Huntingtin: A Protein with a Peculiar Solvent Accessible Surface
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ABSTRACT:
SUBMITTER: Babbi G
PROVIDER: S-EPMC8001614 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Protein interactions are often accompanied by significant changes in conformation. We have analyzed the relationships between protein structures and the conformational changes they undergo upon binding. Based upon this, we introduce a simple measure, the relative solvent accessible surface area, which can be used to predict the magnitude of binding-induced conformational changes from the structures of either monomeric proteins or bound subunits. Applying this to a large set of protein complexes suggests that large conformational changes upon binding are common. In addition, we observe considerable enrichment of intrinsically disordered sequences in proteins predicted to undergo large conformational changes. Finally, we demonstrate that the relative solvent accessible surface area of monomeric proteins can be used as a simple proxy for protein flexibility. This reveals a powerful connection between the flexibility of unbound proteins and their binding-induced conformational changes, consistent with the conformational selection model of molecular recognition.
| S-EPMC3145976 | biostudies-literature
Project description:The burial of hydrophobic amino acids in the protein core is a driving force in protein folding. The extent to which an amino acid interacts with the solvent and the protein core is naturally proportional to the surface area exposed to these environments. However, an accurate calculation of the solvent-accessible surface area (SASA), a geometric measure of this exposure, is numerically demanding as it is not pair-wise decomposable. Furthermore, it depends on a full-atom representation of the molecule. This manuscript introduces a series of four SASA approximations of increasing computational complexity and accuracy as well as knowledge-based environment free energy potentials based on these SASA approximations. Their ability to distinguish correctly from incorrectly folded protein models is assessed to balance speed and accuracy for protein structure prediction. We find the newly developed "Neighbor Vector" algorithm provides the most optimal balance of accurate yet rapid exposure measures.
| S-EPMC2712621 | biostudies-literature
Project description:In solvent-modulated protein folding, under certain physiological conditions, an equilibrium exists between the unfolded and folded states of the protein without any need to break or make a covalent bond. In this process, interactions between various protein groups (peptides) and solvent molecules are known to play a major role in determining the directionality of the chemical reaction. However, an understanding of the mechanism of action of the co(solvent) by a generic theoretical underpinning is lacking. In this study, a generic solvation model is developed based on statistical mechanics and the thermodynamic transfer free energy model by considering the microenvironment polarity of the interacting co(solvent)-protein system. According to this model, polarity and the fractional solvent-accessible surface areas contribute to the interaction energies. The present model includes various orientations of participating interactant solvent surfaces of suitable areas. As model systems, besides the backbone we consider naturally occurring amino acid residues solvated in ten different osmolytes, small organic compounds known to modulate protein stability. The present model is able to predict the correct trend of the osmolyte-peptide interactions ranging from stabilizing to destabilizing not only for the backbone but also for side chains. Our model predicts Asn, Gln, Asp, Glu, Arg and Pro to be highly stable in most of the protecting osmolytes while Ala, Val, Ile, Leu, Thr, Met, Lys, Phe, Trp and Tyr are predicted to be moderately stable, and Ser, Cys and Histidine are predicted to be least stable. However, in denaturing solvents, both backbone and side chain models show similar stabilities in urea and guanidine. One of the important aspects of this model is that it is essentially parameter-free and consistent with the electrostatics of the interaction partners that make this model suitable for estimating any solute-solvent interaction energies.
| S-EPMC11310836 | biostudies-literature
Project description:BackgroundProtein structure prediction and computational protein design require efficient yet sufficiently accurate descriptions of aqueous solvent. We continue to evaluate the performance of the Coulomb/Accessible Surface Area (CASA) implicit solvent model, in combination with the Charmm19 molecular mechanics force field. We test a set of model parameters optimized earlier, and we also carry out a new optimization in this work, using as a target a set of experimental stability changes for single point mutations of various proteins and peptides. The optimization procedure is general, and could be used with other force fields. The computation of stability changes requires a model for the unfolded state of the protein. In our approach, this state is represented by tripeptide structures of the sequence Ala-X-Ala for each amino acid type X. We followed an iterative optimization scheme which, at each cycle, optimizes the solvation parameters and a set of tripeptide structures for the unfolded state. This protocol uses a set of 140 experimental stability mutations and a large set of tripeptide conformations to find the best tripeptide structures and solvation parameters.ResultsUsing the optimized parameters, we obtain a mean unsigned error of 2.28 kcal/mol for the stability mutations. The performance of the CASA model is assessed by two further applications: (i) calculation of protein-ligand binding affinities and (ii) computational protein design. For these two applications, the previous parameters and the ones optimized here give a similar performance. For ligand binding, we obtain reasonable agreement with a set of 55 experimental mutation data, with a mean unsigned error of 1.76 kcal/mol with the new parameters and 1.47 kcal/mol with the earlier ones. We show that the optimized CASA model is not inferior to the Generalized Born/Surface Area (GB/SA) model for the prediction of these binding affinities. Likewise, the new parameters perform well for the design of 8 SH3 domain proteins where an average of 32.8% sequence identity relative to the native sequences was achieved. Further, it was shown that the computed sequences have the character of naturally-occuring homologues of the native sequences.ConclusionOverall, the two CASA variants explored here perform very well for a wide variety of applications. Both variants provide an efficient solvent treatment for the computational engineering of ligands and proteins.
