Measurement of DNA-protein equilibria using gel chromatography: application to the HinfI restriction endonuclease

A method is described for measuring equilibrium constants of DNA-protein interactions using gel chromatography. This technique has been used to study the sequence-specific interaction of the HinfI restriction endonuclease with DNA. HinfI has a monomeric molecular weight of 31000 and exists as a dimer in its active form. The protein binds to supercoiled DNA molecules containing its recognition site with an apparent free energy of -13.9 kcal/mol of sites. This interaction is highly salt sensitive and causes a release of 3.4 ion pairs. The affinity of the nuclease for its recognition site is largely independent of both pH (6.5-8.5) and temperature (7-35 degrees C) and was not affected by variations in the degenerate middle position of the site. Linear DNA fragments containing the HinfI recognition site were bound as tightly as supercoiled molecules. Binding to nonspecific DNA sites or to methylated DNA sites was approximately 6 orders of magnitude weaker. In general, enzyme activity and binding affinity paralleled each other.     

Generating quantitative models describing the sequence specificity of biological processes with the stabilized matrix method

Background  

Many processes in molecular biology involve the recognition of short sequences of nucleic-or amino acids, such as the binding of immunogenic peptides to major histocompatibility complex (MHC) molecules. From experimental data, a model of the sequence specificity of these processes can be constructed, such as a sequence motif, a scoring matrix or an artificial neural network. The purpose of these models is two-fold. First, they can provide a summary of experimental results, allowing for a deeper understanding of the mechanisms involved in sequence recognition. Second, such models can be used to predict the experimental outcome for yet untested sequences. In the past we reported the development of a method to generate such models called the Stabilized Matrix Method (SMM). This method has been successfully applied to predicting peptide binding to MHC molecules, peptide transport by the transporter associated with antigen presentation (TAP) and proteasomal cleavage of protein sequences.     

An automated computer vision and roboticsbased technique for 3-D flexible biomolecular docking and matching

The generation of binding modes between two molecules, alsoknown as molecular docking, is a key problem in rational drugdesign and biomolecular recognition. Docking a ligand, e.g.,a drug molecule or a protein molecule, to a protein receptor,involves recognition of molecular surfaces as molecules interactat their surface. Recent studies report that the activity ofmany molecules induces conformational transitions by ‘hinge-bending’,which involves movements of relatively rigid parts with respectto each other. In ligand–receptor binding, relative rotationalmovements of molecu–lar substructures about their commonhinges have been observed. For automatically predicting flexiblemolecular interactions, we adapt a new technique developed inComputer Vision and Robotics for the efficient recognition ofpartially occluded articulated objects. These type of objectsconsist of rigid parts which are connected by rotary joints(hinges). Our approach is based on an extension and generalizationof the Geometric Hashing and Generalized Hough Transform paradigmfor rigid object recognition. Unlike other techniques whichmatch each part individually, our approach exploits forcefullyand efficiently enough the fact that the different rigid partsdo belong to the same flexible molecule. We show experimentalresults obtained by an implementation of the algorithm for rigidand flexible docking. While the ‘correct’, crystal–boundcomplex is obtained with a small RMSD, additional, predictive‘high scoring’ binding modes are generated as well.The diverse applications and implications of this general, powerfultool are discussed     

Ligand binding affinity determined by temperature-dependent circular dichroism: cyclin-dependent kinase 2 inhibitors

