Ensemble-Based Computational Approach Discriminates Functional Activity of p53 Cancer and Rescue Mutants

The tumor suppressor protein p53 can lose its function upon single-point missense mutations in the core DNA-binding domain (“cancer mutants”). Activity can be restored by second-site suppressor mutations (“rescue mutants”). This paper relates the functional activity of p53 cancer and rescue mutants to their overall molecular dynamics (MD), without focusing on local structural details. A novel global measure of protein flexibility for the p53 core DNA-binding domain, the number of clusters at a certain RMSD cutoff, was computed by clustering over 0.7 µs of explicitly solvated all-atom MD simulations. For wild-type p53 and a sample of p53 cancer or rescue mutants, the number of clusters was a good predictor of in vivo p53 functional activity in cell-based assays. This number-of-clusters (NOC) metric was strongly correlated (r2 = 0.77) with reported values of experimentally measured ΔΔG protein thermodynamic stability. Interpreting the number of clusters as a measure of protein flexibility: (i) p53 cancer mutants were more flexible than wild-type protein, (ii) second-site rescue mutations decreased the flexibility of cancer mutants, and (iii) negative controls of non-rescue second-site mutants did not. This new method reflects the overall stability of the p53 core domain and can discriminate which second-site mutations restore activity to p53 cancer mutants

Bioinformatics analysis of the structural and biochemical effect of the chemical weapon mustard gas on the P53 protein and cell death

The universal and extensive usage of Sulfur Mustard gas (SM) as a disqualification chemical warfare potential in the past century has demonstrated its long-term toxic impacts. Sulfur mustard (SM), also known as mustard gas, is an alkylating compound used as a chemical weapon in World War I and by Iraqi forces against Iranians and indigenous Iraqi Kurds during the Iran–Iraq War of the 1980s. We can notice the carcinogenic effects of exposure to SM gas. The present study characterizes Bioinformatics analysis of the structural and biochemical effect of the chemical weapon mustard gas on the P53 protein and cell death. Inactivation of the p53 gene is essentially due to small mutations (missense and nonsense mutations or insertions/deletions of several nucleotides. For this study we used from Primary databases (experimental results directly into database), secondary databases (results of analysis of primary databases) and aggregate of many databases (Links to other data items, combination of data and consolidation of data).The database used includes: IARC TP53, P53web site-free, UniProt, NCBI and PDB format. Also, we used from some software in methodology such as PYMOL and CROMACS for visualizing, molecular dynamics simulation and analysis. We assay the most important of P53 region means that DNA-binding domain(DBD) from the point of view protein stability after mutation and the its effects on cell cycle arrest (cell death).The results have shown that all missense mutations selected in this case had caused remarkable flexibility and stability on DBD of the P53.Structural alterations had not been observed in DNA-binding domain, so it may be through functional changes in the certain amino acid residues and bounding linkage to DNA

Ensemble-Based Computational Approach Discriminates Functional Activity of p53 Cancer and Rescue Mutants

The tumor suppressor protein p53 can lose its function upon single-point missense mutations in the core DNA-binding domain ("cancer mutants''). Activity can be restored by second-site suppressor mutations ("rescue mutants''). This paper relates the functional activity of p53 cancer and rescue mutants to their overall molecular dynamics (MD), without focusing on local structural details. A novel global measure of protein flexibility for the p53 core DNA-binding domain, the number of clusters at a certain RMSD cutoff, was computed by clustering over 0.7 mu s of explicitly solvated all-atom MD simulations. For wild-type p53 and a sample of p53 cancer or rescue mutants, the number of clusters was a good predictor of in vivo p53 functional activity in cell-based assays. This number-of-clusters (NOC) metric was strongly correlated (r(2) = 0.77) with reported values of experimentally measured Delta Delta G protein thermodynamic stability. Interpreting the number of clusters as a measure of protein flexibility: (i) p53 cancer mutants were more flexible than wild-type protein, (ii) second-site rescue mutations decreased the flexibility of cancer mutants, and (iii) negative controls of non-rescue second-site mutants did not. This new method reflects the overall stability of the p53 core domain and can discriminate which second-site mutations restore activity to p53 cancer mutants

