1,213 research outputs found

    Molecular Modeling in Enzyme Design, Toward In Silico Guided Directed Evolution

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    Directed evolution (DE) creates diversity in subsequent rounds of mutagenesis in the quest of increased protein stability, substrate binding, and catalysis. Although this technique does not require any structural/mechanistic knowledge of the system, the frequency of improved mutations is usually low. For this reason, computational tools are increasingly used to focus the search in sequence space, enhancing the efficiency of laboratory evolution. In particular, molecular modeling methods provide a unique tool to grasp the sequence/structure/function relationship of the protein to evolve, with the only condition that a structural model is provided. With this book chapter, we tried to guide the reader through the state of the art of molecular modeling, discussing their strengths, limitations, and directions. In addition, we suggest a possible future template for in silico directed evolution where we underline two main points: a hierarchical computational protocol combining several different techniques and a synergic effort between simulations and experimental validation.Peer ReviewedPostprint (author's final draft

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

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    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

    Computational approaches to fragment based screening

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    Polarization is an often - neglected term in molecular modelling, and this is particularly the case in docking. However, the growing interest in fragment - based drug design, coupled with the small size of fragments that makes them amenable to quantum mechanical treatment, has created new opportunities for including polarization, anisotropic electrostatics and realistic repulsion potentials in docking. We have shown that polarization implemented as induced charges can offer in the region of a 10-15% improvement in native docking results, as judged by the percentage of poses within a rather tight threshold of 0.5 or 1.0 Å, where accurate prediction of binding interactions, are more likely. This is a significant improvement given the quality of current commercial docking programs (such as Glide use d here). This improvement is most apparent when the correct pose is known a priori, so that the extent of polarization is correctly modelled, and scoring is based on force - fields that do not scale the electrostatics. The introduction of specific active - sit e water molecules was shown to have a far greater effect than the polarization, probably because of the introduction of 3 additional full charges, rather than introduction of smaller charge perturbations. With active site waters , polarization is more likely to improve the docking when the water molecule is carefully orientated using quantum mechanical/molecular mechanics (QM/MM) methods. The placement of such water molecules is a matter of great current interest; we have shown that the water molecule can be placed with some degree of reliability simply by docking with the ligand present, provided that the water makes good hydrogen bonding interactions (these are the very conditions under which it is desirable to include the specific active-site water). Anisotropic electrostatics and exponential repulsion for rigid fragments was investigated using Orient and compared to QM/MM methods, all methods merited further research. The general hierarchy is that native docking using Glide (with polarization)> QM/MM (with MM polarization)> Orient-based methods. Thus, we expanded the Glide (with polarization) dataset to include more realistic crossdocking experiments on over 5000 structures. RMSD analysis resulted in many examples of clear improvement for including polarization

    Molecular dynamics simulations and drug discovery

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    This review discusses the many roles atomistic computer simulations of macromolecular (for example, protein) receptors and their associated small-molecule ligands can play in drug discovery, including the identification of cryptic or allosteric binding sites, the enhancement of traditional virtual-screening methodologies, and the direct prediction of small-molecule binding energies. The limitations of current simulation methodologies, including the high computational costs and approximations of molecular forces required, are also discussed. With constant improvements in both computer power and algorithm design, the future of computer-aided drug design is promising; molecular dynamics simulations are likely to play an increasingly important role
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