Anatomy of protein disorder, flexibility and disease-related mutations

Gene-wise variant burden and genomic characterization of nearly every gene

Aim: Current gene-level prioritization methods aim to provide information for further prioritization of ‘disease-causing’ mutations. Since, they are inherently biased toward disease genes, methods specific to pharmacogenetic (PGx) genes are required. Methods: We proposed a gene-wise variant burden (GVB) method that integrates in silico deleteriousness scores of the multitude of variants of a given gene at a personal-genome level. Results: GVB in its simplest form outperformed the two state-of-the-art methods with regard to predicting pharmacogenes and complex disease genes but not for rare Mendelian disease genes. GVB* adjusted by paralog counts robustly performed well in most of the pharmacogenetic subcategories. Seven molecular genetic features well characterized the unique genomic properties of PGx, complex, and Mendelian disease genes. Conclusion: Altogether, GVB is an individual-specific genescore, especially advantageous for PGx studies.

Protein-Protein Interactions Mediated by Intrinsically Disordered Protein Regions Are Enriched in Missense Mutations

Because proteins are fundamental to most biological processes, many genetic diseases can be traced back to single nucleotide variants (SNVs) that cause changes in protein sequences. However, not all SNVs that result in amino acid substitutions cause disease as each residue is under different structural and functional constraints. Influential studies have shown that protein–protein interaction interfaces are enriched in disease-associated SNVs and depleted in SNVs that are common in the general population. These studies focus primarily on folded (globular) protein domains and overlook the prevalent class of protein interactions mediated by intrinsically disordered regions (IDRs). Therefore, we investigated the enrichment patterns of missense mutation-causing SNVs that are associated with disease and cancer, as well as those present in the healthy population, in structures of IDR-mediated interactions with comparisons to classical globular interactions. When comparing the different categories of interaction interfaces, division of the interface regions into solvent-exposed rim residues and buried core residues reveal distinctive enrichment patterns for the various types of missense mutations. Most notably, we demonstrate a strong enrichment at the interface core of interacting IDRs in disease mutations and its depletion in neutral ones, which supports the view that the disruption of IDR interactions is a mechanism underlying many diseases. Intriguingly, we also found an asymmetry across the IDR interaction interface in the enrichment of certain missense mutation types, which may hint at an increased variant tolerance and urges further investigations of IDR interactions.

Modulation of p53 Transactivation Domain Conformations by Ligand Binding and Cancer-Associated Mutations

Intrinsically disordered proteins (IDPs) are important functional proteins, and their deregulation are linked to numerous human diseases including cancers. Understanding how disease-associated mutations or drug molecules can perturb the sequence-disordered ensemble-function-disease relationship of IDPs remains challenging, because it requires detailed characterization of the heterogeneous structural ensembles of IDPs. In this work, we combine the latest atomistic force field a99SB-disp, enhanced sampling technique replica exchange with solute tempering, and GPU-accelerated molecular dynamics simulations to investigate how four cancer-associated mutations, K24N, N29K/N30D, D49Y, and W53G, and binding of an anti-cancer molecule, epigallocatechin gallate (EGCG), modulate the disordered ensemble of the transactivation domain (TAD) of tumor suppressor p53. Through extensive sampling, in excess of 1.0 μs per replica, well-converged structural ensembles of wild-type and mutant p53-TAD as well as WT p53-TAD in the presence of EGCG were generated. The results reveal that mutants could induce local structural changes and affect secondary structural properties. Interestingly, both EGCG binding and N29K/N30D could also induce long-range structural reorganizations and lead to more compact structures that could shield key binding sites of p53-TAD regulators. Further analysis reveals that the effects of EGCG binding are mainly achieved through nonspecific interactions. These observations are generally consistent with on-going NMR studies and binding assays. Our studies suggest that induced conformational collapse of IDPs may be a general mechanism for shielding functional sites, thus inhibiting recognition of their targets. The current study also demonstrates that atomistic simulations provide a viable approach for studying the sequence-disordered ensemble-function-disease relationships of IDPs and developing new drug design strategies targeting regulatory IDPs.

