Synthesis and anticancer properties of novel dolastatin 10 analogs featuring five-membered heterocyclic rings with a linkable group at the C-terminus.

Dolastatin 10 (Dol-10), a natural marine-source pentapeptide, is a powerful antimitotic agent regarded as one of the most potent anticancer compounds found to date. Dol-10 however, lacks chemical conjugation capabilities, which restricts the feasibility of its application in targeted drug therapy. This limitation has spurred the prospect that chemical structure of the parent molecule might allow conjugation of the derivatives to drug carriers such as antibodies. By first employing docking studies, we designed and prepared a series of novel Dol-10 analogs with a modified C-terminus, preserving high potency of the parent compound while enhancing conjugation capability. The modifications involved the introduction of a methyleneamine functionality at position 4 of the 1,3-thiazole ring, along with the substitution of the thiazole ring with a 1,2,3-triazole moiety, furnished with methylenehydroxy, carboxy, methyleneamine, and N(Me)-methyleneamine tethering functionalities at position 4. Among the synthesized pentapeptides, DA-1 exhibited the highest potency in prostate cancer (PC-3) cells, eliciting apoptosis (IC50 0.2 ± 0.1 nm) and cell cycle arrest at the mitotic stage after at least 6 days of culture. This delayed response suggests the accumulation of cellular stress or significant physiological alterations that profoundly impact the cell cycle. We believe that these novel Dol-10 derivates represent a new and straightforward route for the development of C-terminus modified Dol-10-based microtubule inhibitors, thereby advancing targeted anticancer therapy.

Novel Cyclic Peptides for Targeting EGFR and EGRvIII Mutation for Drug Delivery.

The epidermal growth factor-epidermal growth factor receptor (EGF-EGFR) pathway has become the main focus of selective chemotherapeutic intervention. As a result, two classes of EGFR inhibitors have been clinically approved, namely monoclonal antibodies and small molecule kinase inhibitors. Despite an initial good response rate to these drugs, most patients develop drug resistance. Therefore, new treatment approaches are needed. In this work, we aimed to find a new EGFR-specific, short cyclic peptide, which could be used for targeted drug delivery. Phage display peptide technology and biopanning were applied to three EGFR expressing cells, including cells expressing the EGFRvIII mutation. DNA from the internalized phage was extracted and the peptide inserts were sequenced using next-generation sequencing (NGS). Eleven peptides were selected for further investigation using binding, internalization, and competition assays, and the results were confirmed by confocal microscopy and peptide docking. Among these eleven peptides, seven showed specific and selective binding and internalization into EGFR positive (EGFR+ve) cells, with two of them-P6 and P9-also demonstrating high specificity for non-small cell lung cancer (NSCLC) and glioblastoma cells, respectively. These peptides were chemically conjugated to camptothecin (CPT). The conjugates were more cytotoxic to EGFR+ve cells than free CPT. Our results describe a novel cyclic peptide, which can be used for targeted drug delivery to cells overexpressing the EGFR and EGFRvIII mutation.

Three-Dimensional Modeling of Thyroid Hormone Metabolites Binding to the Cancer-Relevant αvß3 Integrin: In-Silico Based Study.

