DelPhi Suite: New Developments and Review of Functionalities.

Electrostatic potential, energies, and forces affect virtually any process in molecular biology, however, computing these quantities is a difficult task due to irregularly shaped macromolecules and the presence of water. Here, we report a new edition of the popular software package DelPhi along with describing its functionalities. The new DelPhi is a C++ object-oriented package supporting various levels of multiprocessing and memory distribution. It is demonstrated that multiprocessing results in significant improvement of computational time. Furthermore, for computations requiring large grid size (large macromolecular assemblages), the approach of memory distribution is shown to reduce the requirement of RAM and thus permitting large-scale modeling to be done on Linux clusters with moderate architecture. The new release comes with new features, whose functionalities and applications are described as well. © 2019 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc.

Comparative study of the effect of disease causing and benign mutations in position Q92 on cholesterol binding by the NPC1 n-terminal domain.

The Niemann-Pick type C1 (NPC1) protein is a large transmembrane protein located in lysosomes/endosomes. NPC1 binds cholesterol (CLR) and transports it to cellular membrane and endoplasmic reticulum. Mutations in NPC1 cause Niemann-Pick type C (NPC) disease, a rare autosomal disorder characterized by intracellular accumulations of CLR and subsequent neurodegeneration leading to premature death. Among known disease-causing mutations in NPC1, Q92R is the one that is located in the N-terminal cholesterol-binding domain [NTD]. Here we study the effect of the mutation on the ability of NPC1 (NTD) to bind and retain CLR in the binding pocket using structural analysis. We compare characteristics of the Q92R and Q92S mutant type (MT) protein, which is predicted to be benign. We provide detailed investigation of the CLR-NPC1 (NTD) binding process; and propose the mechanism, by which Q92R mutation causes NPC disease. We show that although Q92 residue neither directly participates in catalytic activity of the NPC1 (NTD), nor defines its CLR-binding specificity - it is important for the overall protein structure as well as for providing favorable electrostatic environment for CLR transfer. Our results suggest that a negative electrostatic potential of the CLR binding site (the S-opening) might promote NPC2 interaction with NPC1 (NTD) and/or proper CLR orientation and its enforced transfer. We show that in contrast to the benign Q92S mutation, Q92R significantly reduces electrostatic potential around S-opening, and thus likely affects NPC1 (NTD)-NPC2 interaction and/or CLR transfer from NPC2 to NPC1.

Class III Histidine Kinases: a Recently Accessorized Kinase Domain in Putative Modulators of Type IV Pilus-Based Motility.

Histidine kinases are key components of regulatory systems that enable bacteria to respond to environmental changes. Two major classes of histidine kinases are recognized on the basis of their modular design: classical (HKI) and chemotaxis specific (HKII). Recently, a new type of histidine kinase that appeared to have features of both HKIs and HKIIs was identified and termed HKIII; however, the details of HKIII's relationship to other two classes of histidine kinases, their function, and evolutionary history remain unknown. Here, we carried out genomic, phylogenetic, and protein sequence analyses that allowed us to reveal the unusual evolutionary history of this protein family, formalize its distinctive features, and propose its putative function. HKIIIs are characterized by the presence of sensory domains and the lack of a dimerization domain, which is typically present in all histidine kinases. In addition to a single-domain response regulator, HKIII signal transduction systems utilize CheX phosphatase and, in many instances, an unorthodox soluble chemoreceptor that are usual components of chemotaxis signal transduction systems. However, many HKIII genes are found in genomes completely lacking chemotaxis genes, thus decoupling their function from chemotaxis. By contrast, all HKIII-containing genomes also contain pilT, a marker gene for bacterial type IV pilus-based motility, whose regulation is proposed as a putative function for HKIII. These signal transduction systems have a narrow phyletic distribution but are present in many emerging and opportunistic pathogens, thus offering an attractive potential target for future antimicrobial drug design.IMPORTANCE Bacteria adapt to their environment and their hosts by detecting signals and regulating their cellular functions accordingly. Here, we describe a largely unexplored family of signal transduction histidine kinases, called HKIII, that have a unique modular design. While they are currently identified in a relatively short list of bacterial species, this list contains many emerging pathogens. We show that HKIIIs likely control bacterial motility across solid surfaces, which is a key virulence factor in many bacteria, including those causing severe infections. Full understanding of this putative function may help in designing effective drugs against pathogens that will not affect the majority of the beneficial human microbiome.

