Journal of Computational Biophysics and Chemistry

Water molecules play a key role in all biochemical processes. They help define the shape of proteins, and they are reactant or product in many reactions and are released as ligands are bound. They facilitate the transfer of protons through transmembrane proton channel, pump and transporter proteins. Continuum electrostatics (CE) force fields used by program Multiconformation CE (MCCE) capture electrostatic interactions in biomolecules with an implicit solvent, which captures the averaged solvent water equilibrium properties. Hybrid CE methods can use explicit water molecules within the protein surrounded by implicit solvent. These hybrid methods permit the study of explicit hydrogen bond networks within the protein and allow analysis of processes such as proton transfer reactions. Yet hybrid CE methods have not been rigorously tested. Here, we present an explicit treatment of water molecules in the Gramicidin A (gA) channel using MCCE and compare the resulting distributions of water molecules and key hydration features against those obtained with explicit solvent Molecular Dynamics (MD) simulations with the nonpolarizable CHARMM36 and polarizable Drude force fields. CHARMM36 leads to an aligned water wire in the channel characterized by a large absolute net water dipole moment; the MCCE and Drude analysis lead to a small net dipole moment as the water molecules change orientation within the channel. The correct orientation is not as yet known, so these calculations identify an open question.

Cyclic dipeptides show interesting biological activities such as antitumor, antiviral and so on. In biological systems, the bioavailability of drugs is determined by several parameters such as pKa values. In this study, we used DFT and thermodynamics cycle to determine pKa value of side chain of lysine in linear and cyclic dipeptides. All considered dipeptides were optimized using B3LYP and RMSD tool was used to compare the optimized structures. The calculated pKa values were compared with the available experimental data. Our results show that pKa of side chain of lysine increases for cyclic dipeptides compared to the linear ones. To justify the reason of increasing of pKa of cyclic dipeptides, we used NBO and AIM analyses. The analyses showed that a hydrogen bond in cyclic lysine dipeptides is responsible for increasing of pKa.

We have further improved and validated PKA17, our fast software for predicting p$K_{\text{a}}$ values of protein residues. The methodology employs coarse-grained lattice-based model of proteins. It was previously demonstrated to perform ca. an order of magnitude faster than such successful and widely used frameworks as PROPKA without losing accuracy of the calculations. In this paper, we report the following improvements: (i) We have expanded our training and testing sets of protein residues by 128%, from 442 to 1009 cases; (ii) we have added and parameterized PKA17’s capability to predict acidity constants of cysteine residues that are important in many biomedical applications, including but not limited to binding of such transition metal ions as copper(I) and platinum(II); (iii) we have carried out the comparison of accuracy of predicted Asp and Glu p$K_{\text{a}}$ values not only between PKA17 and PROPKA, but also with DelPhiPKa and H$++$. The computational speed of PKA17 remains the highest of all the methods used in our studies, and the accuracy of PKA17 is somewhat inferior only to those of such more sophisticated methods as Multi-Conformation Continuum Electrostatic (MCCE) ones. For instance, the average unsigned deviations of predicted p$K_{\text{a}}$ values from the experiment for 416 Glu residues were found to be 0.706, 0.766, 0.867, and 0.520pH units when obtained with PROPKA, DelPhiPKa, H$++$, and PKA17, respectively (0.487pH units with PKA17 after refitting). The average unsigned errors for cysteine p$K_{\text{a}}$ values calculated with PROPKA, DelPhiPKa, H$++$, and PKA17 were 3.50, 2.06, 3.17, and 1.26pH units. PKA17 has also performed well in assessing the cysteine acidity constants of the CXXC motif of CopZ protein involved in binding of copper(I) metal ions. Our results demonstrate that the PKA17 methodology and current parameters are accurate and robust, and its computational speed makes it possible to be employed in large-scale p$K_{\text{a}}$ screening calculations and in constant-pH protein dynamics simulations. The resulting PKA17 software has been deployed online at http://kaminski.wpi.edu/PKA17/pka_calc.html.

Apolipophorin-III (ApoLp-III) is required for stabilization of molecular shuttles of lipid fuels in insects and is found to contribute to the insect immune reaction. Rearrangement of its five $\alpha$-helices enables ApoLp-III to reversibly associate with lipids. We investigate computationally the conformational changes of ApoLp-III and the pH-dependence of the binding free energy of ApoLp-III association with a lipid disk. A dominant binding mode along with several minor, low population, modes of the ApoLp-III binding to a lipid disk was identified. The pH-dependence of the binding energy for ApoLp-III with the lipid disk is predicted to be significant, with the pH-optimum at pH$=8.0$. The calculations suggest that there are no direct interactions between the lipid head groups and titratable residues of ApoLp-III. In the physiological pH range from 6.0 to 9.0, the binding free energy of ApoLp-III with the lipid disk decreases significantly with respect to its optimal value at pH 8.0 (at pH$=6.0$, it is 1.02kcal/mol and at pH$=9.0$ it is 0.23kcal/mol less favorable than at the optimal pH$=8.0$), indicating that the pH is an important regulator of ApoLp-III lipid disk association.

