Structural stability of binding sites: Consequences for binding affinity and allosteric effects

Molecular basis for differential recognition of an allosteric inhibitor by receptor tyrosine kinases

Understanding kinase-inhibitor selectivity continues to be a major objective in kinase drug discovery. We probe the molecular basis of selectivity of an allosteric inhibitor (MSC1609119A-1) of the insulin-like growth factor-I receptor kinase (IGF1RK), which has been shown to be ineffective for the homologous insulin receptor kinase (IRK). Specifically, we investigated the structural and energetic basis of the allosteric binding of this inhibitor to each kinase by combining molecular modeling, molecular dynamics (MD) simulations, and thermodynamic calculations. We predict the inhibitor conformation in the binding pocket of IRK and highlight that the charged residues in the histidine-arginine-aspartic acid (HRD) and aspartic acid-phenylalanine-glycine (DFG) motifs and the nonpolar residues in the binding pocket govern inhibitor interactions in the allosteric pocket of each kinase. We suggest that the conformational changes in the IGF1RK residues M1054 and M1079, movement of the ⍺C-helix, and the conformational stabilization of the DFG motif favor the selectivity of the inhibitor toward IGF1RK. Our thermodynamic calculations reveal that the observed selectivity can be rationalized through differences observed in the electrostatic interaction energy of the inhibitor in each inhibitor/kinase complex and the hydrogen bonding interactions of the inhibitor with the residue V1063 in IGF1RK that are not attained with the corresponding residue V1060 in IRK. Overall, our study provides a rationale for the molecular basis of recognition of this allosteric inhibitor by IGF1RK and IRK, which is potentially useful in developing novel inhibitors with improved affinity and selectivity.

Potential molecular mechanisms underlying the ameliorative effect of Cola nitida (Vent.) Schott & Endl. on insulin resistance in rat skeletal muscles

ETHNOPHARMACOLOGICAL RELEVANCE

Cola nitida (Vent.) Schott & Endl. are among the common medicinal plants employed in traditional medicine for treating diabetes and its complications.

AIM OF THE STUDY

The present study investigated the effect of Cola nitida infusion on the expression of key genes involved in insulin signaling vis-à-vis Insulin receptor substrate 1 (IRS-1), tumor protein P53 gene, glucose transporter type 4 (GLUT4), phosphoinositide 3-kinases (PI3K) and B-cell lymphoma-2 (BCL2) in skeletal muscles of type 2 diabetic (T2D) rats.

METHODS

Type 2 diabetic rats were administered C. nitida infusion at low and high doses (150 and 300 mg/kg bodyweight, respectively), while a high dose of the infusion was also administered to a normal toxicological group. Metformin served as the standard antidiabetic drug. The rats were sacrificed at the end of the experimental period. Their psoas muscles were harvested and assayed for the expressions of IRS1, p53, GLUT4, PI3K and BCL2. The studied genes were further subjected to enrichment analysis using the ShinyGO 0.76 online software.

RESULTS

Induction of T2D upregulated the expressions of IRS-1, p53, PI3K and BCL2 in psoas muscles, while concomitantly downregulating GLUT4 expression. These expressions were significantly reversed in type 2 diabetic rats treated with C. nitida infusion, and the results were statistically significant compared to metformin. Gene enrichment analysis revealed that the genes were linked to intrinsic pathways and biological processes involved in insulin resistance. The infusion further improved muscle glucose uptake, ex vivo. Molecular docking and molecular dynamics stimulation of C. nitida infusion phytoconstituents, caffeine and theobromine with IRS-1, p53, GLUT4, PI3K and BCL2 revealed a strong binding affinity as evident by the RMSD and RMSF values.

CONCLUSION

These results indicate the potentials of C. nitida infusion to improve glucose homeostasis in skeletal muscles of type 2 diabetic rats.

Therapeutic Path to Triple Knockout: Investigating the Pan-inhibitory Mechanisms of AKT, CDK9, and TNKS2 by a Novel 2-phenylquinazolinone Derivative in Cancer Therapy- An In-silico Investigation Therapy

BACKGROUND

Blocking the oncogenic Wnt//β-catenin pathway has of late been investigated as a viable therapeutic approach in the treatment of cancer. This involves the multi-targeting of certain members of the tankyrase-kinase family; Tankyrase 2 (TNKS2), Protein Kinase B (AKT), and Cyclin- Dependent Kinase 9 (CDK9), which propagate the oncogenic Wnt/β-catenin signalling pathway.

METHODS

During a recent investigation, the pharmacological activity of 2-(4-aminophenyl)-7-chloro- 3H-quinazolin-4-one was repurposed to serve as a 'triple-target' inhibitor of TNKS2, AKT and CDK9. Yet, the molecular mechanism that surrounds its multi-targeting activity remains unanswered. As such, this study aims to explore the pan-inhibitory mechanism of 2-(4-aminophenyl)-7-chloro-3H-quinazolin- 4-one towards AKT, CDK9, and TNKS2, using in silico techniques.

