Inilathala ang pangatlong aklat pambata sa seryeng Sulong Agham. Tampok ng pinakabagong aklat si Dr. Gay Jane Perez, ang Direktor Heneral ng Philippine Space Agency (PhilSA) at propesor sa Institute of Environmental Science and Meteorology (IESM) sa Kolehiyo ng Agham sa UP Diliman.

The Sulong Agham children’s book series on Filipino scientists has recently published its newest book featuring Dr. Gay Jane Perez, Director General of the Philippine Space Agency (PhilSA) and professor at the University of the Philippines – Diliman College of Science’s Institute of Environmental Science and Meteorology (UPD-CS IESM).

Ang mga lamok tulad ng Aedes aegypti at Aedes albopictus, na kilalang naglilipat ng mga sakit gaya ng dengue, Zika, at chikungunya, ay maaaring may taglay na higit pa sa mga virus na nakakaapekto sa tao. Nagtataglay din sila ng mga insect-specific virus (mga virus na para lang sa insekto) na hindi nakakahawa sa tao; ang ilan pa nga sa mga ito ay maaaring pumigil sa pagdami ng mga virus na nagdudulot ng sakit. Nagpapahiwatig ito na ang mga lamok ay maaaring magsilbing mahalagang kagamitan sa pagtukoy ng mga kilala at umuusbong na virus na maaaring makaapekto sa kalusugan ng publiko. 

Sina Irish Coleen Asin, John Michael Egana, at Dr. Ma. Anita Bautista mula sa National Institute of Molecular Biology and Biotechnology ng University of the Philippines Diliman College of Science (UPD-CS NIMBB), kasama si Dr. Richard Paul ng Institut Pasteur, Université Paris Cité, ay nangolekta ng mga lamok mula sa tatlong lugar sa Los Baños, Laguna na nagkakaiba sa topograpiya at paggamit ng lupa. Gamit ang viral metagenomics—isang pamamaraan na tumutukoy sa lahat ng virus sa isang sampol—sinuri nila ang virome (kabuuan ng mga virus) sa loob ng mga lamok. 

Natuklasan sa kanilang pananaliksik na ang mga lamok ay nagtataglay ng mga virus mula sa 12 magkakaibang taxon group. Karamihan sa mga ito ay mga insect-specific virus (ISV). Pareho ring taglay ng A. aegypti at A. albopictus ang malaking bahagi ng mga natukoy na virus. 

Nangolekta ang mga molecular biologist ng mga sampol ng lamok mula sa tatlong barangay sa Los Baños, Laguna: ang Bagong Silang, Lalakay, at Bayog. Ang Bagong Silang ang upstream (bundok) na site, na matatagpuan 305–331 metro sa itaas ng antas ng dagat (asl), at may maburol na tanawin (rolling landscape). Ang Lalakay naman ang midstream na site—na nailalarawan sa pagkakaroon ng maburol hanggang sa medyo hindi pantay na lupain. Ang Bayog, na siyang tabing-lawa na site (lakeshore site), ay may patag na lupain. 

“Batay sa mga land cover map, napanatili ng Bagong Silang ang forest cover nito sa nakalipas na apat na dekada hanggang sa petsa ng pag-aaral. Sa kaparehong panahon, kapwa sumailalim ang Lalakay at Bayog sa konbersiyon mula sa pagiging agrikultural patungo sa mga built-up area (mga may estruktura at pamayanan),” pagbabahagi nila. 

Ipinakita rito sa pag-aaral na mas maraming uri ng virus ang natagpuan sa mga lugar na nabago na ng aktibidad ng tao—tulad ng mga urbanisado o nakalbong lupa, gaya ng mga Barangay Lalakay at Bayog—kumpara sa kagubatan ng Bagong Silang. “Ang mga lamok na ito ay kadalasang matatag sa mga pagbabago sa kapaligiran (disturbance-resilient), at mas mabisang host para sa iba’t ibang uri o strain ng virus,” dagdag pa ng mga molecular biologist. Kapansin-pansin na hindi nakita ng pangkat ang mga virus ng dengue, Zika, o chikungunya sa mga sampol. Gayunpaman, natuklasan na ang mga lamok mula sa dalawang barangay ay nagtataglay ng Cell Fusing Agent Virus (CFAV). Ang CFAV ay pinaniniwalaang pumipigil sa pagdami ng mga virus ng Dengue at Zika.

