GOSSIP: a method for fast and accurate global alignment of protein structures.

MOTIVATION: The database of known protein structures (PDB) is increasing rapidly. This results in a growing need for methods that can cope with the vast amount of structural data. To analyze the accumulating data, it is important to have a fast tool for identifying similar structures and clustering them by structural resemblance. Several excellent tools have been developed for the comparison of protein structures. These usually address the task of local structure alignment, an important yet computationally intensive problem due to its complexity. It is difficult to use such tools for comparing a large number of structures to each other at a reasonable time. RESULTS: Here we present GOSSIP, a novel method for a global all-against-all alignment of any set of protein structures. The method detects similarities between structures down to a certain cutoff (a parameter of the program), hence allowing it to detect similar structures at a much higher speed than local structure alignment methods. GOSSIP compares many structures in times which are several orders of magnitude faster than well-known available structure alignment servers, and it is also faster than a database scanning method. We evaluate GOSSIP both on a dataset of short structural fragments and on two large sequence-diverse structural benchmarks. Our conclusions are that for a threshold of 0.6 and above, the speed of GOSSIP is obtained with no compromise of the accuracy of the alignments or of the number of detected global similarities. AVAILABILITY: A server, as well as an executable for download, are available at http://bioinfo3d.cs.tau.ac.il/gossip/.

MASS: multiple structural alignment by secondary structures.

We present a novel method for multiple alignment of protein structures and detection of structural motifs. To date, only a few methods are available for addressing this task. Most of them are based on a series of pairwise comparisons. In contrast, MASS (Multiple Alignment by Secondary Structures) considers all the given structures at the same time. Exploiting the secondary structure representation aids in filtering out noisy results and in making the method highly efficient and robust. MASS disregards the sequence order of the secondary structure elements. Thus, it can find non-sequential and even non-topological structural motifs. An important novel feature of MASS is subset alignment detection: It does not require that all the input molecules be aligned. Rather, MASS is capable of detecting structural motifs shared only by a subset of the molecules. Given its high efficiency and capability of detecting subset alignments, MASS is suitable for a broad range of challenging applications: It can handle large-scale protein ensembles (on the order of tens) that may be heterogeneous, noisy, topologically unrelated and contain structures of low resolution.

Lead exposure in scaffolders during refurbishment construction activity--an observational study.

The toxic effects of lead have been known for centuries. Occupational exposure to this chemical hazard has also been well documented in relation to various industry groups, including construction, where workers are recognized as being significantly exposed during refurbishment work, in particular through inhalation and ingestion of lead fumes and dust. It is easy to see how so-called 'burners', 'cutters' and 'blasters'--workers directly involved in removing old lead paint--may become exposed; the influence of personal hygiene, smoking, eating/drinking and nail biting has also been documented in the literature. We now report on one group, the scaffolders, not previously considered to be at risk. Although not directly involved in the paint removal, anecdotal and personal experience of the authors indicate that these workers, who erect and later dismantle access structures during the renovation of previously lead-painted surfaces, may take up significant amounts of lead, mainly by ingestion, to raise their personal blood lead levels (and body burden) in line with recognized 'lead workers'. Exposures of this magnitude would also bring the scaffolders involved in such refurbishment work under the Control of Lead at Work Regulations 1998. The authors make various recommendations on measures to minimize and control exposure of scaffolders to lead.

Protein folding: binding of conformationally fluctuating building blocks via population selection.

Here we review different aspects of the protein folding literature. We present a broad range of observations, showing them to be consistent with a general hierarchical protein folding model. In such a model, local relatively stable, conformationally fluctuating building blocks bind through population selection, to yield the native state. The model includes several components: (1) the fluctuating building blocks that constitute local minima along the polypeptide chain, which even if unstable still possess higher population times than all alternate conformations; (2) the landscape around the bottom of the funnels; (3) the consideration that protein folding involves intramolecular recognition; (4) similar landscapes are observed for folding and for binding, and that (5) the landscape is dynamic, changing with the conditions. The model considers protein folding to be guided by native interactions. The reviewed literature includes the effects of changing the conditions, intermediates and kinetic traps, mutations, similar topologies, fragment complementation experiments, fragments and pathways, focusing on one specific well-studied example, that of the dihydrofolate reductase, chaperones, and chaperonines, in vivo vs. in vitro folding, still using the dihydrofolate example, amyloid formation, and molecular "disorder". These are consistent with the view that binding and folding are similar events, with the differences stemming from different stabilities and hence population times.

