Speech-based characterization of dopamine replacement therapy in people with Parkinson's disease.

People with Parkinson's (PWP) disease are under constant tension with respect to their dopamine replacement therapy (DRT) regimen. Waiting too long between doses results in more prominent symptoms, loss of motor function, and greater risk of falling per step. Shortened pill cycles can lead to accelerated habituation and faster development of disabling dyskinesias. The Unified Parkinson's Disease Rating Scale (MDS-UPDRS) is the gold standard for monitoring Parkinson's disease progression but requires a neurologist to administer and therefore is not an ideal instrument to continuously evaluate short-term disease fluctuations. We investigated the feasibility of using speech to detect changes in medication states, based on expectations of subtle changes in voice and content related to dopaminergic levels. We calculated acoustic and prosodic features for three speech tasks (picture description, reverse counting, and diadochokinetic rate) for 25 PWP, each evaluated "ON" and "OFF" DRT. Additionally, we generated semantic features for the picture description task. Classification of ON/OFF medication states using features generated from picture description, reverse counting and diadochokinetic rate tasks resulted in cross-validated accuracy rates of 0.89, 0.84, and 0.60, respectively. The most discriminating task was picture description which provided evidence that participants are more likely to use action words in ON than in OFF state. We also found that speech tempo was modified by DRT. Our results suggest that automatic speech assessment can capture changes associated with the DRT cycle. Given the ease of acquiring speech data, this method shows promise to remotely monitor DRT effects.

Electrostatic contributions to protein-protein interactions: fast energetic filters for docking and their physical basis.

The methods of continuum electrostatics are used to calculate the binding free energies of a set of protein-protein complexes including experimentally determined structures as well as other orientations generated by a fast docking algorithm. In the native structures, charged groups that are deeply buried were often found to favor complex formation (relative to isosteric nonpolar groups), whereas in nonnative complexes generated by a geometric docking algorithm, they were equally likely to be stabilizing as destabilizing. These observations were used to design a new filter for screening docked conformations that was applied, in conjunction with a number of geometric filters that assess shape complementarity, to 15 antibody-antigen complexes and 14 enzyme-inhibitor complexes. For the bound docking problem, which is the major focus of this paper, native and near-native solutions were ranked first or second in all but two enzyme-inhibitor complexes. Less success was encountered for antibody-antigen complexes, but in all cases studied, the more complete free energy evaluation was able to identify native and near-native structures. A filter based on the enrichment of tyrosines and tryptophans in antibody binding sites was applied to the antibody-antigen complexes and resulted in a native and near-native solution being ranked first and second in all cases. A clear improvement over previously reported results was obtained for the unbound antibody-antigen examples as well. The algorithm and various filters used in this work are quite efficient and are able to reduce the number of plausible docking orientations to a size small enough so that a final more complete free energy evaluation on the reduced set becomes computationally feasible.

Electrostatic aspects of protein-protein interactions.

Structural and mutational analyses reveal a central role for electrostatic interactions in protein-protein association. Experiment and theory both demonstrate that clusters of charged and polar residues that are located on protein-protein interfaces may enhance complex stability, although the total effect of electrostatics is generally net destabilizing. The past year also witnessed significant progress in our understanding of the effect of electrostatics on protein association kinetics, specifically in the characterization of a partially desolvated encounter complex.

Small molecule recognition: solid angles surface representation and molecular shape complementarity.

Here we examine the recognition of small molecules by their protein and DNA receptors. We focus on two questions: First, how well does the solid angle molecular surface representation perform in fitting together the surfaces of small ligands, such as drugs and cofactors to their corresponding receptors; And second, in particular, to what extent does the shape complementarity play a role in the matching (recognition) process of such small molecules. Both questions have been investigated in protein-protein binding: "Critical Points" based on solid angle calculations have been shown to perform well in the matching of large protein molecules. They are robust, may be few in numbers, and capture satisfactorily the molecular shape. Shape complementarity has been shown to be a critical factor in protein-protein recognition, but has not been examined in drug-receptor recognition. To probe these questions, here we dock 185 receptor-small ligand molecule pairs. We find that such a representation performs adequately for the smaller ligands too, and that shape complementarity is also observed. These issues are important, given the large databases of drugs that routinely have to be scanned to find candidate, lead compounds. We have been able to carry out such large scale docking experiments owing to our efficient, computer-vision based docking algorithms. Its fast CPU matching times, on the order of minutes on a PC, allows such large scale docking experiments.

Examination of shape complementarity in docking of unbound proteins.

