Juliyan (Kavinda) Gunasinghe

An avid drug hunter! Currently reading for my PhD at Monash Institute of Pharmaceutical Sciences!

[Juliyan (Kavinda) Gunasinghe @juliyan_g]

Glad to see our work on c-Myc/Max heterodimer done with @RahmanLab was featured on the cover of this week's @ACS_Omega edition!

[Juliyan (Kavinda) Gunasinghe @juliyan_g]

@RahmanLab Wow!

[ATVB: An AHA Journal @atvbahajournals]

BMP binding by matrix Gla protein (MGP) is essential for limiting aortic fibrosis but not the anti-calcific effects.
@UCLAVascularBio @XinjiangCai @Wu_Xiuju @Zhanglily19 @juliyan_g
https://t.co/7dk4ON148W

[Juliyan (Kavinda) Gunasinghe @juliyan_g]

Together with @XinjiangCai, we show how MGP's γ-carboxylation locks in its Ca²⁺-binding, and how Pro64Gly blocks BMP4 binding without touching Ca²⁺ coordination — shifting vascular disease from calcification toward fibrosis in @atvbahajournals.

https://t.co/PPPS8joJlI

[JCIM & JCTC Journals @JCIM_JCTC]

Toward In Situ Dynamics of DNA-Bound Full-Length p53 Tetramer #MolecularDynamics #MSMs
https://t.co/NWthrAbzV8
@EmiliaPBarros @RommieAmaro @UCSanDiego
#JCIM Vol66 Issue2 #compchem

[Juliyan (Kavinda) Gunasinghe @juliyan_g]

Checkout our review on ultra large virtual screening in "Drug Discovery Today"!

#ulvs #virtualscreening #drugdiscovery

[Pedro Ballester @pjballester]

Enjoyed reading "Hit identification in ultra large virtual screening: an integrative review and future challenges"

https://t.co/bJ3KWD7Qtw

[Juliyan (Kavinda) Gunasinghe @juliyan_g]

Our latest review, published in 'Drug Discovery Today', highlights current trends in ultra-large virtual screening and identifies potential bottlenecks across several pipelines.

Check it out!

#ULVS #drugdiscovery #virtualscreening #compchem
Link:

https://t.co/JQqd2x1MGH

[JCIM & JCTC Journals @JCIM_JCTC]

Combining Bayesian and Evidential Uncertainty Quantification for Improved Bioactivity Modeling
https://t.co/bn7dDXPh8A
@BolaK_DDD @kschweig_ @GJPvWesten @hermanvvlijmen #CDDLeiden
#JCIM Vol65 Issue24 #MachineLearning #DeepLearning

[Juliyan (Kavinda) Gunasinghe @juliyan_g]

@shozeb_haider Really enjoyed your talk Prof. @shozeb_haider!

[JCIM & JCTC Journals @JCIM_JCTC]

Adiabatic-Bias Molecular Dynamics Simulations Reveal the Impact of Mutations on Muscarinic Antagonist Unbinding Kinetics #MolecularDynamics
https://t.co/FD2yKZ8LKz
@ChiaravalleAnna @parsec93 @CAMD_DISB @uniurbit
#JCIM Vol65 Issue13 #PharmaceuticalModeling

[Juliyan (Kavinda) Gunasinghe @juliyan_g]

Had a great time presenting @neuralgap_io and latest progress on our structure-based drug discovery platforms! #compchem #neuralgap #drugdiscovery #deeplearning #genesys

[Juliyan (Kavinda) Gunasinghe @juliyan_g]

Together with @RahmanLab, we modeled the full-length LMP1 protein through accelerated molecular dynamics simulations. Our work highlight the C-terminal region, as a promising drug target of the LMP1 protein!
#moleculardynamics #EBV #LMP1

https://t.co/eUXJ8wDJ24

[Andrew Akbashev @Andrew_Akbashev]

MYTH: Great founders drop out of college.
REALITY: PhD is a HUGE plus for a founder.

1⃣ If you look at this list:

- Mark Zuckerberg (co-founder of Facebook) dropped out of Harvard
- Travis Kalanick (co-founder of Uber) dropped out of UCLA
- Jan Koum (co-founder of WhatsApp) dropped out of San Jose State University
- Michael Dell (founder of Dell Tech.) dropped out of the University of Texas
- Larry Ellison (co-founder of Oracle) left UIUC
- Bill Gates (co-founder of Microsoft) dropped out of Harvard
- Evan Williams (co-founder of Twitter) left the University of Nebraska
- Steve Jobs (co-founder of Apple) dropped out of Reed College

You may think:
Being a dropout = Success as a founder?

