1
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Campitelli P, Ross D, Swint-Kruse L, Ozkan SB. Dynamics-based protein network features accurately discriminate neutral and rheostat positions. Biophys J 2024:S0006-3495(24)00625-8. [PMID: 39277794 DOI: 10.1016/j.bpj.2024.09.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 07/03/2024] [Accepted: 09/11/2024] [Indexed: 09/17/2024] Open
Abstract
In some proteins, a unique class of nonconserved positions is characterized by their ability to generate diverse functional outcomes through single amino acid substitutions. Due to their ability to tune protein function, accurately identifying such "rheostat" positions is crucial for protein design, for understanding the impact of mutations observed in humans, and for predicting the evolution of pathogen drug resistance. However, identifying rheostat positions has been challenging, due-in part-to the absence of a clear structural relationship with binding sites. In this study, experimental data from our previous study of the Escherichia coli lactose repressor protein (LacI) was used to identify rheostat positions for which mutations tune in vivo EC50 for the allosteric ligand "IPTG." We next used the rheostat assignments to test the hypothesis that rheostat positions have unique dynamic features that will enable their identification. To that end, we integrated all-atom molecular dynamics simulations with perturbation residue response analysis. Results first revealed distinct dynamic behavior in IPTG-bound LacI compared with apo LacI, which was consistent with IPTG's role as an allosteric inducer. Next, we used a variety of dynamic features to build a classification model that discriminates experimentally characterized rheostat positions in LacI from positions with other types of substitution outcomes. In parallel, we built a second classifier model based on the 3D structural "static" network features of LacI. In comparative studies, the dynamic model better identified rheostat positions that were >8 Å from the binding site. In summary, our study provides insights into the dynamic characteristics of rheostat positions and suggests that models built on dynamic features may be useful for predicting the locations of rheostat positions in a wide range of proteins.
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Affiliation(s)
- P Campitelli
- Department of Physics, Center for Biological Physics, Arizona State University, Tempe, Arizona
| | - D Ross
- Biosystems and Biomaterials Division, Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland
| | - L Swint-Kruse
- Department of Biochemistry and Molecular Biology, The University of Kansas Medical Center, Kansas City, Kansas.
| | - S B Ozkan
- Department of Physics, Center for Biological Physics, Arizona State University, Tempe, Arizona.
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2
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Yang K, Liu H. Mining the Dynamical Properties of Substrate and FAD Binding Pockets of LSD1: Hints for New Inhibitor Design Direction. J Chem Inf Model 2024; 64:4773-4780. [PMID: 38837697 DOI: 10.1021/acs.jcim.4c00398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2024]
Abstract
Lysine-specific demethylase 1 (LSD1), a highly sophisticated epigenetic regulator, orchestrates a range of critical cellular processes, holding promising therapeutic potential for treating diverse diseases. However, the clinical research progress targeting LSD1 is very slow. After 20 years of research, only one small-molecule drug, BEA-17, targeting the degradation of LSD1 and CoREST has been approved by the U.S. Food and Drug Administration. The primary reason for this may be the lack of abundant structural data regarding its intricate functions. To gain a deeper understanding of its conformational dynamics and guide the drug design process, we conducted molecular dynamics simulations to explore the conformational states of LSD1 in the apo state and under the influence of cofactors of flavin adenine dinucleotide (FAD) and CoREST. Our results showed that, across all states, the substrate binding pocket exhibited high flexibility, whereas the FAD binding pocket remained more stable. These distinct dynamical properties are essential for LSD1's ability to bind various substrates while maintaining efficient demethylation activity. Both pockets can be enlarged by merging with adjacent pockets, although only the substrate binding pocket can shrink into smaller pockets. These new pocket shapes can inform inhibitor design, particularly for selectively FAD-competitive inhibitors of LSD1, given the presence of numerous FAD-dependent enzymes in the human body. More interestingly, in the absence of FAD binding, the united substrate and FAD binding pocket are partitioned by the conserved residue of Tyr761, offering valuable insights for the design of inhibitors that disrupt the crucial steric role of Tyr761 and the redox role of FAD. Additionally, we identified pockets that positively or negatively correlate with the substrate and FAD binding pockets, which can be exploited for the design of allosteric or concurrent inhibitors. Our results reveal the intricate dynamical properties of LSD1 as well as multiple novel conformational states, which deepen our understanding of its sophisticated functions and aid in the rational design of new inhibitors.
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Affiliation(s)
- Kecheng Yang
- National Supercomputing Center in Zhengzhou, Zhengzhou University, Zhengzhou, Henan 450001, China
| | - Hongmin Liu
- Key Lab of Advanced Drug Preparation Technologies, Ministry of Education of China, State Key Laboratory of Esophageal Cancer Prevention & Treatment, Key Laboratory of Henan Province for Drug Quality and Evaluation, Institute of Drug Discovery and Development, School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, Henan 450001, China
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3
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Luu DD, Ramesh N, Kazan IC, Shah KH, Lahiri G, Mana MD, Ozkan SB, Van Horn WD. Evidence that the cold- and menthol-sensing functions of the human TRPM8 channel evolved separately. SCIENCE ADVANCES 2024; 10:eadm9228. [PMID: 38905339 PMCID: PMC11192081 DOI: 10.1126/sciadv.adm9228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 05/16/2024] [Indexed: 06/23/2024]
Abstract
Transient receptor potential melastatin 8 (TRPM8) is a temperature- and menthol-sensitive ion channel that contributes to diverse physiological roles, including cold sensing and pain perception. Clinical trials targeting TRPM8 have faced repeated setbacks predominantly due to the knowledge gap in unraveling the molecular underpinnings governing polymodal activation. A better understanding of the molecular foundations between the TRPM8 activation modes may aid the development of mode-specific, thermal-neutral therapies. Ancestral sequence reconstruction was used to explore the origins of TRPM8 activation modes. By resurrecting key TRPM8 nodes along the human evolutionary trajectory, we gained valuable insights into the trafficking, stability, and function of these ancestral forms. Notably, this approach unveiled the differential emergence of cold and menthol sensitivity over evolutionary time, providing a fresh perspective on complex polymodal behavior. These studies provide a paradigm for understanding polymodal behavior in TRPM8 and other proteins with the potential to enhance our understanding of sensory receptor biology and pave the way for innovative therapeutic interventions.
