Hotspot Identification and Drug Design of Protein-Protein Interaction Modulators Using the Fragment Molecular Orbital Method

Protein-protein interactions (PPIs) are essential for the function of many proteins. Aberrant PPIs have the potential to lead to disease, making PPIs promising targets for drug discovery. There are over 64,000 PPIs in the human interactome reference database; however, to date, very few PPI modulators have been approved for clinical use. Further development of PPI-specific therapeutics is highly dependent on the availability of structural data and the existence of reliable computational tools to explore the interface between two interacting proteins. The fragment molecular orbital (FMO) quantum mechanics method offers comprehensive and computationally inexpensive means of identifying the strength (in kcal/mol) and the chemical nature (electrostatic or hydrophobic) of the molecular interactions taking place at the protein-protein interface. We have integrated FMO and PPI exploration (FMO-PPI) to identify the residues that are critical for protein-protein binding (hotspots). To validate this approach, we have applied FMO-PPI to a dataset of protein-protein complexes representing several different protein subfamilies and obtained FMO-PPI results that are in agreement with published mutagenesis data. We observed that critical PPIs can be divided into three major categories: interactions between residues of two proteins (intermolecular), interactions between residues within the same protein (intramolecular), and interactions between residues of two proteins that are mediated by water molecules (water bridges). We extended our findings by demonstrating how this information obtained by FMO-PPI can be utilized to support the structure-based drug design of PPI modulators (SBDD-PPI).

Discovery of Novel UDP-N-Acetylglucosamine Acyltransferase (LpxA) Inhibitors with Activity against Pseudomonas aeruginosa

This study describes a novel series of UDP-N-acetylglucosamine acyltransferase (LpxA) inhibitors that was identified through affinity-mediated selection from a DNA-encoded compound library. The original hit was a selective inhibitor of Pseudomonas aeruginosa LpxA with no activity against Escherichia coli LpxA. The biochemical potency of the series was optimized through an X-ray crystallography-supported medicinal chemistry program, resulting in compounds with nanomolar activity against P. aeruginosa LpxA (best half-maximal inhibitory concentration (IC₅₀) <5 nM) and cellular activity against P. aeruginosa (best minimal inhibitory concentration (MIC) of 4 μg/mL). Lack of activity against E. coli was maintained (IC₅₀ > 20 μM and MIC > 128 μg/mL). The mode of action of analogues was confirmed through genetic analyses. As expected, compounds were active against multidrug-resistant isolates. Further optimization of pharmacokinetics is needed before efficacy studies in mouse infection models can be attempted. To our knowledge, this is the first reported LpxA inhibitor series with selective activity against P. aeruginosa.

Characterising GPCR-ligand interactions using a fragment molecular orbital-based approach

There has been fantastic progress in solving GPCR crystal structures. However, the ability of X-ray crystallography to guide the drug discovery process for GPCR targets is limited by the availability of accurate tools to explore receptor-ligand interactions. Visual inspection and molecular mechanics approaches cannot explain the full complexity of molecular interactions. Quantum mechanical approaches (QM) are often too computationally expensive, but the fragment molecular orbital (FMO) method offers an excellent solution that combines accuracy, speed and the ability to reveal key interactions that would otherwise be hard to detect. Integration of GPCR crystallography or homology modelling with FMO reveals atomistic details of the individual contributions of each residue and water molecule towards ligand binding, including an analysis of their chemical nature.

Computational Methods Used in Hit-to-Lead and Lead Optimization Stages of Structure-Based Drug Discovery

GPCR modeling approaches are widely used in the hit-to-lead (H2L) and lead optimization (LO) stages of drug discovery. The aims of these modeling approaches are to predict the 3D structures of the receptor-ligand complexes, to explore the key interactions between the receptor and the ligand and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this book chapter, we present a brief survey of key computational approaches integrated with hierarchical GPCR modeling protocol (HGMP) used in hit-to-lead (H2L) and in lead optimization (LO) stages of structure-based drug discovery (SBDD). We outline the differences in modeling strategies used in H2L and LO of SBDD and illustrate how these tools have been applied in three drug discovery projects.

Exploring GPCR-Ligand Interactions with the Fragment Molecular Orbital (FMO) Method

The understanding of binding interactions between any protein and a small molecule plays a key role in the rationalization of affinity and selectivity. It is essential for an efficient structure-based drug design (SBDD) process. FMO enables ab initio approaches to be applied to systems that conventional quantum-mechanical (QM) methods would find challenging. The key advantage of the Fragment Molecular Orbital Method (FMO) is that it can reveal atomistic details about the individual contributions and chemical nature of each residue and water molecule toward ligand binding which would otherwise be difficult to detect without using QM methods. In this chapter, we demonstrate the typical use of FMO to analyze 19 crystal structures of β1 and β2 adrenergic receptors with their corresponding agonists and antagonists.