MUSTA--a general, efficient, automated method for multiple structure alignment and detection of common motifs: application to proteins.

Here we present an algorithm designed to carry out multiple structure alignment and to detect recurring substructural motifs. So far we have implemented it for comparison of protein structures. However, this general method is applicable to comparisons of RNA structures and to detection of a pharmacophore in a series of drug molecules. Further, its sequence order independence permits its application to detection of motifs on protein surfaces, interfaces, and binding/active sites. While there are many methods designed to carry out pairwise structure comparisons, there are only a handful geared toward the multiple structure alignment task. Most of these tackle multiple structure comparison as a collection of pairwise structure comparison tasks. The multiple structural alignment algorithm presented here automatically finds the largest common substructure (core) of atoms that appears in all the molecules in the ensemble. The detection of the core and the structural alignment are done simultaneously. The algorithm begins by finding small substructures that are common to all the proteins in the ensemble. One of the molecules is considered the reference; the others are the source molecules. The small substructures are stored in special arrays termed combinatorial buckets, which define sets of multistructural alignments from the source molecules that coincide with the same small set of reference atoms (C(alpha)-atoms here). These substructures are initial small fragments that have congruent copies in each of the proteins. The substructures are extended, through the processing of the combinatorial buckets, by clustering the superpositions (transformations). The method is very efficient.

Protein functional epitopes: hot spots, dynamics and combinatorial libraries.

Recent studies increasingly point to the importance of structural flexibility and plasticity in proteins, highlighting the evolutionary advantage. There are an increasing number of cases in which given, presumably specific, binding sites have been shown to bind a range of ligands with different compositions and shapes. These studies have also revealed that evolution tends to find convergent solutions for stable intermolecular associations, largely via conservation of polar residues as hot spots of binding energy. On the other hand, the ability to bind multiple ligands at a given site is largely derived from hinge-based motions. The consideration of these two factors in functional epitopes allows more realism and robustness in the description of protein binding surfaces and, as such, in applications to mutants, modeled structures and design. Efficient multiple structure comparison and hinge-bending structure comparison tools enable the construction of combinatorial binding epitope libraries.

Automated multiple structure alignment and detection of a common substructural motif.

While a number of approaches have been geared toward multiple sequence alignments, to date there have been very few approaches to multiple structure alignment and detection of a recurring substructural motif. Among these, none performs both multiple structure comparison and motif detection simultaneously. Further, none considers all structures at the same time, rather than initiating from pairwise molecular comparisons. We present such a multiple structural alignment algorithm. Given an ensemble of protein structures, the algorithm automatically finds the largest common substructure (core) of C(alpha) atoms that appears in all the molecules in the ensemble. The detection of the core and the structural alignment are done simultaneously. Additional structural alignments also are obtained and are ranked by the sizes of the substructural motifs, which are present in the entire ensemble. The method is based on the geometric hashing paradigm. As in our previous structural comparison algorithms, it compares the structures in an amino acid sequence order-independent way, and hence the resulting alignment is unaffected by insertions, deletions and protein chain directionality. As such, it can be applied to protein surfaces, protein-protein interfaces and protein cores to find the optimally, and suboptimally spatially recurring substructural motifs. There is no predefinition of the motif. We describe the algorithm, demonstrating its efficiency. In particular, we present a range of results for several protein ensembles, with different folds and belonging to the same, or to different, families. Since the algorithm treats molecules as collections of points in three-dimensional space, it can also be applied to other molecules, such as RNA, or drugs.

Alignment of flexible protein structures.

We present two algorithms which align flexible protein structures. Both apply efficient structural pattern detection and graph theoretic techniques. The FlexProt algorithm simultaneously detects the hinge regions and aligns the rigid subparts of the molecules. It does it by efficiently detecting maximal congruent rigid fragments in both molecules and calculating their optimal arrangement which does not violate the protein sequence order. The FlexMol algorithm is sequence order independent, yet requires as input the hypothesized hinge positions. Due its sequence order independence it can also be applied to protein-protein interface matching and drug molecule alignment. It aligns the rigid parts of the molecule using the Geometric Hashing method and calculates optimal connectivity among these parts by graph-theoretic techniques. Both algorithms are highly efficient even compared with rigid structure alignment algorithms. Typical running times on a standard desktop PC (400 MHz) are about 7 seconds for FlexProt and about 1 minute for FlexMol.

