Predicting folding free energy changes upon single point mutations

Impact of Rett Syndrome Mutations on MeCP2 MBD Stability

Rett syndrome causing missense mutations in the methyl-CpG-binding domain (MBD) of methyl CpG-binding protein 2 (MeCP2) were investigated both in silico and in vitro to reveal their effect on protein stability. It is demonstrated that the vast majority of frequently occurring mutations in the human population indeed alter the MBD folding free energy by a fraction of a kcal/mol up to more than 1 kcal/mol. While the absolute magnitude of the change of the free energy is small, the effect on the MBD functionality may be substantial since the folding free energy of MBD is about 2 kcal/mol only. Thus, it is emphasized that the effect of mutations on protein integrity should be evaluated with respect to the wild-type folding free energy but not with the absolute value of the folding free energy change. Furthermore, it was observed that the magnitude of the effect is correlated neither with the burial of the mutation sites nor with the basic amino acid physicochemical property change. Mutations that strongly perturb the immediate structural features were found to have little effect on folding free energy, while very conservative mutations resulted in large changes of the MBD stability. This observation was attributed to the protein's ability to structurally relax and reorganize to reduce the effect of mutation. Comparison between in silico and in vitro results indicated that some Web servers perform relatively well, while the free energy perturbation approach frequently overpredicts the magnitude of the free energy change especially when a charged amino acid is involved.

ZC4H2, an XLID gene, is required for the generation of a specific subset of CNS interneurons

Miles–Carpenter syndrome (MCS) was described in 1991 as an XLID syndrome with fingertip arches and contractures and mapped to proximal Xq. Patients had microcephaly, short stature, mild spasticity, thoracic scoliosis, hyperextendable MCP joints, rocker-bottom feet, hyperextended elbows and knees. A mutation, p.L66H, in ZC4H2, was identified in a XLID re-sequencing project. Additional screening of linked families and next generation sequencing of XLID families identified three ZC4H2 mutations: p.R18K, p.R213W and p.V75in15aa. The families shared some relevant clinical features. In silico modeling of the mutant proteins indicated all alterations would destabilize the protein. Knockout mutations in zc4h2 were created in zebrafish and homozygous mutant larvae exhibited abnormal swimming, increased twitching, defective eye movement and pectoral fin contractures. Because several of the behavioral defects were consistent with hyperactivity, we examined the underlying neuronal defects and found that sensory neurons and motoneurons appeared normal. However, we observed a striking reduction in GABAergic interneurons. Analysis of cell-type-specific markers showed a specific loss of V2 interneurons in the brain and spinal cord, likely arising from mis-specification of neural progenitors. Injected human wt ZC4H2 rescued the mutant phenotype. Mutant zebrafish injected with human p.L66H or p.R213W mRNA failed to be rescued, while the p.R18K mRNA was able to rescue the interneuron defect. Our findings clearly support ZC4H2 as a novel XLID gene with a required function in interneuron development. Loss of function of ZC4H2 thus likely results in altered connectivity of many brain and spinal circuits.

Methods for library-scale computational protein design

Faced with a protein engineering challenge, a contemporary researcher can choose from myriad design strategies. Library-scale computational protein design (LCPD) is a hybrid method suitable for the engineering of improved protein variants with diverse sequences. This chapter discusses the background and merits of several practical LCPD techniques. First, LCPD methods suitable for delocalized protein design are presented in the context of example design calculations for cellobiohydrolase II. Second, localized design methods are discussed in the context of an example design calculation intended to shift the substrate specificity of a ketol-acid reductoisomerase Rossmann domain from NADPH to NADH.

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.

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.

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.

A novel p.Leu(381)Phe mutation in presenilin 1 is associated with very early onset and unusually fast progressing dementia as well as lysosomal inclusions typically seen in Kufs disease

Whole exome sequencing in a family with suspected dominant Kufs disease identified a novel Presenilin 1 mutation p.Leu(381)Phe in three brothers who, along with their father, developed progressive dementia and motor deficits in their early 30 s. All affected relatives had unusually rapid disease progression (on average 3.6 years from disease onset to death). In silico analysis of mutation p.Leu(381)Phe predicted more detrimental effects when compared to the common Presenilin 1 mutation p.Glu(280)Ala. Electron microscopy study of peripheral fibroblast cells of the proband showed lysosomal inclusions typical for Kufs disease. However, brain autopsy demonstrated typical changes of Alzheimer's disease.