A mutation in a ganglioside biosynthetic enzyme, ST3GAL5, results in salt & pepper syndrome, a neurocutaneous disorder with altered glycolipid and glycoprotein glycosylation.

'Salt & Pepper' syndrome is an autosomal recessive condition characterized by severe intellectual disability, epilepsy, scoliosis, choreoathetosis, dysmorphic facial features and altered dermal pigmentation. High-density SNP array analysis performed on siblings first described with this syndrome detected four shared regions of loss of heterozygosity (LOH). Whole-exome sequencing narrowed the candidate region to chromosome 2p11.2. Sanger sequencing confirmed a homozygous c.994G>A transition (p.E332K) in the ST3GAL5 gene, which encodes for a sialyltransferase also known as GM3 synthase. A different homozygous mutation of this gene has been previously associated with infantile-onset epilepsy syndromes in two other cohorts. The ST3GAL5 enzyme synthesizes ganglioside GM3, a glycosophingolipid enriched in neural tissue, by adding sialic acid to lactosylceramide. Unlike disorders of glycosphingolipid (GSL) degradation, very little is known regarding the molecular and pathophysiologic consequences of altered GSL biosynthesis. Glycolipid analysis confirmed a complete lack of GM3 ganglioside in patient fibroblasts, while microarray analysis of glycosyltransferase mRNAs detected modestly increased expression of ST3GAL5 and greater changes in transcripts encoding enzymes that lie downstream of ST3GAL5 and in other GSL biosynthetic pathways. Comprehensive glycomic analysis of N-linked, O-linked and GSL glycans revealed collateral alterations in response to loss of complex gangliosides in patient fibroblasts and in zebrafish embryos injected with antisense morpholinos that targeted zebrafish st3gal5 expression. Morphant zebrafish embryos also exhibited increased apoptotic cell death in multiple brain regions, emphasizing the importance of GSL expression in normal neural development and function.

Predicting Binding Free Energy Change Caused by Point Mutations with Knowledge-Modified MM/PBSA Method.

A new methodology termed Single Amino Acid Mutation based change in Binding free Energy (SAAMBE) was developed to predict the changes of the binding free energy caused by mutations. The method utilizes 3D structures of the corresponding protein-protein complexes and takes advantage of both approaches: sequence- and structure-based methods. The method has two components: a MM/PBSA-based component, and an additional set of statistical terms delivered from statistical investigation of physico-chemical properties of protein complexes. While the approach is rigid body approach and does not explicitly consider plausible conformational changes caused by the binding, the effect of conformational changes, including changes away from binding interface, on electrostatics are mimicked with amino acid specific dielectric constants. This provides significant improvement of SAAMBE predictions as indicated by better match against experimentally determined binding free energy changes over 1300 mutations in 43 proteins. The final benchmarking resulted in a very good agreement with experimental data (correlation coefficient 0.624) while the algorithm being fast enough to allow for large-scale calculations (the average time is less than a minute per mutation).

SAAFEC: Predicting the Effect of Single Point Mutations on Protein Folding Free Energy Using a Knowledge-Modified MM/PBSA Approach.

UNLABELLED: Folding free energy is an important biophysical characteristic of proteins that reflects the overall stability of the 3D structure of macromolecules. Changes in the amino acid sequence, naturally occurring or made in vitro, may affect the stability of the corresponding protein and thus could be associated with disease. Several approaches that predict the changes of the folding free energy caused by mutations have been proposed, but there is no method that is clearly superior to the others. The optimal goal is not only to accurately predict the folding free energy changes, but also to characterize the structural changes induced by mutations and the physical nature of the predicted folding free energy changes. Here we report a new method to predict the Single Amino Acid Folding free Energy Changes (SAAFEC) based on a knowledge-modified Molecular Mechanics Poisson-Boltzmann (MM/PBSA) approach. The method is comprised of two main components: a MM/PBSA component and a set of knowledge based terms delivered from a statistical study of the biophysical characteristics of proteins. The predictor utilizes a multiple linear regression model with weighted coefficients of various terms optimized against a set of experimental data. The aforementioned approach yields a correlation coefficient of 0.65 when benchmarked against 983 cases from 42 proteins in the ProTherm database. AVAILABILITY: the webserver can be accessed via http://compbio.clemson.edu/SAAFEC/.

