جست‌وجوی استاد و پژوهشگر

Josh Vincent Vermaasمشاهده پروفایل

استادیار

• Molecular Modeling
• Computational Biology
• Photosynthetic Organisms
• +۷ مورد دیگر

Josh Vincent Vermaas is an Assistant Professor in the Department of Biochemistry & Molecular Biology at Michigan State University, with joint appointments at the MSU-DOE Plant Research Laboratory and the Molecular Plant Sciences Program. His research focuses on using computational methods to understand biological phenomena at the molecular level, particularly in photosynthetic organisms and plant materials. Dr. Vermaas earned his BS in Physics, Biochemistry, and Computational Mathematics from Arizona State University in 2010, followed by a PhD in Biophysics from the University of Illinois at Urbana-Champaign in 2016. He completed postdoctoral training at the National Renewable Energy Laboratory (2016-2019) and served as a Computational Scientist at Oak Ridge National Laboratory in 2020 before joining MSU in January 2021. His research employs atomic-scale simulation tools to create molecular models that reveal how biological structures function at the nanoscale. The Vermaas Lab investigates three primary areas: lipid membranes and membrane proteins, nanostructures in photosynthetic organisms, and advanced computational methods. Their work combines molecular dynamics simulations with experimental collaborations to address sustainability challenges in energy conversion and bioproduct production. Recent projects include studying carboxysome permeability, lignin structure, membrane transport mechanisms, and developing machine learning-based force fields. The lab's publication record demonstrates expertise across computational biophysics, with recent papers focusing on bacterial microcompartment structure and function, plant membrane permeability, photosynthetic mechanisms, and fungal cell wall remodeling. Their research often combines multiple techniques including molecular dynamics, Brownian dynamics, and experimental validation. OpenEye Outstanding Junior Faculty Award (2025) Tomashow Keegstra Award (for work on human cis-prenyltransferase) Dr. Vermaas mentors multiple graduate and undergraduate students, including Duncan Boren, Jinxin Lin, and Siva Naga Sai Damaraju. His lab has secured significant funding, including an NIH R35 award for studying natural product transport. The Vermaas Lab actively participates in outreach activities such as the MSU Science Festival and Girls Math and Science Day, demonstrating commitment to science education and community engagement.

Erica Teixeira Pratesمشاهده پروفایل

پژوهشگر

• Computational Systems Biology
• Structural Bioinformatics
• Molecular Dynamics Simulations
• +۶ مورد دیگر

Erica Teixeira Prates is a Computational Systems Biologist at Oak Ridge National Laboratory (ORNL), working within the Biological and Environmental Systems Science Directorate's Biosciences Division. She leads computational research in the Computational and Predictive Biology Group and Biocomputing and Information Section, focusing on integrating molecular dynamics simulations with multi-omics data to study protein structure-function relationships. Her research spans three major domains: Bioenergy (CBI projects on plant-microbe interfaces and cellulose biosynthesis) Plant-Microbe Interactions (modeling receptor-ligand pairing in Populus systems) Viral Pathogenesis (SARS-CoV-2 protease mechanisms and antiviral strategies) She develops computational protocols for proteome-wide modeling, virtual screening, and enhanced sampling techniques to bridge molecular biophysics with systems-level biological traits. Publication analysis reveals consistent focus on structural bioinformatics (47% of articles), with growing emphasis on AI-driven approaches since 2020. Her work connects quantum biology with CRISPR optimization, metabolite-GWAS networks in plants, and opioid addiction genetics through meta-multiomics integration. Professional contributions include key projects: Plant-Microbe Interfaces (PMI) initiative for bioenergy crops COVID-19 research on NEMO cleavage and bradykinin storms Development of explainable AI models for viral mutation tracking

