Molecular Biology has allowed the characterization and manipulation of the molecules of life in the wet lab. Also the structures of those macromolecules are being continuously elucidated. During the last decades of the past century, there was an increasing interest to study how the different genes are organized into different organisms (‘genomes’) and how those genes are expressed into proteins to achieve their functions. Currently the sequences for many genes over several genomes have been determined. In parallel, the efforts to have the structure of the proteins coded by those genes go on. However it is experimentally much harder to obtain the structure of a protein, rather than just its sequence. For this reason, the number of protein structures available in databases is an order of magnitude or so lower than protein sequences. Furthermore, in order to understand how living organisms work at molecular level we need the information about the interaction of those proteins. Elucidating the structure of protein macromolecular assemblies is still more difficult. To that end, the use of computers to predict the structure of these complexes has gained interest over the last decades. The main subject of this thesis is the evaluation of current available computational methods to predict protein – protein interactions and build an atomic model of the complex. The core of the thesis is the evaluation protocol I have developed at Service de Conformation des Macromolécules Biologiques et de Bioinformatique, Université Libre de Bruxelles, and its computer implementation. This method has been massively used to evaluate the results on blind protein – protein interaction prediction in the context of the world-wide experiment CAPRI, which have been thoroughly reviewed in several publications [1-3]. In this experiment the structure of a protein complex (‘the target’) had to be modeled starting from the coordinates of the isolated molecules, prior to the release of the structure of the complex (this is commonly referred as ‘docking’). The assessment protocol let us compute some parameters to rank docking models according to their quality, into 3 main categories: ‘Highly Accurate’, ‘Medium Accurate’, ‘Acceptable’ and ‘Incorrect’. The efficiency of our evaluation and ranking is clearly shown, even for borderline cases between categories. The correlation of the ranking parameters is analyzed further. In the same section where the evaluation protocol is presented, the ranking participants give to their predictions is also studied, since often, good solutions are not easily recognized among the pool of computer generated decoys. An overview of the CAPRI results made per target structure and per participant regarding the computational method they used and the difficulty of the complex. Also in CAPRI there is a new ongoing experiment about scoring previously and anonymously generated models by other participants (the ‘Scoring’ experiment). Its promising results are also analyzed, in respect of the original CAPRI experiment. The Scoring experiment was a step towards the use of combine methods to predict the structure of protein – protein complexes. We discuss here its possible application to predict the structure of protein complexes, from a clustering study on the different results. In the last chapter of the thesis, I present the preliminary results of an ongoing study on the conformational changes in protein structures upon complexation, as those rearrangements pose serious limitations to current computational methods predicting the structure protein complexes. Protein structures are classified according to the magnitude of its conformational re-arrangement and the involvement of interfaces and particular secondary structure elements is discussed. At the end of the chapter, some guidelines and future work is proposed to complete the survey.

There is a need for objective methods for wrist angular velocity measurements for accurate risk assessments because there is a high frequency of musculoskeletal disorder in workers. The goal of this project was to validate the accuracy of inertial measurement unit sensors to measure the angular velocity. More specifically, the purpose of this master thesis project was to apply an alternative algorithm to compute the markers velocity, other than the one from the optical system that Jenny Wingqvist, and Josephine Lantz used. The project used an experimental data of 10 participants from the previous project done by Jenny Wingqvist and Josephine Lantz. To validate the accuracy, the data of angular velocity of the sensors was compared with the data of angular velocity of markers. The lowest mean value of the root mean square differences value was 23.5 degrees/s during flexion and deviation standard movements at 40 BPM (Beats Per Minute) and the maximum value was 110.5 degrees/s at 140 BPM. The mean value of the correlation coefficients between markers and sensors angular velocities in standard movements of flexion and deviation were 0.85, 0.88, and 0.89 at 40 BPM, 90 BPM, and 140 BPM, respectively. The smallest and the largest mean value of the absolute difference in 50th percentile was found in 40 BPM (19.4±11.3), and 140 BPM (51.2±28.5) respectively. The decorrelation coefficient between the subjects 50th percentile of the angular velocity was 0.91 for the standard movements. The upper limit of agreement for the standard movements was 78.36 degrees/s, while the lower limit of agreement was -13.76 degrees/s.  The results show that the error was too large, so there is a need of further research to measure the wrist angular velocity using IMU sensors.

