Tumor-derived RHOA mutants interact with effectors in the GDP-bound state.

RHOA mutations are found at diverse residues in various cancer types, implying mutation- and cell-specific mechanisms of tumorigenesis. Here, we focus on the underlying mechanisms of two gain-of-function RHOA mutations, A161P and A161V, identified in adult T-cell leukemia/lymphoma. We find that RHOAA161P and RHOAA161V are both fast-cycling mutants with increased guanine nucleotide dissociation/association rates compared with RHOAWT and show reduced GTP-hydrolysis activity. Crystal structures reveal an altered nucleotide association in RHOAA161P and an open nucleotide pocket in RHOAA161V. Both mutations perturb the dynamic properties of RHOA switch regions and shift the conformational landscape important for RHOA activity, as shown by 31P NMR and molecular dynamics simulations. Interestingly, RHOAA161P and RHOAA161V can interact with effectors in the GDP-bound state. 1H-15N HSQC NMR spectra support the existence of an active population in RHOAA161V-GDP. The distinct interaction mechanisms resulting from the mutations likely favor an RHOAWT-like "ON" conformation, endowing GDP-bound state effector binding activity.

Dysbiosis in pregnant mice induced by transfer of human vaginal microbiota followed by reversal of pathological changes in the uterus and placenta via progesterone treatment.

OBJECTIVE: The vaginal microbiota dysbiosis induces inflammation in the uterus that triggers tissue damage and is associated with preterm birth. Progesterone is used to prevent labor in pregnant women at risk of preterm birth. However, the mechanism of action of progesterone still needs to be clarified. We aimed to show the immunomodulatory effect of progesterone on the inflammation of uterine tissue triggered by dysbiotic vaginal microbiota in a pregnant mouse model. METHODS: Healthy (n = 6) and dysbiotic (n = 7) vaginal microbiota samples isolated from pregnant women were transferred to control (n = 10) and dysbiotic (n = 14) pregnant mouse groups. The dysbiotic microbiota transferred group was treated with 1 mg progesterone (n = 7). Flow cytometry and immunohistochemistry analyses were used to evaluate inflammatory processes. Vaginal microbiota samples were analyzed by 16 S rRNA sequencing. RESULTS: Vaginal exposure to dysbiotic microbiota resulted in macrophage accumulation in the uterus and cellular damage in the placenta. Even though TNF and IL-6 elevations were not significant after dysbiotic microbiota transplantation, progesterone treatment decreased TNF and IL-6 expressions from 49.085 to 31.274% (p = 0.0313) and 29.279-21.216% (p = 0.0167), respectively. Besides, the macrophage density in the uterus was reduced, and less cellular damage in the placenta was observed. CONCLUSION: Analyzing the vaginal microbiota before or during pregnancy may support the decision for initiation of progesterone therapy. Our results also guide the development of new strategies for preventing preterm birth.

Conformational diversity and protein-protein interfaces in drug repurposing in Ras signaling pathway.

We focus on drug repurposing in the Ras signaling pathway, considering structural similarities of protein-protein interfaces. The interfaces formed by physically interacting proteins are found from PDB if available and via PRISM (PRotein Interaction by Structural Matching) otherwise. The structural coverage of these interactions has been increased from 21 to 92% using PRISM. Multiple conformations of each protein are used to include protein dynamics and diversity. Next, we find FDA-approved drugs bound to structurally similar protein-protein interfaces. The results suggest that HIV protease inhibitors tipranavir, indinavir, and saquinavir may bind to EGFR and ERBB3/HER3 interface. Tipranavir and indinavir may also bind to EGFR and ERBB2/HER2 interface. Additionally, a drug used in Alzheimer's disease can bind to RAF1 and BRAF interface. Hence, we propose a methodology to find drugs to be potentially used for cancer using a dataset of structurally similar protein-protein interface clusters rather than pockets in a systematic way.

A Genome-Wide Functional Screen Identifies Enhancer and Protective Genes for Amyloid Beta-Peptide Toxicity.