RESULTS

Results revealed favourable binding affinities of -34.17 kcal/mol, -28.74 kcal/mol, and -27.30 kcal/mol for 2-(4-aminophenyl)-7-chloro-3H-quinazolin-4-one towards TNKS2, CDK9, and AKT, respectively. Pan-inhibitory binding of 2-(4-aminophenyl)-7-chloro-3H-quinazolin-4-one is illustrated by close interaction with specific residues on tankyrase-kinase. Structurally, 2-(4-aminophenyl)-7-chloro- 3H-quinazolin-4-one had an impact on the flexibility, solvent-accessible surface area, and stability of all three proteins, which was illustrated by numerous modifications observed in the unbound as well as the bound states of the structures, which evidenced the disruption of their biological function. Prediction of the pharmacokinetics and physicochemical properties of 2-(4-aminophenyl)-7-chloro-3H-quinazolin-4- one further established its inhibitory potential, evidenced by the favourable absorption, metabolism, excretion, and minimal toxicity properties.

CONCLUSION

The following structural insights provide a starting point for understanding the paninhibitory activity of 2-(4-aminophenyl)-7-chloro-3H-quinazolin-4-one. Determining the criticality of the interactions that exist between the pyrimidine ring and catalytic residues could offer insight into the structure-based design of innovative tankyrase-kinase inhibitors with enhanced therapeutic effects.

Overcoming phenotypic switching: targeting protein-protein interactions in cancer

Alternative protein-protein interactions (PPIs) arising from mutations or post-translational modifications (PTMs), termed phenotypic switching (PS), are critical for the transmission of alternative pathogenic signals and are particularly significant in cancer. In recent years, PPIs have emerged as promising targets for rational drug design, primarily because their high specificity facilitates targeting of disease-related signaling pathways. However, obstacles exist at the molecular level that arise from the properties of the interaction interfaces and the propensity of small molecule drugs to interact with more than one cleft surface. The difficulty in identifying small molecules that act as activators or inhibitors to counteract the biological effects of mutations raises issues that have not been encountered before. For example, small molecules can bind tightly but may not act as drugs or bind to multiple sites (interaction promiscuity). Another reason is the absence of significant clefts on protein surfaces; if a pocket is present, it may be too small, or its geometry may prevent binding. PS, which arises from oncogenic (alternative) signaling, causes drug resistance and forms the basis for the systemic robustness of tumors. In this review, the properties of PPI interfaces relevant to the design and development of targeting drugs are examined. In addition, the interactions between three tyrosine kinase inhibitors (TKIs) employed as drugs are discussed. Finally, potential novel targets of one of these drugs were identified in silico.

Identification of Drug Combination Therapies for SARS-CoV-2: A Molecular Dynamics Simulations Approach

Purpose

The development of effective treatments for coronavirus infectious disease 19 (COVID-19) caused by SARS-Coronavirus-2 was hindered by the little data available about this virus at the start of the pandemic. Drug repurposing provides a good strategy to explore approved drugs' possible SARS-CoV-2 antiviral activity. Moreover, drug synergism is essential in antiviral treatment due to improved efficacy and reduced toxicity. In this work, we studied the effect of approved and investigational drugs on one of SARS-CoV-2 essential proteins, the main protease (Mpro), in search of antiviral treatments and/or drug combinations.

Methods

Different possible druggable sites of Mpro were identified and screened against an in-house library of more than 4000 chemical compounds. Molecular dynamics simulations were carried out to explore conformational changes induced by different ligands' binding. Subsequently, the inhibitory effect of the identified compounds and the suggested drug combinations on the Mpro were established using a 3CL protease (SARS-CoV-2) assay kit.

Results

Three potential inhibitors in three different binding sites were identified; favipiravir, cefixime, and carvedilol. Molecular dynamics simulations predicted the synergistic effect of two drug combinations: favipiravir/cefixime, and favipiravir/carvedilol. The in vitro inhibitory effect of the predicted drug combinations was established on this enzyme.

Conclusion

In this work, we could study one of the promising SARS-CoV-2 viral protein targets in searching for treatments for COVID-19. The inhibitory effect of several drugs on Mpro was established in silico and in vitro assays. Molecular dynamics simulations showed promising results in predicting the synergistic effect of drug combinations.

Computational prediction of protein functional sites-Applications in biotechnology and biomedicine

There are many computational approaches for predicting protein functional sites based on different sequence and structural features. These methods are essential to cope with the sequence deluge that is filling databases with uncharacterized protein sequences. They complement the more expensive and time-consuming experimental approaches by pointing them to possible candidate positions. In many cases they are jointly used to characterize the functional sites in proteins of biotechnological and biomedical interest and eventually modify them for different purposes. There is a clear trend towards approaches based on machine learning and those using structural information, due to the recent developments in these areas. Nevertheless, "classic" methods based on sequence and evolutionary features are still playing an important role as these features are strongly related to functionality. In this review, the main approaches for predicting general functional sites in a protein are discussed, with a focus on sequence-based approaches.