“YES” - many young people think.

And yet - these are EXCEPTIONS.

The average age of a successful entrepreneur is 45.

2⃣ Dropouts are often very passionate.

But passion alone can’t turn your startup into a billion-dollar business.

What’s important:

- Your ability to correctly calculate risks

- Your ability to pivot your business fast and multiple times

- Your ability to hire, delegate and prioritize.

3⃣ These essential qualities come with experience.

This is why very young founders often fail.
This is why it may take a few failed startups to succeed.

This is why education is so IMPORTANT !
(especially for technical startups)

▫️

❗️ My advice:

Most students see PhD as just a stepping stone into academic or industry positions.

But I suggest viewing it as time for YOUR personal development.

It helps you build resilience, learn risk taking, and develop technical hyperfocus.

If you aim high, all of this is vital for big innovations.

▫️

p.s. Data in the image are from the amazing studies by the group of Ilya Strebulaev (@IlyaStrebulaev), a professor at Stanford Business School.

[JCIM & JCTC Journals @JCIM_JCTC]

NRIMD, a Web Server for Analyzing Protein Allosteric Interactions Based on Molecular Dynamics Simulation #MolecularDynamics #Allostery
https://t.co/XGsIIx0zaX
@DongXu10710609
#JCIM ASAP #ApplicationNote

[Neuralgap @neuralgap_io]

We are releasing our joint tooling and service layer for helping enterprises build AI models that can combine multiple different inputs to predict with exceptional accuracy. Welcome to ModalX - coming soon.

#AI #Multimodal #Enterprise #Advanced #ModalX

[Juliyan (Kavinda) Gunasinghe @juliyan_g]

Explore more on coarse-grained molecular dynamics with @neuralgap_io!

[Neuralgap @neuralgap_io]

Releasing our 3rd part of the Computational Alchemy series, a dive into coarse grained molecular dynamics. Hope you enjoyed it!

#CGMDSimplified
#DrugDiscoveryInnovation
#BiomolecularBreakthroughs
#CoarseGrainedDynamics

https://t.co/3CWEqhdmF7

[Juliyan (Kavinda) Gunasinghe @juliyan_g]

Conventional Molecular Dynamics is an integral part of computational drug discovery pipelines! Explore more with @neuralgap_io! #compchem #md #drug #discovery

[Neuralgap @neuralgap_io]

Exploring All-Atom Molecular Dynamics: Dive into our latest post on the profound impact of atomic-level simulations in biophysics. Enjoy and stay tuned!
https://t.co/v515DEp004

#MolecularDynamics #Biophysics

[JCIM & JCTC Journals @JCIM_JCTC]

Can Current Molecular Docking Methods Accurately Predict RNA Inhibitors? #RNA #Docking
https://t.co/dL82GDGWE1
@juliyan_g @RahmanLab
#JCIM Vol64 Issue15 #compchem

[Juliyan (Kavinda) Gunasinghe @juliyan_g]

Implementation and development of ML-based scoring functions in molecular docking at @neuralgap_io !

[Neuralgap @neuralgap_io]

In our latest article, we discuss the usage of structure-based virtual screening with ML scoring in the drug discovery pipeline. Hope you enjoy it!

#AIDrugDiscovery #NeuralgapInnovation #MachineLearningHealth #VirtualScreening #TherapeuticsRevolution

https://t.co/O1EtOM9oh9

[Juliyan (Kavinda) Gunasinghe @juliyan_g]

Unsupervised ML in Drug Discovery! Explore more with @neuralgap_io!

[Neuralgap @neuralgap_io]

Unlock the future of drug discovery with unsupervised learning! Dive into the potential of AI-driven breakthroughs in cheminformatics.

#DrugDiscovery #UnsupervisedLearning #Cheminformatics #PharmaceuticalResearch

https://t.co/0ryxkIsXB9

[Juliyan (Kavinda) Gunasinghe @juliyan_g]

Deep-learning based QSAR modeling at @neuralgap_io!

[Neuralgap @neuralgap_io]

In this article we are examining the use of graph-based neural networks in the use of Quantitative Structure–Activity Relationships modelling, and why they are very well suited to this type of analysis. Hope you enjoy it!
https://t.co/B7SUB1woDq
#QSARModeling #GraphNeuralNetwork