Alzheimer's disease (AD) is known to be caused by amyloid ß-peptide (Aß) misfolded into ß-sheets, but this knowledge has not yet led to treatments to prevent AD. To identify novel molecular players in Aß toxicity, we carried out a genome-wide screen in Saccharomyces cerevisiae, using a library of 5154 gene knock-out strains expressing Aß1-42. We identified 81 mammalian orthologue genes that enhance Aß1-42 toxicity, while 157 were protective. Next, we performed interactome and text-mining studies to increase the number of genes and to identify the main cellular functions affected by Aß oligomers (oAß). We found that the most affected cellular functions were calcium regulation, protein translation and mitochondrial activity. We focused on SURF4, a protein that regulates the store-operated calcium channel (SOCE). An in vitro analysis using human neuroblastoma cells showed that SURF4 silencing induced higher intracellular calcium levels, while its overexpression decreased calcium entry. Furthermore, SURF4 silencing produced a significant reduction in cell death when cells were challenged with oAß1-42, whereas SURF4 overexpression induced Aß1-42 cytotoxicity. In summary, we identified new enhancer and protective activities for Aß toxicity and showed that SURF4 contributes to oAß1-42 neurotoxicity by decreasing SOCE activity.

Interactome analysis of Bag-1 isoforms reveals novel interaction partners in endoplasmic reticulum-associated degradation.

Bag-1 is a multifunctional protein that regulates Hsp70 chaperone activity, apoptosis, and proliferation. The three major Bag-1 isoforms have different subcellular localizations and partly non-overlapping functions. To identify the detailed interaction network of each isoform, we utilized mass spectrometry-based proteomics and found that interactomes of Bag-1 isoforms contained many common proteins, with variations in their abundances. Bag-1 interactomes were enriched with proteins involved in protein processing and degradation pathways. Novel interaction partners included VCP/p97; a transitional ER ATPase, Rad23B; a shuttling factor for ubiquitinated proteins, proteasome components, and ER-resident proteins, suggesting a role for Bag-1 also in ER-associated protein degradation (ERAD). Bag-1 pull-down from cells and tissues from breast cancer patients validated these interactions and showed cancer-related prominence. Using in silico predictions we detected hotspot residues of Bag-1. Mutations of these residues caused loss of binding to protein quality control elements and impaired proteasomal activity in MCF-7 cells. Following CD147 glycosylation pattern, we showed that Bag-1 downregulated VCP/p97-dependent ERAD. Overall, our data extends the interaction map of Bag-1, and broadens its role in protein homeostasis. Targeting the interaction surfaces revealed in this study might be an effective strategy in the treatment of cancer.

Normal Mode Analysis of KRas4B Reveals Partner Specific Dynamics.

Ras GTPase interacts with its regulators and downstream effectors for its critical function in cellular signaling. Targeting the disrupted mechanisms in Ras-related human cancers requires understanding the distinct dynamics of these protein-protein interactions. We performed normal mode analysis (NMA) of KRas4B in wild-type or mutant monomeric and neurofibromin-1 (NF1), Son of Sevenless 1 (SOS1) or Raf-1 bound dimeric conformational states to reveal partner-specific dynamics of the protein. Gaussian network model (GNM) analysis showed that the known KRas4B lobes further partition into subdomains upon binding to its partners. Furthermore, KRas4B interactions with different partners suppress the flexibility in not only their binding sites but also distant residues in the allosteric lobe in a partner-specific way. The conformational changes can be driven by intrinsic residue fluctuations of the open state KRas4B-GDP, as we illustrated with anisotropic network model (ANM) analysis. The allosteric paths connecting the nucleotide binding residues to the allosteric site at α3-L7 portray differences in the inactive and active states. These findings help in understanding the partner-specific KRas4B dynamics, which could be utilized for therapeutic targeting.

Mechanistic Differences of Activation of Rac1P29S and Rac1A159V.