| S-EPMC2292695 | biostudies-literature
Project description:Molecular dynamics methodologies comprise a vital research tool for structural biology. Molecular dynamics has benefited from technological advances in computing, such as multi-core CPUs and graphics processing units (GPUs), but harnessing the full power of hybrid GPU/CPU computers remains difficult. The generalized Born/solvent-accessible surface area implicit solvent model (GB/SA) stands to benefit from hybrid GPU/CPU computers, employing the GPU for the GB calculation and the CPU for the SA calculation. Here, we explore the computational challenges facing GB/SA calculations on hybrid GPU/CPU computers and demonstrate how NAMD, a parallel molecular dynamics program, is able to efficiently utilize GPUs and CPUs simultaneously for fast GB/SA simulations. The hybrid computation principles demonstrated here are generally applicable to parallel applications employing hybrid GPU/CPU calculations.
| S-EPMC3464051 | biostudies-literature
Project description:Calculating solvent accessible surface areas (SASA) is a run-of-the-mill calculation in structural biology. Although there are many programs available for this calculation, there are no free-standing, open-source tools designed for easy tool-chain integration. FreeSASA is an open source C library for SASA calculations that provides both command-line and Python interfaces in addition to its C API. The library implements both Lee and Richards' and Shrake and Rupley's approximations, and is highly configurable to allow the user to control molecular parameters, accuracy and output granularity. It only depends on standard C libraries and should therefore be easy to compile and install on any platform. The library is well-documented, stable and efficient. The command-line interface can easily replace closed source legacy programs, with comparable or better accuracy and speed, and with some added functionality.
| S-EPMC4776673 | biostudies-literature
Project description:BACKGROUND: From the 1950s computer based renderings of molecules have been produced to aid researchers in their understanding of biomolecular structure and function. A major consideration for any molecular graphics software is the ability to visualise the three dimensional structure of the molecule. Traditionally, this was accomplished via stereoscopic pairs of images and later realised with three dimensional display technologies. Using a haptic feedback device in combination with molecular graphics has the potential to enhance three dimensional visualisation. Although haptic feedback devices have been used to feel the interaction forces during molecular docking they have not been used explicitly as an aid to visualisation. RESULTS: A haptic rendering application for biomolecular visualisation has been developed that allows the user to gain three-dimensional awareness of the shape of a biomolecule. By using a water molecule as the probe, modelled as an oxygen atom having hard-sphere interactions with the biomolecule, the process of exploration has the further benefit of being able to determine regions on the molecular surface that are accessible to the solvent. This gives insight into how awkward it is for a water molecule to gain access to or escape from channels and cavities, indicating possible entropic bottlenecks. In the case of liver alcohol dehydrogenase bound to the inhibitor SAD, it was found that there is a channel just wide enough for a single water molecule to pass through. Placing the probe coincident with crystallographic water molecules suggests that they are sometimes located within small pockets that provide a sterically stable environment irrespective of hydrogen bonding considerations. CONCLUSION: By using the software, named HaptiMol ISAS (available from http://www.haptimol.co.uk), one can explore the accessible surface of biomolecules using a three-dimensional input device to gain insights into the shape and water accessibility of the biomolecular surface that cannot be so easily attained using conventional molecular graphics software.
| S-EPMC2774689 | biostudies-literature
Project description:In this paper, we present dSASA (differentiable SASA), an exact geometric method to calculate solvent accessible surface area (SASA) analytically along with atomic derivatives on GPUs. The atoms in a molecule are first assigned to tetrahedra in groups of four atoms by Delaunay tetrahedrization adapted for efficient GPU implementation and the SASA values for atoms and molecules are calculated based on the tetrahedrization information and inclusion-exclusion method. The SASA values from the numerical icosahedral-based method can be reproduced with more than 98% accuracy for both proteins and RNAs. Having been implemented on GPUs and incorporated into the software Amber, we can apply dSASA to implicit solvent molecular dynamics simulations with inclusion of this nonpolar term. The current GPU version of GB/SA simulations has been accelerated up to nearly 20-fold compared to the CPU version and it outperforms LCPO as the system size increases. The performance and importance of the nonpolar part in implicit solvent modeling are demonstrated in GB/SA simulations of proteins and accurate SASA calculation of nucleic acids.
| S-EPMC10836080 | biostudies-literature
Project description:This article contains inter-residue solvent accessible surface distances between lysines in a comprehensive dataset homo-oligomeric protein complex structures, downloaded from 3D Complex database. Solvent Accessible Surface Distances were calculated with Jwalk algorithm. To avoid unnecessary redundancy due to symmetry, we calculated only distances originating from the first subunit of each protein complex. Redundancy was further reduced by including only the shortest of the two possible inter-subunit alternatives in the final non-redundant dataset. For each protein complexes we also calculated weight ob subunits, number of lysines radius of gyration and average distances. This data can be used for structural analyses of homo-oligomeric protein complexes and for further optimization of distance-based restraints, such as those based on data obtained from chemical cross-linking coupled with mass spectrometry.
| S-EPMC6909155 | biostudies-literature
Project description:We propose a pairwise and readily parallelizable SASA-based nonpolar solvation approach for protein simulations, inspired by our previous pairwise GB polar solvation model development. In this work, we developed a novel function to estimate the atomic and molecular SASAs of proteins, which results in comparable accuracy as the LCPO algorithm in reproducing numerical icosahedral-based SASA values. Implemented in Amber software and tested on consumer GPUs, our pwSASA method reasonably reproduces LCPO simulation results, but accelerates MD simulations up to 30 times compared to the LCPO implementation, which is greatly desirable for protein simulations facing sampling challenges. The value of incorporating the nonpolar term in implicit solvent simulations is explored on a peptide fragment containing the hydrophobic core of HP36 and evaluating thermal stability profiles of four small proteins.
| S-EPMC6600810 | biostudies-literature