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Affiliation(s)
- Dustin D. Luu
- School of Molecular Sciences and The Virginia G. Piper Biodesign Center for Personalized Diagnostics, The Biodesign Institute, Arizona State University, Tempe, AZ, USA
| | - Nikhil Ramesh
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, AZ, USA
| | - I. Can Kazan
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, AZ, USA
| | - Karan H. Shah
- School of Molecular Sciences and The Virginia G. Piper Biodesign Center for Personalized Diagnostics, The Biodesign Institute, Arizona State University, Tempe, AZ, USA
| | - Gourab Lahiri
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Miyeko D. Mana
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - S. Banu Ozkan
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, AZ, USA
| | - Wade D. Van Horn
- School of Molecular Sciences and The Virginia G. Piper Biodesign Center for Personalized Diagnostics, The Biodesign Institute, Arizona State University, Tempe, AZ, USA
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4
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Subhadarshini S, Tandon H, Srinivasan N, Sowdhamini R. Normal Mode Analysis Elicits Conformational Shifts in Proteins at Both Proximal and Distal Regions to the Phosphosite Stemming from Single-Site Phosphorylation. ACS OMEGA 2024; 9:24520-24537. [PMID: 38882086 PMCID: PMC11170700 DOI: 10.1021/acsomega.4c00523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 04/29/2024] [Accepted: 05/13/2024] [Indexed: 06/18/2024]
Abstract
Phosphorylation, a fundamental biochemical switch, intricately regulates protein function and signaling pathways. Our study employs extensive computational structural analyses on a curated data set of phosphorylated and unphosphorylated protein pairs to explore the multifaceted impact of phosphorylation on protein conformation. Using normal mode analysis (NMA), we investigated changes in protein flexibility post-phosphorylation, highlighting an enhanced level of structural dynamism. Our findings reveal that phosphorylation induces not only local changes at the phosphorylation site but also extensive alterations in distant regions, showcasing its far-reaching influence on protein structure-dynamics. Through in-depth case studies on polyubiquitin B and glycogen synthase kinase-3 beta, we elucidate how phosphorylation at distinct sites leads to variable structural and dynamic modifications, potentially dictating functional outcomes. While phosphorylation largely preserves the residue motion correlation, it significantly disrupts low-frequency global modes, presenting a dualistic impact on protein dynamics. We also explored alterations in the total accessible surface area (ASA), emphasizing region-specific changes around phosphorylation sites. This study sheds light on phosphorylation-induced conformational changes, dynamic modulation, and surface accessibility alterations, leveraging an integrated computational approach with RMSD, NMA, and ASA, thereby contributing to a comprehensive understanding of cellular regulation and suggesting promising avenues for therapeutic interventions.
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Affiliation(s)
| | - Himani Tandon
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560012, India
| | | | - Ramanathan Sowdhamini
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560012, India
- Computational Approaches to Protein Science, National Centre for Biological Sciences, Bangalore 560065, India
- Computational Biology, Institute of Bioinformatics and Applied Biotechnology, Bangalore 560100, India
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5
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Ose NJ, Campitelli P, Modi T, Kazan IC, Kumar S, Ozkan SB. Some mechanistic underpinnings of molecular adaptations of SARS-COV-2 spike protein by integrating candidate adaptive polymorphisms with protein dynamics. eLife 2024; 12:RP92063. [PMID: 38713502 PMCID: PMC11076047 DOI: 10.7554/elife.92063] [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] [Indexed: 05/08/2024] Open
Abstract
We integrate evolutionary predictions based on the neutral theory of molecular evolution with protein dynamics to generate mechanistic insight into the molecular adaptations of the SARS-COV-2 spike (S) protein. With this approach, we first identified candidate adaptive polymorphisms (CAPs) of the SARS-CoV-2 S protein and assessed the impact of these CAPs through dynamics analysis. Not only have we found that CAPs frequently overlap with well-known functional sites, but also, using several different dynamics-based metrics, we reveal the critical allosteric interplay between SARS-CoV-2 CAPs and the S protein binding sites with the human ACE2 (hACE2) protein. CAPs interact far differently with the hACE2 binding site residues in the open conformation of the S protein compared to the closed form. In particular, the CAP sites control the dynamics of binding residues in the open state, suggesting an allosteric control of hACE2 binding. We also explored the characteristic mutations of different SARS-CoV-2 strains to find dynamic hallmarks and potential effects of future mutations. Our analyses reveal that Delta strain-specific variants have non-additive (i.e., epistatic) interactions with CAP sites, whereas the less pathogenic Omicron strains have mostly additive mutations. Finally, our dynamics-based analysis suggests that the novel mutations observed in the Omicron strain epistatically interact with the CAP sites to help escape antibody binding.