Rac1 is a small GTPase that plays key roles in actin reorganization, cell motility, and cell survival/growth as well as in various cancer types and neurodegenerative diseases. Similar to other Ras superfamily GTPases, Rac1 switches between active GTP-bound and inactive GDP-bound states. Switch I and II regions open and close during GDP/GTP exchange. P29S and A159V (paralogous to K-RasA146) mutations are the two most common somatic mutations of Rac1. Rac1P29S is a known hotspot for melanoma, whereas Rac1A159V most commonly occurs in head and neck cancer. To investigate how these substitutions induce the Rac1 dynamics, we used atomistic molecular dynamics simulations on the wild-type Rac1 and two mutant systems (P29S and A159V) in the GTP bound state, and on the wild-type Rac1 and P29S mutated system in the GDP bound state. Here, we show that P29S and A159V mutations activate Rac1 with different mechanisms. In Rac1P29S-GTP, the substitution increases the flexibility of Switch I based on RMSF and dihedral angle calculations and leads to an open conformation. We propose that the open Switch I conformation is one of the underlying reasons for rapid GDP/GTP exchange of Rac1P29S. On the other hand, in Rac1A159V-GTP, some of the contacts of the guanosine ring of GTP with Rac1 are temporarily lost, enabling the guanosine ring to move toward Switch I and subsequently close the switch. Rac1A159V-GTP adopts a Ras state 2 like conformation, where both switch regions are in closed conformation and Thr35 forms a hydrogen bond with the nucleotide.

The structural basis of Akt PH domain interaction with calmodulin.

Akt plays a key role in the Ras/PI3K/Akt/mTOR signaling pathway. In breast cancer, Akt translocation to the plasma membrane is enabled by the interaction of its pleckstrin homology domain (PHD) with calmodulin (CaM). At the membrane, the conformational change promoted by PIP3 releases CaM and facilitates Thr308 and Ser473 phosphorylation and activation. Here, using modeling and molecular dynamics simulations, we aim to figure out how CaM interacts with Akt's PHD at the atomic level. Our simulations show that CaM-PHD interaction is thermodynamically stable and involves a ß-strand rather than an α-helix, in agreement with NMR data, and that electrostatic and hydrophobic interactions are critical. The PHD interacts with CaM lobes; however, multiple modes are possible. IP4, the polar head of PIP3, weakens the CaM-PHD interaction, implicating the release mechanism at the plasma membrane. Recently, we unraveled the mechanism of PI3Kα activation at the atomistic level and the structural basis for Ras role in the activation. Here, our atomistic structural data clarify the mechanism of how CaM interacts, delivers, and releases Akt-the next node in the Ras/PI3K pathway-at the plasma membrane.

Inhibition of Nonfunctional Ras.

Intuitively, functional states should be targeted; not nonfunctional ones. So why could drugging the inactive K-Ras4BG12Cwork-but drugging the inactive kinase will likely not? The reason is the distinct oncogenic mechanisms. Kinase driver mutations work by stabilizing the active state and/or destabilizing the inactive state. Either way, oncogenic kinases are mostly in the active state. Ras driver mutations work by quelling its deactivation mechanisms, GTP hydrolysis, and nucleotide exchange. Covalent inhibitors that bind to the inactive GDP-bound K-Ras4BG12C conformation can thus work. By contrast, in kinases, allosteric inhibitors work by altering the active-site conformation to favor orthosteric drugs. From the translational standpoint this distinction is vital: it expedites effective pharmaceutical development and extends the drug classification based on the mechanism of action. Collectively, here we postulate that drug action relates to blocking the mechanism of activation, not to whether the protein is in the active or inactive state.

Identification of potential inhibitors of human methionine aminopeptidase (type II) for cancer therapy: Structure-based virtual screening, ADMET prediction and molecular dynamics studies.