SAAMBE: Webserver to Predict the Charge of Binding Free Energy Caused by Amino Acids Mutations.

Predicting the effect of amino acid substitutions on protein-protein affinity (typically evaluated via the change of protein binding free energy) is important for both understanding the disease-causing mechanism of missense mutations and guiding protein engineering. In addition, researchers are also interested in understanding which energy components are mostly affected by the mutation and how the mutation affects the overall structure of the corresponding protein. Here we report a webserver, the Single Amino Acid Mutation based change in Binding free Energy (SAAMBE) webserver, which addresses the demand for tools for predicting the change of protein binding free energy. SAAMBE is an easy to use webserver, which only requires that a coordinate file be inputted and the user is provided with various, but easy to navigate, options. The user specifies the mutation position, wild type residue and type of mutation to be made. The server predicts the binding free energy change, the changes of the corresponding energy components and provides the energy minimized 3D structure of the wild type and mutant proteins for download. The SAAMBE protocol performance was tested by benchmarking the predictions against over 1300 experimentally determined changes of binding free energy and a Pearson correlation coefficient of 0.62 was obtained. How the predictions can be used for discriminating disease-causing from harmless mutations is discussed. The webserver can be accessed via http://compbio.clemson.edu/saambe_webserver/.

On human disease-causing amino acid variants: statistical study of sequence and structural patterns.

Statistical analysis was carried out on large set of naturally occurring human amino acid variations, and it was demonstrated that there is a preference for some amino acid substitutions to be associated with diseases. At an amino acid sequence level, it was shown that the disease-causing variants frequently involve drastic changes in amino acid physicochemical properties of proteins such as charge, hydrophobicity, and geometry. Structural analysis of variants involved in diseases and being frequently observed in human population showed similar trends: disease-causing variants tend to cause more changes in hydrogen bond network and salt bridges as compared with harmless amino acid mutations. Analysis of thermodynamics data reported in the literature, both experimental and computational, indicated that disease-causing variants tend to destabilize proteins and their interactions, which prompted us to investigate the effects of amino acid mutations on large databases of experimentally measured energy changes in unrelated proteins. Although the experimental datasets were linked neither to diseases nor exclusory to human proteins, the observed trends were the same: amino acid mutations tend to destabilize proteins and their interactions. Having in mind that structural and thermodynamics properties are interrelated, it is pointed out that any large change in any of them is anticipated to cause a disease.

Statistical investigation of surface bound ions and further development of BION server to include pH and salt dependence.

Ions are engaged in multiple biological processes in cells. By binding to the macromolecules or being mobile in the solvent, they maintain the integrity of the structure of macromolecules; participate in their enzymatic activity; or screen electrostatic interactions. While experimental methods are not always able to assign the exact location of ions, computational methods are in demand. Although the majority of computational methods are successful in predicting the position of ions buried inside macromolecules, they are less effective in deciphering positions of surface bound ions. Here, we propose the new BION algorithm (http://compbio.clemson.edu/bion_server_ph/) that predicts the location of the surface bound ions. It is more efficient and accurate compared to the previous version since it uses more advanced clustering algorithm in combination with pairing rules. In addition, the BION webserver allows specifying the pH and the salt concentration in predicting ions positions.

BION web server: predicting non-specifically bound surface ions.

MOTIVATION: Ions are essential component of the cell and frequently are found bound to various macromolecules, in particular to proteins. A binding of an ion to a protein greatly affects protein's biophysical characteristics and needs to be taken into account in any modeling approach. However, ion's bounded positions cannot be easily revealed experimentally, especially if they are loosely bound to macromolecular surface. RESULTS: Here, we report a web server, the BION web server, which addresses the demand for tools of predicting surface bound ions, for which specific interactions are not crucial; thus, they are difficult to predict. The BION is easy to use web server that requires only coordinate file to be inputted, and the user is provided with various, but easy to navigate, options. The coordinate file with predicted bound ions is displayed on the output and is available for download.