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Affiliation(s)
- Nicholas James Ose
- Department of Physics and Center for Biological Physics, Arizona State UniversityTempeUnited States
| | - Paul Campitelli
- Department of Physics and Center for Biological Physics, Arizona State UniversityTempeUnited States
| | - Tushar Modi
- Department of Physics and Center for Biological Physics, Arizona State UniversityTempeUnited States
| | - I Can Kazan
- Department of Physics and Center for Biological Physics, Arizona State UniversityTempeUnited States
| | - Sudhir Kumar
- Institute for Genomics and Evolutionary Medicine, Temple UniversityPhiladelphiaUnited States
- Department of Biology, Temple UniversityPhiladelphiaUnited States
- Center for Genomic Medicine Research, King Abdulaziz UniversityJeddahSaudi Arabia
| | - Sefika Banu Ozkan
- Department of Physics and Center for Biological Physics, Arizona State UniversityTempeUnited States
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6
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Hacisuleyman A, Erman B. Synergy and anti-cooperativity in allostery: Molecular dynamics study of WT and oncogenic KRAS-RGL1. Proteins 2024; 92:665-678. [PMID: 38153169 DOI: 10.1002/prot.26657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 11/03/2023] [Accepted: 12/15/2023] [Indexed: 12/29/2023]
Abstract
This study focuses on investigating the effects of an oncogenic mutation (G12V) on the stability and interactions within the KRAS-RGL1 protein complex. The KRAS-RGL1 complex is of particular interest due to its relevance to KRAS-associated cancers and the potential for developing targeted drugs against the KRAS system. The stability of the complex and the allosteric effects of specific residues are examined to understand their roles as modulators of complex stability and function. Using molecular dynamics simulations, we calculate the mutual information, MI, between two neighboring residues at the interface of the KRAS-RGL1 complex, and employ the concept of interaction information, II, to measure the contribution of a third residue to the interaction between interface residue pairs. Negative II indicates synergy, where the presence of the third residue strengthens the interaction, while positive II suggests anti-cooperativity. Our findings reveal that MI serves as a dominant factor in determining the results, with the G12V mutation increasing the MI between interface residues, indicating enhanced correlations due to the formation of a more compact structure in the complex. Interestingly, although II plays a role in understanding three-body interactions and the impact of distant residues, it is not significant enough to outweigh the influence of MI in determining the overall stability of the complex. Nevertheless, II may nonetheless be a relevant factor to consider in future drug design efforts. This study provides valuable insights into the mechanisms of complex stability and function, highlighting the significance of three-body interactions and the impact of distant residues on the binding stability of the complex. Additionally, our findings demonstrate that constraining the fluctuations of a third residue consistently increases the stability of the G12V variant, making it challenging to weaken complex formation of the mutated species through allosteric manipulation. The novel perspective offered by this approach on protein dynamics, function, and allostery has potential implications for understanding and targeting other protein complexes involved in vital cellular processes. The results contribute to our understanding of the effects of oncogenic mutations on protein-protein interactions and provide a foundation for future therapeutic interventions in the context of KRAS-associated cancers and beyond.
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Affiliation(s)
- Aysima Hacisuleyman
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Burak Erman
- Department of Chemical and Biological Engineering Koc University, Istanbul, Turkey
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7
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Swint-Kruse L, Fenton AW. Rheostats, toggles, and neutrals, Oh my! A new framework for understanding how amino acid changes modulate protein function. J Biol Chem 2024; 300:105736. [PMID: 38336297 PMCID: PMC10914490 DOI: 10.1016/j.jbc.2024.105736] [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: 11/15/2023] [Revised: 01/09/2024] [Accepted: 01/25/2024] [Indexed: 02/12/2024] Open
Abstract
Advances in personalized medicine and protein engineering require accurately predicting outcomes of amino acid substitutions. Many algorithms correctly predict that evolutionarily-conserved positions show "toggle" substitution phenotypes, which is defined when a few substitutions at that position retain function. In contrast, predictions often fail for substitutions at the less-studied "rheostat" positions, which are defined when different amino acid substitutions at a position sample at least half of the possible functional range. This review describes efforts to understand the impact and significance of rheostat positions: (1) They have been observed in globular soluble, integral membrane, and intrinsically disordered proteins; within single proteins, their prevalence can be up to 40%. (2) Substitutions at rheostat positions can have biological consequences and ∼10% of substitutions gain function. (3) Although both rheostat and "neutral" (defined when all substitutions exhibit wild-type function) positions are nonconserved, the two classes have different evolutionary signatures. (4) Some rheostat positions have pleiotropic effects on function, simultaneously modulating multiple parameters (e.g., altering both affinity and allosteric coupling). (5) In structural studies, substitutions at rheostat positions appear to cause only local perturbations; the overall conformations appear unchanged. (6) Measured functional changes show promising correlations with predicted changes in protein dynamics; the emergent properties of predicted, dynamically coupled amino acid networks might explain some of the complex functional outcomes observed when substituting rheostat positions. Overall, rheostat positions provide unique opportunities for using single substitutions to tune protein function. Future studies of these positions will yield important insights into the protein sequence/function relationship.
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Affiliation(s)
- Liskin Swint-Kruse
- Department of Biochemistry and Molecular Biology, The University of Kansas Medical Center, Kansas City, Kansas, USA.