Methionine Aminopeptidases MetAPs are divalent-cofactor dependent enzymes that are responsible for the cleavage of the initiator Methionine from the nascent polypeptides. MetAPs are classified into two isoforms: namely, MetAP1 and MetAP2. Several studies have revealed that MetAP2 is upregulated in various cancers, and its inhibition has shown to suppress abnormal or excessive blood vessel formation and tumor growth in model organisms. Clinical studies show that the natural product fumagillin, and its analogs are potential inhibitors of MetAP2. However, due to their poor pharmacokinetic properties and neurotoxicities in clinical studies, their further developments have received a great setback. Here, we apply structure-based virtual screening and molecular dynamics methods to identify a new class of potential inhibitors for MetAP2. We screened Otava's Chemical Library, which consists of about 3 200 000 tangible-chemical compounds, and meticulously selected the top 10 of these compounds based on their inhibitory potentials against MetAP2. The top hit compounds subjected to ADMET predictor using 3 independent ADMET prediction programs, were found to be drug-like. To examine the stability of ligand binding mode, and efficacy, the unbound form of MetAP2, its complexes with fumagillin, spiroepoxytriazole, and the best promising compounds compound-3369841 and compound-3368818 were submitted to 100 ns molecular dynamics simulation. Like fumagillin, spiroepoxytriazole, and both compound-3369841 and compound-3368818 showed stable binding mode over time during the simulations. Taken together, these uninherited-fumagillin compounds may serve as new class of inhibitors or provide scaffolds for further optimization towards the design of more potent MetAP2 inhibitors -development of such inhibitors would be essential strategy against various cancer types.

Androgen receptor-binding sites are highly mutated in prostate cancer.

Androgen receptor (AR) signalling is essential in nearly all prostate cancers. Any alterations to AR-mediated transcription can have a profound effect on carcinogenesis and tumor growth. While mutations of the AR protein have been extensively studied, little is known about those somatic mutations that occur at the non-coding regions where AR binds DNA. Using clinical whole genome sequencing, we show that AR binding sites have a dramatically increased rate of mutations that is greater than any other transcription factor and specific to only prostate cancer. Demonstrating this may be common to lineage-specific transcription factors, estrogen receptor binding sites were also found to have elevated rate of mutations in breast cancer. We provide evidence that these mutations at AR binding sites, and likely other related transcription factors, are caused by faulty repair of abasic sites. Overall, this work demonstrates that non-coding AR binding sites are frequently mutated in prostate cancer and can impact enhancer activity.

Oncogenic K-Ras4B Dimerization Enhances Downstream Mitogen-activated Protein Kinase Signaling.

Ras recruits and activates effectors that transmit receptor-initiated signals. Monomeric Ras can bind Raf; however, Raf's activation requires dimerization, which can be facilitated by Ras dimerization. Previously, we showed that active K-Ras4B dimerizes in silico and in vitro through two major interfaces: (i) ß-interface, mapped to Switch I and effector-binding regions, (ii) α-interface at the allosteric lobe. Here, we chose constitutively active K-Ras4B as our control and two double mutants (K101D and R102E; and R41E and K42D) in the α- and ß-interfaces. Two of the mutations are from The Cancer Genome Atlas (TCGA) and the Catalogue Of Somatic Mutations In Cancer (COSMIC) data sets. R41 and R102 are found in several adenocarcinomas in Ras isoforms. We performed site-directed mutagenesis, cellular localization experiments, and molecular dynamics (MD) simulations to assess the impact of the mutations on K-Ras4B dimerization and function. α-interface K101D/R102E double mutations reduced dimerization but only slightly reduced downstream phosphorylated extracellular signal-regulated kinase (ERK) (pERK) levels. While ß-interface R41E/K42D double mutations did not interfere with dimerization, they almost completely blocked K-Ras4B-mediated ERK phosphorylation. Both double mutations increased downstream phosphorylated Akt (pAkt) levels in cells. Changes in pERK and pAkt levels altered ERK- and Akt-regulated gene expressions, such as EGR1, JUN, and BCL2L11. These results underscore the role of the α-interface in K-Ras4B homodimerization and the ß-surface in effector binding. MD simulations highlight that the membrane and hypervariable region (HVR) interact with both α- and ß-interfaces of K-Ras4B mutants, respectively, inhibiting homodimerization and probably effector binding. Mutations at both interfaces interfered with mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase signaling but in different forms and extents. We conclude that dimerization is not necessary but enhances downstream MAPK signaling.

