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.     

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. Proteins 32:159–174, 1998. © 1998 Wiley-Liss, Inc.     

Computational Paradigm to Elucidate the Effects of Arts-Based Approaches and Interventions: Individual and Collective Emerging Behaviors in Artwork Construction

Art therapy, as well as other arts-based therapies and interventions, is used to reduce pain, stress, depression, breathlessness and other symptoms in a wide variety of serious and chronic diseases, such as cancer, Alzheimer and schizophrenia. Arts-based approaches are also known to contribute to one’s well-being and quality of life. However, much research is required, since the mechanisms by which these non-pharmacological treatments exert their therapeutic and psychosocial effects are not adequately understood. A typical clinical setting utilizing the arts consists of the creation work itself, such as the artwork, as well as the therapist and the patient, all of which constitute a rich and dynamic environment of occurrences. The underlying complex, simultaneous and interwoven processes of this setting are often considered intractable to human observers, and as a consequence are usually interpreted subjectively and described verbally, which affect their subsequent analyses and understanding. We introduce a computational research method for elucidating and analyzing emergent expressive and social behaviors, aiming to understand how arts-based approaches operate. Our methodology, which centers on the visual language of Statecharts and tools for its execution, enables rigorous qualitative and quantitative tracking, analysis and documentation of the underlying creation and interaction processes. Also, it enables one to carry out exploratory, hypotheses-generating and knowledge discovery investigations, which are empirical-based. Furthermore, we illustrate our method’s use in a proof-of-principle study, applying it to a real-world artwork investigation with human participants. We explore individual and collective emergent behaviors impacted by diverse drawing tasks, yielding significant gender and age hypotheses, which may account for variation factors in response to art use. We also discuss how to gear our research method to systematic and mechanistic investigations, as we wish to provide a broad empirical evidence for the uptake of arts-based approaches, also aiming to ameliorate their use in clinical settings.     

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