Background: Thyroid hormones (TH), T4 and T3, mediate pro-mitogenic effects in cancer cells through binding the membrane receptor αvß3 integrin. The deaminated analogue tetrac effectively blocks TH binding to this receptor and prevents their action. While computational data on TH binding to the αvß3 integrin was published, a comprehensive analysis of additional TH metabolites is lacking. Methods: In-silico docking of 26 TH metabolites, including the biologically active thyroid hormones (T3 and T4) and an array of sulfated, deiodinated, deaminated or decarboxylated metabolites, to the αvß3 receptor binding pocket was performed using DOCK6, based on the three-dimensional representation of the crystallographic structure of the integrin. As the TH binding site upon the integrin is at close proximity to the well-defined RGD binding site, linear and cyclic RGD were included as a reference. Binding energy was calculated for each receptor-ligand complex using Grid score and Amber score with distance movable region protocol. Results: All TH molecules demonstrated negative free energy, suggesting affinity to the αvß3 integrin. Notably, based on both Grid and Amber scores sulfated forms of 3,3' T2 (3,3' T2S) and T4 (T4S) demonstrated the highest binding affinity to the integrin, compared to both cyclic RGD and an array of examined TH metabolites. The major thyroid hormones, T3 and T4, showed high affinity to the integrin, which was superior to that of linear RGD. For all hormone metabolites, decarboxylation led to decreased affinity. This corresponds with the observation that the carboxylic group mediates binding to the integrin pocket via divalent cations at the metal-ion-dependent adhesion (MIDAS) motif site. A similar reduced affinity was documented for deaminated forms of T3 (triac) and T4 (tetrac). Lastly, the reverse forms of T3, T3S, and T3AM showed higher Amber scores relative to their native form, indicating that iodination at position 5 is associated with increased binding affinity compared to position 5'. Summary: Three-dimensional docking of various TH metabolites uncovered a structural basis for a differential computational free energy to the αvß3 integrin. These findings may suggest that naturally occurring endogenous TH metabolites may impact integrin-mediate intracellular pathways in physiology and cancer.

Disrupting the MAD2L2-Rev1 Complex Enhances Cell Death upon DNA Damage.

DNA-damaging chemotherapy agents such as cisplatin have been the first line of treatment for cancer for decades. While chemotherapy can be very effective, its long-term success is often reduced by intrinsic and acquired drug resistance, accompanied by chemotherapy-resistant secondary malignancies. Although the mechanisms causing drug resistance are quite distinct, they are directly connected to mutagenic translesion synthesis (TLS). The TLS pathway promotes DNA damage tolerance by supporting both replication opposite to a lesion and inaccurate single-strand gap filling. Interestingly, inhibiting TLS reduces both cisplatin resistance and secondary tumor formation. Therefore, TLS targeting is a promising strategy for improving chemotherapy. MAD2L2 (i.e., Rev7) is a central protein in TLS. It is an essential component of the TLS polymerase zeta (ζ), and it forms a regulatory complex with Rev1 polymerase. Here we present the discovery of two small molecules, c#2 and c#3, that directly bind both in vitro and in vivo to MAD2L2 and influence its activity. Both molecules sensitize lung cancer cell lines to cisplatin, disrupt the formation of the MAD2L2-Rev1 complex and increase DNA damage, hence underlining their potential as lead compounds for developing novel TLS inhibitors for improving chemotherapy treatments.

The effect of dimerization and ligand binding on the dynamics of Kaposi's sarcoma-associated herpesvirus protease.

The Kaposi's sarcoma-associated herpesvirus protease is essential for virus maturation. This protease functions under allosteric regulation that establishes its enzymatic activity upon dimerization. It exists in equilibrium between an inactive monomeric state and an active, weakly associating, dimeric state that is stabilized upon ligand binding. The dynamics of the protease dimer and its monomer were studied using the Gaussian network model and the anisotropic network model , and its role in mediating the allosteric regulation is demonstrated. We show that the dimer is composed of five dynamical domains. The central domain is formed upon dimerization and composed of helix five of each monomer, in addition to proximal and distal domains of each monomer. Dimerization reduces the mobility of the central domains and increases the mobility of the distal domains, in particular the binding site within them. The three slowest ANM modes of the dimer assist the protease in ligand binding, motion of the conserved Arg142 and Arg143 toward the oxyanion, and reducing the activation barrier for the tetrahedral transition state by stretching the bond that is cleaved by the protease. In addition, we show that ligand binding reduces the motion of helices α1 and α5 at the interface and explain how ligand binding can stabilize the dimer.

Different sea urchin RAG-like genes were domesticated to carry out different functions.