Examining the stability of binding modes of the co-crystallized inhibitors of human HDAC8 by molecular dynamics simulation.

Histone deacetylase (HDAC) 8 has been implicated as a potential therapeutic target in a variety of cancers, neurodegenerative disorders, metabolic dysregulation and autoimmune and inflammatory diseases. Several nonselective HDAC inhibitors have been co-crystallized with HDAC8. Molecular dynamics (MD) studies may yield valuable information on the structural stabilities of the complexes over time as determined by various pharmacophore features of the co-crystallized inhibitors. Here, using 11 unmodified X-ray crystal structures of human HDAC8 (complexes) structure-based pharmacophore models were built and clustered based on distance - a function of the number of common pharmacophore features and the root-mean-squared displacement between the matching features. Based on this information, a total of seven complexes (1T64, 1W22, 3RQD, 3SFF, 3F0R, 5VI6 and 5FCW) were submitted to unrestrained 50 ns-MD simulations using nanoscale MD (NAMD) software. 1T64 (HDAC8 in complex with TSA) was found to show the highest stability over time, presumably because of the TSA's ability to span HDAC8 catalytic channel and form a strong ionic interaction with zinc metal ion. Other stable complexes were 1W22, 3SFF, 3F0R and 5FCW. However, 3RQD and 5VI6 showed relative instability over 50 ns time period. This may be attributed to bulkiness of the capping groups of both largazole thiol and trapoxin A, making them unable to fit well into the active site of HDAC8. They rather formed steric clashes with residues on loop regions near the entrance to the channel. Thus, 1T64 and similar crystal structures may be good candidates for HDAC8 structural dynamics studies and inhibitor design.Communicated by Ramaswamy H. Sarma.

Head and Neck Cancers Promote an Inflammatory Transcriptome through Coactivation of Classic and Alternative NF-κB Pathways.

Head and neck squamous cell carcinomas (HNSCC) promote inflammation in the tumor microenvironment through aberrant NF-κB activation, but the genomic alterations and pathway networks that modulate NF-κB signaling have not been fully dissected. Here, we analyzed genome and transcriptome alterations of 279 HNSCC specimens from The Cancer Genome Atlas (TCGA) cohort and identified 61 genes involved in NF-κB and inflammatory pathways. The top 30 altered genes were distributed across 96% of HNSCC samples, and their expression was often correlated with genomic copy-number alterations (CNA). Ten of the amplified genes were associated with human papilloma virus (HPV) status. We sequenced 15 HPV- and 11 HPV+ human HNSCC cell lines, and three oral mucosa keratinocyte lines, and supervised clustering revealed that 28 of 61 genes exhibit altered expression patterns concordant with HNSCC tissues and distinct signatures related to their HPV status. RNAi screening using an NF-κB reporter line identified 16 genes that are induced by TNFα or Lymphotoxin-ß (LTß) and implicated in the classic and/or alternative NF-κB pathways. Knockdown of TNFR, LTBR, or selected downstream signaling components established cross-talk between the classic and alternative NF-κB pathways. TNFα and LTß induced differential gene expression involving the NF-κB, IFNγ, and STAT pathways, inflammatory cytokines, and metastasis-related genes. Improved survival was observed in HNSCC patients with elevated gene expression in T-cell activation, immune checkpoints, and IFNγ and STAT pathways. These gene signatures of NF-κB activation, which modulate inflammation and responses to the immune therapy, could serve as potential biomarkers in future clinical trials.

3D spatial organization and network-guided comparison of mutation profiles in Glioblastoma reveals similarities across patients.