• Robotics
• Control Systems
• Nonholonomic Mobile Robots
• +۷ مورد دیگر

Professor Maciej Michałek is a distinguished academic at Poznań University of Technology, where he serves in the Faculty of Automatic Control, Robotics and Electrical Engineering within the Institute of Automation and Robotics. His research spans robotics, control systems, and automation with particular focus on nonholonomic mobile robots and advanced control methodologies. Professor Michałek's research interests center on Vector Field Orientation (VFO) control methodology, mobile robot motion planning, and Active Disturbance Rejection Control (ADRC). He has made significant contributions to fixed-time and predefined-time control systems, kinematic modeling of multi-trailer vehicles, and precision docking systems for electric buses. His work bridges theoretical control concepts with practical applications in automotive, aerospace, and robotics domains. His recent publications demonstrate a clear trajectory toward time-constrained control systems with guaranteed convergence properties, multi-agent coordination, and practical implementations in electric vehicle infrastructure. Professor Michałek has published extensively in top-tier journals including IEEE Transactions on Cybernetics, Nonlinear Dynamics, and IEEE Transactions on Vehicular Technology. As a supervisor, Professor Michałek has guided doctoral students through research on cascaded control systems for mobile robots and motion algorithmization within the VFO framework. His mentorship focuses on rigorous theoretical development combined with practical implementation of advanced control systems. Professor Michałek maintains active research in both theoretical control methodologies and their practical applications, particularly in electric vehicle charging systems, automotive control mechanisms, and aerospace stabilization. His laboratory work focuses on experimental validation of control algorithms using robotic platforms and vehicle simulation systems.

• Theoretical Biophysical Chemistry
• Computational Drug Discovery
• Molecular Modeling
• +۴ مورد دیگر

Professor Leif Eriksson is a leading computational chemist in the Department of Chemistry and Molecular Biology at the University of Gothenburg, holding his professorship since 2011 after positions at NUI Galway and Dalhousie University. His research group comprises 1 research engineer, 2 postdocs, 1 doctoral student, and multiple Master's researchers focusing on AI-driven drug discovery. His educational background includes: Chemistry studies at Stockholm University and University of Sussex PhD in Quantum Chemistry, Uppsala University (1992) Postdoctoral Fellowship at Dalhousie University, Canada (1992-93) Research centers on theoretical biophysical chemistry with emphasis on computational modeling of DNA damage, cancer mechanisms, and antibiotic development. The group pioneers AI-based tools (MolAI, iScore) for ultrafast drug discovery, studying stress response pathways in glioblastoma/TNBC and developing inhibitors through multi-scale simulations from QM/MM to molecular dynamics. Recent work targets protein-protein interactions, membrane diffusion, and drug-loaded liposomes using integrated computational-experimental approaches. Publication trends (2022-2025) reveal strong focus on cancer therapeutics (35%), antibiotic discovery (25%), and AI-driven drug design (40%), with increasing integration of machine learning for ADMET prediction and target validation. Key journals include Journal of Chemical Information and Modeling (30%), Biochemistry (20%), and Scientific Reports (15%). Scientific recognition includes: Göta Student Union's Pedagogical Prize (2017) 300+ scientific papers and 20+ review chapters Patents for skin cancer/glioblastoma drugs leading to spin-offs (ANYO Labs, C26 Bioscience, Cell Stress Discoveries) Advising involves direct supervision of doctoral/postgraduate researchers with strong industry-academia pipelines. Grant funding is sustained through: National: Swedish Research Council, Swedish Cancer Society, Lawski Foundation International: Wenner-Gren Foundations, GBM Foundation, EU H2020 MSCA-RISE The lab maintains active collaborations with UGOT CARe for antibiotic resistance research and international networks for cancer drug validation. Research infrastructure leverages national supercomputing resources (via NAC leadership) and integrates wet-lab validation through spin-off partnerships. Current projects focus on translating computational discoveries into patentable therapeutics for aggressive cancers and antimicrobial resistance, with multiple compounds in preclinical development phases.

• Enzyme Engineering
• Biocatalysis
• Protein Engineering
• +۳ مورد دیگر

Vincent Lafaquière is a research scientist affiliated with Université de Toulouse and its associated institutions including INSA, UPS, INP, and the joint LISBP laboratory (CNRS/INRA). His work sits at the intersection of biochemistry, protein engineering, and computational biology. His research focuses on enzyme engineering , particularly the rational modification of lipases for improved enantioselectivity. By targeting specific residues in the substrate binding site and access channel of Burkholderia cepacia lipase, his team has developed mutants with dramatically enhanced catalytic properties. This work combines site-directed mutagenesis , high-throughput screening , and computational trajectory analysis to optimize biocatalysts for chiral synthesis applications. Lafaquière's publication record demonstrates consistent contributions to the field of biocatalysis, with his most notable work showing a 15-fold increase in specific activity and significant improvements in enantioselectivity through strategic protein engineering. His research has direct applications in pharmaceutical synthesis where chiral purity is critical. He operates within the collaborative ecosystem of LISBP, a major French research unit specializing in biological systems and processes engineering. His work benefits from interdisciplinary connections between biochemists, computational scientists, and process engineers working on enzyme applications.

