Physics and Evolution of Biological Macromolecules
Research
PHYSICS AND EVOLUTION OF BIOLOGICAL MACROMOLECULES
Working at the interface between physics and biology, we develop physical models and computational approaches for modelling structures of biomolecules and for predicting their functional characteristics. The research topics in the group include, but are not limited to, protein allostery, biophysics of chromatin and epigenetic regulation, evolution of protein function, evolutionary-inspired design of protein function, and molecular mechanisms of adaptation.ALLOSTERY: RECENT CONCEPTUAL DEVELOPMENTS
Our work on basic mechanisms and
practical implications of allostery,
have continuously propelled us to
be among the world leaders in the
cutting-edge research on allostery.
As an indicator of the group’s
achievements, the Special Issue
“Allostery: From Mechanisms to
Therapies” of the Journal of Molecular
Biology published this year was edited
by Igor Berezovsky and Ruth Nussinov
[1]. The Issue contains a collection
of works, covering different aspects
of allostery on multiple scales, from
intramolecular regulation of protein
function to intercellular signalling.
Continuing our broad studies on fundamental and practical
aspects on allostery [2-6] we contributed to this Issue two original
works: (i) one considers the role of evolutionary conservatism and
diversity in establishing of allosteric communication in different
types of folds/domains and their multidomain/chain assemblies
[7]; (ii) another project explores features of allosteric ligands, sites,
and interactions with the aim to develop computational models
for allosteric drug design [8]. More specifically, in the first work
we learn directly from nature how various major folds provide
structural platforms for allosteric regulation of many enzymatic
and signalling functions. We obtained a picture of conserved
allosteric communication characteristic in different fold types,
including α/ß and ß-barrels, ß-propellers, Ig-like fold, ankyrin and
α/ß leucine-rich repeat proteins, modifications of the structuredriven
signalling patterns via sequence-determined divergence
to specific functions, as well as the emergence and potential
diversification of allosteric regulation in multi-domain proteins and
oligomeric assemblies. Our observations facilitate the engineering
and de novo design of proteins [9] with allosterically regulated
functions, including development of therapeutic biologics.
Figure 2. Archetypal patterns of allosteric communication and their potential alterations in different folds. Inner circle: Conserved patterns of allosteric communication characteristic for various major folds. Outer circle: Diversity of allosteric phenomena and potential for their engineering in different proteins and oligomeric assemblies.
The other contribution “Learning about allosteric drugs and ways to design them” [8] seeks to answer the precision medicine quest on individually targeting and selective drugs with the ability to target the so-called difficult or undruggable targets. We argue that prospected allosteric drugs possess several traits satisfying requirements of personalized therapies, including non-competitiveness, spatiotemporal specificity, as well as pathway and substrate specificity. Complemented by the modulatory rather than on/off mode of action with longlasting changes and ceiling effects, allosteric effectors allow to circumvent or at least to significantly alleviate off-target toxicity and drug resistance typical for traditional orthosteric medicines, also providing an opportunity to implement personalized, accurately tuned drug dosing. We propose a generic protocol for computational design of allosteric effectors, enabling also the allosteric tuning of biologics, in obtaining allosteric control over protein functions.
ALLOSTERY: PROGRESS IN OUTREACH AND PRACTICAL APPLICATIONS
We continue to work on our web-resources for the analysis of allostery, the AlloSigMA server [10] and the AlloMAPS database [11]. Recently, we released the AlloMAPS 2 - 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 from high-quality predicted structures in both databases for each organism/structure. We show that many lowquality AlphaFold predictions may require special treatments. For example, AlphaFold predictions of multi-chain and/or oligomeric proteins should be performed first for individual chains/protomers before assembly into the final structure. The fingerprints of Allosteric Signalling and Probing Maps (ASMs/ APMs) provided here for newly predicted high-quality structures allow to expand the analysis of allosteric communication from the effects of ligand binding and/or mutations to engineering and design of allosteric signalling in newly predicted structures, as well as to target them with newly developed allosteric effectors. Specifically, the ASM fingerprints can be instrumental in diagnostics of broad pathologies, helping to predict allosteric effects of single/multiple mutations, and analyzing their role in the expansion of cancer landscapes and involvements in other diseases. We also anticipate that the exhaustive character of allosteric signalling and probing fingerprints will be useful in future developments of corresponding machine learning applications.
Figure 3. The logogram of the dataset for predicted structures in the AlphaFold database.
BIOPHYSICS OF CHROMATIN AND EPIGENETIC REGULATION
We continue to develop a computational framework for reconstructing whole-genome chromatin ensemble from Hi-C data [12], and for exploring how structures and dynamics of chromatin drive genome expression. The current twostage protocol includes Markov state modelling (MSM) for reconstructing the structural hierarchy of chromatin organization with partitioning and effective interactions, and the stochastic embedding procedure (SEP) for obtaining the 3D ensemble reconstruction.