Ensemble-Based Computational Approach Discriminates Functional Activity of p53 Cancer and Rescue Mutants

The tumor suppressor protein p53 can lose its function upon single-point missense mutations in the core DNA-binding domain ("cancer mutants''). Activity can be restored by second-site suppressor mutations ("rescue mutants''). This paper relates the functional activity of p53 cancer and rescue mutants to their overall molecular dynamics (MD), without focusing on local structural details. A novel global measure of protein flexibility for the p53 core DNA-binding domain, the number of clusters at a certain RMSD cutoff, was computed by clustering over 0.7 mu s of explicitly solvated all-atom MD simulations. For wild-type p53 and a sample of p53 cancer or rescue mutants, the number of clusters was a good predictor of in vivo p53 functional activity in cell-based assays. This number-of-clusters (NOC) metric was strongly correlated (r(2) = 0.77) with reported values of experimentally measured Delta Delta G protein thermodynamic stability. Interpreting the number of clusters as a measure of protein flexibility: (i) p53 cancer mutants were more flexible than wild-type protein, (ii) second-site rescue mutations decreased the flexibility of cancer mutants, and (iii) negative controls of non-rescue second-site mutants did not. This new method reflects the overall stability of the p53 core domain and can discriminate which second-site mutations restore activity to p53 cancer mutants

Ensemble-based computational approach discriminates functional activity of p53 cancer and rescue mutants.

The tumor suppressor protein p53 can lose its function upon single-point missense mutations in the core DNA-binding domain ("cancer mutants"). Activity can be restored by second-site suppressor mutations ("rescue mutants"). This paper relates the functional activity of p53 cancer and rescue mutants to their overall molecular dynamics (MD), without focusing on local structural details. A novel global measure of protein flexibility for the p53 core DNA-binding domain, the number of clusters at a certain RMSD cutoff, was computed by clustering over 0.7 µs of explicitly solvated all-atom MD simulations. For wild-type p53 and a sample of p53 cancer or rescue mutants, the number of clusters was a good predictor of in vivo p53 functional activity in cell-based assays. This number-of-clusters (NOC) metric was strongly correlated (r(2) = 0.77) with reported values of experimentally measured ΔΔG protein thermodynamic stability. Interpreting the number of clusters as a measure of protein flexibility: (i) p53 cancer mutants were more flexible than wild-type protein, (ii) second-site rescue mutations decreased the flexibility of cancer mutants, and (iii) negative controls of non-rescue second-site mutants did not. This new method reflects the overall stability of the p53 core domain and can discriminate which second-site mutations restore activity to p53 cancer mutants

Applications and Improvements in the Molecular Modeling of Protein and Ligand Interactions

Understanding protein and ligand interactions is fundamental to treat disease and avoid toxicity in biological organisms. Molecular modeling is a helpful but imperfect tool used in computer-aided toxicology and drug discovery. In this work, molecular docking and structural informatics have been integrated with other modeling methods and physical experiments to better understand and improve predictions for protein and ligand interactions. Results presented as part of this research include: 1.) an application of single-protein docking for an intermediate state structure, specifically, modeling an intermediate state structure of alpha-1-antitrypsin and using the resulting model to virtually screen for chemical inhibitors that can treat alpha-1-antitrypsin deficiency, 2.) an application of multi-protein docking and metabolism prediction, specifically, modeling the cytochrome P450 metabolism and estrogen receptor activity of an environmental pollutant (PCB-30), and 3.) providing evidence to support the inclusion of anion-pi interactions in molecular modeling by demonstrating the biological roles of anion-pi interactions in stabilizing protein and protein-ligand structures. This work has direct applications for mitigating disease and toxicity, but it also demonstrates useful ways of integrating computational and experimental data to improve upon modeling protein and ligand interactions

Méthodes d’apprentissage et approches expérimentales appliqués aux réseaux d’interfaces protéiques