The closely linked recombination activating genes (RAG1 and RAG2) in vertebrates encode the core of the RAG recombinase that mediates the V(D)J recombination of the immunoglobulin and T-cell receptor genes. RAG1 and RAG2 homologues (RAG1L and RAG2L) are present in multiple invertebrate phyla, including mollusks, nemerteans, cnidarians, and sea urchins. However, the function of the invertebrates' RAGL proteins is yet unknown. The sea urchins contain multiple RAGL genes that presumably originated in a common ancestral transposon. In this study, we demonstrated that two different RAG1L genes in the sea urchin Paracentrutus lividus (PlRAG1La and PlRAG1Lb) lost their mobility and, along with PlRAG2L, were fully domesticated to carry out different functions. We found that the examined echinoid RAGL homologues have distinct expression profiles in early developmental stages and in adult tissues. Moreover, the predicted structure of the proteins suggests that while PlRAG1La could maintain its endonuclease activity and create a heterotetramer with PlRAG2L, the PlRAG1Lb adopted a different function that does not include an interaction with DNA nor a collaboration with PlRAG2L. By characterizing the different RAG homologues in the echinoid lineage, we hope to increase the knowledge about the evolution of these genes and shed light on their domestication processes.

Dynamical comparison between Drosha and Dicer reveals functional motion similarities and dissimilarities.

Drosha and Dicer are RNase III family members of classes II and III, respectively, which play a major role in the maturation of micro-RNAs. The two proteins share similar domain arrangement and overall fold despite no apparent sequence homology. The overall structural and catalytic reaction similarity of both proteins, on the one hand, and differences in the substrate and its binding mechanisms, on the other, suggest that both proteins also share dynamic similarities and dissimilarities. Since dynamics is essential for protein function, a comparison at their dynamics level is fundamental for a complete understanding of the overall relations between these proteins. In this study, we present a dynamical comparison between human Drosha and Giardia Dicer. Gaussian Network Model and Anisotropic Network Model modes of motion of the proteins are calculated. Dynamical comparison is performed using global and local dynamic programming algorithms for aligning modes of motion. These algorithms were recently developed based on the commonly used Needleman-Wunsch and Smith-Waterman algorithms for global and local sequence alignment. The slowest mode of Drosha is different from that of Dicer due to its more bended posture and allow the motion of the double-stranded RNA-binding domain toward and away from its substrate. Among the five slowest modes dynamics similarity exists only for the second slow mode of motion of Drosha and Dicer. In addition, high local dynamics similarity is observed at the catalytic domains, in the vicinity of the catalytic residues. The results suggest that the proteins exert a similar catalytic mechanism using similar motions, especially at the catalytic sites.

Dynamics based clustering of globin family members.

A methodology to cluster proteins based on their dynamics' similarity is presented. For each pair of proteins from a dataset, the structures are superimposed, and the Anisotropic Network Model modes of motions are calculated. The twelve slowest modes from each protein are matched using a local mode alignment algorithm based on the local sequence alignment algorithm of Smith-Waterman. The dynamical similarity distance matrix is calculated based on the top scoring matches of each pair and the proteins are clustered using a hierarchical clustering algorithm. The utility of this method is exemplified on a dataset of protein chains from the globin family and a dataset of tetrameric hemoglobins. The results demonstrate the effect of the quaternary structure of globin members on their intrinsic dynamics and show good ability to distinguish between different states of hemoglobin, revealing the dynamical relations between them.

Dynamical comparison between myoglobin and hemoglobin.

Myoglobin and hemoglobin are globular hemeproteins, when the former is a monomer and the latter a heterotetramer. Despite the structural similarity of myoglobin to α and ß subunits of hemoglobin, there is a functional difference between the two proteins, owing to the quaternary structure of hemoglobin. The effect of the quaternary structure of hemoglobin on the intrinsic dynamics of its subunits is explored by dynamical comparison of the two proteins. Anisotropic Network Model modes of motion were calculated for hemoglobin and myoglobin. Dynamical comparison between the proteins was performed using global and local Anisotropic Network Model mode alignment algorithms based on the algorithms of Smith-Waterman and Needleman-Wunsch for sequence comparison. The results indicate that the quaternary structure of hemoglobin substantially alters the intrinsic dynamics of its subunits, an effect that may contribute to the functional difference between the two proteins. Local dynamics similarity between the proteins is still observed at the major exit route of the ligand.

Dynamical differences of hemoglobin and the ionotropic glutamate receptor in different states revealed by a new dynamics alignment method.