Conservation of polar residues as hot spots at protein interfaces.

A number of studies have addressed the question of which are the critical residues at protein-binding sites. These studies examined either a single or a few protein-protein interfaces. The most extensive study to date has been an analysis of alanine-scanning mutagenesis. However, although the total number of mutations was large, the number of protein interfaces was small, with some of the interfaces closely related. Here we show that although overall binding sites are hydrophobic, they are studded with specific, conserved polar residues at specific locations, possibly serving as energy "hot spots." Our results confirm and generalize the alanine-scanning data analysis, despite its limited size. Previously Trp, Arg, and Tyr were shown to constitute energetic hot spots. These were rationalized by their polar interactions and by their surrounding rings of hydrophobic residues. However, there was no compelling reason as to why specifically these residues were conserved. Here we show that other polar residues are similarly conserved. These conserved residues have been detected consistently in all interface families that we have examined. Our results are based on an extensive examination of residues which are in contact across protein interfaces. We utilize all clustered interface families with at least five members and with sequence similarity between the members in the range of 20-90%. There are 11 such clustered interface families, comprising a total of 97 crystal structures. Our three-dimensional superpositioning analysis of the occurrences of matched residues in each of the families identifies conserved residues at spatially similar environments. Additionally, in enzyme inhibitors, we observe that residues are more conserved at the interfaces than at other locations. On the other hand, antibody-protein interfaces have similar surface conservation as compared to their corresponding linear sequence alignment, consistent with the suggestion that evolution has optimized protein interfaces for function.

Efficient computational algorithms for docking and for generating and matching a library of functional epitopes I. Rigid and flexible hinge-bending docking algorithms.

In this, and the next review article (1), we present highly efficient, computer-vision and robotics based algorithms for docking and for the generation and matching of epitopes on molecular surfaces. We start with descriptions of molecular surfaces, and proceed to utilize these in both rigid-body and flexible matching routines. These algorithms originate in the computer vision and robotics disciplines. Frequently used approaches, both in searches for molecular similarity and for docking, i.e., molecular complementarity, strive to obtain highly accurate correspondence of respective molecular surfaces. However, owing to molecular surface variability in solution, to mutational events, and to the need to use modeled structures in addition to high resolution ones, utilization of epitopes might prove to be a judicious approach to follow. Furthermore, through the deployment of libraries of epitopes which represent recurring features, or motifs in a given family of receptors or of enzymes, in principle we a priori focus on the more critical groups of atoms, or amino acids, essential for the binding of the two molecules. Utilization of recurring motifs may prove more robust than single molecule matchings. In addition, via utilization of epitopes one can make use of information derived from evolutionary related molecules. All of the above combine to represent an approach which may be highly advantageous. Combinatorial approaches have proven their immense utility in the wet laboratory. The combination of efficient computational approaches and the utilization of such libraries may well be particularly profitable. Our highly efficient techniques are amenable to such a task. In this review we focus on rigid and flexible docking algorithms. In the second review (1) we address the generation of epitopes in families of molecules. These may be used by the docking algorithms to identify the more likely bound interfaces.

Efficient computational algorithms for docking and for generating and matching a library of functional epitopes II. Computer vision-based techniques for the generation and utilization of functional epitopes.

This is the second review in a two-part series. In the first review (1) we described the computational complexity involved in the docking of a ligand onto a receptor surface. In particular, we focused on efficient algorithms designed to handle this computational task. Such a procedure results in a large number of potential, geometrically feasible solutions. The difficulty is to pinpoint which of these is the more likely candidate. While there exists a number of approaches to rank these solutions according to different criteria, such as the size of the interface or some approximation of their binding energetics, none of the existing methods has been shown to be consistently successful in this endeavor. If the binding site is unknown a priori, the magnitude of the task is awesome. Here we propose one way of addressing this problem, i.e., via derivation and utilization of binding epitopes. If a library of such epitopes is available, particularly for a large number of protein families, it may be used to predict more likely binding sites for a given ligand. We describe an efficient, computer-vision based method to construct binding epitopes focusing on two ways through which such a library can be generated, (i) molecular surface-based, or (ii) residue-based. Alternatively, the two can be combined. We further describe how such a library may be used efficiently in the matching/docking procedure.

