Biology subjects

Kilinc, M.

Publications and source records attributed to Kilinc, M..

7 recordsLinked to original sources

bioRxiv2025

The Endo-GeneScreen Platform Identifies Drug-Like Probes that Regulate Endogenous Protein Levels within Physiological Contexts

Traditional phenotypic drug discovery platforms have suffered from poor scalability and a lack of mechanistic understanding of newly discovered phenotypic probes. To address this, we created Endo-GeneScreen (EGS), a high-throughput enabled screening platform that identifies bioactive small molecules capable of regulating endogenous protein expression encoded by any preselected target gene within a biologically appropriate context. As a proof-of-concept, EGS successfully identified drug candidates that up-regulate endogenous expression of neuronal Syngap1, a gene that causes a neurodevelopmental disorder when haploinsufficient. For example, SR-1815, a previously unknown and undescribed kinase inhibitor, alleviated major cellular consequences of Syngap1 loss-of-function by restoring normal SynGAP protein levels and dampening neuronal hyperactivity within haploinsufficient neurons. Moreover, we demonstrate that EGS assays accelerate preclinical development of identified drug candidates and facilitate mode-of-action deconvolution studies. Thus, EGS identifies first-in-class bioactive small molecule probes that promote biological discovery and precision therapeutic development.

neuroscience↗

bioRxiv2025

ESMStabP: A Regression Model for Protein Thermostability Prediction

Accurately predicting protein thermostability is crucial for numerous applications in biotechnology, pharmaceuticals, and food science. Experimental methods for determining protein melting temperatures are often time-consuming and costly, driving the need for efficient computational alternatives. In this paper, we introduce ESMStabP, an enhanced regression model for predicting protein thermostability. To improve model performance and generalizability, we assembled a significantly larger dataset by combining and cleaning datasets previously utilized in other thermostability models. Building on Deep-StabP, ESMStabP incorporates significant improvements, using embeddings from the ESM2 protein language model and thermophilic classifications. The predictions from ESMStabP outperform DeepStabP and other existing predictors, achieving an R2 of 0.95 and a Pearson correlation coefficient (PCC) of 0.97. Despite these improvements, challenges such as dataset availability. This work underscores the critical role of specific layer identification for model development and outlines potential directions for future advancements in protein stability predictions

bioinformatics↗

bioRxiv2022

Protein Language Model Performs Efficient Homology Detection

MotivationThere are now 225 million sequences in the UniProtKB database, as of January 2022 and 451 million protein sequences in the NCBI non-redundant database. This huge sequence data is ripe for analysis and can be extremely informative about biological function when analyzed with the appropriate methods. Evolutionary information such as the relationship among protein sequences is key to performing sequence analyses. Since sequence matching is one of the primary ways that annotations are found, higher-quality sequence matches yield a larger number of identified homologs. Thus, there is an essential need for a faster and more accurate homolog detection method to process the huge amount of rapidly growing biological sequences. MethodRecently, we have seen major improvements in various predictive computational tasks such as structure prediction from the ever-improving artificial intelligence methods. One such approach has been to use language models to represent proteins numerically in a representation matrix (embeddings) while retaining context-dependent biochemical, biophysical, and evolutionary information. Computational transformer architectures that utilize attention neural networks can generate these context-aware numerical representations in an unsupervised fashion. One such use for these protein embeddings is remote homolog detection. In this work, we utilize protein language models and then apply discrete cosine transforms to extract the essential part of these embeddings, resulting in a significantly smaller fixed-size matrix for each sequence. This allows us to numerically and efficiently calculate the distance between all pairs of proteins resulting in homolog detection. ResultsOur Protein LAnguage model Search Tool (PLAST) is significantly faster, with linear runtimes in the number of sequences within the query database. With only one CPU core, it can scan a million sequences in less than a second. It essentially removes the noise in the sequence data and leads to significant improvements. PLAST is more accurate in the benchmarks tested from the PFAM, SCOP, and CATH databases than other approaches. When benchmarked with the PFAM database, the increase in the area under the receiver operating characteristic curve (AUROC) 3.1% when compared with NCBI-BLAST. The number of remote homologs that are detectable now is significantly larger and pushes sequence matches deeply into the usual twilight zone. Compared with the state-of-the-art profile-based homology search tools like CSBLAST, the increase was still 2.0%. PLAST can find remote homologs for a significant number of proteins that had been thought to be unique due to homolog detection failure. These homologs that are found usually have less than 20% sequence identity making them indistinguishable from noise with most other sequence matching methods. ConclusionPLAST is an accurate and fast homolog detection tool essential for easy and rapid progress to utilize the vast amount of data generated by next-generation sequencing methods. Quantization of sequence embeddings into highly-compressed noise-free representations with the use of direct cosine transforms allows for the efficient and accurate detection of normal homologs and remote ones that are un-detectable by other sequence similarity methods. The PLAST web server is accessible from https://mesihk.github.io/plast.

bioinformatics↗

bioRxiv2021

Endogenous Syngap1 Alpha Splice Forms Promote Cognitive Function and Seizure Protection

