Structural predictions of biomolecular systems

In this short paper we summarize the current landscape in structural predictions of biomolecular systems and underlying physical principles. The target molecules of predictions are shortly introduced and a summary of current methods for structural characterization is given. Basic principles and methods used in structural predictions are finally summarized

Chelating effect in short polymers for the design of bidentate binders of increased affinity and selectivity

The design of new strong and selective binders is a key step towards the development of new sensing devices and effective drugs. Both affinity and selectivity can be increased through chelation and here we theoretically explore the possibility of coupling two binders through a flexible linker. We prove the enhanced ability of double binders of keeping their target with a simple model where a polymer composed by hard spheres interacts with a spherical macromolecule, such as a protein, through two sticky spots. By Monte Carlo simulations and thermodynamic integration we show the chelating effect to hold for coupling polymers whose radius of gyration is comparable to size of the chelated particle. We show the binding free energy of flexible double binders to be higher than that of two single binders and to be maximized when the binding sites are at distances comparable to the mean free polymer end-to-end distance. The affinity of two coupled binders is therefore predicted to increase non linearly and in turn, by targeting two non-equivalent binding sites, this will lead to higher selectivity

Conformational and translational-rotational entropy from molecular ensembles

Entropy calculation is an important step in the postprocessing of molecular dynamics trajectories or predictive models. In recent years the nearest neighbor method proposed by Demchuk and coworkers [1] has emerged as a powerful method to deal in a flexible way with the dimensionality of the problem. Applications to most important biomolecular processes have been presented [2,3] and a specific development has concerned the computation of rotational-translational entropy which required in turn the definition of a metric in rotation-translation space [4].Two programs have been developed to compute conformational and rotational-translational entropies from biomolecular ensembles [5].Possible estensions of the method will be presented. [1] Nearest neighbor estimates of entropyH Singh, N Misra, V Hnizdo, A Fedorowicz, E DemchukAmerican Journal of Mathematical and Management Sciences, 23 (3-4), 301-321, 2003 [2] Free energy, enthalpy and entropy from implicit solvent end-point simulationsF Fogolari, A Corazza, G EspositoFrontiers in Molecular Biosciences 5, 11, 2018 [3] Distance-based configurational entropy of proteins from molecular dynamics simulationsF Fogolari, A Corazza, S Fortuna, MA Soler, B VanSchouwen, G Brancolini, S Corni, G Melacini, G EspositoPLoS One 10 (7), 2015 [4] Accurate Estimation of the Entropy of Rotation-Translation Probability DistributionsF Fogolari, CJ Dongmo Foumthuim, S Fortuna, MA Soler, A Corazza, G Esposito Journal of chemical theory and computation 12 (1), 1-8, 2016 [5] PDB2ENTROPY and PDB2TRENT: Conformational and Translational-Rotational Entropy from Molecular EnsemblesF Fogolari, O Maloku, CJ Dongmo Foumthuim, A Corazza, G EspositoJournal of chemical information and modeling 58 (7), 1319-1324, 201

Amino acid empirical contact energy definitions for fold recognition in the space of contact maps

BACKGROUND: Contradicting evidence has been presented in the literature concerning the effectiveness of empirical contact energies for fold recognition. Empirical contact energies are calculated on the basis of information available from selected protein structures, with respect to a defined reference state, according to the quasi-chemical approximation. Protein-solvent interactions are estimated from residue solvent accessibility. RESULTS: In the approach presented here, contact energies are derived from the potential of mean force theory, several definitions of contact are examined and their performance in fold recognition is evaluated on sets of decoy structures. The best definition of contact is tested, on a more realistic scenario, on all predictions including sidechains accepted in the CASP4 experiment. In 30 out of 35 cases the native structure is correctly recognized and best predictions are usually found among the 10 lowest energy predictions. CONCLUSION: The definition of contact based on van der Waals radii of alpha carbon and side chain heavy atoms is seen to perform better than other definitions involving only alpha carbons, only beta carbons, all heavy atoms or only backbone atoms. An important prerequisite for the applicability of the approach is that the protein structure under study should not exhibit anomalous solvent accessibility, compared to soluble proteins whose structure is deposited in the Protein Data Bank. The combined evaluation of a solvent accessibility parameter and contact energy allows for an effective gross screening of predictive models