Computational prediction of the pKa of ionizable groups remains a central challenge in biomolecular modeling. Although all-atom fixed-charge force fields could be accurate to describe the interaction network within the biomolecules, proper sampling techniques are required to obtain the thermodynamic information in the (de)protonation event. Sufficient sampling requires an ensemble of structures from simulations with proper treatments of the acid-base equilibria, and the grand canonical simulation technique could be used to model the growth/annihilation of hydrogen atoms by merging Hamiltonians of different protonation states into one simulation ensemble. The electrostatic feature of nucleotide systems is especially difficult to model, and the situation becomes more challenging when the ionizable site is highly perturbed. Although there are many successful predictions obtained from the grand canonical constant pH simulations, few reports focus on highly perturbed nucleotide systems with unconventional base-pair features. In this work, with the discrete constant pH method, we investigate the titration thermodynamics of an adenine in the catalytic triad in a 35-nucleotide single-stranded RNA hairpin, featuring an unconventional GA mismatch and a substantially shifted pKa value. Validation tests are performed with two system setups, both of which provide pKa predictions in good agreement with the experimental value. A single-configuration-based technique is used to calculate the pKa for comparison. The current success indicates the predictive power of the current nucleotide modeling framework.

A common approach to computing protein pKas uses a continuum dielectric model in which the protein is a low dielectric medium with embedded atomic point charges, the solvent is a high dielectric medium with a Boltzmann distribution of ionic charges, and the pKa is related to the electrostatic free energy which is obtained by solving the Poisson–Boltzmann equation. Starting from the model pKa for a titrating residue, the method obtains the intrinsic pKa and then computes the protonation probability for a given pH including site–site interactions. This approach assumes that acid dissociation does not affect protein conformation aside from adding or deleting charges at titratable sites. In this work, we demonstrate our treecode-accelerated boundary integral (TABI) solver for the relevant electrostatic calculations. The pKa computing procedure is enclosed in a convenient Python wrapper which is publicly available at the corresponding author’s website. Predicted results are compared with experimental pKas for several proteins. Among ongoing efforts to improve protein pKa calculations, the advantage of TABI is that it reduces the numerical errors in the electrostatic calculations so that attention can be focused on modeling assumptions.

In this study, molecular dynamics (MD) simulations were performed on cellulose and aminated cellulose. Obtained results show the presence of amine moieties and their protonation, positive charges and repulsive forces increase. As a result, the van der Waals and electrostatic interactions and hydrogen bonding number decrease. Then, paclitaxel was loaded through docking into the structures and was studied by MD simulations. The simulations were performed in several protonation states along with 25^∘C, 37^∘C, 42^∘C and 50^∘C temperatures. The carrier/ligand system behaviors were analyzed. The results indicate the increase of temperature and protonation decrease hydrogen bonding number between drug and carrier and increase binding free energy. At last, to compare the simulations results, paclitaxel was loaded in cellulose and aminated cellulose and investigated in the in vitro release at two conditions (37^∘C, pH 7.4, and 42^∘C, pH 5). Experimental results prove computational results as pH/temperature-responsive system.

Dengue virus causes serious diseases and deaths in the world. Understanding the fundamental mechanisms of dengue virus is highly demanded to develop treatments for dengue virus caused diseases. Here, we present a computational work which focused on the stability of dengue viral capsid. The interactions among E proteins on the dengue viral capsid were studied using several computational approaches. It was found that the electrostatic distribution on a single E protein monomer is highly inhomogeneous, which makes an E protein strongly binding with another E protein. This is the reason why all the E proteins form homodimers as the basic units on the whole dengue viral capsids. The pKa calculations of E proteins demonstrated that the folding energy of an E protein is low and stable in the range of pH 6–10, which is different from many other proteins that are stable at certain pH. The pH dependence of binding energy of E protein homodimer shows that the binding energy is low and independent from pH when the pH is also in the range of 6–10. This finding implies that the dengue virus can survive in a wide range of pH, which can explain why the dengue virus is so widely distributed in the world and spreads fast.