The aim of this study is to understand protein assembly mechanisms. The assembly of a protein in an oligomer is particularly important because it is involved in many pathologies going from bacterial infection, Alzheimer like diseases or even some cancers. Protein assembly is the combination of two or more protein chains to induce a biological activity. The B subunit of the cholera toxin pentamer (CtxB5), which belongs to the family of AB5 toxins, is studied as the main model of assembly. Experimental results have provided information on the assembly of the toxin highlighting the involvement of certain amino acids. The first problem addressed in my thesis is to understand their role and see if network approaches are relevant to such investigation. I was able to show using amino acid mutations, that amino acids influence each other by cascade or "peer to peer" mechanisms in order to coordinate the various steps of the assembly (Chapters 4, 5 and 6). The structure and function of the proteins are defined by amino acid sequences which naturally vary due to genetic mutation. So I decided to expand this field of investigation to see if the cascade mechanism was generalized as a mean of disrupting a protein structure. Here it is to understand how a protein loses its function by way of a significant change of structure upon mutation. First, I studied dataset to know the characteristics of healthy protein networks (Chapter 7, 8 and 9), and after I looked at the effects of the systematic mutation of each amino acid of CtxB5 on its overall structure (Chapter 10 and 11). Mutations led from moderate to very large structural changes around the mutated amino acid or at long distances. These results are consistent with known effects of mutation: robustness (maintenance function), evolution or adaptation (emergence of a new feature) and fragility (pathologies). The results also show a weak correlation between the number of amino acid contacts of the mutated amino acid and the amount of structural change induced by its mutation. It is therefore not easy to anticipate the effect of a mutation: The last chapter of my thesis addresses this problem (Chapter 12).Cette étude s’inscrit dans le cadre d’un problème biologique et son objectif est de comprendre les mécanismes d’assemblage des protéines. L’assemblage d’une protéine en oligomère est particulièrement important car il est impliqué dans de nombreuses pathologies allant de l’infection bactérienne aux maladies de type Alzheimer ou même des cancers. L’assemblage protéique est un mécanisme de combinaison de deux ou plusieurs chaînes protéiques, il est aussi par ailleurs souvent utilisé par les organismes vivants pour déclencher une activité biologique. La sous unité B de la toxine du choléra(CtxB5), qui appartient à la famille des toxines AB5, est étudiée comme modèle principal de l’assemblage. Des résultats expérimentaux ont fourni des informations sur l’assemblage de la toxine mettant en avant l’implication de certains acides aminés. La première question que j’ai abordée pendant ma thèse était de comprendre leur rôle et de voir si les approches réseaux étaient pertinentes pour y répondre. J’ai pu montrer en utilisant des mutations d’acides aminés que ces derniers s’influençaient entre eux suivant des mécanismes en cascade ou de « Peer to Peer » afin de coordonner les étapes de l’assemblage (les chapitres 4, 5 et 6). La structure et la fonction des protéines sont définies par des séquences d’acides aminés qui varient naturellement en raison de mutation génétique. J’ai donc décidé d’élargir ce champ d’investigation pour voir si le mécanisme en cascade était généralisable comme moyen de perturber une structure de protéine par le biais d’une mutation. Ici il s’agit de comprendre les changements de structure liés à des mutations et pouvant menés à des maladies. J’ai tout d’abord étudié des jeux de données pour connaître les caractéristiques réseaux de protéines saines (chapitre 7, 8 et 9), avant de regarder l’effet de la mutation systématique de chacun des acides aminés de CtxB5 sur sa structure globale (chapitre 10 et 11). Les mutations peuvent engendrer des changements de structure modérés ou très grand autour de l’acide aminé muté ou à des distances très éloignées. Ces résultats sont consistants avec tous les effets connus de mutation : robustesse (maintien de la fonction), évolution ou adaptation (émergence d’une nouvelle fonction) et fragilité (pathologies). Les résultats montrent aussi une faible corrélation entre le nombre de contacts d’un acide aminé et la quantité de changement structuraux induit par sa mutation. Il n’est donc pas simple d’anticiper l’effet d’une mutation : Le dernier chapitre de ma thèse aborde ce problème (chapitre 12)