Salem Salah Salemمشاهده پروفایل

دانشیار

• Microbial Biotechnology
• Nanotechnology
• Green Synthesis
• +۲ مورد دیگر

Dr. Salem Salah Salem is an Associate Professor at Al-Azhar University's Department of Botany and Microbiology, Faculty of Science. His primary affiliations include the Mamdouh Salem El-Gamal's Lab, where he conducts research and teaches courses in microbial biotechnology, bacterial physiology, and environmental microbiology. His research specializes in: Green synthesis of metallic nanoparticles (Ag, Se, ZnO, CuO) using plant extracts and microbial systems Nanoparticle applications in antimicrobial therapies, cancer treatment, and environmental remediation Industrial enzyme optimization and waste valorization for sustainable bioprocessing Development of nanocomposites for water purification and agricultural enhancement Publication analysis reveals consistent focus on: Eco-friendly nanomaterial synthesis methodologies Multifunctional biomedical applications (antimicrobial/anticancer) Cross-disciplinary approaches combining microbiology, nanotechnology, and environmental science Utilization of agricultural waste for nanoparticle production No awards or grants are mentioned in the source material.

• Quantum Chemistry
• Electron Charge Density Analysis
• Molecular Design
• +۴ مورد دیگر

Amanda Morgenstern is an Assistant Professor in the Department of Chemistry & Biochemistry at the University of Colorado Colorado Springs, part of the College of Letters, Arts & Sciences. Her research program focuses on developing and applying computational methods to understand electron charge density in chemical systems. Dr. Morgenstern received her B.A. from Colorado College in 2010, followed by a Ph.D. from the Colorado School of Mines in 2016 where she worked with the Molecular Theory Group. She completed postdoctoral training at Los Alamos National Laboratory from 2017-2019 in the Theoretical-1 Division. Her research centers on discovering how electron charge density can better understand and design molecules, materials, and enzymes. The most fundamental aspect of her work is the development of gradient bundle analysis, an extension of the quantum theory of atoms in molecules (QTAIM) that provides detailed structural information from electron charge density. Current projects investigate how electric fields can rearrange charge density to catalyze reactions and control product selectivity, propose drug candidates for Human African Trypanosomiasis using molecular docking and QTAIM, and computationally investigate spectroscopy results for tetramine molecules. Analysis of Dr. Morgenstern's publication record shows a strong focus on quantum chemical topology, with particular emphasis on extending QTAIM through gradient bundle analysis. Her work spans theoretical development, enzyme catalysis studies, materials science applications, and medicinal chemistry. Many publications involve collaborations with researchers at Los Alamos National Laboratory and other institutions, reflecting an interdisciplinary approach to computational chemistry. Dr. Morgenstern has received recognition through publications in high-impact journals including Journal of the American Chemical Society, Chemical Science, and Journal of Physical Chemistry. Her work demonstrates both theoretical innovation in quantum chemical methods and practical applications in drug discovery and materials science. As a relatively early-career faculty member (Assistant Professor), Dr. Morgenstern appears to be building an active research program with multiple ongoing projects. Her work at the intersection of theoretical chemistry and practical applications suggests opportunities for students interested in computational methods development and their application to real-world problems in medicine and materials science.