Glioblastoma multiforme (GBM) is the most aggressive type of brain tumor. Molecular heterogeneity is a hallmark of GBM tumors that is a barrier in developing treatment strategies. In this study, we used the nonsynonymous mutations of GBM tumors deposited in The Cancer Genome Atlas (TCGA) and applied a systems level approach based on biophysical characteristics of mutations and their organization in patient-specific subnetworks to reduce inter-patient heterogeneity and to gain potential clinically relevant insights. Approximately 10% of the mutations are located in "patches" which are defined as the set of residues spatially in close proximity that are mutated across multiple patients. Grouping mutations as 3D patches reduces the heterogeneity across patients. There are multiple patches that are relatively small in oncogenes, whereas there are a small number of very large patches in tumor suppressors. Additionally, different patches in the same protein are often located at different domains that can mediate different functions. We stratified the patients into five groups based on their potentially affected pathways that are revealed from the patient-specific subnetworks. These subnetworks were constructed by integrating mutation profiles of the patients with the interactome data. Network-guided clustering showed significant association between the groups and patient survival (P-value = 0.0408). Also, each group carries a set of signature 3D mutation patches that affect predominant pathways. We integrated drug sensitivity data of GBM cell lines with the mutation patches and the patient groups to analyze the possible therapeutic outcome of these patches. We found that Pazopanib might be effective in Group 3 by targeting CSF1R. Additionally, inhibiting ATM that is a mediator of PTEN phosphorylation may be ineffective in Group 2. We believe that from mutations to networks and eventually to clinical and therapeutic data, this study provides a novel perspective in the network-guided precision medicine.

Cryptochrome deletion in p53 mutant mice enhances apoptotic and anti-tumorigenic responses to UV damage at the transcriptome level.

Previous studies have demonstrated that deletion of cryptochrome (Cry) genes protects p53-/- mutant mice from the early onset of cancer and extends their median life-span by about 1.5-fold. Subsequent in vitro studies had revealed that deletion of Crys enhances apoptosis in response to UV damage through activation of p73 and inactivation of GSK3ß. However, it was not known at the transcriptome-wide level how deletion of Crys delays the onset of cancer in p53-/- mutant mice. In this study, the RNA-seq approach was taken to uncover the differentially expressed genes (DEGs) and pathways following UV-induced DNA damage in p53-/- and p53-/-Cry1-/-Cry2-/- mouse skin fibroblasts. Gene set enrichment analysis with the DEGs demonstrated enrichment in immune surveillance-associated genes regulated by IFN-γ and genes involved in TNFα signaling via NF-κB. Furthermore, protein network analysis enabled identification of DEGs p21, Sirt1, and Jun as key players, along with their interacting partners. It was also observed that the DEGs contained a high ratio of non-coding transcripts. Collectively, the present study suggests new genes in NF-κB regulation and IFN-γ response, as well as non-coding RNAs, may contribute to delaying the onset of cancer in p53-/-Cry1-/-Cry2-/- mice and increasing the life-span of these animals compared to p53-/- mice.

Methods for Discovering and Targeting Druggable Protein-Protein Interfaces and Their Application to Repurposing.

Drug repurposing is a creative and resourceful approach to increase the number of therapies by exploiting available and approved drugs. However, identifying new protein targets for previously approved drugs is challenging. Although new strategies have been developed for drug repurposing, there is broad agreement that there is room for further improvements. In this chapter, we review protein-protein interaction (PPI) interface-targeting strategies for drug repurposing applications. We discuss certain features, such as hot spot residue and hot region prediction and their importance in drug repurposing, and illustrate common methods used in PPI networks to identify drug off-targets. We also collect available online resources for hot spot prediction, binding pocket identification, and interface clustering which are effective resources in polypharmacology. Finally, we provide case studies showing the significance of protein interfaces and hot spots in drug repurposing.

Arl2-Mediated Allosteric Release of Farnesylated KRas4B from Shuttling Factor PDEδ.