To support drug discovery efforts for cyclin-dependent kinase 2 (CDK2), a moderate-throughput binding assay that can rank order or estimate the affinity of lead inhibitors has been developed. The method referred to as temperature-dependent circular dichroism (TdCD) uses the classical temperature-dependent unfolding of proteins by circular dichroism (CD) to measure the degree of protein unfolding in the absence and presence of potential inhibitors. The midpoint of unfolding is the Tm value. Rank ordering the affinity and predictions of the dissociation constant of compounds is obtained by measuring the increase in Tm for different protein-inhibitor complexes. This is the first time an extensive characterization of the TdCD method has been described for characterizing lead inhibitors in a drug discovery mode. The method has several favorable properties. Using the new six-cell Peltier temperature controller for the Jasco 810 spectropolarimeter, one can determine the affinity of 12-18 compounds per day. The method also requires only 20-40 microg protein per sample and can be used to estimate the affinity of compounds with dissociation constants of picomolar to micromolar. An important property of the method for lead discovery is that dissociation constants of approximately 5 microM can be estimated from a single experiment using a low concentration of compound such as 20 microM, which is generally low enough for most small molecules to be soluble for testing. In addition, the method does not require labeling the compound or protein. Although other methods such as isothermal titration calorimetry (ITC) can provide a full thermodynamic characterization of binding, ITC requires 1-2 mg protein per sample, cannot readily determine binding constants below nanomolar values, is most versatile with soluble compounds, and has a throughput of two to three experiments per day. The ITC method is not usually used in a high-throughput drug discovery mode; however, using the thermodynamic information from several ITC experiments can make the TdCD method very robust in determining reliable binding constants. Using the kinase inhibitors BMS-250595, purvalanol B, AG-12275, flavopiridol, and several other compounds, it is demonstrated that one can obtain excellent comparisons between the Kd values of binding to CDK2 obtained by TdCD and ITC.     

Automated docking of peptides and proteins by using a genetic algorithm combined with a tabu search.

A genetic algorithm (GA) combined with a tabu search (TA) has been applied as a minimization method to rake the appropriate associated sites for some biomolecular systems. In our docking procedure, surface complementarity and energetic complementarity of a ligand with its receptor have been considered separately in a two-stage docking method. The first stage was to find a set of potential associated sites mainly based on surface complementarity using a genetic algorithm combined with a tabu search. This step corresponds with the process of finding the potential binding sites where pharmacophores will bind. In the second stage, several hundreds of GA minimization steps were performed for each associated site derived from the first stage mainly based on the energetic complementarity. After calculations for both of the two stages, we can offer several solutions of associated sites for every complex. In this paper, seven biomolecular systems, including five bound complexes and two unbound complexes, were chosen from the Protein Data Bank (PDB) to test our method. The calculated results were very encouraging-the hybrid minimization algorithm successfully reaches the correct solutions near the best binded modes for these protein complexes. The docking results not only predict the bound complexes very well, but also get a relatively accurate complexed conformation for unbound systems. For the five bound complexes, the results show that surface complementarity is enough to find the precise binding modes, the top solution from the tabu list generally corresponds to the correct binding mode. For the two unbound complexes, due to the conformational changes upon binding, it seems more difficult to get their correct binding conformations. The predicted results show that the correct binding mode also corresponds to a relatively large surface complementarity score. In these two test cases, the correct solution can be found in the top several solutions from the tabu list. For unbound complexes, the interaction energy from energetic complementarity is very important, it can be used to filter these solutions from the surface complementarity. After the evaluation of the energetic complementarity, the conformations and orientations close to the crystallographically determined structures are resolved. In most cases, the smallest root mean square distance (r.m.s.d.) from the GA combined with TA solutions is in a relatively small region. Our program of automatic docking is really a universal one among the procedures used for the theoretical study of molecular recognition.     

Pattern recognition based on color-coded quantum mechanical surfaces for molecular alignment

A pattern recognition algorithm for the alignment of drug-like molecules has been implemented. The method is based on the calculation of quantum mechanical derived local properties defined on a molecular surface. This approach has been shown to be very useful in attempting to derive generalized, non-atom based representations of molecular structure. The visualization of these surfaces is described together with details of the methodology developed for their use in molecular overlay and similarity calculations. In addition, this paper also introduces an additional local property, the local curvature (C _L), which can be used together with the quantum mechanical properties to describe the local shape. The method is exemplified using some problems representing common tasks encountered in molecular similarity. Figure Molecular surfaces for Lorazepam (left) and Diazepam (right)     

Determination of best-fit potential parameters for a reactive force field using a genetic algorithm