“Ang potensyal na panganib ng mga umuusbong at posibleng hindi pa kilalang banta ng arbovirus ay nangangailangan ng mas pinalakas na mga programa sa pagsubaybay (surveillance) at advanced na pananaliksik sa mga arboviral disease—mga sakit na naililipat ng mga insekto tulad ng lamok,” ayon sa kanila. Binigyang-diin din nila na ang mga programa sa pagsubaybay sa arbovirus ay mahalaga sa kalusugan ng publiko, dahil binabantayan ang aktibidad ng mga lokal (endemic) at umuusbong na virus sa real-time upang makatulong sa pamamahala ng mga outbreak. Ang ganitong pagsubaybay ay maaaring mapahusay sa pamamagitan ng mga teknik ng next-generation sequencing, kabilang ang virome sequencing.

Nabanggit din ng mga molecular biologist na ang mga lamok ay maaaring magsilbing mahalagang biyolohikal na target para sa mga programa sa pagsubaybay sa mga sakit na zoonotic at arboviral. “Ang mga lamok ay kumikilos na parang mga biyolohikal na heringgilya (biological syringes) na sumisipsip ng dugo sa iba’t ibang uri ng host,” itinala ng pangkat. “Dahil dito, maaari silang magbigay ng mahahalagang kaalaman ukol sa pagkakaiba-iba ng virus sa iba’t ibang espasyo, panahon, at uri ng hayop (species).”

Ang kanilang pag-aaral na pinamagatang “Virome sequencing and analysis of Aedes aegypti and Aedes albopictus from ecologically different sites in the Philippines” ay nailathala sa Parasites & Vectors. Ang internasyonal na journal na ito ay nakatuon sa lahat ng aspeto ng biyolohiya ng mga parasitiko, mga sakit na parasitiko, mga intermediate host, vectors, at mga pathogen na dala ng vector. Ang kanilang gawa ay sinuportahan ng Department of Science and Technology–Philippine Council for Health Research and Development (DOST-PCHRD) at ng UPD Office of the Vice Chancellor for Research and Development. 

Sanggunian: 
Asin, I. C., Egana, J. M., Paul, R. E., & Bautista, M. A. (2025). Virome sequencing and analysis of Aedes aegypti and Aedes albopictus from ecologically different sites in the Philippines. Parasites & Vectors, 18(1). https://doi.org/10.1186/s13071-025-07073-7

Mosquitoes such as Aedes aegypti and Aedes albopictus, which are known to transmit diseases like dengue, Zika, and chikungunya, may carry more than just viruses that affect humans. They also host insect-specific viruses that do not infect people, some of which may even inhibit the multiplication of disease-causing viruses. This implies that mosquitoes can serve as valuable tools for detecting both known and emerging viruses that may impact public health.

Irish Coleen Asin, John Michael Egana, and Dr. Ma. Anita Bautista of the University of the Philippines – Diliman College of Science’s National Institute of Molecular Biology and Biotechnology (UPD-CS NIMBB), together with Dr. Richard Paul of Institut Pasteur, Université Paris Cité, collected mosquitoes from three areas in Los Baños, Laguna that differ in topography and land use. Using viral metagenomics—a method that identifies all viruses in a sample—they analyzed the virome inside the mosquitoes.

Their research revealed that the mosquitoes carried viruses from 12 different taxon groups. Most of these were insect-specific viruses (ISVs), which infect mosquitoes but not humans. Both A. aegypti and A. albopictus also shared the majority of the identified viruses.

The molecular biologists collected mosquito samples from three barangays in Los Baños, Laguna: Bagong Silang, Lalakay, and Bayog. Bagong Silang is the upstream (mountain) site, located 305–331 meters above sea level (asl), with a rolling landscape. Lalakay is the midstream site—characterized by rolling to slightly uneven terrain. Bayog, the lakeshore site, has a flat landscape.

“Based on the land cover maps, Bagong Silang retained its forest cover in the last 4 decades as of the study date. At the same time, both Lalakay and Bayog underwent conversion from agricultural to built-up areas during that period,” they shared.

The study also showed that more types of viruses were found in areas altered by human activity—such as urban or cleared land, like Barangays Lalakay and Bayog—compared to the forested area of Bagong Silang. “These mosquitoes are usually disturbance-resilient and are more competent hosts for several viral isolates or strains,” the molecular biologists added. Notably, the team did not detect dengue, Zika, or chikungunya viruses in the samples. Interestingly, mosquitoes from two barangays were found to harbor the Cell Fusing Agent Virus (CFAV). CFAV has been thought to inhibit the proliferation of Dengue and Zika viruses.