Sin1-mediated mTOR signaling in cell growth, metabolism and immune response

The mammalian target of rapamycin (mTOR) is an evolutionarily conserved Ser/Thr protein kinase with essential cellular function via processing various extracellular and intracellular inputs. Two distinct multi-protein mTOR complexes (mTORC), mTORC1 and mTORC2, have been identified and well characterized in eukaryotic cells from yeast to human. Sin1, which stands for Sty1/Spc1-interacting protein1, also known as mitogen-activated protein kinase (MAPK) associated protein (MAPKAP)1, is an evolutionarily conserved adaptor protein. Mammalian Sin1 interacts with many cellular proteins, but it has been widely studied as an essential component of mTORC2, and it is crucial not only for the assembly of mTORC2 but also for the regulation of its substrate specificity. In this review, we summarize our current knowledge of the structure and functions of Sin1, focusing specifically on its protein interaction network and its roles in the mTOR pathway that could account for various cellular functions of mTOR in growth, metabolism, immunity and cancer.

Residual Structures and Transient Long-Range Interactions of p53 Transactivation Domain: Assessment of Explicit Solvent Protein Force Fields

Molecular dynamics simulations using physics-based atomistic force fields have been increasingly used to characterize the heterogeneous structural ensembles of intrinsically disordered proteins (IDPs). To evaluate the accuracy of the latest atomistic explicit-solvent force fields in modeling larger IDPs with nontrivial structural features, we focus on the 61-residue N-terminal transactivation domain (TAD) of tumor suppressor p53, an important protein in cancer biology that has been extensively studied, and abundant experimental data is available for evaluation of simulated ensembles. We performed extensive replica exchange with solute tempering simulations, in excess of 1.0 μs/replica, to generate disordered structural ensembles of p53-TAD using six latest explicit solvent protein force fields. Multiple local and long-range structural properties, including chain dimension, residual secondary structures, and transient long-range contacts, were analyzed and compared against available experimental data. The results show that IDPs such as p53-TAD remain highly challenging for atomistic simulations due to conformational complexity and difficulty in achieving adequate convergence. Structural ensembles of p53-TAD generated using various force fields differ significantly from each other. The a99SB-disp force field demonstrates the best agreement with experimental data at all levels and proves to be suitable for simulating unbound p53-TAD and how its conformational properties may be modulated by phosphorylation and other cellular signals or cancer-associated mutations. Feasibility of such detailed structural characterization is a key step toward establishing the sequence-disordered ensemble-function-disease relationship of p53 and other biologically important IDPs.

In silico identification of rescue sites by double force scanning

Motivation

A deleterious amino acid change in a protein can be compensated by a second-site rescue mutation. These compensatory mechanisms can be mimicked by drugs. In particular, the location of rescue mutations can be used to identify protein regions that can be targeted by small molecules to reactivate a damaged mutant.

Results

We present the first general computational method to detect rescue sites. By mimicking the effect of mutations through the application of forces, the double force scanning (DFS) method identifies the second-site residues that make the protein structure most resilient to the effect of pathogenic mutations. We tested DFS predictions against two datasets containing experimentally validated and putative evolutionary-related rescue sites. A remarkably good agreement was found between predictions and experimental data. Indeed, almost half of the rescue sites in p53 was correctly predicted by DFS, with 65% of remaining sites in contact with DFS predictions. Similar results were found for other proteins in the evolutionary dataset.

Availability and implementation

The DFS code is available under GPL at https://fornililab.github.io/dfs/.

Supplementary information

Supplementary data are available at Bioinformatics online.

HyRes: a coarse-grained model for multi-scale enhanced sampling of disordered protein conformations

Efficient coarse-grained (CG) models can be coupled with atomistic force fields to accelerate the sampling of atomistic energy landscapes in the multi-scale enhanced sampling (MSES) framework. This approach may be particularly suitable for generating atomistic conformational ensembles of intrinsically disordered proteins (IDPs). While MSES is relatively robust to inherent CG artifacts, achieving optimal sampling efficiency requires CG modeling to generate the local and long-range fluctuations that are largely consistent with those at the atomistic level. Here, we describe a new hybrid resolution CG model (HyRes) for MSES simulations of disordered protein states, which is specifically designed to provide semi-quantitative secondary structure propensities together with a qualitative description of long-range nonspecific interactions. The HyRes model contains an atomistic description of the backbone with intermediate resolution side chains. The secondary structure propensities are tuned by adjusting the backbone hydrogen-bonding strength and the ϕ/ψ torsion profile. The sizes and covalent geometries of the side chains are parameterized to reproduce distributions derived from atomistic simulations. Lennard-Jones parameters for sidechain beads are assigned to reproduce statistical potentials derived from the protein structural database, and then globally parameterized with nonspecific electrostatic interactions to reproduce the free energy profiles of pair wise interactions and the key conformational properties of model peptides. Application of HyRes to MSES simulations of small IDPs suggests that it is capable of driving faster structural transitions at the atomistic level and increasing the convergence rate compared to the Cα-only Gō-like models previously utilized. With further optimization, we believe that the new CG model could greatly improve the efficiency of MSES simulations of the larger and more complex IDPs frequently involved in cellular signalling and regulation.