Belastningsskador hos arbetare är ett ökande problem hos olika företag och det har visat sig finnas en tydlig koppling mellan dessa skador och handledens vinkelhastigheten. Det är därför av stort intresse att kunna mäta dessa vinkelhastigheter på ett noggrant och smidigt sätt. Syftet med denna rapport är att utvärdera precisionen av IMU-sensorers förmåga att beräkna vinkelhastigheten av handleden. Detta görs genom att jämföra data från IMU-sensorer med data från ett optiskt spårningssystem (OTS), vilket klassas som en gold standard inom detta område. Ett experiment bestående av åtta övningar utfördes: tre standard rörelser (flexion och rotation i takterna 40, 90 och 140 slag per minut) och fyra simulerade arbeten (målning, pappersvikning, datorarbete och hårföning). Grad av överensstämmelse ges av 1,96 standardavvikelser (SD) för standardrörelserna (10 deltagare) vilka var -31,8 grader/s och 34,2 grader/s, medan för de simulerade arbetena var det -35,1 grader/s och 34,2 grader/s. Det lägsta medelvärdet av medelkvadratavvikelse (RMSD) var 15,7 grader/s och erhölls vid 40 BPM medan den högsta medelvärdet var 93,9 grader/s och erhölls vid målningsövningen. Medelvärdet av korrelationskoefficienten mellan IMU-sensorer och OTS varierade mellan 0,97 och 0,42 och korrelationskoefficienterna av deltagarnas 50:e percentiler av vinkelhastigheten var 0,95 för standardrörelserna och 0,96 för de simulerade arbetena. Medelvärdet av absoluta differensen mellan sensorer och OTS var givet i percentiler (10:e, 50:e och 90:e). Det största spannet för 50:e percentilen gavs vid 140 BPM (18,3 ± 24,6) och det minsta spannet vid 40 BPM (3,5 ± 4,7). Trots att det fanns mindre differenser mellan metodernas mätningar av vinkelhastighet, anser vi att IMU-sensorer har potential att användas för att mäta vinkelhastigheter hos handledens och med vidare utveckling kan den nuvarande differensen minimeras. / Musculoskeletal disorders (MSDs) are increasingly frequent amongst workers and there is a clear connection between work injuries and wrist angular velocities. One of the biggest issues therefore is the currently limited availability of means to measure these angular velocities. The aim of this study is to validate the usability of the IMU sensors to measure angular velocities. This is done by comparing the data from the IMU:s with the data obtained with the optical motion tracking system (OTS), which is considered gold standard within this field of studies. An experiment consisting of eight exercises was conducted: three standard movements (flexion and rotation in the pace 40, 90 and 140 repetitions per minute) and four simulated practical work tasks (painting, folding paper, computer exercise and using a hairdryer). The limits of agreement for the standard movements (10 subjects) were -31,8 degrees/s and 34,2 degrees/s, whereas for the simulated practical work tasks they were -35,1 degrees/s and 28,2 degrees/s. The lowest mean value of the root mean square deviation (RMSD) value was 15,7 degrees/s which represents the 40 BPM task whilst the highest mean value was 93,9 degrees/s which correspond to the painting task. The mean value of the correlation coefficients between the IMU:s and the OTS ranged between 0,97 and 0,42 and the correlation coefficient between the subjects 50:th percentiles of the angular velocity, was 0,95 for the standard movements whilst for the practical work tasks it was 0,96. The mean value of the absolute difference between the sensors and the OTS was given in percentiles (10th, 50th and 90th). The largest range within the 50th percentile occurred during the 140 BPM task (18,3 ± 24,6) and the smallest range during the 40 BPM task (3,5 ± 4,7). Although the measured angular velocities vary to a certain extent between the two methods, we conclude that the IMU sensors present the potential to work as measuring units for wrist angular velocities and with further development the current differences can be minimized. / Forte dnr: 2017-01209 "Enkel och tideffektiv metod att mät, analysera och presentera biomekaniskbelastning för hand-handled"