“The potential risk of emerging and possibly unknown arboviral threats calls for strengthened surveillance programs and advanced research on arboviral diseases—those transmitted by insects like mosquitoes,” they said, emphasizing that arbovirus surveillance programs are vital to public health, as they monitor the activity of both endemic and emerging viruses in real time to help manage outbreaks. Such monitoring can be enhanced through next-generation sequencing techniques, including virome sequencing.

The molecular biologists also noted that mosquitoes may serve as important biological targets for zoonotic and arboviral disease surveillance programs. “Mosquitoes act like biological syringes, feeding on multiple kinds of hosts,” the team pointed out. “Because of this, they can provide valuable insights into viral diversity across space, time, and species.”

Their study, “Virome sequencing and analysis of Aedes aegypti and Aedes albopictus from ecologically different sites in the Philippines,” was published in Parasites & Vectors. This international journal focuses on all aspects of the biology of parasites, parasitic diseases, intermediate hosts, vectors, and vector-borne pathogens. Their work was supported by the Department of Science and Technology—Philippine Council for Health Research and Development (DOST-PCHRD) and the UPD Office of the Vice Chancellor for Research and Development.

References:

Asin, I. C., Egana, J. M., Paul, R. E., & Bautista, M. A. (2025). Virome sequencing and analysis of Aedes aegypti and Aedes albopictus from ecologically different sites in the Philippines. Parasites & Vectors, 18(1). https://doi.org/10.1186/s13071-025-07073-7

Binuo ni Dr. Bryan Hernandez ng University of the Philippines – Diliman College of Science Institute of Mathematics (UPD-CS IM), kasama sina Patrick Vincent Lubenia at Dr. Eduardo Mendoza ng Center for Natural Science and Environmental Research, De La Salle University, ang Common Species Embedded Networks (CSEN) analysis.

Pinaghahambing ng CSEN analysis ang dalawang reaction networks na pareho o magkatulad ang sistema sa pamamagitan ng pagtuon sa kanilang mga karaniwang species, tulad ng mga protein o kemikal, upang matukoy ang mga pagkakatulad at pagkakaiba.

“Gumagana ang method sa pamamagitan ng unang paghihiwalay sa mga network na ‘naka-embed’ sa loob ng mga modelo na kinasasangkutan lamang ng mga karaniwang species. Para sa mga reaksyon na hindi magkapareho, sinusuri ng method ang mga ‘transformation’—mga mathematical link na maaaring magpaliwanag kung paano maaaring magdulot ng equivalence ang isang set ng reaksyon sa pagitan ng mga system na may underlying embedded networks,” paliwanag ni Dr. Hernandez.

Inihambing ng kanilang grupo ang mga kasalukuyang reaction network na nauugnay sa mga Wnt signaling model na kanilang natukoy, kasama ang mga iyon nina Lee, Schmitz, MacLean, at Feinberg. Sa pamamagitan ng CSEN analysis, nalaman ng mga mathematician na ang ilang umiiral na mga modelo ay lubos na magkatulad dahil ang kanilang mga embedded network ay konektado sa isa’t isa sa pamamagitan ng mga partikular na transformation. Sa kabilang banda, maaari ring mabunyag ng analysis kung walang maihahambing na relasyon ang umiiral sa mga modelo dahil sa kawalan ng naturang transformation.

Ibinahagi ni Dr. Hernandez ang inspirasyon ng grupo sa likod ng paglikha ng CSEN analysis. “Sa larangan ng systems biology, madalas na nagmumungkahi ang iba’t ibang mananaliksik ng iba’t ibang mga reaction network upang ilarawan ang iisang biological process. Sa kasaysayan, mahirap ding paghambingin ang mga modelong ito dahil madalas silang ituring bilang ganap na magkahiwalay na mga entity, na gumagamit ng iba’t ibang hanay ng mga variable at reaction.”

Tinutugunan ng CSEN analysis ang kahirapang ito sa pamamagitan ng pagbibigay-diin sa dalawang pangunahing haligi: network embedding, kung saan sinasala ang mga complex network para ituon lang sa mga species na makikita sa pagitan ng mga model; at mga structural comparison, kung saan sinusuri ang mga embedded network upang matukoy kung ang isang model ay isang mas kumplikadong bersyon ng isa pa o kung ang mga ito ay “halos katumbas” sa pamamagitan ng mga mathematical transformation.

