Protein WISDOM: A Workbench for <em>In silico</em> <em>De novo</em> Design of BioMolecules

The aim of de novo protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity. To disseminate these methods for broader use we present Protein WISDOM (http://www.proteinwisdom.org), a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

The aim of de novo protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity. To disseminate these methods for broader use we present Protein WISDOM (http://www.proteinwisdom.org), a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods

Designed Peptides Competitively Inhibit EZH2 Catalytic Activity.

<p>(A) A radiometric assay was used to determine the EZH2 catalytic activity in the absence (lane 1) or presence of 125 µM of candidate EZH2 inhibitor peptides (lanes 2–11). The inhibitory potential of native H3 peptide (lane 12) and an unrelated peptide (random; lane 13) was assessed. A reaction without peptide, but heat inactivated at 95°C for 5 min prior to incubation, was used to determine the background (lane 14). Shown is a fluorographic image of [³H]-labeled methyl groups incorporated on histone H3 (upper panel). Histones were visualized by Coomassie Blue staining (lower panel). (B) A high throughput radiometric assay was used to determine the inhibitory potential of candidate peptides. Shown is the absolute EZH2 HMT activity (counts per minute, cpm). (C,D) The catalytic activity of EZH2(C) and EZH1(D) was assessed in the absence (lane 2) or presence (lane 3) of SQ037 [125 µM]. Shown is a fluorographic image of [³H]-labeled methyl groups incorporated on histone H3 (upper panel). Histones and PRC2 constituents were visualized by Coomassie Blue staining (lower panel).</p

<i>De Novo</i> Peptide Design and Experimental Validation of Histone Methyltransferase Inhibitors

<div><p>Histones are small proteins critical to the efficient packaging of DNA in the nucleus. DNA–protein complexes, known as nucleosomes, are formed when the DNA winds itself around the surface of the histones. The methylation of histone residues by enhancer of zeste homolog 2 (EZH2) maintains gene repression over successive cell generations. Overexpression of EZH2 can silence important tumor suppressor genes leading to increased invasiveness of many types of cancers. This makes the inhibition of EZH2 an important target in the development of cancer therapeutics. We employed a three-stage computational <i>de novo</i> peptide design method to design inhibitory peptides of EZH2. The method consists of a sequence selection stage and two validation stages for fold specificity and approximate binding affinity. The sequence selection stage consists of an integer linear optimization model that was solved to produce a rank-ordered list of amino acid sequences with increased stability in the bound peptide-EZH2 structure. These sequences were validated through the calculation of the fold specificity and approximate binding affinity of the designed peptides. Here we report the discovery of novel EZH2 inhibitory peptides using the <i>de novo</i> peptide design method. The computationally discovered peptides were experimentally validated <i>in vitro</i> using dose titrations and mechanism of action enzymatic assays. The peptide with the highest <i>in vitro</i> response, SQ037, was validated <i>in nucleo</i> using quantitative mass spectrometry-based proteomics. This peptide had an IC₅₀ of 13.5 M, demonstrated greater potency as an inhibitor when compared to the native and K27A mutant control peptides, and demonstrated competitive inhibition versus the peptide substrate. Additionally, this peptide demonstrated high specificity to the EZH2 target in comparison to other histone methyltransferases. The validated peptides are the first computationally designed peptides that directly inhibit EZH2. These inhibitors should prove useful for further chromatin biology investigations.</p></div

Chromoanasynthesis is a common mechanism that leads to ERBB2 amplifications in a cohort of early stage HER2+ breast cancer samples

Abstract Background HER2 positive (HER2+) breast cancers involve chromosomal structural alterations that act as oncogenic driver events. Methods We interrogated the genomic structure of 18 clinically-defined HER2+ breast tumors through integrated analysis of whole genome and transcriptome sequencing, coupled with clinical information. Results ERBB2 overexpression in 15 of these tumors was associated with ERBB2 amplification due to chromoanasynthesis with six of them containing single events and the other nine exhibiting multiple events. Two of the more complex cases had adverse clinical outcomes. Chromosomes 8 was commonly involved in the same chromoanasynthesis with 17. In ten cases where chromosome 8 was involved we observed NRG1 fusions (two cases), NRG1 amplification (one case), FGFR1 amplification and ADAM32 or ADAM5 fusions. ERBB3 over-expression was associated with NRG1 fusions and EGFR and ERBB3 expressions were anti-correlated. Of the remaining three cases, one had a small duplication fully encompassing ERBB2 and was accompanied with a pathogenic mutation. Conclusion Chromoanasynthesis involving chromosome 17 can lead to ERBB2 amplifications in HER2+ breast cancer. However, additional large genomic alterations contribute to a high level of genomic complexity, generating the hypothesis that worse outcome could be associated with multiple chromoanasynthetic events

Constitutional chromosome rearrangements that mimic the 2017 world health organization acute myeloid leukemia with recurrent genetic abnormalities : A study of three cases and review of the literature.

OBJECTIVES: To identify and characterize constitutional chromosomal rearrangements that mimic recurrent genetic abnormalities in acute myeloid leukemia (AML). METHODS: Bone marrow and blood chromosome studies were reviewed to identify constitutional rearrangements that resemble those designated by the 2017 revised World Health Organization (WHO) AML with recurrent genetic abnormalities . Mate-pair sequencing (MPseq) was performed on cases with constitutional chromosome mimics of recurrent AML abnormalities to further define the rearrangement breakpoints. RESULTS: Three cases with constitutional rearrangements were identified, including t(6;9)(p23;q34), inv(16)(p13.1q22), and t(9;22)(q34.1;q12.2). Two cases were bone marrow specimens being evaluated for hematologic neoplasms, while one case was a blood specimen being evaluated for primary ovarian insufficiency. MPseq provided high-resolution and precise rearrangement breakpoints, and resolved the atypical FISH results generated with each rearrangement. CONCLUSIONS: Our findings illustrate that constitutional rearrangements can mimic recurrent genetic abnormalities observed in AML, and we emphasize the importance of correlating genetic data with clinical and hematopathologic information

Three-Stage <i>De Novo</i> Peptide Design Workflow Diagram.

<p>Stage I is an optimization-based sequence selection stage. Stage II is a fold specificity calculation to determine how well designed sequences fold into the desired template structure compared to the native sequence. Stage III is an approximate binding affinity calculation to determine how well the designed sequences binds to the target protein.</p