On the electrostatic properties of homodimeric proteins.

A large fraction of proteins function as homodimers, but it is not always clear why the dimerization is important for functionality since frequently each monomer possesses a distinctive active site. Recent work (PLoS Computational Biology, 9(2), e1002924) indicates that homodimerization may be important for forming an electrostatic funnel in the spermine synthase homodimer which guides changed substrates toward the active centers. This prompted us to investigate the electrostatic properties of a large set of homodimeric proteins and resulted in an observation that in a vast majority of the cases the dimerization indeed results in specific electrostatic features, although not necessarily in an electrostatic funnel. It is demonstrated that the electrostatic dipole moment of the dimer is predominantly perpendicular to the axis connecting the centers of the mass of the monomers. In addition, the surface points with highest potential are located in the proximity of the interfacial plane of the homodimeric complexes. These findings indicate that frequently homodimerization provides specific electrostatic features needed for the function of proteins.

Continuous development of schemes for parallel computing of the electrostatics in biological systems: implementation in DelPhi.

Due to the enormous importance of electrostatics in molecular biology, calculating the electrostatic potential and corresponding energies has become a standard computational approach for the study of biomolecules and nano-objects immersed in water and salt phase or other media. However, the electrostatics of large macromolecules and macromolecular complexes, including nano-objects, may not be obtainable via explicit methods and even the standard continuum electrostatics methods may not be applicable due to high computational time and memory requirements. Here, we report further development of the parallelization scheme reported in our previous work (Li, et al., J. Comput. Chem. 2012, 33, 1960) to include parallelization of the molecular surface and energy calculations components of the algorithm. The parallelization scheme utilizes different approaches such as space domain parallelization, algorithmic parallelization, multithreading, and task scheduling, depending on the quantity being calculated. This allows for efficient use of the computing resources of the corresponding computer cluster. The parallelization scheme is implemented in the popular software DelPhi and results in speedup of several folds. As a demonstration of the efficiency and capability of this methodology, the electrostatic potential, and electric field distributions are calculated for the bovine mitochondrial supercomplex illustrating their complex topology, which cannot be obtained by modeling the supercomplex components alone.

Predicting nonspecific ion binding using DelPhi.

Ions are an important component of the cell and affect the corresponding biological macromolecules either via direct binding or as a screening ion cloud. Although some ion binding is highly specific and frequently associated with the function of the macromolecule, other ions bind to the protein surface nonspecifically, presumably because the electrostatic attraction is strong enough to immobilize them. Here, we test such a scenario and demonstrate that experimentally identified surface-bound ions are located at a potential that facilitates binding, which indicates that the major driving force is the electrostatics. Without taking into consideration geometrical factors and structural fluctuations, we show that ions tend to be bound onto the protein surface at positions with strong potential but with polarity opposite to that of the ion. This observation is used to develop a method that uses a DelPhi-calculated potential map in conjunction with an in-house-developed clustering algorithm to predict nonspecific ion-binding sites. Although this approach distinguishes only the polarity of the ions, and not their chemical nature, it can predict nonspecific binding of positively or negatively charged ions with acceptable accuracy. One can use the predictions in the Poisson-Boltzmann approach by placing explicit ions in the predicted positions, which in turn will reduce the magnitude of the local potential and extend the limits of the Poisson-Boltzmann equation. In addition, one can use this approach to place the desired number of ions before conducting molecular-dynamics simulations to neutralize the net charge of the protein, because it was shown to perform better than standard screened Coulomb canned routines, or to predict ion-binding sites in proteins. This latter is especially true for proteins that are involved in ion transport, because such ions are loosely bound and very difficult to detect experimentally.

Effect of pH on the Ability of N-Terminal Domain of Human NPC1 to Recognize, Bind, and Transfer Cholesterol.

