Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning

Verkhivker, Gennady M.; Agajanian, Steve; Hu, Guang; Tao, Peng

doi:10.3389/fmolb.2020.00136

Cited by 60 publications

(46 citation statements)

References 355 publications

(463 reference statements)

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“…The goal of these studies ranges from understanding the fundamental biophysical principles to understanding more practical applications for drug design (Borhani and Shaw, 2012;de Vivo et al, 2016). Over the past decades, this topic has been extensively discussed in many excellent articles and reviews (Bagler and Sinha, 2005;Ghosh and Vishveshwara, 2007;Cui and Karplus, 2008;de Ruvo et al, 2012;Bhattacharyya et al, 2016;Astl et al, 2019;Zhang and Nussinov, 2019;Verkhivker et al, 2020;Zhang et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Network theory-based analyses of protein structure (Bagler and Sinha, 2005;Atilgan et al, 2012) and dynamics have provided unprecedented insights into the global structural connectivity of proteins and its complexes in the context of allostery and other biological processes (Atilgan et al, 2012;Di Paola et al, 2013;Bhattacharyya et al, 2016;Gadiyaram et al, 2019;Krieger et al, 2020;Verkhivker et al, 2020). When combined with information on conformational variations, as obtained from molecular dynamics, network approaches have elucidated several examples of protein structure-function relationships (Doruker et al, 2000;Sethi et al, 2009;Bhattacharyya et al, 2013;Papaleo, 2015;Tse and Verkhivker, 2015;Doshi et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…The methods range from direct analysis of the structures to ones developed based on the physical, mathematical, and engineering principles. Many such concepts are integrated together in computational programs to obtain critical biological insights (Greener and Sternberg, 2018;Verkhivker et al, 2020;Zhang et al, 2020). Network theory is a widely used approach which provides explicit information on the role of constituent amino acids on the stability of structure networks at a global level (Atilgan et al, 2010;Brown et al, 2017;Gadiyaram et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…A vast range of experimental and computational studies have taken up the challenge of correlating biological cellular functions to the molecular level changes. Understanding protein connectivity and dynamics can provide molecular mechanistic insights into the various biological processes, like allostery (Atilgan et al, 2007;Verkhivker et al, 2020;Wang et al, 2020a), protein-protein or protein-nucleic acid interactions Keskin et al, 2005;Sathyapriya et al, 2008;Sethi et al, 2009), and ligand/perturbation-induced conformational variations (Csermely et al, 2013;Bandaru et al, 2017;Creixell et al, 2018). Such calculations may also aid the identification of epitopes for drug-binding and capture drug-induced conformational changes in proteins and protein complexes (Csermely et al, 2013;Krieger et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…The focus of this review is to provide a brief account of the different network theory-based techniques targeted at (i) characterizing protein structures as a single entity connected by non-covalent interactions and (ii) integrating with conformational dynamics, for which several comprehensive reviews are available (Atilgan et al, 2012;Hu et al, 2017;Verkhivker et al, 2020). The main emphasis here is on the development and application of protein side-chain network approaches (Bhattacharyya et al, 2016;Salamanca Viloria et al, 2017;Kayikci et al, 2018), which have been shown to capture subtle conformational differences that are sometimes elusive to conventional analyses, such as the root mean square deviation (RMSD) at the backbone level.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Surveying the Side-Chain Network Approach to Protein Structure and Dynamics: The SARS-CoV-2 Spike Protein as an Illustrative Case

Halder

Anto

Subramanyan

et al. 2020

Front. Mol. Biosci.

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Network theory-based approaches provide valuable insights into the variations in global structural connectivity between different dynamical states of proteins. Our objective is to review network-based analyses to elucidate such variations, especially in the context of subtle conformational changes. We present technical details of the construction and analyses of protein structure networks, encompassing both the non-covalent connectivity and dynamics. We examine the selection of optimal criteria for connectivity based on the physical concept of percolation. We highlight the advantages of using side-chain-based network metrics in contrast to backbone measurements. As an illustrative example, we apply the described network approach to investigate the global conformational changes between the closed and partially open states of the SARS-CoV-2 spike protein. These conformational changes in the spike protein is crucial for coronavirus entry and fusion into human cells. Our analysis reveals global structural reorientations between the two states of the spike protein despite small changes between the two states at the backbone level. We also observe some differences at strategic locations in the structures, correlating with their functions, asserting the advantages of the side-chain network analysis. Finally, we present a view of allostery as a subtle synergistic-global change between the ligand and the receptor, the incorporation of which would enhance drug design strategies.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Surveying the Side-Chain Network Approach to Protein Structure and Dynamics: The SARS-CoV-2 Spike Protein as an Illustrative Case

Halder

Anto

Subramanyan

et al. 2020

Front. Mol. Biosci.

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Quantifying the Long‐Range Coupling of Electronic Properties in Proteins with ab initio Molecular Dynamics**

et al. 2021

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The delicate interplay of covalent and non-covalent interactions in proteins is inherently quantum mechanical and highly dynamic in nature. To directly interrogate the evolving nature of the electronic structure of proteins, we carry out 100-ps-scale ab initio molecular dynamics simulations of three representative small proteins with range-separated hybrid density functional theory. We quantify the nature and length-scale of the coupling of residue-specific charge probability distributions in these proteins. While some nonpolar residues exhibit expectedly narrow charge distributions, most polar and charged residues exhibit broad, multimodal distributions. Even for nonpolar residues, we observe sequence-specific deviations correspond-ing to charge accumulation or depletion that would be challenging to capture in a fixed charge force field. We quantify the effect of residue-residue interactions on charge distributions first with linear cross-correlations. We then show how additional insight can be gained from evaluating the mutual information of charge distributions. We show that a significant number of residues couple most strongly with residues that are distant in both sequence and space over a range of secondary structures including α-helical, β-sheet, disulfide bridging, and lasso motifs. The mutual information analysis is necessary to capture coupling between some polar and charged residues that would be otherwise missed.

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Chemical and Biophysical Approaches to Allosteric Modulation

Civera

Moroni²,

Sorrentino

et al. 2021

Eur J Org Chem

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Allosteric regulation, i. e. the control exerted on an orthosteric site by an effector interacting at a distinct and distant site, represents a prime example of a precise tuning system of several key biological processes like gene transcription, cell adhesion and, most importantly, signal transduction. Since its discovery sixty years ago, the molecular mechanisms underlying this phenomenon have been extensively investigated. The aim of this minireview is to introduce the reader to the topic of protein allostery. In particular, we briefly overview the allosteric models postulated over the years and we describe the most relevant chemical and biophysical approaches reported so far for the identification of putative allosteric sites and/or for the investigation of allosteric signal propagation throughout the protein. An outlook of the main computational and experimental methods is followed by four case studies representative of different proteins classes: enzymes, hub proteins, cell receptors, and intrinsically disordered proteins.

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Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning

Cited by 60 publications

References 355 publications

Surveying the Side-Chain Network Approach to Protein Structure and Dynamics: The SARS-CoV-2 Spike Protein as an Illustrative Case

Surveying the Side-Chain Network Approach to Protein Structure and Dynamics: The SARS-CoV-2 Spike Protein as an Illustrative Case

Quantifying the Long‐Range Coupling of Electronic Properties in Proteins with ab initio Molecular Dynamics**

Chemical and Biophysical Approaches to Allosteric Modulation

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