Computational Methods for Structure-Based Drug Design Through System Biology

The advances in computational chemistry and biology, computer science, structural biology, and molecular biology go in parallel with the rapid progress in target-based systems. This technique has become a powerful tool in medicinal chemistry for the identification of hit molecules. The recent developments in target-based systems have played a major role in the creation of libraries of compounds, and it has also been widely applied for the design of molecular docking methods. The main advantage of this method is that it hits the fragment that has the strongest binding, has relatively small size, and leads to better compounds in terms of pharmacokinetic properties when compared with virtual screening (VS) and high-throughput screening (HTS) hits. De novo design is an essential aspect of target-based systems and requires the synthesis of chemical to allow the design of promising compound.

CANDOCK: Chemical Atomic Network-Based Hierarchical Flexible Docking Algorithm Using Generalized Statistical Potentials

Small-molecule docking has proven to be invaluable for drug design and discovery. However, existing docking methods have several limitations such as improper treatment of the interactions of essential components in the chemical environment of the binding pocket (e.g., cofactors, metal ions, etc.), incomplete sampling of chemically relevant ligand conformational space, and the inability to consistently correlate docking scores of the best binding pose with experimental binding affinities. We present CANDOCK, a novel docking algorithm, that utilizes a hierarchical approach to reconstruct ligands from an atomic grid using graph theory and generalized statistical potential functions to sample biologically relevant ligand conformations. Our algorithm accounts for protein flexibility, solvent, metal ions, and cofactor interactions in the binding pocket that are traditionally ignored by current methods. We evaluate the algorithm on the PDBbind, Astex, and PINC proteins to show its ability to reproduce the binding mode of the ligands that is independent of the initial ligand conformation in these benchmarks. Finally, we identify the best selector and ranker potential functions such that the statistical score of the best selected docked pose correlates with the experimental binding affinities of the ligands for any given protein target. Our results indicate that CANDOCK is a generalized flexible docking method that addresses several limitations of current docking methods by considering all interactions in the chemical environment of a binding pocket for correlating the best-docked pose with biological activity. CANDOCK along with all structures and scripts used for benchmarking is available at https://github.com/chopralab/candock_benchmark.

Binding site plasticity in viral PPxY Late domain recognition by the third WW domain of human NEDD4

The recognition of PPxY viral Late domains by the third WW domain of the HECT-E3 ubiquitin ligase NEDD4 (hNEDD4-WW3) is essential for the completion of the budding process of numerous enveloped viruses, including Ebola, Marburg, HTLV1 or Rabies. hNEDD4-WW3 has been validated as a promising target for the development of novel host-oriented broad spectrum antivirals. Nonetheless, finding inhibitors with good properties as therapeutic agents remains a challenge since the key determinants of binding affinity and specificity are still poorly understood. We present here a detailed structural and thermodynamic study of the interactions of hNEDD4-WW3 with viral Late domains combining isothermal titration calorimetry, NMR structural determination and molecular dynamics simulations. Structural and energetic differences in Late domain recognition reveal a highly plastic hNEDD4-WW3 binding site that can accommodate PPxY-containing ligands with varying orientations. These orientations are mostly determined by specific conformations adopted by residues I859 and T866. Our results suggest a conformational selection mechanism, extensive to other WW domains, and highlight the functional relevance of hNEDD4-WW3 domain conformational flexibility at the binding interface, which emerges as a key element to consider in the search for potent and selective inhibitors of therapeutic interest.

Structural Dynamics of Agonist and Antagonist Binding to the Androgen Receptor

Androgen receptor (AR) is a steroid hormone nuclear receptor which upon binding its endogenous androgenic ligands (agonists), testosterone and dihydrotestosterone (DHT), alters gene transcription, producing a diverse range of biological effects. Antiandrogens, such as the pharmaceuticals bicalutamide and hydroxyflutamide, act as agonists in the absence of androgens and as antagonists in their presence or in high concentration. The atomic level mechanism of action by agonists and antagonists of AR is less well characterized. Therefore, in this study, multiple 1 μs molecular dynamics (MD), docking simulations, and perturbation-response analyses were performed to more fully explore the nature of interaction between agonist or antagonist and AR and the conformational changes induced in the AR upon interaction with different ligands. We characterized the mechanism of the ligand entry/exit and found that helix-12 and nearby structural motifs respond dynamically in that process. Modeling showed that the agonist and antagonist/agonist form a hydrogen bond with Thr877/Asn705 and that this interaction is absent for antagonists. Agonist binding to AR increases the mobility of residues at allosteric sites and coactivator binding sites, while antagonist binding decreases mobility at these important sites. A new site was also identified as a potential surface for allosteric binding. These results shed light on the effect of agonists and antagonists on the structure and dynamics of AR.