Computational and experimental approaches to reveal the effects of single nucleotide polymorphisms with respect to disease diagnostics

DNA mutations are the cause of many human diseases and they are the reason for natural differences among individuals by affecting the structure, function, interactions, and other properties of DNA and expressed proteins. The ability to predict whether a given mutation is disease-causing or harmless is of great importance for the early detection of patients with a high risk of developing a particular disease and would pave the way for personalized medicine and diagnostics. Here we review existing methods and techniques to study and predict the effects of DNA mutations from three different perspectives: in silico, in vitro and in vivo. It is emphasized that the problem is complicated and successful detection of a pathogenic mutation frequently requires a combination of several methods and a knowledge of the biological phenomena associated with the corresponding macromolecules.

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.

Computational and theoretical methods for protein folding

A computational approach is essential whenever the complexity of the process under study is such that direct theoretical or experimental approaches are not viable. This is the case for protein folding, for which a significant amount of data are being collected. This paper reports on the essential role of in silico methods and the unprecedented interplay of computational and theoretical approaches, which is a defining point of the interdisciplinary investigations of the protein folding process. Besides giving an overview of the available computational methods and tools, we argue that computation plays not merely an ancillary role but has a more constructive function in that computational work may precede theory and experiments. More precisely, computation can provide the primary conceptual clues to inspire subsequent theoretical and experimental work even in a case where no preexisting evidence or theoretical frameworks are available. This is cogently manifested in the application of machine learning methods to come to grips with the folding dynamics. These close relationships suggested complementing the review of computational methods within the appropriate theoretical context to provide a self-contained outlook of the basic concepts that have converged into a unified description of folding and have grown in a synergic relationship with their computational counterpart. Finally, the advantages and limitations of current computational methodologies are discussed to show how the smart analysis of large amounts of data and the development of more effective algorithms can improve our understanding of protein folding.

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.

Molecular mechanisms of disease-causing missense mutations

Genetic variations resulting in a change of amino acid sequence can have a dramatic effect on stability, hydrogen bond network, conformational dynamics, activity and many other physiologically important properties of proteins. The substitutions of only one residue in a protein sequence, so-called missense mutations, can be related to many pathological conditions and may influence susceptibility to disease and drug treatment. The plausible effects of missense mutations range from affecting the macromolecular stability to perturbing macromolecular interactions and cellular localization. Here we review the individual cases and genome-wide studies that illustrate the association between missense mutations and diseases. In addition, we emphasize that the molecular mechanisms of effects of mutations should be revealed in order to understand the disease origin. Finally, we report the current state-of-the-art methodologies that predict the effects of mutations on protein stability, the hydrogen bond network, pH dependence, conformational dynamics and protein function.

A Y328C missense mutation in spermine synthase causes a mild form of Snyder-Robinson syndrome

Snyder-Robinson syndrome (SRS, OMIM: 309583) is an X-linked intellectual disability (XLID) syndrome, characterized by a collection of clinical features including facial asymmetry, marfanoid habitus, hypertonia, osteoporosis and unsteady gait. It is caused by a significant decrease or loss of spermine synthase (SMS) activity. Here, we report a new missense mutation, p.Y328C (c.1084A>G), in SMS in a family with XLID. The affected males available for evaluation had mild ID, speech and global delay, an asthenic build, short stature with long fingers and mild kyphosis. The spermine/spermidine ratio in lymphoblasts was 0.53, significantly reduced compared with normal (1.87 average). Activity analysis of SMS in the index patient failed to detect any activity above background. In silico modeling demonstrated that the Y328C mutation has a significant effect on SMS stability, resulting in decreased folding free energy and larger structural fluctuations compared with those of wild-type SMS. The loss of activity was attributed to the increase in conformational dynamics in the mutant which affects the active site geometry, rather than preventing dimer formation. Taken together, the biochemical and in silico studies confirm the p.Y328C mutation in SMS is responsible for the patients having a mild form of SRS and reveal yet another molecular mechanism resulting in a non-functional SMS causing SRS.

Enhancing human spermine synthase activity by engineered mutations

Spermine synthase (SMS) is an enzyme which function is to convert spermidine into spermine. It was shown that gene defects resulting in amino acid changes of the wild type SMS cause Snyder-Robinson syndrome, which is a mild-to-moderate mental disability associated with osteoporosis, facial asymmetry, thin habitus, hypotonia, and a nonspecific movement disorder. These disease-causing missense mutations were demonstrated, both in silico and in vitro, to affect the wild type function of SMS by either destabilizing the SMS dimer/monomer or directly affecting the hydrogen bond network of the active site of SMS. In contrast to these studies, here we report an artificial engineering of a more efficient SMS variant by transferring sequence information from another organism. It is confirmed experimentally that the variant, bearing four amino acid substitutions, is catalytically more active than the wild type. The increased functionality is attributed to enhanced monomer stability, lowering the pKa of proton donor catalytic residue, optimized spatial distribution of the electrostatic potential around the SMS with respect to substrates, and increase of the frequency of mechanical vibration of the clefts presumed to be the gates toward the active sites. The study demonstrates that wild type SMS is not particularly evolutionarily optimized with respect to the reaction spermidine → spermine. Having in mind that currently there are no variations (non-synonymous single nucleotide polymorphism, nsSNP) detected in healthy individuals, it can be speculated that the human SMS function is precisely tuned toward its wild type and any deviation is unwanted and disease-causing.