The ReaxFF interatomic potential, used for organic materials, involves more than 600 adjustable parameters, the best-fit values of which must be determined for different materials. A new method of determining the set of best-fit parameters for specific molecules containing carbon, hydrogen, nitrogen and oxygen is presented, based on a parameter reduction technique followed by genetic algorithm (GA) minimization. This work has two novel features. The first is the use of a parameter reduction technique to determine which subset of parameters plays a significant role for the species of interest; this is necessary to reduce the optimization space to manageable levels. The second is the application of the GA technique to a complex potential (ReaxFF) with a very large number of adjustable parameters, which implies a large parameter space for optimization. In this work, GA has been used to optimize the parameter set to determine best-fit parameters that can reproduce molecular properties to within a given accuracy. As a test problem, the use of the algorithm has been demonstrated for nitromethane and its decomposition products.     

A method for biomolecular structural recognition and docking allowing conformational flexibility.

In this work, we present an algorithm developed to handle biomolecular structural recognition problems, as part of an interdisciplinary research endeavor of the Computer Vision and Molecular Biology fields. A key problem in rational drug design and in biomolecular structural recognition is the generation of binding modes between two molecules, also known as molecular docking. Geometrical fitness is a necessary condition for molecular interaction. Hence, docking a ligand (e.g., a drug molecule or a protein molecule), to a protein receptor (e.g., enzyme), involves recognition of molecular surfaces. Conformational transitions by "hinge-bending" involves rotational movements of relatively rigid parts with respect to each other. The generation of docked binding modes between two associating molecules depends on their three dimensional structures (3-D) and their conformational flexibility. In comparison to the particular case of rigid-body docking, the computational difficulty grows considerably when taking into account the additional degrees of freedom intrinsic to the flexible molecular docking problem. Previous docking techniques have enabled hinge movements only within small ligands. Partial flexibility in the receptor molecule is enabled by a few techniques. Hinge-bending motions of protein receptors domains are not addressed by these methods, although these types of transitions are significant, e.g., in enzymes activity. Our approach allows hinge induced motions to exist in either the receptor or the ligand molecules of diverse sizes. We allow domains/subdomains/group of atoms movements in either of the associating molecules. We achieve this by adapting a technique developed in Computer Vision and Robotics for the efficient recognition of partially occluded articulated objects. These types of objects consist of rigid parts which are connected by rotary joints (hinges). Our method is based on an extension and generalization of the Hough transform and the Geometric Hashing paradigms for rigid object recognition. We show experimental results obtained by the successful application of the algorithm to cases of bound and unbound molecular complexes, yielding fast matching times. While the "correct" molecular conformations of the known complexes are obtained with small RMS distances, additional, predictive good-fitting binding modes are generated as well. We conclude by discussing the algorithm's implications and extensions, as well as its application to investigations of protein structures in Molecular Biology and recognition problems in Computer Vision.     

A hierarchical method for molecular docking using cloud computing

Discovering small molecules that interact with protein targets will be a key part of future drug discovery efforts. Molecular docking of drug-like molecules is likely to be valuable in this field; however, the great number of such molecules makes the potential size of this task enormous. In this paper, a method to screen small molecular databases using cloud computing is proposed. This method is called the hierarchical method for molecular docking and can be completed in a relatively short period of time. In this method, the optimization of molecular docking is divided into two subproblems based on the different effects on the protein–ligand interaction energy. An adaptive genetic algorithm is developed to solve the optimization problem and a new docking program (FlexGAsDock) based on the hierarchical docking method has been developed. The implementation of docking on a cloud computing platform is then discussed. The docking results show that this method can be conveniently used for the efficient molecular design of drugs.     

McVol - A program for calculating protein volumes and identifying cavities by a Monte Carlo algorithm

In this paper, we describe a Monte Carlo method for determining the volume of a molecule. A molecule is considered to consist of hard, overlapping spheres. The surface of the molecule is defined by rolling a probe sphere over the surface of the spheres. To determine the volume of the molecule, random points are placed in a three-dimensional box, which encloses the whole molecule. The volume of the molecule in relation to the volume of the box is estimated by calculating the ratio of the random points placed inside the molecule and the total number of random points that were placed. For computational efficiency, we use a grid-cell based neighbor list to determine whether a random point is placed inside the molecule or not. This method in combination with a graph-theoretical algorithm is used to detect internal cavities and surface clefts of molecules. Since cavities and clefts are potential water binding sites, we place water molecules in the cavities. The potential water positions can be used in molecular dynamics calculations as well as in other molecular calculations. We apply this method to several proteins and demonstrate the usefulness of the program. The described methods are all implemented in the program McVol, which is available free of charge from our website at .     