| | - Aron W Fenton
- Department of Biochemistry and Molecular Biology, The University of Kansas Medical Center, Kansas City, Kansas, USA
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8
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Meller A, Kelly D, Smith LG, Bowman GR. Toward physics-based precision medicine: Exploiting protein dynamics to design new therapeutics and interpret variants. Protein Sci 2024; 33:e4902. [PMID: 38358129 PMCID: PMC10868452 DOI: 10.1002/pro.4902] [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: 09/01/2023] [Revised: 12/01/2023] [Accepted: 01/04/2024] [Indexed: 02/16/2024]
Abstract
The goal of precision medicine is to utilize our knowledge of the molecular causes of disease to better diagnose and treat patients. However, there is a substantial mismatch between the small number of food and drug administration (FDA)-approved drugs and annotated coding variants compared to the needs of precision medicine. This review introduces the concept of physics-based precision medicine, a scalable framework that promises to improve our understanding of sequence-function relationships and accelerate drug discovery. We show that accounting for the ensemble of structures a protein adopts in solution with computer simulations overcomes many of the limitations imposed by assuming a single protein structure. We highlight studies of protein dynamics and recent methods for the analysis of structural ensembles. These studies demonstrate that differences in conformational distributions predict functional differences within protein families and between variants. Thanks to new computational tools that are providing unprecedented access to protein structural ensembles, this insight may enable accurate predictions of variant pathogenicity for entire libraries of variants. We further show that explicitly accounting for protein ensembles, with methods like alchemical free energy calculations or docking to Markov state models, can uncover novel lead compounds. To conclude, we demonstrate that cryptic pockets, or cavities absent in experimental structures, provide an avenue to target proteins that are currently considered undruggable. Taken together, our review provides a roadmap for the field of protein science to accelerate precision medicine.
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Affiliation(s)
- Artur Meller
- Department of Biochemistry and Molecular BiophysicsWashington University in St. LouisSt. LouisMissouriUSA
- Medical Scientist Training ProgramWashington University in St. LouisSt. LouisMissouriUSA
- Departments of Biochemistry & Biophysics and BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Devin Kelly
- Departments of Biochemistry & Biophysics and BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Louis G. Smith
- Departments of Biochemistry & Biophysics and BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Gregory R. Bowman
- Departments of Biochemistry & Biophysics and BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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9
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Ose NJ, Campitelli P, Modi T, Can Kazan I, Kumar S, Banu Ozkan S. Some mechanistic underpinnings of molecular adaptations of SARS-COV-2 spike protein by integrating candidate adaptive polymorphisms with protein dynamics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.14.557827. [PMID: 37745560 PMCID: PMC10515954 DOI: 10.1101/2023.09.14.557827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
We integrate evolutionary predictions based on the neutral theory of molecular evolution with protein dynamics to generate mechanistic insight into the molecular adaptations of the SARS-COV-2 Spike (S) protein. With this approach, we first identified Candidate Adaptive Polymorphisms (CAPs) of the SARS-CoV-2 Spike protein and assessed the impact of these CAPs through dynamics analysis. Not only have we found that CAPs frequently overlap with well-known functional sites, but also, using several different dynamics-based metrics, we reveal the critical allosteric interplay between SARS-CoV-2 CAPs and the S protein binding sites with the human ACE2 (hACE2) protein. CAPs interact far differently with the hACE2 binding site residues in the open conformation of the S protein compared to the closed form. In particular, the CAP sites control the dynamics of binding residues in the open state, suggesting an allosteric control of hACE2 binding. We also explored the characteristic mutations of different SARS-CoV-2 strains to find dynamic hallmarks and potential effects of future mutations. Our analyses reveal that Delta strain-specific variants have non-additive (i.e., epistatic) interactions with CAP sites, whereas the less pathogenic Omicron strains have mostly additive mutations. Finally, our dynamics-based analysis suggests that the novel mutations observed in the Omicron strain epistatically interact with the CAP sites to help escape antibody binding.
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Affiliation(s)
- Nicholas J. Ose
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America
| | - Paul Campitelli
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America
| | - Tushar Modi
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America
| | - I. Can Kazan
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America
| | - Sudhir Kumar
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, Pennsylvania, United States of America
- Department of Biology, Temple University, Philadelphia, Pennsylvania, United States of America
- Center for Genomic Medicine Research, King Abdulaziz University, Jeddah, Saudi Arabia
| | - S. Banu Ozkan
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America
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10
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Begum MN, Mahtarin R, Ahmed S, Shahriar I, Hossain SR, Mia MW, Qadri SS, Qadri F, Mannoor K, Akhteruzzaman S. Investigation of the impact of nonsynonymous mutations on thyroid peroxidase dimer. PLoS One 2023; 18:e0291386. [PMID: 37699049 PMCID: PMC10497151 DOI: 10.1371/journal.pone.0291386] [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: 02/16/2023] [Accepted: 08/25/2023] [Indexed: 09/14/2023] Open
Abstract
Congenital hypothyroidism is one of the most common preventable endocrine disorders associated with thyroid dysgenesis or dyshormonogenesis. Thyroid peroxidase (TPO) gene defect is mainly responsible for dyshormonogenesis; a defect in the thyroid hormone biosynthesis pathway. In Bangladesh, there is limited data regarding the genetic etiology of Congenital Hypothyroidism (CH). The present study investigates the impact of the detected mutations (p.Ala373Ser, and p.Thr725Pro) on the TPO dimer protein. We have performed sequential molecular docking of H2O2 and I- ligands with both monomers of TPO dimer to understand the iodination process in thyroid hormone biosynthesis. Understanding homodimer interactions at the atomic level is a critical challenge to elucidate their biological mechanisms of action. The docking results reveal that mutations in the dimer severely disrupt its catalytic interaction with essential ligands. Molecular dynamics simulation has been performed to validate the docking results, thus realizing the consequence of the mutation in the biological system's mimic. The dynamics results expose that mutations destabilize the TPO dimer protein. Finally, principal component analysis exhibits structural and energy profile discrepancies in wild-type and mutant dimers. The findings of this study highlight that the mutations in TPO protein can critically affect the dimer structure and loss of enzymatic activity is persistent. Other factors also might influence the hormone synthesis pathway, which is under investigation.