A new algorithm for comparison of protein dynamics is presented. Compared protein structures are superposed and their modes of motions are calculated using the anisotropic network model. The obtained modes are aligned using the dynamic programming algorithm of Needleman and Wunsch, commonly used for sequence alignment. Dynamical comparison of hemoglobin in the T and R2 states reveals that the dynamics of the allosteric effector 2,3-bisphosphoglycerate binding site is different in the two states. These differences can contribute to the selectivity of the effector to the T state. Similar comparison of the ionotropic glutamate receptor in the kainate+(R,R)-2b and ZK bound states reveals that the kainate+(R,R)-2b bound states slow modes describe upward motions of ligand binding domain and the transmembrane domain regions. Such motions may lead to the opening of the receptor. The upper lobes of the LBDs of the ZK bound state have a smaller interface with the amino terminal domains above them and have a better ability to move together. The present study exemplifies the use of dynamics comparison as a tool to study protein function. Proteins 2017; 85:1507-1517. © 2014 Wiley Periodicals, Inc.

Toward the development of a novel non-RGD cyclic peptide drug conjugate for treatment of human metastatic melanoma.

The newly discovered short (9 amino acid) non-RGD S-S bridged cyclic peptide ALOS-4 (H-cycl(Cys-Ser-Ser-Ala-Gly-Ser-Leu-Phe-Cys)-OH), which binds to integrin αvß3 is investigated as peptide carrier for targeted drug delivery against human metastatic melanoma. ALOS4 binds specifically the αvß3 overexpressing human metastatic melanoma WM-266-4 cell line both in vitro and in ex vivo assays. Coupling ALOS4 to the topoisomerase I inhibitor Camptothecin (ALOS4-CPT) increases the cytotoxicity of CPT against human metastatic melanoma cells while reduces dramatically the cytotoxicity against non-cancerous cells as measured by the levels of γH2A.X, active caspase 3 and cell viability. Moreover, conjugating ALOS4 to CPT even increases the chemo-stability of CPT under physiological pH. Bioinformatic analysis using Rosetta platform revealed potential docking sites of ALOS4 on the αvß3 integrin which are distinct from the RGD binding sites. We propose to use this specific non-RGD cyclic peptide as the therapeutic carrier for conjugation of drugs in order to improve efficacy and reduce toxicity of currently available treatments of human malignant melanoma.

Novel synthetic cyclic integrin αvß3 binding peptide ALOS4: Antitumor activity in mouse melanoma models.

ALOS4, a unique synthetic cyclic peptide without resemblance to known integrin ligand sequences, was discovered through repeated biopanning with pIII phage expressing a disulfide-constrained nonapeptide library. Binding assays using a FITC-labeled analogue demonstrated selective binding to immobilized αvß3 and a lack of significant binding to other common proteins, such as bovine serum albumin and collagen. In B16F10 cell cultures, ALOS4 treatment at 72 h inhibited cell migration (30%) and adhesion (up to 67%). Immunofluorescent imaging an ALOS4-FITC analogue with B16F10 cells demonstrated rapid cell surface binding, and uptake and localization in the cytoplasm. Daily injections of ALOS4 (0.1, 0.3 or 0.5 mg/kg i.p.) to mice inoculated with B16F10 mouse melanoma cells in two different cancer models, metastatic and subcutaneous tumor, resulted in reduction of lung tumor count (metastatic) and tumor mass (subcutaneous) and increased survival of animals monitored to 45 and 60 days, respectively. Examination of cellular activity indicated that ALOS4 produces inhibition of cell migration and adhesion in a concentration-dependent manner. Collectively, these results suggest that ALOS4 is a structurally-unique selective αvß3 integrin ligand with potential anti-metastatic activity.

Dynamics and allostery of the ionotropic glutamate receptors and the ligand binding domain.

