Background:Myosin X (MYO10) was recently reported to promote tumour invasion by transporting integrins to filopodial tips in breast cancer. However, the role of MYO10 in tumours remains poorly defined. Here, we report that MYO10 is required in invadopodia to mediate invasive growth and extracellular matrix degradation, which depends on the binding of MYO10's pleckstrin homology domain to PtdIns(3,4,5)P3.Methods:The expression of MYO10 and its associations with clinicopathological and biological factors were examined in breast cancer cells and breast cancer specimens (n=120). Cell migration and invasion were investigated after the silencing of MYO10. The ability of cells to form invadopodia was studied using a fluorescein isothiocyanate-conjugated gelatin degradation assay. A mouse model was established to study tumour invasive growth and metastasis in vivo.Results:Elevated MYO10 levels were correlated with oestrogen receptor status, progesterone receptor status, poor differentiation, and lymph node metastasis. Silencing MYO10 reduced cell migration and invasion. Invadopodia were responsible for MYO10's role in promoting invasion. Furthermore, decreased invasive growth and lung metastasis were observed in the MYO10-silenced nude mouse model.Conclusions:Our findings suggest that elevated MYO10 expression increases the aggressiveness of breast cancer; this effect is dependent on the involvement of MYO10 in invadopodial formation.

Pharmacophore modeling is a successful yet very diverse subfield of computer-aided drug design. The concept of the pharmacophore has been widely applied to the rational design of novel drugs. In this paper, we review the computational implementation of this concept and its common usage in the drug discovery process. Pharmacophores can be used to represent and identify molecules on a 2D or 3D level by schematically depicting the key elements of molecular recognition. The most common application of pharmacophores is virtual screening, and different strategies are possible depending on the prior knowledge. However, the pharmacophore concept is also useful for ADME-tox modeling, side effect, and off-target prediction as well as target identification. Furthermore, pharmacophores are often combined with molecular docking simulations to improve virtual screening. We conclude this review by summarizing the new areas where significant progress may be expected through the application of pharmacophore modeling; these include protein-protein interaction inhibitors and protein design. Keywords: ADME-tox, computer-aided drug design, pharmacophore fingerprint, protein design, virtual screening What is computer-aided drug design?Drug design is an expensive and laborious process of developing new medicine. This process has its origin in herbal remedies dating back millennia.1 Only since the last century have drugs had a (semi)synthetic origin.2 The first hit compounds often lack both potency and safety, and must therefore be optimized. While historically this was a trial-and-error process, 3,4 soon rational strategies were developed to improve potency. 5,6 As with any data handling procedures, computers have become a more prominent and ubiquitous tool in drug discovery since the 1980s. The crossover between computational and pharmaceutical research is typically designated computer-aided drug design (CADD). 8,9 CADD covers a broad range of applications spanning the drug discovery pipeline, although these are highly clustered in the early phases. The main purpose of CADD is to speed up and rationalize the drug design process while reducing costs. 10 The aim of the earliest phase in drug discovery is to identify the first hit compounds, which is sometimes attempted by high-throughput screening (HTS), the testing of many thousands of compounds with a suitable activity assay. The in silico counterpart of in vitro HTS is referred to as virtual screening and aims at filtering libraries of molecules using computational methods to prioritize those most likely to be active for a given

Human D-3-phosphoglycerate dehydrogenase (PHGDH), a key enzyme in de novo serine biosynthesis, is amplified in various cancers and serves as a potential target for anticancer drug development. To facilitate this process, more information is needed on the basic biochemistry of this enzyme. For example, PHGDH was found to form tetramers in solution and the structure of its catalytic unit (sPHGDH) was solved as a dimer. However, how the oligomeric states affect PHGDH enzyme activity remains elusive. We studied the dependence of PHGDH enzymatic activity on its oligomeric states. We found that sPHGDH forms a mixture of monomers and dimers in solution with a dimer dissociation constant of ∼0.58 μM, with the enzyme activity depending on the dimer content. We computationally identified hotspot residues at the sPHGDH dimer interface. Single-point mutants at these sites disrupt dimer formation and abolish enzyme activity. Molecular dynamics simulations showed that dimer formation facilitates substrate binding and maintains the correct conformation required for enzyme catalysis. We further showed that the full-length PHGDH exists as a dynamic mixture of monomers, dimers, and tetramers in solution with enzyme concentration-dependent activity. Mutations that can completely disrupt the sPHGDH dimer show different abilities to interrupt the full-length PHGDH tetramer. Among them, E108A and I121A can also disrupt the oligomeric structures of the full-length PHGDH and abolish its enzyme activity. Our study indicates that disrupting the oligomeric structure of PHGDH serves as a novel strategy for PHGDH drug design and the hotspot residues identified can guide the design process.