Folding funnels and conformational transitions via hinge-bending motions.

In this article we focus on presenting a broad range of examples illustrating low-energy transitions via hinge-bending motions. The examples are divided according to the type of hinge-bending involved; namely, motions involving fragments of the protein chains, hinge-bending motions involving protein domains, and hinge-bending motions between the covalently unconnected subunits. We further make a distinction between allosterically and nonallosterically regulated proteins. These transitions are discussed within the general framework of folding and binding funnels. We propose that the conformers manifesting such swiveling motions are not the outcome of "induced fit" binding mechanism; instead, molecules exist in an ensemble of conformations that are in equilibrium in solution. These ensembles, which populate the bottoms of the funnels, a priori contain both the "open" and the "closed" conformational isomers. Furthermore, we argue that there are no fundamental differences among the physical principles behind the folding and binding funnels. Hence, there is no basic difference between funnels depicting ensembles of conformers of single molecules with fragment, or domain motions, as compared to subunits in multimeric quaternary structures, also showing such conformational transitions. The difference relates only to the size and complexity of the system. The larger the system, the more complex its corresponding fused funnel(s). In particular, funnels associated with allosterically regulated proteins are expected to be more complicated, because allostery is frequently involved with movements between subunits, and consequently is often observed in multichain and multimolecular complexes. This review centers on the critical role played by flexibility and conformational fluctuations in enzyme activity. Internal motions that extend over different time scales and with different amplitudes are known to be essential for the catalytic cycle. The conformational change observed in enzyme-substrate complexes as compared to the unbound enzyme state, and in particular the hinge-bending motions observed in enzymes with two domains, have a substantial effect on the enzymatic catalytic activity. The examples we review span the lipolytic enzymes that are particularly interesting, owing to their activation at the water-oil interface; an allosterically controlled dehydrogenase (lactate dehydrogenase); a DNA methyltransferase, with a covalently-bound intermediate; large-scale flexible loop motions in a glycolytic enzyme (TIM); domain motion in PGK, an enzyme which is essential in most cells, both for ATP generation in aerobes and for fermentation in anaerobes; adenylate kinase, showing large conformational changes, owing to their need to shield their catalytic centers from water; a calcium-binding protein (calmodulin), involved in a wide range of cellular calcium-dependent signaling; diphtheria toxin, whose large domain motion has been shown to yield "domain swapping;" the hexameric glutamate dehydrogenase, which has been studied both in a thermophile and in a mesophile; an allosteric enzyme, showing subunit motion between the R and the T states (aspartate transcarbamoylase), and the historically well-studied lac repressor. Nonallosteric subunit transitions are also addressed, with some examples (aspartate receptor and BamHI endonuclease). Hence, using this enzyme-catalysis-centered discussion, we address energy funnel landscapes of large-scale conformational transitions, rather than the faster, quasi-harmonic, thermal fluctuations.

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.

Flexible structural comparison allowing hinge-bending, swiveling motions.

We present an efficient method for flexible comparison of protein structures, allowing swiveling motions. In all currently available methodologies developed and applied to the comparisons of protein structures, the molecules are considered to be rigid objects. The method described here extends and generalizes current approaches to searches for structural similarity between molecules by viewing proteins as objects consisting of rigid parts connected by rotary joints. During the matching, the rigid subparts are allowed to be rotated with respect to each other around swiveling points in one of the molecules. This technique straightforwardly detects structural motifs having hinge(s) between their domains. Whereas other existing methods detect hinge-bent motifs by initially finding the matching rigid parts and subsequently merging these together, our method automatically detects recurring substructures, allowing full 3 dimensional rotations about their swiveling points. Yet the method is extremely fast, avoiding the time-consuming full conformational space search. Comparison of two protein structures, without a predefinition of the motif, takes only seconds to one minute on a workstation per hinge. Hence, the molecule can be scanned for many potential hinge sites, allowing practically all C(alpha) atoms to be tried as swiveling points. This algorithm provides a highly efficient, fully automated tool. Its complexity is only O(n2), where n is the number of C(alpha) atoms in the compared molecules. As in our previous methodologies, the matching is independent of the order of the amino acids in the polypeptide chain. Here we illustrate the performance of this highly powerful tool on a large number of proteins exhibiting hinge-bending domain movements. Despite the motions, known hinge-bent domains/motifs which have been assembled and classified, are correctly identified. Additional matches are detected as well. This approach has been motivated by a technique for model based recognition of articulated objects originating in computer vision and robotics.