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Affiliation(s)
- Mst. Noorjahan Begum
- Department of Genetic Engineering & Biotechnology, University of Dhaka, Dhaka, Bangladesh
- Institute for Developing Science and Health Initiatives (ideSHi), ECB Chattar, Mirpur, Dhaka, Bangladesh
- Virology Laboratory, Infectious Diseases Division, International Centre for Diarrhoeal Disease Research, Bangladesh, Mohakhali, Dhaka, Bangladesh
| | - Rumana Mahtarin
- Institute for Developing Science and Health Initiatives (ideSHi), ECB Chattar, Mirpur, Dhaka, Bangladesh
- Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet, Bangladesh
| | - Sinthyia Ahmed
- Division of Computer Aided Drug Design, The Red-Green Research Centre, BICCB, Tejgaon, Dhaka, Bangladesh
| | - Imrul Shahriar
- Division of Computer Aided Drug Design, The Red-Green Research Centre, BICCB, Tejgaon, Dhaka, Bangladesh
| | - Shekh Rezwan Hossain
- Institute for Developing Science and Health Initiatives (ideSHi), ECB Chattar, Mirpur, Dhaka, Bangladesh
| | - Md. Waseque Mia
- Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet, Bangladesh
| | - Syed Saleheen Qadri
- Institute for Developing Science and Health Initiatives (ideSHi), ECB Chattar, Mirpur, Dhaka, Bangladesh
| | - Firdausi Qadri
- Institute for Developing Science and Health Initiatives (ideSHi), ECB Chattar, Mirpur, Dhaka, Bangladesh
- Mucosal Immunology and Vaccinology, Infectious Diseases Division, International Centre for Diarrhoeal Disease Research, Bangladesh, Mohakhali, Dhaka, Bangladesh
| | - Kaiissar Mannoor
- Institute for Developing Science and Health Initiatives (ideSHi), ECB Chattar, Mirpur, Dhaka, Bangladesh
| | - Sharif Akhteruzzaman
- Department of Genetic Engineering & Biotechnology, University of Dhaka, Dhaka, Bangladesh
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11
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Lu J, Rahman MI, Kazan IC, Halloran NR, Bobkov AA, Ozkan SB, Ghirlanda G. Engineering gain-of-function mutants of a WW domain by dynamics and structural analysis. Protein Sci 2023; 32:e4759. [PMID: 37574787 PMCID: PMC10464296 DOI: 10.1002/pro.4759] [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: 03/22/2023] [Revised: 07/17/2023] [Accepted: 08/10/2023] [Indexed: 08/15/2023]
Abstract
Proteins gain optimal fitness such as foldability and function through evolutionary selection. However, classical studies have found that evolutionarily designed protein sequences alone cannot guarantee foldability, or at least not without considering local contacts associated with the initial folding steps. We previously showed that foldability and function can be restored by removing frustration in the folding energy landscape of a model WW domain protein, CC16, which was designed based on Statistical Coupling Analysis (SCA). Substitutions ensuring the formation of five local contacts identified as "on-path" were selected using the closest homolog native folded sequence, N21. Surprisingly, the resulting sequence, CC16-N21, bound to Group I peptides, while N21 did not. Here, we identified single-point mutations that enable N21 to bind a Group I peptide ligand through structure and dynamic-based computational design. Comparison of the docked position of the CC16-N21/ligand complex with the N21 structure showed that residues at positions 9 and 19 are important for peptide binding, whereas the dynamic profiles identified position 10 as allosterically coupled to the binding site and exhibiting different dynamics between N21 and CC16-N21. We found that swapping these positions in N21 with matched residues from CC16-N21 recovers nature-like binding affinity to N21. This study validates the use of dynamic profiles as guiding principles for affecting the binding affinity of small proteins.
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Affiliation(s)
- Jin Lu
- Department of Physics and Center for Biological PhysicsArizona State UniversityTempeArizonaUSA
| | | | - I. Can Kazan
- Department of Physics and Center for Biological PhysicsArizona State UniversityTempeArizonaUSA
| | | | - Andrey A. Bobkov
- Conrad Prebys Center for Chemical GenomicsSanford Burnham Prebys Medical Discovery InstituteCaliforniaUSA
| | - S. Banu Ozkan
- Department of Physics and Center for Biological PhysicsArizona State UniversityTempeArizonaUSA
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12
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Gorostiola González M, van den Broek RL, Braun TGM, Chatzopoulou M, Jespers W, IJzerman AP, Heitman LH, van Westen GJP. 3DDPDs: describing protein dynamics for proteochemometric bioactivity prediction. A case for (mutant) G protein-coupled receptors. J Cheminform 2023; 15:74. [PMID: 37641107 PMCID: PMC10463931 DOI: 10.1186/s13321-023-00745-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 08/10/2023] [Indexed: 08/31/2023] Open
Abstract
Proteochemometric (PCM) modelling is a powerful computational drug discovery tool used in bioactivity prediction of potential drug candidates relying on both chemical and protein information. In PCM features are computed to describe small molecules and proteins, which directly impact the quality of the predictive models. State-of-the-art protein descriptors, however, are calculated from the protein sequence and neglect the dynamic nature of proteins. This dynamic nature can be computationally simulated with molecular dynamics (MD). Here, novel 3D dynamic protein descriptors (3DDPDs) were designed to be applied in bioactivity prediction tasks with PCM models. As a test case, publicly available G protein-coupled receptor (GPCR) MD data from GPCRmd was used. GPCRs are membrane-bound proteins, which are activated by hormones and neurotransmitters, and constitute an important target family for drug discovery. GPCRs exist in different conformational states that allow the transmission of diverse signals and that can be modified by ligand interactions, among other factors. To translate the MD-encoded protein dynamics two types of 3DDPDs were considered: one-hot encoded residue-specific (rs) and embedding-like protein-specific (ps) 3DDPDs. The descriptors were developed by calculating distributions of trajectory coordinates and partial charges, applying dimensionality reduction, and subsequently condensing them into vectors per residue or protein, respectively. 3DDPDs were benchmarked on several PCM tasks against state-of-the-art non-dynamic protein descriptors. Our rs- and ps3DDPDs outperformed non-dynamic descriptors in regression tasks using a temporal split and showed comparable performance with a random split and in all classification tasks. Combinations of non-dynamic descriptors with 3DDPDs did not result in increased performance. Finally, the power of 3DDPDs to capture dynamic fluctuations in mutant GPCRs was explored. The results presented here show the potential of including protein dynamic information on machine learning tasks, specifically bioactivity prediction, and open opportunities for applications in drug discovery, including oncology.