“Madalas napaghihiwalay ang mga modelo ng mga traditional approach batay sa mga specific property, tulad ng kung mayroon silang isang long-term state (mono-stationarity) o multiple long term states (multi-stationarity). Iba ang CSEN dahil tinitingnan nito ang underlying structure at dynamic equivalence,” dagdag ni Dr. Hernandez.

Naging insightful ang CSEN analysis sa Wnt signaling, na nagpapakitang ang ilang models—na noong una ay itinuturing na naiiba dahil sa kanilang mga stability property—ay talagang halos magkapareho sa istruktura.

Ayon kay Dr. Hernandez, isang pangkalahatang mathematical tool ang CSEN analysis na maaaring ilapat sa mga modelo para sa mga system maliban pa sa Wnt signaling. “Habang ipinakita namin ang paggamit nito sa Wnt signaling, maaari itong ilapat sa anumang system na kinakatawan ng mga reaction network. Kabilang dito ang iba pang biological pathway, gaya ng insulin signaling o metabolism, pati na rin ang mga potential non-biological network gaya ng mga chemical engineering process o ecological model.”

Maaaring maging mahalaga ang CSEN analysis sa pagpino ng mga model sa biological at chemical systems sa pamamagitan ng pagtukoy kung aling mga bahagi ng isang modelo—o kung aling mga modelo—ang natatangi at alin ang redundant. Maaaring bigyan ng pansin ng analysis na ito ang mga robust target: kung maraming mga modelo, sa kabila ng kanilang mga pagkakaiba, ay nagkakaisa sa iisang interaction na nagdudulot ng isang uri ng sakit, ang interaction na ito ay nagiging isang mas maaasahan at robust na therapeutic target.

Ang kanilang pagsasaliksik, “Embedding-based comparison of reaction networks of Wnt signaling,” ay kasama sa MATCH Communications in Mathematical and in Computer Chemistry, isang open-access na journal na naglalathala ng mga orihinal na pananaliksik pati na rin ang mga review ukol sa chemically important mathematical results at non-routine na paggamit ng mga mathematical technique sa mga chemical problem.

References:

Hernandez, B. S., Lubenia, P. V., & Mendoza, E. R. (2024). Embedding-based comparison of reaction networks of Wnt signaling. MATCH Communications in Mathematical and in Computer Chemistry, 93(1), 235-245. https://doi.org/10.46793/match.93-1.223h

Dr. Bryan Hernandez of the University of the Philippines – Diliman College of Science’s Institute of Mathematics (UPD-CS IM), along with Patrick Vincent Lubenia and Dr. Eduardo Mendoza of the Center for Natural Science and Environmental Research, De La Salle University, developed the Common Species Embedded Networks (CSEN) analysis.

The CSEN analysis compares two reaction networks of the same or similar systems by focusing on their common species, such as proteins or chemicals, to identify similarities and differences.

“The method works by first isolating the networks ‘embedded’ within the models that involve only the common species. For the reactions that are not identical, the method checks for ‘transformations’—mathematical links that can explain how one reaction set might induce equivalence between the systems with the underlying embedded networks,” Dr. Hernandez explained.

Their group compared existing reaction networks associated with Wnt signaling models they had identified, including those by Lee, Schmitz, MacLean, and Feinberg. Through the CSEN analysis, the mathematicians found that some existing models are strongly similar because their embedded networks are connected through specific transformations. Conversely, the analysis can also reveal when no comparable relationship exists due to the absence of such transformations.

Dr. Hernandez shared the team’s inspiration behind creating the CSEN analysis. “In the field of systems biology, different researchers often propose different reaction networks to describe the same biological process. Historically, it has also been difficult to compare these models because they are often treated as entirely separate entities, utilizing different sets of variables and reactions.”

The CSEN analysis addresses this difficulty by emphasizing two key pillars: network embedding, which narrows complex networks to focus only on the species shared between models; and structural comparisons, in which the embedded networks are analyzed to determine whether one model is a more complex version of another or if they are “proximately equivalent” through mathematical transformations.