Proper localization of Ras proteins at the plasma membrane (PM) is crucial for their functions. To get to the PM, KRas4B and some other Ras family proteins bind to the PDEδ shuttling protein through their farnesylated hypervariable regions (HVRs). The docking of their farnesyl (and to a lesser extent geranylgeranyl) in the hydrophobic pocket of PDEδ's stabilizes the interaction. At the PM, guanosine 5'-triphosphate (GTP)-bound Arf-like protein 2 (Arl2) assists in the release of Ras from the PDEδ. However, exactly how is still unclear. Using all-atom molecular dynamics simulations, we unraveled the detailed mechanism of Arl2-mediated release of KRas4B, the most abundant oncogenic Ras isoform, from PDEδ. We simulated ternary Arl2-PDEδ-KRas4B HVR complexes and observed that Arl2 binding weakens the PDEδ-farnesylated HVR interaction. Our detailed analysis showed that allosteric changes (involving ß6 of PDEδ and additional PDEδ residues) compress the hydrophobic PDEδ pocket and push the HVR out. Mutating PDEδ residues that mediate allosteric changes in PDEδ terminates the release process. Mutant Ras proteins are enriched in human cancers, with currently no drugs in the clinics. This mechanistic account may inspire efforts to develop drugs suppressing oncogenic KRas4B release.

Unraveling the molecular mechanism of interactions of the Rho GTPases Cdc42 and Rac1 with the scaffolding protein IQGAP2.

IQ motif-containing GTPase-activating proteins (IQGAPs) are scaffolding proteins playing central roles in cell-cell adhesion, polarity, and motility. The Rho GTPases Cdc42 and Rac1, in their GTP-bound active forms, interact with all three human IQGAPs. The IQGAP-Cdc42 interaction promotes metastasis by enhancing actin polymerization. However, despite their high sequence identity, Cdc42 and Rac1 differ in their interactions with IQGAP. Two Cdc42 molecules can bind to the Ex-domain and the RasGAP site of the GTPase-activating protein (GAP)-related domain (GRD) of IQGAP and promote IQGAP dimerization. Only one Rac1 molecule might bind to the RasGAP site of GRD and may not facilitate the dimerization, and the exact mechanism of Cdc42 and Rac1 binding to IQGAP is unclear. Using all-atom molecular dynamics simulations, site-directed mutagenesis, and Western blotting, we unraveled the detailed mechanisms of Cdc42 and Rac1 interactions with IQGAP2. We observed that Cdc42 binding to the Ex-domain of GRD of IQGAP2 (GRD2) releases the Ex-domain at the C-terminal region of GRD2, facilitating IQGAP2 dimerization. Cdc42 binding to the Ex-domain promoted allosteric changes in the RasGAP site, providing a binding site for the second Cdc42 in the RasGAP site. Of note, the Cdc42 "insert loop" was important for the interaction of the first Cdc42 with the Ex-domain. By contrast, differences in Rac1 insert-loop sequence and structure precluded its interaction with the Ex-domain. Rac1 could bind only to the RasGAP site of apo-GRD2 and could not facilitate IQGAP2 dimerization. Our detailed mechanistic insights help decipher how Cdc42 can stimulate actin polymerization in metastasis.

Enriching Traditional Protein-protein Interaction Networks with Alternative Conformations of Proteins.

Traditional Protein-Protein Interaction (PPI) networks, which use a node and edge representation, lack some valuable information about the mechanistic details of biological processes. Mapping protein structures to these PPI networks not only provides structural details of each interaction but also helps us to find the mutual exclusive interactions. Yet it is not a comprehensive representation as it neglects the conformational changes of proteins which may lead to different interactions, functions, and downstream signalling. In this study, we proposed a new representation for structural PPI networks inspecting the alternative conformations of proteins. We performed a large-scale study by creating breast cancer metastasis network and equipped it with different conformers of proteins. Our results showed that although 88% of proteins in our network has at least two structures in Protein Data Bank (PDB), only 22% of them have alternative conformations and the remaining proteins have different regions saved in PDB. However, using even this small set of alternative conformations we observed a considerable increase in our protein docking predictions. Our protein-protein interaction predictions increased from 54% to 76% using the alternative conformations. We also showed the benefits of investigating structural data and alternative conformations of proteins through three case studies.