Exploring allosteric communication in multiple states of the bacterial ribosome using residue network analysis

In Silico Identification of Putative Allosteric Pockets and Inhibitors for the KRASG13D-SOS1 Complex in Cancer Therapy

RAS mutations occur in about 30% of human cancers, leading to enhanced RAS signaling and tumor growth. KRAS is the most commonly mutated oncogene in human tumors, especially lung, pancreatic, and colorectal cancers. Direct targeting of KRAS is difficult due to its highly conserved sequence; but, its complex with the guanine nucleotide exchange factor Son of Sevenless (SOS) 1 promises an attractive target for inhibiting RAS-mediated signaling. Here, we first revealed putative allosteric binding sites of the SOS1, KRASG12C-SOS1 complex, and the ternary KRASG13D-SOS1 complex structures using two network-based models, the essential site scanning analysis and the residue interaction network model. The results enabled us to identify two new putative allosteric pockets for the ternary KRASG13D-SOS1 complex. These were then screened together with the known ligand binding site against the natural compounds in the InterBioScreen (IBS) database using the Glide software package developed by Schrödinger, Inc. The docking poses of seven hit compounds were assessed using 400 ns long molecular dynamics (MD) simulations with two independent replicas using Desmond, coupled with thermal MM-GBSA calculations for the estimation of the binding free energy values. The structural skeleton of the seven proposed compounds consists of different functional groups and heterocyclic rings that possess anti-cancer activity and exhibit persistent interactions with key residues in binding pockets throughout the MD simulations. STOCK1N-09823 was determined as the most promising hit that promoted the disruption of the interactions R73 (chain A)/N879 and R73 (chain A)/Y884, which are key for SOS1-mediated KRAS activation.

Exploring Druggable Binding Sites on the Class A GPCRs Using the Residue Interaction Network and Site Identification by Ligand Competitive Saturation

G protein-coupled receptors (GPCRs) play a central role in cellular signaling and are linked to many diseases. Accordingly, computational methods to explore potential allosteric sites for this class of proteins to facilitate the identification of potential modulators are needed. Importantly, the availability of rich structural data providing the locations of the orthosteric ligands and allosteric modulators targeting different GPCRs allows for the validation of approaches to identify new allosteric binding sites. Here, we validate the combination of two computational techniques, the residue interaction network (RIN) model and the site identification by ligand competitive saturation (SILCS) method, to predict putative allosteric binding sites of class A GPCRs. RIN analysis identifies hub residues that mediate allosteric signaling within a receptor and have a high capacity to alter receptor dynamics upon ligand binding. The known orthosteric (and allosteric) binding sites of 18 distinct class A GPCRs were successfully predicted by RIN through a dataset of 105 crystal structures (91 ligand-bound, 14 unbound) with up to 77.8% (76.9%) sensitivity, 92.5% (95.3%) specificity, 51.9% (50%) precision, and 86.2% (92.4%) accuracy based on the experimental and theoretical binding site data. Moreover, graph spectral analysis of the residue networks revealed that the proposed sites were located at the interfaces of highly interconnected residue clusters with a high ability to coordinate the functional dynamics. Then, we employed the SILCS-Hotspots method to assess the druggability of the novel sites predicted for 7 distinct class A GPCRs that are critical for a variety of diseases. While the known orthosteric and allosteric binding sites are successfully explored by our approach, numerous putative allosteric sites with the potential to bind drug-like molecules are proposed. The computational approach presented here promises to be a highly effective tool to predict putative allosteric sites of GPCRs to facilitate the design of effective modulators.