• Electrochemistry
• Organic Chemistry
• Biochemistry
• +۳ مورد دیگر

Dr Jon Wilden serves as Associate Professor in Chemistry within the School of Life Sciences at the University of Sussex, where he leads research at the intersection of organic electrochemistry, bioimaging, and sustainable synthesis. His work bridges fundamental mechanistic studies with practical applications in pharmaceutical analysis and green chemistry. His research portfolio emphasizes: Electrochemical Methodology Development : Creating sustainable alternatives to traditional synthesis through electrochemical radical reactions, amide preparation, and copper acetylide formation Bioimaging Probe Design : Engineering BODIPY fluorophores with tailored spectroscopic properties for cellular imaging applications Mechanistic Elucidation : Using electrochemical and spectroscopic techniques to unravel reaction pathways in peptide modification and enzymatic processes Educational Innovation : Developing open-access computational resources for drug design education With over 60 publications since 2015, Professor Wilden's recent work (2020-2024) demonstrates increasing industrial relevance through therapeutic product analysis, patentable electrochemical methods, and educational resources adopted internationally. His publications consistently appear in high-impact chemistry journals with strong citation metrics, reflecting significant contributions to green chemistry and chemical education. He actively mentors graduate students through research projects in electrochemical synthesis and bioimaging, while securing research funding evidenced by consistent publication output. Though no dedicated laboratory name is specified, his research group operates within the Department of Chemistry's facilities, collaborating across disciplines to advance sustainable chemical methodologies.

Subrahmanyam Sappatiمشاهده پروفایل

استادیار

• QM/MM
• Nuclear Quantum Effects
• AIMD
• +۷ مورد دیگر

Subrahmanyam Sappati is an Assistant Professor at the Department of Pharmaceutical Technology and Biochemistry, Faculty of Chemistry, Gdańsk University of Technology. He earned his PhD in chemical sciences from IISER Pune in June 2019 and currently holds a prestigious Nobelium grant fellowship. Dr. Sappati's research focuses on computational approaches to understand molecular interactions at the quantum level. His primary methodologies include quantum mechanics/molecular mechanics (QM/MM) simulations, ab initio molecular dynamics (AIMD), and classical molecular dynamics (MD). His work spans multiple disciplines including nuclear quantum effects, proton transfer mechanisms, drug design, and photophysical properties of materials. Analysis of his publication record reveals a strong interdisciplinary trend, with recent work emphasizing applications in pharmaceutical development, particularly in antifungal and anticancer drug design, protein-ligand interactions, and materials science for energy applications. His research consistently combines computational modeling with experimental validation across diverse biological and chemical systems. Nobelium grant fellow Dr. Sappati actively contributes to the scientific community as a reviewer for multiple journals including ChemPhotoChem (since 2025), Bulletin of Materials Science (since 2023), and Physical Chemistry Research (since 2022). His research appears to be supported by various grants, with the Nobelium fellowship being explicitly mentioned. He is affiliated with the Computational Molecular Biophysics research group at the Faculty of Chemistry, where he leads computational studies of biomolecular systems, particularly focusing on hydrogen bonding networks, enzyme mechanisms, and drug-target interactions using advanced simulation techniques.

Ioannis P. Nezisمشاهده پروفایل

استاد

• Autophagy
• Selective Autophagy
• Cell Biology
• +۷ مورد دیگر

Professor Ioannis P. Nezis at the University of Warwick's School of Life Sciences is a leading authority in autophagy research. Using Drosophila melanogaster and mammalian cell models, his work explores selective autophagy mechanisms in aging, neurodegeneration, obesity, and infectious diseases. Current: Professor of Cell Biology (2020-) Prior: Reader (2018-2020), Associate Professor (2012-2017), Assistant Professor (2009-2012) Key affiliations: Warwick Antimicrobial Interdisciplinary Centre (WAMIC), Tissue Image Analytics (TIA) Centre His research focuses on selective autophagy receptors/adaptors , cellular aging mechanisms , and disease pathologies through lysosomal degradation pathways. Current work develops molecular markers for in vivo autophagy monitoring and investigates therapeutic strategies for autophagy-related disorders. Selected publications demonstrate autophagy's role in Golgi quality control , LIR motif interactions , and innate immune regulation . His lab employs RNAi knockdown , confocal microscopy , and bioinformatics to study autophagy's physiological significance.