Loss-of-function variants in SYNAGP1 cause a developmental encephalopathy defined by cognitive impairment, autistic features, and epilepsy. SYNGAP1 splicing leads to expression of distinct functional protein isoforms. Splicing imparts multiple cellular functions of SynGAP proteins through coding of distinct C-terminal motifs. However, it remains unknown how these different splice sequences function in vivo to regulate neuronal function and behavior. Reduced expression of SynGAP-1/2 C-terminal splice variants in mice caused severe phenotypes, including reduced survival, impaired learning, and reduced seizure latency. In contrast, upregulation of 1/2 expression improved learning and increased seizure latency. Mice expressing 1-specific mutations, which disrupted SynGAP cellular functions without altering protein expression, promoted seizure, disrupted synapse plasticity, and impaired learning. These findings demonstrate that endogenous SynGAP isoforms with 1/2 spliced sequences promote cognitive function and impart seizure protection. Regulation of SynGAP- expression or function may be a viable therapeutic strategy to broadly improve cognitive function and mitigate seizure.

neuroscience↗

bioRxiv2020

Splicing of the SynGAP Carboxyl-Terminus Enables Isoform-Specific Tuning of NMDA Receptor Signaling Linked to Cognitive Function

SynGAP-1 is a splice variant of the neurodevelopmental disorder risk gene, SYNGAP1/Syngap1. 1 encodes the C-terminal PDZ binding motif (PBM) that promotes liquid-liquid phase separation, a candidate process for postsynaptic density organization within excitatory synapses. However, it remains unknown how the endogenous SynGAP PBM regulates synapse properties and related cognitive functions. We found that a major PBM function in mice is to limit the mobility of SynGAP-1 in response to NMDA receptor activation. Genetic disruption of the PBM increased SynGAP-1 mobility to levels consistent with other non-PBM-containing C-terminal isoforms. This resulted in a lowering of the threshold for NMDA receptor-dependent signaling required for plasticity, leading to aberrant strengthening of excitatory synapses in spontaneously active neurons. PBM-deficient animals also exhibited a lower seizure threshold, disrupted LTP, and impaired cognition. Thus, the PBM enables isoform-specific SynGAP gating of NMDA receptor function, a mechanism linking synaptic signaling dynamics to network excitability and cognition.

neuroscience↗

bioRxiv2019

Syngap Splice Variants Display Heterogeneous Spatio-Temporal Expression And Subcellular Distribution In The Developing Mammalian Brain

The Syngap1 gene is a major regulator of synapse biology and neural circuit function. Genetic variants linked to epilepsy and intellectual disability disrupt synaptic function and neural excitability. The SynGAP protein has been involved in multiple signaling pathways and can regulate small GTPases with very different functions. Yet, the molecular bases behind this pleiotropy are poorly understood. We hypothesize that different SynGAP isoforms will mediate different sets of functions and that deciphering their spatio-temporal expression and subcellular localization will accelerate our understanding of the multiple functions performed by SynGAP. Using antibodies that detect all isoforms of SynGAP, we found that its subcellular localization changed throughout postnatal development. Consistent with previous reports, SynGAP was enriched in the postsynaptic density in the mature forebrain. However, this was age-dependent and SynGAP was predominantly found in non-synaptic locations in a period of postnatal development highly sensitive to SynGAP levels. Furthermore, we identified different expression patterns in the spatial and temporal axes for different SynGAP isoforms. Particularly noticeable was the delayed expression of SynGAP 1 isoforms, which bind to PSD-95 at the postsynaptic density, in cortex and hippocampus during the first two weeks of postnatal development. The subcellular localization of SynGAP was also isoform-dependent. While, 1 isoforms were highly enriched in the postsynaptic density, other C-terminal isoforms were less enriched or even more abundant in non-synaptic locations, particularly during the postnatal period. Thus, the regulation of expression and subcellular distribution of SynGAP isoforms may contribute to isoform-specific regulation of small GTPases, explaining SynGAP pleiotropy.

neuroscience↗

bioRxiv2018

Re-expression of SynGAP Protein in Adulthood Improves Translatable Measures of Brain Function and Behavior in a Model of Neurodevelopmental Disorders

BackgroundNeurodevelopmental disorder (NDD) risk genes have pleiotropic biological functions, such as control over both developmental and non-developmental processes that influence disease-related phenotypes. Currently, it remains unclear how developmental versus non-developmental processes influence the duration and/or effectiveness of permissive treatment windows for NDDs. SYNGAP1 haploinsufficiency causes an NDD defined by autistic traits, cognitive impairment, and epilepsy. Syngap1 heterozygosity in mice disrupts a developmental critical period, and, consistent with this, certain behavioral abnormalities are resistant to gene therapy initiated in adulthood. However, the Syngap1 endophenotype is extensive and this protein has diverse cell biological functions. Therefore, SynGAP pleiotropy may influence the permissive treatment window for previously untested disease-relevant phenotypes.\n\nMethodsA whole-body gene restoration technique was used to determine how restoration of SynGAP protein in adult heterozygous mice impacted previously untested phenotypes, such as memory, seizure susceptibility, systems-level cortical hyperexcitability, and hippocampal oscillations linked to mnemonic processes.\n\nResultsAdult restoration of SynGAP protein in haploinsufficient mice reversed long-term contextual memory deficits and behavioral measures of seizure susceptibility. Moreover, SynGAP re-expression in adult mice eliminated brain state-dependent, patient-linked paroxysmal interictal spiking and increased the amplitude of hippocampal theta oscillations.\n\nConclusionsSynGAP protein in the mature brain dynamically regulates neural circuit function and influences disease-relevant phenotypes. The impact of these findings is that treatments targeting certain debilitating aspects of SYNGAP1-related disorders may be effective throughout life. Moreover, the efficacy of experimental treatments for SYNGAP1 patients may be quantifiable through changes in species-conserved, state-dependent pathological electroencephalogram signals.

neuroscience↗