Identifying and Assessing Putative Allosteric Sites and Modulators for CXCR4 Predicted through Network Modeling and Site Identification by Ligand Competitive Saturation

The chemokine receptor CXCR4 is a critical target for the treatment of several cancer types and HIV-1 infections. While orthosteric and allosteric modulators have been developed targeting its extracellular or transmembrane regions, the intramembrane region of CXCR4 may also include allosteric binding sites suitable for the development of allosteric drugs. To investigate this, we apply the Gaussian Network Model (GNM) to the monomeric and dimeric forms of CXCR4 to identify residues essential for its local and global motions located in the hinge regions of the protein. Residue interaction network (RIN) analysis suggests hub residues that participate in allosteric communication throughout the receptor. Mutual residues from the network models reside in regions with a high capacity to alter receptor dynamics upon ligand binding. We then investigate the druggability of these potential allosteric regions using the site identification by ligand competitive saturation (SILCS) approach, revealing two putative allosteric sites on the monomer and three on the homodimer. Two screening campaigns with Glide and SILCS-Monte Carlo docking using FDA-approved drugs suggest 20 putative hit compounds including antifungal drugs, anticancer agents, HIV protease inhibitors, and antimalarial drugs. In vitro assays considering mAB 12G5 and CXCL12 demonstrate both positive and negative allosteric activities of these compounds, supporting our computational approach. However, in vivo functional assays based on the recruitment of β-arrestin to CXCR4 do not show significant agonism and antagonism at a single compound concentration. The present computational pipeline brings a new perspective to computer-aided drug design by combining conformational dynamics based on network analysis and cosolvent analysis based on the SILCS technology to identify putative allosteric binding sites using CXCR4 as a showcase.

Tunnel-like region observed as a potential allosteric site in Staphylococcus aureus Glyceraldehyde-3-phosphate dehydrogenase

Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) catalyzing the sixth step of glycolysis has been investigated for allosteric features that might be used as potential target for specific inhibition of Staphylococcus aureus (S.aureus). X-ray structure of bacterial enzyme for which a tunnel-like opening passing through the center previously proposed as an allosteric site has been subjected to six independent 500 ns long Molecular Dynamics simulations. Harmonic bond restraints were employed at key residues to underline the allosteric feature of this region. A noticeable reduction was observed in the mobility of NAD+ binding domains when restrictions were applied. Also, a substantial decrease in cross-correlations between distant Cα fluctuations was detected throughout the structure. Mutual information (MI) analysis revealed a similar decrease in the degree of correspondence in positional fluctuations in all directions everywhere in the receptor. MI between backbone and side-chain torsional variations changed its distribution profile and decreased considerably around the catalytic sites when restraints were employed. Principal component analysis clearly showed that the restrained state sampled a narrower range of conformations than apo state, especially in the first principal mode due to restriction in the conformational flexibility of NAD+ binding domain. Clustering the trajectory based on catalytic site residues displayed a smaller repertoire of conformations for restrained state compared to apo. Representative snapshots subjected to k-shortest pathway analysis revealed the impact of bond restraints on the allosteric communication which displayed distinct optimal and suboptimal pathways for two states, where observed frequencies of critical residues Gln51 and Val283 at the proposed site changed considerably.

Modeling the ribosome as a bipartite graph

Developing mathematical representations of biological systems that can allow predictions is a challenging and important research goal. It is demonstrated here how the ribosome, the nano-machine responsible for synthesizing all proteins necessary for cellular life, can be represented as a bipartite network. Ten ribosomal structures from Bacteria and six from Eukarya are explored. Ribosomal networks are found to exhibit unique properties despite variations in the nodes and edges of the different graphs. The ribosome is shown to exhibit very large topological redundancies, demonstrating mathematical resiliency. These results can potentially explain how it can function consistently despite changes in composition and connectivity. Furthermore, this representation can be used to analyze ribosome function within the large machinery of network theory, where the degrees of freedom are the possible interactions, and can be used to provide new insights for translation regulation and therapeutics.

Modeling of Electron Hole Transport within a Small Ribosomal Subunit

Abstract—

Synchronized operation of various parts of the ribosome during protein synthesis implies the presence of a coordinating pathway, however, this is still unknown. We have recently suggested that such a pathway can be based on charge transport along the transfer and ribosomal RNA molecules and localization of the charges in functionally important areas of the ribosome. In the current study, using density functional theory calculations, we show that charge carriers (electron holes) can efficiently migrate within the central element of the small ribosomal subunit—the h44 helix. Monte-Carlo modeling revealed that electron holes tend to localize in the functionally important areas of the h44 helix, near the decoding center and intersubunit bridges. On the basis of the results obtained, we suggest that charge transport and localization within the h44 helix could coordinate intersubunit ratcheting with other processes occurring during protein synthesis.

