MCPath: Monte Carlo path generation approach to predict likely allosteric pathways and functional residues

Kaya, Cihan; Armutlulu, Andaç; Ekesan, Şölen; Haliloğlu, Türkan

doi:10.1093/nar/gkt284

Cited by 66 publications

(64 citation statements)

References 37 publications

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“…During the last decade, advances in the understanding of allostery and widespread application of biophysical methods, such as X‐ray crystallography, solid‐state and relaxation dispersion nuclear magnetic resonance (NMR), H/D exchange mass spectrometry, high‐throughput screening (HTS), patch‐clamp fluorometry, and electrophysiology, together with computational approaches, such as molecular dynamics (MD) simulations and bioinformatics analysis, provide unprecedented opportunities to discover allosteric proteins as well as design and develop novel efficient therapeutic drugs targeted to allosteric sites. Therefore, the repertoire of allostery has been experiencing an upsurge, which is evidenced by an explosive growth in the number of allosteric proteins and allosteric modulators in recent years …”

Section: Introdctionmentioning

confidence: 99%

Harnessing Allostery: A Novel Approach to Drug Discovery

Zhang

2014

Medicinal Research Reviews

124

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Allostery is the most direct and efficient way for regulation of biological macromolecule function, ranging from the control of metabolic mechanisms to signal transduction pathways. Allosteric modulators target to allosteric sites, offering distinct advantages compared to orthosteric ligands that target to active sites, such as greater specificity, reduced side effects, and lower toxicity. Allosteric modulators have therefore drawn increasing attention as potential therapeutic drugs in the design and development of new drugs. In recent years, advancements in our understanding of the fundamental principles underlying allostery, coupled with the exploitation of powerful techniques and methods in the field of allostery, provide unprecedented opportunities to discover allosteric proteins, detect and characterize allosteric sites, design and develop novel efficient allosteric drugs, and recapitulate the universal features of allosteric proteins and allosteric modulators. In the present review, we summarize the recent advances in the repertoire of allostery, with a particular focus on the aforementioned allosteric compounds.

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Section: Introdctionmentioning

confidence: 99%

Harnessing Allostery: A Novel Approach to Drug Discovery

Zhang

2014

Medicinal Research Reviews

124

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“…Alternatively, specific approaches that can identify peptide binding sites include PepSite (Trabuco et al 2012), PeptiMap (Lavi et al 2013), and PEPSiteFinder (Saladin et al 2014). Lastly, difficulties in detecting allosteric sites can be alleviated by recently developed open-access web servers such as SPACER (Goncearenco et al 2013), MCPath (Kaya et al 2013), Allosite (Huang et al 2013), and PARS (Panjkovich and Daura 2014). A systematic assessment of a number of available web servers and stand-alone protein-ligand binding site prediction programs was published previously .…”

Section: Binding Site Prediction or Identificationmentioning

confidence: 99%

Role of computer-aided drug design in modern drug discovery

Macalino¹,

Gosu²,

Hong³

et al. 2015

Arch. Pharm. Res.

517

318

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Drug discovery utilizes chemical biology and computational drug design approaches for the efficient identification and optimization of lead compounds. Chemical biology is mostly involved in the elucidation of the biological function of a target and the mechanism of action of a chemical modulator. On the other hand, computer-aided drug design makes use of the structural knowledge of either the target (structure-based) or known ligands with bioactivity (ligand-based) to facilitate the determination of promising candidate drugs. Various virtual screening techniques are now being used by both pharmaceutical companies and academic research groups to reduce the cost and time required for the discovery of a potent drug. Despite the rapid advances in these methods, continuous improvements are critical for future drug discovery tools. Advantages presented by structure-based and ligand-based drug design suggest that their complementary use, as well as their integration with experimental routines, has a powerful impact on rational drug design. In this article, we give an overview of the current computational drug design and their application in integrated rational drug development to aid in the progress of drug discovery research.

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“…a protein's crystal structure. 45 None of these models, however, directly account for the ensemble nature of protein structure and the associated allosteric behavior. 11 All-atom molecular dynamics (aaMD) is a well-established method to sample the configurational ensemble of a protein.…”

Section: Introductionmentioning

confidence: 99%

Residue-Level Allostery Propagates Through the Effective Coarse-Grained Hessian

Lake

Davidson

Klem

et al. 2019

Preprint

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AbstractThe long-ranged coupling between residues that gives rise to allostery in a protein is built up from short-ranged physical interactions. Computational tools used to predict this coupling and its functional relevance have relied on the application of graph theoretical metrics to residue-level correlations measured from all-atom molecular dynamics (aaMD) simulations. The short-ranged interactions that yield these long-ranged residue-level correlations are quantified by the effective coarse-grained Hessian. Here we compute an effective harmonic coarse-grained Hessian from aaMD simulations of a benchmark allosteric protein, IGPS, and demonstrate the improved locality of this graph Laplacian over two other connectivity matrices. Additionally, two centrality metrics are developed that indicate the direct and indirect importance of each residue at producing the covariance between the effector binding pocket and the active site. The residue importance indicated by these two metrics is corroborated by previous mutagenesis experiments and leads to unique functional insights; in contrast to previous computational analyses, our results suggest that fP76-hK181 is the most important contact for conveying direct allosteric paths across the HisF-HisH interface. The connectivity around fD98 is found to be important at affecting allostery through indirect means.

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MCPath: Monte Carlo path generation approach to predict likely allosteric pathways and functional residues

Cited by 66 publications

References 37 publications

Harnessing Allostery: A Novel Approach to Drug Discovery

Harnessing Allostery: A Novel Approach to Drug Discovery

Role of computer-aided drug design in modern drug discovery

Residue-Level Allostery Propagates Through the Effective Coarse-Grained Hessian

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