Sexual communication in copepods and rotifers

The problem of locating mates and identifying them as conspecifics is similar for Copepoda, Cladocera, and Rotifera since they are all relatively small animals moving in a large volume of water. Chemoreception is a potentially effective means of identifying mates in aquatic environments. In zooplankton, mate recognition systems based on chemoreception have evolved which can distinguish conspecifics from other species and can discriminate males from females. The evidence for the role of chemical signals in copepod mating is indirect, based on observations of mating behavior. The small size and limited metabolic capability of zooplankton, and high diffusion rates at 1–10 mm spatial scales, restrict the volume through which chemical signals can be effectively transmitted. An alternative to using diffusible molecules for sexual communication is to bind signal molecules to cell surfaces, allowing energetically costly molecules like proteins to serve as signals without their loss through diffusion. Contact chemoreception has been described in copepod and rotifer mating and perhaps represents a general solution to the problem of chemical communication by small zooplankters. The types of signals used, their mechanisms of transmission and reception, and their role in maintaining reproductive isolation among species has yet to be characterized for any aquatic invertebrate. In this review, I compare the methods used by copepods and rotifers for mate seeking and recognition, describe the behavioral evidence supporting the existence of chemical cues, and examine experiments describing the biochemical characteristics of the signal molecules. In copepods, male mate seeking behavior occurs without previous female contact, suggesting the reception of a diffusible signal. The signal molecule is small and lacks species specificity in the species investigated. Male rotifers do not respond to females from a distance. Mates are located by random male swimming and contact chemoreception of a species-specific signal. Mate recognition in both copepods and rotifers is based on contact chemoreception of a species-specific signal. The pheromones responsible are not known for copepods, but surface glycoproteins with pheromonal activity have been identified in rotifers. The structure of the rotifer sex pheromone has been probed by selective enzymatic degradation and lectin binding, electrophoretic characterization, and attachment to agarose beads to assess its biological activity. Glycoproteins play a key role in the sexual communication of some algal and ciliate species and have well characterized roles in cellular recognition phenomena like sperm-egg binding. The significance of these studies lies in their contribution to our understanding of zooplankton reproductive biology, the chemical ecology of male-female communication, the molecular basis of chemoreception in the aquatic environment, and the evolution of pre-mating reproductive isolating mechanisms in zooplankton.     

Resistance Gene Analogues as a Tool for Rapid Identification and Cloning of Disease Resistance Genes in Plants 3 A Review

Most of the disease resistance genes (R-genes) discovered in plants have conserved functional domains, predominantly among them are nucleotide binding sites (NBS) and leucine rich repeats (LRR). The sequence information of the conserved domains can be invariably used to mine similar sequences from other plant species, using degenerate and specific primers for their amplification in a polymerase chain reaction. Such derived sequences, known as Resistance Gene Analogues (RGAs), can serve as molecular markers for rapid identification and isolation of R-genes. Besides, they can also provide clues about the evolutionary mechanism of resistance genes and the interaction involved in pathogen recognition. In the recent years, this sequence-homology based approach has been used extensively for the cloning and mapping of RGAs in cereals, pulses, oilseeds, coffee, spices, forest trees and horticultural crops. In this article, the current status of cloning of RGAs from different crops has been reviewed. A general method of RGA cloning and its modifications like NBS-profiling and AFLP-NBS have also been discussed along with examples. Further, it has been suggested that the RGAs cloned in various crops would be a useful genomic resource for developing cultivars with durable resistance to diseases in different crop breeding programmes.     