“Traditional approaches often discriminate between models based on specific properties, such as whether they have one long-term state (mono-stationarity) or the capacity for multiple long-term states (multi-stationarity). CSEN is different because it looks at the underlying structure and dynamical equivalence,” Dr. Hernandez added.

The CSEN analysis was particularly insightful for Wnt signaling, revealing that certain models—previously thought to differ fundamentally due to their stability properties—are actually structurally very similar.

According to Dr. Hernandez, the CSEN analysis is a general mathematical tool that can be applied to models in systems beyond Wnt signaling. “While we demonstrated its use with Wnt signaling, it can be applied to any system represented by reaction networks. This includes other biological pathways, such as insulin signaling or metabolism, as well as potentially non-biological networks such as chemical engineering processes or ecological models.”

The CSEN analysis can be vital in refining models in biological and chemical systems by identifying which parts of a model—or which models—are unique and which are redundant. This method can highlight robust targets: if many models, despite their differences, agree that a specific interaction drives a disease, that interaction becomes a more reliable and robust therapeutic target.

Their research, “Embedding-based comparison of reaction networks of Wnt signaling,” is included in MATCH Communications in Mathematical and in Computer Chemistry, an open-access journal that publishes papers of original research as well as reviews on chemically important mathematical results and non-routine applications of mathematical techniques to chemical problems.

References:

Hernandez, B. S., Lubenia, P. V., & Mendoza, E. R. (2024). Embedding-based comparison of reaction networks of Wnt signaling. MATCH Communications in Mathematical and in Computer Chemistry, 93(1), 235-245. https://doi.org/10.46793/match.93-1.223h

Habang patuloy ang paghina o pagkawalang bisa ng mga tradisyunal na antibiotic sanhi ng antimicrobial resistance (AMR), ay lalong nagiging mahalaga ang paghahanap ng mga bagong gamot. Isa sa mga pinakapromising na solusyon ay ang antimicrobial peptides (AMPs), na isang klase ng mga compound na kayang pumatay ng bacteria. Upang mapabilis ang proseso ng pagtuklas ng AMPs, bumuo sila Remmer Salas, Dr. Portia Mahal Sabido, at Dr. Ricky Nellas ng University of the Philippines Diliman – College of Science (UPD-CS) ng isang AI tool.

Ang ISCAPE (Interpretable Support Vector Classifier of Antibacterial Activity of Peptides against Escherichia coli) ay isang AI-powered tool na tumutulong na mag-predict kung ang isang peptide ay may kakayahang pumatay o pumigil sa pagdami ng E. coli. Kailangan lamang ng system na ito ng Simplified Molecular-Input Line-Entry System (SMILES) string bilang input, bagay na magpapadali sa mga researcher na suriin ang mga kandidatong molecule.

“Ayon sa tradisyunal na paraan, ang pagtuklas ng antibacterial peptides ay nangangailangan ng paggawa o pag-synthesize ng maraming kandidato at pagsubok sa mga ito isa-isa. Matagal ang prosesong ito,” sabi ni Salas. “Gumamit kami ng AI upang matuto mula sa umiiral na datos at matukoy ang mga pattern na nagkakaiba sa mga aktibo at hindi aktibong peptide.”

Bukod-tangi din sa mga AI tools ang abilidad ng ISCAPE na tukuyin kung aling mga molecular feature ang nagpapabisa sa isang peptide. Ayon kay Salas, nakatutulong ito upang makatipid ng oras at resources ang mga researcher. Nababawasan nito ang trial-and-error experiments at nagbibigay-daan upang mas mahusay na makapagdisenyo ng peptide.

“Tumutulong ang ISCAPE sa laban sa antimicrobial resistance sa pamamagitan ng pagpapabilis ng early-stage screening gamit ang data-driven peptide design,” dagdag pa ni Salas. “Hindi nito pinapalitan ang laboratory experiments, ngunit ginagawa nitong mas episyente ang discovery process at tinutulungan ang mga researcher na magpokus sa mga pinakapromising na kandidato.”

Maaaring ding magamit ang AI-powered model  laban sa ibang bacteria bukod sa E. coli. Gayunpaman, kailangan muna itong sanayin muli gamit ang mataas na kalidad na datasets na partikular sa bacterial strains na nais pag-aralan. Maaari ring gamitin ang ISCAPE approach upang hulaan o mag-predict ng activity ng iba pang bioactive peptides.