Figure 4. The flowchart of the computational framework for the analysis of chromatin hierarchy and the 3D whole-genome chromatin reconstruction.
Members
| Senior Principal Investigator | BEREZOVSKY Igor N. | [View Bio] |
| Senior Scientist II | SU Tran-to Chinh |
| Scientist | TEE Wei Ven |
| Scientist | DONG Bingxue |
| Research Officer | KRITHIKA Subramani |
| PhD Student | AMANGELDINA Aidana |
| Research Officer | Raechell |
Selected Publications
- Wodak, S.J., Paci, E., Dokholyan, N., Berezovsky, I.N., Horovitz, A., Li, J., Hilser, V.J., Bahar, I. et al. 2019. Allostery in its many disguises: from theory to applications.Structure 27, 566-578.
- Tee, W.V., Guarnera, E. & Berezovsky, I.N. 2020. Disorder driven allosteric control of protein activity. Curr. Res. Struct. Biol. 2, 191-203.
- Guarnera E, Berezovsky IN. (2019) Toward comprehensive allosteric control over protein activity. Structure 27, 866-878.
- Guarnera E, Berezovsky IN. (2019) On the perturbation nature of allostery: sites, mutations, and signal modulation. Curr. Opin. Struct. Biol. 56, 18-27.
- Ghode, A., Gross, L.Z.F., Tee, W.V., Guarnera, E., Berezovsky, I.N., Biondi, R.M. & Anand, G.S. 2020. Synergistic allostery in multiligand-protein interactions. Biophys. J. 119, 1833-1848.
- Guarnera E, Berezovsky IN. (2020) Allosteric drugs and mutations: chances, challenges, and necessity. Curr. Opin. Struct. Biol. 62, 149-157.
- Tee WV, Guarnera E, Berezovsky IN. (2019) On the allosteric effect of nsSNPs and the emerging importance of allosteric polymorphism. J. Mol. Biol 431, 3933-3942.
- Tee, W.V., Tan, Z.W., Lee, K., Guarnera, E. & Berezovsky, I.N. 2021. Exploring the allosteric territory of protein function. J Phys Chem B 125, 3763-3780.
- Tan, Z.W., Tee, W.V., Samsudin, F., Guarnera, E., Bond, P.J., & Berezovsky, I.N. 2022. Allosteric perspective on the mutability and druggability of the SARS-CoV-2 Spike protein. Structure 30, in press.
- Tan, Z.W., Guarnera, E., Tee, W.V. & Berezovsky, I.N. 2020. AlloSigMA 2: Paving the way to designing allosteric effectors and to exploring allosteric effects of mutations. Nucl. Acids. Res. 48, W116-W124.
- Tan ZW, Tee WV, Guarnera E, Booth L, Berezovsky IN. (2019) AlloMAPS: Allosteric mutation analysis and polymorphism of signaling database. Nucl. Acids. Res. 47, D265-D270.
- Berezovsky IN. (2019) Towards descriptor of elementary functions for protein design. Curr. Opin. Struct. Biol. 58, 159-165
- Yin, M., Goncearenco, A., & Berezovsky, I.N. 2021. Deriving and using descriptors of elementary functions in rational protein design. Frontiers in Bioinformatics 1, 657529.
- Guarnera, E., Tan, Z.W., & Berezovsky, I.N. 2021. Three-dimensional Chromatin Ensemble Reconstruction via Stochastic Embedding. Structure 29, 622-634.
Berezovsky Igor N.
 |
BEREZOVSKY Igor N. Senior Principal Investigator Email: igorb@bii.a-star.edu.sg Research Group: Physics and Evolution of Biological Macromolecules |
Igor Berezovsky studied physics at the Moscow Engineering Physics Institute (MSc, 1993) and obtained PhD in physics and mathematics from the Moscow Institute of Physics and Technology (1997). He started his scientific career at the Engelhardt Institute of Molecular Biology (Moscow) where he conducted his MSc and PhD research, then worked as a research fellow (until 1998). After postdoctoral researcher at the Weizmann Institute of Science (1999-2002) and the Harvard University (2003-2006), Igor was a senior scientist/group leader at the Bergen Center for Computational Science, University of Bergen (Norway) before joining the Bioinformatics Institute in January 2014.
Group Members
| Senior Scientist II | SU Tran-to Chinh |
| Scientist | TEE Wei Ven |
| Scientist | DONG Bingxue |
| Research Officer | KRITHIKA Subramani |
| Research Officer | Raechell |
| PhD Student | AMANGELDINA Aidana |
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