Le docking moléculaire est une méthode permettant de prédire l'orientation d'une molécule donnée relativement à une autre lorsque celles-ci forment un complexe. Le premier algorithme de docking moléculaire a vu jour en 1990 afin de trouver de nouveaux candidats face à la protéase du VIH-1. Depuis, l'utilisation de protocoles de docking est devenue une pratique standard dans le domaine de la conception de nouveaux médicaments. Typiquement, un protocole de docking comporte plusieurs phases. Il requiert l'échantillonnage exhaustif du site d'interaction où les éléments impliqués sont considérées rigides. Des algorithmes de clustering sont utilisés afin de regrouper les candidats à l'appariement similaires. Des méthodes d'affinage sont appliquées pour prendre en compte la flexibilité au sein complexe moléculaire et afin d'éliminer de possibles artefacts de docking. Enfin, des algorithmes d'évaluation sont utilisés pour sélectionner les meilleurs candidats pour le docking. Cette thèse présente de nouveaux algorithmes de protocoles de docking qui facilitent la prédiction des structures de complexes protéinaires, une des cibles les plus importantes parmi les cibles visées par les méthodes de conception de médicaments. Une première contribution concerne l‘algorithme Docktrina qui permet de prédire les conformations de trimères protéinaires triangulaires. Celui-ci prend en entrée des prédictions de contacts paire-à-paire à partir d'hypothèse de corps rigides. Ensuite toutes les combinaisons possibles de paires de monomères sont évalués à l'aide d'un test de distance RMSD efficace. Cette méthode à la fois rapide et efficace améliore l'état de l'art sur les protéines trimères. Deuxièmement, nous présentons RigidRMSD une librairie C++ qui évalue en temps constant les distances RMSD entre conformations moléculaires correspondant à des transformations rigides. Cette librairie est en pratique utile lors du clustering de positions de docking, conduisant à des temps de calcul améliorés d'un facteur dix, comparé aux temps de calcul des algorithmes standards. Une troisième contribution concerne KSENIA, une fonction d'évaluation à base de connaissance pour l'étude des interactions protéine-protéine. Le problème de la reconstruction de fonction d'évaluation est alors formulé et résolu comme un problème d'optimisation convexe. Quatrièmement, CARBON, un nouvel algorithme pour l'affinage des candidats au docking basés sur des modèles corps-rigides est proposé. Le problème d'optimisation de corps-rigides est vu comme le calcul de trajectoires quasi-statiques de corps rigides influencés par la fonction énergie. CARBON fonctionne aussi bien avec un champ de force classique qu'avec une fonction d'évaluation à base de connaissance. CARBON est aussi utile pour l'affinage de complexes moléculaires qui comportent des clashes stériques modérés à importants. Finalement, une nouvelle méthode permet d'estimer les capacités de prédiction des fonctions d'évaluation. Celle-ci permet d‘évaluer de façon rigoureuse la performance de la fonction d'évaluation concernée sur des benchmarks de complexes moléculaires. La méthode manipule la distribution des scores attribués et non pas directement les scores de conformations particulières, ce qui la rend avantageuse au regard des critères standard basés sur le score le plus élevé. Les méthodes décrites au sein de la thèse sont testées et validées sur différents benchmarks protéines-protéines. Les algorithmes implémentés ont été utilisés avec succès pour la compétition CAPRI concernant la prédiction de complexes protéine-protéine. La méthodologie développée peut facilement être adaptée pour de la reconnaissance d'autres types d'interactions moléculaires impliquant par exemple des ligands, de l'ARN… Les implémentations en C++ des différents algorithmes présentés seront mises à disposition comme SAMSON Elements de la plateforme logicielle SAMSON sur http://www.samson-connect.net ou sur http://nano-d.inrialpes.fr/software. / Molecular docking is a method that predicts orientation of one molecule with respect to another one when forming a complex. The first computational method of molecular docking was applied to find new candidates against HIV-1 protease in 1990. Since then, using of docking pipelines has become a standard practice in drug discovery. Typically, a docking protocol comprises different phases. The exhaustive sampling of the binding site upon rigid-body approximation of the docking subunits is required. Clustering algorithms are used to group similar binding candidates. Refinement methods are applied to take into account flexibility of the molecular complex and to eliminate possible docking artefacts. Finally, scoring algorithms are employed to select the best binding candidates. The current thesis presents novel algorithms of docking protocols that facilitate structure prediction of protein complexes, which belong to one of the most important target classes in the structure-based drug design. First, DockTrina - a new algorithm to predict conformations of triangular protein trimers (i.e. trimers with pair-wise contacts between all three pairs of proteins) is presented. The method takes as input pair-wise contact predictions from a rigid-body docking program. It then scans and scores all possible combinations of pairs of monomers using a very fast root mean square deviation (RMSD) test. Being fast and efficient, DockTrina outperforms state-of-the-art computational methods dedicated to predict