Exploring species-specific inhibitors with multiple target sites on S. aureus pyruvate kinase using a computational workflow

Experimental evidence indicated that bacterial pyruvate kinase of glycolysis can be evaluated as an alternative target to eliminate infections, while antibiotic resistance poses a global threat. Here, we use a computational workflow to reveal and investigate the potential allosteric sites of methicillin-resistant S. aureus PK, which can help in designing species-specific drugs to inhibit activity of this organism. Residue interaction networks point to a known allosteric site at the small C-C interface, a potential allosteric site near the small interface (site #1), and a second potential allosteric site at the large interface (site #2). 2 µs-long molecular dynamics (MD) simulations with AMBER16 generate different conformations of one narrow target site. Known and potential allosteric sites on the selected conformers are investigated using ensemble docking with AutoDock Vina and a library of 2447 FDA-approved drugs. We determine 18 hits, comprising ergot-alkaloids, anti-cancer-agents, antivirals, analgesics, cardiac glycosides, all with a high docking z-score for three sites. 5 selected compounds with high, average and low z-scores are subjected to 50 ns-long MD simulations for MM-GBSA calculations. ΔG_bind values up to -49.3 kcal/mol at the C-C interface, up to -32.7 kcal/mol at site #1, and up to -53.3 kcal/mol at site #2 support the docking calculations. We investigate mitapivat and TT-232 as reference compounds under clinical trial, targeting human PK isomers. We suggest 18 FDA-approved hits from the docking calculations and TT-232 as potential inhibitors with multiple target sites on S. aureus PK. This study also proposes pharmacophores models for de novo drug design.Communicated by Ramaswamy H. Sarma.

Potential allosteric sites captured in glycolytic enzymes via residue-based network models: Phosphofructokinase, glyceraldehyde-3-phosphate dehydrogenase and pyruvate kinase

Likelihood of new allosteric sites for glycolytic enzymes, phosphofructokinase (PFK), glyceraldehyde-3-phosphate dehydrogenase (GADPH) and pyruvate kinase (PK) was evaluated for bacterial, parasitic and human species. Allosteric effect of a ligand binding at a site was revealed on the basis of low-frequency normal modes via C_α-harmonic residue network model. In bacterial PFK, perturbation of the proposed allosteric site outperformed the known allosteric one, producing a high amount of stabilization or reduced dynamics, on all catalytic regions. Another proposed allosteric spot at the dimer interface in parasitic PFK exhibited major stabilization effect on catalytic regions. In parasitic GADPH, the most desired allosteric response was observed upon perturbation of its tunnel region which incorporated key residues for functional regulation. Proposed allosteric site in bacterial PK produced a satisfactory allosteric response on all catalytic regions, whereas in human and parasitic PKs, a partial inhibition was observed. Residue network model based solely on contact topology identified the 'hub residues' with high betweenness tracing plausible allosteric communication pathways between distant functional sites. For both bacterial PFK and PK, proposed sites accommodated hub residues twice as much as the known allosteric site. Tunnel region in parasitic GADPH with the strongest allosteric effect among species, incorporated the highest number of hub residues. These results clearly suggest a one-to-one correspondence between the degree of allosteric effect and the number of hub residues in that perturbation site, which increases the likelihood of its allosteric nature.

Repurposing of FDA-approved drugs against active site and potential allosteric drug-binding sites of COVID-19 main protease