The dynamics of the ligand-binding domain (LBD) and the intact ionotropic glutamate receptor (iGluR) were studied using Gaussian Network Model (GNM) analysis. The dynamics of LBDs with various allosteric modulators is compared using a novel method of multiple alignment of GNM modes of motion. The analysis reveals that allosteric effectors change the dynamics of amino acids at the upper lobe interface of the LBD dimer as well as at the hinge region between the upper- and lower- lobes. For the intact glutamate receptor the analysis show that the clamshell-like movement of the LBD upper and lower lobes is coupled to the bending of the trans-membrane domain (TMD) helices which may open the channel pore. The results offer a new insight on the mechanism of action of allosteric modulators on the iGluR and support the notion of TMD helices bending as a possible mechanism for channel opening. In addition, the study validates the methodology of multiple GNM modes alignment as a useful tool to study allosteric effect and its relation to proteins dynamics.

Multiple Gaussian network modes alignment reveals dynamically variable regions: the hemoglobin case.

Gaussian network model (GNM) modes of motion are calculated to a dataset of hemoglobin (Hb) structures and modes with dynamics similarity to the T state are multiply aligned. The sole criterion for the alignment is the mode shape itself and not sequence or structural similarity. Standard deviation (SD) of the GNM value score along the alignment is calculated, regions with high SD are defined as dynamically variable. The analysis shows that the α1ß1/α2ß2 interface is a dynamically variable region but not the α1ß2/α2ß1 and the α1α2/ß1ß2 interfaces. The results are in accordance with the T→R2 transition of Hb. We suggest that dynamically variable regions are regions that are likely to undergo structural change in the protein upon binding, conformational transition, or any other relevant chemical event. The represented technique of multiple dynamics-based alignment of modes is novel and may offer a new insight in proteins' dynamics to function relation.

Large-scale analysis of the dynamics of enzymes.

Protein enzymes enable the cell to execute chemical reactions in short time by accelerating the rate of the reactions in a selective manner. The motions or dynamics of the enzymes are essential for their function. Comparison of the dynamics of a set of 1247 nonhomologous enzymes was performed. For each enzyme, the slowest modes of motion are calculated using the Gaussian network model (GNM) and they are globally aligned. Alignment is done using the dynamic programming algorithm of Needleman and Wunsch, commonly used for sequence alignment. Only 96 pairs of proteins were identified to have three similar GNM slow modes with 63 of them having a similar structure. The most frequent slowest mode of motion describes a two domains anticorrelated motion that characterizes at least 23% of the enzymes. Therefore, dynamics uniqueness cannot be accounted for by the slowest mode itself but rather by the combination of several slow modes. Different quaternary structure packing can restrain the motion of enzyme subunits differently and may serve as another mechanism that increases the dynamics uniqueness.

Dynamics alignment: comparison of protein dynamics in the SCOP database.

A novel methodology for comparison of protein dynamics is presented. Protein dynamics is calculated using the Gaussian network model and the modes of motion are globally aligned using the dynamic programming algorithm of Needleman and Wunsch, commonly used for sequence alignment. The alignment is fast and can be used to analyze large sets of proteins. The methodology is applied to the four major classes of the SCOP database: "all alpha proteins," "all beta proteins," "alpha and beta proteins," and "alpha/beta proteins". We show that different domains may have similar global dynamics. In addition, we report that the dynamics of "all alpha proteins" domains are less specific to structural variations within a given fold or superfamily compared with the other classes. We report that domain pairs with the most similar and the least similar global dynamics tend to be of similar length. The significance of the methodology is that it suggests a new and efficient way of mapping between the global structural features of protein families/subfamilies and their encoded dynamics.

Designing coarse grained-and atom based-potentials for protein-protein docking.

BACKGROUND: Protein-protein docking is a challenging computational problem in functional genomics, particularly when one or both proteins undergo conformational change(s) upon binding. The major challenge is to define a scoring function soft enough to tolerate these changes and specific enough to distinguish between near-native and "misdocked" conformations. RESULTS: Using a linear programming (LP) technique, we developed two types of potentials: (i) Side chain-based and (ii) Heavy atom-based. To achieve this we considered a set of 161 transient complexes and generated a large set of putative docked structures (decoys), based on a shape complementarity criterion, for each complex. The demand on the potentials was to yield, for the native (correctly docked) structure, a potential energy lower than those of any of the non-native (misdocked) structures. We show that the heavy atom-based potentials were able to comply with this requirement but not the side chain-based one. Thus, despite the smaller number of parameters, the capability of heavy atom-based potentials to discriminate between native and "misdocked" conformations is improved relative to those of the side chain-based potentials. The performance of the atom-based potentials was evaluated by a jackknife test on a set of 50 complexes taken from the Zdock2.3 decoys set. CONCLUSIONS: Our results show that, using the LP approach, we were able to train our potentials using a dataset of transient complexes only the newly developed potentials outperform three other known potentials in this test.