“Ang paggamit ng ISCAPE para sa ibang biological targets ay nangangailangan ng maayos na curated datasets na may experimentally validated activity,” dagdag ni Salas. “Pagkatapos nito, kailangang sanayin muli ang model gamit ang molecular features na natukoy naming pinakamainam para sa peptides.”

Umaasa ang grupo na makatutulong ang ISCAPE upang mas mahusay at mas mabilis na makapagdisenyo ang mga researcher ng antibacterial peptides at makatulong sa pandaigdigang laban kontra AMR.

Bukas sa publiko ang ISCAPE para magamit ng ibang siyentista. Maaaring ma-access ang web server nito sa Hugging Face Spaces. Available din sa GitHub ang training data at code para sa large-scale prediction.

Ang research paper na pinamagatang “Interpretable support vector classifier for reliable prediction of antibacterial activity of modified peptides against Escherichia coli” ay nailathala sa Journal of Molecular Graphics and Modelling. Ang internasyonal na publikasyong ito ay naglalaman ng mga papel tungkol sa paggamit ng computer sa teoretikal na pag-aaral ng molecular structure, function, interaction, at design. Saklaw nito ang lahat ng aspeto ng molecular modeling at computational chemistry.

References:

Salas, R. L., Sabido, P. M., & Nellas, R. B. (2026). Interpretable support vector classifier for reliable prediction of antibacterial activity of modified peptides against Escherichia coli. Journal of Molecular Graphics and Modelling, 142, 109188. https://doi.org/10.1016/j.jmgm.2025.109188

As antimicrobial resistance (AMR) continues to make traditional antibiotics less effective worldwide, the search for new antibacterial treatments has become increasingly urgent. One promising solution is antimicrobial peptides (AMPs), small molecules that can kill bacteria. To help accelerate their discovery, researchers at the University of the Philippines Diliman – College of Science (UPD-CS) have developed an AI tool designed to accelerate the discovery of new antibacterial peptides.

Remmer Salas, Dr. Portia Mahal Sabido, and Dr. Ricky Nellas of the UPD-CS Institute of Chemistry (IC) developed ISCAPE (Interpretable Support Vector Classifier of Antibacterial Activity of Peptides against Escherichia coli). It is an AI-powered tool that helps experimentalists predict whether a peptide can kill or inhibit the growth of E. coli. The system requires only a Simplified Molecular-Input Line-Entry System (SMILES) string as input, making it simple for researchers to evaluate candidate molecules.

“Traditionally, discovering antibacterial peptides means synthesizing many candidates and testing them one by one. This process is time-consuming,” said Salas. “We used AI to learn from existing data and identify patterns that distinguish active peptides from inactive ones.”

Unlike many AI tools, ISCAPE also shows which molecular features make a peptide effective. He noted that this helps researchers save time and resources. It reduces trial-and-error experiments and allows them to design better peptides more efficiently.

“ISCAPE helps address antimicrobial resistance by accelerating early-stage screening through data-driven peptide design,” Salas further explained. “It doesn’t replace laboratory experiments, but it makes discovery more efficient and helps researchers focus on the most promising candidates.”

The AI-powered model can be adapted to predict activity against bacteria other than E. coli. However, it would need to be retrained using high-quality datasets specific to the bacterial strains of interest. The ISCAPE approach could also be applied to predict the activity of other bioactive peptides. 

“Applying ISCAPE to other biological targets requires well-curated datasets with experimentally validated activity,” Salas added. “The model must then be retrained using the molecular features we identified as optimal for peptides.”

The team hopes the tool will help researchers design better antibacterial peptides more efficiently and contribute to the global fight against AMR.

ISCAPE is publicly available for other scientists. The web server can be accessed through Hugging Face Spaces. The training data and code for large-scale prediction are available on GitHub.

The chemists’ research paper, titled “Interpretable support vector classifier for reliable prediction of antibacterial activity of modified peptides against Escherichia coli,” was included in the Journal of Molecular Graphics and Modelling. This international publication features papers on the use of computers in theoretical investigations of molecular structure, function, interaction, and design. It covers all aspects of molecular modeling and computational chemistry.

References:

Salas, R. L., Sabido, P. M., & Nellas, R. B. (2026). Interpretable support vector classifier for reliable prediction of antibacterial activity of modified peptides against Escherichia coli. Journal of Molecular Graphics and Modelling, 142, 109188. https://doi.org/10.1016/j.jmgm.2025.109188