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Affiliation(s)
- Marina Gorostiola González
- Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
- ONCODE Institute, Leiden, The Netherlands
| | - Remco L van den Broek
- Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Thomas G M Braun
- Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Magdalini Chatzopoulou
- Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Willem Jespers
- Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Adriaan P IJzerman
- Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Laura H Heitman
- Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
- ONCODE Institute, Leiden, The Netherlands
| | - Gerard J P van Westen
- Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
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13
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Kazan IC, Mills JH, Ozkan SB. Allosteric regulatory control in dihydrofolate reductase is revealed by dynamic asymmetry. Protein Sci 2023; 32:e4700. [PMID: 37313628 PMCID: PMC10357497 DOI: 10.1002/pro.4700] [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: 12/16/2022] [Revised: 06/05/2023] [Accepted: 06/06/2023] [Indexed: 06/15/2023]
Abstract
We investigated the relationship between mutations and dynamics in Escherichia coli dihydrofolate reductase (DHFR) using computational methods. Our study focused on the M20 and FG loops, which are known to be functionally important and affected by mutations distal to the loops. We used molecular dynamics simulations and developed position-specific metrics, including the dynamic flexibility index (DFI) and dynamic coupling index (DCI), to analyze the dynamics of wild-type DHFR and compared our results with existing deep mutational scanning data. Our analysis showed a statistically significant association between DFI and mutational tolerance of the DHFR positions, indicating that DFI can predict functionally beneficial or detrimental substitutions. We also applied an asymmetric version of our DCI metric (DCIasym ) to DHFR and found that certain distal residues control the dynamics of the M20 and FG loops, whereas others are controlled by them. Residues that are suggested to control the M20 and FG loops by our DCIasym metric are evolutionarily nonconserved; mutations at these sites can enhance enzyme activity. On the other hand, residues controlled by the loops are mostly deleterious to function when mutated and are also evolutionary conserved. Our results suggest that dynamics-based metrics can identify residues that explain the relationship between mutation and protein function or can be targeted to rationally engineer enzymes with enhanced activity.
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Affiliation(s)
- I. Can Kazan
- Center for Biological Physics and Department of PhysicsArizona State UniversityTempeArizonaUSA
| | - Jeremy H. Mills
- School of Molecular Sciences and The Biodesign Center for Molecular Design and BiomimeticsArizona State UniversityTempeArizonaUSA
| | - S. Banu Ozkan
- Center for Biological Physics and Department of PhysicsArizona State UniversityTempeArizonaUSA
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14
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Ose NJ, Campitelli P, Patel R, Kumar S, Ozkan SB. Protein dynamics provide mechanistic insights about epistasis among common missense polymorphisms. Biophys J 2023; 122:2938-2947. [PMID: 36726312 PMCID: PMC10398253 DOI: 10.1016/j.bpj.2023.01.037] [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: 10/12/2022] [Revised: 12/20/2022] [Accepted: 01/26/2023] [Indexed: 02/03/2023] Open
Abstract
Sequencing of the protein coding genome has revealed many different missense mutations of human proteins and different population frequencies of corresponding haplotypes, which consist of different sets of those mutations. Here, we present evidence for pairwise intramolecular epistasis (i.e., nonadditive interactions) between many such mutations through an analysis of protein dynamics. We suggest that functional compensation for conserving protein dynamics is a likely evolutionary mechanism that maintains high-frequency mutations that are individually nonneutral but epistatically compensating within proteins. This analysis is the first of its type to look at human proteins with specific high population frequency mutations and examine the relationship between mutations that make up that observed high-frequency protein haplotype. Importantly, protein dynamics revealed a separation between high and low frequency haplotypes within a target protein cytochrome P450 2A7, with the high-frequency haplotypes showing behavior closer to the wild-type protein. Common protein haplotypes containing two mutations display dynamic compensation in which one mutation can correct for the dynamic effects of the other. We also utilize a dynamics-based metric, EpiScore, that evaluates the epistatic interactions and allows us to see dynamic compensation within many other proteins.
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Affiliation(s)
- Nicholas J Ose
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona
| | - Paul Campitelli
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona
| | - Ravi Patel
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, Pennsylvania; Department of Biology, Temple University, Philadelphia, Pennsylvania
| | - Sudhir Kumar
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, Pennsylvania; Department of Biology, Temple University, Philadelphia, Pennsylvania; Center for Genomic Medicine Research, King Abdulaziz University, Jeddah, Saudi Arabia.
| | - S Banu Ozkan
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona.
