Physics and Evolution of Biological Macromolecules

Igor N. BEREZOVSKY
Principal Investigator

Enrico GUARNERA
Senior Research Scientist

TAN Zhen Wah
Senior Post Doc Research Fellow

YIN Melvin Chee Peng
Research Officer

TEE Wei Ven, AMANGELDINA Aidana
PhD Students

Igor N. BEREZOVSKY
Principal Investigator

GROUP MEMBERS:

Enrico GUARNERA
Senior Research Scientist

TAN Zhen Wah
Senior Post Doc Research Fellow

YIN Melvin Chee Peng
Research Officer

TEE Wei Ven, AMANGELDINA Aidana
PhD Students

Research

Beginning of the millennium coincidentally became the time of a great quality transition in the molecular and structural biology. The changes had started with an arrival of high-throughput data delivered by new sequencing methods, microarray technology, and advanced biophysical techniques, shifting experimental biology towards more quantitative realm of exact sciences. The ease and speed at which data are obtained nowadays requires researches not only to ad-hoc process wealth of information without invoking computational support, but also to learn how to challenge existing theoretical concepts and to modify old and develop new computational approaches.

Our group works at the interface between the physics and biology, exploring the structure and function of biological macromolecules and their complexes. We develop minimalistic physical models and computational approaches, use them for modelling and prediction, which are verified in collaboration with our experimental colleagues. The current areas of our research include, but not limited to:

Allostery in proteins and molecular machines

We developed structure-based statistical mechanical model of allostery [SBSMMA, PLoS Comp Biol 12, e1004678 (2016)], showed that reversibility of allosteric signalling allows one to predict latent allosteric sites and to induce and tune required allosteric response [PLoS Comp Biol 14, e1006228 (2018)], experimentally verified predictive power of the model by activating Insulin-Degrading Enzyme against the A substrate [Biochemistry 56, 228 (2017)]. We implemented SBSMMA in the AlloSigMA web-server, which provides an interactive framework for estimating the allosteric free energy as a result of the ligand binding, mutations, and their combinations [Bioinformatics 33, 3396, (2017)]. The AlloMAPS database contains data on allosteric signalling in 46 proteins with comprehensively annotated functional and allosteric sites, 1908 proteins and protein chains from PDBselect connection with low sequence identity, and 33 proteins with more than 50 pathological SNPs in each molecule [NAR 47, doi:10.1093/nar/gky1028 (2019)]. We widely discuss our views on allostery and future directions [Curr Opin Struct Biol 37, 1 (2016); Curr Opin Struct Biol 56, 18 (2019)], and we have a number of ongoing projects in this fascinating field of research.

Chromatin structure and epigenetic regulation

A new era in chromatin research started with the availability of Hi-C data and new experimental techniques driving improvements in data resolution enable us to achieve a deeper understanding of the chromatin structure and function, while calling, at the same time, for the development of more advanced analytical methods. We proposed a new computational method for exploring chromatin structural organization based on Markov State Modelling of Hi-C data, represented as an interaction network between genomic loci. A Markov process describes the random walk of a traveling probe in the corresponding energy landscape, mimicking the motion of a biomolecule involved in chromatin function. By studying the metastability of the associated Markov State Model upon annealing, the hierarchical structure of individual chromosomes is observed, and a corresponding set of structural partitions is identified at each level of hierarchy. The overall static picture of whole-genome interactions was also obtained, providing the foundation for chromatin structural reconstruction and for modelling the chromatin dynamics and for exploring the regulation of genome function.

Evolution and design of protein function

We learn from nature how fundamental rules of physics govern evolution of protein function, determining optimal sizes and shapes of basic units at all stages of protein evolution [Physical Biology 12, 045002 (2015)]. We showed that contemporary proteins are built from a limited number of elementary functional loops (EFLs), which form diversity of protein functions. Using the prototype of the phosphate-binding loop (P-loop) in computational protein design, we have generated simple proteins of 55 residues and experimentally verified their functionality – binding of a range of phosphate-containing ligands, RNA, and single-strand DNA [PNAS USA, doi:10.1037/pnas 1812400115 (2019)]. The nucleotide binding database NBDB [NAR 44, D301 (2015)],contains profiles for 249 EFLs that interact with 24 different nucleotide-containing ligands and biologically relevant cofactors/coenzymes, which can be used in future design efforts.