Docking of antizyme to ornithine decarboxylase and antizyme inhibitor using experimental mutant and double-mutant cycle data.

Antizyme (Az) is a highly conserved key regulatory protein bearing a major role in regulating polyamine levels in the cell. It has the ability to bind and inhibit ornithine decarboxylase (ODC), targeting it for degradation. Az inhibitor (AzI) impairs the activity of Az. In this study, we mapped the binding sites of ODC and AzI on Az using Ala scan mutagenesis and generated models of the two complexes by constrained computational docking. In order to scan a large number of mutants in a short time, we developed a workflow combining high-throughput mutagenesis, small-scale parallel partial purification of His-tagged proteins and their immobilization on a tris-nitrilotriacetic-acid-coated surface plasmon resonance chip. This combination of techniques resulted in a significant reduction in time for production and measurement of large numbers of mutant proteins. The data-driven docking results suggest that both proteins occupy the same binding site on Az, with Az binding within a large groove in AzI and ODC. However, single-mutant data provide information concerning the location of the binding sites only, not on their relative orientations. Therefore, we generated a large number of double-mutant cycles between residues on Az and ODC and used the resulting interaction energies to restrict docking. The model of the complex is well defined and accounts for the mutant data generated here, and previously determined biochemical data for this system. Insights on the structure and function of the complexes, as well as general aspects of the method, are discussed.

Intrinsic dynamics of enzymes in the unbound state and relation to allosteric regulation.

In recent years, there has been a surge in the number of studies exploring the relationship between proteins' equilibrium dynamics and structural changes involved in function. An emerging concept, supported by both theory and experiments, is that under native state conditions proteins have an intrinsic ability to sample conformations that meet functional requirements. A typical example is the ability of enzymes to sample open and closed forms, irrespective of substrate, succeeded by the stabilization of one form (usually closed) upon substrate binding. This ability is structure-encoded, and plays a key role in facilitating allosteric regulation, which suggests complementing the sequence-encodes-structure paradigm of protein science by structure-encodes-dynamics-encodes-function. The emerging connection implies an evolutionary role in selecting/conserving structures based on their ability to achieve functional dynamics, and in turn, selecting sequences that fold into such 'apt' structures.

Recruitment of rare 3-grams at functional sites: is this a mechanism for increasing enzyme specificity?

BACKGROUND: A wealth of unannotated and functionally unknown protein sequences has accumulated in recent years with rapid progresses in sequence genomics, giving rise to ever increasing demands for developing methods to efficiently assess functional sites. Sequence and structure conservations have traditionally been the major criteria adopted in various algorithms to identify functional sites. Here, we focus on the distributions of the 203 different types of 3-grams (or triplets of sequentially contiguous amino acid) in the entire space of sequences accumulated to date in the UniProt database, and focus in particular on the rare 3-grams distinguished by their high entropy-based information content. RESULTS: Comparison of the UniProt distributions with those observed near/at the active sites on a non-redundant dataset of 59 enzyme/ligand complexes shows that the active sites preferentially recruit 3-grams distinguished by their low frequency in the UniProt. Three cases, Src kinase, hemoglobin, and tyrosyl-tRNA synthetase, are discussed in details to illustrate the biological significance of the results. CONCLUSION: The results suggest that recruitment of rare 3-grams may be an efficient mechanism for increasing specificity at functional sites. Rareness/scarcity emerges as a feature that may assist in identifying key sites for proteins function, providing information complementary to that derived from sequence alignments. In addition it provides us (for the first time) with a means of identifying potentially functional sites from sequence information alone, when sequence conservation properties are not available.