A new method to detect related function among proteins independent of sequence and fold homology

A new method has been developed to detect functional relationships among proteins independent of a given sequence or fold homology. It is based on the idea that protein function is intimately related to the recognition and subsequent response to the binding of a substrate or an endogenous ligand in a well-characterized binding pocket. Thus, recognition of similar ligands, supposedly linked to similar function, requires conserved recognition features exposed in terms of common physicochemical interaction properties via the functional groups of the residues flanking a particular binding cavity. Following a technique commonly used in the comparison of small molecule ligands, generic pseudocenters coding for possible interaction properties were assigned for a large sample set of cavities extracted from the entire PDB and stored in the database Cavbase. Using a particular query cavity a series of related cavities of decreasing similarity is detected based on a clique detection algorithm. The detected similarity is ranked according to property-based surface patches shared in common by the different clique solutions. The approach either retrieves protein cavities accommodating the same (e.g. co-factors) or closely related ligands or it extracts proteins exhibiting similar function in terms of a related catalytic mechanism. Finally the new method has strong potential to suggest alternative molecular skeletons in de novo design. The retrieval of molecular building blocks accommodated in a particular sub-pocket that shares similarity with the pocket in a protein studied by drug design can inspire the discovery of novel ligands.     

The betaI/betaIII-tubulin isoforms and their complexes with antimitotic agents. Docking and molecular dynamics studies

Both microtubule destabilizer and stabilizer agents are important molecules in anticancer therapy. In particular, paclitaxel has been demonstrated to be effective for the treatment of ovarian, breast, and nonsmall cell lung carcinomas. It has been shown that emergence of resistance against this agent correlates with an increase in the relative abundance of tubulin isoform betaIII and that the more recently discovered IDN5390 can be effectively used once resistance has emerged. In this paper, we analyze the binding modes of these antimitotic agents to type I and III isoforms of beta-tubulin by computational methods. Our results are able to provide a molecular explanation of the experimental data. Using the same protocol, we could also show that no preference for any of the two isoforms can be detected for epothilone A, a potentially very interesting drug for which no data about the emergence of resistance is currently available. Our analysis provides structural insights about the recognition mode and the stabilization mechanism of these antimitotic agents and provides useful suggestions for the design of more potent and selective antimitotic agents.     

The Interactions of Allium sativum leaf agglutinin with a chaperonin group of unique receptor protein isolated from a bacterial endosymbiont of the mustard aphid

The homopteran sucking insect, Lipaphis erysimi (mustard aphid) causes severe damage to various crops. This pest not only affects plants by sucking on the phloem, but it also transmits single-stranded RNA luteoviruses while feeding, which cause disease and damage in the crop. The mannose-binding Allium sativum (garlic) leaf lectin has been found to be a potent control agent of L. erysimi. The lectin receptor protein isolated from brush border membrane vesicle of insect gut was purified to determine the mechanism of lectin binding to the gut. Purified receptor was identified as an endosymbiotic chaperonin, symbionin, using liquid chromatography-tandem mass spectrometry. Symbionin from endosymbionts of other aphid species have been reported to play a significant role in virus transmission by binding to the read-through domain of the viral coat protein. To understand the molecular interactions of the said lectin and this unique symbionin molecule, the model structures of both molecules were generated using the Modeller program. The interaction was confirmed through docking of the two molecules forming a complex. A surface accessibility test of these molecules demonstrated a significant reduction in the accessibility of the complex molecule compared with that of the free symbionin molecule. This reduction in surface accessibility may have an effect on other molecular interactive processes, including "symbionin virion recognition", which is essential for such symbionin-mediated virus transmission. Thus, garlic leaf lectin provides an important component of a crop management program by controlling, on one hand, aphid attack and on the other hand, symbionin-mediated luteovirus transmission.     

