Mass & secondary structure propensity of amino acids explain their mutability and evolutionary replacements

Why is an amino acid replacement in a protein accepted during evolution? The answer given by bioinformatics relies on the frequency of change of each amino acid by another one and the propensity of each to remain unchanged. We propose that these replacement rules are recoverable from the secondary structural trends of amino acids. A distance measure between high-resolution Ramachandran distributions reveals that structurally similar residues coincide with those found in substitution matrices such as BLOSUM: Asn Asp, Phe Tyr, Lys Arg, Gln Glu, Ile Val, Met → Leu; with Ala, Cys, His, Gly, Ser, Pro, and Thr, as structurally idiosyncratic residues. We also found a high average correlation (\overline{R} R = 0.85) between thirty amino acid mutability scales and the mutational inertia (I X ), which measures the energetic cost weighted by the number of observations at the most probable amino acid conformation. These results indicate that amino acid substitutions follow two optimally-efficient principles: (a) amino acids interchangeability privileges their secondary structural similarity, and (b) the amino acid mutability depends directly on its biosynthetic energy cost, and inversely with its frequency. These two principles are the underlying rules governing the observed amino acid substitutions. © 2017 The Author(s)

Computational methods to design biophysical experiments for the study of protein dynamics

In recent years, new software and automated instruments have enabled us to imagine autonomous or "self-driving" laboratories of the future. However, ways to design new scientific studies remain unexplored due to challenges such as minimizing associated time, labor, and expense of sample preparation and data acquisition. In the field of protein biophysics, computational simulations such as molecular dynamics and spectroscopy-based experiments such as double electron-electron resonance and Fluorescence resonance energy transfer techniques have emerged as critical experimental tools to capture protein dynamic behavior, a change in protein structure as a function of time which is important for their cellular functions. These techniques can lead to the characterization of key protein conformations and can capture protein motions over a diverse range of timescales. This work addresses the problem of the choice of probe positions in a protein, which residue-pairs should experimentalists choose for spectroscopy experiments. For this purpose, molecular dynamics simulations and Markov state models of protein conformational dynamics are utilized to rank sets of labeled residue-pairs in terms of their ability to capture the conformational dynamics of the protein. The applications of our experimental study design methodology called OptimalProbes on different types of proteins and experimental techniques are examined. In order to utilize this method for a previously uncharacterized protein, atomistic molecular dynamics simulations are performed to study a bacterial di/tri-peptide transporter a typical representative of the Major Facilitator Superfamily of membrane proteins. This was followed by ideal double electron-electron resonance experimental choice predictions based on the simulation data. The predicted choices are superior to the residue-pair choices made by experimentalists which failed to capture the slowest dynamical processes in the conformational ensemble obtained from our long timescale simulations. For molecular dynamics simulations based design of experimental studies to succeed both ensembles need to be comparable. Since this has not been the case for double electron-electron resonance distance distributions and molecular simulations, we explore possible reasons that can lead to mismatches between experiments and simulations in order to reconcile simulated ensembles with experimentally obtained distance traces. This work is one of the first studies towards integrating spectroscopy experiment design into a computational method systematically based on molecular simulations

The Energy Landscape, Folding Pathways and the Kinetics of a Knotted Protein

The folding pathway and rate coefficients of the folding of a knotted protein are calculated for a potential energy function with minimal energetic frustration. A kinetic transition network is constructed using the discrete path sampling approach, and the resulting potential energy surface is visualized by constructing disconnectivity graphs. Owing to topological constraints, the low-lying portion of the landscape consists of three distinct regions, corresponding to the native knotted state and to configurations where either the N- or C-terminus is not yet folded into the knot. The fastest folding pathways from denatured states exhibit early formation of the N-terminus portion of the knot and a rate-determining step where the C-terminus is incorporated. The low-lying minima with the N-terminus knotted and the C-terminus free therefore constitute an off-pathway intermediate for this model. The insertion of both the N- and C-termini into the knot occur late in the folding process, creating large energy barriers that are the rate limiting steps in the folding process. When compared to other protein folding proteins of a similar length, this system folds over six orders of magnitude more slowly.Comment: 19 page

Complete Configuration Space Analysis for Structure Determination of Symmetric Homo-oligomers by NMR