Rapid and accurate assessment of GPCR-ligand interactions Using the fragment molecular orbital-based density-functional tight-binding method

The reliable and precise evaluation of receptor–ligand interactions and pair‐interaction energy is an essential element of rational drug design. While quantum mechanical (QM) methods have been a promising means by which to achieve this, traditional QM is not applicable for large biological systems due to its high computational cost. Here, the fragment molecular orbital (FMO) method has been used to accelerate QM calculations, and by combining FMO with the density‐functional tight‐binding (DFTB) method we are able to decrease computational cost 1000 times, achieving results in seconds, instead of hours. We have applied FMO‐DFTB to three different GPCR–ligand systems. Our results correlate well with site directed mutagenesis data and findings presented in the published literature, demonstrating that FMO‐DFTB is a rapid and accurate means of GPCR–ligand interactions. © 2017 Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Identification of a novel prostate cancer susceptibility variant in the KLK3 gene transcript

Genome-wide association studies (GWAS) have identified more than 30 prostate cancer (PrCa) susceptibility loci. One of these (rs2735839) is located close to a plausible candidate susceptibility gene, KLK3, which encodes prostate-specific antigen (PSA). PSA is widely used as a biomarker for PrCa detection and disease monitoring. To refine the association between PrCa and variants in this region, we used genotyping data from a two-stage GWAS using samples from the UK and Australia, and the Cancer Genetic Markers of Susceptibility (CGEMS) study. Genotypes were imputed for 197 and 312 single nucleotide polymorphisms (SNPs) from HapMap2 and the 1000 Genome Project, respectively. The most significant association with PrCa was with a previously unidentified SNP, rs17632542 (combined P = 3.9 × 10⁻²²). This association was confirmed by direct genotyping in three stages of the UK/Australian GWAS, involving 10,405 cases and 10,681 controls (combined P = 1.9 × 10⁻³⁴). rs17632542 is also shown to be associated with PSA levels and it is a non-synonymous coding SNP (Ile179Thr) in KLK3. Using molecular dynamic simulation, we showed evidence that this variant has the potential to introduce alterations in the protein or affect RNA splicing. We propose that rs17632542 may directly influence PrCa risk.

Genetic, functional, and histopathological evaluation of two C-terminal BRCA1 missense variants

BACKGROUND

The vast majority of BRCA1 missense sequence variants remain uncharacterized for their possible effect on protein expression and function, and therefore are unclassified in terms of their pathogenicity. BRCA1 plays diverse cellular roles and it is unlikely that any single functional assay will accurately reflect the total cellular implications of missense mutations in this gene.

OBJECTIVE

To elucidate the effect of two BRCA1 variants, 5236G>C (G1706A) and 5242C>A (A1708E) on BRCA1 function, and to survey the relative usefulness of several assays to direct the characterisation of other unclassified variants in BRCA genes.

METHODS AND RESULTS

Data from a range of bioinformatic, genetic, and histopathological analyses, and in vitro functional assays indicated that the 1708E variant was associated with the disruption of different cellular functions of BRCA1. In transient transfection experiments in T47D and 293T cells, the 1708E product was mislocalised to the cytoplasm and induced centrosome amplification in 293T cells. The 1708E variant also failed to transactivate transcription of reporter constructs in mammalian transcriptional transactivation assays. In contrast, the 1706A variant displayed a phenotype comparable to wildtype BRCA1 in these assays. Consistent with functional data, tumours from 1708E carriers showed typical BRCA1 pathology, while tumour material from 1706A carriers displayed few histopathological features associated with BRCA1 related tumours.

CONCLUSIONS

A comprehensive range of genetic, bioinformatic, and functional analyses have been combined for the characterisation of BRCA1 unclassified sequence variants. Consistent with the functional analyses, the combined odds of causality calculated for the 1706A variant after multifactorial likelihood analysis (1:142) indicates a definitive classification of this variant as "benign". In contrast, functional assays of the 1708E variant indicate that it is pathogenic, possibly through subcellular mislocalisation. However, the combined odds of 262:1 in favour of causality of this variant does not meet the minimal ratio of 1000:1 for classification as pathogenic, and A1708E remains formally designated as unclassified. Our findings highlight the importance of comprehensive genetic information, together with detailed functional analysis for the definitive categorisation of unclassified sequence variants. This combination of analyses may have direct application to the characterisation of other unclassified variants in BRCA1 and BRCA2.

