Search PubMed⌕ Search

PubMed · 16287115

Molecular surface generation using a variable-radius solvent probe.

Abstract

Protein-ligand binding occurs through interactions at the molecular surface. Hence, a proper description of this surface is essential to our understanding of the process of molecular recognition. Recent studies have noted the inadequacy of using a fixed 1.4 A solvent probe radius to generate the molecular surface. This assumes that water molecules approach all surface atoms at an equal distance irrespective of polarity, which is not the case. To adequately model the protein-water boundary requires that the solvent probe radius change according to the polarity of its contacting atoms, smaller near polar atoms and larger near apolar atoms. To our knowledge, no method currently exists to generate the molecular surface of a protein in this manner. Using a modification of the marching tetrahedra algorithm, we present a method to generate molecular surfaces using a variable radius solvent probe. The resulting surface lacks many of the unrealistic small crevices in nonpolar regions that are found when utilizing an invariant 1.4 A solvent probe, while maintaining the fine detail of the surface at polar regions. On application of the method on a test set of 20 protein structures taken from the Protein Data Bank (PDB), we also find far fewer empty unsolvated cavities that are present when using only a 1.4 A solvent probe, while the majority of solvated and polar cavities is retained. This suggests that the majority of empty cavities previously observed in protein structures might simply be artifacts of the surfacing method. We also find that the variable probe surface can have significant effects on electrostatic calculations by generating a better tuned description of the protein-water boundary. We also examined the binding interfaces of a diverse set of 55 protein-protein complexes. We find that using a variable probe results in an increase in perceived shape complementarity at these sites compared to using a 1.4 A solvent probe. The molecular volume and surface area are geometric values that determine various important properties for macromolecules, and the altered description afforded by a variable solvent probe molecular surface can have significant implications in protein recognition, energetics, folding, and stability calculations.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sathesh Bhat, Enrico O Purisima. 2006-01-01. Molecular surface generation using a variable-radius solvent probe.. https://doi.org/10.1002/prot.20682

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Quantifying the peripheral surface information entropy from conformational ensembles of globular protein-peptide complexes.

Predicting favorable protein-peptide binding events remains a central challenge in biophysics, with continued uncertainty surrounding how nonlocal effects shape the global energy landscape. Here, we introduce peripheral surface information entropy, SΨ, a quantitative measure of the statistical variability in apolar and charged non-interacting surface (NIS) proportions across conformational ensembles. Within the Gibbs free-energy relation ΔG = ΔH - TΔS, SΨ is proposed as a computationally tractable entropic proxy rather than a direct thermodynamic observable or stand-alone estimator of binding affinity. Using energy-directed molecular docking via HADDOCK3 and explicit-solvent molecular dynamics simulations, it is demonstrated that favorable binding partners exhibit emergent, low-entropy N-states (discrete macrostates in NIS state space) indicative of preferential apolar/charged surface configurations. Across dozens of peptides and multiple receptor systems (WW, PDZ, and MDM2 domains), dominant N-states persisted under varied docking parameters and initial conditions. A meta-ensemble of 657 complexes from 36 experiments over 15 years confirmed the presence of dominant NIS modes independent of in silico methodology, suggesting an evolutionary selection pressure toward specific NIS fingerprints. These findings establish SΨ as a thermoinformatic descriptor that encodes favorable binding constraints into unique statistical signatures of the NIS.

Entropy↗

Effects of entropy on the gas-phase pyrolysis of ethyl N,N-dimethylcarbamate.

In this study, we examined the gas-phase pyrolysis of ethyl N,N-dimethylcarbamate theoretically at various theoretical levels. The reaction consists of a two-step mechanism, with N,N-dimethylcarbamic acid and ethylene as reaction intermediates. In the first step, the reaction proceeds via a six-membered cyclic transition state (TS), which is more favorable than that via a four-membered cyclic TS. Here, the contribution of entropy to the overall potential energy surface was found to play an important role in determining the rate-limiting step, which was found to be the second step when viewed in terms of the enthalpy of activation (DeltaH(not equal)), but the first step when entropy changes (-TDeltaS(not equal)) were considered. These results are consistent with experimental findings. Moreover, the experimental activation entropy can be reproduced by using the hindered rotor approximation, which converts some low vibration frequencies that correspond to internal rotational modes into hindered rotors.

Entropy↗

Analysis and design of echo state networks.

The design of echo state network (ESN) parameters relies on the selection of the maximum eigenvalue of the linearized system around zero (spectral radius). However, this procedure does not quantify in a systematic manner the performance of the ESN in terms of approximation error. This article presents a functional space approximation framework to better understand the operation of ESNs and proposes an information-theoretic metric, the average entropy of echo states, to assess the richness of the ESN dynamics. Furthermore, it provides an interpretation of the ESN dynamics rooted in system theory as families of coupled linearized systems whose poles move according to the input signal dynamics. With this interpretation, a design methodology for functional approximation is put forward where ESNs are designed with uniform pole distributions covering the frequency spectrum to abide by the richness metric, irrespective of the spectral radius. A single bias parameter at the ESN input, adapted with the modeling error, configures the ESN spectral radius to the input-output joint space. Function approximation examples compare the proposed design methodology versus the conventional design.

Entropy↗