Free Energy, Enthalpy and Entropy from Implicit Solvent End-Point Simulations

Free energy is the key quantity to describe the thermodynamics of biological systems. In this perspective we consider the calculation of free energy, enthalpy and entropy from end-point molecular dynamics simulations. Since the enthalpy may be calculated as the ensemble average over equilibrated simulation snapshots the difficulties related to free energy calculation are ultimately related to the calculation of the entropy of the system and in particular of the solvent entropy. In the last two decades implicit solvent models have been used to circumvent the problem and to take into account solvent entropy implicitly in the solvation terms. More recently outstanding advancement in both implicit solvent models and in entropy calculations are making the goal of free energy estimation from end-point simulations more feasible than ever before. We review briefly the basic theory and discuss the advancements in light of practical applications. \ua9 2018 Fogolari, Corazza and Esposito

A decoy set for the thermostable subdomain from chicken villin headpiece, comparison of different free energy estimators

BACKGROUND: Estimators of free energies are routinely used to judge the quality of protein structural models. As these estimators still present inaccuracies, they are frequently evaluated by discriminating native or native-like conformations from large ensembles of so-called decoy structures. RESULTS: A decoy set is obtained from snapshots taken from 5 long (100 ns) molecular dynamics (MD) simulations of the thermostable subdomain from chicken villin headpiece. An evaluation of the energy of the decoys is given using: i) a residue based contact potential supplemented by a term for the quality of dihedral angles; ii) a recently introduced combination of four statistical scoring functions for model quality estimation (FRST); iii) molecular mechanics with solvation energy estimated either according to the generalized Born surface area (GBSA) or iv) the Poisson-Boltzmann surface area (PBSA) method. CONCLUSION: The decoy set presented here has the following features which make it attractive for testing energy scoring functions: 1) it covers a broad range of RMSD values (from less than 2.0 Å to more than 12 Å); 2) it has been obtained from molecular dynamics trajectories, starting from different non-native-like conformations which have diverse behaviour, with secondary structure elements correctly or incorrectly formed, and in one case folding to a native-like structure. This allows not only for scoring of static structures, but also for studying, using free energy estimators, the kinetics of folding; 3) all structures have been obtained from accurate MD simulations in explicit solvent and after molecular mechanics (MM) energy minimization using an implicit solvent method. The quality of the covalent structure therefore does not suffer from steric or covalent problems. The statistical and physical effective energy functions tested on the set behave differently when native simulation snapshots are included or not in the set and when averaging over the trajectory is performed

Constraint Logic Programming approach to protein structure prediction

BACKGROUND: The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by Constraint Logic Programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. RESULTS: Constraint Logic Programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, Constraint Logic Programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test implementation their (known) secondary structure and the presence of disulfide bridges are used as constraints. Simplified structures obtained in this way have been converted to all atom models with plausible structure. Results have been compared with a similar approach using a well-established technique as molecular dynamics. CONCLUSIONS: The results obtained on small proteins show that Constraint Logic Programming techniques can be employed for studying protein simplified models, which can be converted into realistic all atom models. The advantage of Constraint Logic Programming over other, much more explored, methodologies, resides in the rapid software prototyping, in the easy way of encoding heuristics, and in exploiting all the advances made in this research area, e.g. in constraint propagation and its use for pruning the huge search space

CLP-based protein fragment assembly

The paper investigates a novel approach, based on Constraint Logic Programming (CLP), to predict the 3D conformation of a protein via fragments assembly. The fragments are extracted by a preprocessor-also developed for this work- from a database of known protein structures that clusters and classifies the fragments according to similarity and frequency. The problem of assembling fragments into a complete conformation is mapped to a constraint solving problem and solved using CLP. The constraint-based model uses a medium discretization degree Ca-side chain centroid protein model that offers efficiency and a good approximation for space filling. The approach adapts existing energy models to the protein representation used and applies a large neighboring search strategy. The results shows the feasibility and efficiency of the method. The declarative nature of the solution allows to include future extensions, e.g., different size fragments for better accuracy.Comment: special issue dedicated to ICLP 201

Biomolecular electrostatics with the linearized Poisson-Boltzmann equation

4openopenFOGOLARI F.; ZUCCATO P.; ESPOSITO G.; VIGLINO PFogolari, Federico; Zuccato, P.; Esposito, Gennaro; Viglino, Paol