Symmetric homo-oligomers (protein complexes with similar subunits arranged symmetrically) play pivotal roles in complex biological processes such as ion transport and cellular regulation. Structure determination of these complexes is necessary in order to gain valuable insights into their mechanisms. Nuclear Magnetic Resonance (NMR) spectroscopy is an experimental technique used for structural studies of such complexes. The data available for structure determination of symmetric homo-oligomers by NMR is often sparse and ambiguous in nature, raising concerns about existing heuristic approaches for structure determination. We have developed an approach that is complete in that it identifies all consistent conformations, data-driven in that it separately evaluates the consistency of structures to data and biophysical constraints and efficient in that it avoids explicit consideration of each of the possible structures separately. By being complete, we ensure that native conformations are not missed. By being data-driven, we are able to separately quantify the information content in the data alone versus data and biophysical modeling. We take a configuration space (degree-of-freedom) approach that provides a compact representation of the conformation space and enables us to efficiently explore the space of possible conformations. This thesis demonstrates that the configuration space-based method is robust to sparsity and ambiguity in the data and enables complete, data-driven and efficient structure determination of symmetric homo-oligomers

On the role of residue phosphorylation in 14-3-3 partners: AANAT as a case study

Twenty years ago, a novel concept in protein structural biology was discovered: the intrinsically disordered regions (IDRs). These regions remain largely unstructured under native conditions and the more are studied, more properties are attributed to them. Possibly, one of the most important is their ability to conform a new type of protein-protein interaction. Besides the classical domain-to-domain interactions, IDRs follow a ´fly-casting´ model including ´induced folding´. Unfortunately, it is only possible to experimentally explore initial and final states. However, the complete movie of conformational changes of protein regions and their characterization can be addressed by in silico experiments. Here, we simulate the binding of two proteins to describe how the phosphorylation of a single residue modulates the entire process. 14-3-3 protein family is considered a master regulator of phosphorylated proteins and from a modern point-of-view, protein phosphorylation is a three component system, with writers (kinases), erasers (phosphatases) and readers. This later biological role is attributed to the 14-3-3 protein family. Our molecular dynamics results show that phosphorylation of the key residue Thr31 in a partner of 14-3-3, the aralkylamine N-acetyltransferase, releases the fly-casting mechanism during binding. On the other hand, the non-phosphorylation of the same residue traps the proteins, systematically and repeatedly driving the simulations into wrong protein-protein conformations.Fil: Masone, Diego Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Cienicas Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; Argentina. Universidad Nacional de Cuyo. Facultad de Ingeniería; ArgentinaFil: Uhart, Marina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Cienicas Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Bustos, Diego Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Cienicas Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; Argentina. Universidad Nacional de Cuyo. Facultad de Ciencias Exactas y Naturales; Argentin

Methods for estimation of model accuracy in CASP12

Methods to reliably estimate the quality of 3D models of proteins are essential drivers for the wide adoption and serious acceptance of protein structure predictions by life scientists. In this paper, the most successful groups in CASP12 describe their latest methods for Estimates of Model Accuracy (EMA). We show that pure single model accuracy estimation methods have shown clear progress since CASP11; the three top methods (MESHI, ProQ3, SVMQA) all perform better than the top method of CASP11 (ProQ2). While the pure single model accuracy estimation methods outperform quasi-single (ModFOLD6 variations) and consensus methods (Pcons, ModFOLDclust2, Pcomb-domain and Wallner) in model selection, they are still not as good as those methods in absolute model quality estimation and predictions of local quality. Finally, we show that when using contact based model quality measures (CAD, lDDT) the single model quality methods perform relatively better

Computational Modeling of (De)-Solvation Effects and Protein Flexibility in Protein-Ligand Binding using Molecular Dynamics Simulations

Water is a crucial participant in virtually all cellular functions. Evidently, water molecules in the binding site contribute significantly to the strength of intermolecular interactions in the aqueous phase by mediating protein-ligand interactions, solvating and de-solvating both ligand and protein upon protein-ligand dissociation and association. Recently many published studies use water distributions in the binding site to retrospectively explain and rationalize unexpected trends in structure-activity relationships (SAR). However, traditional approaches cannot quantitatively predict the thermodynamic properties of water molecules in the binding sites and its associated contribution to the binding free energy of a ligand. We have developed and validated a computational method named WATsite to exploit high-resolution solvation maps and thermodynamic profiles to elucidate the water molecules’ potential contribution to protein-ligand and protein-protein binding. We have also demonstrated the utility of the computational method WATsite to help direct medicinal chemistry efforts by using explicit water de-solvation. In addition, protein conformational change is typically involved in the ligand-binding process which may completely change the position and thermodynamic properties of the water molecules in the binding site before or upon ligand binding. We have shown the interplay between protein flexibility and solvent reorganization, and we provide a quantitative estimation of the influence of protein flexibility on desolvation free energy and, therefore, protein-ligand binding. Different ligands binding to the same target protein can induce different conformational adaptations. In order to apply WATsite to an ensemble of different protein conformations, a more efficient implementation of WATsite based on GPU-acceleration and system truncation has been developed. Lastly, by extending the simulation protocol from pure water to mixed water-organic probes simulations, accurate modeling of halogen atom-protein interactions has been achieved