Inherent versus induced protein flexibility: Comparisons within and between apo and holo structures

Understanding how ligand binding influences protein flexibility is important, especially in rational drug design. Protein flexibility upon ligand binding is analyzed herein using 305 proteins with 2369 crystal structures with ligands (holo) and 1679 without (apo). Each protein has at least two apo and two holo structures for analysis. The inherent variation in structures with and without ligands is first established as a baseline. This baseline is then compared to the change in conformation in going from the apo to holo states to probe induced flexibility. The inherent backbone flexibility across the apo structures is roughly the same as the variation across holo structures. The induced backbone flexibility across apo-holo pairs is larger than that of the apo or holo states, but the increase in RMSD is less than 0.5 Å. Analysis of χ1 angles revealed a distinctly different pattern with significant influences seen for ligand binding on side-chain conformations in the binding site. Within the apo and holo states themselves, the variation of the χ1 angles is the same. However, the data combining both apo and holo states show significant displacements. Upon ligand binding, χ1 angles are frequently pushed to new orientations outside the range seen in the apo states. Influences on binding-site variation could not be easily attributed to features such as ligand size or x-ray structure resolution. By combining these findings, we find that most binding site flexibility is compatible with the common practice in flexible docking, where backbones are kept rigid and side chains are allowed some degree of flexibility.

Peptide-based development of PKA activators

Activation of the PKA catalytic unit by small peptide (SE1). Development of peptidomimetics.

A Cooperative Folding Unit as the Structural Link for Energetic Coupling within a Protein

Previously, we demonstrated that binding of a ligand to Escherichia coli cofactor-dependent phosphoglycerate mutase (dPGM), a homodimeric protein, is energetically coupled with dimerization. The equilibrium unfolding of dPGM occurs with a stable, monomeric intermediate. Binding of several nonsubstrate metabolites stabilizes the dimeric native form over the monomeric intermediate, reducing the population of the intermediate. Both the active site and the dimer interface appear to be unfolded in the intermediate. We hypothesized that a loop containing residues 118-152 was responsible for the energetic coupling between the dimer interface and the distal active site and was unfolded in the intermediate. Here, we investigated the structure of the dPGM intermediate by probing side-chain interactions and solvent accessibility of the peptide backbone. By comparing the effect of a mutation on the global stability and the stability of the intermediate, we determine an equilibrium φ value (φ_eq value), which provides information about whether side-chain interactions are retained or lost in the intermediate. Hydrogen/deuterium exchange coupled with mass spectrometry (HDX-MS) was used to investigate differences in the solvent accessibility of the peptide backbone in the intermediate and native forms of dPGM. The results of φ_eq value analysis and HDX-MS reveal the least stable folding unit of dPGM, which is unfolded in the intermediate and links the active site to the dimer interface. The structure of the intermediate reveals how the cooperative network of residues in dPGM gives rise to the observed energetic coupling between dimerization and ligand binding.

Decomposing Dynamical Couplings in Mutated scFv Antibody Fragments into Stabilizing and Destabilizing Effects

Conformational fluctuations within scFv antibodies are characterized by a novel perturbation-response decomposition of molecular dynamics trajectories. Both perturbation and response profiles are stratified into stabilizing and destabilizing conditions. The linker between the VH and VL domains exhibits the dominant dynamical response by being coupled to nearly the entire protein, responding to both stabilizing and destabilizing perturbations. Perturbations within complementarity-determining regions (CDR) induce rich behavior in dynamic response. Among many effects, stabilizing any CDR loop in the VH domain triggers a destabilizing response in all CDR loops in the VL domain and vice versa. Destabilizing residues within the VL domain are likely to stabilize all CDR loops in the VH domain, and, when these residues are not buried, the CDR loops in the VL domain are also likely to be stabilized. These effects, described by shifts in normal mode characteristics, initiate a propensity for dynamic allostery with possible functional implications in bispecific antibodies.

WITHDRAWN: Role of osmolytes in protein folding and aggregation in cells and its applications in biotechnology

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Indole-3-carbinol (I3C) analogues are potent small molecule inhibitors of NEDD4-1 ubiquitin ligase activity that disrupt proliferation of human melanoma cells

The HECT domain-containing E3 ubiquitin ligase NEDD4-1 (Neural precursor cell Expressed Developmentally Down regulated gene 4-1) is frequently overexpressed in human cancers and displays oncogenic-like properties through the ubiquitin-dependent regulation of multiple protein substrates. However, little is known about small molecule enzymatic inhibitors of HECT domain-containing ubiquitin ligases. We now demonstrate that indole-3-carbinol (I3C), a natural anti-cancer phytochemical derived from cruciferous vegetables such as cabbage and broccoli, represents a new chemical scaffold of small molecule enzymatic inhibitors of NEDD4-1. Using in vitro ubiquitination assays, I3C, its stable synthetic derivative 1-benzyl-I3C and five novel synthetic analogues were shown to directly inhibit NEDD4-1 ubiquitination activity. Compared to I3C, which has an IC50 of 284μM, 1-benzyl-I3C was a significantly more potent NEDD4-1 enzymatic inhibitor with an IC50 of 12.3μM. Compounds 2242 and 2243, the two indolecarbinol analogues with added methyl groups that results in a more nucleophilic benzene ring π system, further enhanced potency with IC50s of 2.71μM and 7.59μM, respectively. Protein thermal shift assays that assess small ligand binding, in combination with in silico binding simulations with the crystallographic structure of NEDD4-1, showed that each of the indolecarbinol compounds bind to the purified catalytic HECT domain of NEDD4-1. The indolecarbinol compounds inhibited human melanoma cell proliferation in a manner that generally correlated with their effectiveness as NEDD4-1 enzymatic inhibitors. Taken together, we propose that I3C analogues represent a novel set of anti-cancer compounds for treatment of human melanomas and other cancers that express indolecarbinol-sensitive target enzymes.