Multiple structural alignment and core detection by geometric hashing.

A Multiple Structural Alignment algorithm is presented. The algorithm accepts an ensemble of protein structures and finds the largest substructure (core) of C alpha atoms whose geometric configuration appear in all the molecules of the ensemble (core). Both the detection of this core and the resulting structural alignment are done simultaneously. Other large enough multistructural superimpositions are detected as well. Our method is based on the Geometric Hashing paradigm and a superimposition clustering technique which represents superimpositions by sets of matching atoms. The algorithm proved to be efficient on real data in a series of experiments. The same method can be applied to any ensemble of molecules (not necessarily proteins) since our basic technique is sequence order independent.

Flexible docking allowing induced fit in proteins: insights from an open to closed conformational isomers.

Here we dock a ligand onto a receptor surface allowing hinge-bending domain/substructural movements. Our approach mimics and manifests induced fit in molecular recognition. All angular rotations are allowed on the one hand, while a conformational space search is avoided on the other. Rather than dock each of the molecular parts separately with subsequent reconstruction of the consistently docked molecules, all parts are docked simultaneously while still utilizing the position of the hinge from the start. Like pliers closing on a screw, the receptor automatically closes on its ligand in the best surface-matching way. Movements are allowed either in the ligand or in the larger receptor, hence reproducing induced molecular fit. Hinge bending movements are frequently observed when molecules associate. There are numerous examples of open versus closed conformations taking place upon binding. Such movements are observed when the substrate binds to its respective enzyme. In particular, such movements are of interest in allosteric enzymes. The movements can involve entire domains, subdomains, loops, (other) secondary structure elements, or between any groups of atoms connected by flexible joints. We have implemented the hinges at points and at bonds. By allowing 3-dimensional (3-D) rotation at the hinge, several rotations about (consecutive or nearby) bonds are implicitly taken into account. Alternatively, if required, the point rotation can be restricted to bond rotation. Here we illustrate this hinge-bending docking approach and the insight into flexibility it provides on a complex of the calmodulin with its M13 ligand, positioning the hinges either in the ligand or in the larger receptor. This automated and efficient method is adapted from computer vision and robotics. It enables utilizing entire molecular surfaces rather than focusing a priori on active sites. Hence, allows attaining the overall optimally matching surfaces, the extent and type of motions which are involved. Here we do not treat the conformational flexibility of side-chains or of very small pieces of the molecules. Therefore, currently available methods addressing these issues and the method presented here, are complementary to each other, expanding the repertoire of computational docking tools foreseen to aid in studies of recognition, conformational flexibility and drug design.

Molecular shape comparisons in searches for active sites and functional similarity.

Here we examine the reliability of surface comparisons in searches for active sites in proteins. Detection of a patch of surface on one protein which is similar to an active site in another, may suggest similarities in enzymatic mechanisms, in enzyme functions and implicate a potential target for ligand/inhibitor design. Specifically, we compare the efficacy of molecular surface comparisons with comparisons of surface atoms and of C(alpha) backbone atoms. We further investigate comparisons of specific atoms, belonging to a predefined pattern of catalytic residues versus comparisons of molecular surfaces and, separately, of surface atoms. This aspect is particularly relevant, as catalytic residues may be (partially) buried. We also explore active site comparisons versus comparisons in which the entire molecular surfaces are scanned. While here we focus on the geometrical aspect of the problem, we also investigate the effect of adding residue labels in these comparisons. Our extensive studies cover the serine proteases, containing the highly conserved triad motif, and the chorismate mutases. Since such active site comparisons entail comparisons between unconnected points in 3D space, an order-independent comparison technique is necessary. The geometric hashing algorithm is ideally suited to handling such a task. It can perform both global shape matching for the whole surfaces of large protein molecules and searching for local shape similarities for small surface motifs. Our results show that molecular surface comparisons work best when the similarity is high. As the similarity deteriorates, the number of potential solutions increases rapidly, making their ranking difficult, particularly when scanning entire molecular surfaces. Utilizing atomic coordinates directly appears more adequate under such circumstances.

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.