Molecular mechanism of adaptation to extreme environments

DNA, RNA, and proteins are major biological macromolecules that coevolve and adapt to environments as components of one highly interconnected system. We explore sequence/structure determinants of mechanisms of adaptation of these molecules, links between them, and results of their mutual evolution [NAR 42, 2879 (2015)]. We found that there is a fundamental tradeoff between the nucleotide and amino acid compositions, which is the unifying property of all prokaryotes regardless of the differences in their phylogenies, life styles, and extreme environments [Biol Direct 9, 29 (2014)]. The tradeoff is determined by the interplay between the genetic code, optimization of the codon entropy, and demands on the structure and stability of nucleic acids and proteins. It underlies mutational biases characteristic for genomes with different nucleotide and amino acid compositions, providing foundation for evolution and adaptation. Halophilic adaptation is our current project in this field.

  • SPACER: Server for Predicting Allosteric Communication and Effects of Regulation

    Server analyzes protein structure, finds potential functional/effector binding sites, and shows allosteric communication between the sites.

  • AlloSigMA: Allosteric Signaling and Mutation Analysis

    Server for exploring and quantifying the effects of allosteric ligand binding and mutations

  • AlloMAPS: Allosteric Mutation Analysis and Polymorphism of Signaling database

    The database provides data on the energetics of communication in proteins with well-documented allosteric regulation, allosteric signalling in PDBselect chains, and allosteric effects of mutations.

  • NBDB: Nucleotide Binding Data Base

    NBDB database provides profiles of Elementary Functional Loops (EFLs) involved in binding of nucleotide-containing ligands. Each EFL in form of a PSSM (position-specific scoring matrix) profile is complemented with the information on SCOP entities, structural representatives in the PDB, and interactions between EFLs residues and corresponding parts of ligands. A comprehensive set of 249 profiles covers interactions with 24 nucleotide-containing ligands, cofactors and vitamins. You can explore profile interactions with different ligands and their chemical moieties. It also allows to search for EFLs involved into binding of nucleotide-containing ligands given the protein sequence of interest.

Physics and Evolution of Biological Macromolecules Members

Dr. BEREZOVSKY Igor
Principal Investigator
 
  Biography Details
NameTitle
Dr. BEREZOVSKY IgorPrincipal Investigator
Dr. GUARNERA EnricoSenior Research Scientist
Dr. TAN Zhen WahSenior Post-Doctoral Research Fellow
Mr. YIN Chee Peng, MelvinResearch Officer
Mr. TEE Wei Ven PhD student
Ms. AMANGELDINA Aidana PhD student
No Publications PDF

Research

Beginning of the millennium coincidentally became the time of a great quality transition in the molecular and structural biology. The changes had started with an arrival of high-throughput data delivered by new sequencing methods, microarray technology, and advanced biophysical techniques, shifting experimental biology towards more quantitative realm of exact sciences. The ease and speed at which data are obtained nowadays requires researches not only to ad-hoc process wealth of information without invoking computational support, but also to learn how to challenge existing theoretical concepts and to modify old and develop new computational approaches.

Our group works at the interface between the physics and biology, exploring the structure and function of biological macromolecules and their complexes. We develop minimalistic physical models and computational approaches, use them for modelling and prediction, which are verified in collaboration with our experimental colleagues. The current areas of our research include, but not limited to:

Allostery in proteins and molecular machines

We developed structure-based statistical mechanical model of allostery [SBSMMA, PLoS Comp Biol 12, e1004678 (2016)], showed that reversibility of allosteric signalling allows one to predict latent allosteric sites and to induce and tune required allosteric response [PLoS Comp Biol 14, e1006228 (2018)], experimentally verified predictive power of the model by activating Insulin-Degrading Enzyme against the A substrate [Biochemistry 56, 228 (2017)]. We implemented SBSMMA in the AlloSigMA web-server, which provides an interactive framework for estimating the allosteric free energy as a result of the ligand binding, mutations, and their combinations [Bioinformatics 33, 3396, (2017)]. The AlloMAPS database contains data on allosteric signalling in 46 proteins with comprehensively annotated functional and allosteric sites, 1908 proteins and protein chains from PDBselect connection with low sequence identity, and 33 proteins with more than 50 pathological SNPs in each molecule [NAR 47, doi:10.1093/nar/gky1028 (2019)]. We widely discuss our views on allostery and future directions [Curr Opin Struct Biol 37, 1 (2016); Curr Opin Struct Biol 56, 18 (2019)], and we have a number of ongoing projects in this fascinating field of research.