Proteins are constantly subjected to evolutionary pressure to assure the organism's survival and reproduction. At the same time, the proteins' amino acid sequence undergoes mutations, some of which may cause diseases while others may be reflecting natural differences within the population (non-synonymous single nucleotide polymorphism, nsSNP). In this study we examine the human spermine synthase (HsSMS), for which currently there are no nsSNPs, while rare disease mutations are known to cause Snyder-Robinson syndrome. What is so special with this protein? Maybe the HsSMS is so well optimized for its function that any change of the wild type sequence should be degrading its performance. To check such a possibility, we engineered a mutant of HsSMS with enhanced stability, electrostatic and mechanical properties. The mutant was confirmed experimentally to be a better enzyme than the wild type. Thus, the HsSMS is not evolutionally optimized with respect to its enzymatic reaction, its amino acid sequence differs only in sick individuals and so far its sequence was found to be identical in all healthy individuals. Therefore, it can be speculated that the HsSMS function is precisely tuned toward the wild type characteristics such so any deviation is unwanted and is disease-causing.

A rational free energy-based approach to understanding and targeting disease-causing missense mutations

BACKGROUND AND SIGNIFICANCE

Intellectual disability is a condition characterized by significant limitations in cognitive abilities and social/behavioral adaptive skills and is an important reason for pediatric, neurologic, and genetic referrals. Approximately 10% of protein-encoding genes on the X chromosome are implicated in intellectual disability, and the corresponding intellectual disability is termed X-linked ID (XLID). Although few mutations and a small number of families have been identified and XLID is rare, collectively the impact of XLID is significant because patients usually are unable to fully participate in society.

OBJECTIVE

To reveal the molecular mechanisms of various intellectual disabilities and to suggest small molecules which by binding to the malfunctioning protein can reduce unwanted effects.

METHODS

Using various in silico methods we reveal the molecular mechanism of XLID in cases involving proteins with known 3D structure. The 3D structures were used to predict the effect of disease-causing missense mutations on the folding free energy, conformational dynamics, hydrogen bond network and, if appropriate, protein-protein binding free energy.

RESULTS

It is shown that the vast majority of XLID mutation sites are outside the active pocket and are accessible from the water phase, thus providing the opportunity to alter their effect by binding appropriate small molecules in the vicinity of the mutation site.

CONCLUSIONS

This observation is used to demonstrate, computationally and experimentally, that a particular condition, Snyder-Robinson syndrome caused by the G56S spermine synthase mutation, might be ameliorated by small molecule binding.

Combination of Enveloping Distribution Sampling (EDS) of a Soft-Core Reference-State Hamiltonian with One-Step Perturbation to Predict the Effect of Side Chain Substitution on the Relative Stability of Right- and Left-Helical Folds of β-Peptides

Folding free enthalpies of many not too different polypeptides can be efficiently and accurately predicted with the one-step perturbation (OSP) method using only one or a few molecular dynamics (MD) simulations. In this article, we introduce a combination of enveloping distribution sampling (EDS) and the OSP method (EDS-OSP) and apply it to predict the free enthalpy differences between a right-handed 2.710/12-helix and a left-handed 314-helix for 16 β-peptides with slightly different side-chain substitution patterns. An EDS simulation of a designed soft-core reference-state peptide was carried out in which both helices were sampled. Then, the soft-core atoms were perturbed into physical atoms. Thus, free enthalpy differences between the two helices for the 16 β-peptides can be predicted from only one simulation. The results predicted by EDS-OSP and a previous OSP study are very similar, i.e., the deviations between the results of the 16 peptides are mostly within the order of kBT, and the average absolute deviation is 1.2 kJ mol(-1). Together with the EDS parameter update simulation, about 128 ns of MD simulations needed to be carried out using the EDS-OSP method, while 700 ns of MD simulations were required in the previous OSP study where two separate reference-state simulations and an additional long time MD simulation of one of the 16 β-peptides were carried out. Thus, the computational effort was significantly reduced, i.e., by more than a factor of 5, using the EDS-OSP method. Hence, we consider this method an efficient tool to predict conformational free enthalpy differences from MD simulations.

