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Tee WV, Lim SJM, Berezovsky IN. Toward the Design of Allosteric Effectors: Gaining Comprehensive Control of Drug Properties and Actions. J Med Chem 2024. [PMID: 39326868 DOI: 10.1021/acs.jmedchem.4c01043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/28/2024]
Abstract
While the therapeutic potential of allosteric drugs is increasingly realized, the discovery of effectors is largely incidental. The rational design of allosteric effectors requires new state-of-the-art approaches to account for the distinct characteristics of allosteric ligands and their modes of action. We present a broadly applicable computational framework for obtaining allosteric site-effector pairs, providing targeted, highly specific, and tunable regulation to any functional site. We validated the framework using the main protease from SARS-CoV-2 and the K-RasG12D oncoprotein. High-throughput per-residue quantification of the energetics of allosteric signaling and effector binding revealed known drugs capable of inducing the required modulation upon binding. Starting from fragments of known well-characterized drugs, allosteric effectors and binding sites were designed and optimized simultaneously to achieve targeted and specific signaling to distinct functional sites, such as, for example, the switch regions of K-RasG12D. The generic framework proposed in this work will be instrumental in developing allosteric therapies aligned with a precision medicine approach.
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Affiliation(s)
- Wei-Ven Tee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore
| | - Sylvester J M Lim
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore
| | - Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore
- Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, Singapore 117579, Singapore
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Zheng Z, Goncearenco A, Berezovsky IN. Back in time to the Gly-rich prototype of the phosphate binding elementary function. Curr Res Struct Biol 2024; 7:100142. [PMID: 38655428 PMCID: PMC11035071 DOI: 10.1016/j.crstbi.2024.100142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Revised: 03/31/2024] [Accepted: 04/03/2024] [Indexed: 04/26/2024] Open
Abstract
Binding of nucleotides and their derivatives is one of the most ancient elementary functions dating back to the Origin of Life. We review here the works considering one of the key elements in binding of (di)nucleotide-containing ligands - phosphate binding. We start from a brief discussion of major participants, conditions, and events in prebiotic evolution that resulted in the Origin of Life. Tracing back to the basic functions, including metal and phosphate binding, and, potentially, formation of primitive protein-protein interactions, we focus here on the phosphate binding. Critically assessing works on the structural, functional, and evolutionary aspects of phosphate binding, we perform a simple computational experiment reconstructing its most ancient and generic sequence prototype. The profiles of the phosphate binding signatures have been derived in form of position-specific scoring matrices (PSSMs), their peculiarities depending on the type of the ligands have been analyzed, and evolutionary connections between them have been delineated. Then, the apparent prototype that gave rise to all relevant phosphate-binding signatures had also been reconstructed. We show that two major signatures of the phosphate binding that discriminate between the binding of dinucleotide- and nucleotide-containing ligands are GxGxxG and GxxGxG, respectively. It appears that the signature archetypal for dinucleotide-containing ligands is more generic, and it can frequently bind phosphate groups in nucleotide-containing ligands as well. The reconstructed prototype's key signature GxGGxG underlies the role of glycine residues in providing flexibility and interactions necessary for binding the phosphate groups. The prototype also contains other ancient amino acids, valine, and alanine, showing versatility towards evolutionary design and functional diversification.
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Affiliation(s)
- Zejun Zheng
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
| | | | - Igor N. Berezovsky
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
- Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117579, Singapore
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Amangeldina A, Tan ZW, Berezovsky IN. Living in trinity of extremes: Genomic and proteomic signatures of halophilic, thermophilic, and pH adaptation. Curr Res Struct Biol 2024; 7:100129. [PMID: 38327713 PMCID: PMC10847869 DOI: 10.1016/j.crstbi.2024.100129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 01/16/2024] [Accepted: 01/16/2024] [Indexed: 02/09/2024] Open
Abstract
Since nucleic acids and proteins of unicellular prokaryotes are directly exposed to extreme environmental conditions, it is possible to explore the genomic-proteomic compositional determinants of molecular mechanisms of adaptation developed by them in response to harsh environmental conditions. Using a wealth of currently available complete genomes/proteomes we were able to explore signatures of adaptation to three environmental factors, pH, salinity, and temperature, observing major trends in compositions of their nucleic acids and proteins. We derived predictors of thermostability, halophilic, and pH adaptations and complemented them by the principal components analysis. We observed a clear difference between thermophilic and salinity/pH adaptations, whereas latter invoke seemingly overlapping mechanisms. The genome-proteome compositional trade-off reveals an intricate balance between the work of base paring and base stacking in stabilization of coding DNA and r/tRNAs, and, at the same time, universal requirements for the stability and foldability of proteins regardless of the nucleotide biases. Nevertheless, we still found hidden fingerprints of ancient evolutionary connections between the nucleotide and amino acid compositions indicating their emergence, mutual evolution, and adjustment. The evolutionary perspective on the adaptation mechanisms is further studied here by means of the comparative analysis of genomic/proteomic traits of archaeal and bacterial species. The overall picture of genomic/proteomic signals of adaptation obtained here provides a foundation for future engineering and design of functional biomolecules resistant to harsh environments.