Here we carry out an examination of shape complementarity as a criterion in protein-protein docking and binding. Specifically, we examine the quality of shape complementarity as a critical determinant not only in the docking of 26 protein-protein "bound" complexed cases, but in particular, of 19 "unbound" protein-protein cases, where the structures have been determined separately. In all cases, entire molecular surfaces are utilized in the docking, with no consideration of the location of the active site, or of particular residues/atoms in either the receptor or the ligand that participate in the binding. To evaluate the goodness of the strictly geometry-based shape complementarity in the docking process as compared to the main favorable and unfavorable energy components, we study systematically a potential correlation between each of these components and the root mean square deviation (RMSD) of the "unbound" protein-protein cases. Specifically, we examine the non-polar buried surface area, polar buried surface area, buried surface area relating to groups bearing unsatisfied buried charges, and the number of hydrogen bonds in all docked protein-protein interfaces. For these cases, where the two proteins have been crystallized separately, and where entire molecular surfaces are considered without a predefinition of the binding site, no correlation is observed. None of these parameters appears to consistently improve on shape complementarity in the docking of unbound molecules. These findings argue that simplicity in the docking process, utilizing geometrical shape criteria may capture many of the essential features in protein-protein docking. In particular, they further reinforce the long held notion of the importance of molecular surface shape complementarity in the binding, and hence in docking. This is particularly interesting in light of the fact that the structures of the docked pairs have been determined separately, allowing side chains on the surface of the proteins to move relatively freely. This study has been enabled by our efficient, computer vision-based docking algorithms. The fast CPU matching times, on the order of minutes on a PC, allow such large-scale docking experiments of large molecules, which may not be feasible by other techniques. Proteins 1999;36:307-317.

Two distinct binding sites for globotriaosyl ceramide on verotoxins: identification by molecular modelling and confirmation using deoxy analogues and a new glycolipid receptor for all verotoxins.

BACKGROUND: The Escherichia coli verotoxins (VTs) can initiate human vascular disease via the specific recognition of globotriaosyl-ceramide (Gb3) on target endothelial cells. To explore the structural basis for receptor recognition by different VTs we used molecular modelling based on the crystal structure of VT1, mutational data and binding data for deoxy galabiosyl receptors. RESULTS: We propose a model for the verotoxin 'cleft-site complex' with Gb3. Energy minimizations of Gb3 within the 'cleft site' of verotoxins VT1, VT2, VT2c and VT2e resulted in stable complexes with hydrogen-bonding systems that were in agreement with binding data obtained for mono-deoxy analogues of Gb3. N-deacetylated globoside (aminoGb4), which was found to be a new, efficient receptor for all verotoxins, can be favourably accommodated in the cleft site of the VTs by formation of a salt bridge between the galactosamine and a cluster of aspartates in the site. The model is further extended to explain the binding of globoside by VT2e. Docking data support the possibility of an additional binding site for Gb3 on VT1. CONCLUSIONS: The proposed models for the complexes of verotoxins with their globoglycolipid receptors are consistent with receptor analogue binding data and explain previously published mutational studies. The results provide a first approach to the design of specific inhibitors of VT-receptor binding.

Molecular surface complementarity at protein-protein interfaces: the critical role played by surface normals at well placed, sparse, points in docking.

Rigid-body docking of two molecules involves matching of their surfaces. A successful docking methodology considers two key issues: molecular surface representation, and matching. While approaches to the problem differ, they all employ certain surface geometric features. While surface normals are routinely created with molecular surfaces, their employment has surprisingly been almost completely overlooked. Here we show how the normals to the surface, at specific, well placed points, can play a critical role in molecular docking. If the points for which the normals are calculated represent faithfully and accurately the molecular surfaces, the normals can substantially ameliorate the efficiency of the docking in a number of ways. The normals can drastically reduce the combinatorial complexity of the receptor-ligand docking. Furthermore, they can serve as a powerful filter in screening for quality docked conformations. Below we show how deploying such a straight forward device, which is easy to calculate, large protein-protein molecules are docked with unparalleled short times and with a manageable number of potential solutions. Considering the facts that here we dock (1) two large protein molecules, including several large immunoglobulin-lysozyme complexes; (2) that we use the entire molecular surfaces, without a predefinition of the active sites, or of the epitopes, of neither the ligand nor the receptor; that (3) the docking is completely automated, without any labelling, or pre-specification, of the input structural database, and (4) with a single set of parameters, without any further tuning whatsoever, such results are highly desirable. This approach is specifically geared towards matching of the surfaces of large protein molecules and is not applicable to small molecule drugs.

Shape complementarity at protein-protein interfaces.