The novel coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still has serious negative effects on health, social life, and economics. Recently, vaccines from various companies have been urgently approved to control SARS-CoV-2 infections. However, any specific antiviral drug has not been confirmed so far for regular treatment. An important target is the main protease (Mpro ), which plays a major role in replication of the virus. In this study, Gaussian and residue network models are employed to reveal two distinct potential allosteric sites on Mpro that can be evaluated as drug targets besides the active site. Then, Food and Drug Administration (FDA)-approved drugs are docked to three distinct sites with flexible docking using AutoDock Vina to identify potential drug candidates. Fourteen best molecule hits for the active site of Mpro are determined. Six of these also exhibit high docking scores for the potential allosteric regions. Full-atom molecular dynamics simulations with MM-GBSA method indicate that compounds docked to active and potential allosteric sites form stable interactions with high binding free energy (∆Gbind ) values. ∆Gbind values reach -52.06 kcal/mol for the active site, -51.08 kcal/mol for the potential allosteric site 1, and - 42.93 kcal/mol for the potential allosteric site 2. Energy decomposition calculations per residue elucidate key binding residues stabilizing the ligands that can further serve to design pharmacophores. This systematic and efficient computational analysis successfully determines ivermectine, diosmin, and selinexor currently subjected to clinical trials, and further proposes bromocriptine, elbasvir as Mpro inhibitor candidates to be evaluated against SARS-CoV-2 infections.

Walking around Ribosomal Small Subunit: A Possible "Tourist Map" for Electron Holes

Despite several decades of research, the physics underlying translation-protein synthesis at the ribosome-remains poorly studied. For instance, the mechanism coordinating various events occurring in distant parts of the ribosome is unknown. Very recently, we suggested that this allosteric mechanism could be based on the transport of electric charges (electron holes) along RNA molecules and localization of these charges in the functionally important areas; this assumption was justified using tRNA as an example. In this study, we turn to the ribosome and show computationally that holes can also efficiently migrate within the whole ribosomal small subunit (SSU). The potential sites of charge localization in SSU are revealed, and it is shown that most of them are located in the functionally important areas of the ribosome-intersubunit bridges, Fe₄S₄ cluster, and the pivot linking the SSU head to its body. As a result, we suppose that hole localization within the SSU can affect intersubunit rotation (ratcheting) and SSU head swiveling, in agreement with the scenario of electronic coordination of ribosome operation. We anticipate that our findings will improve the understanding of the translation process and advance molecular biology and medicine.

Organic nanoelectronics inside us: charge transport and localization in RNA could orchestrate ribosome operation

Translation - protein synthesis at the ribonucleic acid (RNA) based molecular machine, the ribosome, - proceeds in a similar manner in all life forms. However, despite several decades of research, the physics underlying this process remains enigmatic. Specifically, during translation, a ribosome undergoes large-scale conformational changes of its distant parts, and these motions are coordinated by an unknown mechanism. In this study, we suggest that such a mechanism could be related to charge (electron hole) transport along and between the RNA molecules, localization of these charges at certain sites and successive relaxation of the molecular geometry. Thus, we suppose that RNA-based molecular machines, e.g., the ribosome, could be electronically controlled, having "wires", "actuators", "a battery", and other "circuitry". Taking transfer RNA as an example, we justify the reasonability of our suggestion using ab initio and atomistic simulations. Specifically, very large hole transfer integrals between the nucleotides (up to above 100 meV) are observed so that the hole can migrate over nearly the whole tRNA molecule. Hole localization at several guanines located at functionally important sites (G27, G10, G34 and G63) is predicted, which is shown to induce geometry changes in these sites, their neighborhoods and even rather distant moieties. If our hypothesis is right, we anticipate that our findings will qualitatively advance the understanding of the key biological processes and could inspire novel approaches in medicine.

Network theory of the bacterial ribosome

In the past two decades, research into the biochemical, biophysical and structural properties of the ribosome have revealed many different steps of protein translation. Nevertheless, a complete understanding of how they lead to a rapid and accurate protein synthesis still remains a challenge. Here we consider a coarse network analysis in the bacterial ribosome formed by the connectivity between ribosomal (r) proteins and RNAs at different stages in the elongation cycle. The ribosomal networks are found to be dis-assortative and small world, implying that the structure allows for an efficient exchange of information between distant locations. An analysis of centrality shows that the second and fifth domains of 23S rRNA are the most important elements in all of the networks. Ribosomal protein hubs connect to much fewer nodes but are shown to provide important connectivity within the network (high closeness centrality). A modularity analysis reveals some of the different functional communities, indicating some known and some new possible communication pathways Our mathematical results confirm important communication pathways that have been discussed in previous research, thus verifying the use of this technique for representing the ribosome, and also reveal new insights into the collective function of ribosomal elements.