From Binding-Induced Dynamic Effects in SH3 Structures to Evolutionary Conserved Sectors

Src Homology 3 domains are ubiquitous small interaction modules known to act as docking sites and regulatory elements in a wide range of proteins. Prior experimental NMR work on the SH3 domain of Src showed that ligand binding induces long-range dynamic changes consistent with an induced fit mechanism. The identification of the residues that participate in this mechanism produces a chart that allows for the exploration of the regulatory role of such domains in the activity of the encompassing protein. Here we show that a computational approach focusing on the changes in side chain dynamics through ligand binding identifies equivalent long-range effects in the Src SH3 domain. Mutation of a subset of the predicted residues elicits long-range effects on the binding energetics, emphasizing the relevance of these positions in the definition of intramolecular cooperative networks of signal transduction in this domain. We find further support for this mechanism through the analysis of seven other publically available SH3 domain structures of which the sequences represent diverse SH3 classes. By comparing the eight predictions, we find that, in addition to a dynamic pathway that is relatively conserved throughout all SH3 domains, there are dynamic aspects specific to each domain and homologous subgroups. Our work shows for the first time from a structural perspective, which transduction mechanisms are common between a subset of closely related and distal SH3 domains, while at the same time highlighting the differences in signal transduction that make each family member unique. These results resolve the missing link between structural predictions of dynamic changes and the domain sectors recently identified for SH3 domains through sequence analysis.

Small protein domains as Src Homology 3 often act as docking sites and serve as regulatory elements. To understand their role in the regulation of a protein’s activity, one needs to understand how their backbone and sidechain dynamics are affected when binding to peptides. We have therefore computationally analyzed eight different SH3 domain structures, predicting dynamical effects induced by binding through our MCIT approach that has been shown to correlate well with experimental data. We show first that binding the Src SH3 domain triggers a particular cascade of dynamic effects, which are compatible with an induced fit mechanism reported before. We then combined the predictions for the eight SH3 domains into different consensus models, with the aim of analyzing, for the first time from a structural perspective, commonalities and differences in the transduction mechanisms among these SH3 domains. These consensus results are, on one hand, in agreement with the domain sectors recently identified for the entire family of SH3 domains. On the other hand, they reveal also that differences exist between the different subgroups that were studied here, requiring extensive experimental investigations of the importance of these differences for the proteins wherein these SH3 domains can be found.

Energetic Coupling between Ligand Binding and Dimerization in Escherichia coli Phosphoglycerate Mutase

Energetic coupling of two molecular events in a protein molecule is ubiquitous in biochemical reactions mediated by proteins, such as catalysis and signal transduction. Here, we investigate energetic coupling between ligand binding and folding of a dimer using a model system that shows three-state equilibrium unfolding of an exceptional quality. The homodimeric Escherichia coli cofactor-dependent phosphoglycerate mutase (dPGM) was found to be stabilized by ATP in a proteome-wide screen, although dPGM does not require or utilize ATP for enzymatic function. We investigated the effect of ATP on the thermodynamic stability of dPGM using equilibrium unfolding. We found that, in the absence of ATP, dPGM populates a partially unfolded, monomeric intermediate during equilibrium unfolding. However, addition of 1.0 mM ATP drastically reduces the population of the intermediate by selectively stabilizing the native dimer. Using a computational ligand docking method, we predicted ATP binds to the active site of the enzyme using the triphosphate group. By performing equilibrium unfolding and isothermal titration calorimetry with active-site variants of dPGM, we confirmed that active-site residues are involved in ATP binding. Our findings show that ATP promotes dimerization of the protein by binding to the active site, which is distal from the dimer interface. This cooperativity suggests an energetic coupling between the active site and the dimer interface. We also propose a structural link to explain how ligand binding to the active site is energetically coupled with dimerization.

Bovine glutamate dehydrogenase immobilization on magnetic nanoparticles: conformational changes and catalysis

Glutamate dehydrogenase (GDH) was immobilized on different supports and systematically investigated in order to provide a better understanding of the immobilization effects on the catalysis of multimeric enzymes.

Protein/peptide secondary structural mimics: design, characterization, and modulation of protein–protein interactions

This review discusses general aspects of novel artificial peptide secondary structure mimics for modulation of PPIs, their therapeutic applications and future prospects.

Effects of Non-Natural Amino Acid Incorporation into the Enzyme Core Region on Enzyme Structure and Function

Techniques to incorporate non-natural amino acids (NNAAs) have enabled biosynthesis of proteins containing new building blocks with unique structures, chemistry, and reactivity that are not found in natural amino acids. It is crucial to understand how incorporation of NNAAs affects protein function because NNAA incorporation may perturb critical function of a target protein. This study investigates how the site-specific incorporation of NNAAs affects catalytic properties of an enzyme. A NNAA with a hydrophobic and bulky sidechain, 3-(2-naphthyl)-alanine (2Nal), was site-specifically incorporated at six different positions in the hydrophobic core of a model enzyme, murine dihydrofolate reductase (mDHFR). The mDHFR variants with a greater change in van der Waals volume upon 2Nal incorporation exhibited a greater reduction in the catalytic efficiency. Similarly, the steric incompatibility calculated using RosettaDesign, a protein stability calculation program, correlated with the changes in the catalytic efficiency.