Protein Nano-Object Integrator (ProNOI) for generating atomic style objects for molecular modeling

Background

With the progress of nanotechnology, one frequently has to model biological macromolecules simultaneously with nano-objects. However, the atomic structures of the nano objects are typically not available or they are solid state entities. Because of that, the researchers have to investigate such nano systems by generating models of the nano objects in a manner that the existing software be able to carry the simulations. In addition, it should allow generating composite objects with complex shape by combining basic geometrical figures and embedding biological macromolecules within the system.

Results

Here we report the Protein Nano-Object Integrator (ProNOI) which allows for generating atomic-style geometrical objects with user desired shape and dimensions. Unlimited number of objects can be created and combined with biological macromolecules in Protein Data Bank (PDB) format file. Once the objects are generated, the users can use sliders to manipulate their shape, dimension and absolute position. In addition, the software offers the option to charge the objects with either specified surface or volumetric charge density and to model them with user-desired dielectric constants. According to the user preference, the biological macromolecule atoms can be assigned charges and radii according to four different force fields: Amber, Charmm, OPLS and PARSE. The biological macromolecules and the atomic-style objects are exported as a position, charge and radius (PQR) file, or if a default dielectric constant distribution is not selected, it is exported as a position, charge, radius and epsilon (PQRE) file. As illustration of the capabilities of the ProNOI, we created a composite object in a shape of a robot, aptly named the Clemson Robot, whose parts are charged with various volumetric charge densities and holds the barnase-barstar protein complex in its hand.

Conclusions

The Protein Nano-Object Integrator (ProNOI) is a convenient tool for generating atomic-style nano shapes in conjunction with biological macromolecule(s). Charges and radii on the macromolecule atoms and the atoms in the shapes are assigned according to the user’s preferences allowing various scenarios of modeling. The default output file is in PQR (PQRE) format which is readable by almost any software available in biophysical field. It can be downloaded from: http://compbio.clemson.edu/downloadDir/ProNO_integrator.tar.gz

Oncogenic potential is related to activating effect of cancer single and double somatic mutations in receptor tyrosine kinases

Aberrant activation of receptor tyrosine kinases (RTKs) is a common feature of many cancer cells. It was previously suggested that the mechanisms of kinase activation in cancer might be linked to transitions between active and inactive states. Here, we estimate the effects of single and double cancer mutations on the stability of active and inactive states of the kinase domains from different RTKs. We show that singleton cancer mutations destabilize active and inactive states; however, inactive states are destabilized more than the active ones, leading to kinase activation. We show that there exists a relationship between the estimate of oncogenic potential of cancer mutation and kinase activation. Namely, more frequent mutations have a higher activating effect, which might allow us to predict the activating effect of the mutations from the mutation spectra. Independent evolutionary analysis of mutation spectra complements this observation and finds the same frequency threshold defining mutation hotspots. We analyze double mutations and report a positive epistasis and additional advantage of doublets with respect to cancer cell fitness. The activation mechanisms of double mutations differ from those of single mutations and double mutation spectrum is found to be dissimilar to the mutation spectrum of singletons.

Assessing predictors of changes in protein stability upon mutation using self-consistency

The ability to predict the effect of mutations on protein stability is important for a wide range of tasks, from protein engineering to assessing the impact of SNPs to understanding basic protein biophysics. A number of methods have been developed that make these predictions, but assessing the accuracy of these tools is difficult given the limitations and inconsistencies of the experimental data. We evaluate four different methods based on the ability of these methods to generate consistent results for forward and back mutations, and examine how this ability varies with the nature and location of the mutation. We find that, while one method seems to outperform the others, the ability of these methods to make accurate predictions is limited.

Analyzing effects of naturally occurring missense mutations

Single-point mutation in genome, for example, single-nucleotide polymorphism (SNP) or rare genetic mutation, is the change of a single nucleotide for another in the genome sequence. Some of them will produce an amino acid substitution in the corresponding protein sequence (missense mutations); others will not. This paper focuses on genetic mutations resulting in a change in the amino acid sequence of the corresponding protein and how to assess their effects on protein wild-type characteristics. The existing methods and approaches for predicting the effects of mutation on protein stability, structure, and dynamics are outlined and discussed with respect to their underlying principles. Available resources, either as stand-alone applications or webservers, are pointed out as well. It is emphasized that understanding the molecular mechanisms behind these effects due to these missense mutations is of critical importance for detecting disease-causing mutations. The paper provides several examples of the application of 3D structure-based methods to model the effects of protein stability and protein-protein interactions caused by missense mutations as well.