structure of protein oligomers on the collected benchmark of protein trimers. Second, RigidRMSD - a C++ library that in constant time computes RMSDs between molecular poses corresponding to rigid-body transformations is presented. The library is practically useful for clustering docking poses, resulting in ten times speed up compared to standard RMSD-based clustering algorithms. Third, KSENIA - a novel knowledge-based scoring function for protein-protein interactions is developed. The problem of scoring function reconstruction is formulated and solved as a convex optimization problem. As a result, KSENIA is a smooth function and, thus, is suitable for the gradient-base refinement of molecular structures. Remarkably, it is shown that native interfaces of protein complexes provide sufficient information to reconstruct a well-discriminative scoring function. Fourth, CARBON - a new algorithm for the rigid-body refinement of docking candidates is proposed. The rigid-body optimization problem is viewed as the calculation of quasi-static trajectories of rigid bodies influenced by the energy function. To circumvent the typical problem of incorrect stepsizes for rotation and translation movements of molecular complexes, the concept of controlled advancement is introduced. CARBON works well both in combination with a classical force-field and a knowledge-based scoring function. CARBON is also suitable for refinement of molecular complexes with moderate and large steric clashes between its subunits. Finally, a novel method to evaluate prediction capability of scoring functions is introduced. It allows to rigorously assess the performance of the scoring function of interest on benchmarks of molecular complexes. The method manipulates with the score distributions rather than with scores of particular conformations, which makes it advantageous compared to the standard hit-rate criteria. The methods described in the thesis are tested and validated on various protein-protein benchmarks. The implemented algorithms are successfully used in the CAPRI contest for structure prediction of protein-protein complexes. The developed methodology can be easily adapted to the recognition of other types of molecular interactions, involving ligands, polysaccharides, RNAs, etc. The C++ versions of the presented algorithms will be made available as SAMSON Elements for the SAMSON software platform at http://www.samson-connect.net or at http://nano-d.inrialpes.fr/software.

Le docking moléculaire est une méthode permettant de prédire l'orientation d'une molécule donnée relativement à une autre lorsque celles-ci forment un complexe. Le premier algorithme de docking moléculaire a vu jour en 1990 afin de trouver de nouveaux candidats face à la protéase du VIH-1. Depuis, l'utilisation de protocoles de docking est devenue une pratique standard dans le domaine de la conception de nouveaux médicaments. Typiquement, un protocole de docking comporte plusieurs phases. Il requiert l'échantillonnage exhaustif du site d'interaction où les éléments impliqués sont considérées rigides. Des algorithmes de clustering sont utilisés afin de regrouper les candidats à l'appariement similaires. Des méthodes d'affinage sont appliquées pour prendre en compte la flexibilité au sein complexe moléculaire et afin d'éliminer de possibles artefacts de docking. Enfin, des algorithmes d'évaluation sont utilisés pour sélectionner les meilleurs candidats pour le docking. Cette thèse présente de nouveaux algorithmes de protocoles de docking qui facilitent la prédiction des structures de complexes protéinaires, une des cibles les plus importantes parmi les cibles visées par les méthodes de conception de médicaments. Une première contribution concerne l‘algorithme Docktrina qui permet de prédire les conformations de trimères protéinaires triangulaires. Celui-ci prend en entrée des prédictions de contacts paire-à-paire à partir d'hypothèse de corps rigides. Ensuite toutes les combinaisons possibles de paires de monomères sont évalués à l'aide d'un test de distance RMSD efficace. Cette méthode à la fois rapide et efficace améliore l'état de l'art sur les protéines trimères. Deuxièmement, nous présentons RigidRMSD une librairie C++ qui évalue en temps constant les distances RMSD entre conformations moléculaires correspondant à des transformations rigides. Cette librairie est en pratique utile lors du clustering de positions de docking, conduisant à des temps de calcul améliorés d'un facteur dix, comparé aux temps de calcul des algorithmes standards. Une troisième contribution concerne KSENIA, une fonction d'évaluation à base de connaissance pour l'étude des interactions protéine-protéine. Le problème de la reconstruction de fonction d'évaluation est alors formulé et résolu comme un problème