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15
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Lagniton PNP, Tam B, Wang SM. DARVIC: Dihedral angle-reliant variant impact classifier for functional prediction of missense VUS. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 238:107596. [PMID: 37201251 DOI: 10.1016/j.cmpb.2023.107596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Revised: 04/19/2023] [Accepted: 05/10/2023] [Indexed: 05/20/2023]
Abstract
BACKGROUND Of the large number of genetic variants identified, the functional impact for most of them remains unknown. Mutations in DNA damage repair genes such as MUTYH, which is involved in repairing A:8-oxoG mismatches caused by reactive oxygen species, can cause a higher risk of cancer. Mutations happening in other key genes such as TP53 also pose huge health threats and risk of cancer. The interpretation of genetic variants' functional impact is a forefront issue that needs to be addressed. Many different in silico methods based on different principles have been developed and applied in interpreting genetic variants. However, a current challenge is that many existing methods tend to overpredict the pathogenicity of benign variants. A new approach is needed to tackle this issue to improve genetic variant interpretation through the use of in silico methods. METHODS In this study, we developed another protein structural-based approach called Dihedral angle-reliant variant impact classifier (DARVIC) to predict the deleterious impact of the coding-changing missense variants. DARVIC uses Ramachandran's principle of protein stereochemistry as the theoretical foundation and uses molecular dynamics simulations coupled with a supervised machine learning algorithm XGBoost to determine the functional impact of missense variants on protein structural stability. RESULTS We characterized the features of dihedral angles in dynamic protein structures. We also tested the performance of DARVIC in MUTYH and TP53 missense variants and achieved satisfactory results in reflecting the functional impacts of the variants on protein structure. The method achieved a balanced accuracy of 84% in a functionally validated MUTYH dataset containing both benign and pathogenic missense variants, higher than other existing in silico methods. Along with that, DARVIC was able to predict 119 (47%) deleterious variants from a dataset of 254 MUTYH VUS. Further application of DARVIC to a functionally validated TP53 dataset had a balanced accuracy of 94%, topping other methods, demonstrating DARVIC's robustness. CONCLUSION DARVIC provides a valuable tool to predict the functional impacts of missense variants based on their effects on protein structural stability and motion. At its current state, DARVIC performed well in predicting the functional impact of the missense variants both in MUTYH and TP53. We expect its high potential to predict functional impact for the missense variants in other genes.
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Affiliation(s)
- Philip Naderev P Lagniton
- Cancer Centre and Institute of Translational Medicine, Department of Public Health and Medical Administration, Faculty of Health Sciences, Ministry of Education Frontiers Science Center for Precision Oncology, University of Macau, Macao
| | - Benjamin Tam
- Cancer Centre and Institute of Translational Medicine, Department of Public Health and Medical Administration, Faculty of Health Sciences, Ministry of Education Frontiers Science Center for Precision Oncology, University of Macau, Macao
| | - San Ming Wang
- Cancer Centre and Institute of Translational Medicine, Department of Public Health and Medical Administration, Faculty of Health Sciences, Ministry of Education Frontiers Science Center for Precision Oncology, University of Macau, Macao; Senior Author, Macao.
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16
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Nakhaei-Rad S, Janatifard F, Dvorsky R, Ahmadian MR, Housaindokht MR. Molecular analyses of the C-terminal CRAF variants associated with cardiomyopathy reveal their opposing impacts on the active conformation of the kinase domain. J Biomol Struct Dyn 2023; 41:15328-15338. [PMID: 36927384 DOI: 10.1080/07391102.2023.2187221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 02/28/2023] [Indexed: 03/18/2023]
Abstract
The germline mutations in the C-terminus of CRAF kinase, particularly L603, and S612T/L613V, are associated with congenital heart disorders, for example, dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM). The experimental data suggest that genetic alternation at position 603 impairs, while those at positions 612/613 enhance the CRAF kinase activity. However, the underlying mechanistic details by which these mutations increase or decrease kinase activity remain elusive. Therefore, we applied molecular dynamic simulation to investigate the impacts of these point mutations on the conformation of the CRAF kinase domain. The results revealed that the substitution of Leucine 603 for proline transits the kinase domain to a state that exhibits the molecular hallmarks of an inactive kinase, for example, a closed activation loop, 'αC-helix out' conformation and a distorted regulatory hydrophobic spine. However, two HCM-associated variants (S612T and L613V) show features of an active conformation, such as an open activation loop conformation, 'αC-helix in', the assembly of the hydrophobic spine, and more surface-exposed catalytic residues of phosphoryl transfer reaction. Overall, our study provides a mechanistic basis for the contradictory effects of the CRAF variants associated with HCM and DCM.
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Affiliation(s)
- Saeideh Nakhaei-Rad
- Stem Cell Biology, and Regenerative Medicine Research Group, Institute of Biotechnology, Ferdowsi University of Mashhad, Mashhad, Iran
| | - Fatemeh Janatifard
- Department of Chemistry, Faculty of Science, Ferdowsi University of Mashhad, Mashhad, Iran
| | | | - Mohammad R Ahmadian
- Institute of Biochemistry and Molecular Biology II, Medical Faculty, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
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17
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Banerjee A, Saha S, Tvedt NC, Yang LW, Bahar I. Mutually beneficial confluence of structure-based modeling of protein dynamics and machine learning methods. Curr Opin Struct Biol 2023; 78:102517. [PMID: 36587424 PMCID: PMC10038760 DOI: 10.1016/j.sbi.2022.102517] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 11/19/2022] [Accepted: 11/22/2022] [Indexed: 12/31/2022]
Abstract
Proteins sample an ensemble of conformers under physiological conditions, having access to a spectrum of modes of motions, also called intrinsic dynamics. These motions ensure the adaptation to various interactions in the cell, and largely assist in, if not determine, viable mechanisms of biological function. In recent years, machine learning frameworks have proven uniquely useful in structural biology, and recent studies further provide evidence to the utility and/or necessity of considering intrinsic dynamics for increasing their predictive ability. Efficient quantification of dynamics-based attributes by recently developed physics-based theories and models such as elastic network models provides a unique opportunity to generate data on dynamics for training ML models towards inferring mechanisms of protein function, assessing pathogenicity, or estimating binding affinities.