A matching algorithm using surface complementarity between receptor and ligand protein molecules is outlined. The molecular surfaces are represented by "critical points," describing holes and knobs. Holes (maxima of a shape function) are matched with knobs (minima). This simple and appealing surface representation has been previously described by Connolly [(1986) Biopolymers, Vol. 25, pp. 1229-1247]. However, attempts to implement this description in a docking scheme have been unsuccessful (e.g., Connolly, ibid.). In order to decrease the combinatorial complexity, and to make the execution time affordable, four critical hole/knob point matches were sought. This approach failed since some bound interfaces are relatively flat and do not possess four critical point matches. On the otherhand, matchings of fewer critical points require a very time-consuming, full conformational (grid) space search [Wang, (1991) Journal of Computational Chemistry, Vol. 12, pp. 746-750]. Here we show that despite the initial failure of this approach, with a simple and straightforward modification in the matching algorithm, this surface representation works well. Out of the 16 protein-protein complexes we have tried, 15 were successfully docked, including two immunoglobulins. The entire molecular surfaces were considered, with absolutely no additional information regarding the binding sites. The whole process is completely automated, with no manual intervention, either in the input atomic coordinate data, or in the matching. We have been able to reach this level of performance with the hole/knob surface description by using pairs of critical points along with their surface normals in the calculation of the transformation matrix. The success of this approach suggests that future docking methods should use geometric docking as the first screening filter.(ABSTRACT TRUNCATED AT 250 WORDS)

Molecular surface recognition by a computer vision-based technique.

Correct docking of a ligand onto a receptor surface is a complex problem, involving geometry and chemistry. Geometrically acceptable solutions require close contact between corresponding patches of surfaces of the receptor and of the ligand and no overlap between the van der Waals spheres of the remainder of the receptor and ligand atoms. In the quest for favorable chemical interactions, the next step involves minimization of the energy between the docked molecules. This work addresses the geometrical aspect of the problem. It is assumed that we have the atomic coordinates of each of the molecules. In principle, since optimally matching surfaces are sought, the entire conformational space needs to be considered. As the number of atoms residing on molecular surfaces can be several hundred, sampling of all rotations and translations of every patch of a surface of one molecule with respect to the other can reach immense proportions. The problem we are faced with here is reminiscent of object recognition problems in computer vision. Here we borrow and adapt the geometric hashing paradigm developed in computer vision to a central problem in molecular biology. Using an indexing approach based on a transformation invariant representation, the algorithm efficiently scans groups of surface dots (or atoms) and detects optimally matched surfaces. Potential solutions displaying receptor--ligand atomic overlaps are discarded. Our technique has been applied successfully to seven cases involving docking of small molecules, where the structures of the receptor--ligand complexes are available in the crystallographic database and to three cases where the receptors and ligands have been crystallized separately. In two of these three latter tests, the correct transformations have been obtained.

Surface motifs by a computer vision technique: searches, detection, and implications for protein-ligand recognition.

We describe the application of a method geared toward structural and surface comparison of proteins. The method is based on the Geometric Hashing Paradigm adapted from Computer Vision. It allows for comparison of any two sets of 3-D coordinates, such as protein backbones, protein core or protein surface motifs, and small molecules such as drugs. Here we apply our method to 4 types of comparisons between pairs of molecules: (1) comparison of the backbones of two protein domains; (2) search for a predefined 3-D C alpha motif within the full backbone of a domain; and in particular, (3) comparison of the surfaces of two receptor proteins; and (4) comparison of the surface of a receptor to the surface of a ligand. These aspects complement each other and can contribute toward a better understanding of protein structure and biomolecular recognition. Searches for 3-D surface motifs can be carried out on either receptors or on ligands. The latter may result in the detection of pharmacophoric patterns. If the surfaces of the binding sites of either the receptors or of the ligands are relatively similar, surface superpositioning may aid significantly in the docking problem. Currently, only distance invariants are used in the matching, although additional geometric surface invariants are considered. The speed of our Geometric Hashing algorithm is encouraging, with a typical surface comparison taking only seconds or minutes of CPU time on a SUN 4 SPARC workstation. The direct application of this method to the docking problem is also discussed. We demonstrate the success of this method in its application to two members of the globin family and to two dehydrogenases.

A model for the adjustment of the mitotic clock by cyclin and MPF levels.

A mathematical model of cell cycle progression is presented, which integrates recent biochemical information on the interaction of the maturation promotion factor (MPF) and cyclin. The model retrieves the dynamics observed in early embryos and explains how multiple cycles of MPF activity can be produced and how the internal clock that determines durations and number of cycles can be adjusted by modulating the rate of change in MPF or cyclin concentrations. Experiments are suggested for verifying the role of MPF activity in determining the length of the somatic cell cycle.