d'optimisation convexe. Quatrièmement, CARBON, un nouvel algorithme pour l'affinage des candidats au docking basés sur des modèles corps-rigides est proposé. Le problème d'optimisation de corps-rigides est vu comme le calcul de trajectoires quasi-statiques de corps rigides influencés par la fonction énergie. CARBON fonctionne aussi bien avec un champ de force classique qu'avec une fonction d'évaluation à base de connaissance. CARBON est aussi utile pour l'affinage de complexes moléculaires qui comportent des clashes stériques modérés à importants. Finalement, une nouvelle méthode permet d'estimer les capacités de prédiction des fonctions d'évaluation. Celle-ci permet d‘évaluer de façon rigoureuse la performance de la fonction d'évaluation concernée sur des benchmarks de complexes moléculaires. La méthode manipule la distribution des scores attribués et non pas directement les scores de conformations particulières, ce qui la rend avantageuse au regard des critères standard basés sur le score le plus élevé. Les méthodes décrites au sein de la thèse sont testées et validées sur différents benchmarks protéines-protéines. Les algorithmes implémentés ont été utilisés avec succès pour la compétition CAPRI concernant la prédiction de complexes protéine-protéine. La méthodologie développée peut facilement être adaptée pour de la reconnaissance d'autres types d'interactions moléculaires impliquant par exemple des ligands, de l'ARN… Les implémentations en C++ des différents algorithmes présentés seront mises à disposition comme SAMSON Elements de la plateforme logicielle SAMSON sur http://www.samson-connect.net ou sur http://nano-d.inrialpes.fr/software. / Molecular docking is a method that predicts orientation of one molecule with respect to another one when forming a complex. The first computational method of molecular docking was applied to find new candidates against HIV-1 protease in 1990. Since then, using of docking pipelines has become a standard practice in drug discovery. Typically, a docking protocol comprises different phases. The exhaustive sampling of the binding site upon rigid-body approximation of the docking subunits is required. Clustering algorithms are used to group similar binding candidates. Refinement methods are applied to take into account flexibility of the molecular complex and to eliminate possible docking artefacts. Finally, scoring algorithms are employed to select the best binding candidates. The current thesis presents novel algorithms of docking protocols that facilitate structure prediction of protein complexes, which belong to one of the most important target classes in the structure-based drug design. First, DockTrina - a new algorithm to predict conformations of triangular protein trimers (i.e. trimers with pair-wise contacts between all three pairs of proteins) is presented. The method takes as input pair-wise contact predictions from a rigid-body docking program. It then scans and scores all possible combinations of pairs of monomers using a very fast root mean square deviation (RMSD) test. Being fast and efficient, DockTrina outperforms state-of-the-art computational methods dedicated to predict structure of protein oligomers on the collected benchmark of protein trimers. Second, RigidRMSD - a C++ library that in constant time computes RMSDs between molecular poses corresponding to rigid-body transformations is presented. The library is practically useful for clustering docking poses, resulting in ten times speed up compared to standard RMSD-based clustering algorithms. Third, KSENIA - a novel knowledge-based scoring function for protein-protein interactions is developed. The problem of scoring function reconstruction is formulated and solved as a convex optimization problem. As a result, KSENIA is a smooth function and, thus, is suitable for the gradient-base refinement of molecular structures. Remarkably, it is shown that native interfaces of protein complexes provide sufficient information to reconstruct a well-discriminative scoring function. Fourth, CARBON - a new algorithm for the rigid-body refinement of docking candidates is proposed. The rigid-body optimization problem is viewed as the calculation of quasi-static trajectories of rigid bodies influenced by the energy function. To circumvent the typical problem of incorrect stepsizes for rotation and translation movements of molecular complexes, the concept of controlled advancement is introduced. CARBON works well both in combination with a classical force-field and a knowledge-based scoring function. CARBON is also suitable for refinement of molecular complexes with moderate and large steric clashes between its subunits. Finally, a novel method to evaluate prediction capability of scoring functions is introduced. It allows to rigorously