Decoding Cancer Variants of Unknown Significance for Helicase–Nuclease–RPA Complexes Orchestrating DNA Repair During Transcription and Replication

All tumors have DNA mutations, and a predictive understanding of those mutations could inform clinical treatments. However, 40% of the mutations are variants of unknown significance (VUS), with the challenge being to objectively predict whether a VUS is pathogenic and supports the tumor or whether it is benign. To objectively decode VUS, we mapped cancer sequence data and evolutionary trace (ET) scores onto crystallography and cryo-electron microscopy structures with variant impacts quantitated by evolutionary action (EA) measures. As tumors depend on helicases and nucleases to deal with transcription/replication stress, we targeted helicase–nuclease–RPA complexes: (1) XPB-XPD (within TFIIH), XPF-ERCC1, XPG, and RPA for transcription and nucleotide excision repair pathways and (2) BLM, EXO5, and RPA plus DNA2 for stalled replication fork restart. As validation, EA scoring predicts severe effects for most disease mutations, but disease mutants with low ET scores not only are likely destabilizing but also disrupt sophisticated allosteric mechanisms. For sites of disease mutations and VUS predicted to be severe, we found strong co-localization to ordered regions. Rare discrepancies highlighted the different survival requirements between disease and tumor mutations, as well as the value of examining proteins within complexes. In a genome-wide analysis of 33 cancer types, we found correlation between the number of mutations in each tumor and which pathways or functional processes in which the mutations occur, revealing different mutagenic routes to tumorigenesis. We also found upregulation of ancient genes including BLM, which supports a non-random and concerted cancer process: reversion to a unicellular, proliferation-uncontrolled, status by breaking multicellular constraints on cell division. Together, these genes and global analyses challenge the binary “driver” and “passenger” mutation paradigm, support a gradient impact as revealed by EA scoring from moderate to severe at a single gene level, and indicate reduced regulation as well as activity. The objective quantitative assessment of VUS scoring and gene overexpression in the context of functional interactions and pathways provides insights for biology, oncology, and precision medicine.

Novel dynamic residue network analysis approaches to study homodimeric allosteric modulation in SARS-CoV-2 Mpro and in its evolutionary mutations

The rational search for allosteric modulators and the allosteric mechanisms of these modulators in the presence of evolutionary mutations, including resistant ones, is a relatively unexplored field. Here, we established novel in silico approaches and applied to SARS-CoV-2 main protease (Mpro). First, we identified six potential allosteric modulators (SANC00302, SANC00303, SANC00467, SANC00468, SANC00469, SANC00630) from the South African Natural Compounds Database (SANCDB) bound to the allosteric pocket of Mpro that we determined in our previous work. We also checked the stability of these compounds against Mpro of laboratory strain HCoV-OC43 and identified differences due to residue changes between the two proteins. Next, we focused on understanding the allosteric effects of these modulators on each protomer of the reference Mpro protein, while incorporating the symmetry problem in the functional homodimer. In general, asymmetric behavior of multimeric proteins is not commonly considered in computational analysis. We introduced a novel combinatorial approach and dynamic residue network (DRN) analysis algorithms to examine patterns of change and conservation of critical nodes, according to five independent criteria of network centrality (betweenness centrality (BC), closeness centrality (CC), degree centrality (DC), eigencentrality (EC) and katz centrality (KC)). The relationships and effectiveness of each metric in characterizing allosteric behavior were also investigated. We observed highly conserved network hubs for each averaged DRN metric on the basis of their existence in both protomers in the absence and presence of all ligands, and we called them persistent hubs (residues 17, 111, 112 and 128 for averaged BC; 6, 7, 113, 114, 115, 124, 125, 126, 127 and 128 for averaged CC; 36, 91, 146, 150 and 206 for averaged DC; 7, 115 and 125 for EC; 36, 125 and 146 for KC). We also detected ligand specific signal changes some of which were in or around functional residues (i.e. chameleon switch PHE140). Using EC persistent hubs and ligand introduced hubs we identified a residue communication path between allosteric binding site and catalytic site. Finally, we examined the effects of the mutations on the behavior of the protein in the presence of selected potential allosteric modulators and investigated the ligand stability. The hit compounds showed various levels of stability in the presence of SARS-CoV-2 Mpro mutations, being most stable in A173V, N274D and R279C, and least stable in R60C, N151D V157I, C160S and A255V. SANC00468 was the most stable compound in the 43 mutant protein systems. We further used DRN metric analysis to define cold spots as being those regions that are least impacted, or not impacted, by mutations. One crucial outcome of this study was to show that EC centrality hubs form an allosteric communication path between the allosteric ligand binding site to the active site going through the interface residues of Domain I and II; and this path was either weakened or lost in the presence of some of the mutations. Overall, the results of this study revealed crucial aspects that need to be considered in drug discovery in COVID-19 specifically and in general for rational computational drug design purposes.

Allosteric modulation of LRRC8 channels by targeting their cytoplasmic domains

Members of the LRRC8 family form heteromeric assemblies, which function as volume-regulated anion channels. These modular proteins consist of a transmembrane pore and cytoplasmic leucine-rich repeat (LRR) domains. Despite their known molecular architecture, the mechanism of activation and the role of the LRR domains in this process has remained elusive. Here we address this question by generating synthetic nanobodies, termed sybodies, which target the LRR domain of the obligatory subunit LRRC8A. We use these binders to investigate their interaction with homomeric LRRC8A channels by cryo-electron microscopy and the consequent effect on channel activation by electrophysiology. The five identified sybodies either inhibit or enhance activity by binding to distinct epitopes of the LRR domain, thereby altering channel conformations. In combination, our work provides a set of specific modulators of LRRC8 proteins and reveals the role of their cytoplasmic domains as regulators of channel activity by allosteric mechanisms.

GluN2A and GluN2B NMDA receptors use distinct allosteric routes

Allostery represents a fundamental mechanism of biological regulation that involves long-range communication between distant protein sites. It also provides a powerful framework for novel therapeutics. NMDA receptors (NMDARs), glutamate-gated ionotropic receptors that play central roles in synapse maturation and plasticity, are prototypical allosteric machines harboring large extracellular N-terminal domains (NTDs) that provide allosteric control of key receptor properties with impact on cognition and behavior. It is commonly thought that GluN2A and GluN2B receptors, the two predominant NMDAR subtypes in the adult brain, share similar allosteric transitions. Here, combining functional and structural interrogation, we reveal that GluN2A and GluN2B receptors utilize different long-distance allosteric mechanisms involving distinct subunit-subunit interfaces and molecular rearrangements. NMDARs have thus evolved multiple levels of subunit-specific allosteric control over their transmembrane ion channel pore. Our results uncover an unsuspected diversity in NMDAR molecular mechanisms with important implications for receptor physiology and precision drug development.

Allosteric perspective on the mutability and druggability of the SARS-CoV-2 Spike protein

Recent developments in the SARS-CoV-2 pandemic point to its inevitable transformation into an endemic disease, urging both diagnostics of emerging variants of concern (VOCs) and design of the variant-specific drugs in addition to vaccine adjustments. Exploring the structure and dynamics of the SARS-CoV-2 Spike protein, we argue that the high mutability characteristic of RNA viruses coupled with the remarkable flexibility and dynamics of viral proteins result in a substantial involvement of allosteric mechanisms. While allosteric effects of mutations should be considered in predictions and diagnostics of new VOCs, allosteric drugs advantageously avoid escaping mutations via non-competitive inhibition originating from many alternative distal locations. The exhaustive allosteric signalling and probing maps provide a comprehensive picture of allostery in the Spike protein, making it possible to locate sites of potential mutations that could work as new VOCs 'drivers', and to determine binding patches that may be targeted by newly developed allosteric drugs.