Novel DNA sequence variants in the hHR21 DNA repair gene in radiosensitive cancer patients

PURPOSE

Radiation therapy is an important treatment modality for oncology patients. DNA sequence variants have so far been identified in only a few genes in radiosensitive cancer patients. Patients known to be clinically radiosensitive were tested for mutation of a gene involved in DNA double-strand break repair and sister chromatid cohesion--hHR21.

METHODS AND MATERIALS

Clinically radiation-sensitive patients were accrued to the study after giving informed consent. Blood samples were obtained and lymphoblastoid cell lines established. Reverse transcriptase-polymerase chain reaction (RT-PCR) was performed to amplify the hHR21 gene, and the DNA product was sequenced to identify any genetic abnormalities. Northern blot analysis, cell survival, and growth assays were performed on control cells and cells with hHR21 variants, and a restriction digest assay was developed to screen for carriers of a detected gene variant.

RESULTS

The DNA sequence of the hHR21 gene was determined in 19 radiation-sensitive cancer patients. In 6 of the 19 patients, a thymidine (T) to cytosine (C) transition was detected at position 1440 of the hHR21 open reading frame (T1440C). This variant did not alter the amino acid sequence and was likely to be a polymorphism. One patient with a particularly severe radiation reaction had a second sequence variant immediately adjacent to the first. This was a guanine (G) to adenine (A) transition (G1441A), resulting in a change of the amino acid sequence (glycine --> arginine) in a portion of the protein conserved in evolution. This suggests that this DNA alteration may be biologically significant. Restriction digest with the HpaII enzyme confirmed the presence of both sequence variants on the same allele.

CONCLUSIONS

We describe the first two DNA sequence variants ever found in the hHR21 gene, in patients with clinical radiation hypersensitivity. Although no direct evidence for the involvement of hHR21 alterations in the radiosensitivity of the cancer patients examined has been demonstrated, the possibility exists that homozygous mutations or other mutations of this gene could contribute to radiosensitivity. A simple test is described that could be applied to screening for these variants in relevant populations.

Mutation analysis of BRCA1 and BRCA2 cancer predisposition genes in radiation hypersensitive cancer patients

PURPOSE

The dose intensity of radiotherapy (RT) used in cancer treatment is limited in rare individuals who display severe normal tissue reactions after standard RT treatments. Novel predictive assays are required to identify these individuals prior to treatment. The mechanisms responsible for such reactions are unknown, but may involve dysfunction of genes involved in the sensing and response of cells to DNA damage. The breast cancer susceptibility genes BRCA1 and BRCA2 are implicated in DNA damage repair and the control of genome stability. The purpose of this study was to determine if clinical radiation hypersensitivity is related to mutations of the BRCA1 and BRCA2 genes. Such information is of potential use in the clinical management of BRCA mutation carriers and their families.

METHODS AND MATERIALS

Twenty-two cancer patients who developed severe normal tissue reactions after RT were screened for mutations of BRCA1 and BRCA2, using various methods including protein truncation testing, direct DNA sequencing, and a PCR-based BRCA1 exon 13 duplication test.

RESULTS

No mutations were detected in the 22 patients tested, despite screening for the majority of commonly described types of mutations of BRCA1 and BRCA2.

CONCLUSION

These early results suggest that genes other than BRCA1 and BRCA2 probably account for most cases of clinical radiation hypersensitivity, and that screening for mutations of BRCA1 and BRCA2 is unlikely to be useful in predicting response to radiotherapy. However, it has not been excluded that some BRCA1 or BRCA2 heterozygotes might experience unexpected RT toxicity; further BRCA mutation screening on radiation sensitive individuals is warranted.

Molecular analysis in the diagnosis of pediatric lymphomas

Thirty-five pediatric lymphomas were categorized as either Burkitt's lymphoma (BL), lymphoblastic lymphoma (LL), or large cell anaplastic lymphoma (LCAL) by histological and immunophenotypic methods. They were further characterized by molecular analysis of their antigen receptor genes. Southern blot (SB) and polymerase chain reaction (PCR) techniques were compared in the detection of immunogloblin heavy chain gene (IgH) rearrangement. T cell receptor beta (TCR beta) rearrangements were analyzed by SB and TCR gamma gene rearrangements by PCR. The PCR method of IgH and TCR gamma gene analysis was preferred to the SB methods, because there were fewer equivocal results in IgH gene analysis, TCR gamma rearrangement was more frequently detected than TCR beta in both lymphoblastic and large cell anaplastic lymphomas, and the PCR technique was more rapid, required less DNA, and could be used with archival material. In addition, analysis of IgH gene rearrangement by PCR was more specific for assessing B cell lineage. Although most of the molecular data were easily interpreted, occasional ambiguous results were seen due to genetic events other than antigen receptor gene rearrangement affecting the genetic analysis. Thus, it is imperative to interpret these genetic data in the context of adequate morphological and immunophenotypic analysis.