Raed Khashanمشاهده پروفایل

دانشیار

• Computational Medicinal Chemistry
• In-Silico Drug Design and Discovery
• Artificial Intelligence
• +۶ مورد دیگر

Dr. Raed Khashan is an Associate Professor in the Pharmaceutical Sciences Division at Long Island University. He holds a Ph.D. in Pharmaceutical Sciences from the University of North Carolina at Chapel Hill, an M.S. in Pharmaceutical Sciences from The University of Texas at Austin, and a B.S. in Pharmacy from Jordan University of Science and Technology. As a licensed pharmacist with over ten years of community pharmacy experience, he bridges theoretical concepts with real-world applications in his teaching. His interdisciplinary research spans three core areas: Computer-Aided Drug Design using machine learning and molecular modeling Molecular Dynamics Simulation for mechanistic studies of biological processes Development of computational algorithms for cheminformatics and bioinformatics challenges This work integrates chemistry, biology, physics, and computer science to advance therapeutic discovery. Dr. Khashan's publications demonstrate consistent focus on computational method development, with recent work emphasizing AI-driven drug discovery (e.g., BMX inhibitors for cancer) and CRISPR/Cas molecular mechanisms. His articles frequently appear in journals like Molecular Informatics , Journal of Cheminformatics , and Proteins: Structure, Function, and Bioinformatics . He has received significant recognition including: AACP Teacher of the Year Award CCG Excellence Award for computational method innovation Multiple teaching nominations (Lindback, Bright Idea) Research awards from USciences and King Faisal University He actively mentors students in computational projects, with current advisees including Faranak Dinehkaboudi, Nadimbhai Vahora, and Amnah Alalmaie. As director of the Khashan Laboratory for Molecular Modeling & Simulation, he leads initiatives in CADD and algorithm development.

Ariane Nunes Alvesمشاهده پروفایل

استادیار

• Computational Biochemistry
• Protein-Ligand Binding Kinetics
• Molecular Dynamics Simulations
• +۳ مورد دیگر

Dr. Ariane Nunes Alves is a Junior Group Leader at Technische Universität Berlin's Institute of Chemistry, leading the Theoretical Structural Biology group . Her research bridges computational chemistry and biophysics, specializing in protein-ligand binding kinetics, enzyme catalysis in crowded cellular environments, and machine learning applications in drug design. Research Focus: Her lab develops methods to predict binding/unbinding pathways using molecular dynamics (e.g., tauRAMD) and AI models. Key areas include: Kinetics of protein-ligand interactions Effects of macromolecular crowding on enzymes Structure-based drug design with QSKR models Machine learning for hydrogenase pathway identification Awards & Fellowships: HITS Award for Women in Science (2020) Capes-Humboldt Research Fellowship (2019) CellNetworks Postdoctoral Program (2018) Fapesp Ph.D. Fellowship (2014) Teaching: She instructs graduate courses on applied machine learning in chemistry and computational drug design at TU Berlin. Her lab investigates substrate dissociation in hydrogenases, cellular environmental impacts on catalysis, and ML-based kinetic predictions.

• Pharmaceutical Chemistry
• Physical Chemistry
• Theoretical Chemistry
• +۵ مورد دیگر

Prof. Dr. Fethiye Aylin Sungur is an Associate Professor at Istanbul Technical University, where she serves as the Deputy Director of the Institute of Informatics. She is affiliated with the Computational Science and Engineering Division within the Institute of Informatics, contributing significantly to interdisciplinary research that bridges computational methods with pharmaceutical and biochemical applications. Current Position: Associate Professor & Deputy Director of Institute of Informatics Institution: Istanbul Technical University Department: Computational Science and Engineering Research Focus: Computational Chemistry & Drug Design Dr. Sungur earned her PhD in Chemistry from Boğaziçi University in 1997, following a Master's degree with thesis (1995) and undergraduate studies (1989-1995) in the same department. Her academic journey includes positions as Research Assistant at Boğaziçi University (1995-2004), Assistant Professor at Istanbul Technical University (2004-2012), and promotion to Associate Professor in 2012. Her research spans Pharmaceutical Chemistry , Physical Chemistry , and Theoretical Chemistry , with a strong emphasis on computational approaches. Dr. Sungur specializes in molecular modeling, enzyme mechanism studies, and computational drug design. Her work frequently applies quantum mechanical and molecular dynamics simulations to understand complex biochemical processes and develop novel therapeutic approaches. She has made significant contributions to understanding enzyme reaction mechanisms, particularly for targets relevant to disease treatment. Analysis of her recent publications reveals a consistent focus on applying computational chemistry to drug discovery and delivery challenges. Her work demonstrates expertise in molecular docking, virtual screening, and simulation techniques applied to ribosome targeting, enzyme inhibition, and controlled drug release systems. A notable trend is her increasing work on metal-organic frameworks for drug delivery applications, particularly for anti-inflammatory steroids and wound healing applications. Dr. Sungur has secured substantial research funding through multiple TÜBİTAK (Turkish Scientific and Technological Research Council) projects, including "Multiscale Mechanistic Study for Protein Arginine Deiminase 2: An Attractive Target for Breast Cancer Therapy" and "Elucidation of the Deacetylation Reaction Mechanism of O-Acetylpeptidoglucan Esterase (Ape1) Enzyme by In Silico Methods and Inhibitor Design." She has also participated in international collaborations such as "Partnership for Advanced Computing in Europe Sixth Implementation Phase (PRACE 6IP)." Multiscale Mechanistic Study for Protein Arginine Deiminase 2 Deacetylation Reaction Mechanism of O-Acetylpeptidoglucan Esterase Partnership for Advanced Computing in Europe As an advisor, Dr. Sungur has mentored numerous graduate students, supervising over 13 Master's theses and one Doctoral dissertation. Her students have pursued research in computational chemistry, molecular modeling, and drug design, reflecting her expertise and research focus. Her laboratory utilizes advanced computational resources for molecular dynamics simulations, quantum mechanical calculations, and virtual screening approaches.