Evidence of Conformational Selection Driving the Formation of Ligand Binding Sites in Protein-Protein Interfaces

Many protein-protein interactions (PPIs) are compelling targets for drug discovery, and in a number of cases can be disrupted by small molecules. The main goal of this study is to examine the mechanism of binding site formation in the interface region of proteins that are PPI targets by comparing ligand-free and ligand-bound structures. To avoid any potential bias, we focus on ensembles of ligand-free protein conformations obtained by nuclear magnetic resonance (NMR) techniques and deposited in the Protein Data Bank, rather than on ensembles specifically generated for this study. The measures used for structure comparison are based on detecting binding hot spots, i.e., protein regions that are major contributors to the binding free energy. The main tool of the analysis is computational solvent mapping, which explores the surface of proteins by docking a large number of small “probe” molecules. Although we consider conformational ensembles obtained by NMR techniques, the analysis is independent of the method used for generating the structures. Finding the energetically most important regions, mapping can identify binding site residues using ligand-free models based on NMR data. In addition, the method selects conformations that are similar to some peptide-bound or ligand-bound structure in terms of the properties of the binding site. This agrees with the conformational selection model of molecular recognition, which assumes such pre-existing conformations. The analysis also shows the maximum level of similarity between unbound and bound states that is achieved without any influence from a ligand. Further shift toward the bound structure assumes protein-peptide or protein-ligand interactions, either selecting higher energy conformations that are not part of the NMR ensemble, or leading to induced fit. Thus, forming the sites in protein-protein interfaces that bind peptides and can be targeted by small ligands always includes conformational selection, although other recognition mechanisms may also be involved.     

Features of molecular recognition of intrinsically disordered proteins via coupled folding and binding

The sequence–structure–function paradigm of proteins has been revolutionized by the discovery of intrinsically disordered proteins (IDPs) or intrinsically disordered regions (IDRs). In contrast to traditional ordered proteins, IDPs/IDRs are unstructured under physiological conditions. The absence of well‐defined three‐dimensional structures in the free state of IDPs/IDRs is fundamental to their function. Folding upon binding is an important mode of molecular recognition for IDPs/IDRs. While great efforts have been devoted to investigating the complex structures and binding kinetics and affinities, our knowledge on the binding mechanisms of IDPs/IDRs remains very limited. Here, we review recent advances on the binding mechanisms of IDPs/IDRs. The structures and kinetic parameters of IDPs/IDRs can vary greatly, and the binding mechanisms can be highly dependent on the structural properties of IDPs/IDRs. IDPs/IDRs can employ various combinations of conformational selection and induced fit in a binding process, which can be templated by the target and/or encoded by the IDP/IDR. Further studies should provide deeper insights into the molecular recognition of IDPs/IDRs and enable the rational design of IDP/IDR binding mechanisms in the future.     

Computational Analysis of Phosphopeptide Binding to the Polo-Box Domain of the Mitotic Kinase PLK1 Using Molecular Dynamics Simulation

The Polo-Like Kinase 1 (PLK1) acts as a central regulator of mitosis and is over-expressed in a wide range of human tumours where high levels of expression correlate with a poor prognosis. PLK1 comprises two structural elements, a kinase domain and a polo-box domain (PBD). The PBD binds phosphorylated substrates to control substrate phosphorylation by the kinase domain. Although the PBD preferentially binds to phosphopeptides, it has a relatively broad sequence specificity in comparison with other phosphopeptide binding domains. We analysed the molecular determinants of recognition by performing molecular dynamics simulations of the PBD with one of its natural substrates, CDC25c. Predicted binding free energies were calculated using a molecular mechanics, Poisson-Boltzmann surface area approach. We calculated the per-residue contributions to the binding free energy change, showing that the phosphothreonine residue and the mainchain account for the vast majority of the interaction energy. This explains the very broad sequence specificity with respect to other sidechain residues. Finally, we considered the key role of bridging water molecules at the binding interface. We employed inhomogeneous fluid solvation theory to consider the free energy of water molecules on the protein surface with respect to bulk water molecules. Such an analysis highlights binding hotspots created by elimination of water molecules from hydrophobic surfaces. It also predicts that a number of water molecules are stabilized by the presence of the charged phosphate group, and that this will have a significant effect on the binding affinity. Our findings suggest a molecular rationale for the promiscuous binding of the PBD and highlight a role for bridging water molecules at the interface. We expect that this method of analysis will be very useful for probing other protein surfaces to identify binding hotspots for natural binding partners and small molecule inhibitors.