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Affiliation(s)
- Aidana Amangeldina
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
- Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117579, Singapore
| | - Zhen Wah Tan
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
| | - Igor N. Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
- Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117579, Singapore
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Tee WV, Berezovsky IN. Allosteric drugs: New principles and design approaches. Curr Opin Struct Biol 2024; 84:102758. [PMID: 38171188 DOI: 10.1016/j.sbi.2023.102758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 11/30/2023] [Indexed: 01/05/2024]
Abstract
Focusing on an important biomedical implication of allostery - design of allosteric drugs, we describe characteristics of allosteric sites, effectors, and their modes of actions distinguishing them from the orthosteric counterparts and calling for new principles and protocols in the quests for allosteric drugs. We show the importance of considering both binding affinity and allosteric signaling in establishing the structure-activity relationships (SARs) toward design of allosteric effectors, arguing that pairs of allosteric sites and their effector ligands - the site-effector pairs - should be generated and adjusted simultaneously in the framework of what we call directed design protocol. Key ideas and approaches for designing allosteric effectors including reverse perturbation, targeted and agnostic analysis are also discussed here. Several promising computational approaches are highlighted, along with the need for and potential advantages of utilizing generative models to facilitate discovery/design of new allosteric drugs.
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Affiliation(s)
- Wei-Ven Tee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A∗STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671.
| | - Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A∗STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671; Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117579, Singapore.
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Mughal F, Caetano-Anollés G. Evolution of Intrinsic Disorder in Protein Loops. Life (Basel) 2023; 13:2055. [PMID: 37895436 PMCID: PMC10608553 DOI: 10.3390/life13102055] [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: 09/13/2023] [Revised: 10/08/2023] [Accepted: 10/10/2023] [Indexed: 10/29/2023] Open
Abstract
Intrinsic disorder accounts for the flexibility of protein loops, molecular building blocks that are largely responsible for the processes and molecular functions of the living world. While loops likely represent early structural forms that served as intermediates in the emergence of protein structural domains, their origin and evolution remain poorly understood. Here, we conduct a phylogenomic survey of disorder in loop prototypes sourced from the ArchDB classification. Tracing prototypes associated with protein fold families along an evolutionary chronology revealed that ancient prototypes tended to be more disordered than their derived counterparts, with ordered prototypes developing later in evolution. This highlights the central evolutionary role of disorder and flexibility. While mean disorder increased with time, a minority of ordered prototypes exist that emerged early in evolutionary history, possibly driven by the need to preserve specific molecular functions. We also revealed the percolation of evolutionary constraints from higher to lower levels of organization. Percolation resulted in trade-offs between flexibility and rigidity that impacted prototype structure and geometry. Our findings provide a deep evolutionary view of the link between structure, disorder, flexibility, and function, as well as insights into the evolutionary role of intrinsic disorder in loops and their contribution to protein structure and function.