Niemann-Pick type C1 (NPC1) is a large multidomain transmembrane protein essential for transporting cholesterol (CLR) from late endosomes and lysosomes to the endoplasmic reticulum and other cellular compartments. The lumen-facing N-terminal domain (NTD), involved in direct binding of CLR, is expected to have an optimum activity at acidic pH = 4.5. Here, we show that acidic pH is vital for the functionality of NPC1(NTD) and should be taken into account when studying the protein activity. We applied evolutionary, structural, and physicochemical analyses to decipher the consequences of a change in pH from acidic (pH = 4.5) to neutral (pH = 7.2) on the structural integrity of the NTD and its ability to bind CLR. We revealed that the change in pH from 4.5 to 7.2 increases the potential energy of the protein in both apo- and holo-states making the system less energetically favorable. At neutral pH, the flexibility of the protein in the apo-state is decreased caused by the alteration of specific interactions, which in turn might have a high impact on ligand recognition and binding. In contrast, neutral pH significantly exaggerates the flexibility of the protein with bound CLR that causes a partial exposure of the ligand to the water phase and its mislocation inside the ligand-binding pocket, which might obstruct CLR translocation through the membrane.

How Bacterial Chemoreceptors Evolve Novel Ligand Specificities.

Chemoreceptor-based signaling pathways are among the major modes of bacterial signal transduction, and Pseudomonas aeruginosa PAO1 is an important model to study their function. Of the 26 chemoreceptors of this strain, PctA has a broad ligand range and responds to most of the proteinogenic amino acids, whereas PctB and PctC have a much narrower range and show strong ligand preference for l-glutamine and γ-aminobutyrate, respectively. Using several comparative genomics approaches, we show that these receptors are paralogs: pctA gene duplication in the common ancestor of the genus Pseudomonas led to pctC, whereas pctB originated through another, independent pctA duplication in the common ancestor of P. aeruginosa Thus, the broad-range amino acid chemoreceptor was evolutionarily older, and chemoreceptors that complemented "missing" amino acid sensing abilities arose later in specific Pseudomonas lineages. Using comparative sequence analysis, newly solved crystal structures of PctA, PctB, and PctC ligand-binding domains, and their molecular dynamics simulations, we identified a conserved amino acid recognition motif and changes in the ligand-binding pocket that led to novel ligand specificities. In addition, we determined major forces driving the evolution of this group of chemoreceptors.IMPORTANCE Many bacteria possess a large number of chemoreceptors that recognize a variety of different compounds. More than 60% of the genomes analyzed in this study contain paralogous chemoreceptors, suggesting that they emerge with high frequency. We provide first insight on how paralogous receptors have evolved and show that two chemoreceptors with a narrow ligand range have evolved from an ancestral protein with a broad chemoeffector spectrum. Protein structures show that multiple changes in the ligand-binding site account for the differences in the ligand spectrum. This work lays the ground for further studies aimed at establishing whether the principles of ligand-binding evolution reported here can be generalized for a wider spectrum of sensory proteins in bacteria.

Structural and physico-chemical effects of disease and non-disease nsSNPs on proteins.

This review emphasizes the effects of naturally occurring mutations on structural features and physico-chemical properties of proteins. The basic protein characteristics considered are stability, dynamics, and the binding of proteins and methods for assessing effects of mutations on these macromolecular characteristics are briefly outlined. It is emphasized that the above entities mostly reflect global characteristics of considered macromolecules, while given mutations may alter the local structural features such as salt bridges and hydrogen bonds without affecting the global ones. Furthermore, it is pointed out that disease-causing mutations frequently involve a drastic change of amino acid physico-chemical properties such as charge, hydrophobicity, and geometry, and are less surface exposed than polymorphic mutations.

Ion binding to biological macromolecules.

Biological macromolecules carry out their functions in water and in the presence of ions. The ions can bind to the macromolecules either specifically or non-specifically, or can simply to be a part of the water phase providing physiological gradient across various membranes. This review outlines the differences between specific and non-specific ion binding in terms of the function and stability of the corresponding macromolecules. Furthermore, the experimental techniques to identify ion positions and computational methods to predict ion binding are reviewed and their advantages compared. It is indicated that specifically bound ions are relatively easier to be revealed while non-specifically associated ions are difficult to predict. In addition, the binding and the residential time of non-specifically bound ions are very much sensitive to the environmental factors in the cells, specifically to the local pH and ion concentration. Since these characteristics differ among the cellular compartments, the non-specific ion binding must be investigated with respect to the sub-cellular localization of the corresponding macromolecule.