Enhanced Sampling of Intrinsic Structural Heterogeneity of the BH3-Only Protein Binding Interface of Bcl-xL

Antiapoptotic Bcl-xL plays central roles in regulating programed cell death. Partial unfolding of Bcl-xL has been observed at the interface upon specific binding to the pro-apoptotic BH3-only protein PUMA, which in turn disrupts the interaction of Bcl-xL with tumor suppressor p53 and promotes apoptosis. Previous analysis of existing Bcl-xL structures and atomistic molecular dynamics (MD) simulations have suggested that substantial intrinsic structure heterogeneity exists at the BH3-only protein binding interface of Bcl-xL to facilitate its conformational transitions upon binding. In this study, enhanced sampling is applied to further characterize the interfacial conformations of unbound Bcl-xL in explicit solvent. Extensive replica exchange with solute tempering (REST) simulations, with a total accumulated time of 16 μs, were able to cover much wider conformational spaces for the interfacial region of Bcl-xL. The resulting structural ensembles are much better converged, with local and long-range structural features that are highly consistent with existing NMR data. These simulations further demonstrate that the BH3-only protein binding interface of Bcl-xL is intrinsically disordered and samples many rapidly interconverting conformations. Intriguingly, all previously observed conformers are well represented in the unbound structure ensemble. Such intrinsic structural heterogeneity and flexibility may be critical for Bcl-xL to undergo partial unfolding induced by PUMA binding, and likely provide a robust basis that allows Bcl-xL to respond sensitively to binding of various ligands in cellular signaling and regulation.

All-Atom MD Predicts Magnesium-Induced Hairpin in Chemically Perturbed RNA Analog of F10 Therapeutic

Given their increasingly frequent usage, understanding the chemical and structural properties which allow therapeutic nucleic acids to promote the death of cancer cells is critical for medical advancement. One molecule of interest is a 10-mer of FdUMP (5-fluoro-2'-deoxyuridine-5'-O-monophosphate) also called F10. To investigate causes of structural stability, we have computationally restored the 2' oxygen on each ribose sugar of the phosphodiester backbone, creating FUMP[10]. Microsecond time-scale, all-atom, simulations of FUMP[10] in the presence of 150 mM MgCl₂ predict that the strand has a 45% probability of folding into a stable hairpin-like secondary structure. Analysis of 16 μs of data reveals phosphate interactions as likely contributors to the stability of this folded state. Comparison with polydT and polyU simulations predicts that FUMP[10]'s lowest order structures last for one to 2 orders of magnitude longer than similar nucleic acid strands. Here we provide a brief structural and conformational analysis of the predicted structures of FUMP[10], and suggest insights into its stability via comparison to F10, polydT, and polyU.

Structural characterization of single nucleotide variants at ligand binding sites and enzyme active sites of human proteins

Functional sites on proteins play an important role in various molecular interactions and reactions between proteins and other molecules. Thus, mutations in functional sites can severely affect the overall phenotype. Progress of genome sequencing projects has yielded a wealth of information on single nucleotide variants (SNVs), especially those with less than 1% minor allele frequency (rare variants). To understand the functional influence of genetic variants at a protein level, we investigated the relationship between SNVs and protein functional sites in terms of minor allele frequency and the structural position of variants. As a result, we observed that SNVs were less abundant at ligand binding sites, which is consistent with a previous study on SNVs and protein interaction sites. Additionally, we found that non-rare variants tended to be located slightly apart from enzyme active sites. Examination of non-rare variants revealed that most of the mutations resulted in moderate changes of the physico-chemical properties of amino acids, suggesting the existence of functional constraints. In conclusion, this study shows that the mapping of genetic variants on protein structures could be a powerful approach to evaluate the functional impact of rare genetic variations.