Melanophilin Stimulates Myosin-5a Motor Function by Allosterically Inhibiting the Interaction between the Head and Tail of Myosin-5a

The tail-inhibition model is generally accepted for the regulation of myosin-5a motor function. Inhibited myosin-5a is in a folded conformation in which its globular tail domain (GTD) interacts with its head and inhibits its motor function, and high Ca²⁺ or cargo binding may reduce the interaction between the GTD and the head of myosin-5a, thus activating motor activity. Although it is well established that myosin-5a motor function is regulated by Ca²⁺, little is known about the effects of cargo binding. We previously reported that melanophilin (Mlph), a myosin-5a cargo-binding protein, is capable of activating myosin-5a motor function. Here, we report that Mlph-GTBDP, a 26 amino-acid-long peptide of Mlph, is sufficient for activating myosin-5a motor function. We demonstrate that Mlph-GTBDP abolishes the interaction between the head and GTD of myosin-5a, thereby inducing a folded-to-extended conformation transition for myosin-5a and activating its motor function. Mutagenesis of the GTD shows that the GTD uses two distinct, non-overlapping regions to interact with Mlph-GTBDP and the head of myosin-5a. We propose that the GTD is an allosteric protein and that Mlph allosterically inhibits the interaction between the GTD and head of myosin-5a, thereby activating myosin-5a motor function.

Structural and dynamics aspects of ASC speck assembly

Activation of the inflammasome is accompanied by rapid formation of a micrometer-sized perinuclear structure called the ASC speck, a platform for caspase-1 activity. The ASC speck is often referred to as an aggregate and shares certain features with aggresomes. It is thus an open question whether the ASC speck formation takes place via nonspecific aggregation of hydrophobic patches or specific interactions of its domains; PYD and CARD, which belong to the death fold superfamily. Bringing together structure and dynamics studies using the Gaussian network model of PYD and CARD, and molecular dynamics simulations of the wild-type and in silico mutated PYD, with the mutational analysis on the ASC structure and its separate domains in human cells, we show that the ASC speck is an organized structure with at least two levels of distinct compaction mechanisms based on the specific interactions of PYD and CARD.

Effects of HIV-1 protease on cellular functions and their potential applications in antiretroviral therapy

Human Immunodeficiency Virus Type 1 (HIV-1) protease inhibitors (PIs) are the most potent class of drugs in antiretroviral therapies. However, viral drug resistance to PIs could emerge rapidly thus reducing the effectiveness of those drugs. Of note, all current FDA-approved PIs are competitive inhibitors, i.e., inhibitors that compete with substrates for the active enzymatic site. This common inhibitory approach increases the likelihood of developing drug resistant HIV-1 strains that are resistant to many or all current PIs. Hence, new PIs that move away from the current target of the active enzymatic site are needed. Specifically, allosteric inhibitors, inhibitors that prohibit PR enzymatic activities through non-competitive binding to PR, should be sought. Another common feature of current PIs is they were all developed based on the structure-based design. Drugs derived from a structure-based strategy may generate target specific and potent inhibitors. However, this type of drug design can only target one site at a time and drugs discovered by this method are often associated with strong side effects such as cellular toxicity, limiting its number of target choices, efficacy, and applicability. In contrast, a cell-based system may provide a useful alternative strategy that can overcome many of the inherited shortcomings associated with structure-based drug designs. For example, allosteric PIs can be sought using a cell-based system without considering the site or mechanism of inhibition. In addition, a cell-based system can eliminate those PIs that have strong cytotoxic effect. Most importantly, a simple, economical, and easy-to-maintained eukaryotic cellular system such as yeast will allow us to search for potential PIs in a large-scaled high throughput screening (HTS) system, thus increasing the chances of success. Based on our many years of experience in using fission yeast as a model system to study HIV-1 Vpr, we propose the use of fission yeast as a possible surrogate system to study the effects of HIV-1 protease on cellular functions and to explore its utility as a HTS system to search for new PIs to battle HIV-1 resistant strains.

Comparison of tertiary structures of proteins in protein-protein complexes with unbound forms suggests prevalence of allostery in signalling proteins

BACKGROUND

Most signalling and regulatory proteins participate in transient protein-protein interactions during biological processes. They usually serve as key regulators of various cellular processes and are often stable in both protein-bound and unbound forms. Availability of high-resolution structures of their unbound and bound forms provides an opportunity to understand the molecular mechanisms involved. In this work, we have addressed the question "What is the nature, extent, location and functional significance of structural changes which are associated with formation of protein-protein complexes?"