Cryo-EM structures of inhibitory antibodies complexed with arginase 1 provide insight into mechanism of action

Human Arginase 1 (hArg1) is a metalloenzyme that catalyzes the hydrolysis of l-arginine to l-ornithine and urea, and modulates T-cell-mediated immune response. Arginase-targeted therapies have been pursued across several disease areas including immunology, oncology, nervous system dysfunction, and cardiovascular dysfunction and diseases. Currently, all published hArg1 inhibitors are small molecules usually less than 350 Da in size. Here we report the cryo-electron microscopy structures of potent and inhibitory anti-hArg antibodies bound to hArg1 which form distinct macromolecular complexes that are greater than 650 kDa. With local resolutions of 3.5 Å or better we unambiguously mapped epitopes and paratopes for all five antibodies and determined that the antibodies act through orthosteric and allosteric mechanisms. These hArg1:antibody complexes present an alternative mechanism to inhibit hArg1 activity and highlight the ability to utilize antibodies as probes in the discovery and development of peptide and small molecule inhibitors for enzymes in general.

Serotonin Heteroreceptor Complexes and Their Integration of Signals in Neurons and Astroglia—Relevance for Mental Diseases

The heteroreceptor complexes present a novel biological principle for signal integration. These complexes and their allosteric receptor–receptor interactions are bidirectional and novel targets for treatment of CNS diseases including mental diseases. The existence of D2R-5-HT2AR heterocomplexes can help explain the anti-schizophrenic effects of atypical antipsychotic drugs not only based on blockade of 5-HT2AR and of D2R in higher doses but also based on blocking the allosteric enhancement of D2R protomer signaling by 5-HT2AR protomer activation. This research opens a new understanding of the integration of DA and 5-HT signals released from DA and 5-HT nerve terminal networks. The biological principle of forming 5-HT and other heteroreceptor complexes in the brain also help understand the mechanism of action for especially the 5-HT hallucinogens, including putative positive effects of e.g., psilocybin and the indicated prosocial and anti-stress actions of MDMA (ecstasy). The GalR1-GalR2 heterodimer and the putative GalR1-GalR2-5-HT1 heteroreceptor complexes are targets for Galanin N-terminal fragment Gal (1–15), a major modulator of emotional networks in models of mental disease. GPCR-receptor tyrosine kinase (RTK) heteroreceptor complexes can operate through transactivation of FGFR1 via allosteric mechanisms and indirect interactions over GPCR intracellular pathways involving protein kinase Src which produces tyrosine phosphorylation of the RTK. The exciting discovery was made that several antidepressant drugs such as TCAs and SSRIs as well as the fast-acting antidepressant drug ketamine can directly bind to the TrkB receptor and provide a novel mechanism for their antidepressant actions. Understanding the role of astrocytes and their allosteric receptor–receptor interactions in modulating forebrain glutamate synapses with impact on dorsal raphe-forebrain serotonin neurons is also of high relevance for research on major depressive disorder.

Dimeric allostery mechanism of the plant circadian clock photoreceptor ZEITLUPE

In Arabidopsis thaliana, the Light-Oxygen-Voltage (LOV) domain containing protein ZEITLUPE (ZTL) integrates light quality, intensity, and duration into regulation of the circadian clock. Recent structural and biochemical studies of ZTL indicate that the protein diverges from other members of the LOV superfamily in its allosteric mechanism, and that the divergent allosteric mechanism hinges upon conservation of two signaling residues G46 and V48 that alter dynamic motions of a Gln residue implicated in signal transduction in all LOV proteins. Here, we delineate the allosteric mechanism of ZTL via an integrated computational approach that employs atomistic simulations of wild type and allosteric variants of ZTL in the functional dark and light states, together with Markov state and supervised machine learning classification models. This approach has unveiled key factors of the ZTL allosteric mechanisms, and identified specific interactions and residues implicated in functional allosteric changes. The final results reveal atomic level insights into allosteric mechanisms of ZTL function that operate via a non-trivial combination of population-shift and dynamics-driven allosteric pathways.