The yin-yang of kinase activation and unfolding explains the peculiarity of Val600 in the activation segment of BRAF

Many driver mutations in cancer are specific in that they occur at significantly higher rates than – presumably – functionally alternative mutations. For example, V600E in the BRAF hydrophobic activation segment (AS) pocket accounts for >95% of all kinase mutations. While many hypotheses tried to explain such significant mutation patterns, conclusive explanations are lacking. Here, we use experimental and in silico structure-energy statistical analyses, to elucidate why the V600E mutation, but no other mutation at this, or any other positions in BRAF’s hydrophobic pocket, is predominant. We find that BRAF mutation frequencies depend on the equilibrium between the destabilization of the hydrophobic pocket, the overall folding energy, the activation of the kinase and the number of bases required to change the corresponding amino acid. Using a random forest classifier, we quantitatively dissected the parameters contributing to BRAF AS cancer frequencies. These findings can be applied to genome-wide association studies and prediction models.

DOI:http://dx.doi.org/10.7554/eLife.12814.001

Mutations in the gene that encodes a protein called BRAF are commonly found in certain cancers, such as melanomas. The same BRAF mutation is found in nearly all of these cancers. This mutation causes the 600th amino acid in the BRAF protein – an amino acid called a valine – to be replaced with another amino acid, a glutamate.

BRAF is a type of enzyme called a kinase, and it transmits signals inside cells to promote cell growth. Kinases work by adding a phosphate group to other proteins to alter their activity. The structure of the BRAF kinase contains a pocket-like shape, and the valine at position 600 sits buried inside this pocket when the enzyme is inactive. The “valine-to-glutamate” mutation (often called V600E for short) disrupts the interactions that create this pocket. This in turn results in a permanently active form of BRAF and uncontrolled cell growth. However, it remains unclear why the valine-to-glutamate mutation is so much more common in cancer cells than any other mutation that could affect the pocket in BRAF.

To address this question, Kiel et al. used a computational tool to generate three-dimensional models for all the different amino acid substitutions that could occur in BRAF’s pocket. Each mutation was then assessed to see how it might destabilize the structure of BRAF. Only the mutations that affected the 600th amino acid were predicted to be able to open the pocket without destabilizing the part of the enzyme that adds phosphate groups to other proteins.

Kiel et al. validated their computational predictions by introducing normal or mutant versions of the BRAF-encoding gene into human cells grown in the laboratory. These experiments showed that a mutation that introduced an amino acid called histidine into position 600 could activate BRAF as much the valine-to-glutamate mutation. Kiel et al. suggest that this “valine-to-histidine” substitution is not found in cancers because it requires three changes to the DNA sequence of the BRAF gene, whereas the valine-to-glutamate substitution only requires one.

The results underscore the importance of considering changes at both the DNA and protein level when attempting to understand why certain cancer-causing mutations are more common than others.

DOI:http://dx.doi.org/10.7554/eLife.12814.002

Distribution of single-nucleotide variants on protein-protein interaction sites and its relationship with minor allele frequency

Recent advances in DNA sequencing techniques have identified rare single-nucleotide variants with less than 1% minor allele frequency. Despite the growing interest and physiological importance of rare variants in genome sciences, less attention has been paid to the allele frequency of variants in protein sciences. To elucidate the characteristics of genetic variants on protein interaction sites, from the viewpoints of the allele frequency and the structural position of variants, we mapped about 20,000 human SNVs onto protein complexes. We found that variants are less abundant in protein interfaces, and specifically the core regions of interfaces. The tendency to "avoid" the interfacial core is stronger among common variants than rare variants. As amino acid substitutions, the trend of mutating amino acids among rare variants is consistent in different interfacial regions, reflecting the fact that rare variants result from random mutations in DNA sequences, whereas amino acid changes of common variants vary between the interfacial core and rim regions, possibly due to functional constraints on proteins. This study illustrated how the allele frequency of variants relates to the protein structural regions and the functional sites in general and will lead to deeper understanding of the potential deleteriousness of rare variants at the structural level. Exceptional cases of the observed trends will shed light on the limitations of structural approaches to evaluate the functional impacts of variants.