Physics and Evolution of Biological Macromolecules

BII - Physics and Evolution of Biological Macromolecules


Working at the interface between the physics and biology, we develop physical models and computational approaches for modelling structures of biomolecules and for predicting their functional characteristics. We verify our models and predictions in collaboration with experimentalists. We highlight here two major areas of research pursued in the group: (i) protein allostery; (ii) biophysics of chromatin and epigenetic regulation. Other research topics in the group include, but are not limited to, evolution of protein function, evolutionary-inspired design of protein function, and molecular mechanisms of adaptation.


Continuing our work on allostery [1], we explored allosteric mechanisms mediated by structural disorder [2] using our structure-based statistical mechanical model of allostery (SBSMMA, [3,4]). The first goal here was to learn how back and forth disorder-order transitions can work as perturbations causing allosteric signalling in different phenomenologies of the allosteric regulation, such as formation of the dimer interface in BirA, preorganization of the binding pocket in SrtA, blocking the active conformation of Rac1 by engineered extrinsic disorder. Then, considering a set of esterase homologues with different thermostability, we addressed a question of a generic strategy for disorder/order-based allosteric tuning of protein activity.

In collaboration with Professor Ganesh Anand (DBS/NUS, currently Pennsylvania State University), we studied allosteric signal propagation in cooperative, dual-liganded protein kinase PDK1 [5]. Analyzing combinatorial coupling effects of a cooperative ligand pair binding with the help of amide hydrogen-deuterium exchange mass spectrometry (HDXMS), we obtained a quantitative description (using SBSMMA) of the integration of allosteric signals at Lys111. We also observed and investigated bidirectional and synergistic allosteric propagation, which offers a specific strategy for combinatorial drug development.

Figure 1. Disorder-order transitions establish the allosteric control scale of protein activity. Introducing structural order and disorder at distal locations leads to the inducing and preventing of the conformational changes at protein functional sites, respectively.

Continuing the drug design theme, we reviewed an emerging field of allosteric medicines, considering major targets for prospected allosteric medicines, currently available allosteric compounds, and drug candidates at different stages of research and (pre)clinical trials [6]. We proposed the ways of implementing SBSMMA-based framework of comprehensive allosteric control of protein activity in pharmacological applications. Outstanding questions formulated and partially discussed in this work also include allosteric effects of mutations, which are widely involved in the action of SNPs [7] and latent cancer drivers. The allosteric effects of mutaitons can also be used in fine and specific tuning of biologics, providing great potential in diagnostics and therapy.

Aiming at as comprehensive as possible a picture of the involvement of allostery in modulating protein activity, we explored “the allosteric territory of protein function“ [8], demarcating it, describing possible scenarios of allosteric phenomenology, their major elements, and rules underlying the allosteric mechanisms.

In this work, we exemplified the diversity of allosteric regulation modes, showing their universality regardless of the protein type, structure, function, and interactions. To this end, we considered four human and viral proteins involved in two completely unrelated diseases of serious concerns, cancers and coronavirus disease (COVID-19): (i) the metabolic enzymes isocitrate dehydrogenase 1 (IDH1) and fumarate hydratase (FH) implicated in gliomas and hereditary leiomyomatosis and renal cell cancer (HLRCC); (ii) the viroporin 3a and RNA-dependent RNA polymerase (RdRp) from SARS-CoV-2. We propose a generic computational framework, which not only allows one to obtain a comprehensive allosteric control over proteins, but also provides an opportunity to approach the fragmentbased design of allosteric effectors and drug candidates.

An unfortunate emergence of the SARS-CoV-2 pandemic prompted us among many other researchers to explore molecular mechanisms and, in particular, the allosteric components of the virus’s mutability and potential for druggability [8,9]. From the perspective of allosteric regulation, both mutability and druggability, can be viewed as two sides of the same coin, anchored by the cornerstone of protein dynamics. On the ‘dark side’, the high mutability of viral proteins is a source of a myriad of mutations, some of them with the potential to modulate the structure and dynamics allosterically, leading to new variants of concern (VOCs). On the ‘bright side’, however, druggable allosteric sites can be targeted, and rescue mutations can neutralize the effect of the harmful ones. We provide here openly accessible on-line (links are in STAR* Methods in [9]) exhaustive allosteric signalling and probing maps with a comprehensive picture of allostery in the spike protein, making it possible to locate potential mutations that could work as new VOC ‘‘drivers’’ and to determine binding patches that can be considered as candidate targets for newly developed allosteric drugs. This work was done in a fruitful collaboration with Dr. Peter Bond’s group (BMAD/BII).



Figure 2. Charting the allosteric territory of protein function. The hypothetical energy landscape illustrates that allosteric effectors and mutations allow a protein (gray, N-native state) to adopt different conformational states separated by large energy barriers. Substrate, activator, inhibitor, and mutation are indicated as S, A, I, and M, respectively (Subscript 1 indicates a perturbation at the orthosteric (functional) site; 2,3- at allosteric sites).

We continue to develop our web-resources for the analysis of allostery. The AlloSigMA server was updated with a new option, Allosteric Probing Maps (APM), and with modified framework for fragment-based-like design of allosteric effectors [10]. The AlloMAPS database was complemented with Allosteric Signalling/Probing Maps (ASMs/APMs) for 6370 trRosettapredicted structures of PFAM domain [11]. In a future work, among projects on different aspects of allostery, we plan to work on incorporating the allosteric regulation in de novo design of protein function [12,13].

Figure 3. Two sides of the coin: mutability and druggability as a manifestation of the ‘‘dark’’ and ‘‘bright’’ sides of viral protein dynamics


We developed a comprehensive method for reconstructing the wholegenome chromatin ensemble from the Hi-C data [14]. The procedure starts from the Markov state modeling (MSM), delineating the structural hierarchy of chromatin organization with partitioning and effective interactions archetypal for corresponding levels of hierarchy. Then, an original stochastic embedding (SEP) developed in the group provides the 3D ensemble reconstruction, using effective interactions obtained by the MSM as the input. The structural ensemble of a genome obtained in the procedure allows one to model the functional and the cell-type variability in chromatin. The whole-genome reconstructions are exemplified here by the human B lymphoblastoid (GM12878) and lung fibroblast (IMR90) Hi-C data, which show distinctions in their morphologies and in the spatial arrangement of intermingling chromosomal territories. The stochastic embedding procedure developed for this reconstruction allows to obtain an ensemble of the whole-genome chromatin conformations, thus, paving the way to studies of chromatin dynamics, developmental changes, and conformational transitions taking place in normal cells, cell differentiation, and during potential pathological developments.


Figure 4. Reconstructions of the human B lymphoblastoid (GM12878) and lung fibroblast (IMR90) 3D whole-genome chromatin structures.


 Senior Principal Investigator BEREZOVSKY Igor N.   |    [View Bio]   
 Research Scientist TAN Zhen Wah 
 Research Scientist SU Tran-to Chinh 
 Post-Doctoral Research Fellow  TEE Wei Ven
 Research Officer LIM Sylvester 
 PhD Student AMANGELDINA Aidana
 Post-Doctoral Research Fellow DONG Bingxue

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.