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Affiliation(s)
- Anupam Banerjee
- Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh PA 15261, USA
| | - Satyaki Saha
- Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh PA 15261, USA
| | - Nathan C Tvedt
- Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh PA 15261, USA; Computational and Applied Mathematics and Statistics, The College of William and Mary, Williamsburg, VA 23185, USA
| | - Lee-Wei Yang
- Institute of Bioinformatics and Structural Biology, and PhD Program in Biomedical Artificial Intelligence, National Tsing Hua University, Hsinchu 300044, Taiwan; Physics Division, National Center for Theoretical Sciences, Taipei 106319, Taiwan
| | - Ivet Bahar
- Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh PA 15261, USA.
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18
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Smith IN, Dawson JE, Eng C. Comparative Protein Structural Network Analysis Reveals C-Terminal Tail Phosphorylation Structural Communication Fingerprint in PTEN-Associated Mutations in Autism and Cancer. J Phys Chem B 2023; 127:634-647. [PMID: 36626331 PMCID: PMC9885960 DOI: 10.1021/acs.jpcb.2c06776] [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: 09/23/2022] [Revised: 11/24/2022] [Indexed: 01/11/2023]
Abstract
PTEN (phosphatase and tensin homolog deleted on chromosome 10) is a tightly regulated dual-specificity phosphatase and key regulator of the PI3K/AKT/mTOR signaling pathway. PTEN phosphorylation at its carboxy-terminal tail (CTT) serine/threonine cluster negatively regulates its tumor suppressor function by inducing a stable, closed, and inactive conformation. Germline PTEN mutations predispose individuals to PTEN hamartoma tumor syndrome (PHTS), a rare inherited cancer syndrome and, intriguingly, one of the most common causes of autism spectrum disorder (ASD). However, the mechanistic details that govern phosphorylated CTT catalytic conformational dynamics in the context of PHTS-associated mutations are unknown. Here, we utilized a comparative protein structure network (PSN)-based approach to investigate PTEN CTT phosphorylation-induced conformational dynamics specific to PTEN-ASD compared to PTEN-cancer phenotypes. Results from our study show differences in structural flexibility, inter-residue contacts, and allosteric communication patterns mediated by CTT phosphorylation, differentiating PTEN-ASD and PTEN-cancer phenotypes. Further, we identified perturbations among global metapaths and community network connections within the active site and inter-domain regions, indicating the significance of these regions in transmitting information across the PSN. Together, our studies provide a mechanistic underpinning of allosteric regulation through the coupled interplay of CTT phosphorylation conformational dynamics in PTEN-ASD and PTEN-cancer mutations. Importantly, the detailed atomistic interactions and structural consequences of PTEN variants reveal potential allosteric druggable target sites as a viable and currently unexplored treatment approach for individuals with different PHTS-associated mutations.
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Affiliation(s)
- Iris N. Smith
- Genomic
Medicine Institute, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, NE-50, Cleveland, Ohio44195, United States
| | - Jennifer E. Dawson
- Genomic
Medicine Institute, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, NE-50, Cleveland, Ohio44195, United States
| | - Charis Eng
- Genomic
Medicine Institute, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, NE-50, Cleveland, Ohio44195, United States
- Cleveland
Clinic Lerner College of Medicine, Case
Western Reserve University, 9500 Euclid Avenue, Cleveland, Ohio44195, United
States
- Case
Comprehensive Cancer Center, Case Western
Reserve University School of Medicine, 10900 Euclid Avenue, Cleveland, Ohio44106, United States
- Taussig
Cancer Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, Ohio44195, United States
- Department
of Genetics and Genome Sciences, Case Western
Reserve University School of Medicine, 10900 Euclid Avenue, Cleveland, Ohio44106, United States
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19
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McBride JM, Eckmann JP, Tlusty T. General Theory of Specific Binding: Insights from a Genetic-Mechano-Chemical Protein Model. Mol Biol Evol 2022; 39:msac217. [PMID: 36208205 PMCID: PMC9641994 DOI: 10.1093/molbev/msac217] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Proteins need to selectively interact with specific targets among a multitude of similar molecules in the cell. However, despite a firm physical understanding of binding interactions, we lack a general theory of how proteins evolve high specificity. Here, we present such a model that combines chemistry, mechanics, and genetics and explains how their interplay governs the evolution of specific protein-ligand interactions. The model shows that there are many routes to achieving molecular discrimination-by varying degrees of flexibility and shape/chemistry complementarity-but the key ingredient is precision. Harder discrimination tasks require more collective and precise coaction of structure, forces, and movements. Proteins can achieve this through correlated mutations extending far from a binding site, which fine-tune the localized interaction with the ligand. Thus, the solution of more complicated tasks is enabled by increasing the protein size, and proteins become more evolvable and robust when they are larger than the bare minimum required for discrimination. The model makes testable, specific predictions about the role of flexibility and shape mismatch in discrimination, and how evolution can independently tune affinity and specificity. Thus, the proposed theory of specific binding addresses the natural question of "why are proteins so big?". A possible answer is that molecular discrimination is often a hard task best performed by adding more layers to the protein.
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Affiliation(s)
- John M McBride
- Center for Soft and Living Matter, Institute for Basic Science, Ulsan 44919, South Korea
| | - Jean-Pierre Eckmann
- Département de Physique Théorique and Section de Mathématiques, University of Geneva, Geneva, Switzerland
| | - Tsvi Tlusty
- Center for Soft and Living Matter, Institute for Basic Science, Ulsan 44919, South Korea
- Departments of Physics and Chemistry, Ulsan National Institute of Science and Technology, Ulsan 44919, South Korea
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