assess the performance of the scoring function of interest on benchmarks of molecular complexes. The method manipulates with the score distributions rather than with scores of particular conformations, which makes it advantageous compared to the standard hit-rate criteria. The methods described in the thesis are tested and validated on various protein-protein benchmarks. The implemented algorithms are successfully used in the CAPRI contest for structure prediction of protein-protein complexes. The developed methodology can be easily adapted to the recognition of other types of molecular interactions, involving ligands, polysaccharides, RNAs, etc. The C++ versions of the presented algorithms will be made available as SAMSON Elements for the SAMSON software platform at http://www.samson-connect.net or at http://nano-d.inrialpes.fr/software.

Molecular Biology has allowed the characterization and manipulation of the molecules of life in the wet lab. Also the structures of those macromolecules are being continuously elucidated. During the last decades of the past century, there was an increasing interest to study how the different genes are organized into different organisms (‘genomes’) and how those genes are expressed into proteins to achieve their functions. Currently the sequences for many genes over several genomes have been determined. In parallel, the efforts to have the structure of the proteins coded by those genes go on. However it is experimentally much harder to obtain the structure of a protein, rather than just its sequence. For this reason, the number of protein structures available in databases is an order of magnitude or so lower than protein sequences. Furthermore, in order to understand how living organisms work at molecular level we need the information about the interaction of those proteins. Elucidating the structure of protein macromolecular assemblies is still more difficult. To that end, the use of computers to predict the structure of these complexes has gained interest over the last decades.<p>The main subject of this thesis is the evaluation of current available computational methods to predict protein – protein interactions and build an atomic model of the complex. The core of the thesis is the evaluation protocol I have developed at Service de Conformation des Macromolécules Biologiques et de Bioinformatique, Université Libre de Bruxelles, and its computer implementation. This method has been massively used to evaluate the results on blind protein – protein interaction prediction in the context of the world-wide experiment CAPRI, which have been thoroughly reviewed in several publications [1-3]. In this experiment the structure of a protein complex (‘the target’) had to be modeled starting from the coordinates of the isolated molecules, prior to the release of the structure of the complex (this is commonly referred as ‘docking’).<p>The assessment protocol let us compute some parameters to rank docking models according to their quality, into 3 main categories: ‘Highly Accurate’, ‘Medium Accurate’, ‘Acceptable’ and ‘Incorrect’. The efficiency of our evaluation and ranking is clearly shown, even for borderline cases between categories. The correlation of the ranking parameters is analyzed further. In the same section where the evaluation protocol is presented, the ranking participants give to their predictions is also studied, since often, good solutions are not easily recognized among the pool of computer generated decoys.<p>An overview of the CAPRI results made per target structure and per participant regarding the computational method they used and the difficulty of the complex. Also in CAPRI there is a new ongoing experiment about scoring previously and anonymously generated models by other participants (the ‘Scoring’ experiment). Its promising results are also analyzed, in respect of the original CAPRI experiment. The Scoring experiment was a step towards the use of combine methods to predict the structure of protein – protein complexes. We discuss here its possible application to predict the structure of protein complexes, from a clustering study on the different results.<p>In the last chapter of the thesis, I present the preliminary results of an ongoing study on the conformational changes in protein structures upon complexation, as those rearrangements pose serious limitations to current computational methods predicting the structure protein complexes. Protein structures are classified according to the magnitude of its conformational re-arrangement and the involvement of interfaces and particular secondary structure elements is discussed. At the end of the chapter, some guidelines and future work is proposed to complete the survey. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished