Structural dynamics and allostery of Rab proteins: strategies for drug discovery and design.

Rab proteins represent the largest family of the Rab superfamily guanosine triphosphatase (GTPase). Aberrant human Rab proteins are associated with multiple diseases, including cancers and neurological disorders. Rab subfamily members display subtle conformational variations that render specificity in their physiological functions and can be targeted for subfamily-specific drug design. However, drug discovery efforts have not focused much on targeting Rab allosteric non-nucleotide binding sites which are subjected to less evolutionary pressures to be conserved, hence are likely to offer subfamily specificity and may be less prone to undesirable off-target interactions and side effects. To discover druggable allosteric binding sites, Rab structural dynamics need to be first incorporated using multiple experimentally and computationally obtained structures. The high-dimensional structural data may necessitate feature extraction methods to identify manageable representative structures for subsequent analyses. We have detailed state-of-the-art computational methods to (i) identify binding sites using data on sequence, shape, energy, etc., (ii) determine the allosteric nature of these binding sites based on structural ensembles, residue networks and correlated motions and (iii) identify small molecule binders through structure- and ligand-based virtual screening. To benefit future studies for targeting Rab allosteric sites, we herein detail a refined workflow comprising multiple available computational methods, which have been successfully used alone or in combinations. This workflow is also applicable for drug discovery efforts targeting other medically important proteins. Depending on the structural dynamics of proteins of interest, researchers can select suitable strategies for allosteric drug discovery and design, from the resources of computational methods and tools enlisted in the workflow.

Aggregation and Cellular Toxicity of Pathogenic or Non-pathogenic Proteins.

More than 20 unique diseases such as diabetes, Alzheimer's disease, Parkinson's disease are caused by the abnormal aggregations of pathogenic proteins such as amylin, ß-amyloid (Aß), and α-synuclein. All pathogenic proteins differ from each other in biological function, primary sequences, and morphologies; however, the proteins are toxic when aggregated. Here, we investigated the cellular toxicity of pathogenic or non-pathogenic protein aggregates. In this study, six proteins were selected and they were incubated at acid pH and high temperature. The aggregation kinetic and cellular toxicity of protein species with time were characterized. Three non-pathogenic proteins, bovine serum albumin (BSA), catalase, and pepsin at pH 2 and 65 °C were stable in protein structure and non-toxic at a lower concentration of 1 mg/mL. They formed aggregates at a higher concentration of 20 mg/mL with time and they induced the toxicity in short incubation time points, 10 min and 20 min only and they became non-toxic after 30 min. Other three pathogenic proteins, lysozyme, superoxide dismutase (SOD), and insulin, also produced the aggregates with time and they caused cytotoxicity at both 1 mg/mL and 20 mg/mL after 10 min. TEM images and DSC analysis demonstrated that fibrils or aggregates at 1 mg/mL induced cellular toxicity due to low thermal stability. In DSC data, fibrils or aggregates of pathogenic proteins had low thermal transition compared to fresh samples. The results provide useful information to understand the aggregation and cellular toxicity of pathogenic and non-pathogenic proteins.

Inhibition of lysozyme aggregation and cellular toxicity by organic acids at acidic and physiological pH conditions.

The misfolding of proteins can lead to fibrillar and non-fibrillar deposits that are the hallmark of numerous human diseases. Inhibition of protein aggregation is considered as a promising strategy for the prevention of such diseases. Here we induced the fibrillar and non-fibrillar aggregates of hen egg white lysozyme (HEWL) at acidic (pH 3) and physiological (pH 7.4) environments. HEWL formed non-fibrillar aggregates rapidly at pH 7.4, whereas fibrillar HEWL aggregates were formed slowly at pH 3. Both fibrillar and non-fibrillar aggregates had cytotoxic effects on PC12 cells. Next, four organic acids, succinic acid, maleic acid, tartaric acid and citric acid, were tested for their inhibition potencies against fibrillar and non-fibrillar HEWL species. The four inhibitors were found to prevent the aggregation of HEWL at pH 7.4 with a reduction rate of over 95% as compared with the reduction rate of 42-58% for HEWL aggregation at pH 3. Other biophysical and computational analyses reveal that the candidate inhibitors have higher inhibition efficacy against HEWL monomers incubated at pH 7.4 than at pH 3. These results emphasize the importance of validating the newly identified aggregation drugs against different aggregate species, which would enhance the understanding of small molecules-induced protein aggregation inhibition.

Computational and Experimental Approaches to Design Inhibitors of Amylin Aggregation.

Amylin is a neuroendocrine peptide hormone secreted by pancreatic ß-cells; however, amylin is toxic to ß-cells when it is aggregated in type 2 diabetes mellitus (T2DM). It is important to understand amylin's structures and aggregation mechanism for the discovery and design of effective drugs to inhibit amylin aggregation. In this review, we investigated experimental and computational studies on amylin structures and inhibitors. Our review provides some novel insights into amylin, particularly for the design of its aggregation inhibitors to treat T2DM. We detailed the potential inhibitors that have been studied hitherto and highlighted the neglected need to consider different amylin attributes that depend on the presence/absence of physiologically relevant conditions, such as membranes. These conditions and the experimental methods can greatly influence the results of studies on amylininhibitor complexes. Text-mining over 3,000 amylin-related PubMed abstracts suggests the combined therapeutic potential of amylin with leptin and glucagon-like peptide-1, which are two key hormones in obesity. The results also suggest that targeting amylin aggregation can contribute to therapeutic efforts for Alzheimer's disease (AD). Therefore, we have also reviewed the role of amylin in other conditions including obesity and AD. Finally, we provided insights for designing inhibitors of different types (small molecules, proteins, peptides/mimetics, metal ions) to inhibit amylin aggregation.

Allosteric binding sites in Rab11 for potential drug candidates.

Rab11 is an important protein subfamily in the RabGTPase family. These proteins physiologically function as key regulators of intracellular membrane trafficking processes. Pathologically, Rab11 proteins are implicated in many diseases including cancers, neurodegenerative diseases and type 2 diabetes. Although they are medically important, no previous study has found Rab11 allosteric binding sites where potential drug candidates can bind to. In this study, by employing multiple clustering approaches integrating principal component analysis, independent component analysis and locally linear embedding, we performed structural analyses of Rab11 and identified eight representative structures. Using these representatives to perform binding site mapping and virtual screening, we identified two novel binding sites in Rab11 and small molecules that can preferentially bind to different conformations of these sites with high affinities. After identifying the binding sites and the residue interaction networks in the representatives, we computationally showed that these binding sites may allosterically regulate Rab11, as these sites communicate with switch 2 region that binds to GTP/GDP. These two allosteric binding sites in Rab11 are also similar to two allosteric pockets in Ras that we discovered previously.

Inhibition of Human Amylin Aggregation and Cellular Toxicity by Lipoic Acid and Ascorbic Acid.

More than 30 human degenerative diseases result from protein aggregation such as Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM). Islet amyloid deposits, a hallmark in T2DM, are found in pancreatic islets of more than 90% of T2DM patients. An association between amylin aggregation and reduction in ß-cell mass was also established by post-mortem studies. A strategy in preventing protein aggregation-related disorders is to inhibit the protein aggregation and associated toxicity. In this study, we demonstrated that two inhibitors, lipoic acid and ascorbic acid, significantly inhibited amylin aggregation. Compared to amylin (15 µM) as 100%, lipoic acid and ascorbic acid reduced amylin fibril formation to 42.1 ± 17.2% and 42.9 ± 12.8%, respectively, which is confirmed by fluorescence and TEM images. In cell viability tests, both inhibitors protected RIN-m5f ß-cells from the toxicity of amylin aggregates. At 10:1 molar ratio of lipoic acid to amylin, lipoic acid with amylin increased the cell viability to 70.3%, whereas only 42.8% RIN-m5f ß-cells survived in amylin aggregates. For ascorbic acid, an equimolar ratio achieved the highest cell viability of 63.3% as compared to 42.8% with amylin aggregates only. Docking results showed that lipoic acid and ascorbic acid physically interact with amylin amyloidogenic region (residues Ser20-Ser29) via hydrophobic interactions; hence reducing aggregation levels. Therefore, lipoic acid and ascorbic acid prevented amylin aggregation via hydrophobic interactions, which resulted in the prevention of cell toxicity in vitro.

Structural analysis of protein tyrosine phosphatase 1B reveals potentially druggable allosteric binding sites.

Catalytic proteins such as human protein tyrosine phosphatase 1B (PTP1B), with conserved and highly polar active sites, warrant the discovery of druggable nonactive sites, such as allosteric sites, and potentially, therapeutic small molecules that can bind to these sites. Catalyzing the dephosphorylation of numerous substrates, PTP1B is physiologically important in intracellular signal transduction pathways in diverse cell types and tissues. Aberrant PTP1B is associated with obesity, diabetes, cancers, and neurodegenerative disorders. Utilizing clustering methods (based on root mean square deviation, principal component analysis, nonnegative matrix factorization, and independent component analysis), we have examined multiple PTP1B structures. Using the resulting representative structures in different conformational states, we determined consensus clustroids and used them to identify both known and novel binding sites, some of which are potentially allosteric. We report several lead compounds that could potentially bind to the novel PTP1B binding sites and can be further optimized. Considering the possibility for drug repurposing, we discovered homologous binding sites in other proteins, with ligands that could potentially bind to the novel PTP1B binding sites.

Discovery of Rab1 binding sites using an ensemble of clustering methods.

Targeting non-native-ligand binding sites for potential investigative and therapeutic applications is an attractive strategy in proteins that share common native ligands, as in Rab1 protein. Rab1 is a subfamily member of Rab proteins, which are members of Ras GTPase superfamily. All Ras GTPase superfamily members bind to native ligands GTP and GDP, that switch on and off the proteins, respectively. Rab1 is physiologically essential for autophagy and transport between endoplasmic reticulum and Golgi apparatus. Pathologically, Rab1 is implicated in human cancers, a neurodegenerative disease, cardiomyopathy, and bacteria-caused infectious diseases. We have performed structural analyses on Rab1 protein using a unique ensemble of clustering methods, including multi-step principal component analysis, non-negative matrix factorization, and independent component analysis, to better identify representative Rab1 proteins than the application of a single clustering method alone does. We then used the identified representative Rab1 structures, resolved in multiple ligand states, to map their known and novel binding sites. We report here at least a novel binding site on Rab1, involving Rab1-specific residues that could be further explored for the rational design and development of investigative probes and/or therapeutic small molecules against the Rab1 protein. Proteins 2017; 85:859-871. © 2016 Wiley Periodicals, Inc.

R248Q mutation--Beyond p53-DNA binding.

R248 in the DNA binding domain (DBD) of p53 interacts directly with the minor groove of DNA. Earlier nuclear magnetic resonance (NMR) studies indicated that the R248Q mutation resulted in conformation changes in parts of DBD far from the mutation site. However, how information propagates from the mutation site to the rest of the DBD is still not well understood. We performed a series of all-atom molecular dynamics (MD) simulations to dissect sterics and charge effects of R248 on p53-DBD conformation: (i) wild-type p53 DBD; (ii) p53 DBD with an electrically neutral arginine side-chain; (iii) p53 DBD with R248A; (iv) p53 DBD with R248W; and (v) p53 DBD with R248Q. Our results agree well with experimental observations of global conformational changes induced by the R248Q mutation. Our simulations suggest that both charge- and sterics are important in the dynamics of the loop (L3) where the mutation resides. We show that helix 2 (H2) dynamics is altered as a result of a change in the hydrogen bonding partner of D281. In turn, neighboring L1 dynamics is altered: in mutants, L1 predominantly adopts the recessed conformation and is unable to interact with the major groove of DNA. We focused our attention the R248Q mutant that is commonly found in a wide range of cancer and observed changes at the zinc-binding pocket that might account for the dominant negative effects of R248Q. Furthermore, in our simulations, the S6/S7 turn was more frequently solvent exposed in R248Q, suggesting that there is a greater tendency of R248Q to partially unfold and possibly lead to an increased aggregation propensity. Finally, based on the observations made in our simulations, we propose strategies for the rescue of R248Q mutants.

Exploiting protein intrinsic flexibility in drug design.

Molecular recognition in biological systems relies on the existence of specific attractive interactions between two partner molecules. Structure-based drug design seeks to identify and optimize such interactions between ligands and their protein targets. The approach followed in medicinal chemistry follows a combination of careful analysis of structural data together with experimental and/or theoretical studies on the system. This chapter focuses on the fact that a protein is not fully characterized by a single structure, but by an ensemble of states, some of them represent "hidden conformations" with cryptic binding sites. We highlight case studies where both experimental and computational methods have been used to mutually drive each other in an attempt to improve the success of the drug design approaches.Advances in both experimental techniques and computational methods have greatly improved our physico-chemical understanding of the functional mechanisms in biomolecules and opened a debate about the interplay between molecular structure and biomolecular function. The beautiful static pictures of protein structures may have led to neglecting the intrinsic protein flexibility, however we are entering a new era where more sophisticated methods are used to exploit this ability of macromolecules, and this will definitely lead to the inclusion of the notion in the pharmaceutical field of drug design.

Mapping the structural and dynamical features of multiple p53 DNA binding domains: insights into loop 1 intrinsic dynamics.

The transcription factor p53 regulates cellular integrity in response to stress. p53 is mutated in more than half of cancerous cells, with a majority of the mutations localized to the DNA binding domain (DBD). In order to map the structural and dynamical features of the DBD, we carried out multiple copy molecular dynamics simulations (totaling 0.8 µs). Simulations show the loop 1 to be the most dynamic element among the DNA-contacting loops (loops 1-3). Loop 1 occupies two major conformational states: extended and recessed; the former but not the latter displays correlations in atomic fluctuations with those of loop 2 (~24 Å apart). Since loop 1 binds to the major groove whereas loop 2 binds to the minor groove of DNA, our results begin to provide some insight into the possible mechanism underpinning the cooperative nature of DBD binding to DNA. We propose (1) a novel mechanism underlying the dynamics of loop 1 and the possible tread-milling of p53 on DNA and (2) possible mutations on loop 1 residues to restore the transcriptional activity of an oncogenic mutation at a distant site.

Conformational dynamics of capping protein and interaction partners: simulation studies.

Capping protein (CP) is important for the regulation of actin polymerization. CP binds to the barbed end of the actin filament and prevents actin polymerization. This interaction is modulated through competitive binding by regulatory proteins such as myotrophin (V-1) and the capping protein interacting (CPI) motif from CARMIL. The binding site of myotrophin overlaps with the region of CP that binds to the barbed end of actin filament, whereas CPI binds at a distant site. The binding of CPI to the myotrophin-CP complex dissociates myotrophin from CP. Detailed multicopy molecular dynamics simulations suggest that the binding of CPI shifts the conformational equilibria of CP away from states that favor myotrophin binding. This shift is underpinned by allosteric effects where CPI inhibits CP through suppression of flexibility and disruption of concerted motions that appear to mediate myotrophin binding. Accompanying these effects are changes in electrostatic interactions, notably those involving residue K142ß, which appears to play a critical role in regulating flexibility. In addition, accessibility of the site on CP for binding the key hydrophobic residue W8 of myotrophin is modulated by CPI. These results provide insights into the modulation of CP by CPI and myotrophin and indicate the mechanism by which CPI drives the dissociation of the myotrophin-CP complex.

Novel allosteric sites on Ras for lead generation.

Aberrant Ras activity is a hallmark of diverse cancers and developmental diseases. Unfortunately, conventional efforts to develop effective small molecule Ras inhibitors have met with limited success. We have developed a novel multi-level computational approach to discover potential inhibitors of previously uncharacterized allosteric sites. Our approach couples bioinformatics analysis, advanced molecular simulations, ensemble docking and initial experimental testing of potential inhibitors. Molecular dynamics simulation highlighted conserved allosteric coupling of the nucleotide-binding switch region with distal regions, including loop 7 and helix 5. Bioinformatics methods identified novel transient small molecule binding pockets close to these regions and in the vicinity of the conformationally responsive switch region. Candidate binders for these pockets were selected through ensemble docking of ZINC and NCI compound libraries. Finally, cell-based assays confirmed our hypothesis that the chosen binders can inhibit the downstream signaling activity of Ras. We thus propose that the predicted allosteric sites are viable targets for the development and optimization of new drugs.

The distinct conformational dynamics of K-Ras and H-Ras A59G.

Ras proteins regulate signaling cascades crucial for cell proliferation and differentiation by switching between GTP- and GDP-bound conformations. Distinct Ras isoforms have unique physiological functions with individual isoforms associated with different cancers and developmental diseases. Given the small structural differences among isoforms and mutants, it is currently unclear how these functional differences and aberrant properties arise. Here we investigate whether the subtle differences among isoforms and mutants are associated with detectable dynamical differences. Extensive molecular dynamics simulations reveal that wild-type K-Ras and mutant H-Ras A59G are intrinsically more dynamic than wild-type H-Ras. The crucial switch 1 and switch 2 regions along with loop 3, helix 3, and loop 7 contribute to this enhanced flexibility. Removing the gamma-phosphate of the bound GTP from the structure of A59G led to a spontaneous GTP-to-GDP conformational transition in a 20-ns unbiased simulation. The switch 1 and 2 regions exhibit enhanced flexibility and correlated motion when compared to non-transitioning wild-type H-Ras over a similar timeframe. Correlated motions between loop 3 and helix 5 of wild-type H-Ras are absent in the mutant A59G reflecting the enhanced dynamics of the loop 3 region. Taken together with earlier findings, these results suggest the existence of a lower energetic barrier between GTP and GDP states of the mutant. Molecular dynamics simulations combined with principal component analysis of available Ras crystallographic structures can be used to discriminate ligand- and sequence-based dynamic perturbations with potential functional implications. Furthermore, the identification of specific conformations associated with distinct Ras isoforms and mutants provides useful information for efforts that attempt to selectively interfere with the aberrant functions of these species.

Unraveling evolutionary constraints: a heterogeneous conservation in dynamics of the titin Ig domains.

The giant protein titin, which comprises immunoglobulin (Ig) domains, acts as a bidirectional spring in muscle. The unfolding of Ig domains has been extensively studied, but their dynamics under native states have not been well-characterized. We performed molecular dynamics simulation on a single titin Ig domain and multi-domains. Mobile regions displaying concerted motions were identified. The dynamics of Ig domains are constrained by evolutionary pressures, in such a way that global dominant motion is conserved, yet different flexibilities within Ig domains and in linkers connecting neighbouring domains were observed. We explain these heterogeneous conserved dynamics in relation to sequence conservation across species and the sequence diversity among neighbouring Ig domains.

A network of dynamically conserved residues deciphers the motions of maltose transporter.

The maltose transporter of Escherichia coli is a member of the ATP-binding cassette (ABC) transporter superfamily. The crystal structures of maltose transporter MalK have been determined for distinct conformations in the presence and absence of the ligand ATP, and other interacting proteins. Using the distinct MalK structures, normal mode analysis was performed to understand the dynamics behavior of the system. A network of dynamically important residues was obtained from the normal mode analysis and the analysis of point mutation on the normal modes. Our results suggest that the intradomain rotation occurs earlier than the interdomain rotation during the maltose-binding protein (MBP)-driven conformational changes of MalK. We inquire if protein motion and functional-driven evolutionary conservation are related. The sequence conservation of MalK was analyzed to derive a network of evolutionarily important residues. There are highly significant correlations between protein sequence and protein dynamics in many regions on the maltose transporter MalK, suggesting a link between the protein evolution and dynamics. The significant overlaps between the network of dynamically important residues and the network of evolutionarily important residues form a network of dynamically conserved residues.

Computational methods for Traditional Chinese Medicine: a survey.

Traditional Chinese Medicine (TCM) has been actively researched through various approaches, including computational techniques. A review on basic elements of TCM is provided to illuminate various challenges and progresses in its study using computational methods. Information on various TCM formulations, in particular resources on databases of TCM formulations and their integration to Western medicine, are analyzed in several facets, such as TCM classifications, types of databases, and mining tools. Aspects of computational TCM diagnosis, namely inspection, auscultation, pulse analysis as well as TCM expert systems are reviewed in term of their benefits and drawbacks. Various approaches on exploring relationships among TCM components and finding genes/proteins relating to TCM symptom complex are also studied. This survey provides a summary on the advance of computational approaches for TCM and will be useful for future knowledge discovery in this area.