RESULTS

A database of 76 non-redundant sets of high resolution 3-D structures of protein-protein complexes, representing diverse functions, and corresponding unbound forms, has been used in this analysis. Structural changes associated with protein-protein complexation have been investigated using structural measures and Protein Blocks description. Our study highlights that significant structural rearrangement occurs on binding at the interface as well as at regions away from the interface to form a highly specific, stable and functional complex. Notably, predominantly unaltered interfaces interact mainly with interfaces undergoing substantial structural alterations, revealing the presence of at least one structural regulatory component in every complex.Interestingly, about one-half of the number of complexes, comprising largely of signalling proteins, show substantial localized structural change at surfaces away from the interface. Normal mode analysis and available information on functions on some of these complexes suggests that many of these changes are allosteric. This change is largely manifest in the proteins whose interfaces are altered upon binding, implicating structural change as the possible trigger of allosteric effect. Although large-scale studies of allostery induced by small-molecule effectors are available in literature, this is, to our knowledge, the first study indicating the prevalence of allostery induced by protein effectors.

CONCLUSIONS

The enrichment of allosteric sites in signalling proteins, whose mutations commonly lead to diseases such as cancer, provides support for the usage of allosteric modulators in combating these diseases.

Sequence evolution correlates with structural dynamics

Biochemical activity and core stability are essential properties of proteins, maintained usually by conserved amino acids. Structural dynamics emerged in recent years as another essential aspect of protein functionality. Structural dynamics enable the adaptation of the protein to binding substrates and to undergo allosteric transitions, while maintaining the native fold. Key residues that mediate structural dynamics would thus be expected to be conserved or exhibit coevolutionary patterns at least. Yet, the correlation between sequence evolution and structural dynamics is yet to be established. With recent advances in efficient characterization of structural dynamics, we are now in a position to perform a systematic analysis. In the present study, a set of 34 enzymes representing various folds and functional classes is analyzed using information theory and elastic network models. Our analysis shows that the structural regions distinguished by their coevolution propensity as well as high mobility are predisposed to serve as substrate recognition sites, whereas residues acting as global hinges during collective dynamics are often supported by conserved residues. We propose a mobility scale for different types of amino acids, which tends to vary inversely with amino acid conservation. Our findings suggest the balance between physical adaptability (enabled by structure-encoded motions) and chemical specificity (conferred by correlated amino acid substitutions) underlies the selection of a relatively small set of versatile folds by proteins.

Molecular dynamics of Mycobacterium tuberculosis KasA: implications for inhibitor and substrate binding and consequences for drug design

Inhibition of the production of fatty acids as essential components of the mycobacterial cell wall has been an established way of fighting tuberculosis for decades. However, increasing resistances and an outdated medical treatment call for the validation of new targets involved in this crucial pathway. In this regard, the β-ketoacyl ACP synthase KasA is a promising enzyme. In this study, three molecular dynamics simulations based on the wildtype crystal structures of inhibitor bound and unbound KasA were performed in order to investigate the flexibility and conformational space of this target. We present an exhaustive analysis of the binding-site flexibility and representative pocket conformations that may serve as new starting points for structure-based drug design. We also revealed a mechanism which may account for the comparatively low binding affinity of thiolactomycin. Furthermore, we examined the behavior of water molecules within the binding pocket and provide recommendations how to handle them in the drug design process. Finally, we analyzed the dynamics of a channel that accommodates the long-chain fatty acid substrates and, thereby, propose a mechanism of substrate access to this channel and how products are most likely released.

Pocket-space maps to identify novel binding-site conformations in proteins

The identification of novel binding-site conformations can greatly assist the progress of structure-based ligand design projects. Diverse pocket shapes drive medicinal chemistry to explore a broader chemical space and thus present additional opportunities to overcome key drug discovery issues such as potency, selectivity, toxicity, and pharmacokinetics. We report a new automated approach to diverse pocket selection, PocketAnalyzer(PCA), which applies principal component analysis and clustering to the output of a grid-based pocket detection algorithm. Since the approach works directly with pocket shape descriptors, it is free from some of the problems hampering methods that are based on proxy shape descriptors, e.g. a set of atomic positional coordinates. The approach is technically straightforward and allows simultaneous analysis of mutants, isoforms, and protein structures derived from multiple sources with different residue numbering schemes. The PocketAnalyzer(PCA) approach is illustrated by the compilation of diverse sets of pocket shapes for aldose reductase and viral neuraminidase. In both cases this allows identification of novel computationally derived binding-site conformations that are yet to be observed crystallographically. Indeed, known inhibitors capable of exploiting these novel binding-site conformations are subsequently identified, thereby demonstrating the utility of PocketAnalyzer(PCA) for rationalizing and improving the understanding of the molecular basis of protein-ligand interaction and bioactivity. A Python program implementing the PocketAnalyzer(PCA) approach is available for download under an open-source license ( http://sourceforge.net/projects/papca/ or http://cpclab.uni-duesseldorf.de/downloads ).

Overview of computational methods employed in early-stage drug discovery

BACKGROUND

The understanding of biomolecular interactions ultimately depends on knowledge about the structural and dynamic details of the interacting system. Rational structure-based drug design implements computational methodology in this rationale.