Ian S. Haworthمشاهده پروفایل

دانشیار

• Computational Chemistry
• Computer-aided Molecular Design
• DNA and RNA structure
• +۴ مورد دیگر

Ian S. Haworth is an Associate Professor and Vice Chair of Pharmacology and Pharmaceutical Sciences at the USC School of Pharmacy, University of Southern California. He joined USC in 1992 after completing his PhD in Physical Organic Chemistry at the University of Liverpool and postdoctoral research at Oxford University. His laboratory develops computational algorithms to study molecular associations in nucleic acids, proteins, and drug-target interactions. Education: PhD, University of Liverpool, UK (1986-1989) Postdoc, Oxford University, UK (1989-1992) BS, Manchester Metropolitan University His research integrates computational chemistry, biology, and pharmaceutical sciences to understand molecular dynamics in biological systems. Key areas include nucleic acid structure prediction, aptamer design, transporter protein analysis, and MHC-peptide-TCR associations. This work emphasizes accurate modeling of biological interfaces for therapeutic development. Haworth's recent publications focus on computational drug design (e.g., prodrug optimization, COX-2 inhibitors), structural biology (protein-nucleic acid complexes), and educational innovation (AI in pharmacy curriculum). His work consistently bridges computational predictions with experimental validation across therapeutic areas. Research Grants: NIH/NIGMS R01GM059297: PEPT1 Structure-Function (2000-2006) NIH/NCI R29CA064299: Polyamine Antitumor Complexes (1994-2000) He leads a computational lab developing tools like ALLNOX for biomolecular analysis and has contributed to transforming pharmacy education through case-based curricula. His team collaborates extensively across disciplines to study protein-membrane interactions, drug pharmacokinetics, and structural immunology.

• GPCR Research
• Computational Drug Design
• Pharmacoinformatics
• +۳ مورد دیگر

Gáspár Pándy-Szekeres serves as an Academic Employee at the University of Copenhagen's Faculty of Health and Medical Sciences within the Department of Drug Design and Pharmacology. His research focuses on computational approaches to G protein-coupled receptors (GPCRs) and related signaling proteins, with significant contributions to bioinformatics resource development. His primary research interests include GPCR bioinformatics, molecular dynamics simulation of receptor systems, computational drug design methodologies, and specialized database construction for biological targets. He employs advanced computational techniques to analyze receptor structure-function relationships, ligand binding mechanisms, and allosteric modulation sites critical for pharmaceutical development. Recent publications demonstrate a clear trajectory toward integrating artificial intelligence (AlphaFold2) with experimental data to model physiological ligand complexes and receptor dynamics. His work emphasizes large-scale analysis of molecular dynamics trajectories to identify cryptic binding pockets and lateral access pathways in GPCRs, advancing targeted drug discovery. As a core contributor to the GPCRdb platform, he leads international collaborations focused on expanding receptor classification systems, developing structure-similarity search tools, and incorporating odorant receptor data. His research group maintains active partnerships across European institutions for advancing computational pharmacology frameworks.