016/j.molliq.2021.117284] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 08/10/2021] [Accepted: 08/12/2021] [Indexed: 12/24/2022]
Abstract
The COVID-19 pandemic has accelerated the study of the potential of multi-target drugs (MTDs). The mixture of homologues called ivermectin (avermectin-B1a + avermectin-B1b) has been shown to be a MTD with potential antiviral activity against SARS-CoV-2 in vitro. However, there are few reports on the effect of each homologue on the flexibility and stiffness of proteins associated with COVID-19, described as ivermectin targets. We observed that each homologue was stably bound to the proteins studied and was able to induce detectable changes with Elastic Network Models (ENM). The perturbations induced by each homologue were characteristic of each compound and, in turn, were represented by a disruption of native intramolecular networks (interactions between residues). The homologues were able to slightly modify the conformation and stability of the connection points between the Cα atoms of the residues that make up the structural network of proteins (nodes), compared to free proteins. Each homologue was able to modified differently the distribution of quasi-rigid regions of the proteins, which could theoretically alter their biological activities. These results could provide a biophysical-computational view of the potential MTD mechanism that has been reported for ivermectin.
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Affiliation(s)
- Lenin González-Paz
- Universidad del Zulia (LUZ), Facultad Experimental de Ciencias (FEC), Departamento de Biología. Laboratorio de Genética y Biología Molecular (LGBM), 4001 Maracaibo, Republica Bolivariana de Venezuela.,Instituto Venezolano de Investigaciones Científicas (IVIC), Centro de Estudios Botánicos y Agroforestales (CEBA), Laboratorio de Protección Vegetal (LPV), 4001 Maracaibo, Republica Bolivariana de Venezuela
| | - María Laura Hurtado-León
- Universidad del Zulia (LUZ), Facultad Experimental de Ciencias (FEC), Departamento de Biología. Laboratorio de Genética y Biología Molecular (LGBM), 4001 Maracaibo, Republica Bolivariana de Venezuela
| | - Carla Lossada
- Instituto Venezolano de Investigaciones Científicas (IVIC), Centro de Investigación y Tecnología de Materiales (CITeMA), Laboratorio de Caracterización Molecular y Biomolecular, 4001 Maracaibo, Republica Bolivariana de Venezuela
| | - Francelys V Fernández-Materán
- Instituto Venezolano de Investigaciones Científicas (IVIC), Centro de Investigación y Tecnología de Materiales (CITeMA), Laboratorio de Caracterización Molecular y Biomolecular, 4001 Maracaibo, Republica Bolivariana de Venezuela
| | - Joan Vera-Villalobos
- Facultad de Ciencias Naturales y Matemáticas, Departamento de Química y Ciencias Ambientales, Laboratorio de Análisis Químico Instrumental (LAQUINS), Escuela Superior Politécnica del Litoral, Guayaquil, Ecuador
| | - Marcos Loroño
- Departamento Académico de Química Analítica e Instrumental, Facultad de Química e Ingeniería Química, Universidad Nacional Mayor de San Marcos, Lima, Perú
| | - J L Paz
- Departamento Académico de Química Inorgánica, Facultad de Química e Ingeniería Química, Universidad Nacional Mayor de San Marcos, Lima, Perú
| | - Laura Jeffreys
- Liverpool School of Tropical Medicine, Pembroke Place, Liverpool L3 5QA, UK
| | - Ysaias J Alvarado
- Instituto Venezolano de Investigaciones Científicas (IVIC), Centro de Investigación y Tecnología de Materiales (CITeMA), Laboratorio de Caracterización Molecular y Biomolecular, 4001 Maracaibo, Republica Bolivariana de Venezuela
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9
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Evolution of dynamical networks enhances catalysis in a designer enzyme. Nat Chem 2021; 13:1017-1022. [PMID: 34413499 DOI: 10.1038/s41557-021-00763-6] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 06/30/2021] [Indexed: 02/08/2023]
Abstract
Activation heat capacity is emerging as a crucial factor in enzyme thermoadaptation, as shown by the non-Arrhenius behaviour of many natural enzymes. However, its physical origin and relationship to the evolution of catalytic activity remain uncertain. Here we show that directed evolution of a computationally designed Kemp eliminase reshapes protein dynamics, which gives rise to an activation heat capacity absent in the original design. These changes buttress transition-state stabilization. Extensive molecular dynamics simulations show that evolution results in the closure of solvent-exposed loops and a better packing of the active site. Remarkably, this gives rise to a correlated dynamical network that involves the transition state and large parts of the protein. This network tightens the transition-state ensemble, which induces a negative activation heat capacity and non-linearity in the activity-temperature dependence. Our results have implications for understanding enzyme evolution and suggest that selectively targeting the conformational dynamics of the transition-state ensemble by design and evolution will expedite the creation of novel enzymes.
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Singh S, Thulasiram HV, Sengupta D, Kulkarni K. Dynamic coupling analysis on plant sesquiterpene synthases provides leads for the identification of product specificity determinants. Biochem Biophys Res Commun 2020; 536:107-114. [PMID: 33387748 DOI: 10.1016/j.bbrc.2020.12.041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 12/13/2020] [Indexed: 10/22/2022]
Abstract
Sesquiterpene synthases catalyse cyclisation of farnesyl pyrophosphate to produce diverse sesquiterpenes. Despite utilising the same substrate and exhibiting significant sequence and structural homology, these enzymes form different products. Previous efforts were based on identifying the effect of divergent residues present at the catalytic binding pocket on the product specificity of these enzymes. However, the rationales deduced for the product specificity from these studies were not generic enough to be applicable to other phylogenetically distant members of this family. To address this problem, we have developed a novel approach combining sequence, structural and dynamical information of plant sesquiterpene synthases (SSQs) to predict product modulating residues (PMRs). We tested this approach on the SSQs with known PMRs and also on sesquisabinene synthase 1 (SaSQS1), a SSQ from Indian sandalwood. Our results show that the dynamical sectors of SSQs obtained from molecular dynamics simulation and their hydrophobicity and vicinity indices together provide leads for the identification of PMRs. The efficacy of the technique was tested on SaSQS1 using mutagenesis. To the best of our knowledge, this is a first technique of this kind which provides cues on PMRs of SSQs, with divergent phylogenetic relationship.
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Affiliation(s)
- Sneha Singh
- Division of Biochemical Sciences, CSIR - National Chemical Laboratory, Pune, 411008, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Hirekodathakallu V Thulasiram
- Division of Organic Chemistry, CSIR - National Chemical Laboratory, Pune, 411008, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.
| | - Durba Sengupta
- Division of Physical and Materials Chemistry, CSIR - National Chemical Laboratory, Pune, 411008, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Kiran Kulkarni
- Division of Biochemical Sciences, CSIR - National Chemical Laboratory, Pune, 411008, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.
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