DISCUSSION

Together with increasing throughput of structural biology, molecular modeling has progressively contributed to rational drug design and elucidation of nontoxic and patient-tailored interventions, helping to make drug development more cost-efficient. But in this challenging time for the pharmaceutical industry, the successful discovery of novel therapeutics should rely on integration of computational modeling with experimentation when it comes to ligand-binding energetics, system flexibility and genetic diversity/heterogeneity of the target. Moreover, it appears that many drugs--even those for which specific receptors have been identified--intercalate in biological membranes, which could also become the actual target.

CONCLUSIONS

Understanding the drug-target and drug-unwanted-target interactions at the atomic level is fundamental in the initial phases of the drug development process. Molecular dynamics simulations and complementary computational methods are already contributing in this endeavor for the soluble pharmacological targets and show an increasing importance in the understanding of membrane-ligand interactions.

An accurate feature-based method for identifying DNA-binding residues on protein surfaces

Proteins that interact with DNA play vital roles in all mechanisms of gene expression and regulation. In order to understand these activities, it is crucial to analyze and identify DNA-binding residues on DNA-binding protein surfaces. Here, we proposed two novel features B-factor and packing density in combination with several conventional features to characterize the DNA-binding residues in a well-constructed representative dataset of 119 protein-DNA complexes from the Protein Data Bank (PDB). Based on the selected features, a prediction model for DNA-binding residues was constructed using support vector machine (SVM). The predictor was evaluated using a 5-fold cross validation on above dataset of 123 DNA-binding proteins. Moreover, two independent datasets of 83 DNA-bound protein structures and their corresponding DNA-free forms were compiled. The B-factor and packing density features were statistically analyzed on these 83 pairs of holo-apo proteins structures. Finally, we developed the SVM model to accurately predict DNA-binding residues on protein surface, given the DNA-free structure of a protein. Results showed here indicate that our method represents a significant improvement of previously existing approaches such as DISPLAR. The observation suggests that our method will be useful in studying protein-DNA interactions to guide consequent works such as site-directed mutagenesis and protein-DNA docking.

Phosfinder: a web server for the identification of phosphate-binding sites on protein structures

Phosfinder is a web server for the identification of phosphate binding sites in protein structures. Phosfinder uses a structural comparison algorithm to scan a query structure against a set of known 3D phosphate binding motifs. Whenever a structural similarity between the query protein and a phosphate binding motif is detected, the phosphate bound by the known motif is added to the protein structure thus representing a putative phosphate binding site. Predicted binding sites are then evaluated according to (i) their position with respect to the query protein solvent-excluded surface and (ii) the conservation of the binding residues in the protein family. The server accepts as input either the PDB code of the protein to be analyzed or a user-submitted structure in PDB format. All the search parameters are user modifiable. Phosfinder outputs a list of predicted binding sites with detailed information about their structural similarity with known phosphate binding motifs, and the conservation of the residues involved. A graphical applet allows the user to visualize the predicted binding sites on the query protein structure. The results on a set of 52 apo/holo structure pairs show that the performance of our method is largely unaffected by ligand-induced conformational changes. Phosfinder is available at http://phosfinder.bio.uniroma2.it.

PoPMuSiC 2.1: a web server for the estimation of protein stability changes upon mutation and sequence optimality

Background

The rational design of modified proteins with controlled stability is of extreme importance in a whole range of applications, notably in the biotechnological and environmental areas, where proteins are used for their catalytic or other functional activities. Future breakthroughs in medical research may also be expected from an improved understanding of the effect of naturally occurring disease-causing mutations on the molecular level.

Results

PoPMuSiC-2.1 is a web server that predicts the thermodynamic stability changes caused by single site mutations in proteins, using a linear combination of statistical potentials whose coefficients depend on the solvent accessibility of the mutated residue. PoPMuSiC presents good prediction performances (correlation coefficient of 0.8 between predicted and measured stability changes, in cross validation, after exclusion of 10% outliers). It is moreover very fast, allowing the prediction of the stability changes resulting from all possible mutations in a medium size protein in less than a minute. This unique functionality is user-friendly implemented in PoPMuSiC and is particularly easy to exploit. Another new functionality of our server concerns the estimation of the optimality of each amino acid in the sequence, with respect to the stability of the structure. It may be used to detect structural weaknesses, i.e. clusters of non-optimal residues, which represent particularly interesting sites for introducing targeted mutations. This sequence optimality data is also expected to have significant implications in the prediction and the analysis of particular structural or functional protein regions. To illustrate the interest of this new functionality, we apply it to a dataset of known catalytic sites, and show that a much larger than average concentration of structural weaknesses is detected, quantifying how these sites have been optimized for function rather than stability.

Conclusion

The freely available PoPMuSiC-2.1 web server is highly useful for identifying very rapidly a list of possibly relevant mutations with the desired stability properties, on which subsequent experimental studies can be focused. It can also be used to detect sequence regions corresponding to structural weaknesses, which could be functionally important or structurally delicate regions, with obvious applications in rational protein design.