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Affiliation(s)
- Fizza Mughal
- Evolutionary Bioinformatics Laboratory, Department of Crop Sciences, University of Illinois, Urbana, IL 61801, USA
| | - Gustavo Caetano-Anollés
- Evolutionary Bioinformatics Laboratory, Department of Crop Sciences, University of Illinois, Urbana, IL 61801, USA
- C.R. Woese Institute for Genomic Biology, University of Illinois, Urbana, IL 61801, USA
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Sánchez-Moguel I, Costa-Silva TA, Pillaca-Pullo OS, Flores-Santos JC, Freire RKB, Carretero G, da Luz Bueno J, Camacho-Córdova DI, Santos JH, Sette LD, Pessoa-Jr A. Antarctic yeasts as a source of L-asparaginase: characterization of a glutaminase-activity free L-asparaginase from psychrotolerant yeast Leucosporidium scottii L115. Process Biochem 2023. [DOI: 10.1016/j.procbio.2023.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/09/2023]
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Tan ZW, Tee WV, Guarnera E, Berezovsky IN. AlloMAPS 2: allosteric fingerprints of the AlphaFold and Pfam-trRosetta predicted structures for engineering and design. Nucleic Acids Res 2022; 51:D345-D351. [PMID: 36169226 PMCID: PMC9825619 DOI: 10.1093/nar/gkac828] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 08/26/2022] [Accepted: 09/15/2022] [Indexed: 01/29/2023] Open
Abstract
AlloMAPS 2 is an update of the Allosteric Mutation Analysis and Polymorphism of Signalling database, which contains data on allosteric communication obtained for predicted structures in the AlphaFold database (AFDB) and trRosetta-predicted Pfam domains. The data update contains Allosteric Signalling Maps (ASMs) and Allosteric Probing Maps (APMs) quantifying allosteric effects of mutations and of small probe binding, respectively. To ensure quality of the ASMs and APMs, we performed careful and accurate selection of protein sets containing high-quality predicted structures in both databases for each organism/structure, and the data is available for browsing and download. The data for remaining structures are available for download and should be used at user's discretion and responsibility. We believe these massive data can facilitate both diagnostics and drug design within the precision medicine paradigm. Specifically, it can be instrumental in the analysis of allosteric effects of pathological and rescue mutations, providing starting points for fragment-based design of allosteric effectors. The exhaustive character of allosteric signalling and probing fingerprints will be also useful in future developments of corresponding machine learning applications. The database is freely available at: http://allomaps.bii.a-star.edu.sg.
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Affiliation(s)
- Zhen Wah Tan
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
| | - Wei-Ven Tee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
| | - Enrico Guarnera
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
| | - Igor N Berezovsky
- To whom correspondence should be addressed. Tel: +65 6478 8269; Fax: +65 6478 9047;
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Nussinov R, Zhang M, Liu Y, Jang H. AlphaFold, Artificial Intelligence (AI), and Allostery. J Phys Chem B 2022; 126:6372-6383. [PMID: 35976160 PMCID: PMC9442638 DOI: 10.1021/acs.jpcb.2c04346] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 08/03/2022] [Indexed: 02/08/2023]
Abstract
AlphaFold has burst into our lives. A powerful algorithm that underscores the strength of biological sequence data and artificial intelligence (AI). AlphaFold has appended projects and research directions. The database it has been creating promises an untold number of applications with vast potential impacts that are still difficult to surmise. AI approaches can revolutionize personalized treatments and usher in better-informed clinical trials. They promise to make giant leaps toward reshaping and revamping drug discovery strategies, selecting and prioritizing combinations of drug targets. Here, we briefly overview AI in structural biology, including in molecular dynamics simulations and prediction of microbiota-human protein-protein interactions. We highlight the advancements accomplished by the deep-learning-powered AlphaFold in protein structure prediction and their powerful impact on the life sciences. At the same time, AlphaFold does not resolve the decades-long protein folding challenge, nor does it identify the folding pathways. The models that AlphaFold provides do not capture conformational mechanisms like frustration and allostery, which are rooted in ensembles, and controlled by their dynamic distributions. Allostery and signaling are properties of populations. AlphaFold also does not generate ensembles of intrinsically disordered proteins and regions, instead describing them by their low structural probabilities. Since AlphaFold generates single ranked structures, rather than conformational ensembles, it cannot elucidate the mechanisms of allosteric activating driver hotspot mutations nor of allosteric drug resistance. However, by capturing key features, deep learning techniques can use the single predicted conformation as the basis for generating a diverse ensemble.
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Affiliation(s)
- Ruth Nussinov
- Computational
Structural Biology Section, Frederick National
Laboratory for Cancer Research, Frederick, Maryland 21702, United States
- Department
of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
| | - Mingzhen Zhang
- Computational
Structural Biology Section, Frederick National
Laboratory for Cancer Research, Frederick, Maryland 21702, United States
| | - Yonglan Liu
- Cancer
Innovation Laboratory, National Cancer Institute, Frederick, Maryland 21702, United States
| | - Hyunbum Jang
- Computational
Structural Biology Section, Frederick National
Laboratory for Cancer Research, Frederick, Maryland 21702, United States
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Berezovsky IN, Nussinov R. Multiscale Allostery: Basic Mechanisms and Versatility in Diagnostics and Drug Design. J Mol Biol 2022; 434:167751. [PMID: 35863488 DOI: 10.1016/j.jmb.2022.167751] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Affiliation(s)
- Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore; Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117579, Singapore.
| | - Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Cancer Innovation Laboraory, National Cancer Institute, Frederick, MD 21702, USA; Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel.
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