Chromatin structure and epigenetic regulation

A new era in chromatin research started with the availability of Hi-C data and new experimental techniques driving improvements in data resolution enable us to achieve a deeper understanding of the chromatin structure and function, while calling, at the same time, for the development of more advanced analytical methods. We proposed a new computational method for exploring chromatin structural organization based on Markov State Modelling of Hi-C data, represented as an interaction network between genomic loci. A Markov process describes the random walk of a traveling probe in the corresponding energy landscape, mimicking the motion of a biomolecule involved in chromatin function. By studying the metastability of the associated Markov State Model upon annealing, the hierarchical structure of individual chromosomes is observed, and a corresponding set of structural partitions is identified at each level of hierarchy. The overall static picture of whole-genome interactions was also obtained, providing the foundation for chromatin structural reconstruction and for modelling the chromatin dynamics and for exploring the regulation of genome function.

Evolution and design of protein function

We learn from nature how fundamental rules of physics govern evolution of protein function, determining optimal sizes and shapes of basic units at all stages of protein evolution [Physical Biology 12, 045002 (2015)]. We showed that contemporary proteins are built from a limited number of elementary functional loops (EFLs), which form diversity of protein functions. Using the prototype of the phosphate-binding loop (P-loop) in computational protein design, we have generated simple proteins of 55 residues and experimentally verified their functionality – binding of a range of phosphate-containing ligands, RNA, and single-strand DNA [PNAS USA, doi:10.1037/pnas 1812400115 (2019)]. The nucleotide binding database NBDB [NAR 44, D301 (2015)],contains profiles for 249 EFLs that interact with 24 different nucleotide-containing ligands and biologically relevant cofactors/coenzymes, which can be used in future design efforts.

Molecular mechanism of adaptation to extreme environments

DNA, RNA, and proteins are major biological macromolecules that coevolve and adapt to environments as components of one highly interconnected system. We explore sequence/structure determinants of mechanisms of adaptation of these molecules, links between them, and results of their mutual evolution [NAR 42, 2879 (2015)]. We found that there is a fundamental tradeoff between the nucleotide and amino acid compositions, which is the unifying property of all prokaryotes regardless of the differences in their phylogenies, life styles, and extreme environments [Biol Direct 9, 29 (2014)]. The tradeoff is determined by the interplay between the genetic code, optimization of the codon entropy, and demands on the structure and stability of nucleic acids and proteins. It underlies mutational biases characteristic for genomes with different nucleotide and amino acid compositions, providing foundation for evolution and adaptation. Halophilic adaptation is our current project in this field.

  • SPACER: Server for Predicting Allosteric Communication and Effects of Regulation

    Server analyzes protein structure, finds potential functional/effector binding sites, and shows allosteric communication between the sites.

  • AlloSigMA: Allosteric Signaling and Mutation Analysis

    Server for exploring and quantifying the effects of allosteric ligand binding and mutations

  • AlloMAPS: Allosteric Mutation Analysis and Polymorphism of Signaling database

    The database provides data on the energetics of communication in proteins with well-documented allosteric regulation, allosteric signalling in PDBselect chains, and allosteric effects of mutations.

  • NBDB: Nucleotide Binding Data Base

    NBDB database provides profiles of Elementary Functional Loops (EFLs) involved in binding of nucleotide-containing ligands. Each EFL in form of a PSSM (position-specific scoring matrix) profile is complemented with the information on SCOP entities, structural representatives in the PDB, and interactions between EFLs residues and corresponding parts of ligands. A comprehensive set of 249 profiles covers interactions with 24 nucleotide-containing ligands, cofactors and vitamins. You can explore profile interactions with different ligands and their chemical moieties. It also allows to search for EFLs involved into binding of nucleotide-containing ligands given the protein sequence of interest.

Physics and Evolution of Biological Macromolecules Members

Dr. BEREZOVSKY Igor
Principal Investigator
 
  Biography Details
NameTitle
Dr. BEREZOVSKY IgorPrincipal Investigator
Dr. GUARNERA EnricoSenior Research Scientist
Dr. TAN Zhen WahSenior Post-Doctoral Research Fellow
Mr. YIN Chee Peng, MelvinResearch Officer
Mr. TEE Wei Ven PhD student
Ms. AMANGELDINA Aidana PhD student
No Publications PDF