Predicting the Impact of Missense Mutations on Protein-Protein Binding Affinity.

The crucial prerequisite for proper biological function is the protein's ability to establish highly selective interactions with macromolecular partners. A missense mutation that alters the protein binding affinity may cause significant perturbations or complete abolishment of the function, potentially leading to diseases. The availability of computational methods to evaluate the impact of mutations on protein-protein binding is critical for a wide range of biomedical applications. Here, we report an efficient computational approach for predicting the effect of single and multiple missense mutations on protein-protein binding affinity. It is based on a well-tested simulation protocol for structure minimization, modified MM-PBSA and statistical scoring energy functions with parameters optimized on experimental sets of several thousands of mutations. Our simulation protocol yields very good agreement between predicted and experimental values with Pearson correlation coefficients of 0.69 and 0.63 and root-mean-square errors of 1.20 and 1.90 kcal mol-1 for single and multiple mutations, respectively. Compared with other available methods, our approach achieves high speed and prediction accuracy and can be applied to large datasets generated by modern genomics initiatives. In addition, we report a crucial role of water model and the polar solvation energy in estimating the changes in binding affinity. Our analysis also reveals that prediction accuracy and effect of mutations on binding strongly depends on the type of mutation and its location in a protein complex.

Chronic Beryllium Disease: revealing the role of beryllium ion and small peptides binding to HLA-DP2.

Chronic Beryllium (Be) Disease (CBD) is a granulomatous disorder that predominantly affects the lung. The CBD is caused by Be exposure of individuals carrying the HLA-DP2 protein of the major histocompatibility complex class II (MHCII). While the involvement of Be in the development of CBD is obvious and the binding site and the sequence of Be and peptide binding were recently experimentally revealed [1], the interplay between induced conformational changes and the changes of the peptide binding affinity in presence of Be were not investigated. Here we carry out in silico modeling and predict the Be binding to be within the acidic pocket (Glu26, Glu68 and Glu69) present on the HLA-DP2 protein in accordance with the experimental work [1]. In addition, the modeling indicates that the Be ion binds to the HLA-DP2 before the corresponding peptide is able to bind to it. Further analysis of the MD generated trajectories reveals that in the presence of the Be ion in the binding pocket of HLA-DP2, all the different types of peptides induce very similar conformational changes, but their binding affinities are quite different. Since these conformational changes are distinctly different from the changes caused by peptides normally found in the cell in the absence of Be, it can be speculated that CBD can be caused by any peptide in presence of Be ion. However, the affinities of peptides for Be loaded HLA-DP2 were found to depend of their amino acid composition and the peptides carrying acidic group at positions 4 and 7 are among the strongest binders. Thus, it is proposed that CBD is caused by the exposure of Be of an individual carrying the HLA-DP2*0201 allele and that the binding of Be to HLA-DP2 protein alters the conformational and ionization properties of HLA-DP2 such that the binding of a peptide triggers a wrong signaling cascade.

ProBLM web server: protein and membrane placement and orientation package.

The 3D structures of membrane proteins are typically determined without the presence of a lipid bilayer. For the purpose of studying the role of membranes on the wild type characteristics of the corresponding protein, determining the position and orientation of transmembrane proteins within a membrane environment is highly desirable. Here we report a geometry-based approach to automatically insert a membrane protein with a known 3D structure into pregenerated lipid bilayer membranes with various dimensions and lipid compositions or into a pseudomembrane. The pseudomembrane is built using the Protein Nano-Object Integrator which generates a parallelepiped of user-specified dimensions made up of pseudoatoms. The pseudomembrane allows for modeling the desolvation effects while avoiding plausible errors associated with wrongly assigned protein-lipid contacts. The method is implemented into a web server, the ProBLM server, which is freely available to the biophysical community. The web server allows the user to upload a protein coordinate file and any missing residues or heavy atoms are regenerated. ProBLM then creates a combined protein-membrane complex from the given membrane protein and bilayer lipid membrane or pseudomembrane. The user is given an option to manually refine the model by manipulating the position and orientation of the protein with respect to the membrane.